Sulfur Dioxide (2010) Nonattainment Area State/Area/County Report
ABRAMS ENVIRONMENTAL LAW CLINIC OF THE UNIVERSITY OF CHICAGO LAW SCHOOL
October 11, 2019
Via E-Filing Only Ms. Lisa Felice Michigan Public Service Commission 7109 W. Saginaw Hwy. P. O. Box 30221 Lansing, MI 48917 RE: MPSC Case No. U-20471
Dear Ms. Felice:
Please find enclosed Official Exhibits of Soulardarity SOU 1 – SOU 27 and accompanying proof of service. Please do not hesitate to contact my office with any questions or comments.
Sincerely,
Mark N. Templeton, pro hac vice 6020 S. University Avenue Chicago, IL 60637 Phone: (773) 702-9611 Email: [email protected] xc: Parties to Case No. U-20471
U-20471 Official Exhibits of Soulardarity Exhibit SOU-1 Page 1 of 4
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Sulfur Dioxide (2010) Nonattainment Area State/Area/County Report
Data is current as of July 31, 2019
ARIZONA (Region IX) Hayden, AZ (Nonattainment) Gila County (P) Pinal County (P) Miami, AZ (Nonattainment) Gila County (P) FLORIDA (Region IV) Hillsborough County, FL (Nonattainment) Hillsborough County (P) Hillsborough-Polk County, FL (Nonattainment) Hillsborough County (P) Polk County (P) GUAM (Region IX) Piti-Cabras, GU (Nonattainment) Guam (P) ILLINOIS (Region V) Alton Township, IL (Nonattainment) Madison County (P) Lemont, IL (Nonattainment) Cook County (P) Lemont Township Will County (P) DuPage Township and Lockport Township
Pekin, IL (Nonattainment) Peoria County (P) Hollis Township Tazewell County (P) Cincinnati Township and Pekin Township Williamson County, IL (Nonattainment) Williamson County INDIANA (Region V) Huntington, IN (Nonattainment) U-20471 Official Exhibits of Soulardarity Exhibit SOU-1 Page 2 of 4 Huntington County (P) Huntington Township Indianapolis, IN (Nonattainment) Marion County (P) Wayne Township, Center Township, Perry Township Morgan County, IN (Nonattainment) Morgan County (P) Clay Township, Washington Township Southwest Indiana, IN (Nonattainment) Daviess County (P) Veale Township Pike County (P) Washington Township IOWA (Region VII) Muscatine, IA (Nonattainment) Muscatine County (P) KENTUCKY (Region IV) Jefferson County, KY (Nonattainment) Jefferson County (P) LOUISIANA (Region VI) Evangeline Parish (Partial), LA (Nonattainment) Evangeline Parish (P) St. Bernard Parish, LA (Nonattainment) St. Bernard Parish MARYLAND (Region III) Anne Arundel County and Baltimore County, MD (Nonattainment) Anne Arundel County (P) Baltimore County (P) MICHIGAN (Region V) Detroit, MI (Nonattainment) Wayne County (P) St. Clair, MI (Nonattainment) St. Clair County (P)
MISSOURI (Region VII) Jackson County, MO (Nonattainment) Jackson County (P)
Jefferson County, MO (Nonattainment) Jefferson County (P) NEW HAMPSHIRE (Region I) Central New Hampshire, NH (Nonattainment) Hillsborough County (P) Goffstown Town Merrimack County (P) U-20471 Official Exhibits of Soulardarity Exhibit SOU-1 Page 3 of 4 Rockingham County (P) Candia Town, Deerfield Town, Northwood Town OHIO (Region V) Muskingum River, OH (Nonattainment) Morgan County (P) Center Township Washington County (P) Waterford Township Steubenville, OH-WV (Nonattainment) Jefferson County (P) PENNSYLVANIA (Region III) Allegheny, PA (Nonattainment) Allegheny County (P) Beaver, PA (Nonattainment) Beaver County (P) Indiana, PA (Nonattainment) Armstrong County (P) Indiana County Warren, PA (Nonattainment) Warren County (P) PUERTO RICO (Region II) Guayama-Salinas, PR (Nonattainment) Salinas Municipio (P) Aguirre Ward., Lapa Ward. San Juan, PR (Nonattainment) Bayamon Municipio (P) Juan Sanchez Ward. Catano Municipio Guaynabo Municipio (P) Pueblo Viejo Ward. San Juan Municipio (P) San Juan Antiguo Ward., Santurce Ward., Hato Rey Norte Ward., Gobernador Pinero Ward. Toa Baja Municipio (P) Palo Seco Ward., Sabana Seca Ward.
TENNESSEE (Region IV) Sullivan County, TN (Nonattainment) Sullivan County (P)
TEXAS (Region VI) Freestone and Anderson Counties, TX (Nonattainment) Anderson County (P) Freestone County (P) Rusk and Panola Counties, TX (Nonattainment) Panola County (P) Rusk County (P) U-20471 Official Exhibits of Soulardarity Exhibit SOU-1 Page 4 of 4 Titus County, TX (Nonattainment) Titus County (P) WEST VIRGINIA (Region III) Marshall, WV (Nonattainment) Marshall County (P) Steubenville, OH-WV (Nonattainment) Brooke County (P) WISCONSIN (Region V) Rhinelander, WI (Nonattainment) Oneida County (P)
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2019-07-31 U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 1 of 10
Staff Report U-20169 August 10, 2018
Sally A. Talberg, Chairman Norman J. Saari, Commissioner Rachael A. Eubanks, Commissioner
U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 2 of 10
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Contents Executive Summary ...... i
Introduction...... 1
Incident Reporting – R 460.3804 ...... 1
DTE Report Evaluation ...... 2
Staff Investigation ...... 3
Distribution System Investigation ...... 4
Wire Down Procedure Investigation ...... 6
Inspection Program Investigation ...... 6
Potential Violations ...... 7
Staff Findings and Recommendations ...... 10
Company Recommendations ...... 11
Commission Recommendations ...... 12
Appendix A – Staff Questions and DTE Electric Responses ...... 15 U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 4 of 10
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Executive Summary On May 17, 2018, the Michigan Public Service Commission (Commission) issued an order in MPSC Docket No. U-20169 after a severe wind storm swept through southeastern lower-Michigan and the thumb area beginning May 4, 2018. High wind speeds, with gusts approaching 70 mph, resulted in several hundred downed wires, thousands of customer outages, and a confirmed electrocution fatality due to a downed wire on May 7, 2018. The Commission order was issued based on the concern that areas of DTE’s electric distribution system are not able to provide safe and reliable service; therefore, the order was issued with a focus on safety to determine if system maintenance is contributing to safety hazards. DTE and, later, the Michigan Public Service Commission Staff (Staff) were directed to file reports. Staff was specifically directed to:
“… file an evaluation of DTE Electric’s report. The Staff shall carefully examine the factual basis for assertions in the report, and the strength of the analysis and information provided by the company. The Staff’s report shall include an analysis and recommendations, where necessary, regarding: (1) potential violations; (2) improvements to DTE Electric’s method of transmitting and supplying electricity; (3) the strength and effectiveness of DTE Electric’s procedures addressing downed wires (both regulatory and internal); and (4) the degree of adherence to the program of inspection required under the Commission’s rules.”
Overall, Staff believes that the DTE Electric report provided a fair review of what the Commission asked the Company to address. However, Staff does believe that there were areas within the Company’s report that lacked detail and thus failed to address what the Commission order requested. Staff was not satisfied with how the Company addressed the Commission’s concern “that parts of DTE Electric’s distribution system are exhibiting an inability to routinely provide the level of safe and reliable service that is required by law” and the concern “with the operation of the 4.8 kV system and the question of whether it presents unique hazards.” Staff issued a total of 68 questions and initiated meetings from July to early August to address areas of concern raised in the Commission’s order that Staff believed the Company’s report failed to address.
Staff’s investigation included a review of the Company’s distribution system, wire down procedures, and inspection program and identified potential violations. After reviewing the vegetation density results, the number of wire downs and outages, and the operations and maintenance (O&M) tree-trim spend amounts on the 4.8 kV system in the City of Detroit as part of the investigation, Staff has determined that there are areas within DTE Electric’s distribution system that have experienced variable levels of tree-trim maintenance on an overhead circuit basis. Staff also finds that prior to 2015 “equipment” was used as the default cause for “unknown” outage causes to the customer’s secondary service lines which leads Staff to believe that some of the outages caused by equipment in the 2013-2015 timeframe may not have been related to equipment. Staff is concerned with the 4.8 kV system as a whole given the fact that it is an ungrounded system and although the system is equipped with some ground alarm capabilities,
i U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 6 of 10 single-phased downed wires may not produce fault currents large enough to engage safety devices and remain energized. Staff believes that the system also presents unique hazards in the City of Detroit due to the amount of rear-lot construction, which significantly impacts accessibility to the entire system and the ability to perform maintenance, emergency response, and remediation efforts.
As a result of its investigation, Staff makes nine recommendations to the Company and recommendations to the Commission.
ii U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 7 of 10 Introduction On May 17, 2018, the Michigan Public Service Commission (Commission) issued an order in MPSC Docket No. U-20169 after a severe wind storm swept through southeastern lower-Michigan and the thumb area beginning May 4, 2018. High wind speeds, with gusts approaching 70 mph, resulted in several hundred downed wires, thousands of customer outages, and a confirmed electrocution fatality due to a downed wire on May 7, 2018. The Commission order was issued based on the concern that areas of DTE’s electric distribution system are not able to provide safe and reliable service; therefore, the order was issued with a focus on safety to determine if system maintenance is contributing to safety hazards. DTE and, later, the Michigan Public Service Commission Staff (Staff) were directed to file reports. Staff was specifically directed to:
“… file an evaluation of DTE Electric’s report. The Staff shall carefully examine the factual basis for assertions in the report, and the strength of the analysis and information provided by the company. The Staff’s report shall include an analysis and recommendations, where necessary, regarding: (1) potential violations; (2) improvements to DTE Electric’s method of transmitting and supplying electricity; (3) the strength and effectiveness of DTE Electric’s procedures addressing downed wires (both regulatory and internal); and (4) the degree of adherence to the program of inspection required under the Commission’s rules.”
Incident Reporting – R 460.38041 Staff performed a five-year review and analysis of incidents2 reported by DTE Electric in accordance with Michigan Administrative Rule 460.3804 from June 30, 2013 through June 30, 2018. The review, summarized in Figure 1 below, reflects a total of 20 reported incidents associated with DTE Electric’s facilities within three distribution categories: 1) the 4.8 kV system in the City of Detroit, 2) the 4.8 kV system outside of the City of Detroit, and 3) the rest of the distribution system which is mostly comprised of the 8.3 kV and 13.2 kV systems3. Figure 1 shows that the 4.8 kV system in the City of Detroit had eight reported incidents versus six in each of the two remaining categories. Additionally, the data shows that over half of the total incidents reported on the 4.8 kV system were due to downed wires. Of the total downed wire incidents,
1 Administrative Rule 460.3804 entitled “Accidents; notice to commission” states that “[e]ach utility shall promptly notify the commission of fatalities and serious injuries that are substantially related to the facilities or operations of the facilities.” 2 The locations and health status associated with the incidents was determined based on the information that was initially reported to Staff. Subsequent updates related to location or health status may not be reflected in the analysis. 3 Staff chose to display the data under these three categories to not only show how the 4.8 kV system compares to the rest of the system, but to also compare areas within the 4.8 kV system.
1
U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 8 of 10 over 87% were related to storm events. The review also included an analysis of the percentage of incidents which resulted in fatal injury. For the 4.8 kV system in the City of Detroit, 100% of incidents resulted in fatal injury. For the 4.8 kV system outside the City of Detroit, approximately 83% of incidents resulted in fatal injury, and approximately 33% of incidents resulted in fatal injury for the remainder of the system.
Figure 1: DTE Incidents Reported Under R 460.3804 (June 30, 2013 - June 30, 2018)
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8
7
6
5
4
3
2
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0 4.8 kV Detroit 4.8 kV Non-Detroit Remainder of System Incidents Related to Wire Downs Incidents Non-Related to Wire Downs
DTE Report Evaluation The Commission order directed DTE to file a report in MPSC Docket No. U-20169. The Commission’s directive was made with a focus on safety to inform the Commission and address concerns “that parts of DTE Electric’s distribution system are exhibiting an inability to routinely provide the level of safe and reliable service that is required by law” and “the operation of the 4.8 kV system and the question of whether it presents unique hazards” as provided below:
“The report shall detail the performance of DTE Electric’s system during and after the May 4 windstorm event, including why outages occurred, how the utility responded, and whether changes should be implemented to reduce the potential for massive power outages, injury, or death. The report shall also provide a detailed examination of the utility’s ongoing efforts to ensure compliance with the regulations listed above. The
2
U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 9 of 10 report shall also include a description of DTE Electric’s internal safety protocols, and an analysis of compliance with those protocols. The Commission is particularly interested in whether DTE Electric is in compliance with these rules and protocols on a daily basis, and whether the utility experiences a comparable degree of compliance across all geographic areas of its distribution system.”
Overall, Staff believes that the DTE Electric report provided a fair review of what the Commission asked the Company to address. DTE provided an overview of the May 4th wind storm’s intensity showing areas of the lower-peninsula that saw the highest impacts from the storm. The Company also provided an adequate overview of the impacts the May 4th storm had on its distribution system, providing the number of wire downs, customer outages, broken poles, and amount of wire replaced. Along with the storm analysis, the Company provided its response to the storm by explaining the staging and preparation to support restoration efforts, providing details on the specific numbers of restoration resources, mutual assistance contact timing, and restoration plan in order to meet Commission Rule requirements. The Company’s internal protocols were summarized and demonstrated that the Company does have internal procedures to protect the public in a wire down event designed to reduce potential hazards that may endanger life or property. The Company also provided an overview of compliance with the regulations outlined by individually addressing each of the Commission Rules specified in the Commission order. Finally, Staff appreciated the fact that the Company acknowledges that there are areas for improvement by outlining three areas in detail; prevention of downed wires through maintenance and upgrades, further education and communication regarding downed wires, and responsiveness to reported downed wires during major storms.
However, Staff does believe that there were areas within the Company’s report that lacked detail and thus failed to address what the Commission order requested. Staff was not satisfied with how the Company addressed the Commission’s concern “that parts of DTE Electric’s distribution system are exhibiting an inability to routinely provide the level of safe and reliable service that is required by law” and the concern “with the operation of the 4.8 kV system and the question of whether it presents unique hazards.” The areas Staff believed to lack detail and analysis are:
• Analysis of why the large number of customer outages occurred, aside from the fact that the May 4th wind storm appeared to have been concentrated on DTE Electric’s service territory. • Analysis of compliance with internal safety protocols. • Analysis of compliance across all geographic service distribution areas, as they relate to preventative maintenance programs.
Staff Investigation Staff sought more information from the Company in its investigation through meetings and multiple questions and requests for clarification to further its analysis after DTE Electric’s report
3
U-20471 Official Exhibits of Soulardarity Exhibit SOU-2 Page 10 of 10
Appendix A Staff Questions and DTE Electric Responses Page 1 of 73
DTE Electric Company Auditor: T. Becker Case No. U-20169 Request No:TJB-1.1 Page: 1 of 1
Request:
1. Exhibit 3.4 on page 27 of DTE’s five-year distribution plan outlines that DTEE Distribution has a total of 28,459 overhead circuit miles. Please confirm the total overhead miles in each category.
a. 4.8 kV Detroit b. 4.8 kV non-Detroit c. Rest of distribution service territory (8.3 kV and 13.2 kV)
Response:
The primary overhead miles for each category is provided in the table below.
Category Primary Overhead Miles 4.8 Detroit 2,412 4.8 non-Detroit 14,372 8.3 & 13.2 11,675 Total 28,459 U-20471 Official Exhibits of Soulardarity Exhibit SOU-3 Page 1 of 4
MPSC Case No. U-18352 Attachment MECDE-1.2 2016 Respondent: T. L. Schroeder Page: 1 of 32
Renewables Program Focus Groups
Report (9.8.2016) U-20471 Official Exhibits of Soulardarity Exhibit SOU-3 Page 2 of 4
MPSC Case No. U-18352 Attachment MECDE-1.2 2016 Respondent: T. L. Schroeder Page: 4 of 32
Qualitative – Methodology and Sample
This Phase I study consisted of six, two‐hour focus groups among 48 DTE Energy customers, with four groups in Troy on July 26‐27th (servicing Detroit and northern suburbs) and two groups in Ann Arbor on August 3rd (servicing Ann Arbor). The groups included electric‐only and combo residential customers, small business customers, and GreenCurrents customers. Respondents were recruited to meet the following specifications: Could not work for a utility, market research, or property management company Must be primary or shared decision maker regarding utility costs and usage Must be Electric Only or Combo Customers Mix of business sizes and types • No more than one church per group Mix of satisfaction levels with DTE Energy/no completely unsatisfied customers Most must be in DTE “Affluent Green” or “Green” segments –note that additional “green” / philanthropic behavior qualified respondents in the Ann Arbor groups.
4 Renewables Program Report U-20471 Official Exhibits of Soulardarity Exhibit SOU-3 Page 3 of 4
MPSC Case No. U-18352 Attachment MECDE-1.2 2016 Respondent: T. L. Schroeder Page: 13 of 32
Proprietary and Confidential: For DTE Energy Internal Use Only Based on consideration and estimates in sign‐up rates, DTE Energy can expect between 1‐2% of its target market will join the program.
Based on the description they read in the survey, nearly one in five respondents would definitely consider the program, with nearly another five in ten probably considering the program. This demonstrates that the sample used in the survey effectively targeted the right customers and that DTE Energy should use that as a baseline for marketing the right people to the program. Applying a conservative estimate that 5% of those definitely considering and 1% of those probably considering would actually sign up, it is estimated that roughly 1‐2 out of every 100 targeted DTE Energy customers will sign up for the program. It is important to note, however, that this sample is weighted toward GreenCurrents customers, “green” segments, those with a higher income, and those more satisfied with DTE Energy. Based on results from Phase I, the sample also did NOT include businesses located in Detroit. Other demographic/behavioral data suggests that some populations are more propensed to consider the program. Residential – younger, female, Caucasian, higher income, college graduate, electric‐only customers and those who have a tendency to recycle, use only energy efficient light bulbs and green cleaners are more likely to consider the program. Business – smaller businesses and those businesses that tend to belong to a recycling and/or donate to charities are more likely to consider the program. 13 Renewables Program Report U-20471 Official Exhibits of Soulardarity Exhibit SOU-3 Page 4 of 4
MPSC Case No. U-18352 Attachment MECDE-1.2 2016 Respondent: T. L. Schroeder Page: 28 of 32
Beyond targeting the “Green” and “Affluent Green” residential customers, and business customers outside of Detroit, there are other groups that DTE Energy should target first to maximize its marketing dollar. If possible, consider targeting the following residential groups, each of which registered significantly higher consideration than their counterparts: Younger Female Caucasian Higher income College graduate Electric‐only customers Those residential customers who have a tendency to recycle and use only energy efficient light bulbs and green cleaners While small businesses had fewer differentiators for targeting, consider prioritizing the following, if possible: Smaller businesses (under six employees) Those businesses that tend to belong to a recycling and/or donate to charities
28 Renewables Program Report U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 1 of 10
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DTE Energy Front Groups U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 2 of 10
Michigan Energy Promise, a new front group with strong ties to the Michigan monopoly utility, DTE Energy, recently began backing the utility’s arguments against rooftop solar power. The group’s appearance comes at a time when the Michigan Public Service Commission will soon decide how much solar customers are compensated for the excess power that they produce and send back to the grid.
According to Midwest Energy News, Michigan Energy Promise is backing DTE Energy’s position on net metering and other issues before the Michigan Public Service Commission.
The group registered with the state on January 2, 2019, and created a Twitter account and Facebook profile a few weeks later.
On February 26, Bishop W.L. Starghill, Jr, a member of the new group and the Michigan Democratic Black Caucus, authored an opinion piece in Bridge Magazine attacking the solar industry with various utility industry talking points.
Michigan Energy Promise’s web pages state that it is a “project” of the Alliance For Michigan Power. Alliance For Michigan Power originated from a 501(c)(4) organization called Michigan Energy First. Michigan Energy First incorporated in December 2014 and filed documents less than a year later to register Alliance For Michigan Power.
The Department of Licensing and Regulatory Affairs database shows that the assumed names for Michigan Energy First are also Alliance For Michigan Power and Michigan Energy Promise. In other words, all three organizations appear to be coordinated jointly as a single entity. According to its 990 tax forms, Michigan Energy First has received over $28 million in contributions since 2014. The group has not disclosed its donors, but it has close ties to DTE Energy. U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 3 of 10
Assumed Names from Michigan Energy First Connections to DTE Energy
Michigan Energy First’s president is DTE Energy’s Vice President of Corporate and Government Affairs Renze Hoeksema, and its treasurer is Theresa Uzenski, a manager of regulatory accounting at DTE Energy.
DTE Energy spokesperson Peter Ternes told Midwest Energy News that the utility is “part of the Alliance for Michigan Power coalition” and Hoeksema and Uzenski “serve in an advisory capacity” on the organizations’ boards “to provide Renze information” about issues. Hoeksema Latest Industry Tactic of Rallying Communities of Color to Frame Solar Debate
Michigan Energy Promise’s spokesman Ron Fournier told the Midwest Energy News that the group is a “wide and broad coalition including leaders in specific communities in Detroit that need the most help so they’re not easily preyed upon U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 4 of 10
… Specifically African-American ministers who are tired of people coming into their community selling them services and contracts they don’t need.”
Ron Fournier is the former editor of Crain’s Detroit Business and former senior political columnist at the conservative National Journal magazine. He is now the President of the Lansing-based public relations firm Truscott Rossman.
The allies listed on Michigan Energy Promise are mostly churches, chambers of commerce, and nonprofits that advocate for communities of color. Many of the groups have either received money from the DTE Energy Foundation in recent years, list the utility as a corporate sponsor on organization websites, or a utility employee is a member of the board:
◾ Arab Community Center for Economic and Social Services has received $150,000 from the utility’s foundation from 2016 to 2017.
◾ Detroit Association of Black Organizations received $112,500 since 2015.
◾ Latin Americans for Social and Economic Development received $55,000 in 2016.
◾ Church of God in Christ received $30,000 in 2015. U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 5 of 10
◾ Urban League of Detroit and Southeast Michigan received $10,000 in 2015 and 2017.
◾ Detroit Cristo Rey High School received $4,500 in 2016 and 2017.
◾ Chaldean American Chamber of Commerce lists DTE Energy as a corporate partner.
◾ Council of Asian Pacific Americans lists DTE Energy as a sponsor, and four members of its advisory board are DTE Energy employees.
◾ Michigan Hispanic Chamber of Commerce’s executive board includes DTE Energy’s Vice President of Legal and Chief Tax Officer JoAnn Chavez.
In 2012, the electric utility’s trade association, the Edison Electric Institute, began a campaign to rally organizations against rooftop solar. EEI funded organizations and then lobbied the groups to pass anti-rooftop solar resolutions, including the National Black Caucus of State Legislators, the National Policy Alliance, and the National Organization of Black Elected Legislative Women. The groups all focused on the industry’s cost-shift argument, which is what Michigan Energy Promise also purports.
Multiple studies have shown that solar customers provide more benefits than costs to all electric customers, and a report from the Lawrence Berkeley National Lab offers the latest evidence that the utilities’ cost shift argument is, for the most part, a self-serving myth.
When EEI and its partners presented to the Congressional Black Caucus in Washington D.C. several years ago, the Huffington Post reported that the speakers pitched the members of Congress on the alleged cost-shift. A source told the outlet that there were some “pretty preposterous things being claimed there” and “it was just a lot of rhetoric, some of which was backed up by specifics, most of which was debatable.” U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 6 of 10
As noted by Midwest Energy News, other utilities have tried similar tactics to present rooftop solar as detrimental to communities of color. Duke Energy targeted African-American communities as part of its campaign against rooftop solar, according to critics. Rev. Nelson Johnson, a pastor of the predominantly African-American Faith Community Church and executive director of the Beloved Community Center, co-wrote a letter to Duke Energy CEO Lynn Good that said:
“I (Rev. Nelson Johnson) have been visited in recent months by three different individuals selling Duke’s “solar power hurts the poor” message. The claim is that the poor are left to subsidize more affluent customers who are able to buy rooftop solar power systems — because the non-solar customers are left to pay more than “their share” for Duke Energy’s large, expensive power plants.
It appears evident that this “solar hurts the poor” strategy has been coordinated by Duke and its cohorts in the corporate electric power industry and used in many states recently. Fortunately, the scheme has been rejected by the NAACP’s national board, by various state NAACP chapters, and by the Congressional Black Caucus, among others. Nevertheless, Duke Energy is vigorously pursuing this same deception in North Carolina. This cynical corporate activity is an affront to the people of this state, and it is your personal responsibility to stop it.”
ComEd also targeted African-American groups when it created a group called the Illinois Smart Solar Alliance. Just like Michigan Energy Promise, the Illinois Smart Solar Alliance included members of organizations that advocated for communities of color, some with funding or board ties to the utility.
Other groups representing communities of color have been critical of DTE’s track record. U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 7 of 10
Soulardarity advocates for energy democracy and clean energy in Highland Park, Michigan. Executive Director Jackson Koeppel told Midwest Energy News that DTE’s proposed rate increase in the same case that will decide the solar compensation rate would disproportionately raise rates for low-income customers.
“What they’ve put forward in the rate case is really egregious,” Koeppel said. “With the formation of this new front group and framing it so solar is fair to all customers is completely disingenuous.”
The national NAACP meanwhile has urged its chapters to advocate for strong rooftop solar policies, including net metering, as part of its energy democracy agenda. The national organization has supported NAACP state leadership in Nevada, Indiana, Utah, Mississippi, Colorado, Missouri that have advocated for net metering policies.
A 2017 report from the NAACP, “Lights Out In The Cold,” criticized DTE Energy for its shutoff policy and its public relations campaigns to reposition the issue after 2010 shutoffs led to deadly house fires in Detroit. The report also criticized the utility’s charity The Heat and Warmth Fund:
“Not only do these programs protect only seniors from utility shutoffs during the winter, but they also place families into payment plans that essentially keep them in a state of permanent debt to the company. In many cases, families cannot afford to stay on track with the payment plans that are offered and end up having their power disconnected anyway.” U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 8 of 10
Similarities to the Consumers Energy-funded Citizens For Energizing Michigan’s Economy
Michigan Energy First is registered to long-time campaign-finance and election attorney Eric Doster. Doster also filed the documents to register Alliance for Michigan Power and Michigan Energy Promise.
Participants in Michigan politics and its energy debates are likely familiar with Doster, a former counsel to the Michigan Republican Party and author of a book on Michigan campaign finance law. Doster is also the registered agent for Citizens For Energizing Michigan’s Economy (CEME).
Doster’s firm, CEME, and the Michigan Energy First organizations also share the same address: 2145 Commons Parkway in Okemos.
CEME is also a 501(c)(4) and has been in the news for the past several months.
The Energy and Policy Institute revealed that Consumers Energy contributed over $43 million to that entity since 2014. CEME used some of the Consumers Energy money to run radio, television, and print advertisements in primary and general election races to promote, unseat, or prevent specific candidates from winning this last election cycle. According to the Michigan Campaign Finance Network, CEME spent an estimated $830,000 on TV ads in 2018 alone. CEME promoted candidates who ran against lawmakers that supported restoring old net metering rates or favored utility deregulation – energy policies that would create competition with the investor-owned utility companies.
Just like CEME, Alliance For Michigan Power also got involved in Michigan’s 2018 elections. In the Republican primary for the 24th Senate District, Alliance U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 9 of 10
For Michigan Power sent mailers in support of Brett Roberts, who ran and lost against Representative Tom Barrett. Months earlier, Rep. Barrett had slammed the PSC for effectively ending net metering in the state:
“This short-sighted decision is beyond what the legislative directive was in the 2016 energy bill, which sought to ensure that rooftop solar users were covering their grid costs … This decision makes it harder for farmers to find solutions for their families and businesses. I am dedicated to working with the governor and legislative leaders to fix this decision.”
The Michigan Public Service Commission recently ruled in the Consumers Energy rate case that the utility is prohibited from contributing money, including its corporate dollars, to all IRS 501(c)(4) and IRS registered 527 political organizations for as long as the rates are in effect. (Consumers Energy has since said it will essentially ignore the PSC ruling by having its parent company, CMS Energy, contribute to political organizations.)
In August, Patrick Anderson, a tax policy expert and CEO of the Anderson Economic Group, filed a complaint against CEME to the IRS for violating campaign finance and federal tax laws. In his complaint, Anderson noted that CEME paid a proxy tax:
“The CEME organization is well aware that it behaves in a manner that involves prohibited activities for organizations that accept contributions that may be deducted as a trade or business expense. This is clear from their payment (as indicated in their Form 990, part XI, page 10) of a “proxy tax” of $1.51 million in 2016.”
In its 2016 IRS 990, Michigan Energy First reports paying a proxy tax of $1,650,706. U-20471 Official Exhibits of Soulardarity Exhibit SOU-4 Page 10 of 10
Photo credit: By Ikcerog at English Wikipedia – Transferred from en.wikipedia to Commons by Jay8g using CommonsHelper., Public Domain
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Posted in: DTE Energy, Front Groups Tagged in: Alliance For Michigan Power, Arab Community Center for Economic and Social Services, Bishop W.L. Starghill, Chaldean American Chamber of Commerce, Church of God in Christ, Council of Asian Pacific Americans, Detroit Association of Black Organizations, Detroit Cristo Rey High School, DTE Energy, Edison Electric Institute, Eric Doster, JoAnn Chavez, Latin Americans for Social and Economic Development, Michigan Energy First, Michigan Energy Promise, Michigan Hispanic Chamber of Commerce, Peter Ternes, Renze Hoeksema, Theresa Uzenski, Urban League of Detroit and Southeast Michigan
Posted by Matt Kasper
Matt Kasper is the Research Director at the Energy & Policy Institute. He focuses on defending policies that further the development of clean energy sources. He also frequently focuses on the companies and their front groups that obstruct policy solutions to global warming. Before joining the Energy & Policy Institute, Matt was a research assistant at the Center for American Progress where he worked on various state and local policy issues, including renewable energy standards. His work has appeared in The Guardian, the New York Times, the Washington Post, and other outlets.
All Posts Website U-20471 Official Exhibits of Soulardarity Exhibit SOU-5 Page 1 of 4
CARBON Building a Carbon-free Future REPORT
1 | Xcel Energy Carbon Report 2019 U-20471 Official Exhibits of Soulardarity Exhibit SOU-5 Page 2 of 4
Xcel Energy is committed to serving customers, and that includes responding to the concerns of many customers around the risk of climate change. National and international studies paint a sobering picture about this risk and call for nothing less than a transformation of our industry to help address it. While that transformation will be challenging, we see an opportunity for our company and those we serve to significantly reduce greenhouse gas emissions reliably, safely and at a low cost.
In 2018, we reduced carbon emissions from the electricity that serves our customers by 38 percent compared to 2005 levels and plan to do even more. As technologies have improved and costs have fallen, we are making significant changes — more than we imagined possible a decade ago — without compromising the reliability or affordability that our customers expect. We need all three components — clean, reliable and affordable — to make this transition work.
As we carry out Xcel Energy’s vision to be a preferred and trusted energy provider, leading the clean energy transition continues to be a strategic priority for us. It’s helping to achieve our other two strategic priorities as well — to keep customer bills low and enhance the customer experience.
We’re a national leader in wind energy and are harnessing it through our Steel for Fuel strategy, which we expect to reduce costs for customers. We also offer a leading portfolio of energy efficiency and renewable choice programs because an increasing number of customers want to power their homes and businesses with clean energy and take steps to reduce their own carbon footprints.
To our While our existing efforts are significant, we want to do even more and do it sooner than anticipated. That is why I set an ambitious vision to reduce our carbon emissions 80 percent from 2005 levels by 2030. Longer term, Stakeholders: we aspire to serve our customers with carbon-free electricity by 2050. The technology to achieve this aspiration isn’t commercially available yet, but I believe it can be available if we make it a priority today.
In this report, we discuss our vision, including the opportunities, risks and challenges we face getting there. We describe how our carbon transition can have an even larger impact in other sectors, such as transportation. We also show how our commitment compares to the targets of international climate agreements.
Xcel Energy is leading the clean energy transition. We know from experience that our goals are ambitious. This change will require collaborative, long-term solutions that are cost effective as well as advanced clean energy technologies. Broad stakeholder support, smart public policy and favorable economics are essential factors in this ongoing transformation.
We can’t achieve this transition alone — it will take all of us working together. I look forward to your partnership.
Sincerely,
Ben Fowke Chairman, President and CEO U-20471 Official Exhibits of Soulardarity Exhibit SOU-5 Page 3 of 4 Contents
Aspiration for a Carbon-free Energy Future...... 4 Analysis Related to Our Vision...... 7 Reporting and Measuring Progress...... 15 Managing the Risks Associated with Climate Change...... 16 Opportunities to Lead the Carbon Transition...... 18 Driving Change...... 22 Conclusion...... 25 References...... 26 About Us Xcel Energy is a major U.S. electricity and natural gas company with annual revenues of $11.4 billion. Based in Minneapolis, we operate in eight states and provide a comprehensive portfolio of energy-related products and services to 3.6 million electricity customers and 2 million natural gas customers. Addressing climate change is a priority for many of our customers, investors and key stakeholders, and is a priority for us as well. In delivering on our strategic focus to lead the clean energy transition, we are successfully reducing carbon emissions and providing clean energy solutions from a variety of renewable sources, reliably and affordably for customers. More information on our clean energy strategy, corporate governance and risk management is available at xcelenergy.com in our corporate reports, including Xcel Energy’s Annual Report, Proxy Statement, Corporate Responsibility Report and EEI Environmental, Social, Governance and Sustainability Report.
Forward Looking Statements The material in this report contains forward-looking statements that are subject to certain risks, uncertainties and assumptions. Such forward-looking statements include projections related to emission reductions, changes in our generation portfolio, planned retirements, and planned capital investments and are identified in this document by the words “aim”, “aspire”, “assuming”, “believe”, “could”, “expect”, “may”, and similar expressions. Actual results may vary materially. Factors that could cause actual results to differ materially include, but are not limited to: general economic conditions, including the availability of credit, actions of rating agencies and their impact on capital expenditures; business conditions in the energy industry: competitive factors; unusual weather; effects of geopolitical events; including war and acts of terrorism; changes in federal or state legislation; regulation; actions of regulatory bodies; and other risk factors listed from time to time by Xcel Energy in its Annual Report on Form 10-K for the fiscal year ended Dec. 31, 2018 (including the items described under Factors Affecting Results of Operations) and the other risk factors listed from time to time by Xcel Energy Inc. in reports filed with the SEC.
3 | Xcel Energy Carbon Report 2019 U-20471 Official Exhibits of Soulardarity Exhibit SOU-5 Page 4 of 4 Aspiration for a Carbon-free Energy Future
For more than a decade, Xcel Energy has demonstrated leadership on clean energy — proactively reducing carbon emissions at levels that currently surpass state and federal goals. This environmental commitment is woven into our company’s strategy, governance, executive compensation and daily operations. To respond to growing stakeholder expectations, we have regularly established and achieved increasingly ambitious carbon reduction goals.
Where We Aim to Be 20% Our vision for the future includes industry-leading goals shown in Figure 1. In this report, we demonstrate how our goals align with0% an emissions trajectory needed for the electric power sector to meet the goals of the Paris climate agreement. 2005 2010 2020 2030 2040 2050 Baseline Year 201 By 2030, we-20 aim% to reduce carbon dioxide35% emissions 80 percent below 2005 levels company-wide. This means that by 2030, our annual carbon emissionsAchieved from the electricity that serves our customers will be about 17 million tons, or 80 percent-40% lower than in 2005. We believe these emission reductions can be achieved cost effectively with continued fleet transition and operational changes, and with20 0 the renewable, carbon-free generation and energy storage technologies-60% available today. 80% By 2050, we aspire to provide our customers across all statesGoal with 100 percent carbon-free electricity. In the next 30 years,-80% we will transition to serve our customers with electric resources that emit zero carbon dioxide emissions. To fulfill this aspiration, we will continue to increase renewable energy sources on our system, as well % as technologies% Reduction in Carbon Emissions -100 that enable renewable integration. We will need new carbon-free dispatchable technologies — 20 0 technologies not yet commercially available at the cost and scale needed to achieve our 2050 aspiration. Because of this, there needs to be significant research and development to ensure we have theseZERO technologies to deploy in the Carbon Aspiration coming decades.
Xcel Energy Carbon Reduction Trajectory
0% 2005 2010 2020 2030 2040 2050 Baseline Year -20%
-40%
-60%
-80% Percent Carbon Emission Reduction -100%
201 20 0 20 0 38% 80% 100% Achieved Goal Carbon-free Electricity Aspiration
Figure 1: Our vision for the clean energy transition 2030 and 2050
4 | Xcel Energy Carbon Report 2019 U-20471 Official Exhibits of Soulardarity Exhibit SOU-6 Page 1 of 4
Northern Indiana Public Service Company LLC
2018 Integrated Resource Plan
October 31, 2018
Northern Indiana Public Service Company LLC
U-20471 Official Exhibits of Soulardarity Exhibit SOU-6 Page 2 of 4
About the 2018 Integrated Resource Plan NIPSCO initiated stakeholder advisory eorts for its 2018 IRP Current Supply in March, hosting a public meeting and launching a web page for To help ensure that we continue to meet the needs of our customers, NIPSCO’s current resource portfolio is composed of hydroelectric, interested stakeholders to follow the progress. Four additional public we must have a road map to prepare for future energy needs. Our wind, demand-side resources and natural gas-fired sources in meetings followed in May, July, September and October. NIPSCO also 2018 IRP charts a path for how best to meet those needs over the next addition to the company’s coal-fired plants. hosted public forums to discuss specific topics arising from the IRP. 20 years. NIPSCO presents this plan to the Indiana Utility Regulatory Coal remains the largest part of NIPSCO’s fleet, accounting for In addition to posting public invitations on our IRP web page, we Commission (IURC). more than half of total capacity, followed by natural gas-fired sent an invitation to past IRP stakeholder participants. Members of our The electric industry, customer needs, expectations and the way electric generation. executive leadership team and several of our subject matter experts energy is consumed continue to evolve. Technologies are rapidly NIPSCO also oers a Net Metering Program and a Feed-in Tari 2018 Integrated Resource Plan Executive Summary attended each meeting to hear feedback and answer questions. changing and expanding. The electric generation landscape is shifting Program (FIT), which allows commercial and residential customers Throughout the IRP process, stakeholders were also invited to dramatically, not just for NIPSCO but for the country as a whole. to generate their own power from renewable resources such as meet with us on a one-on-one basis to discuss key concerns and wind, solar, hydro and biomass. perspectives. Each interaction provided a forum for discussion and To further support renewable energy development, we give NIPSCO’s 2018 Integrated Resource Plan feedback related to the many components of the IRP. At NIPSCO, we’re proud that our work provides the energy customers the power to choose green energy not only through Valuable discussions arose in several key areas, including Resource planning is a complex undertaking, one that requires the Net Metering and FIT Programs, but also through the that northern Indiana families and businesses rely on to environmental regulations, fuel costs, load forecasting addressing the inherent uncertainties and risks that exist in the electric Green Power Program, in which we buy renewable energy calculations, energy eciency program analysis and power their daily lives. We work each day with the goal of industry. Key factors referred to in the IRP include market conditions, credits on customers’ behalf. fuel prices, environmental regulations, economic conditions and renewable energy development. growing alongside our communities and responding to technology advancements. The feedback gathered during the stakeholder process raised our customers’ needs. Using in-depth data, modeling and risk-based analysis provided by valuable questions, helped us better evaluate our options and internal and external subject matter experts, we project future energy improved the final plan. A summary of the meeting materials, needs and evaluate available options to meet those needs. including presentations and stakeholder questions, is available at As our customers’ needs have changed, so New to NIPSCO’s IRP, we issued a formal Request for Proposals NIPSCO.com/IRP. has the energy market. Now we stand at the About NIPSCO (RFP) solicitation to uncover the breadth of actionable projects that crossroads of the future, with the opportunity Forecasting Future Customer Demand More than 460,000 northern Indiana were available to NIPSCO within the marketplace across all technology to invest in balanced energy options and make homes and businesses depend on types. The RFP also served to collapse uncertainty about the costs of Projecting customers’ energy needs is another key component of the energy more aordable and cleaner. NIPSCO each day for safe, reliable various technologies, particularly renewables. IRP process. Looking 20 years into the future does not come without and aordable energy. Northern With an eye toward the future, we’ve been The projections included in our plan are based on the best available challenges, so we rely on data-driven models to help develop our performing a comprehensive analysis of our future Indiana is fortunate to be home to some of the top production facilities information at this point in time. Changes that aect our plan may best estimates. Specific models are developed for residential users, energy mix and meeting with our customers, in the United States. This has a arise, which is why it’s important for us to remain flexible and commercial users and industrial users, as well as for all other types of our employees and local community leaders unique impact on NIPSCO’s energy continually evaluate current market conditions, the evolution of customers, including street lighting, public authorities, railroads and over the past year. The result of this process is demand profile. Five of our largest technology—particularly renewables—and demand side resources, as company use. industrial customers, primarily in steel an Integrated Resource Plan (IRP). well as laws and environmental regulations. Data sources used in creating the forecast include energy, customer The plan—which presents over $4 billion in and oil refining, account for about 40 percent of NIPSCO’s energy demand. and price data, economic drivers, weather data and appliance long-term cost savings—is a balanced, gradual Engaging Customer and Public Stakeholders saturation. Given the unique makeup of NIPSCO’s customer base, transition that will strengthen our region now and As a member of the regional industrial operations are another significant variable. In order to put us on a path to a more cost-eective, cleaner transmission organization Resource planning requires the consideration of diverse points of view, best model their load requirements, we rely on discussions with Midcontinent Independent System and more sustainable future. which is one of the reasons that external stakeholder involvement is a our 20 largest industrial customers. It’s “Your Energy” and it’s “Your Future.” Operator (MISO), NIPSCO is able to critical component throughout the development of the IRP. supplement its own energy resources With this data, we developed multiple scenario forecasts to We engaged stakeholder groups and individuals in a variety of ways through other participating utilities capture the range of uncertainty for both energy requirements and in MISO’s footprint. This relationship throughout the entirety of the planning process. peak demand. helps ensure reliability and cost- eective operations.
NIPSCO's 2018 Integrated Resource Plan • Executive Summary • Page 1
Analyzing Future Supply Options— Energy E ciency Short-Term Action Plans (2019–Through 2021) Request for Proposals Promoting energy eciency not only is good for customers, it can The objective of the plan is to ensure that NIPSCO can confidently New to the process in the 2018 IRP, NIPSCO play an important role in helping ensure that we can meet future transition to the least-cost, cleanest supply portfolio available while issued a formal Request for Proposals (RFP) to energy needs. NIPSCO oers a variety of programs to help residential maintaining reliability, diversity and flexibility for technology and help inform the planning process, and to gain better and business customers save energy. The programs are tailored to market changes during this period. information on available, real projects at real costs from customers and designed to help ensure energy savings. within the marketplace. Since 2010, NIPSCO customers have saved more than 1 million • Initiate retirement of R.M. Schahfer Coal-Fired Units 14, 15, 17, and All energy technologies were eligible to participate, and NIPSCO megawatt hours of electricity by participating in the range of energy 18 by 2023 received 90 proposals—the sum of which represented over three eciency programs oered by NIPSCO. • Identify and implement required reliability and transmission times NIPSCO’s current generating capacity. Technologies continue to change, and it’s important that we upgrades resulting from retirement of the units Evaluating each source of electric generation for its total cost, constantly evaluate our oerings. We regularly track and report on • Select replacement projects identified from the 2018 RFP evaluation process, prioritizing resources that have expiring environmental benefits, reliability, impact on the electric system program performance, which helps to inform and improve future federal tax incentives to achieve lowest customer cost and risks is an important step in the IRP. program filings and customer oerings. File for Certificate(s) of Public Convenience and Necessity and Results from the RFP provided better information that could • other necessary approvals for selected replacement projects be incorporated into the analysis and decision-making process. Findings and Next Steps • Procure short-term capacity as needed from the MISO market or Specific screening criteria include energy source availability, Throughout the IRP analysis, we are striving to balance the needs of through short-term PPA(s) technical feasibility, commercial availability, economic our customers, employees and other community stakeholder interests. • Continue to actively monitor technology and MISO market attractiveness and environmental compatibility. Our goal as we look forward is to transition to the best-cost, trends, while staying engaged with project developers and asset cleanest electric supply mix available while keeping options open for owners to understand landscape the future as technologies and markets change. • Conduct a subsequent All-Source RFP to identify preferred resources to fill remainder of 2023 capacity need (likely Analysis shows that the most viable path for customers involves renewables and storage) accelerating the retirement of a majority of NIPSCO’s remaining Continue implementation of filed Energy Eciency Programs coal-fired generation in the next five years and all coal within the next • Plan for 2019 to 2021 10 years. Replacement options point toward lower-cost renewable • Comply with North American Electric Reliability Corporation, U.S. energy resources such as wind, solar and battery storage technology. Environmental Protection Agency and other regulations As we gradually transition to creating a more diversified energy mix • Continue planned investments in infrastructure modernization to that will be more cost eective and better serve customers in the maintain the safe and reliable delivery of energy services future, we are committed to ensuring that this plan limits the impact on local employees and our economy as a result of the remaining Long-Term Action Plans (2023–Beyond) coal retirements. • Fully retire the R.M. Schahfer Coal-Fired Units 14, 15, 17, and 18 by the end of 2023 and the Michigan City Coal-Fired Unit 12 by the end of 2028 • Monitor market and industry evolution and refine future IRP plans
While NIPSCO will continue to update its long-term plan within the next IRP, we believe that these actions coming out of the 2018 IRP will place NIPSCO on a course to continue providing reliable power while enabling lower costs and providing significant environmental benefits. U-20471 Official Exhibits of Soulardarity Exhibit SOU-6 Page 3 of 4
About the 2018 Integrated Resource Plan NIPSCO initiated stakeholder advisory eorts for its 2018 IRP Current Supply in March, hosting a public meeting and launching a web page for To help ensure that we continue to meet the needs of our customers, NIPSCO’s current resource portfolio is composed of hydroelectric, interested stakeholders to follow the progress. Four additional public we must have a road map to prepare for future energy needs. Our wind, demand-side resources and natural gas-fired sources in meetings followed in May, July, September and October. NIPSCO also 2018 IRP charts a path for how best to meet those needs over the next addition to the company’s coal-fired plants. hosted public forums to discuss specific topics arising from the IRP. 20 years. NIPSCO presents this plan to the Indiana Utility Regulatory Coal remains the largest part of NIPSCO’s fleet, accounting for In addition to posting public invitations on our IRP web page, we Commission (IURC). more than half of total capacity, followed by natural gas-fired sent an invitation to past IRP stakeholder participants. Members of our The electric industry, customer needs, expectations and the way electric generation. executive leadership team and several of our subject matter experts energy is consumed continue to evolve. Technologies are rapidly NIPSCO also oers a Net Metering Program and a Feed-in Tari attended each meeting to hear feedback and answer questions. changing and expanding. The electric generation landscape is shifting Program (FIT), which allows commercial and residential customers Throughout the IRP process, stakeholders were also invited to dramatically, not just for NIPSCO but for the country as a whole. Portfolio to generate their own power from renewable resources such as meet with us on a one-on-one basis to discuss key concerns and wind, solar, hydro and biomass. perspectives. Each interaction provided a forum for discussion and To further support renewable energy development, we give NIPSCO’s 2018 Integrated Resource Plan feedback related to the many components of the IRP. Aordable customers the power to choose green energy not only through Valuable discussions arose in several key areas, including Resource planning is a complex undertaking, one that requires the Net Metering and FIT Programs, but also through the Reliable environmental regulations, fuel costs, load forecasting addressing the inherent uncertainties and risks that exist in the electric Green Power Program, in which we buy renewable energy Compliant calculations, energy eciency program analysis and industry. Key factors referred to in the IRP include market conditions, credits on customers’ behalf. fuel prices, environmental regulations, economic conditions and Diverse renewable energy development. technology advancements. The feedback gathered during the stakeholder process raised Using in-depth data, modeling and risk-based analysis provided by Flexible valuable questions, helped us better evaluate our options and internal and external subject matter experts, we project future energy improved the final plan. A summary of the meeting materials, needs and evaluate available options to meet those needs. including presentations and stakeholder questions, is available at As our customers’ needs have changed, so New to NIPSCO’s IRP, we issued a formal Request for Proposals NIPSCO.com/IRP. has the energy market. Now we stand at the (RFP) solicitation to uncover the breadth of actionable projects that crossroads of the future, with the opportunity were available to NIPSCO within the marketplace across all technology Forecasting Future Customer Demand to invest in balanced energy options and make types. The RFP also served to collapse uncertainty about the costs of Projecting customers’ energy needs is another key component of the energy more aordable and cleaner. various technologies, particularly renewables. IRP process. Looking 20 years into the future does not come without With an eye toward the future, we’ve been The projections included in our plan are based on the best available challenges, so we rely on data-driven models to help develop our performing a comprehensive analysis of our future information at this point in time. Changes that aect our plan may best estimates. Specific models are developed for residential users, energy mix and meeting with our customers, arise, which is why it’s important for us to remain flexible and commercial users and industrial users, as well as for all other types of our employees and local community leaders continually evaluate current market conditions, the evolution of customers, including street lighting, public authorities, railroads and over the past year. The result of this process is technology—particularly renewables—and demand side resources, as company use. an Integrated Resource Plan (IRP). well as laws and environmental regulations. Data sources used in creating the forecast include energy, customer The plan—which presents over $4 billion in and price data, economic drivers, weather data and appliance long-term cost savings—is a balanced, gradual Engaging Customer and Public Stakeholders saturation. Given the unique makeup of NIPSCO’s customer base, transition that will strengthen our region now and industrial operations are another significant variable. In order to put us on a path to a more cost-eective, cleaner Resource planning requires the consideration of diverse points of view, best model their load requirements, we rely on discussions with and more sustainable future. which is one of the reasons that external stakeholder involvement is a our 20 largest industrial customers. It’s “Your Energy” and it’s “Your Future.” critical component throughout the development of the IRP. With this data, we developed multiple scenario forecasts to We engaged stakeholder groups and individuals in a variety of ways capture the range of uncertainty for both energy requirements and throughout the entirety of the planning process. peak demand.
NIPSCO's 2018 Integrated Resource Plan • Executive Summary • Page 2
Analyzing Future Supply Options— Energy E ciency Short-Term Action Plans (2019–Through 2021) Request for Proposals Promoting energy eciency not only is good for customers, it can The objective of the plan is to ensure that NIPSCO can confidently New to the process in the 2018 IRP, NIPSCO play an important role in helping ensure that we can meet future transition to the least-cost, cleanest supply portfolio available while issued a formal Request for Proposals (RFP) to energy needs. NIPSCO oers a variety of programs to help residential maintaining reliability, diversity and flexibility for technology and help inform the planning process, and to gain better and business customers save energy. The programs are tailored to market changes during this period. information on available, real projects at real costs from customers and designed to help ensure energy savings. within the marketplace. Since 2010, NIPSCO customers have saved more than 1 million • Initiate retirement of R.M. Schahfer Coal-Fired Units 14, 15, 17, and All energy technologies were eligible to participate, and NIPSCO megawatt hours of electricity by participating in the range of energy 18 by 2023 received 90 proposals—the sum of which represented over three eciency programs oered by NIPSCO. • Identify and implement required reliability and transmission times NIPSCO’s current generating capacity. Technologies continue to change, and it’s important that we upgrades resulting from retirement of the units Evaluating each source of electric generation for its total cost, constantly evaluate our oerings. We regularly track and report on • Select replacement projects identified from the 2018 RFP evaluation process, prioritizing resources that have expiring environmental benefits, reliability, impact on the electric system program performance, which helps to inform and improve future federal tax incentives to achieve lowest customer cost and risks is an important step in the IRP. program filings and customer oerings. File for Certificate(s) of Public Convenience and Necessity and Results from the RFP provided better information that could • other necessary approvals for selected replacement projects be incorporated into the analysis and decision-making process. Findings and Next Steps • Procure short-term capacity as needed from the MISO market or Specific screening criteria include energy source availability, Throughout the IRP analysis, we are striving to balance the needs of through short-term PPA(s) technical feasibility, commercial availability, economic our customers, employees and other community stakeholder interests. • Continue to actively monitor technology and MISO market attractiveness and environmental compatibility. Our goal as we look forward is to transition to the best-cost, trends, while staying engaged with project developers and asset cleanest electric supply mix available while keeping options open for owners to understand landscape the future as technologies and markets change. • Conduct a subsequent All-Source RFP to identify preferred resources to fill remainder of 2023 capacity need (likely Analysis shows that the most viable path for customers involves renewables and storage) accelerating the retirement of a majority of NIPSCO’s remaining Continue implementation of filed Energy Eciency Programs coal-fired generation in the next five years and all coal within the next • Plan for 2019 to 2021 10 years. Replacement options point toward lower-cost renewable • Comply with North American Electric Reliability Corporation, U.S. energy resources such as wind, solar and battery storage technology. Environmental Protection Agency and other regulations As we gradually transition to creating a more diversified energy mix • Continue planned investments in infrastructure modernization to that will be more cost eective and better serve customers in the maintain the safe and reliable delivery of energy services future, we are committed to ensuring that this plan limits the impact on local employees and our economy as a result of the remaining Long-Term Action Plans (2023–Beyond) coal retirements. • Fully retire the R.M. Schahfer Coal-Fired Units 14, 15, 17, and 18 by the end of 2023 and the Michigan City Coal-Fired Unit 12 by the end of 2028 • Monitor market and industry evolution and refine future IRP plans
While NIPSCO will continue to update its long-term plan within the next IRP, we believe that these actions coming out of the 2018 IRP will place NIPSCO on a course to continue providing reliable power while enabling lower costs and providing significant environmental benefits. U-20471 Official Exhibits of Soulardarity Exhibit SOU-6 Page 4 of 4 Section 7. Environmental Considerations
7.1 Environmental Sustainability
NIPSCO is committed to compliance, stewardship, and continuing to provide energy in an environmentally responsible way. NIPSCO’s current electric generation portfolio consists of assets that includes coal and natural gas plants, wind contracts, and hydroelectric power plants. Environmental improvement targets were announced in 2017, and this resource plan contemplates a transition of coal generation assets to renewable energy that would result in enhanced environmental improvements in electric generation by 2028 (from 2005 levels), as follows:
90% Reduction in Greenhouse Gas (“GHG”) Emissions
99% Reduction in Water Withdrawal and Wastewater Discharge
99% Reduction in NOx Emissions
99+% Reduction in SO2 and Mercury Emissions
100% Reduction in Coal Ash Generated 7.2 Environmental Compliance Plan Development
NIPSCO operations are subject to environmental statutes and regulations related to air quality, water quality, hazardous waste, and solid waste that protect health and the environment. NIPSCO is committed to complying with all regulatory requirements. This commitment is embodied in the NiSource Environmental, Health & Safety and Climate Change Policies and is implemented through a comprehensive environmental management system. Compliance plans are developed, reviewed, and evaluated for implementation to meet new and changing legislative and regulatory developments.
NIPSCO uses a combination of external and internal resources to develop and adapt environmental compliance plans. Consultants and engineering firms are utilized to assist NIPSCO in developing cost estimates and performing modeling. Compliance plans are drafted to address proposed and final EPA and Indiana Department of Environmental Management (“IDEM”) rules. As rules change, compliance plans are modified to comply with new requirements. 7.3 Environmental Regulations
7.3.1 Solid Waste Management
The EPA finalized a rule regulating the management and disposal of Coal Combustion Residuals (“CCR”) which became effective on October 19, 2015. The CCR rule regulates CCRs under the Resource, Conservation, and Recovery Act (RCRA) Subtitle D as nonhazardous. The CCR rule is implemented in phases establishing requirements related to groundwater monitoring,
103 Northern Indiana Public Service Company LLC U-20471 Official Exhibits of Soulardarity Exhibit SOU-7 Page 1 of 10 U-20471 Official Exhibits of Soulardarity Exhibit SOU-7 Page 2 of 10
Acknowledgements This report was written by Dow Sustainability Masters Fellows in partnership with Soulardarity. Thanks to Shimekia , Soulardarity; Maria Thomas, Soulardarity; Jackson Koeppel,
Soulardarity; Grace Brosnan;Nichols Soulardarity; Margaret Woolridge, Dow Sustainability Fellows Program; Nicole Berg, Graham Institute of Sustainability; Tony Reames; School for Environment and Sustainability; David Brosch, University Park Solar Co-op; Lisa Stolarski and Brian Donovan, the Cooperation Group; Rick Bunch, Southeast Michigan Regional Energy Office
Authors Caillin Buchanan, School for Environment and Sustainability and Chemical Engineering Tyler Fitch, School for Environment and Sustainability Benny Jeong, Energy Systems Engineering Anna Lenhart, Ford School of Public Policy
December 2017
Understanding the Potential for Community Solar in Highland Park U-20471 Official Exhibits of Soulardarity Exhibit SOU-7 Page 3 of 10 2
Table of Contents
Acknowledgements ...... 1 Authors ...... 1
Table of Contents ...... 2
1. Executive Summary ...... 4
2. Background ...... 5 2.1 Highland Park Context ...... 5 2.1.1 Highland Park ...... 5 2.1.2 About Our Client: Soulardarity ...... 6 2.2 Solar Resource Potential in Highland Park ...... 7
3. Problem Definition & Objectives ...... 9
4. Community Solar and Energy Democracy in Highland Park ...... 10 4.1 What does a Just & Effective Community Solar Project Look Like? ...... 11 4.2 Proposed Business Model: Community Power Purchase Agreement (PPA) ...... 12
5. Methods: Community Solar Calculator ...... 13 5.1 Inputs ...... 13 5.2 Outputs ...... 15
6. Results: Case Studies & Sensitivity Analysis ...... 15 6.1 Parker Village ...... 15 6.2 Labelle Towers ...... 16 6.3 Nandi’s Knowledge Cafe ...... 16 6.4 Calculator Outputs ...... 17 6.5 Sensitivity Analysis ...... 18
7. Policy Considerations for Community Solar ...... 20 7.1 Federal Policy ...... 20 7.1.1 Tax Incentives ...... 20 7.1.2. Federal (and, if applicable, state) Securities Regulation...... 21
Understanding the Potential for Community Solar in Highland Park U-20471 Official Exhibits of Soulardarity Exhibit SOU-7 Page 4 of 10
7.2. State Policy ...... 21 7.2.1. Renewable Portfolio Standard (RPS) and Renewable Energy Certificates (RECS) ...... 21 7.2.2. Net Metering ...... 22 7.2.3. Property Taxes ...... 22
8. Making Community Solar a Reality ...... 23 8.1 Setting project objectives ...... 23 8.2 Forming a Special Purpose Entity: ...... 24 8.3 Building relationships with potential partners...... 25 8.4 Getting Legal & Accounting Support ...... 26
9. Discussion and Conclusions ...... 26
Appendices ...... 27
References ...... 27
Understanding the Potential for Community Solar in Highland Park U-20471 Official Exhibits of Soulardarity Exhibit SOU-7 Page 5 of 10 4
1. Executive Summary
Urban, poverty-stricken, and disinvested communities are struggling to reliably and affordably secure the energy services they need. At the same time, the moral and economic case for distributed renewable energy technologies promises transformative change for how electricity is created and consumed. Together, these trends enable a future where communities exercise agency over the way their energy is produced and consumed. Soulardarity, a grassroots community organization centered in Highland Park, Michigan, is working to make this vision of energy democracy a reality. The Dow Sustainability Fellowship team partnered with Soulardarity to assess the feasibility of installing a community-owned and operated solar project in Highland Park.
Community solar projects—where community members co-invest in an array of solar panels, and each receive benefits as the solar project generates electricity—are taking off around the country as the price for solar continues to decline.i They’re proving to be a viable solution for expanding solar access to the estimated 50% of households who wouldn’t otherwise be able to install solar due to renters status, inappropriate roof material, or other factors.ii But there are substantial barriers to community solar in Highland Park. State policies disallow group net metering and discourage third parties from being able to operate their own solar projects.
We propose that Soulardarity considers a community power purchase agreement (community PPA). Rather than working directly with utility companies to manage a community solar program, a community group might buy solar panels, then partner with a host institution—like a church or a community center—and install the solar project onsite. Then the host institution pays the owner— in this case, the community group—for the energy from the solar panels. This way, the community institution gets cheaper and cleaner power, and the community group can raise money for futre projects. While community PPAs are a relatively new concept, the model has already seen success at Maryland’s University Park Solar Co-Op.
While a community PPA is logistically feasible, it must also be economically feasible in Highland Park. We created a Community Solar Calculator, which models the technical, economic, and financial details of a community solar project based on user inputs. Using the Community Solar Calculator, Soulardarity can model the costs of a project, the amount of roof space needed, and the economic returns for any potential solar project. Based on preliminary research in Highland Park,
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we chose three community institutions as case studies for the calculator: Nandi’s Knowledge Cafe, Parker Village, and Labelle Towers.
Our case studies found that while results vary substantially based on the chosen financing model, installed cost, markdown to project host, and discount rate, community solar projects have the potential to be economically viable at low-cost financing. While launching an innovative, long-term partnership such as a community PPA requires careful legal and accounting consideration, our research indicates that the basic economics are sound: a community PPA in Highland Park will save a Highland Park institution money on their utility bills while funding Soulardarity’s mission.
2. Background
2.1 Highland Park Context
2.1.1 Highland Park Highland Park is a community in Southeast Michigan, surrounded by the City of Detroit. Its population peaked around 52,000 in the 1930’s with the early automotive industry, as both Ford and Chrysler were headquartered in the city. Since the 1930’s Highland Park’s population has declined. The population of Highland Park is now estimated at around 10,888 (2016 population estimate).iii In the late 1900’s Ford and Chrysler moved their headquarters instigating decades of economic decline in the community. According to The American Community Survey 2011-2015, 49.3% of the population lives below the poverty line, a number significantly above the national average of 14.7%.iv As seen in Figure 1, median income in Highland Park is $17,250 (the median property value is $36,000 with 36% of residents owning a home).v
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Figure 1: Median Income In Highland Park (city outlined in yellow)
According to The American Community Survey 2011-2015, 91.9% of the residents (10,203 +/- 274) identify as Black. 18.8% of the residents are between 5-18 years of age and 14.9% are between 45- 54 years of age.vi
2.1.2 About Our Client: Soulardarity Soulardarity’s mission is to build a brighter future in Highland Park with education, organizing, and people-powered clean energy. Soulardarity is a membership-based 501c3 non-profit working to install solar-powered streetlights, save money on energy bills, and work together with neighboring communities to build a just and equitable energy system for all.vii
Jackson Koeppel founded the organization in 2011 in response to DTE Energy’s repossession of
over 1,000 streetlightco- s from Highland Park. Soulardarity installed a pilot solar light in 2012, and has since worked with Highland Park on a proposal to erect 200 solar streetlights around the city. In the process, they’ve grown to over 120 members—a significant portion of Highland Park’s 10,888 residents. Their vision and purpose has expanded to not simply replacing streetlights but also to reducing energy burdens on their community.
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2.2 Solar Resource Potential in Highland Park Highland Park could pursue several types of renewable energy, but based on the interest of our client, Soulardarity, and scope of the project, we assumed that solar power would be employed. To confirm that Highland Park had sufficient solar resources, we conducted an initial solar energy assessment. We used several software programs to determine the total amount of solar energy possible through both rooftop panel installation and vacant lot conversion to ground solar panel systems. Google’s Project Sunroof estimates that 68% of Highland Park’s buildings are viable for rooftop solar panels, and that 83,000 MWh of AC electricity could be generated annually if every available rooftop had solar panels installed.viii Figure 2 and 3 depict Project Sunroof’s output for Highland Park specifically.
Figure 2: Google’s Project Sunroof rooftop solar potential for Highland Park, MIix
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8
Figure 3: Google Project Sunroof Electricity estimations for Highland Park, MIx
In addition to rooftop potential, we assumed that ground solar panel systems could be installed on vacant lots throughout Highland Park. The Motor City Mapping Highland Park Tool was used to find the total number of vacant lots available for solar power generation in Highland Park.xi As seen in Figure 4, vacant lots account for approximately 30% of all lots in Highland Park. To deliver a rough estimate, we assumed that 30% of total land area within Highland Park consisted of vacant lots. Using this method, an assumption of 20% panel efficiency and an average solar irradiation of 4.41 kWh/m2/day, we determined that the total electricity available from vacant lot solar panel systems could reach approximately 707,400 MWh/yr.
Figure 4: Output of Motor City Tool, with vacant lots in Highland Park highlighted.xii
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The total average annual energy demand in Highland Park for residential and commercial sectors is approximately 86,200 MWh, suggesting that if all viable rooftops in Highland Park had solar panels installed, then 96% of total residential and commercial energy demand could be met.xiii Vacant lot solar panel systems could supply almost ten times the energy that Highland Park’s residential and commercial sectors currently demand.
3. Problem Definition & Objectives
Low-income households tend to pay a higher portion of their income toward their utility bills. For the poorest households in Detroit, the percentage paid toward energy can reach over 15% of total income.xiv High energy burdens such as these can crowd out other payments, displace investments, or force households to choose between heating their home and other needs. Similar research has shown a discrepancy in this energy burden between white households and households of color.
As Soulardarity’s membership has grown, their mission has expanded to include alleviating community energy burden. Soulardarity members believe they are being mistreated by the utilities (DTE Energy) and are interested in becoming energy sovereign. They asked us to do two things, 1) get a better sense of the problem and potential need for solar energy to address financial burden and injustice in the community through a community survey, and 2) perform a feasibility study of bringing community solar to Highland Park. To do this, a Community Solar Calculator was developed to estimate solar capacity and rate of return on investment for specific sites. This will be discussed in greater detail in Section 5.
On July 9, 2017 Soulardarity volunteers, led by Intern Grace Brosnan, walked the neighborhoods of Highland Park to conduct a survey about the resident’s experiences with energy utilities (Appendix A: Survey Questions and Appendix B: Survey Results have been redacted from the public edition of this report). The purpose of the survey was to gain a better understanding of the need for community solar from both an economic and social justice perspective. Specifically, according to “Lights Out In The Cold” Environmental and Climate Justice Program NAACP, in Michiganxv:
• Notice of disconnections must be provided by phone or mailing. Phone notice must be attempted two times at least one day before the scheduled disconnection. Mailed notice must be sent at least five days before the scheduled disconnection.
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Michigan Technological University Digital Commons @ Michigan Tech
Department of Social Sciences Publications Department of Social Sciences
2-20-2019 Policies to overcome barriers for renewable energy distributed generation: A Case study of utility structure and regulatory regimes in Michigan Emily Prehoda Michigan Technological University
Joshua M. Pearce Michigan Technological University
Chelsea Schelly Michigan Technological University
Follow this and additional works at: https://digitalcommons.mtu.edu/social-sciences-fp Part of the Energy Policy Commons, and the Environmental Policy Commons
Recommended Citation Prehoda, E., Pearce, J. M., & Schelly, C. (2019). Policies to overcome barriers for renewable energy distributed generation: A Case study of utility structure and regulatory regimes in Michigan. Energies, 12(4). http://dx.doi.org/10.3390/en12040674 Retrieved from: https://digitalcommons.mtu.edu/social-sciences-fp/164
Follow this and additional works at: https://digitalcommons.mtu.edu/social-sciences-fp
Part of the Energy Policy Commons, and the Environmental Policy Commons U-20471 Official Exhibits of Soulardarity Exhibit SOU-8 energies Page 2 of 8
Review Policies to Overcome Barriers for Renewable Energy Distributed Generation: A Case Study of Utility Structure and Regulatory Regimes in Michigan
Emily Prehoda 1, Joshua M. Pearce 2,3,* and Chelsea Schelly 1 1 Department of Social Sciences, Michigan Technological University, Houghton, MI 49931, USA; [email protected] (E.P.); [email protected] (C.S.) 2 Department of Material Science & Engineering and Department of Electrical & Computer Engineering, Michigan Technological University, Houghton, MI 49931, USA 3 Department of Electronics and Nanoengineering, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland * Correspondence: [email protected] or joshua.pearce@aalto.fi
Received: 9 January 2019; Accepted: 14 February 2019; Published: 20 February 2019
Abstract: Because of its environmental damage and now often being the most expensive source for electricity production, coal use is declining throughout the United States. Michigan has no active coal mining and seemingly supportive legislation for distributed generation (DG) and renewable energy (RE) technologies. However, Michigan still derives approximately half of its power production from large centralized coal plants, despite the availability of much lower cost RE DG technologies. To understand this conundrum, this study reviews how Michigan investor owned utilities utilize their political power to perpetuate utility structures that work toward the financial interests of the utilities rather than the best interests of the state’s electricity consumers, including other firms and residents. Background is provided covering the concept of DG, the cost savings associated with DG, and utility regulatory regimes at the national, regional, state, and local levels. Recent case studies from specific utility strategies are provided in order to illustrate how Michigan utilities manipulate regulatory regimes via policy misinterpretation to deter or hinder the proliferation of DG in favor of maintaining the existing interests in centralized, fossil fuel-based electrical energy production. The results of this study demonstrate how DG proliferation is hindered by Michigan regulated utilities via the exercise of political power within existing legal and regulatory regimes. This highlights the need to think about how utilities may interpret and implement rules when designing energy legislation and policy to maximize the benefits for consumers and society. Policy recommendations and alternate strategies are provided to help enhance the role of energy policy to improve rather than limit the utilization of RE DG.
Keywords: distributed generation; energy policy; renewable energy; electric utilities; utility regulation
1. Introduction Nearly half of electrical generation in Michigan is provided by coal-fired electrical power plants that are concentrated in the Lower Peninsula [1]. Although there are some coal resources underground in Michigan, the state has no active coal mines [2]. This requires Michigan to import all of its fuel for these coal-fired power plants, moving money out of the state [3]. Yet, Michigan has substantial renewable energy (RE) resource potential in the form of biomass from an abundance of forestland area [4], hydroelectric power along many rivers [5], as well as ample wind [6] and solar energy [7,8]. Modern solar photovoltaic (PV) [9] and wind energy [10] technologies provide a lower levelized cost of electricity [11–13] than coal-fired electricity [14,15]. In addition, they can be inherently distributed (e.g.
Energies 2019, 12, 674; doi:10.3390/en12040674 www.mdpi.com/journal/energies U-20471 Official Exhibits of Soulardarity Exhibit SOU-8 Page 3 of 8 Energies 2019, 12, 674 2 of 23 each electricity consumer produces some or all of their electricity on site). Distributed generation (DG) has several technical advantages, including improved reliability and reduced transmission losses [16, 17]. RE resources in general and DG RE in particular increase access to more affordable and locally (or even individually) owned energy systems, arguably a more socially just technological application for the provision of electrical energy services [18–22]. Despite these benefits, Michigan’s RE profile remains low [1] and some of Michigan’s residential electricity consumers are paying approximately 20% more for electricity than the United States (U.S.) averages [9]. To understand why Michigan continues to use more expensive and less environmentally benign electricity generation technologies, this study investigates the utility structures and regulatory regimes in Michigan. It explores how existing utility entities in the state navigate the implementation of existing energy policy, finding that policy interpretation and implementation serve to perpetuate the existing, fossil fuel dependent energy regime. As with other U.S. states, electrical energy is provided to Michigan’s customers by various utility entities organized in three utility structures: (i) municipally owned entities, (ii) cooperative electric associations, and (iii) investor owned utilities (IOUs). Municipal utilities and rural electric cooperatives or rural electric associations are organized as public entities. IOUs, on the other hand, are private and for-profit firms that provide electricity to 67% [23] of U.S. and 84% of Michigan customers [24]. As privately owned utility companies, IOUs must comply with regulatory measures that are set by the state. However, the implementation of regulatory measures involves interpretation. In the past, Michigan utilities’ interpretation and implementation of existing federal and state energy laws functioned to disincentivize DG proliferation, which limited the growth of RE deployment. For example, Michigan maintains a Renewable Energy Standard (RES) that requires regulated utilities to obtain 15% of electrical generation from renewables by 2021 [25]. A net metering program that provides DG customers with credit for excess generation is within the RES; Michigan legislation states that “An electric utility or alternative electric supplier is not required to allow for a distributed generation program that is greater than 1% of its average in-state peak load for the preceding five calendar years” [26]. Some IOUs operating in the state interpret this as a maximum and cap net metering capacity to 1% of the peak generation load [27]. Michigan legislation also provides choice of electric supplier to consumers, yet the legislation limits participation to 10% of the generation load [28]. These are just two examples of how utility interpretation and implementation of energy legislation function to limit DG within the state of Michigan. As a result, the DG capacity of Michigan at the end of 2017 was roughly 30 MW [29], totaling 10% of Michigan total energy usage [30]. The purpose of this study is to investigate how IOUs in Michigan utilize their political power to perpetuate utility structures that work in the financial interests of the utilities rather than the best interests of the state’s electricity consumers, including other firms and residents. Background is provided covering the concept of DG, the cost savings associated with DG, and utility regulatory regimes at the national, regional, state, and local levels. Recent case studies of specific utility strategies are provided to illustrate how Michigan utilities use policy interpretation and implementation to deter or hinder the proliferation of DG in favor of the maintenance of existing interests in centralized, fossil fuel-based electrical energy production. Finally, policy recommendations and alternate strategies are provided to help in enhancing the role of energy policy to improve rather than limit RE DG.
2. Background This section begins with a brief description of DG including the cost savings associated with DG for Michigan utility customers before turning to the Michigan Public Service Commission (MPSC) compliance requirements to the Michigan legislature regarding DG reporting. It then describes the multilevel governance structures within which U.S. utilities operate. The Federal Energy Regulatory Commission (FERC) oversees the wholesale electricity market along with the interstate transmission of electricity. Public Service Commissions (PSC), which are also known as Public Utility Commissions U-20471 Official Exhibits of Soulardarity Exhibit SOU-8 Page 4 of 8 Energies 2019, 12, 674 3 of 23
(PUC), regulate the retail rates of utilities within each state. Different utility types are regulated differently in each state; this section describes utility regulation only as specifically applicable in Michigan.
2.1. What is Distributed Generation? Distributed generation refers to technology that generates electricity at or near where it will be used [31–33]. DG has different scales and applications, including a residence [34,35], a business [31], or a larger system [36] operating as a microgrid for resilience or security [37]. Utility scale energy generation, by contrast, and regardless of energy source, involves much larger systems, which are often located further away from the site of use, which are owned and operated by or for utility needs first. DG can be powered with RE sources, such as solar [31], wind [32], and hydro [38], as well as other conventional fuels, such as diesel-powered [39] generators and various hybrid arrangements of multiple sources [34,40]. This paper specifically focuses on DG from RE sources for their ability to promote locally owned and operated energy systems as well as the improvement of electrical grid operations by decreasing load and stress on transmission and distribution lines [41–45]. The environmental benefits of RE production as an alternative to conventional fossil fuels are also well established [19–21], such as reduced pollution [46], lower rates of morbidity and mortality from air pollution [47], and lessened environmental degradation [48]. On average, Michigan residential consumers pay $0.1512/kWh for electricity [9]. In order to show that DG technologies, particularly solar PV, can provide electricity savings to residential customers in almost all Michigan counties, the following analysis was conducted. A state of Michigan county shapefile was obtained from the GIS Open Data database [49]. The electricity rates for each IOU were obtained from the Michigan Public Service Commission bank of electric rate books [50]. Potential savings for each county were calculated using the levelized cost of energy following the method outlined by Branker et al. [11] from the electric rates using the following assumptions: inputting average sun hours/county, an average 5 kW solar residential system capacity, and average $/W cost of $2.50/W (The PV $/W cost was obtained through personal communication with solar development firms in Michigan, including Chart House Energy, LLC, Quality Solar, and Strawberry Solar. The value used is the average of PV suppliers and it does not include any tax credit). In addition, the LCOE is based on average annual sun hours between 3.4 and 4.4 kWh/m2/day in each county, the capacity factor calculated from sun hours, inverter replacement period of 10 years, PV system warranty of 30 years, solar PV system degradation rate of 0.5% per year, and 3.0% annual discount rate for present-value calculations. Subsequently, the savings were calculated by subtracting the solar LCOE from the IOU rates then geolocated onto each Michigan county utilizing ArcMap version 10.6.1. Table 1 breaks down each county by IOU residential rates, LCOE, sun hours [51], and the PV savings per kWh. The average monthly savings of a residential consumer that utilizes 600 kWh/month is shown in Figure 1. It is important to note that most counties contain municipal, electric cooperative, and IOUs. As this paper specifically focuses on IOU strategies to hinder DG proliferation, that is the utility type reflected in both Table 1 and Figure 1. It should also be pointed out that no incentives of any kind were assumed (e.g. current 30% federal investment tax credit), so the PV savings are an extremely conservative estimate. U-20471 Official Exhibits of Soulardarity Exhibit SOU-8 Page 5 of 8 Energies 2019, 12, 674 4 of 23
Table 1. Michigan County solar photovoltaic (PV) savings for residential systems breakdown per kWh.
Solar Flux PV LCOE Residential PV Savings County Utility (kW/m2/day) $/kWh Rates $/kWh $/kWh Alcona Consumers Energy 3.75 $0.109 $0.162 $0.052 Upper Peninsula Power Alger 3.57 $0.115 $0.185 $0.070 Co (UPPCo) Allegan Consumers Energy 3.80 $0.108 $0.162 $0.054 Alpena Alpena Power Co. 3.71 $0.110 $0.133 $0.023 Antrim Consumers Energy 3.65 $0.112 $0.162 $0.049 Arenac Consumers Energy 3.79 $0.108 $0.162 $0.054 Baraga UPPCo 3.62 $0.113 $0.185 $0.072 Barry Consumers Energy 3.79 $0.108 $0.162 $0.054 Bay Consumers Energy 3.78 $0.108 $0.162 $0.054 Benzie Consumers Energy 3.74 $0.109 $0.162 $0.052 Indiana Michigan Power Berrien 3.79 $0.108 $0.125 $0.017 (IMP) Branch Consumers Energy 3.81 $0.107 $0.162 $0.054 Calhoun Consumers Energy 3.81 $0.107 $0.162 $0.054 Cass IMP 3.82 $0.107 $0.125 $0.018 Charlevoix Consumers Energy 3.68 $0.111 $0.162 $0.051 Cheboygan Consumers Energy 3.68 $0.111 $0.162 $0.051 Chippewa non-IOU 3.66 $0.000 $0.000 $0.000 Clare Consumers Energy 3.73 $0.110 $0.162 $0.052 Clinton Consumers Energy 3.79 $0.108 $0.162 $0.054 Crawford Consumers Energy 3.70 $0.111 $0.162 $0.051 Delta UPPCo 3.70 $0.111 $0.185 $0.074 Dickinson UMERC 3.69 $0.111 $0.138 $0.027 Eaton Consumers Energy 3.80 $0.108 $0.162 $0.054 Emmet Consumers Energy 3.66 $0.112 $0.162 $0.049 Genesee Consumers Energy 3.79 $0.108 $0.162 $0.054 Gladwin Consumers Energy 3.76 $0.109 $0.162 $0.052 Gogebic Xcel 3.65 $0.112 $0.115 $0.003 Grand Traverse Consumers Energy 3.69 $0.111 $0.162 $0.051 Gratiot Consumers Energy 3.78 $0.108 $0.162 $0.054 Hillsdale Consumers Energy 3.82 $0.107 $0.162 $0.054 Houghton UPPCo 3.64 $0.112 $0.185 $0.073 Huron DTE 3.73 $0.110 $0.133 $0.023 Ingham Consumers Energy 3.80 $0.108 $0.162 $0.054 Ionia Consumers Energy 3.78 $0.108 $0.162 $0.054 Iosco Consumers Energy 3.77 $0.109 $0.162 $0.052 Iron UMERC 3.67 $0.112 $0.138 $0.026 Isabella Consumers Energy 3.76 $0.109 $0.162 $0.052 Jackson Consumers Energy 3.81 $0.107 $0.162 $0.054 Kalamazoo Consumers Energy 3.81 $0.107 $0.162 $0.054 Kalkaska Consumers Energy 3.67 $0.112 $0.162 $0.049 Kent Consumers Energy 3.78 $0.108 $0.162 $0.054 Keweenaw UPPCo 3.63 $0.113 $0.185 $0.072 Lake Consumers Energy 3.73 $0.110 $0.162 $0.052 Lapeer DTE 3.77 $0.109 $0.133 $0.024 Leelanau Consumers Energy 3.66 $0.112 $0.162 $0.049 Lenawee Consumers Energy 3.84 $0.107 $0.162 $0.054 Livingston DTE 3.81 $0.107 $0.133 $0.026 Luce non-IOU 3.63 $0.000 $0.000 $0.000 Mackinac non-IOU 3.70 $0.000 $0.000 $0.000 Macomb DTE 3.81 $0.107 $0.133 $0.026 Manistee Consumers Energy 3.73 $0.110 $0.162 $0.052 Marquette UPPCo 3.63 $0.113 $0.185 $0.072 Mason Consumers Energy 3.76 $0.109 $0.162 $0.052 Mecosta Consumers Energy 3.74 $0.109 $0.162 $0.052 Menominee UMERC 3.75 $0.109 $0.138 $0.029 U-20471 Energies 2019, 12, x FOR PEER REVIEW Official5 Exhibitsof 23 of Soulardarity Exhibit SOU-8 Page 6 of 8 MidlandEnergies 2019 , 12, 674Consumers Energy 3.77 $0.109 $0.162 5$0.052 of 23 Missaukee Consumers Energy 3.69 $0.111 $0.162 $0.051 Monroe DTE 3.85 $0.106 $0.133 $0.027 Table 1. Cont. Montcalm Consumers Energy 3.76 $0.109 $0.162 $0.052 Montmorency Consumers Energy 3.70Solar Flux $0.111PV LCOE Residential $0.162 PV Savings $0.051 County Utility Muskegon Consumers Energy 3.78(kW/m 2/day) $0.108$/kWh Rates $0.162$/kWh $/kWh $0.054 NewaygoMidland Consumers Consumers Energy Energy 3.76 3.77 $0.109 $0.109 $0.162 $0.162 $0.052 $0.052 OaklandMissaukee DTE Consumers Energy 3.80 3.69$0.108 $0.111 $0.162$0.133 $0.051$0.025 OceanaMonroe Consumers EnergyDTE 3.77 3.85$0.109 $0.106 $0.133$0.162 $0.027$0.052 Montcalm Consumers Energy 3.76 $0.109 $0.162 $0.052 Ogemaw Consumers Energy 3.75 $0.109 $0.162 $0.052 Montmorency Consumers Energy 3.70 $0.111 $0.162 $0.051 OntonagonMuskegon UPPCo Consumers Energy 3.61 3.78 $0.113 $0.108 $0.162 $0.185 $0.054 $0.072 OsceolaNewaygo Consumers Consumers Energy Energy 3.72 3.76$0.110 $0.109 $0.162$0.162 $0.052$0.052 OscodaOakland Consumers EnergyDTE 3.72 3.80$0.110 $0.108 $0.133$0.162 $0.025$0.052 OtsegoOceana Consumers Consumers Energy Energy 3.68 3.77 $0.111 $0.109 $0.162 $0.162 $0.052 $0.051 Ogemaw Consumers Energy 3.75 $0.109 $0.162 $0.052 OttawaOntonagon Consumers EnergyUPPCo 3.80 3.61 $0.108 $0.113 $0.185 $0.162 $0.072 $0.054 PresqueOsceola Isle Consumers Consumers Energy Energy 3.68 3.72 $0.111 $0.110 $0.162 $0.162 $0.052 $0.051 RoscommonOscoda Consumers Consumers Energy Energy 3.73 3.72 $0.110 $0.110 $0.162 $0.162 $0.052 $0.052 SaginawOtsego Consumers Consumers Energy Energy 3.78 3.68$0.108 $0.111 $0.162$0.162 $0.051$0.054 Ottawa Consumers Energy 3.80 $0.108 $0.162 $0.054 St. Clair DTE 3.66 $0.112 $0.133 $0.021 Presque Isle Consumers Energy 3.68 $0.111 $0.162 $0.051 St. JosephRoscommon Consumers Consumers Energy Energy 3.80 3.73 $0.108 $0.110 $0.162 $0.162 $0.052 $0.054 SanilacSaginaw DTE Consumers Energy 3.78 3.78$0.108 $0.108 $0.162$0.133 $0.054$0.025 SchoolcraftSt. Clair UPPCo DTE 3.82 3.66 $0.107 $0.112 $0.133 $0.185 $0.021$0.078 ShiawasseeSt. Joseph Consumers Consumers Energy Energy 3.74 3.80 $0.109 $0.108 $0.162 $0.162 $0.054 $0.052 Sanilac DTE 3.78 $0.108 $0.133 $0.025 TuscolaSchoolcraft DTE UPPCo 3.77 3.82$0.109 $0.107 $0.185$0.133 $0.078$0.024 Van BurenShiawassee Consumers Consumers Energy Energy 3.81 3.74 $0.107 $0.109 $0.162 $0.162 $0.052 $0.054 WashtenawTuscola DTE DTE 3.83 3.77 $0.107 $0.109 $0.133$0.133 $0.024$0.026 WayneVan BurenDTE Consumers Energy 3.84 3.81$0.107 $0.107 $0.162$0.133 $0.054$0.026 Washtenaw DTE 3.83 $0.107 $0.133 $0.026 WexfordWayne Consumers EnergyDTE 3.70 3.84 $0.111 $0.107 $0.133 $0.162 $0.026 $0.051 Wexford Consumers Energy 3.70 $0.111 $0.162 $0.051
Figure 1. Savings ($/kWh) provided to each Michigan county from residential solar PV.
Figure 1. Savings ($/kWh) provided to each Michigan county from residential solar PV.
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4. Policy Interpretation and Implementation as Utility Driven Manipulation The history of the electricity industry credits Samuel Insull with the consolidation of utilities into larger, investor owned, centralized electrical generation stations [84]. Since this time, utilities have increasingly operated according to the main goal of maximizing profits. Decisions surrounding how to maximize profits do not usually occur without a precedent or prior experience of the firm or regulators [85]. Profits and previous experience shaped and explained utility companies’ behaviors during the first half of the 20th century [86]. However, contemporary IOUs, as examined here in the case study of Michigan utilities, continue to rely on these considerations to manipulate the interpretation and implementation of laws in ways that align with business as usual utility operations and cost recovery goals.
4.1. Rate Cases and the New Inflow/Outflow Methodology The first way that a public utility can manipulate the law is through proposed rate cases. IOUs are subject to state regulation by PSCs [82], and the PSCs set prices for different customer types as well as determining the rate of return on investment for a utility. This is a measure of profitability for the utility and therefore it is constantly updated with each rate case that a utility proposes. Prior to Michigan’s 2016 legislation, regulated utilities could self-implement rate increases if the MPSC had not issued a final order within six months of receiving the rate case. As stated above, the MPSC recently accepted an inflow/outflow methodology of crediting DG customers for their excess generation. This means that utilities will use instantaneous metering to read any electricity that flows into the customer’s home, business, or building as well as excess generation from the DG system. As per the 2016 energy legislation (section 460.1177), “the credit per kilowatt hour for kilowatt hours delivered into the utility’s distribution system shall be either of the following: (a) The monthly average real-time locational marginal price for energy at the commercial pricing node within the electric utility’s distribution service territory, or for the distributed generation customers on a time-based rate schedule, the monthly average real-time locational marginal price for energy at the commercial pricing node within the electric utility’s distribution service territory during the time-of-use pricing period. (b) The electric utility’s or alternative electric supplier’s power supply component, excluding transmission charges, of the full retail rate during the billing period or the time-of-use pricing period.” Utilities can choose to select one of these two options to credit DG customers. Option (a) utilizes locational marginal pricing from the MISO Michigan Hub. Utilities that select this option would essentially credit DG customer outflow at a wholesale rate, or $0.03/kWh (2017 average MISO Michigan Hub price) [87]. MPSC staff was not aware of any utility selecting this option to credit DG customers under the current net metering program (Personal communication with MPSC staff on October 31st, 2018.). However, DTE recently submitted their proposed DG tariff [79], in which they propose to credit customers with the locational marginal pricing, in which power from DG sources is less valued and it does not reflect DG’s contribution to reducing overall DTE operations costs, capacity, and other factors that would be considered in a Cost of Service Study, such as avoided transmission, distribution and voltage control costs [88]. Several studies have shown that DG actually lowers the electric grid operational costs that are incurred by the utility and they should be valued higher than the proposed LMP [88]. Accepting an outflow credit at this rate would create a great deterrent in the development of grid-connected DG systems. Under this model, utilities would be the only grid-connected entity that is able to take advantage of the economics and benefits from DG. Given the economics of DG solar in Michigan, this could catalyze grid defection [89] with utility customers choosing to produce their own power with a hybrid system that is made of up solar, batteries, and gas cogeneration units [11]. This risks creating a utility death spiral [90].
4.2. Legal Maneuvers Utilities can use litigation strategies, such as maneuvering or stalling, to delay legal proceedings to change public perception. One specific example is the use of the narrative that DG customers that U-20471 Official Exhibits of Soulardarity Exhibit SOU-8 Page 8 of 8 Energies 2019, 12, 674 11 of 23 are enrolled in net metering place extra cost burdens on traditional and lower income customers; put another way, some claim that traditional customers subsidize DG customers [91,92]. For example, DTE states that DG “customers are not supporting the costs of the infrastructure required for their service” [93]. However, as shown above, DG can actually reduce the costs for the utility and its customers [88], yet DTE appears to make the above claim without conducting its own study assessing the benefits of DG. In response to a cross-examination question regarding analyses on beneficial impacts of DG on the electrical grid, a DTE witness stated, “we have not performed those studies” [94]. DTE’s proposed DG tariff seeks to reflect the discrepancy between DG and non-DG customers costs. However, in response to including DG cost assessments in historical or projected figures to justify the proposed higher costs for DG customers, another DTE employee and witness stated that such evidence was “not in mine [testimony]” [94]. A second example of IOU tactics to hinder DG is to use lobbying as a way to influence new legislation or amend existing legislation. Electric utilities fund organizations and committees to elect governors, state legislators, and attorneys general, who can enact laws and implement rules to support utility positions. The electric utility industry has the third largest lobbying contribution, spending roughly $2.4 billion [95]. Utilities have contributed some of the highest amounts of campaign money this current election cycle [96] as compared to the election cycles from 2010 onward. While utilities contributions typically lean towards the Republican Party [96], they generally support candidates in the lead, evenly contributing when elections are competitive [97]. Utilities can also use stalling tactics to buy more time during negotiation periods. This can come in the form of requesting new information [98], establishing arbitrary timelines [99], or advocating for the need for additional research before a decision can be made [30]. Utilities can slow legal proceedings to support a traditional cost recovery model where they own and operate generation [100]. In many states, the prices of utility scale DG have decreased dramatically, matching a utility’s avoided costs. There has been recent pushback regarding PURPA’s contract lengths, rates, and other changes, such as the need for capacity. The MPSC recently underwent a process to revise and redefine the avoided costs of qualifying facilities under PURPA, which had not been done in roughly 30 years. The MPSC revised the PURPA contract length to 20 years and increased the capacity to 2 MW; the previous contract project size was capped at 100 kW [101]. They halted implementations to work out challenges with utilities. Specifically, the Consumers Energy Company argues that they should not be required to purchase power from PURPA qualified facilities because they do not need any new generation in the next 10 years, yet they plan to close two coal fired power plants and ramp up RE energy generation to 40% and utilize clean energy, meaning both RE systems and energy efficiency projects [102]. This could be in response to the number of PURPA projects Consumers is facing (Per personal communication with MPSC staff, Consumers Energy has 2700 MW of potential contracts in the PURPA queue.). Even if regulators rule against Consumers Energy, this legal maneuver has the potential to halt any progress or implementation of PURPA projects, as it could take several months for the MPSC to successfully argue whether Consumers Energy needs capacity.
4.3. Shifting Control Diversification activity is another response by utilities to maneuver around regulations. Specifically, utilities can expand their business dealings into loosely regulated arenas [94]. Put another way, utilities can attempt to shift control away from PSCs. They can do this through implementing various forms of demand charges, over which PSCs can have little control. They also have discretion with treating minimum legislative targets as caps and with shifting to fixed charges for energy use. All of these can function to increase the costs for customers that are interested in installing DG systems [94], but they can also be detrimental if they do not accurately reflect the costs that are imposed by DG systems [42]. Instituting arbitrary net metering caps without fully factoring in DG impacts to cost recovery can lead to further issues and ultimately “under-deployment of distributed generation” [94]. Shifting control using these price signals inaccurately assigns and misrepresents the U-20471 Official Exhibits of Soulardarity Exhibit SOU-9 Page 1 of 2 U-18232 - August 28, 2018 Official Exhibits of Soulardarity Exhibit SOU-13; Source: SDE-1.9b and attachments Page 67 of 80
How renewable energy is improving grid reliability
While wind turbines and solar panels are still intermittent power sources dependent on sunny and breezy days to produce electricity, improvements in technology are improving the reliability of these growing renewable energies.
More durable construction, higher-efficiency equipment and advancements in energy storage by DTE Energy and other companies are making it easier for grid operators to reliably integrate wind farms and solar arrays into overall grid operations.
A study released last month by the American Wind Energy Association explored the positive impact renewable energy is having on maintaining consistent supply and demand. When looking at the issue of reliability, the study concluded that wind and solar are providing “grid reliability services as well as or better than conventional power plants.”
Portfolio diversity, the study stressed, is key. No power source, including power plants fueled by coal, natural gas or nuclear, operate at 100 percent all of the time. So grid operators are accustomed to fluctuation and plan for the contributions made by renewable resources with the same tools used to evaluate other power sources.
Some of the advancements in renewable energy technology include higher output wind turbine designs, new software applications that create smarter wind farms, and new solar panel design and construction. Turbine manufacturers are designing and building turbines that can function effectively both on and off shore. Improvements to design are increasing capacity; enhancements to gearboxes are minimizing breakdowns, and highly sophisticated hardware and software applications are making this equipment smarter and more connected than ever before.
U-20471 Official Exhibits of Soulardarity Exhibit SOU-9 Page 2 of 2
U-18232 - August 28, 2018 Official Exhibits of Soulardarity Exhibit SOU-13; Source: SDE-1.9b and attachments Page 68 of 80
On the solar side, demand in the U.S. is at an all-time high, with the country poised to soon become the second largest solar market in the world. One of the latest advancements in solar panel technology is the double-sided panel, formally known as bi-facial solar panels. When mounted on the ground, these panels improve efficiency and reliability because they capture light that is naturally reflected off the ground. In the winter, the modules will capture light reflected on snow-covered ground as well as light from the sun.
At DTE Energy, we are also very focused on proactive, preventative maintenance. For example, DTE recently installed condition monitoring systems on all of our turbines that provide early detection of equipment problems. By detecting problems, prior to failures, we can often address problems before they can become major issues thus avoiding large expenditures and extended downtime. We also opened an operations facility, the Huron Renewable Energy Center, close to our wind parks so technicians are nearby should an issue arise.
With generation capacity improving and advances in technology, renewable energy is now playing an important role in improving the overall grid reliability. Want to learn more? →
U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 1 of 24 Coal Blooded
Putting Profits Before People
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 2 of 24 National Association for the Advancement of Colored People 4805 Mt. Hope Drive Baltimore, MD 21215 (410) 580-5777 [email protected] www.naacp.org
Indigenous Environmental Network P.O. Box 485 Bemidji, MN 56619 (218) 751-4967 [email protected] www.ienearth.org
Little Village Environmental Justice Organization 2856 South Millard Ave Chicago, IL 60623 (773) 762.6991 [email protected] www.lvejo.org
Lead Researcher-Author: Adrian Wilson Doctoral Student, Dept. of Economics University of Massachusetts at Amherst [email protected]
Contributing Researchers-Authors: Jacqui Patterson, NAACP Kimberly Wasserman, LVEJO Amanda Starbuck and Annie Sartor, Rainforest Action Network Judy Hatcher John Fleming Katie Fink, NAACP
Edited by Monique W. Morris Layout-Design by Larissa Johnson
Much thanks to Gopal Dayaneni, Michael K. Dorsey, and Dina Kruger for the contribution of extensive feedback, to Jesse Clarke, Robert Gardner, David Millar, and Tadzio Mueller for their critical input and to Monique Harden for her guidance in developing the report.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 3 of 24 Coal-Fired Power Plants: Dirty In, Dirty Out
In 2010, there were 378 coal-fired power plants larger than 100 Megawatts (MW) in the United States (one megawatt is enough electricity to power about 800 average American homes).1819 U.S. coal power plants produced 2.1 gigawatt-hours of electricity in 2007 — which amounts to nearly 26 percent of the world’s total coal-fired electricity production, second in the world only to China (32%).20
Coal power plants, and their negative effects on public health, are highly regionally concentrated. In other words, only a handful of states are responsible for the majority of U.S. coal energy production. These states also experience disproportionately high rates of lung cancer and other respiratory diseases. Just ten states produce more than half the coal-fired electricity in the U.S. in 2005 (see figure below)—Texas (7%), Ohio (7%), Indiana (6%), Pennsylvania (6%), Illinois (5%), Kentucky (5%), West Virginia (5%), Georgia (4%), North Carolina (4%), and Missouri (4%). By contrast, the ten smallest coal energy-producing states — Connecticut, Oregon, California, South Dakota, Hawaii, Maine, Alaska, Idaho, Rhode Island, and Vermont — produced a combined total of less than 1 percent of the nation’s coal-fired electricity.21
The top ten coal-energy- producing states have an average lung cancer rate of 98.3 per 100,000 (or 19% higher than the U.S. average); while the bottom ten states have an average lung cancer rate of 77.2 per 100,000 (or nearly 7% lower than the U.S. average).22
Figure 2: Percent of Coal-Fired Electricity in the U.S, 200523
An analysis of the physical effects of the coal industry reveal that it is important to consider not only climate change, but also environmental justice, or the disproportionate location and impact of coal-fired power plant activity on low-income communities and people of color.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 4 of 24 Nearly six million Americans live within three miles of a coal power plant. As noted below, coal power plants tend to be disproportionately located in low-income communities and communities of color:24
People who live within three miles of a coal power plant have an average per capita income of $18,400, which is lower than the U.S. average of $21,587. Among those living within three miles of a coal power plant, 39 percent are people of color — a figure that is higher than the 36 percent proportion of people of color in the total U.S. population. Moreover, the coal plants that have been built within urban areas in the U.S. tend overwhelmingly to be located in communities of color.
Living in such close proximity to coal plants has serious consequences for those communities. Coal plants are single-handedly responsible for a large proportion of toxic emissions that directly poison local communities in the United States. Below is a summary of pollutants associated with coal power plants that disproportionately cause negative health effects in low- income communities and communities of color:
Sulfur dioxide, or SO2, is one of the Nitrogen oxides, collectively referred primary pollutants produced by to as NOX, comprise a key category of burning coal. In fact, coal power plants pollutants produced by coal power alone produce 74 percent of all SO2 plants, as these plants produce 18 pollution in the United percent of all NOX pollution in the 2526 2829 States. Immediately, SO2 causes U.S. Not only do NOX increase the coughing, wheezing, and nasal risk of respiratory disease in children. inflammation. Longer-term, it can They also reacts with sunlight to cause or increase the severity of produce ozone (O3), which, like SO2, asthma, which is widespread in increases the risk and severity of communities of color. African- asthma, and causes coughing, Americans are hospitalized for asthma wheezing, and shortness of breath. at three times the rate of whites, and Again, communities of color are the death rate from asthma is 172 disproportionately impacted by percent higher for African-Americans asthma in comparison with white than for whites.27 communities, and therefore are disproportionately negatively impacted by the presence of these additional pollutants.30
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 5 of 24
Fine particle pollution (PM2.5), which percent of the mercury emitted from is emitted directly by coal power industrial sources in the U.S. plants, is created when SO2 and NOX particles react in the atmosphere. This form of pollution may be among the deadliest: fine particulate pollution can cause premature death in people with heart or lung disease, as well as cause chronic bronchitis, irregular heart conditions, and aggravated asthma.31 In addition to producing 74 percent of SO2 pollution and 18 percent of NOX pollution in the U.S. (which react to produce PM2.5), coal is responsible for 85 percent of direct PM2.5 emissions from U.S. power plants.3233
Other pollutants. While this report focuses on SO2 and NOX (which in turn produce PM2.5), coal power plants release a wide variety of other toxins into the air and water — including mercury, uranium, arsenic, lead, and other heavy metals. When pregnant women are exposed to mercury, it can cause a wide variety of developmental disorders in their fetuses, including impaired brain functions, blindness, and other forms of developmental delay. The EPA estimates that power plants in general are responsible for 50 percent of the mercury, 60 percent of the arsenic, and over 50 percent of many acidic gases emitted in the U.S. in 2009 — and coal power plants comprise a large proportion of this total.34Coal plants are responsible for far more mercury pollution than the next ten largest sources of mercury pollution combined.35In 1999 (the last year for which reliable data are available), coal-fired power plants were responsible for nearly 42
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 6 of 24 The report card, above, shows the absolute worst 75 environmental justice offending plants in the country, all of which received a letter grade of an F. It is important to also examine plants that fall within an expanded definition of the word "failing" to encompass all of the plants that are causing the most harm. The expanded definition of "failing" refers to plants with a grade of a D+ or worse on their environmental justice performance scores. Like in school settings, a grade of a D+ or worse requires urgent remediation. The map below uses the expanded definition of the word "failing," D+ or below, to color codes states by the number of failing plants within the state's borders to show where the most attention is needed.
Figure 5. Map of the states with their corresponding failing power plants (plants given a grade between D+ and F), created for this report.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 7 of 24 Finding #2: The ‘12 Top Environmental Justice Offenders’ Disproportionately Affect LowIncome People of Color
Out of the 378 coal-fired power plants examined for this study, the following 12 had the worst environmental justice performance scores:
1. Crawford Gen. Station, Chicago, IL (Edison International) 2. Fisk Gen. Station, Chicago, IL (Edison International) 3. Hudson Gen. Station, Jersey City, NJ (PSEG) 4. Valley Power Plant, Milwaukee, WI (Wisconsin Energy) 5. State Line Plant, Hammond, IN (Dominion) 6. Lake Shore Plant, Cleveland, OH (FirstEnergy) 7. River Rouge Plant, River Rouge, MI (DTE Energy) 8. R. Gallagher Gen. Station, New Albany, IN (Duke Energy) 9. Cherokee Station, Commerce City, CO (Xcel Energy) 10. Bridgeport Station, Bridgeport, CT (PSEG) 11. Four Corners Plant, Niinahnízaad, NM (Arizona Public Service Co.) 12. Waukegan Gen. Station, Waukegan, IL (Edison International)
Collectively, these 12 plants produced a total of 48,582 gigawatt-hours (Gown) of electricity in 2005 — only 1.2 percent of total U.S. electricity production7273Yet, between 2007 and 2010, these “worst offending” plants emitted an annual average total of 117,743 tons of sulfur dioxide and 81,376 tons of nitrogen oxide. Consequently, from 2007-2010, of the 1437 operational units74, the 12 “worst offending plants” alone accounted for1.8% of total emissions from power plant sources, while being only.8% of the total power plant fleet75. In short, closing these 12 plants would dramatically improve the health of local communities and impacts to the climate, with barely negligible impacts on U.S. electricity production.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 8 of 24
Figure 6: Map of Plant Locations76
Approximately two million Americans live within three miles of one of these 12 plants and the average per capita income of these nearby residents is $14,626 (compared with the U.S. average of $21,587). Approximately 76 percent of these nearby residents are people of color.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 9 of 24 Finding #3: The impact of these failing plants disproportionally impacts communities from five states: Illinois, Indiana, Michigan, Wisconsin and Ohio.
As the table and accompanying map in Figure 3 above shows, five states of the Midwest – Illinois, Indiana, Michigan, Wisconsin and Ohio - are home to 32% of the failing coal-fired power plants in the U.S. In addition, 8 of the 12 worst offending coal plants are located in communities in these states.
As we will discuss in Part III, the concentration of power plants in these states creates a disproportionate impact on low income communities and communities of color. This concentration of plants also has political consequences – it leads to a disproportionate concentration of political power that makes change difficult. These themes will be discussed more below.
VOICES FROM AFFECTED COMMUNITIES
“We’re in front of a power plant owned by DTE while conducting the interview. The plant is located right in the middle of the community. About a block and a half down [from the plant], you can see actual homes where there’s a full community of people living in this environment. This is a park that we’re standing in. In the park you’ll see children playing and there’s actually the Rouge River which comes through here and we have a number of people who are fishing in this area. This is a mixed community but mostly minorities you’ll find a lot of Latinos, a lot of African-Americans in this area. And I believe less than a block or so away is an elementary school. And so, this area is very critical when it comes to environmental issues”
– Yvonne White, River Rouge Michigan
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 10 of 24
PART III: A Corporate Environmental Justice Performance Ranking of Coal Power Companies
The previous section of this report, along with the accompanying ranking of 378 U.S. coal plants in Appendix 1, focuses on the environmental justice performance of individual power plants. While the owners of these plants are listed in Appendix 1 — and while it is apparent from this listing that some companies own multiple coal power plants that perform poorly by environmental justice standards, it is critical to perform a more comprehensive ranking of corporate environmental justice performance, in which scores are assigned to each company based on the environmental justice performance of all coal-fired power plants owned by that company.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 11 of 24 As Ash and Boyce (2009) point out, there has historically existed a gap between environmental justice (EJ) and corporate environmental performance (CEP) research:
The difference between CEP and EJ studies is, in part, methodological: in CEP the unit of analysis is the source of pollution, the firm or an individual facility; in EJ the unit of analysis is the receptor, the community or households on the receiving end. The two strands of research also differ in their audiences and aims. The main audience for CEP research is socially responsible managers, investors, and consumers, with the main aim being to improve firm behavior. The main audience for EJ research is the impacted communities and responsible government officials, the main aim being to protect communities from disproportionate hazards.77
By combining EJ and CEP analysis into a study of corporate environmental justice performance (CEJP), it is possible to measure the extent to which particular company’s polluting facilities specifically impact low-income people and people of color. As Ash and Boyce argue, “regular measurement of CEJP can provide stakeholders — investors, managers, regulators, consumers, and residents of affected communities — with a report card for assessing levels and changes in performance.”78 Furthermore, it can provide environmental justice advocates with a powerful tool that enables them to shift from campaigning against an entire sector or industry and toward especially irresponsible companies within that industry.
In this report, corporate environmental justice performance ‘scores’ have been assigned to 59 leading U.S. power companies and agencies, based on the environmental justice performance of the coal-fired power plants owned by each company. (For the complete ranking of these 59 companies, see Appendix 2). This ranking is not an average of the environmental justice performance scores of each company’s coal plants; rather, it is based on the cumulative effects of all of each company’s coal plants on low-income people and people of color. (For a complete description of our methodology, see Appendix 3).
Similar to the ranking of individual plants, it is important to emphasize that this is not a ranking of the total toxicity of the coal power plants owned by a particular company — in other words, the fact that a particular company receives a grade of F does not necessarily mean that it is among the biggest coal power producers in the United States. Like the environmental justice performance ranking of individual plants, this corporate environmental justice performance ranking uses a complex algorithm (See Appendix III), combining total SO2 and NOX emissions together with demographic factors, in order to calculate each company’s score, ranking, and grade. For example, many companies with a CEJP grade of “F” own relatively few coal plants, and thus the total emissions of their plants is relatively low, but the plants that they own are sited disproportionately in densely populated areas with high proportions of low-income people and people of color; conversely, many companies with higher CEJP grades own a fairly large number of coal plants, and thus the total emissions of
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 12 of 24 their plants is relatively high, but the plants that they own are sited in sparsely populated areas with low proportions of low-income people and people of color.
It is important to acknowledge that higher grades have been assigned to some companies that grassroots activists have long been campaigning against. This evaluation by no means is meant to undermine the merit of criticisms raised by those campaigns; rather, this is specifically a corporate environmental justice performance (CEJP) ranking, which exists as a separate and equally important tool alongside overall corporate environmental performance (CEP) rankings. As Ash and Boyce argue, “the joint measurement of total impact (CEP) and disparate impacts (CEJP) provides the most robust picture of corporate environmental performance. Although correlated, neither measure adequately conveys information about the other. Both dimensions are relevant, and both should — and can — be incorporated into the assessment of corporate social responsibility.”79
Key Finding: Corporations that Receive an “F” on their CEJP Score Own a Majority of the Worst Offending Coal-Fired Plants in the U.S.
The 12 companies that received a grade of “F” as their CEJP score own 39 of the 75 failing plants — including all of the twelve worst plants. Out of the 5.9 million Americans who live within three miles of a coal-fired power plant, 3.6 million live within three miles of a coal plant owned by one of these 12 companies. Listed below are the 12 U.S. coal power companies that received failing CEJP grades. (For the complete ranking, see Appendix 2).
Company Grade 1. Edison International F 2. FirstEnergy F 3. Unisource Energy F 4. Public Service Enterprise Group F (PSEG) 5. GenOn Energy F 6. Dominion Resources F 7. Duke Energy F 8. Wisconsin Energy F 9. Cogentrix/Goldman Sachs F 10. Xcel Energy F 11. Southern Company F 12. DTE Energy F
Discussion of Select Company Performance Among the 12 worst performing companies, according to EJ standards are several that warrant a more detailed review. Below is a discussion of the policies and practices that resulted in companies being listed as “worst offenders” on environmental justice issues.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 13 of 24 APPENDIX I: Complete Plant-Level Environmental Justice Performance Ranking
Below is a listing of all 378 coal fired power plants that were ranked based for the purpose of this study.
Electricity SO NO 2 X Pop. 3-Mile % of State Parent Capacity Production Emissions Emissions 3-Mile Overall State City Plant Name Within Average Average Grade Company/Entity (MW) (MWh, av. (tons, av. (tons, av. POC Pop. Rank 3 Miles Income Income 2005-08) 2007-10) 2007-10) Edison IL Chicago International Crawford 597 2,968,888 7,276 1,978 373,690 $11,097 48.0% 83.9% 1 F Edison IL Chicago International Fisk Street 374 1,805,725 4,464 1,125 314,632 $15,076 65.3% 83.1% 2 F Public Service NJ Jersey City Electric & Gas Hudson 660 2,807,633 2,452 2,565 309,478 $21,596 80.0% 74.0% 3 F Wisconsin WI Milwaukee Energy Valley 272 1,462,832 5,999 2,407 209,421 $12,852 60.4% 66.0% 4 F State Line IN Hammond Dominion Energy 614 3,338,043 10,326 7,885 77,931 $14,408 70.6% 78.9% 5 F OH Cleveland FirstEnergy Lake Shore 256 1,117,463 3,492 1,326 103,333 $10,866 51.7% 90.6% 6 F River MI Rouge DTE Energy River Rouge 651 2,949,460 14,614 4,861 68,262 $13,037 58.8% 65.3% 7 F New IN Albany Duke Energy R Gallagher 600 3,044,369 37,604 4,332 60,333 $12,868 63.1% 60.8% 8 F Commerce CO City Xcel Energy Cherokee 801 5,208,081 6,750 9,482 61,559 $13,682 56.9% 64.4% 9 F Public Service Bridgeport CT Bridgeport Electric & Gas Station 400 2,803,500 2,044 1,404 145,133 $16,817 58.5% 67.0% 10 F Pinnacle West NM Fruitland Capital Four Corners 2270 16,378,361 11,032 40,685 488 $6,762 39.2% 94.9% 11 F Edison IL Waukegan International Waukegan 682 4,697,553 11,690 3,326 67,776 $16,197 70.1% 72.1% 12 F UniSource H. Wilson AZ Tucson Energy Sundt 173 808,407 2,040 1,428 56,609 $10,258 50.6% 74.7% 13 F
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 14 of 24 Electricity SO2 NOX Pop. 3-Mile % of State 3-Mile Parent Capacity Production Emissions Emissions Overall State City Plant Name Within Average Average POC Grade Company/Entity (MW) (MWh, av. (tons, av. (tons, av. Rank 3 Miles Income Income Pop. 2005-08) 2007-10) 2007-10) MA Somerset Dominion Brayton Point 1125 8,321,916 28,802 5,016 77,676 $16,461 63.4% 9.4% 14 F VA Chesapeake Dominion Chesapeake 650 3,934,895 18,161 4,583 53,955 $16,751 69.9% 43.3% 15 F TN Memphis U.S. Government Allen 990 5,743,971 12,156 6,434 2,589 $9,412 48.5% 99.2% 16 F City of Omaha, NE Omaha NE North Omaha 645 3,728,722 13,358 6,272 43,133 $13,858 70.7% 56.7% 17 F Tri-State Generation & Transmission Association NM Prewitt (cooperative) Escalante 257 1,859,191 1,211 3,332 372 $6,701 38.8% 90.2% 18 F CO Denver Xcel Energy Arapahoe 160 1,010,656 2,556 2,608 137,267 $21,990 91.4% 41.6% 19 F PA Birdsboro GenOn Energy Titus 225 1,352,967 11,204 1,860 82,086 $16,699 80.0% 39.0% 20 F Edison Joliet 9/Joliet IL Joliet International 29 1680 7,688,413 18,407 6,813 43,392 $18,810 81.4% 41.7% 21 F Public Service NJ Hamilton Electric & Gas Mercer 653 3,116,778 10,796 1,000 81,676 $19,365 71.7% 42.0% 22 F City of Kansas KS Kansas City City, KS Quindaro 239 1,192,071 4,003 3,424 42,539 $15,561 75.9% 69.9% 23 F City of Lansing, MI Lansing MI Eckert 375 1,766,547 5,212 2,011 96,255 $17,959 81.0% 39.2% 24 F PA Eddystone Exelon Eddystone 707 3,033,299 5,322 4,124 93,912 $19,181 91.9% 26.2% 25 F Colorado City of Colorado CO Springs Springs, CO Martin Drake 257 2,047,603 7,758 4,192 78,101 $20,905 86.9% 26.6% 26 F MI Muskegon CMS Energy B C Cobb 313 2,182,116 10,753 2,771 43,990 $15,161 68.4% 37.6% 27 F Goldman Sachs Spruance VA Richmond (Cogentrix) Genco 230 1,531,379 5,776 4,045 31,903 $17,627 73.5% 59.4% 28 F SC Pineville Santee Cooper Cross 1738 11,513,871 8,563 5,965 1,068 $10,626 56.5% 76.3% 29 F SC Beech Island SCANA Urquhart 100 717,757 5,588 790 7,464 $12,623 67.2% 77.2% 30 F Goldman Sachs Edgecombe NC Battleboro (Cogentrix) Genco 115 902,847 4,864 2,964 4,370 $11,735 57.8% 67.2% 31 F WI Green Bay Integrys Pulliam 350 2,494,016 7,198 5,210 52,071 $16,275 76.5% 22.5% 32 F OH Willoughby FirstEnergy Eastlake 1257 8,810,886 52,315 8,478 39,044 $20,947 99.7% 3.3% 33 F
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 15 of 24 Electricity SO2 NOX Pop. 3-Mile % of State 3-Mile Parent Capacity Production Emissions Emissions Overall State City Plant Name Within Average Average POC Grade Company/Entity (MW) (MWh, av. (tons, av. (tons, av. Rank 3 Miles Income Income Pop. 2005-08) 2007-10) 2007-10) Goldman Sachs FL Indiantown (Cogentrix) Indiantown 395 2,322,170 12,682 8,873 3,403 $13,107 60.8% 68.2% 34 F CO Pueblo Xcel Energy Comanche 779 4,944,487 7,150 5,139 10,355 $14,584 60.6% 57.7% 35 F City of Lakeland, FL Lakeland FL C D McIntosh Jr 364 2,699,208 5,722 3,518 29,782 $15,386 71.4% 38.7% 36 F Southern AL Gadsden Company Gadsden 138 429,828 7,257 1,577 24,955 $13,600 74.8% 49.9% 37 F SC Eastover SCANA Wateree 772 4,957,624 28,160 3,716 367 $12,422 66.1% 82.8% 38 F TX Amarillo Xcel Energy Harrington 1080 8,040,270 20,197 8,525 4,724 $9,134 46.6% 46.3% 39 F W.H. NC Lumberton Progress Energy Weatherspoon 166 847,634 6,600 2,575 10,450 $11,867 58.4% 50.3% 40 F NY Tonawanda NRG Energy C R Huntley 436 2,752,167 7,381 1,939 55,349 $17,306 74.0% 12.0% 41 F Michigan IN City NiSource Michigan City 540 2,547,056 10,941 2,881 29,568 $16,523 81.0% 29.7% 42 F Edison IL Pekin International Powerton 1786 9,265,378 21,694 21,673 16,131 $16,614 71.9% 8.2% 43 F IL Baldwin Dynegy Baldwin 1894 13,720,906 24,716 4,452 4,121 $13,419 58.1% 51.7% 44 F NM Waterflow PNM Resources San Juan 1848 12,826,273 8,928 20,093 937 $11,982 69.4% 74.9% 45 F City of Orlando, FL Orlando FL Stanton 929 6,636,861 5,392 7,706 6,581 $14,035 65.1% 48.1% 46 F City of IL Springfield Springfield, IL Dallman/Lakeside 463 3,123,218 8,739 3,531 28,821 $19,288 83.5% 29.1% 47 F Goldman Sachs Cogentrix VA Portsmouth (Cogentrix) Portsmouth 115 710,463 1,313 676 53,186 $19,424 81.0% 40.4% 48 F NY Dunkirk NRG Energy Dunkirk 627 3,628,244 9,057 2,656 16,916 $14,578 62.3% 23.2% 49 F City of Kansas KS Kansas City City, KS Nearman Creek 261 1,625,474 6,344 3,832 25,710 $19,661 95.9% 43.7% 50 F Goldman Sachs NJ Swedesboro (Cogentrix) Logan 242 1,642,435 12,145 1,019 17,446 $16,924 62.7% 27.8% 51 F Westmoreland NC Weldon Coal Company Roanoke Valley 240 1,600,880 8,707 1,620 15,693 $15,339 75.5% 42.1% 52 F IN Indianapolis AES Harding Street 698 3,863,590 25,259 3,525 35,209 $17,092 83.8% 8.3% 53 F VA Alexandria GenOn Energy Potomac River 514 1,304,808 1,988 1,515 138,380 $34,352 143.3% 54.9% 54 F
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 16 of 24 Electricity SO2 NOX Pop. 3-Mile % of State 3-Mile Parent Capacity Production Emissions Emissions Overall State City Plant Name Within Average Average POC Grade Company/Entity (MW) (MWh, av. (tons, av. (tons, av. Rank 3 Miles Income Income Pop. 2005-08) 2007-10) 2007-10) PA Masontown FirstEnergy Hatfields Ferry 1728 10,405,940 99,918 22,912 8,398 $15,126 72.4% 5.6% 55 F IL Alton Dynegy Wood River 500 3,244,354 8,047 2,561 29,889 $16,381 70.9% 12.4% 56 F HI Kapolei AES AES Hawaii 203 1,547,814 23,971 7,193 2,497 $20,931 97.2% 87.0% 57 F LA Lena Cleco Rodemacher 558 3,419,394 9,340 4,222 1,237 $11,154 66.0% 66.7% 58 F Southern AL Forkland Company Greene County 568 3,873,062 30,007 5,213 480 $13,821 76.0% 78.8% 59 F SC Goose Creek SCANA Williams 633 4,605,303 15,821 3,698 4,496 $9,653 51.4% 32.6% 60 F Trenton MI Trenton DTE Energy Channel 776 4,226,915 26,277 5,318 43,301 $29,078 131.2% 5.9% 61 F Great Plains MO Kansas City Energy Hawthorn 594 3,892,129 1,902 1,488 31,335 $14,647 73.5% 32.3% 62 F Goldman Sachs James River VA Hopewell (Cogentrix) Cogeneration 115 642,619 2,448 1,728 22,623 $17,981 75.0% 37.4% 63 F WI Sheboygan Alliant Energy Edgewater 770 4,769,205 14,929 3,857 29,814 $18,812 88.4% 15.7% 64 F MI Monroe DTE Energy Monroe 3280 20,279,954 94,568 27,098 7,999 $19,202 86.6% 15.8% 65 F PA Springdale GenOn Energy Cheswick 637 2,924,260 27,161 3,521 35,690 $19,266 92.3% 8.2% 66 F Ohio Valley Electric Corp. (AEP [43.4%], FirstEnergy [20.5%], Buckeye [12.5%], and four other IN Madison corporations) Clifty Creek 1303 9,415,079 63,807 14,535 14,216 $17,546 86.0% 5.6% 67 F Edison IL Romeoville International Will County 1269 6,045,575 15,332 6,355 27,062 $20,997 90.9% 15.3% 68 F NY Johnson City AES AES Westover 119 799,783 4,183 513 62,201 $18,747 80.2% 15.6% 69 F Constellation Brandon MD Curtis Bay Energy Shores 1370 8,833,833 29,011 7,921 25,441 $23,050 90.0% 7.8% 70 F Goldman Sachs Chambers NJ Carneys Point (Cogentrix) (Carneys Point) 285 1,941,304 15,388 1,231 14,158 $18,900 70.0% 28.0% 71 F Southern Jack GA Smyrna Company McDonough 598 3,870,476 21,473 3,435 43,319 $32,515 153.7% 54.1% 72 F
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 17 of 24 APPENDIX II:
Complete Corporate Environmental Justice Performance Ranking
2010 2010 Coal- Percent of Total Pop. Revenues Profits # Fired State Company Utilities Owned Total SO2 Total NOX Within 3 Percent POC Rank Grade (millions (millions Plants Capacity Average Miles USD) USD) (MW) Income Edison International Southern California Edison (CA) 12,409 1,251 7 8,400 188,247 54,836 848,059 59.9% 76.3% 1 F FirstEnergy Allegheny Power (WV, VA, MD, PA), Ohio Edison (OH), The Illuminating12,911 Co. (OH),784 Toledo Edison 16 15,517 (OH), Penn Power 396,094 (PA), Penelec 111,914 (PA), Met-Ed (PA), 252,818 Jersey Central 73.4% Power & Light 40.3%(NJ) (+ 20.5% of OVEC)2 F UniSource Energy UniSource Energy Services (AZ) 1,341 112 2 1,023 8,681 7,906 56,751 50.6% 74.6% 3 F Public Service Enterprise Group Public Service Electric & Gas (NJ) 11,793 1,564 3 1,713 15,292 4,969 536,287 72.9% 67.2% 4 F GenOn Energy Non-utility; power producer/distributor in TX, PA, NJ, GA, CA, MD,2,270 MA, NY, VA -50 15 11,216 430,987 74,484 354,959 109.7% 32.7% 5 F Dominion Resources Dominion (NC, VA) 15,197 2,808 11 8,670 154,375 60,762 333,611 81.7% 32.4% 6 F Duke Energy Duke Energy (NC, SC, IN, OH, KY) 13,972 1,318 17 18,443 388,135 99,925 136,249 80.1% 32.9% 7 F Wisconsin Energy We Energies (WI, MI) 4,203 457 4 3,259 31,491 16,071 258,472 67.7% 55.0% 8 F Cogentrix/Goldman Sachs Non-utility; power producer/distributor in FL, NJ, NC, PA,N/A VA N/A 9 1,903 66,090 27,005 190,227 78.7% 34.7% 9 F Xcel Energy Xcel Energy (CO, MN, WI, TX, NM, MI, ND, SD) 10,234 752 11 8,186 102,905 72,299 339,651 91.5% 36.3% 10 F Southern Company Alabama Power (AL), Georgia Power (GA), Gulf Power (FL), Mississippi17,374 Power 1,975 (MS) 20 26,478 762,083 169,196 148,718 114.2% 34.2% 11 F DTE Energy Detroit Edison (MI) 8,557 630 6 7,770 196,955 57,260 132,408 88.8% 36.8% 12 F Cleco Cleco Power (LA) 1,148 255 2 1,279 23,951 9,216 1,649 69.8% 62.6% 13 D- Omaha Public Power District (City ofOmaha Omaha, Public NE) Power District (NE) *986 *40 2 1,297 31,249 16,058 44,836 71.3% 54.8% 14 D- Pinnacle West Capital Arizona Public Service Co. (AZ) 3,181 350 2 3,399 24,631 51,764 1,564 56.7% 48.4% 15 D- AES Indianapolis Power & Light Co. (IN) 16,647 9 12 5,278 175,079 48,917 156,690 80.8% 12.6% 16 D- Great Plains Energy Kansas City Power & Light (KS, MO) 2,256 210 5 3,986 55,548 30,135 34,850 75.2% 29.4% 17 D PNM Resources PNM (NM), TNMP (TX), First Choice Power (TX) 1,674 -45 2 2,197 13,710 21,760 1,265 73.6% 61.1% 18 D PPL PPL (PA), Louisville Gas & Electric Co. (KY), Kentucky Utilities Co.8,521 (KY, VA) 938 10 11,711 263,559 88,675 94,162 90.5% 12.9% 19 D NRG Energy Reliant Energy (TX) 8,849 468 6 8,263 142,953 39,209 94,824 82.6% 21.0% 20 D CMS Energy Consumers Energy (MI) 6,432 324 4 3,101 73,186 19,815 66,155 78.5% 27.2% 21 D+ American Electric Power AEP Ohio (OH, WV), AEP Texas (TX), Appalachian Power (WV, VA,14,427 TN), Indiana 1,211 Michigan Power19 26,596 (IN, MI), Kentucky 601,886 Power (KY), 185,781 Public Service Co. 61,329 of Oklahoma (OK), 93.8% Southwestern 4.9% Electric Power Co.22 (TX, AR,D+ LA) (+ 43.4% of OVEC) NV Energy Sierra Pacific Power (NV), Nevada Power (NV) 3,280 227 2 1,204 8,181 11,518 505 67.8% 48.3% 23 D+ Santee Cooper Santee Cooper (SC); owned by State of SC *1895 *97 4 3,507 36,371 13,927 20,455 89.3% 39.8% 24 D+ Tennessee Valley Authority Non-utility; power producer/distributor in TN, AL, MS, KY, GA, *10874NC, VA; owned *972 by U.S. Gov’t11 17,407 282,099 123,140 42,967 89.8% 11.6% 25 C- Alliant Energy Alliant Energy (IA, MN, WI) 3,416 288 9 3,875 90,547 24,230 105,331 90.8% 13.7% 26 C- Progress Energy Progress Energy (NC, SC, FL) 10,190 856 9 7,927 175,538 49,909 46,331 91.7% 24.3% 27 C- NiSource NIPSCO (IN) 6,422 292 3 3,087 52,227 22,485 34,261 85.9% 26.5% 28 C- CPS Energy (City of San Antonio, TX)CPS Energy (TX) *2115 *79 1 1,498 23,265 7,103 2,994 90.2% 42.6% 29 C Dynegy Non-utility; power producer/distributor in CA, NV, IL, TN, PA, NY,2,323 ME -234 5 3,575 55,207 11,980 57,086 80.2% 16.7% 30 C Salt River Project (State of Arizona) Salt River Project (AZ); owned by State of AZ *2702 *371 2 3,231 18,424 44,709 2,864 87.1% 37.9% 31 C Integrys Integrys Energy Services (CT, DE, DC, IL, ME, MD, MA, MI, NH, NJ,5,203 NY, OH, PA, RI)221 3 1,437 17,076 9,852 62,420 81.7% 19.3% 32 C Constellation Energy Baltimore Gas & Electric (MD) 14,340 -983 5 2,491 73,166 18,502 69,092 88.9% 9.1% 33 C+ Tri-State Generation Cooperative Non-utility; owned by 44 electric cooperatives in CO, NE, NM, WY*1212 *77 3 1,710 6,110 20,705 4,824 70.5% 17.7% 34 C+ Grand River Dam Authority (State of GrandOklahoma) River Dam Authority (OK) *398 *63 1 1,010 17,720 14,229 2,277 79.5% 26.2% 35 C+ Ameren Ameren Illinois (IL), AmerenUE (MO) 7,449 139 11 10,718 239,341 49,357 59,463 97.8% 2.7% 36 C+ MidAmerican Energy (PacifiCorp) MidAmerican Energy (IA, IL, SD), Pacific Power (OR, WA, CA), Rocky*11127 Mountain *1310 Power (UT,11 WY, 11,278ID) 142,355 108,972 51,058 110.2% 15.7% 37 INC SCANA South Carolina Electric & Gas (SC) 4,601 376 6 2,706 75,915 15,920 37,665 115.2% 32.1% 38 INC Energy Future Holdings (Luminant) TXU Energy (TX) *8235 *2812 4 6,501 226,643 38,498 2,940 95.4% 26.2% 39 INC Associated Electric Cooperative Non-utility; power producer/distributor in MO, IA, OK *1055 *46 2 2,335 30,698 20,384 732 76.7% 21.4% 40 INC Ohio Valley Electric Corporation Non-utility; power producer/distributor in IN, OH 0 0 2 2,390 134,589 23,432 17,901 86.0% 5.0% 41 INC TransAlta Non-utility; power producer/distributor in Canada 2,887 224 1 1,460 2,648 11,179 2,352 73.5% 13.9% 42 INC DPL Dayton Power & Light Co. (OH) 1,831 290 3 3,516 60,884 22,808 29,592 91.7% 5.3% 43 INC Otter Tail Power Otter Tail Power (MN, ND, SD) 1,119 -1.3 3 1,035 27,549 25,341 17,139 84.3% 3.4% 44 INC Hoosier Energy Rural Electric CooperativeNon-utility; owned by 18 electric cooperatives in IN, IL *653 *32 2 1,313 36,072 8,816 4,612 79.7% 1.0% 45 INC ALLETE Minnesota Power (MN), Superior Water Light & Power (WI) 907 75 3 1,441 21,265 14,940 4,156 81.0% 2.0% 46 INC Entergy Entergy (AR, LA, MS, TX) 11,488 1,250 3 4,015 76,184 34,807 10,734 99.3% 14.0% 47 INC Westar Energy Westar Energy (KS) 2,056 204 3 2,958 37,616 27,354 25,777 106.7% 15.7% 48 INC Seminole Electric Cooperative Non-utility; owned by 10 electric cooperatives in FL *1459 *60 1 1,429 19,289 10,556 1,514 85.9% 9.0% 49 INC East Kentucky Power Cooperative Non-utility; owned by 16 electric cooperatives in KY *827 *33 3 1,839 46,298 10,254 9,813 90.2% 3.1% 50 INC Big Rivers Electric Corporation Non-utility; owned by 3 electric cooperatives in KY *527 *4 4 1,854 20,270 15,933 12,599 94.7% 2.6% 51 INC OGE Energy Oklahoma Gas & Electric (OK, AR) 3,717 295 2 2,854 43,299 26,452 7,781 118.0% 25.9% 52 INC TECO Energy Tampa Electric (FL) 3,488 239 2 2,149 10,621 14,847 8,935 120.5% 14.9% 53 INC Basin Electric Power Cooperative Non-utility; power producer/distributor in MT, ND, SD, MN, IA, WY,*1541 NE, CO, NM*9 3 3,236 70,788 40,787 985 93.7% 5.6% 54 INC Lower Colorado River Authority (StateNon-utility; of Texas) power producer/distributor in TX *1244 *111 1 1,690 29,416 6,592 541 91.2% 10.3% 55 INC Intermountain Power Agency Non-utility n/a n/a 1 1,640 5,242 26,728 104 86.1% 5.8% 56 INC JEA (City of Jacksonville, FL) JEA (FL) *1910 *126 1 1,358 10,098 13,855 2,713 96.5% 5.8% 57 INC Nebraska Public Power District (StateNebraska of Nebraska) Public Power District (NE) *925 *61 2 1,592 35,044 21,707 653 100.8% 4.2% 58 INC Great River Energy Non-utility; owned by 28 electric cooperatives in MN *847 *27 2 1,400 27,112 11,678 355 100.9% 2.2% 59 INC Page | 85
U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 18 of 24 APPENDIX III: Methodology
Plant-Level Environmental Justice Performance Ranking Our initial data source for the list of coal-fired power plants that we compared in this ranking was the U.S. Energy Information Administration (EIA)’s 2008 “Existing Electric Generating Units in the United States” database.142 We first filtered out all generating units for which the primary energy source was listed as “Anthracite/Bituminous Coal,” “Lignite Coal,” “Subbituminous Coal,” “Waste/Other Coal,” and “Coal Synfuel,” leaving us with 601 coal-fired or partially coal-fired power plants (containing a total of 1,458 coal-fired generating units).
For the purposes of this ranking, we included the 378 currently-operating coal-fired power plants from this database that have a capacity greater than 100 megawatts (MW). We cut from this ranking several plants which, as of July 1, 2011, have been fully decommissioned; have been converted to fuel stocks other than coal; or were fully non-operational between 2007 and 2010 (thus leaving us without relevant SO2 and NOX emissions data for the relevant time period).
Data Sets We then compiled the five relevant data sets for each of these 378 coal-fired power plants:
SO2 and NOX emissions For 350 out of the 378 plants in this ranking, the data listed for each plant’s SO2 and NOX emissions is an average of that plant’s annual emissions between 2007 and 2010; our data source was the U.S. Environmental Protection Agency (EPA)’s Clean Air Markets Program database of unit-level emissions, collected under the Agency’s Acid Rain Program. These data are collected on a quarterly basis as part of EPA’s emissions trading programs, and are based on self-reporting.143 This data source, unlike others at the EPA, has data more recent than 2007, allowing us to account for the fact that many of these plants added SO2 emissions controls between 2007 and 2010 (thus reducing those plants’ emissions, and improving their scores).
For the 28 plants for which data was not reported under the Clean Air Markets Program, the data listed for each plant’s SO2 and NOX emissions is from 2007 only, from the EPA’s Emissions & Generation Resource Integrated Database. This data source “integrates many different federal data sources on power plants and power companies, from three different federal agencies: EPA, the Energy
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 19 of 24 144 Information Administration (EIA), and the Federal Energy Regulatory Commission (FERC).” (In Appendix 1, the SO2 and NOX data for these 28 plants is italicized.)
Population within 3 miles For the three categories of demographic data — population within 3 miles, per capita income of population within 3 miles, and percentage people of color of population within 3 miles — data was accessed using Free Demographics, an online geographic information tool designed by Alteryx LLC, a geographic business intelligence company.145Free Demographics uses census block-level data from the 2000 U.S. Census; census block-level data is the smallest scale on which demographic data is collected by the U.S. Census, with the average census block containing roughly 600-3,000 residents in 2000.146
Prior to the writing of this report, precise geographic coordinates for each plant had already been researched by the lead author, in his capacity as a researcher for CoalSwarm/Center for Media and Democracy. Coal-fired power plants listed on the EIA’s “Existing Electric Generating Units” database were first plugged into the EPA’s Envirofacts Air Facility System search engine to obtain geographic coordinates and street addresses for each plant. However, many of these geographic coordinates (which have been the basis for most previous studies on coal power plant pollution) were inaccurate, with disparities from the actual plant’s pollution source stack ranging from several hundred feet to, in some cases, several hundred miles. We then mapped the EPA’s geographic locations using Google Earth, and used a combination of cross-checking addresses, accessing company information, and general internet searching and phone calls to secure the precise geographic coordinates for each plant’s pollution source stack; these coordinates were then plugged into the FreeDemographics, in order to ensure that the geographic data in this report would be as accurate as possible.
The three-mile range that we used in calculating demographic data was selected based on Anderton et al’s (1994) definition of “surrounding area” as “any tract for which at least 50% of the surrounding area fell within a 2.5 mile radius.”147 (Distances used for demographic calculations by the FreeDemographic tool must be integer values; thus, we rounded up to three miles.) Thus, the three-mile range that we chose is based on precedent, but is nonetheless, as Anderton et al (1994) point out, “somewhat arbitrary,” as are all geographical radii used in demographic calculations of environmental justice; as Boyce (2003) puts it, “there is no obvious a priori basis for judging the ‘right’ spatial unit of analysis — how close people must live to an environmental hazard for it to be judged relevant to their well-being, and hence relevant to analyses of environmental justice.”148
We were also concerned that demographic data in sparsely populated areas would not be representative if the population sample was too low. For this reason, in cases where fewer than 1,000 people lived within 3 miles of the plant, we increased the radius (by 2
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 20 of 24 miles at a time) until the population living within the modified radius was greater than 1,000, and used the data on per capita income and percentage people of color from this modified radius; for the population within 3 miles figure, we then divided the modified population by the ratio between the areas of the modified radius and the 3-mile radius:
X 2 POP MOD = POP XMILES 32
Average per capita income of population living within 3 miles, as a percentage of state average per capita income In order to obtain data on average per capita income of population living within 3 miles, we used the FreeDemographics tool with CoalSwarm-calculated geographic coordinates, as described above. However, we decided to use “within-region” data for average income, as described by Ash & Boyce (2009):
Alternative benchmarks for assessing disproportionality include the share of the group in the population of the specific regions — for example, states or metropolitan areas — in which the firm’s facilities are located…. A region- specific benchmark would be consistent with the view that the facility siting decisions of firms are often “within-region” choices, constrained by the desire to locate within a certain part of the country for ease of access to input or output markets.149
Following this logic, we divided each plant’s average per capita income of population living within 3 miles by average per capita income of the state within which that plant was sited, in order to obtain the average per capita income of population living within 3 miles as a percentage of state average per capita income; 1999 state per capita income data was obtained from the U.S. Census Bureau.150
Percentage people of color of population living within 3 miles In order to obtain data on percentage people of color of population living within 3 miles, we used the FreeDemographics tool with CoalSwarm-calculated geographic coordinates, as described above. The FreeDemographics tool lists “race” and “Hispanic origin” separately, as does the U.S. Census; it does not, however, include the “White Non-Hispanic” category, as the census does. Following Ash & Boyce (2009), we defined “percentage people of color” as the sum of the percentages of people who identified as “American Indian and Alaska Native Alone,” “Asian Alone,” “Black Alone,” “Native Hawaiian and Other Pacific Islander Alone,” and “Hispanic or Latino” in the census.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 21 of 24 In this case, we did not adjust race data on a “within-region” basis, as race & ethnicity — unlike income — shows much greater and smaller-scale geographic variability, making use of state- or MSA-level data less useful in regionally contextualizing race & ethnicity data.
Calculating the Plant-Level Environmental Justice Performance Ranking and Grade The plant-level environmental justice performance ranking was based on two scores: an exposure score and a demographic score.
The exposure score (EXP) was calculated by multiplying the plant’s SO2 emissions in tons (SO2), its NOX emissions in tons (NOX), and the cube of the population living within 3 miles of the plant (POP):
3 EXP SO 2 NO X POP
The demographic score (DEM) was calculated by multiplying the percentage of people of color living within 3 miles (POC) by the average per capita income of population living within 3 miles (INC3) as a percentage of state average per capita income (INCSTATE):
INC3 DEM = POC INCSTATE
We then ranked the exposure scores (EXP) of all 378 plants to generate the exposure ranking (EXPR), and ranked the demographic scores (DEM) of all 378 plants to generate the demographic ranking (DEMR).
Finally, each plant’s overall score (SCORE) was generated by multiplying the exposure ranking (EXPR) by the demographic ranking (DEMR):
SCORE =EXPR DEMR
The 378 plants were then ranked by this final score in order to generate each plant’s overall environmental justice performance ranking.
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 22 of 24
Environmental justice performance “grades” were then assigned to each plant by dividing the 378 plants into 15 roughly equal-size grade groups (F, D-, D, D+, etc.)All grades below D- were listed simply as F, rather than creating separate grades for F+ and F-; thus, 75 plants earned a grade of F. The grades in the ‘A’ and ‘B’ ranges were not used because we believe that any plant that is causing harm by polluting any person should not receive a positive grade. Instead these plants received an “INC” for Incomplete, as the aim is to ensure that no plant is polluting communities.
Corporate Environmental Justice Performance Ranking Prior to the writing of this report, ultimate parent company/entity ownership of all 601 coal-fired or partially coal-fired power plants in the U.S. had already been researched by CoalSwarm (primarily by the lead author).151 In a similar process to the Political Economy Research Institute’s Corporate Toxics Information Project, the parent company of each of the plant owners for all coal-fired or partially coal-fired power plants listed in the EIA’s “Existing Electric Generating Units in the United States” was exhaustively researched.152 This research was conducted using a combination of sources, including the EPA’s TRI reports, the Bloomberg Terminal, the BusinessWeek Company Insight Center, Hoover’s, reports to the Securities and Exchange Commission, annual reports, company websites, and telephone calls. In instances in which ownership of a plant was shared between multiple parent companies, the company with the controlling ownership share was listed as the sole parent company.
This information was updated in March 2010, and again in June 2011, to account for mergers, acquisitions, transfers of facilities to new owners, and addition of new facilities. The “Parent Company” column in this ranking is based on this extensive research.153
The 59 parent companies or entities which owned coal-fired power plants with a total of 1,000 Megawatts or more of generating capacity were included in the corporate environmental justice performance ranking; the 49 parent companies or entities owning less than 1,000 Megawatts of coal-fired generating capacity were excluded.
Data Sets We then compiled the five relevant data sets for each of these 59 parent companies:
SO2 and NOX emissions For each of these two figures (SO2COM and NOXCOM), we totaled SO2 and NOX emissions (separately, of course) for all plants owned by each parent company or entity, e.g.:
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 23 of 24
SO2COM SO2
Population within 3 miles For this figure (POPCOM), we totaled the population living within 3 miles for all plants owned by each parent company or entity:
POPCOM POP
Average per capita income of population living within 3 miles, as a percentage of state average per capita income For this figure (INCCOM), we used the following formula:
INC3 POP
INCSTATE INCCOM POPCOM
Percentage people of color of population living within 3 miles For this figure (POCCOM), we used the following formula:
POC POP POC COM POP COM
Calculating the Corporate Environmental Justice Performance Ranking and Grade The procedure for calculating the corporate environmental justice performance was identical to that for calculating the plant-level environmental justice performance ranking. We will reiterate that procedure below for the sake of clarity.
The corporate environmental justice performance ranking was based on two scores: an exposure score and a demographic score.
The exposure score (EXPCOM) was calculated by multiplying the plant’s SO2 emissions in tons (SO2COM), its NOX emissions in tons (NOXCOM), and the cube of the population living within 3 miles of the plant (POPCOM):
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-10 Page 24 of 24
3 EXPCOM SO2COM NOXCOM POPCOM
The demographic score (DEMCOM) was calculated by multiplying the percentage of people of color living within 3 miles (POCCOM) by the average per capita income of population living within 3 miles as a percentage of state average per capita income (INCCOM):
DEMCOM POCCOM INCCOM
We then ranked the exposure scores (EXPCOM) of all 59 ranked companies to generate the exposure ranking (EXPRCOM), and ranked the demographic scores (DEMCOM) of all 59 ranked companies to generate the demographic ranking (DEMRCOM).
Finally, each company’s overall score (SCORECOM) was generated by multiplying the exposure ranking (EXPRCOM) by the demographic ranking (DEMRCOM):
SCORECOM EXPRCOM DEMRCOM
The 59 companies were then ranked by this score in order to generate each company’s overall corporate environmental justice performance ranking.
Corporate environmental justice performance “grades” were then assigned to each company by dividing the 59 companies into 15 equal-size grade groups (F, D-, D, etc.), . Again, all grades below D- were listed simply as F, rather than creating separate grades for F+ and F- . As with the plant scoring, the grades in the ‘A’ and ‘B’ ranges were not used because any company that is causing harm by polluting any person should not receive a positive grade. Instead these companies received an “INC” for Incomplete, as there is still work to do by all to ensure that no one is breathing polluted air.
APPENDIX IV: Review of the Policy Landscape
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-11 Page 1 of 2 Case No.: U-20471 DTE Electric Company Respondent: Y. Zhou U-20162 SDE-1.11-01 2014 Study Page: 1 of 59 Proprietary and Confidential: For DTE Energy Internal Use Only
MPSC Case No. U-18352 Attachment: MECDE-1.2 2014 Respondent: T. L. Schroeder Page: 1 of 59
Renewable Energy Programs Exploration Final Report June 19, 2014
5455 Corporate Drive, Suite 120 Troy, MI 48098 (248) 952-1600 www.consumerinsightsinc.com U-20471 Official Exhibits of Soulardarity Exhibit SOU-11 Page 2 of 2 Case No.: U-20471 DTE Electric Company Respondent: Y. Zhou U-20162 SDE-1.11-01 2014 Study Page: 35 of 59 Proprietary and Confidential: For DTE Energy Internal Use Only
MPSC Case No. U-18352 Attachment: MECDE-1.2 2014 Even with a higher initial investment, Idea S2 was intriguing to many respondents.Respondent: T. L. Schroeder Page: 35 of 59
• For customers who were highly opposed to an ongoing premium paid to DTE Energy for adding renewable energy sources, S2 provided a way to recover an initial investment in green energy over time. • Customers were surprisingly open to forgoing a more profitable return via other investments in order to capture the environmental benefit of the solar energy. • There was also an element of “bragging rights” associated with S2: • An installation within the county means there would be a physical reminder of the customer’s investment. • Several customers talked about either showing off “their” panel to grandkids or purchasing a panel as an interesting gift for someone else. • The primary concern with this concept was the actual size of the initial investment; several customers suggested that if they could spread the $475 over several months, they would be more likely to sign up. • Multiple customers were also concerned about the impact of moving, and wanted to make sure they would remain in the program even if they moved to a different county within the DTE service area. U-20471 Official Exhibits of Soulardarity Exhibit SOU-12 Page 1 of 18 !
Advantage Local Why Local Energy Ownership Matters
John Farrell September 2014 U-20471 Official Exhibits of Soulardarity Exhibit SOU-12 Page 2 of 18 ! ! Executive Summary
Executive Summary Why does ownership of renewable energy matter? Because the number of jobs and economic returns for communities are substantially higher when electricity generation from wind and sun can be captured by local hands.
Local Ownership Means More Jobs & More Local Economic Impact
Job Impact of Local Ownership Economic Impact of Local Ownership
1x 1x
1.1x 1.5x
2.8x 3.4x
Source: National Renewable Energy Laboratory Absentee-owned Locally-owned (low) Locally-owned (high)
This economic self-interest motivates rapid expansion of renewable energy and builds political support for a low-carbon, more local and economically rewarding energy system. This report serves as a resource, especially for communities seeking independence from big out-of-state projects like high voltage transmission lines.
Local Ownership Dramatically Improves Attitudes Toward Wind Power
Not local
+77% net approval
Local ownership
Source: Fabian David Musall and Onno Kulk
0 25 50 75 100
very negative negative neutral positive very positive
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Unfortunately, there are at least five substantial barriers to local ownership in the U.S. energy system: • Tradition: in its 100-year history, the U.S. electricity grid has primarily been controlled by centralized, vertically integrated utilities that are reluctant to lose market share. • Capital: collectively raising capital for a locally owned renewable energy project tends to run afoul of Securities and Exchange Commission rules for investment that are unduly onerous for the size and scale of community-based projects. • Cash Flow: revenue sources for renewable energy projects may come from four or more sources, complicating the challenge of making finance payments and recovering the initial investment. • Legal: the most logical legal structures for local ownership, e.g. nonprofits or cooperatives, are often ineligible for federal tax incentives. • Utilities: opposed to the erosion of their control of the technical and economic elements of the electricity system, utilities raise policy and technical barriers to the development of locally owned energy projects.
Fortunately, there are policy solutions to these barriers, including: • Incentives for locally owned projects, rewarding their higher economic returns to state and community. • Community renewable energy programs (like Colorado’s Solar Gardens) that codify and simplify the organization of locally owned projects. • Virtual net metering rules that allow the sharing of electricity output among many customers within a community. • Crowd financing rules that remove financial and legal barriers to collective efforts to raise capital. • Feed-in tariffs or CLEAN contracts that dramatically simplify a project’s cash flow. • Abandoning the tax code and switching renewable energy incentives to a cash basis.
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! Acknowledgments
Acknowledgments Thank you to Chris Mitchell for his help in setting up the Energy Self-Reliant States blog, from which much of this material originates. Also thanks to David Morris for his thoughtful comments and review, and Jake Rounds, for reviving this report.
Recent ILSR Publications All Hands On Deck: MN Local Government Models for Expanding Fiber Internet Access By Christopher Mitchell and Lisa Gonzalez, September 2014
Growing Local Fertility: A Guide to Community Composting Energy Self-Reliant States By Highfields Center for Composting an ongoing web resource and ILSR, July 2014 energyselfreliantstates.org
State of Composting in the US: What, Why, Where & How By Brenda Platt, Nora Goldstein and Craig Coker, July 2014 Since 1974, the Institute for Local Self- Reliance (ILSR) has worked with citizen Minnesota’s Value of Solar groups, governments and private By John Farrell, April 2014 businesses to extract the maximum value from local resources. Energy Storage: The Next Charge for Distributed Energy 2014 by the Institute for Local By John Farrell, March 2014 Self-Reliance. Permission is granted under a Creative Minnesota Local Governments Commons license to replicate and distribute Advance Super Fast Internet Networks this report freely for noncommercial By Christopher Mitchell and Lisa purposes. To view a copy of this license, visit Gonzalez, March 2014 http://creativecommons.org/licenses/by-nc- nd/3.0/. It’s Not Just San Francisco Anymore! A Report on San Diego’s First Zero Waste Conference By Neil Seldman, March 2014
Santa Monica City Net: An Incremental Approach to Building a Fiber Optic Network By Eric Lampland and Christopher Mitchell, March 2014 Cover photo credit: Black Rock Solar
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!Table of Contents
Table of Contents The Value of Local Ownership ...... 2 Local Economic Value ...... 2 Local and National Political Value ...... 3 State Economic and Policy Value ...... 5 Barriers to Ownership ...... 6 Models for Ownership ...... 9 Policy Makes a Difference ...... 11 Further Reading ...... 12 References ...... 13
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! The Value of Local Ownership
The Value of Local Ownership Renewable energy is growing exponentially in the United States. Tens of Fig. 1 Rapid Growth of Wind and Solar Power in the US thousands of megawatts (MW) of wind and solar are boosting rural and urban 70,000 15,000 economies across the country. Megawatts
But most clean energy projects fail to 52,500 11,250 maximize the economic benefit to the Wind (left axis) communities and states where they are Solar (right axis) located by ignoring the value of local ownership. 35,000 7,500
Local Economic Value 17,500 3,750 The rewards of maintaining local control and ownership are substantial. Locally- owned wind projects create an average of twice as many jobs as absentee-owned 0 0 wind projects. And the total economic 1999 2002 2005 2008 2011 value to the community of locally-owned Sources: AWEA and SEIA projects is 50 to 240% greater, as well.1
For example, a 20 megawatt wind energy project built in Minnesota but owned by Spanish firm Iberdrola would add $20 million to the state’s economy and create about 10 long-term jobs. But if that same project were owned by Minnesota farmers or Kandiyohi Power Cooperative, it would create 20 long-term jobs and as generate as much as $68 million in economic activity for the state.
Fig. 2 Local Ownership Means More Jobs & More Local Economic Impact
Job Impact of Local Ownership Economic Impact of Local Ownership
1x 1x
1.1x 1.5x
2.8x 3.4x
Source: National Renewable Energy Laboratory Absentee-owned Locally-owned (low) Locally-owned (high)
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! The Value of Local Ownership
Solar provides a similar long-term economic value. Installing a 1 megawatt solar project built near St. Louis, MO, would, regardless of ownership, create 28 jobs and $3.1 million in economic impact throughout the supply chain.2 But there’s a huge local dollar flow advantage if the project is locally owned.
In a solar lease, for example, the benefits of the federal tax credit and accelerated depreciation would flow to the leasing company. Lease payments would also likely consume around a third of the energy savings from net metering. The result is that a locally owned 1 megawatt project would provide nearly twice the dollar flows to the local community; nearly $5.7 million in net present value over the 25-year project life.3
Local and National Political Value Local ownership also helps build political support for renewable energy by reducing resistance and building a constituency to support expansion of renewable energy production.
Many wind power projects have come under fire from nearby residents in the United States, often claiming ill health effects from the turbine noise or shadow. It's not that people are made physically ill by new renewable energy projects. Rather, they are sick and tired of seeing the economic benefits of their local wind and sun leaving their community. Opposition to solar projects is less common since the physical presence is much smaller, but some large-scale solar projects planned for deserts of the Southwest have come under fire for the environmental impact of development on virgin desert land.
Such opposition is perfectly rational, since investments in renewable energy can be quite lucrative (private developers and their equity partners routinely seek 10 percent return on Credit: London Permaculture investment or higher). In most cases, renewable energy is absentee-owned and the lion’s share of economic value leaves the community.
Of course, not-in-my-backyard (NIMBY) rarely manifests itself as an economic argument, and there's a good reason for that. In the typical project development process, there are precious few opportunities for public comment, and almost all of them represent up-or-down votes. None offer an opportunity to change the structure of the wind or solar development to allow for greater local ownership– And no project will be halted simply because it isn't locally owned. On the other hand, projects can and have been stopped on the basis of health and environmental impacts. Some people call it Wind Turbine Syndrome.
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! The Value of Local Ownership
The result is long delays and higher costs – at best – for many wind power projects, as restrictive siting rules and resistance to new transmission infrastructure effectively kills many proposed wind farms.
A European study of strategies for developing renewable energy projects found that renewable energy developers would find more local support for their efforts if they focused on the ways they can benefit the community. The study authors categorized these mechanisms as addressing local environmental, opportunism, and NIMBY concerns:
In a sentence: people want to avoid environmental and personal harm and share in the economic benefits of their local renewable energy resources and developers will increase their chances of success by addressing local desires.4
In a study published in “Energy Policy” in 2011, authors found significantly higher support for expanding wind power production when an existing wind power plant was locally owned. Looking at two German towns, each with an adjacent wind park, the study found that local ownership increased the net support for additional wind power (support less opposition) from -44% to +33%: a shift of 77 percentage points!5
Fig. 3 Local Ownership Dramatically Improves Attitudes Toward Wind Power
Not local
+77% net approval
Local ownership
Source: Fabian David Musall and Onno Kulk
0 25 50 75 100
very negative negative neutral positive very positive
Thus, local ownership is not only good economic policy. It is good politics.
Expanding local ownership can build public support for policies favoring renewable energy, from state renewable energy mandates to federal tax incentives. Already, several state legislatures have debated bills to undermine state renewable energy policies and Congress has debated terminating incentives for wind and solar power in the name of fiscal conservatism. In an era of hostile state legislatures and deep federal deficits, strong public support for renewable energy will be essential to keep the market for wind and solar power alive.
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! The Value of Local Ownership Fig. 4 Missourians Get Much More from Local Wind Power
$15,000 $14,200 $11,250
$7,500 Millions
$3,750 $4,200 Source: ILSR $200 $0 Electricity savings from imported wind power Economic benefit from local wind power Economic benefit from locally owned power
State Economic and Policy Value Consider what is happening in Missouri. Residents may lose out on their best opportunity for clean energy benefits. In 2008, voters approved a state renewable energy standard with a two- thirds majority, requiring utilities to get 15% of their power from renewable sources within the state or nearby. But in January of 2011, the Republican-controlled legislature fired the first salvo against Proposition C, stripping the “buy local” provision from the law and allowing Missouri utilities to acquire renewable energy via accounting rather than constructing wind and solar projects in the state.
Opponents to the original renewable energy law have cited high costs, but their actions are heavy with irony: the economic benefits of keeping the “buy local” provision are at least 20 times higher than the savings from importing renewable energy from elsewhere.
Assuming a generous savings of 1.5 cents per kilowatt-hour from remote wind power, Missouri ratepayers could save – at best – about $200 million by importing electricity from the windiest Midwestern states. But these savings are dwarfed by the economic value of in-state renewable energy. Fig. 5 Benefits of Solar “Home Rule” The economic benefit of a single 2-megawatt wind (20% Solar) for D.C. turbine is $2 million, according to the American Wind Energy Association. If the state met its $1,500 renewable standard with in-state wind instead of $1,500 imports, the economy would gain at least $4.2 billion and over 3,000 jobs. If that wind power were $1,125 locally owned, the economic value could rise as high as $14 billion, supporting nearly 9,000 jobs.6 $750
A similar and significant benefit is possible for Millions Washington, DC, where getting nearly 20 percent $375 $432 of its electricity from rooftop solar PV could provide Source: ILSR the District with nearly 15,000 jobs and $1.5 $267 billion in economic activity. Once again, local $0 Electricity savings from local solar power ownership provides the impetus for the largest Economic benefit from local solar power economic gains from more energy self-reliance. Economic benefit from locally owned solar power
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! Barriers to Ownership
Barriers to Ownership Unfortunately, local ownership is restrained by federal and state policies. The biggest barrier is the system of federal tax incentives that leaves only the wealthy and large corporations able to participate in renewable energy projects.
For solar, a 30% federal tax credit and accelerated depreciation favor commercially-owned projects that can use depreciation. The tax credit also means that investors in solar need substantial tax liability to make full use the tax credit. Half of American families pay too little in taxes to use the Investment Tax Credit for a rooftop solar array.7
The situation is even worse with wind power, where federal tax rules limit the Production Tax Credit to passive income (essentially, business income). Thus, most Americans are unable to effectively use the federal incentives to become renewable energy producers.
The result is that the few successful community- Credit: Chris Gaw owned projects have to do executive financing Local Ownership Requires Financing acrobatics, executing deals like the “Minnesota Acrobatics flip,” “sale/leaseback,” and “inverted lease” to find an arrangement that preserves some of the value of the federal incentives while allowing local participation.8 In each of these situations, the local owners have to take on an “equity partner” who provides some of the upfront cash for project development in exchange for the federal tax incentives. Of course, this equity partner takes its cut, so much of the tax incentives are diverted to the equity partner’s bottom line rather than buying down the cost of wind or solar power. And all of that revenue leaves the local economy.
Federal incentive Ownership Barrier Accelerated Only available to commercial renewable depreciation energy projects, not residential. 30% Investment Tax Requires substantial tax liability that half of Credit (solar) Americans lack, also precludes cities, non- profits and cooperatives. Production Tax Can only be used against business income, Credit (wind) also precludes cities, non-profits and cooperatives.
The recession that started with the 2008 financial crisis provided an opportunity to quantify the costs of the tax credit scheme and to understand its impact on project ownership. In
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! Barriers to Ownership
2009, Congress converted the tax credits into cash Fig. 6 The Shrinking Tax Equity Market grants. Thus, a wind or solar project wouldn’t need a lot of tax liability to use the incentive (though they $7 still had to be a taxable entity). $6.1 The rationale behind the cash grant was revealing. $5 Using equity partners to finance wind and solar projects requires equity partners have a steady income (and tax bill). When the recession destroyed $4
the balance sheets of most financial firms, the tax Billions $3.4 equity market also dried up (see graphic). No tax equity meant no wind or solar projects could be $2 financed. Renewable energy projects were only $1.2 narrowly saved by a temporary transition of the federal tax credits to cash grants. $0 2007 2008 2009 While the cash grant program was developed to save Source: ILSR the industry from poor policy design, it had two unintended benefits.
On the one hand, it saved money. A study of the cash grant program released in 2011 revealed that because local developers sold their tax credits to equity partners for as little as 50 cents on the dollar, cash grants were twice as effective as tax credits for renewable energy development.9 In fact, using tax credits instead of cash grants for wind and solar projects increased the cost per kilowatt-hour produced by 18 and 27 percent, respectively.10 Fig. 7 Increased Cost of Renewable Energy The cash grant not only saved the renewable Projects When Using Tax Credits Instead of industry from the failing tax equity market, but Cash Incentives meant that fewer projects had to use equity partners at all. The ratio of solar projects owned 27% by third-party investors fell during the recession 27% as developers able to use the cash grant no longer needed tax equity partners.11 One 7-turbine wind 20% project in South Dakota, for example, was able to pass the cash grant through to 600 local 18% investors. 12 Unfortunately, the cash grant 14% program expired at the end of 2011, shuttering the brief window of opportunity for more local ownership. 7%
There are four other barriers to local ownership of Wind Power Solar Power renewable energy projects.13 0% Source: ILSR One is the tradition of centralized ownership and control of the electricity system in vertically integrated utilities, uninterested in losing market share.
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! Barriers to Ownership
Another barrier is the expense and legal complication of organizing multiple investors. The most likely strategy – forming a cooperative – is often precluded because most cooperatives don’t pay taxes and therefore have no tax liability to assuage with federal tax credits. The second-best strategy of a public investment offering is often hindered by and Exchange Commission registration rules that make such a program very expensive for small projects.14 Thus, the few successful community-owned projects tend to rely on complex partnerships with tax equity firms that let much of the project’s revenue slip out of the local economy in exchange for access to federal tax incentives. The 2012 federal JOBS Act has promised to allow more crowd financing opportunities, but the rules haven’t been finalized by mid-2014,15 and the only guidance thus far is that these crowd solicitations should not use social media to advertise.
A third additional barrier is managing complicated cash flows. A U.S. commercial solar project may have revenue from as many as four sources: energy savings from the utility, a state or utility rebate, federal tax credit, and federal accelerated depreciation.
A final barrier is the electric utility, which raises supposed technical limitations to installing more local solar or wind power. Regulators tend to defer to utilities over technical issues, causing hardship for local projects attempting to get online.16
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! Models for Ownership
Models for Ownership Despite the challenges of realizing local ownership of renewable energy, a few models have emerged to make it easier to achieve and more replicable.
In Germany, a renewable energy policy called a feed-in tariff (also known as CLEAN Contracts in the U.S.) provides any prospective renewable energy producer with a guaranteed, long- term contract and grid connection at a financially attractive price. The simplicity has helped induce over 73,000 megawatts of renewable energy by the end of 2012, with over half that owned by individuals.17
This CLEAN Contract policy has also been enacted in North America, including Ontario, Vermont, Hawaii, and by municipal utilities in Gainesville, FL, and San Antonio, TX.18 However, through mid-2012 only 132 megawatts of renewable energy had been installed under U.S. CLEAN programs out of program capacity of over 1200 megawatts. Additionally, most U.S. programs set their prices on the presumption that developers will use federal tax incentives, undercutting much of the potential to support local ownership.
Few local ownership policies have been adopted in the United States and, to date, their impact has been modest. There are two policies in Minnesota supporting local ownership. One is the Community-Based Energy Development statute in Minnesota, which requires utilities to offer a separate tariff to community-based projects that meet certain thresholds for local ownership and local benefit.19 The policy has helped to develop over 100 MW of locally-owned wind power since 2005. Minnesota’s early use of a production incentive for
Fig. 8 Germany’s Massive Renewable Energy Market is Dominated by Local Ownership
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! Models for Ownership
small wind projects (2 MW and smaller) that helped birth the community-wind industry in the state.20
Washington state has a community solar policy supporting 75 kW and smaller solar projects owned by public entities or utilities (but voluntarily ratepayer funded). The significant incentive ($0.30 per kilowatt-hour) has so far only been claimed by two solar projects.
Other models have tried to adapt to the existing, if flawed, renewable energy policy framework. For example, a law in Colorado establishes a type of community solar called Community Solar Gardens. Colorado utilities are obligated to buy at least 6 MW of power from these small-scale solar projects (up to 2 MW), with each project having at least 10 “subscribers.”21 Projects can be built and financed by organizations that can use federal tax incentives, but then individuals can subscribe to get a proportional share of the electricity output from these solar gardens. The solar gardens should broaden participation in solar electricity generation while skirting some of the barriers to ownership.
While the Colorado program is relatively small, it has given birth to other community solar and “virtual net metering” policies that allow multiple electric customers of a utility to share the energy output from a shared solar array. The following chart shows the 11 states with virtual net metering policies enacted through February 2014.22
Fig. 9 Virtual Net Metering Offered in 11 States by 2014
Source: ILSR
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! Models for Ownership
With and without the community solar laws, a number of interesting community ownership models have arisen to accommodate a difficult policy environment.
A community wind project in South Dakota also succeeded in attracting over 600 local owners in a clever strategy. Four local agricultural trade organizations bought seven turbines out of a larger, adjacent wind project being built by the local electric cooperative and solicited their members to buy shares. The project was able to pass the federal cash grant through to individual investors, and used an “intra-state” offering to avoid the costs of a full Securities and Exchange Commission registration. Unfortunately, the model may be of limited value since the cash grant in lieu of tax credits has expired.23
One strategy that allows individuals to become shareholders in solar power without buying into a specific project is the SolarShare bonds being sold by a non-profit in Ontario. The bonds provide a 5% annual return on investment and will be used to finance solar power projects in Ontario (made into a lower-risk investment by Ontario’s feed-in tariff program).24 This allows any Ontario resident to see a return on investment and a small slice of ownership in the solar energy economy.
A California company, Mosaic, is pioneering a similar strategy in the U.S. Investors in California and New York (and soon other states) can be financiers of local solar projects, providing low-cost financing and earning a modest return on investment.25
With fewer than 1 percent of U.S. renewable energy capacity in locally-owned projects, the unfortunate truth is that successful local ownership is the exception rather than the rule. The successful projects tend to combine one-time funding or ingenuity in a fashion that satisfies complex federal and state requirements without easy replicability.
Policy Makes a Difference • Feed-in tariffs or CLEAN Contracts that offer a comprehensive price for power (exclusive of tax incentives) could open the door for a variety of local ownership structures and dramatically simplify financing. • Changing federal tax incentives into refundable tax credits or converting them permanently to cash grants could also reduce the burden on cities, non-profits or cooperatives in financing renewable energy projects, broadening opportunities for ownership and the pool of capital for renewable energy investments. • Even small changes, such as statewide virtual net metering rules that allow many people to share the electricity from a single, centrally-located community-scale power plant could make it easier for locally-owned energy projects to capture economies of scale and simplify financing.
The economic benefits of local ownership justify changes – some small, some large – to American energy policy.
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! Further Reading
Further Reading • Energy Self-Reliant States – an ongoing web resource on distributed renewable energy • Community Solar Power: Obstacles and Opportunities – profiling nine successful community solar projects and the policy changes needed to make community solar easier • Energy Self-Reliant States, 2nd edition – a groundbreaking atlas of state-by-state renewable energy potential • Democratizing the Electricity System – a guide to the transition from a centralized, 20th century grid system to a 21st century, decentralized electricity system • A Rooftop Revolution – a series of two reports and other resources about the transformational opportunity of rooftop solar energy. • The Future of Solar Economics and Policy – an extensive analysis of how solar will work for utilities and solar customers over the next decade.
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! References
10 Since the tax credits only represent 30% of References a project’s cost, being twice as expensive as 1 Lantz, E. and S. Tegen. Economic tax credits had a smaller impact on total Development Impacts of Community Wind project cost. Projects: A Review and Empirical Evaluation. 11 (National Renewable Energy Laboratory, April Farrell, John. How Renewable Incentives 2009). Accessed 9/19/11 at http:// Affect Project Ownership. (Institute for Local tinyurl.com/62qq3ee. Self-Reliance, 12/6/10). Accessed 10/4/11 at http://tinyurl.com/6kyr8se. 2 ILSR analysis using the National Renewable 12 Energy Laboratory JEDI economic model. Farrell, John. Change in Federal Incentive Model results run 7/30/14, available at Enables Cooperative to Own Wind Project. http://cl.ly/WpLQ. (Institute for Local Self-Reliance, 5/19/11). Accessed 10/4/11 at http://tinyurl.com/ 3 ILSR analysis, based on a project cost of 3l222bd. $3.75/Watt, annual output of 1322 kWh AC 13 per kW DC, 0.5% annual output decrease, 3% Farrell, John. 5 Barriers to and Solutions for electricity price inflation, 5% discount rate, Community Renewable Energy. (Institute for and initial net metering rate of $0.115 per Local Self-Reliance, 5/3/13). Accessed kWh. 7/29/14 at http://bit.ly/1lSjgI0. 14 4 van Elburg, Jan Coen, et al. Benefit-Sharing Farrell, John. Broadening Wind Energy Mechanisms in Renewable Energy. (REShare, Ownership by Changing Federal Incentives. June 2011). Accessed 9/19/11 at http:// (Institute for Local Self-Reliance, April 2008). tinyurl.com/3tj5p82 Accessed 9/19/11 at http://tinyurl.com/ 5wvfjab. 5 Musall, Fabian David and Onno Kulk. Local 15 acceptance of renewable energy—A case Farrell, John. Crowdfunding for Community study from southeast Germany. (Energy Power? (Institute for Local Self-Reliance, Policy, v39n6, June 2011). Accessed 9/19/11 6/19/12). Accessed 7/29/14 at http://bit.ly/ at http://tinyurl.com/3uqvk2b. 1lSk7bK. 16 6 Farrell, John. Missouri Voters Will Have to Farrell, John. How Archaic Utility Rules Stall Try Again for Energy Self-Reliance. (Institute Local Solar [Infographic]. (Institute for Local for Local Self-Reliance, 6/29/11). Accessed Self-Reliance, 8/8/12. Accessed 7/29/14 at 9/19/11 at http://tinyurl.com/62fbclo. http://bit.ly/1lSkC5K. 17 7 Farrell, John. Federal Solar Tax Credits Rule Farrell, John. Citizen Ownership Remains Out Half of Americans. (Institute for Local Foundation of German Renewable Energy Self-Reliance, 1/11/11). Accessed 9/20/11 at Explosion. (Institute for Local Self-Reliance, http://tinyurl.com/6e8lbmm. 6/2/14). Accessed 7/29/14 at http://bit.ly/ XacSqj. 8 Farrell, John. More Than a 'Flip' - 18 Community Wind Projects Still Require Farrell, John. U.S. Clean Programs: Where Financing Acrobatics. (Institute for Local Self- Are We Now? What Have We Learned? Reliance, 1/26/11). Accessed 9/19/11 at (Institute for Local Self-Reliance, June 2012). http://tinyurl.com/6959mqn. Accessed 7/29/14 at http://bit.ly/Xad5cW. 19 9 Farrell, John. Cash Incentives for For more information, see the website of c- Renewables Cost Half as Much as Tax bed.org Credits. (Institute for Local Self-Reliance, 20 Minnesota - Renewable Energy Production 3/30/11). Accessed 9/19/11 at http:// Incentive. (Database State Incentives for tinyurl.com/42ats2n. Renewables & Efficiency, 6/1/11). Accessed 9/19/11 at http://tinyurl.com/3jt6lmn.
13 | Advantage Local www.ilsr.org U-20471 Official Exhibits of Soulardarity Exhibit SOU-12 Page 18 of 18 !
! References
21 Farrell, John. A First Look at Colorado's Community Solar Gardens. (Institute for Local Self-Reliance, 2/24/11). Accessed 9/19/11 at http://tinyurl.com/3r8klro. 22 Farrell, John. Virtual Net Metering. (Institute for Local Self-Reliance, Feb. 2014). Accessed 7/29/14 at http://bit.ly/1lSlCqp. 23 Farrell, John. 600 Investors in South Dakota’s Premier Community Wind Project: Episode 7 of Local Energy Rules Podcast. (Institute for Local Self-Reliance, 4/18/13). Accessed 7/29/14 at http://bit.ly/1lSlU0x. 24 Farrell, John. SolarShare Bonds Help Democratize Ontario’s Electricity System. (Institute for Local Self-Reliance, 8/10/11). Accessed 9/19/11 at http://tinyurl.com/ 3kxlx4b.
25 Farrell, John. Millions of People Investing in Solar – Episode 16 of Local Energy Rules. (Institute for Local Self-Reliance, 2/20/14). Accessed 7/29/14 at http://bit.ly/1lSmueQ.
14 | Advantage Local www.ilsr.org U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 1 of 4
ELECTRIC UTILITY PERFORMANCE RANKING MICHIGAN AMONGST THE STATES • 2019 EDITION U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 2 of 4
U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 3 of 4 The Citizens Utility Board of Michigan (CUB of MI) was formed in 2018 to represent the interests of residential energy customers across the state of Michigan. CUB of MI educates and engages Michigan consumers in support of cost-effective investment in energy efficiency and renewable energy and against unfair rate increase requests. CUB of MI gives a voice to Michigan utility customers and helps to ensure that citizens of the state pay the lowest reasonable rate for utility services and also benefit from the environmental implications of investment in clean energy. CUB of MI is a nonpartisan, nonprofit organization whose members are individual residential customers of Michigan’s energy utilities. For more information, visit www.cubofmichigan.org.
This report was prepared for Citizens Utility Board of Michigan by 5 Lakes Energy. 5 Lakes Energy is a Michigan-based policy consulting firm dedicated to advancing policies and programs that promote clean energy and sound water policy for a resilient environment. For more information, visit https://5lakesenergy.com/.
1
U-20471 Official Exhibits of Soulardarity Exhibit SOU-13 Page 4 of 4 Average minutes to restore power to a customer (CAIDI)
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U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 1 of 20
The True Value of Solar
Measuring the Benefits of Rooftop Solar Power U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 2 of 20
The True Value of Solar Measuring the Benefits of Rooftop Solar Power
Written by: Gideon Weissman Frontier Group Emma Searson and Rob Sargent Environment America Research and Policy Center
July 2019 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 3 of 20
Acknowledgments
Environment America Research & Policy Center sincerely thanks Karl R. Rábago of the Pace Energy and Climate Center, John Farrell of the Institute for Local Self-Reliance, Kevin Lucas and Rachel Goldstein of the Solar Energy Industries Association and Nathan Phelps of Vote Solar for their review of this document. Thanks also to Tony Dutzik, Susan Rakov and Jonathan Sundby of Frontier Group for editorial support.
The authors bear responsibility for any factual errors. The recommendations are those of Environment America Research & Policy Center. The views expressed in this report are those of the authors and do not necessarily reflect the views those who provided review.
2019 Environment America Research & Policy Center
Environment America Research & Policy Center is a 501(c)(3) organization. We are dedicated to protecting our air, water and open spaces. We investigate problems, craft solutions, educate the public and decision-makers, and help the public make their voices heard in local, state and national debates over the quality of our environment and our lives. For more information about Environment America Research & Policy Center or for additional copies of this report, please visit www.environmentamericacenter.org.
Frontier Group provides information and ideas to help citizens build a cleaner, healthier, fairer and more democratic America. We address issues that will define our nation’s course in the 21st century – from fracking to solar energy, global warming to transportation, clean water to clean elections. Our experts and writers deliver timely research and analysis that is accessible to the public, applying insights gleaned from a variety of disciplines to arrive at new ideas for solving pressing problems. For more information about Frontier Group, please visit www.frontiergroup.org.
Layout: Alec Meltzer/meltzerdesign.net
Cover photo: National Renewable Energy Laboratory U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 4 of 20
Table of Contents
Executive Summary ...... 1
Introduction ...... 3
The Value of Solar Power Has Important Implications for Renewable Energy Adoption ...... 4
Solar Power Delivers Important Environmental and Public Health Benefits ...... 5 Grid Benefits ...... 6 Societal Benefits ...... 7
Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits ...... 9
Conclusion and Recommendations ...... 12
Notes ...... 13 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 5 of 20 Executive Summary
istributed solar energy is on the rise, gen- To help develop smart public policy around solar erating enough electricity to power more energy, many public utilities commissions, utilities than 6 million homes each year, and result- and other organizations have conducted or spon- ingD in annual carbon dioxide emission reductions sored “value-of-solar” studies that attempt to quan- equivalent to taking 4.4 million passenger vehicles tify the monetary value of the benefits delivered, and off the road.1 Public policy has been a key factor in costs imposed, by the addition of solar energy to the driving the growth of solar energy – recognizing the electric grid. Studies that include a full range of solar enormous benefits that solar power can provide both energy’s benefits – including benefits to the environ- today and in the future. ment and society – reliably conclude that the value of
Figure ES-1. The Benefits of Rooftop Solar Energy2
Benefit Category Benefit
Avoided electricity generation
Energy Reduced line losses
Market price response
Avoided capacity investment
Grid Capacity and Grid Investments Avoided transmission and distribution investment
Reduced need for grid support services
Reduced exposure to price volatility Risk and Reliability Benefits Improved grid resiliency and reliability
Compliance Reduced environmental compliance costs
Avoided greenhouse gas emissions
Avoided air pollution Environment Societal Health benefits
Avoided fossil fuel lifecycle costs
Economy Local jobs and businesses
Executive Summary 1 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 6 of 20 those benefits approximates or exceeds the compen- exceeds the retail rate of electricity. Recent studies sation solar panel owners receive through policies from states including Maine, Pennsylvania and such as net metering. Arkansas have found that solar energy brings substantial environmental benefits, and that Many value-of-solar studies, however – especially rooftop solar owners would provide a net benefit those conducted by electric utilities – have left out key to society even with net metering compensation.3 benefits of solar energy. Policymakers and members of the public who consult these studies may be left with • Studies commissioned by electric utilities gener- a false impression of solar energy’s value to the grid ally fail to account for benefits beyond the grid, and society, with damaging results for public policy. resulting in far lower values of solar. A 2016 report published by Environment America Research and To make decisions that serve the public interest, Policy Center and Frontier Group reviewed value- policymakers should account for the full value of of-solar studies and found that, of 16 studies solar energy, including societal benefits to the reviewed, only eight accounted for avoided green- environment and public health. house gas emissions, and no studies commis- Rooftop solar energy brings a wide variety of sioned by utilities accounted for the value of solar benefits to the grid and to society. energy beyond the grid. The studies that left out societal benefits valued solar, on average, at 14.3 • Rooftop solar power generally adds value to the cents per kilowatt-hour, compared to 22.9 cents electric grid. It not only reduces the need for gener- for those studies that at least accounted for green- ation from and investment in central power plants, house gas emissions. but over the long lifetime of solar energy systems it also can increase price stability and grid reliability, Value-of-solar studies should account for all of and reduce environmental compliance costs. solar energy’s benefits to the grid and society.
• As a clean, emission-free energy source often • Policymakers must account for the societal value located on private property and built with of reduced power plant emissions, in particular considerable private, non-ratepayer investment, the value of avoided greenhouse gas emissions rooftop solar brings valuable societal benefits. and pollutants that contribute to the formation of Solar energy reduces global warming pollution, smog and soot. and also reduces emissions of dangerous air • Policymakers should also seek to account for pollutants such as nitrogen oxides, mercury and broader societal impacts of solar energy, including particulate matter. “upstream” impacts of fossil fuel production and Value-of-solar studies inconsistently account for use, such as methane emissions from fracking, and solar energy’s benefits, especially beyond the local economic development impacts. electric grid, resulting in dramatically different Public policy that fails to account for the full range of conclusions. benefits may deter the addition of solar power to the • Studies that include the benefits of solar energy grid, with ramifications for the environment, public beyond the grid generally find that its value health, and the operation of the electric grid.
2 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 7 of 20 Introduction
he electricity system that powers our homes, tion and minimize harm to our health and environ- businesses and factories imposes heavy costs ment. But while many states aspire to least-cost utility on our environment and our health. These planning, and some even incorporate the social cost costsT accrue in a variety of ways. Particulate mat- of carbon into certain planning decisions, no state ter from burning coal harms our bodies, increases fully accounts for the external costs of electricity in mortality rates and strains the health care system.4 pricing or investment decisions.9 Fracking and coal mining degrade the environment, In the 20th century, the vast majority of electricity threaten water quality, and require expensive envi- was generated from fossil fuels at large, centralized ronmental rehabilitation.5 Each new ton of global power plants. Today, the availability of clean, afford- warming pollution – whether carbon dioxide from able renewable energy, coupled with the potential to power plants, or methane leaked from natural gas generate power close to where it is used, forces a re- wells – adds to the burden we and future genera- thinking of traditional ways of setting utility rates and tions will face from extreme weather, rising seas, and comparing the value of various options for generat- economic and societal disruption.6 ing electricity. The ways in which we choose to assign Most of these costs are quantifiable, and all are vast. value to various options for generating electricity will For instance, one U.S. Environmental Protection help to shape the electricity system of the future. It is Agency study found that the impact of fossil fuel critical that we get it right. electricity generation on premature mortality, lost As the following pages show, one important step work days, and health care costs add up to hundreds policymakers can take is to begin accurately assess- of billions of dollars each year.7 Per unit of energy, ing the costs and benefits of one of our most prom- these health costs alone often exceed the price we ising clean energy resources: rooftop solar energy. pay on our electric bill.8 By doing so, they can adhere to sound policymak- Policymakers have a variety of tools at their disposal ing principles, while putting the U.S. on a path to a to minimize the societal costs of electricity genera- cleaner, healthier and more prosperous future.
Introduction 3 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 8 of 20 The Value of Solar Power Has Important Implications for Renewable Energy Adoption
hat is the value of solar energy? The difference can be dramatic. For example, a 2013 study by the Vermont Public Service Department In recent years, as distributed solar en- found that the costs and benefits of solar energy were ergy has grown into an important piece W approximately equal when environmental benefits of the American electricity system – now generat- were ignored. When greenhouse gas emissions were ing enough electricity to power more than 6 million accounted for, however, each kilowatt-hour of solar en- homes each year –policymakers, utilities, solar energy ergy generated brought a societal benefit of 4.3 cents.11 trade organizations and other energy policy experts have grappled with the question.10 Their attempts to The value attributed to solar energy – and how that calculate the cents per kilowatt-hour value of solar value is integrated into ratemaking and investment energy have had important ramifications – “value of decisions – has important implications for renew- solar” studies have been used as evidence for energy able energy adoption. Any homeowner or business policymaking that affects the speed and quantity of owner considering installing solar panels needs to solar energy adoption, which in turn affects the envi- compare the upfront cost of the investment with the ronment, public health, and the economy. likely utility bill savings over time – including both avoided electricity purchases and any compensation Authors of value-of-solar studies typically must paid by the utility for the excess solar power sup- contend with a variety of complex questions, but plied to the grid. Differences in the valuation of those the most important question is really the simplest: extra kilowatt-hours supplied to the grid can make What is the universe of benefits that will be included or break a distributed solar power project from a fi- and quantified in the analysis? Their answer can nancial perspective. This is reflected by the success of determine whether policymakers ultimately view net metering policies, which value solar energy at the solar energy as bringing a net benefit to society, with retail rate of electricity, in driving adoption of rooftop consequences for energy rates and the compensa- solar power. Of the 10 states that generated the most tion rooftop solar owners receive for excess energy small-scale solar energy per capita in 2017, all but two they feed to the grid. had a state net metering policy.12
4 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 9 of 20 Solar Power Delivers Important Environmental and Public Health Benefits
ot all energy is created equal. Some energy The benefits of distributed solar power can be di- – like electricity generated by burning coal vided into two categories: benefits to the grid (which – imposes enormous costs on the public benefit utility ratepayers in their capacity as consum- Nand the environment, including air pollution, envi- ers) and benefits to the environment and society ronmental degradation and adverse health impacts. (which benefit ratepayers and others in their capacity Energy sources such as wind and solar power impose as residents and taxpayers). The following describes fewer environmental costs than fossil fuel sources, many of those benefits in detail. and can even reduce the cost of operating the grid.
Figure 1. The Benefits of Rooftop Solar Energy13
Benefit Category Benefit
Avoided electricity generation
Energy Reduced line losses
Market price response
Avoided capacity investment
Grid Capacity and Grid Investments Avoided transmission and distribution investment
Reduced need for grid support services
Reduced exposure to price volatility Risk and Reliability Benefits Improved grid resiliency and reliability
Compliance Reduced environmental compliance costs
Avoided greenhouse gas emissions
Avoided air pollution Environment Societal Health benefits
Avoided fossil fuel lifecycle costs
Economy Local jobs and businesses
Solar Power Delivers Important Environmental and Public Health Benefits 5 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 10 of 20 Grid Benefits Market price response: Distributed solar energy also reduces the price of electricity by reducing overall Energy generated using solar panels on rooftops of demand on the grid, which can suppress wholesale homes and businesses benefits the electric grid. Not electricity prices.16 In other words, ratepayers not only only do solar panels reduce the need for electricity benefit when utilities must purchase less electricity to from central power plants, but the integration of dis- satisfy demand, but they also gain because each unit tributed clean energy resources can also help create a of electricity purchased becomes cheaper.17 These more modern, resilient and efficient grid. demand reduction-induced price effects can repre- sent an important value to ratepayers. Energy Avoided electricity costs: Solar energy sent to the grid Capacity and grid investments reduces the amount of electricity that utilities must Avoided capacity, transmission and distribution invest- generate or purchase from power plants. The value of ment: Expanding the amount of electricity we gener- this avoided electricity consumption is often greatest ate from the sun can defer or eliminate the need for in the summer months, when demand for electricity new grid capacity investments, particularly because rises due to increased air conditioning demand and demand for energy from the grid is often highest solar energy production is near its peak. Adding solar during the day when the sun is shining. By reducing energy to the system reduces the need to power up overall and peak demand, expanding solar energy expensive, often inefficient generators that run only production helps ratepayers and utilities avoid the a few times a year, or to purchase expensive peak cost of investing in new power plants, transmission power on wholesale markets, reducing the cost of and distribution lines, and other forms of electricity electricity for all ratepayers. infrastructure. Reduced line losses: Distributed solar energy also Reduced need for ancillary services: Solar energy reduces the amount of electricity lost as heat as it may also reduce certain costs of keeping the grid travels from large, centralized power plants to our running smoothly, including regulating voltage sockets. The U.S. Energy Information Administration and reducing the need to keep backup power estimated that the United States lost about $21 bil- plants running (“spinning reserves”). Solar energy lion worth of electricity in 2017, or 5 percent of the to- systems installed with “smart inverters” and other tal amount of electricity generated that year.14 These technologies that increase two-way communica- losses cause us to generate more electricity than we tion with the grid, for example, have the potential need, increasing costs for ratepayers. to improve grid operation and reduce the need for Rooftop solar PV systems drastically reduce the centralized grid support services.18 Without such amount of system losses by producing electricity on- equipment, solar energy may increase certain grid site, thereby reducing the amount of electricity trans- support costs. mitted and distributed through the grid. Solar power is particularly effective in reducing line losses because it reduces demand on grid infrastructure at times Risk and Reliability Benefits when line losses are highest. Line losses increase with Reduced exposure to price volatility: Fossil fuel price the square of the load on the distribution system, volatility has long been a concern for utilities and with losses as high as 30 percent during the high-load ratepayers alike, but the risk has become greater as hours when most solar output is delivered.15 power companies have shifted from coal to natural
6 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 11 of 20 gas – a fuel with a history of price volatility.19 Because Societal Benefits solar panels, once installed, do not incur fuel costs, Solar panels provide valuable benefits to society integrating more solar energy capacity onto the beyond what is addressed by current electricity rates. electric grid can reduce exposure to sudden swings Namely, solar energy reduces the need for the extrac- in the price of fossil fuels or wholesale electricity. tion, transportation and combustion of fossil fuels, Research has shown that the risk of fuel price volatil- which impose heavy costs on the environment and ity is primarily borne by ratepayers, rather than utility public health. shareholders.20 Some utilities also engage in fuel price hedging strategies to ensure that a portion of electricity costs are stable. Solar energy can help en- Environment sure price stability, a contribution with financial value Avoided greenhouse gas emissions: In 2017, the elec- for utilities and grid users.21 tricity sector was responsible for 28 percent of all U.S. Improved grid resiliency and reliability: Solar panels greenhouse gas pollution.23 The generation of elec- create a more diverse and geographically dispersed tricity with both coal and natural gas has a substantial energy portfolio, and generate energy close to the climate impact. Although natural gas is less carbon point of consumption. These attributes may help intensive than coal at the point of combustion, the reduce congestion in transmission and distribution process of natural gas extraction and transportation systems, and create a more reliable grid less prone results in vast emissions of methane, a gas that traps to central disruptions, power outages or rolling approximately 86 times more heat in the atmosphere blackouts.22 than the same amount of carbon dioxide over a 20- year time frame.24
Compliance Research suggests that every metric ton of carbon dioxide released into the air causes $37 of economic Avoided environmental compliance costs: Adding and social damage.25 In 2017, the United States elec- solar energy to the grid allows local utilities and tric power sector emitted more than 1.7 billion metric municipalities to avoid some of the growing costs tons of carbon dioxide emissions, equivalent to more of compliance with environmental regulations. than $64 billion in economic and social damages.26 Increasing distributed solar energy capacity helps Solar energy, on the other hand, is renewable and utilities avoid or reduce the costs of installing emission-free, and avoids the costs of both future new technologies to curb air and water pollution damage and future environmental compliance. or installing renewable energy. Solar energy also reduces the costs of compliance with regulations Rooftop solar in particular is also fast and flexible to on criteria pollutants like sulfur dioxide and nitro- implement, making it an important tool for taking on gen oxides, as well as greenhouse gas reduction climate change. Residential rooftop projects typically programs such as the Regional Greenhouse Gas take just a few months from initial deposit to power Initiative in the northeastern U.S., California’s cap- generation.27 Distributed solar energy can also be in- and-trade program for greenhouse gas emissions, stalled in a wide variety of urban settings, including on and any future programs that may be adopted at rooftops and parking lot canopies, making it well-suit- the state or federal levels. ed for densely populated and energy-intensive regions.
Solar Power Delivers Important Environmental and Public Health Benefits 7 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 12 of 20 Health benefits and avoided air pollution: Solar energy and risks chemical contamination of drinking water. reduces emissions of dangerous air pollutants such as Coal mining puts coal-worker health at risk, and has nitrogen oxides, mercury and particulate matter that caused environmental devastation including the harm public health.28 Solar energy production can loss of thousands of miles of streams.33 Burning coal reduce emissions beyond the level required by envi- generates millions of tons of coal ash that are often ronmental regulations, or address environmental and stored on site at power plants, threatening ground- public health threats that are inadequately regulated, water and occasionally resulting in catastrophic spills. providing value such as reduced illness and mortality. And thermoelectric power plants – coal, natural gas and nuclear – require water for cooling, and can have According to a 2018 report by the American Lung adverse effects on water resources and ecosystems.34 Association, 41 percent of Americans live in a county where air pollution often reaches dangerous levels.29 Air pollution is linked to increased incidence of asth- Economy ma and chronic bronchitis, and has also been shown Local jobs and businesses: The solar energy industry to cause hundreds of thousands of premature deaths has created thousands of new jobs and businesses per year.30 A typical coal-fired power plant without across the nation. As of November 2017, the solar en- technology to limit emissions sends 170 pounds of ergy industry employed more than 250,000 people, mercury – an extremely harmful neurological toxin – a 168 percent increase from 2010.35 The Bureau of into the air each year.31 Labor Statistics projects that solar installation jobs Expanding the nation’s ability to source clean elec- will be the nation’s fastest growing occupation in tricity from the sun reduces our dependence on fossil terms of total employment through 2026.36 There are fuels, and lessens the amount of harmful emissions more than 10,000 solar companies in the U.S., and that flow into the air we breathe. in 2017 the solar industry generated $17 billion of investment in the U.S. economy.37 Because rooftop Avoided fossil fuel lifecycle costs: Use of solar energy solar installations take place in our communities, they reduces the need for fossil fuels, which impose a generate local spending and opportunities for local steep cost on society not just at the point of com- businesses, and serve as visible reminders of the local bustion, but also during extraction and transporta- economic benefits of clean energy. tion.32 Natural gas drilling uses vast water resources,
8 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 13 of 20 Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits
ood policymaking requires accurate in- ronmental benefits, should be included in valuations, formation, and accurately valuing energy as these were typically among the reasons for policy resources is a critical part of setting good enactment in the first place.”40 energyG policy. In Karl R. Rábago and Radina Valova’s Often, however, utilities present assessments of the 2018 Electricity Journal article attempting to deter- value of solar that exclude key benefits to society, the mine new principles for modern rate design, the environment, or the grid. In 2016, Environment Amer- authors contend that policymakers must work to ica and Frontier Group published Shining Rewards, “fully comprehend and reflect resource value in which assessed recent value-of-solar studies, mostly rates” through “conscious engagement with objec- either commissioned by public utility commissions tive, data-driven valuation processes.”38 For poli- or submitted as evidence in ratemaking cases. Of 16 cymakers to fully comprehend the value of solar, studies published, only eight accounted for avoided they must understand solar energy’s full range of greenhouse gas emissions, and only three accounted costs and benefits, including environmental, public for economic development benefits. No studies com- health, and other societal impacts – and incor- missioned by utilities accounted for the value of solar porate them appropriately into rate-setting and energy beyond the grid. investment decisions.
Many states already incorporate solar energy’s so- cietal and environmental benefits in value-of-solar studies. In Maine, for example, the state Legislature The societal benefits of [distributed solar required the public utilities commission to “determine generation] policies, such as job growth, the value of distributed solar energy generation” and in doing so to account for “the societal value of the health benefits and environmental benefits, reduced environmental impacts of the energy.”39 should be included in valuations, as these were typically among the reasons for policy The Interstate Renewable Energy Council, which works to provide energy regulators with best prac- enactment in the first place.” tices and other policy resources, has written that the “societal benefits of [distributed solar generation] - Interstate Renewable Energy Council policies, such as job growth, health benefits and envi-
Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits 9 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 14 of 20 Those studies that left out societal benefits valued Meanwhile, at least two recent utility value-of-solar solar power, on average, at 14.3 cents per kilowatt- studies have accounted for the societal value of solar hour, compared to 22.9 cents for those studies that energy. A value-of-solar study conducted by Austin at least included greenhouse gas emissions.41 The Energy, a publicly owned utility that compensates difference is even starker when studies include public rooftop solar owners based on its calculated value of health, economic or other societal values. solar, accounts for the avoided carbon dioxide emis- sions using the social cost of carbon (as estimated by More recent value-of-solar studies from 2017 and the U.S. EPA).45 And in Minnesota, Xcel Energy’s 2019 2018 have also left out the societal value of solar value-of-solar tariff calculation includes avoided en- energy. South Carolina utilities, using a state-deter- vironmental costs that are based on the social cost of mined methodology, reported that solar generation carbon, and externality costs for non-CO2 emissions had zero value for avoided CO emissions, since they 2 developed by the Minnesota Public Utility Commis- only assessed avoided compliance costs.43 Oregon sion.46 Xcel Energy’s calculation was made using a utilities, also using a state-determined methodol- required, state-commissioned methodology.47 ogy, based avoided emission values on “anticipated environmental standards” – the estimated avoided In both studies, despite only including a subset of cost of compliance with future greenhouse gas stan- societal benefits, those benefits were found to be sig- dards – and therefore did not include the full societal nificant: Environmental benefits accounted for more benefits of avoided emissions.44 than 17 percent of the value of solar energy in Austin
40
35
30
25 Study Includes Some Societal Bene t Economic Development and Jobs Creation 20 Avoided Greenhouse Gas Emissions Societal Bene ts Cost of Environmental Compliance 15 Grid Resiliency 10 Reduced Financial Risks Grid
Bene ts Avoided Capital and Capacity Investment 5 Avoided Energy Costs Value of Solar Energy (Cents per kWh) Value Costs of Solar Integration 0 Miscellaneous -5 (U)—Studies written by, or commissioned by, utilities E3 (O) (PUC)—Studies written by, or commissioned by, public SAIC (U) Xcel (U) Acadia (O) utilities commissions CPR (NJ) (O) CPR (PA) (O) (O)—Studies written by, or commissioned by, non-utility CPR (Utah) (O) Synapse (PUC) CPR (Austin) (U) CPR/Xcel (PUC) organizations Maine PUC (PUC) SolarCity/NRDC (O) Vermont DPS (PUC) CPR (San Antonio)Crossborder (O) (AZ Crossborder2013) (AZ 2016)
Among 16 value-of-solar studies included in Environment America Research & Policy Center and Frontier Group’s 2016 report Shining Rewards, only eight accounted for any societal benefits, none conducted by or for utilities.42
10 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 15 of 20 Energy’s analysis, and more than 33 percent in Xcel solar energy for the excess electricity they supply to Energy’s.48 Yet these substantial benefits are typically the grid. For example, a solar cost-benefit analysis left out of utility analyses. conducted for the Louisiana Public Service Commis- sion that did not include social benefits informed Failing to account for the full value of solar energy legislation that severely restricted Louisiana’s solar may have costly ramifications. Utility regulators, tax credit.49 legislators and the public are keenly focused on ensuring that utility rate-setting and investment deci- Understanding the full value of solar installations sions do not impose undue burdens on ratepayers. can help policymakers develop and implement ap- Value-of-solar studies that fail to include key societal, propriate tools to compensate owners of distributed environmental and grid benefits of solar power have solar projects for the value they provide. The full been used to undermine support for policies such as range of benefits to society needs to be reflected in net metering that compensate owners of distributed those policies.
Value-of-Solar Studies Should Account for All of Solar Energy’s Societal Benefits 11 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 16 of 20 Conclusion and Recommendations
s policymakers consider the future of • The societal value of other avoided pollutants, America’s energy system, they should seek including criteria pollutants such as particulate to make decisions that serve the public matter, lead, and sulfur dioxide. Ainterest. In his seminal and oft-cited work on util- Policymakers should also seek to quantify and ac- ity ratemaking, Principles of Public Utility Rates, count for a broader set of societal impacts of solar James Bonbright defined “the theory of rates” as energy, including: “the systematic development of principles of rate- making policy, the complete or qualified observance • The local economic benefits of solar energy, of which would subserve the public interest or the including the creation of local jobs and businesses. social welfare.”50 • The societal value of avoided costs imposed by In 2019, serving the public interest means considering fossil fuels throughout their life cycle, including: the broad impacts of electricity generation, which is closely tied to many of America’s most pressing ºº Impacts from resource extraction, such as 52 environmental and public health challenges. In 2017, methane emissions associated with fracking. electricity generation accounted for 28 percent ºº Health care and mortality costs associated with of U.S. global warming emissions, and as America pollution from the entire fossil fuel lifecycle. moves toward the electrification of transportation and heating, the importance of clean electricity will ºº Potential impacts of accidents and spills associ- only increase.51 ated with fossil fuels, including coal ash, frack- ing and pipeline spills. When it comes to solar energy, that means basing policy decisions on studies that accurately and fully After accounting for the full value of solar, policymakers assess the impact of solar energy on the grid and so- should seek to ensure that electricity rates, investment ciety. Failing to account for solar energy’s full range of decisions, and other energy policies fully reflect their benefits is not only unsound policymaking, but also findings. There is precedent for ensuring that electricity risks putting America on a path to a less healthy, less rates incorporate societal costs and benefits beyond sustainable, and less prosperous future. energy costs, and doing so is both justifiable and neces- sary.53 In some cases, legislators may need to ensure that To craft energy policy that accurately reflects the state utility commissions have the authority to account value of solar energy resources, policymakers should for external costs and benefits in ratemaking decisions. account for the societal as well as the grid benefits of solar energy, specifically including: The decisions we make about our use of power not only impact the grid, but also our health, our quality of • The societal value of avoided greenhouse gas life, and our future. Energy policy should reflect that – emissions. after all, ratepayers are taxpayers and citizens too.
12 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 17 of 20 Notes
1 Based on 2018 “small-scale solar photovoltaic” 5 Union of Concerned Scientists, The Hidden Costs generation and 2017 household electricity use, and of Fossil Fuels, archived on 11 May 2019 at http://web.ar- EPA emissions calculator https://www.eia.gov/electric- chive.org/web/20190511145203/https://www.ucsusa.org/ ity/data/browser/; https://www.eia.gov/tools/faqs/faq. clean-energy/coal-and-other-fossil-fuels/hidden-cost-of- php?id=97&t=3; https://www.epa.gov/energy/green- fossils. house-gas-equivalencies-calculator. 6 U.S. Environmental Protection Agency, The 2 Based on a number of studies, including ICF, Social Cost of Carbon, archived on 26 March 2019 Review of Recent Cost-Benefit Studies Related to Net Me- at http://web.archive.org/web/20190326203039/ tering and Distributed Solar, https://www.icf.com/blog/ https://19january2017snapshot.epa.gov/climatechange/ energy/value-solar-studies; and Rocky Mountain Institute, social-cost-carbon_.html. A Review of Solar PV Benefit and Cost Studies nd2 Edition, 7 See note 4. September 2013, archived at https://web.archive.org/ web/20190614151829/https://rmi.org/wp-content/up- 8 Ibid. loads/2017/05/RMI_Document_Repository_Public-Reprts_ eLab-DER-Benefit-Cost-Deck_2nd_Edition131015.pdf. 9 Ibid.
3 Maine and Pennsylvania: Gideon Weissman, 10 Solar Energy Industries Association, U.S. Solar Frontier Group and Bret Fanshaw, Environment America Market Insight, 13 December 2018, archived on 5 March Research & Policy Center, Shining Rewards 2016 Edition, 2019 at http://web.archive.org/web/20190305024257/ October 2016; Arkansas: Arkansas Public Service Com- https://www.seia.org/us-solar-market-insight. mission Net-Metering Working Group, Joint Report and 11 Vermont Public Service Department, Evaluation Recommendations of The Net-Metering Working Group, of Net Metering in Vermont Conducted Pursuant to Act 125 15 September 2017, archived at https://web.archive.org/ of 2012, 15 January 2013, available at http://www.leg.state. web/20190201025654/http://www.apscservices.info/ vt.us/reports/2013ExternalReports/285580.pdf; see also: pdf/16/16-027-R_228_1.pdf Damian Pitt and Gilbert Michaud, “Assessing the Value of 4 Ben Machol and Sarah Rizk, “Economic Value of Distributed Solar Energy Generation”, Curr Sustainable Re- U.S. Fossil Fuel Electricity Health Impacts,” Environment newable Energy Rep, 2015, DOI:10.1007/s40518-015-0030-0. International, February 2013, https://doi.org/10.1016/j. envint.2012.03.003.
Notes 13 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 18 of 20 12 Small-scale solar generation: U.S. Energy Infor- 18 Daymark Energy Advisors prepared for Mary- mation Administration, Electricity Data Browser, accessed at land Public Service Commission, Benefits and Costs of https://www.eia.gov/electricity/data/browser/ on 1 Febru- Utility Scale and Behind the Meter Solar Resources In Mary- ary 2019; net metering by state: N.C. Clean Energy Tech- land, 10 April 2018, archived at http://web.archive.org/ nology Center, DSIRE Net Metering Summary Map, April web/20180514201412/http://www.psc.state.md.us/wp- 2019, available at https://s3.amazonaws.com/ncsolarcen- content/uploads/MD-Costs-and-Benefits-of-Solar-Draft- prod/wp-content/uploads/2019/05/DSIRE_Net_Metering_ for-stakeholder-review.pdf. April2019.pdf; U.S. population by state: U.S. Census Bureau, 19 Union of Concerned Scientists, The Natural Gas Table 1. Annual Estimates of the Resident Population for the Gamble: A Risky Bet on America’s Clean Energy Future, March United States, Regions, States, and Puerto Rico: April 1, 2010 to 2015. July 1, 2018 (NST-EST2018-01), December 2018, available at https://www.census.gov/newsroom/press-kits/2018/pop- 20 Mark Bolinger, Lawrence Berkeley National estimates-national-state.html. Laboratory, Using Probability of Exceedance to Compare the Resource Risk of Renewable and Gas-Fired Generation, March 13 See note 2. 2017, available at http://eta-publications.lbl.gov/sites/de- 14 Line losses: U.S. Energy Information Administra- fault/files/lbnl-1007269.pdf. tion, United States Electricity Profile 2017: Table 10. Supply 21 Thomas Jenkin et al, National Renewable Energy and disposition of electricity, 1990 through 2017, 8 January Laboratory, Ray Byrne, Sandia National Laboratories, The 2019, available at https://www.eia.gov/electricity/state/ Use of Solar and Wind as a Physical Hedge against Price Vari- unitedstates/; average 2017 retail price of electricity was ability within a Generation Portfolio, August 2013. 10.48 cents per kWh: U.S. Energy Information Administra- tion, 22 Richard Perez et al., Clean Power Research pre- pared for Mid‐Atlantic Solar Energy Industries Association Electric Power Annual With Data for 2017: Table 2.4. Aver- and Pennsylvania Solar Energy Industries Association, The age Price of Electricity to Ultimate Customers, 22 October Value of Distributed Solar Electric Generation to New Jersey 2018, available at https://www.eia.gov/electricity/annual/. and Pennsylvania, November 2012, archived at http://web. 15 Lazar, J. and Baldwin, X., Valuing the Contribution archive.org/web/20170829111033/http://mseia.net/site/ of Energy Efficiency to Avoided Marginal Line Losses and wp-content/uploads/2012/05/MSEIA-Final-Benefits-of- Reserve Requirements, Regulatory Assistance Project, 2011. Solar-Report-2012-11-01.pdf. Also see: Rocky Mountain Institute, A Review of Solar PV Benefit and Cost Studies nd2 16 Michael Craig et al., “A Retrospective Analysis Edition, September 2013, archived at https://web.archive. of the Market Price Response to Distributed Photovoltaic org/web/20190614151829/https://rmi.org/wp-content/ Generation in California,” Energy Policy, 14 July 2018, doi: uploads/2017/05/RMI_Document_Repository_Public- 10.1016/j.enpol.2018.05.061. Reprts_eLab-DER-Benefit-Cost-Deck_2nd_Edition131015. 17 Paul Chernick, Resource Insight, Inc., John J. Plun- pdf. kett, Green Energy Economics Group Inc., Price Effects as a 23 U.S. Environmental Protection Agency, Sources Benefit of Energy-Efficiency Programs, 2014. of Greenhouse Gas Emissions, archived on 12 June 2019 at http://web.archive.org/web/20190612083429/https:// www.epa.gov/ghgemissions/sources-greenhouse-gas- emissions.
14 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 19 of 20 24 Elizabeth Ridlington and Gideon Weissman, Fron- 33 Ibid. tier Group, Natural Gas and Global Warming, Summer 2016, 34 Kristen Averyt et al., Union of Concerned Scien- archived at http://web.archive.org/web/20161020192209/ tists, Freshwater Use by U.S. Power Plants: Electricity’s Thirst http://frontiergroup.org:80/sites/default/files/reports/ for a Precious Resource, November 2011, available at https:// full%20report%20-%20Frontier%20Group%20-%20 www.ucsusa.org/clean_energy/our-energy-choices/en- Natural%20Gas%20and%20Global%20Warming%20-%20 ergy-and-water-use/freshwater-use-by-us-power-plants. July%202016.pdf; Gunnar Myhre et al., “Anthropogenic html. and Natural Radiative Forcing,” in T.F. Stocker et al. (eds.), Climate Change 2013: The Physical Science Basis. Contribu- 35 The Solar Foundation, National Solar Jobs Census tion of Working Group I to the Fifth Assessment Report of 2017, January 2018. the Intergovernmental Panel on Climate Change (Cam- bridge, United Kingdom and New York, NY, USA: Cam- 36 U.S. Bureau of Labor Statistics, Occupational bridge University Press, 2013), 714. Outlook Handbook – Fastest Growing Occupations, 12 April 2019, archived at http://web.archive.org/ 25 Peter Howard, Environmental Defense Fund, web/20190612165516/https://www.bls.gov/ooh/fastest- Institute for Policy Integrity and the Natural Resources growing.htm. Defense Council, Omitted Damages: What’s Missing from the Social Cost of Carbon, 13 March 2014. 37 Solar Energy Industries Association, Solar Industry Research Data, archived on 1 February 2019 at http://web. 26 Tons of carbon dioxide pollution multiplied by archive.org/web/20190201231745/https://www.seia.org/ $37. Electric power carbon dioxide emissions: U.S. Envi- solar-industry-research-data. ronmental Protection Agency, Greenhouse Gas Inventory Data Explorer, accessed at: https://cfpub.epa.gov/ghgdata/ 38 Karl R. Rábago and Radina Valova, “Revisiting inventoryexplorer/ on 13 June 2019. Bonbright’s Principles of Public Utility Rates in a DER World,” The Electricity Journal, October 2018, https://doi. 27 SEIA, Siting & Permitting, archived at web.archive. org/10.1016/j.tej.2018.09.004. org/web/20160916220218/http://www.seia.org/policy/ th power-plant-development/siting-permitting. 39 126 Maine Legislature, An Act to Support Solar Energy Development in Maine, enacted 24 April 2014. 28 U.S. Environmental Protection Agency, Air Pollut- ants, 1 June 2015, accessed at: www.epa.gov/air/airpollut- 40 Interstate Renewable Energy Council, A Regula- ants.html. tor’s Guidebook: Calculating the Benefits and Costs of Distrib- uted Solar Generation, October 2013, available at https:// 29 American Lung Association, State of the irecusa.org/2013/10/experts-propose-standard-valuation- Air 2018, 2018, archived at http://web.archive.org/ method-to-determine-benefits-and-costs-of-distributed- web/20190214160111/https://www.lung.org/our-initia- solar-generation/. tives/healthy-air/sota/key-findings/. 41 Gideon Weissman, Frontier Group and Bret 30 Ibid. Fanshaw, Environment America Research & Policy Cen- ter, Shining Rewards: The Value of Rooftop Solar Power for 31 Union of Concerned Scientists, Environmental Im- Consumers and Society - 2016 Edition, 18 October 2016, pacts of Coal Power: Air Pollution, accessed at www.ucsusa. available at https://frontiergroup.org/reports/fg/shining- org/clean_energy/coalvswind/c02c.html#.VW5vus9Viko, 2 rewards-0. June 2015. 42 Ibid. 32 See note 5.
Notes 15 U-20471 Official Exhibits of Soulardarity Exhibit SOU-14 Page 20 of 20 43 South Carolina Office of Regulatory Staff,Status 49 Energy and Policy Institute, Louisiana Solar Energy Report on Distributed Energy Resource and Net Energy Meter- Attacked, date not given, archived at https://web.archive. ing Implementation, July 2017, available at https://www. org/web/20190614182149/https://www.energyandpolicy. scstatehouse.gov/reports/ORS/FINAL%20DER%20and%20 org/renewable-energy-state-policy-attacks-report-2015/ NEM%20Report%202017.pdf; further methodological louisiana-net-metering-attacked/; Brian Slodysko, “Law- details: Public Service Commission of South Carolina, IN RE: makers Curtail Louisiana’s Generous Solar Tax Break, Petition of the Office of Regulatory Staff to Establish Generic Cause Industry to Cry Foul,” Associated Press, 24 June 2015, Proceeding Pursuant to the Distributed Energy Resource available at https://www.theadvocate.com/baton_rouge/ Program Act, Act No. 236 of 2014, Ratification No. 241, Senate news/politics/legislature/article_fc19cfdd-24d4-5f56- Bill No. 1189 - DOCKET NO. 2014-246-E - ORDER NO. 2015- a557-7a1e104188a5.html; Acadian Consulting Group on 194, available at https://dms.psc.sc.gov/Attachments/ behalf of Louisiana Public Service Commission, Estimating Order/29cf4369-155d-141f-23b1536c046aebc5. the Impact of Net Metering on LPSC Jurisdictional Ratepay- ers, 27 February 2015, archived at http://web.archive. 44 Jacob Goodspeed, Portland General Electric org/web/20171230032152/http://lpscstar.louisiana.gov/ Company, RE: UM 1912 - Portland General Electric Resource star/ViewFile.aspx?Id=f2b9ba59-eaca-4d6f-ac0b-a22b- Value of Solar Filing, 4 December 2017, archived at https:// 4b0600d5. web.archive.org/web/20190131205939/https://edocs.puc. state.or.us/efdocs/HAA/haa163313.pdf. 50 James C. Bonbright, Principles of Public Utility Rates, (New York: Columbia University Press, 1961), 27, 45 Austin Energy, 2018 Value of Solar (VOS) Up- available at https://www.raponline.org/wp-content/ date, May 2017, archived at https://web.archive.org/ uploads/2016/05/powellgoldstein-bonbright-principlesof- web/20190206034952/http://www.austintexas.gov/edims/ publicutilityrates-1960-10-10.pdf. document.cfm?id=277018. 51 U.S. Environmental Protection Agency, Sources 46 Xcel Energy 2019 Value of Solar calculation: of Greenhouse Gas Emissions, archived on 18 May 2019 at See Minnesota Public Utilities Commission docket no. http://web.archive.org/web/20190518043422/https:// E002/M-13-867, available at https://www.edockets.state. www.epa.gov/ghgemissions/sources-greenhouse-gas- mn.us/EFiling/edockets/searchDocuments.do?method=sh emissions, owPoup&documentId={F06EBB69-0000-C012-9D35-422A1 9F427EA}&documentTitle=20193-151380-01; state meth- 52 See note 24. odology: Minnesota Department of Commerce, Division 53 For example, the New Jersey Societal Benefit of Energy Resources, Minnesota Value of Solar: Method- Charge: New Jersey’s Clean Energy Program, Societal ology, 9 April 2014, archived at http://web.archive.org/ Benefits Charge (SBC), archived on 28 September 2018 at web/20170521032153/http://mn.gov/commerce-stat/pdfs/ http://web.archive.org/web/20180928201733/http://www. vos-methodology.pdf. njcleanenergy.com:80/societal-benefits-charge. 47 Ibid.
48 See note 45 and note 46.
16 The True Value of Solar U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 1 of 6 AJPH ENVIRONMENTAL JUSTICE
Disparities in Distribution of Particulate Matter Emission Sources by Race and Poverty Status
Ihab Mikati, BS, Adam F. Benson, MSPH, Thomas J. Luben, PhD, MSPH, Jason D. Sacks, MPH, and Jennifer Richmond-Bryant, PhD
Objectives. To quantify nationwide disparities in the location of particulate matter cardiovascular diseases as well as premature 6–8 (PM)-emitting facilities by the characteristics of the surrounding residential population mortality. Although proximity to facilities and to illustrate various spatial scales at which to consider such disparities. emitting PM is not a direct measure of ex- Methods. We assigned facilities emitting PM in the 2011 National Emissions Inventory posure, it is a valuable metric. Unlike natural to nearby block groups across the 2009 to 2013 American Community Survey population. events that contribute to ambient PM, such as wildfires, the siting of a facility is the result of We calculated the burden from these emissions for racial/ethnic groups and by poverty a decision-making process. Disparities in siting status. We quantified disparities nationally and for each state and county in the country. may indicate underlying disparities in the Results. For PM of 2.5 micrometers in diameter or less, those in poverty had 1.35 times power to influence that process. For example, higher burden than did the overall population, and non-Whites had 1.28 times higher an Environmental Protection Agency (EPA) burden. Blacks, specifically, had 1.54 times higher burden than did the overall population. investigation in Flint, Michigan, found a direct These patterns were relatively unaffected by sensitivity analyses, and disparities held not link between racial discrimination and the only nationally but within most states and counties as well. permitting of a power station there, stating, Conclusions. Disparities in burden from PM-emitting facilities exist at multiple geo- “The preponderance of evidence supports a graphic scales. Disparities for Blacks are more pronounced than are disparities on the finding of discriminatory treatment of African basis of poverty status. Strictly socioeconomic considerations may be insufficient to Americans by [the Department of Environ- reduce PM burdens equitably across populations. (Am J Public Health. 2018;108:480– mental Quality] in the public participation process.”9 485. doi:10.2105/AJPH.2017.304297) We aimed to quantify nationwide disparities in the distribution of PM-emitting facilities by See also Houston, p. 441. the characteristics of the surrounding residential populations and to illustrate various spatial scales at he inequitable distribution of hazardous those in poverty than for those above the whichtoconsidersuchdisparities.Previouslit- T fi sites such as land lls and industrial fa- poverty line, whereas the disparity for non- erature has shown that non-Whites and below- cilities is one of the longest-standing concerns Whites (37% higher concentrations than for poverty individuals are more likely to reside near in the field of environmental justice. More 3 10 Whites) was substantially greater. stationary sites of PM2.5 emissions ; we sought to than 3 decades ago in one of the earliest There is considerable evidence concerning updateandexpandonthesefindings. environmental justice studies, the US gov- human health impacts of residential proximity ernment reported a disproportionately high to facilities emitting air pollutants.4 One such representation of socially disadvantaged pollutant is particulate matter (PM), a mixture populations residing in communities near of solid and liquid particles suspended in the landfills.1 Disparities in residential proximity METHODS air.5 Exposure to PM (PM £ 10 mmindi- to pollution sources have been evaluated in 10 We combined facility emissions data with ameter) and especially to PM (PM £ 2.5 mm terms of income level and poverty as well as 2.5 demographic data to investigate racial/ethnic race/ethnicity. A nationally representative in diameter) has been associated with a number and economic disparities in residential 1986 sample found that Blacks were 1.54 of health effects, including respiratory and proximity to sources of air pollution. times more likely than were Whites to live within 1 mile of a facility listed in the Toxics ABOUT THE AUTHORS Release Inventory—a gap that remained Ihab Mikati and Adam F. Benson are participants in the Oak Ridge Institute for Science and Education research training program fi stationed with the National Center for Environmental Assessment, Office of Research and Development, US Environmental statistically signi cant even after accounting Protection Agency, Research Triangle Park, NC. Thomas J. Luben, Jason D. Sacks, and Jennifer Richmond-Bryant are staff for income and education level.2 The dis- members with the National Center for Environmental Assessment, Office of Research and Development, US Environmental tributions of specific air pollutants, and not Protection Agency, Research Triangle Park, NC. Correspondence should be sent to Ihab Mikati, ORISE Program participant at the National Center for Environmental Assessment, just the facilities emitting them, also reflect Office of Research and Development, US Environmental Protection Agency—109 T.W. Alexander Drive, Research Triangle Park, racial disparities. For example, mean resi- NC 27709 (e-mail: [email protected]; please cc: [email protected] to ensure receipt). Reprints can be ordered at http:// www.ajph.org by clicking the “Reprints” link. dential ambient nitrogen dioxide concen- This article was accepted December 16, 2017. trations in 2010 were about 7% higher for doi: 10.2105/AJPH.2017.304297
480 Research Peer Reviewed Mikati et al. AJPH April 2018, Vol 108, No. 4 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 2 of 6 AJPH ENVIRONMENTAL JUSTICE
Data Sources hazards relative to those in large rural tracts.15 Sensitivity Analyses We accessed population data via the US To address this, we used a distance-based We conducted several sensitivity analyses Census Bureau’s 2009 to 2013 American “centroid-containment” assignment in- to address the potential for small methodo- 15 Community Survey (ACS).11 The ACS stead. We assigned each facility and its logical changes to bias our results. To examine provides self-reported data on racial/ethnic corresponding emissions (in tons per year) to whether disparities were consistent at various identification and poverty status at the census all census block groups containing a centroid distances from emissions sources, we used block group level for all 50 states and within a set radius of the facility’s geographic assignment radii at 0.50, 1.25, and 5.00 miles Washington, DC. The block group is a single coordinates. We analyzed radii ranging from as alternatives to the 2.50-mile centroid- level of resolution finer than the census tract 0.5 to 5.0 miles; in our main analysis, we used containment radius in the main analysis. To and commonly contains 600 to 3000 a 2.5-mile radius, following the NEI facility address whether the reported disparities were 10 residents. assignment of Boyce and Pastor. We assigned driven by assignments in extremely sparse or For our analyses, “White” refers to only facilities and emissions meeting the centroid- dense areas, we repeated the main analysis non-Hispanic Whites; “non-White” refers to containment criteria for a block group to the after eliminating the largest and smallest decile all others. Included in the latter group are Black population residing within that block group. of block groups (by area). An additional (non-Hispanic) and Hispanic (any race). The We measured the between-group differ- analysis ensured that facilities were always Census Bureau determines poverty status by ences in residential proximity to facilities and assigned to their host block group by com- comparing household income to a threshold facility emissions by using 2 metrics: the ab- bining the centroid-containment assignment that varies by household size and composition.12 solute burden (i.e., the average number of with the traditional unit–hazard coinci- Because there are differences between facilities or average amount of PM, in tons/ dence; this helped us address concerns that rural and urban areas both in industrialization year, emitted within a set distance from an centroid-containment assignment could un- and in demographic composition, we also individual’s block group centroid) and the derestimate the burden in rural areas, where noted rural–urban status for all block groups. proportional burden (i.e., the ratio between facilities may be far from their host block We made rural–urban status determinations a demographic subgroup’s average burden group’s centroid. from the US Department of Agriculture’s and that of the overall population). We repeated the main analysis using racial/ rural–urban commuting area (RUCA) codes To determine average absolute burden ethnic population data from the 2010 De- for 2010.13 These codes are determined on (Equation 1) for demographic subgroups, we cennial Census (poverty data unavailable for the basis of census tract–level population multiplied the emissions (or total number of this data set) to show that disparities were not density, urbanization, and daily commuting facilities) assigned to each block group by specific to the census methodology of the levels; they can be used to distinguish be- the subgroup’s population size. We divided ACS. We considered recent shifts in pollution tween metropolitan and micropolitan urban the sum of this value across block groups data by substituting the 2008 or 2014 NEI in centers, commuting (suburban) areas, small by the total subgroup population, similar to place of the 2011 data set. To gauge general towns, and rural areas.13 previous studies.10,16,17 applicability to other emissions, we also an- We collected emissions data on stationary ð1Þ Absolute Burden alyzed other criteria air pollutants available human-made point sources from the US P in the NEI: carbon monoxide (CO), lead ðPopulation · Emissions Þ P BlockGroup BlockGroup EPA National Emissions Inventory (NEI) ¼ (Pb), oxides of nitrogen (NOX), and sulfur PopulationBlockGroup “Facility-level by Pollutant” files for 2011, dioxide (SO2). the year most closely aligned to the census We calculated proportional burdens data we used for our analysis.14 This data (Equation 2) by dividing the absolute burden source allowed us to consider not just the in a subgroup of the population by the ab- presence or absence of a facility but also the solute burden in the overall population. amount of the pollutant emitted. We con- RESULTS Scores above 1.0 indicate that the subgroup sidered annual NEI totals, in tons per year, for On average, there are 5.7 NEI facilities experienced higher burden than would be primary PM and primary PM . within 2.5 miles of an individual’s census 2.5 10 expected in a perfectly equitable scenario. block group centroid (i.e., a facility burden ð Þ 2 Proportional BurdenSubgroup of 5.7). For an individual in the overall Data Analysis US population, the mean absolute burden ¼ Absolute BurdenSubgroup The spatial size (i.e., land area) of block of PM2.5 and PM10 emitted from nearby Absolute BurdenOverall groups can vary substantially between urban facilities is 22.4 and 29.2 tons per year, re- and rural areas because of the block group’s We carried out all data management and spectively. As reported in Table 1, non- restricted population range. As population analysis by using R software version 3.1.2 Whites and those living in poverty face densities increase and block groups shrink in (R Foundation for Statistical Computing, a disproportionate burden from PM-emitting urban areas, assignment via “unit–hazard Vienna, Austria; packages used: dplyr, tidyr, facilities. Blacks in particular are likely to live coincidence” (the matching of a site to its host bit64, data.table for data management; tigris in high-emission areas; the average PM2.5 unit and no others, regardless of proximity) for block group coordinates; Hmisc for cal- burden in this group is 1.54 times that of the may underestimate the number of nearby culation of correlations). population overall. It is notable that this racial
April 2018, Vol 108, No. 4 AJPH Mikati et al. Peer Reviewed Research 481 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 3 of 6 AJPH ENVIRONMENTAL JUSTICE
TABLE 1—Mean Absolute and Proportional Burdens From Facilities Emitting PM in the 2011 National Emissions Inventory, Selected Subgroups: American Community Survey, United States, 2009–2013
PM2.5 Burden, PM10 Burden, Facility Burden, Variable Proportion of Population, % Absolute (Proportional) Absolute (Proportional) Absolute (Proportional) Overall population 1.00 22.4 (. . .) 29.2 (. . .) 5.7 (. . .) Race/ethnicitya White 0.63 18.8 (0.84) 24.7 (0.85) 4.1 (0.72) Non-White 0.37 28.6 (1.28) 37.0 (1.27) 8.5 (1.49) Black 0.12 34.5 (1.54) 43.6 (1.49) 6.2 (1.09) Hispanic 0.17 26.9 (1.20) 35.9 (1.23) 9.8 (1.70) Poverty level Above poverty 0.85 20.9 (0.93) 27.2 (0.93) 5.5 (0.95) Below poverty 0.15 30.3 (1.35) 39.3 (1.35) 7.2 (1.26)
Note. PM = particulate matter; PM2.5 = PM of £ 2.5 mm in diameter; PM10 = PM of £ 10 mm in diameter. Poverty level determined by the US Census Bureau in 2013. Burdens represent the PM emissions or the number of facilities in the 2011 National Emissions Inventory that are near the block group of residenceforan average individual in the 2009–2013 American Community Survey population. Absolute burden units for PM emissions are tons/year; for facilities, they are the total number. Proportional burden is the ratio of subgroup burden to overall population burden. a“White” refers to only non-Hispanic Whites; “non-White” refers to all others. Included in the latter group are Black (non-Hispanic) and Hispanic (any race).
disparity is larger than is the poverty-based subgroups. Because of a highly nonnormal Whites (8.7 tons/year) is less than is half the
PM2.5 disparity (1.35 times the overall pop- distribution, individuals residing in block absolute burden for equivalent non-Whites ulation average). Proportional burdens for groups with emissions above the overall mean (20.1 tons/year).
PM2.5 are highly similar to those for PM10, are among the top 15% most burdened. The proportional PM2.5 burden for non- but this is not true for proportional burdens in Across the distribution, the gap in burden Whites at the national level is 1.28 (Table 1). the total number of facilities. This difference between those above and those below the This indicates that high non-White pop- suggests that the magnitude of emissions from poverty line is smaller than is the gap between ulations coincide with high emissions na- a facility, and not simply its presence or ab- Whites and non-Whites. At the 50th per- tionally. Burdens can also be considered sence, is valuable information when charac- centile, Whites have an absolute PM2.5 within finer spatial scales—for example, the terizing burden. burden below 0.1 tons per year—more than ratio of burdens between non-Whites and the Figure 1 illustrates the population-wide an order of magnitude below the burden of overall population in a particular state or distribution of absolute PM2.5 burden for the any of their non-White counterparts. At the county. Disparities operate in different ways overall population as well as for several 80th percentile, the absolute burden for at each scale, yet overall higher burdens for non-Whites are a consistent outcome at both state (Figure A, part a [available as a supple- 10 000 Overall Hispanic ment to the online version of this article at 1000 White Above poverty http://www.ajph.org]) and county (Figure Black Below poverty A, part b) levels. All but 4 states (Maryland, 100 New Mexico, North Dakota, and West (Mean: 22.4) Virginia) and Washington, DC, have an 10 elevated mean PM2.5 burden for the non- 1.0 White population (i.e., proportional burdens > 1.0). Comparing the White and non-White 0.1 burdens across all states confirms a statistically significant overall difference in absolute Absolute Burden, Tons/Year 0.0 PM burdens (paired t test mean of 0 20 40 60 80 100 2.5 differences = –11.04 (–15.30, –6.79); – Percentile in Total Population t(50) = –5.22; P < 10 5). Likewise, the ma-
Note. PM2.5 = particulate matter of 2.5 micrometers in diameter or less. Burden scale (y-axis) is displayed jority of counties have higher absolute PM2.5 logarithmically. Poverty level determined by the US Census Bureau in 2013. burdens for their non-White residents (paired t test mean of differences = –3.43 (–4.37, –2.48); — – FIGURE 1 Distribution of Absolute Burdens of PM2.5 Emissions From Nearby Facilities in the t(3140) = –7.12; P < 10 11). fi 2011 National Emissions Inventory, Strati ed by Race/Ethnicity and Poverty Status: We recognized rural–urban status as American Community Survey, United States, 2009–2013 a potential modifier because of the
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industrialization of cities combined with 2014 NEI by a mean of 11.7 tons per year in including all facilities hosted in a block group, the high representation of non-Whites in the overall population (i.e., a 38% drop over regardless of distance to centroid; and using population-dense centers. For this reason, we the 6-year interval). This drop was slightly 2010 Decennial Census data instead of the used the RUCA codes to characterize and smaller (33%) for Blacks and slightly greater 2009 to 2013 ACS. The results of these an- stratify block groups by rural–urban status (41%) for Hispanics. Despite large drops in alyses were largely consistent with the original (Table A [available as a supplement to the absolute burden for all groups, proportional analysis, suggesting robustness in results de- online version of this article at http://www. burdens appear stagnant. The proportional spite alterations in methodology (Table C ajph.org]). As shown in Figure 2, the overall PM2.5 burden of 1.61 for Blacks in the 2014 [available as a supplement to the online national burdens are largely driven by high NEI is higher than are the proportional version of this article at http://www.ajph. emissions in the metropolitan and micro- burdens in the 2011 NEI (1.54; Table 1) and org]). Extending the analysis to other criteria politan cores (those with populations of at the 2008 NEI (1.50; Table B). Data are also pollutants tracked by the NEI (CO, Pb, least 50 000 and those with populations of at provided using the 2012 to 2016 ACS and NOX, and SO2) also remained largely con- least 10 000 but less than 50 000, respectively). 2014 NEI (Table B). However, because sistent with PM results with few exceptions Although those living above the poverty comparison of overlapping ACS data sets is (Table D [available as a supplement to the line do experience a lower burden than do advised against,18 this analysis is limited in that online version of this article at http://www. those below it within these urban areas, the it considers only changes in PM2.5 emissions ajph.org]). The block group Spearman cor- disparities in emissions are especially pro- and not changes in demographics during this relation of CO, Pb, NOX, and SO2 to PM2.5 nounced for Blacks—reinforcing the overall time span. It is not possible to determine assignments were 0.92, 0.77, 0.94, and 0.93, finding that racial disparities appear to be a causal relationship for changes over time respectively (Table E [available as a supple- markedly higher than are poverty-based from this analysis. Although there is evidence ment to the online version of this article at disparities. that lower property values attract minority http://www.ajph.org]); the amount of PM2.5 We also explored recent changes in populations after siting, high representation of emitted near a block group is likely a general emission distributions by considering avail- those groups generally also exists before the indicator of the overall emissions in that area. able NEI year data for a 6-year range (Table B siting of a facility in an area.19 [available as a supplement to the online We performed sensitivity analyses by re- version of this article at http://www.ajph. peating the main analysis after adjusting the org]). Absolute PM2.5 burden dropped for all centroid-containment radius; removing the DISCUSSION examined subgroups between the 2008 and smallest and largest decile of block groups; We characterized the populations residing near NEI facilities to determine whether individuals from certain subgroups face dis- Overall population Hispanic proportionately high burden from nearby PM 50 White Above poverty RUCA Description emissions. We observed disproportionately Black Below poverty 1 Metropolitan core 2 Metropolitan high-commuting high burdens for non-Whites and those living 3 Metropolitan low-commuting 40 in poverty (Table 1; Figure 1). Disparities 4 Micropolitan core 5 Micropolitan high-commuting for non-Whites persist at multiple scales: 6 Micropolitan low-commuting nationally, in the vast majority of states 7 Small town core 30 8 Small town high-commuting (Figure A, part a) and in the majority of in- 9 Small town low-commuting dividual counties (Figure A, part b). The lack 10 Rural of individual-level data on the intersection of 20 racial/ethnic identification and poverty status limited our ability to make direct compari- sons; however, overall, racial disparities for 10
Absolute Burden, Tons/Year both PM2.5 and PM10—specifically between Blacks and Whites—are stronger than are 0 poverty-based disparities (Table 1). This is Overall 1 2 3 4 5 6 7 8 9 10 a consistent observation even when consid- RUCA Code ering urban Whites and Blacks alone (Figure 2). PM2.5 and PM10 disparities for Hispanics Note. PM2.5 = particulate matter of 2.5 micrometers in diameter or less; RUCA = rural–urban commuting area. are less pronounced or consistent but still Dashed line indicates mean overall burden for all groups in the United States (22.4 tons/year). The US Department of Agriculture defines and assigns RUCA codes. Poverty level determined by the US Census Bureau present. The diversity within the Hispanic in 2013. population, which includes both native-born persons and recent immigrants from a variety — fi FIGURE 2 RUCA-Strati ed Absolute Burdens of PM2.5 Emissions From Nearby Facilities in of countries, has made the catchall “Hispanic” fi the 2011 National Emissions Inventory, Further Strati ed by Race/Ethnicity and Poverty designation vexing for public health Status: American Community Survey, United States, 2009–2013 research.20,21
April 2018, Vol 108, No. 4 AJPH Mikati et al. Peer Reviewed Research 483 U-20471 Official Exhibits of Soulardarity Exhibit SOU-15 Page 5 of 6 AJPH ENVIRONMENTAL JUSTICE
Our main finding of national disparities et al.2 found a disproportionately high areas. Because of the higher representation of
in PM2.5 burdens by race is consistent with number of Black residences near polluting the non-White population in urban areas, that of Boyce and Pastor,10 who carried out facilities in Midwestern metropolitan areas— centroid containment offers a more appro-
a similar analysis on PM2.5 using the 2008 NEI much more so than in Southern cities and in priate characterization of Black burdens na- and reported results equivalent to a pro- rural areas. No single scale can be considered tionally. We took several sensitivity measures portional burden of 1.25 for non-Whites best for grouping populations. In this case, to address the potential resulting un- (compared with our finding of 1.28). Such results at national, state, and county scales all derestimates of burdens in rural areas. In one disparities in residential proximity to sites of indicate that non-Whites tend to be burdened analysis, we combined unit–hazard co- pollution potentially correspond to disparities disproportionately to Whites. incidence with centroid containment to – in a range of health outcomes.22 24 calculate burdens; in others, we varied the
Exposure to PM2.5 has been linked to containment radius between 0.5 and 5.0 – increased morbidity and mortality.6 8 Al- Strengths and Limitations miles. Neither of these alterations to the though our study focused on point source Our methodology has advantages as well as methodology substantially changed the values
emissions and not on ambient PM2.5, the limitations. We relied on proximity to sta- reported in the main analysis, suggesting racial disparity in burdens from nearby facil- tionary, human-made point sources of pri- a robust result (Table C). Furthermore, ities parallels the disparities seen in both mary PM emissions rather than ambient even limiting analysis only to urban areas, modeled16 (Table F [available as a supplement concentrations. Because there is a collection a Black individual living in a metropolitan or to the online version of this article at http:// of other factors that may affect ambient PM micropolitan core has a higher burden than www.ajph.org]) and monitored17 ambient concentrations—including natural events, does her urban White counterpart (Figure 2).
PM2.5 concentration data. Disparities in ex- roadway activity, and the formation of sec- An additional strength of our analysis is the posure between Blacks and Whites have been ondary PM from precursor pollutants—this inclusion of the total amount of pollutants reported to be greater than are disparities on metric should not be interpreted as a direct emitted at each site, as opposed to only the the basis of poverty status,16 whether con- measure of PM exposure. Aggregation of presence or absence of a nearby facility. As sidering only urban, suburban, or rural census burdens to the census tract level allowed us seen in Table 1, the proportional burden in tracts.17 This potential increase in exposure to compare our absolute burden assignments facility number for Blacks is only 1.09; the
for the Black population coupled with higher to EPA’s Fused Air Quality Surface Using proportional burdens in total PM2.5 (1.54) 29 prevalence of conditions such as cardiovas- Downscaling model of PM2.5 daily con- and PM10 (1.49) are much higher. This is cular disease mortality25 and asthma,26 which centration averages for 2011. Despite the consistent with studies suggesting that scaling are known to be linked to PM exposure, presence of small racial disparities in resi- sites by the amount of pollution emitted 32 makes for a population of concern. Equiva- dential ambient PM2.5 for the contiguous can further reinforce findings of inequity. lent increases in PM2.5 have been linked to United States (Table F), mean ambient PM2.5 The difference between disparities in facility statistically significantly higher associations in concentration and tract PM2.5 burden from number and disparities in total PM implies Blacks than in Whites for health outcomes emissions were only weakly correlated that the few extra facilities near the average ranging from asthma attacks27 to overall (Spearman r = 0.30). However, there are Black residence tend to be among the highest mortality.28 In the US Medicare population, benefits to understanding proximity that go emitters. The distribution shown in Figure 1 Blacks who are not eligible for Medicaid (a beyond direct health impacts, including suggests that a relatively small proportion of proxy for higher economic status) have higher monetary reasons. Nearby pollution- the US population bears the vast majority of
PM2.5-related mortality risk than do Whites generating sites are a tangible and accessible burden from PM2.5 emissions. Analysis on the who are eligible.28 marker of pollution, and residents’ awareness basis of the EPA’s Toxic Release Inventory Our analysis considered disparities at var- of such sites is demonstrated by the negative shows that extremely high-polluting “toxic ious scales. Racial disparity at the national effect on housing values.30 outliers” tend to exist in places with higher scale is driven by high emissions in areas with Our method of assignment was to link non-White and low-income populations.33 high non-White populations. However, areas facilities to all block groups that had a centroid with a proportionately higher White pop- within a set radius of the coordinates given in ulation may still be internally inequitable. The the NEI. Centroid-containment and other Public Health Implications few non-Whites who do reside in such an area distance-based methods employing circular This research demonstrates an aspect of are disproportionately likely to live near buffers are better equipped than is unit– a multifaceted public health problem faced by a source of PM emissions. Figure A, part hazard coincidence (i.e., the assignment of marginalized groups. As was exemplified in a highlights such areas; the largely White point sources to only their host census unit) in the EPA’s investigation of racially discrimi- Midwestern states contain some of the most assigning nearby hazards to a population.15,31 natory treatment in a public participation 9 disproportionately high internal PM2.5 bur- Unit–hazard coincidence inherently de- process, the lack of political capital is an den for non-Whites. Indiana, for instance, emphasizes the impact of facilities near bor- obstacle to obtaining more desirable living is more than 80% White, but the dis- ders, which becomes increasingly important conditions. In addition, social and economic proportionality in non-White burden is in small, dense, urban block groups. The challenges can lead marginalized people to greater there than in any other state. Mohai result is an overrepresentation of large, rural further populate an area made less desirable by
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proximity to sources of pollution.19 The the Americans’ Changing Lives Study. Am J Public Health. 19. Mohai P, Saha R. Which came first, people or pol- – potential health effects of the resulting en- 2009;99(suppl 3):S649 S656. lution? Assessing the disparate siting and post-siting de- 3. Clark LP, Millet DB, Marshall JD. Changes in mographic change hypotheses of environmental injustice. vironmental burdens on these groups should Environ Res Lett. 2015;10:115008. transportation-related air pollution exposures by race- be considered in conjunction with existing ethnicity and socioeconomic status: outdoor nitrogen 20. Borrell LN. Racial identity among Hispanics: im- health disparities: access to health care has dioxide in the United States in 2000 and 2010. Environ plications for health and well-being. Am J Public Health. – well-documented disparities by race/eth- Health Perspect. 2017;125(9):097012. 2005;95(3):379 381. nicity,34 and the prevalence of certain diseases 4. Brender JD, Maantay JA, Chakraborty J. Residential 21. Palloni A, Arias E. Paradox lost: explaining the proximity to environmental hazards and adverse health Hispanic adult mortality advantage. Demography. 2004; is notably higher in non-White pop- outcomes. Am J Public Health. 2011;101(suppl 1): 41(3):385–415. 25,26 – ulations. Along with other inequitable S37 S52. 22. Maantay J. Asthma and air pollution in the Bronx: social and physical determinants of health, 5. US Environmental Protection Agency. Particulate methodological and data considerations in using GIS for these interlocking mechanisms must all be matter (PM) basics. Available at: https://www.epa.gov/ environmental justice and health research. Health Place. 2007;13(1):32–56. addressed to establish environmental and pm-pollution/particulate-matter-pm-basics. Accessed April 6, 2017. 23. Kouznetsova M, Huang X, Ma J, Lessner L, Carpenter public health justice. 6. Franklin M, Zeka A, Schwartz J. Association between DO. Increased rate of hospitalization for diabetes and We have presented a framework with PM2.5 and all-cause and specific-cause mortality in 27 US residential proximity of hazardous waste sites. Environ – which to consider the racial and economic communities. J Expo Sci Environ Epidemiol. 2006;17(3): Health Perspect. 2007;115(1):75 79. disparities in residential proximity to sources 279–287. 24. Choi HS, Shim YK, Kaye WE, Ryan PB. Potential of pollution in the United States. We have 7. Pope CA, Dockery DW. Health effects of fine par- residential exposure to toxics release inventory chemicals ticulate air pollution: lines that connect. J Air Waste Manag during pregnancy and childhood brain cancer. Environ – shown that a focus on poverty to the ex- Assoc. 2006;56(6):709–742. Health Perspect. 2006;114(7):1113 1118. clusion of race may be insufficient to meet the 8. Brook RD, Rajagopalan S, Pope CA, et al. Particulate 25. Mensah GA, Mokdad AH, Ford ES, Greenlund KJ, needs of all burdened populations. Applica- matter air pollution and cardiovascular disease: an update Croft JB. State of disparities in cardiovascular health in the – tion of this knowledge can be a valuable to the scientific statement from the American Heart United States. Circulation. 2005;111(10):1233 1241. – resource in improving equity. Disparity Association. Circulation. 2010;121(21):2331 2378. 26. Centers for Disease Control and Prevention. Trends in 9. US Environmental Protection Agency. 01R-94-R5 asthma prevalence, health care use, and mortality in the persists at multiple scales of observation, – MDEQ closure letter. 2017. Available at: https://www. United States, 2001 2010. 2012. Available at: https:// and this suggests that solutions can also be epa.gov/ocr/01r-94-r5-mdeq-closure-letter. Accessed www.cdc.gov/nchs/products/databriefs/db94.htm. Accessed April 17, 2017. approached on multiple levels. March 24, 2017. 27. Nachman KE, Parker JD. Exposures to fine particulate 10. Boyce JK, Pastor M. Clearing the air: incorporating air CONTRIBUTORS air pollution and respiratory outcomes in adults using two quality and environmental justice into climate policy. national datasets: a cross-sectional study. Environ Health. I. Mikati led project design, data analysis, and writing. Clim Change. 2013;120(4):801–814. A. F. Benson contributed to design, writing, and data 2012;11:25. 11. US Census Bureau. American Community Survey visualization. T. J. Luben, J. D. Sacks, and J. Richmond- 28. Di Q, Wang Y, Zanobetti A, et al. Air pollution and (ACS). Available at: https://www.census.gov/programs- Bryant supported project design and writing. mortality in the Medicare population. N Engl J Med. 2017; surveys/acs. Accessed April 17, 2017. 376(26):2513–2522. 12. US Census Bureau. How the census bureau measures ACKNOWLEDGMENTS 29. US Environmental Protection Agency. RSIG-related poverty. Available at: https://www.census.gov/topics/ This research was supported in part by an appointment downloadable data files. Available at: https://www.epa. income-poverty/poverty/guidance/poverty-measures. to the Research Participation Program for the US Envi- gov/hesc/rsig-related-downloadable-data-files. Accessed html. Accessed August 1, 2017. ronmental Protection Agency (EPA), Office of Research April 17, 2017. and Development, administered by the Oak Ridge In- 13. US Department of Agriculture. 2010 rural–urban 30. Davis LW. The effect of power plants on local housing stitute for Science and Education through an interagency commuting area (RUCA) codes documentation. Avail- values and rents. Rev Econ Stat. 2011;93(4):1391–1402. agreement between the US Department of Energy and the able at: https://www.ers.usda.gov/data-products/rural– EPA. urban-commuting-area-codes/documentation. Accessed 31. Chakraborty J, Maantay JA, Brender JD. Dispro- We thank Julian Marshall for his suggestions on April 17, 2017. portionate proximity to environmental health hazards: strengthening the study design and Danelle Lobdell and methods, models, and measurement. Am J Public Health. 14. US Environmental Protection Agency. 2011 Na- Jen Nichols for their helpful comments on the article. 2011;101(suppl 1):S27–S36. tional Emissions Inventory (NEI) data. Available at: Note. This document was reviewed in accordance https://www.epa.gov/air-emissions-inventories/ 32. McMaster RB, Leitner H, Sheppard E. GIS-based with EPA policy and approved for publication. Mention 2011-national-emissions-inventory-nei-data. Accessed environmental equity and risk assessment: methodolog- of trade names or commercial products does not constitute April 17, 2017. ical problems and prospects. Cartogr Geogr Inform. 1997; endorsement or recommendation for use. The views 24(3):172–189. 15. Mohai P, Saha R. Reassessing racial and socioeco- expressed in this article are those of the authors and do not “ ” necessarily reflect the views or policies of the EPA. nomic disparities in environmental justice research. De- 33. Collins MB, Munoz I, JaJa J. Linking toxic outliers mography. 2006;43(2):383–399. to environmental justice communities. Environ Res Lett. 2016;11(1):015004. HUMAN PARTICIPANT PROTECTION 16. Bell ML, Ebisu K. Environmental inequality in ex- 34. Smedley BD, Stith AY, Nelson AR, eds. Unequal No protocol approval was necessary because all data were posures to airborne particulate matter components in the Treatment: Confronting Racial and Ethnic Disparities in Health obtained from publicly available secondary sources. United States. Environ Health Perspect. 2012;120(12): Care. Washington, DC: National Academies Press; 2003. 1609–1704. REFERENCES 17. Bravo MA, Anthopolos R, Bell ML, Miranda ML. 1. US General Accounting Office. Siting of hazardous Racial isolation and exposure to airborne particulate waste landfills and their correlation with racial and eco- matter and ozone in understudied US populations: en- nomic status of surrounding communities. 1983. Avail- vironmental justice applications of downscaled numerical able at: http://www.gao.gov/products/RCED-83-168. model output. Environ Int. 2016;92–93:247–255. Accessed March 13, 2017. 18. US Census Bureau. Comparing ACS data. Available 2. Mohai P, Lantz PM, Morenoff J, House JS, Mero RP. at: https://www.census.gov/programs-surveys/acs/ Racial and socioeconomic disparities in residential guidance/comparing-acs-data.html. Accessed April 11, proximity to polluting industrial facilities: evidence from 2017.
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Page 1 of 10
Energy and Buildings 143 (2017) 25–34
Contents lists available at ScienceDirect
Energy and Buildings
j ournal homepage: www.elsevier.com/locate/enbuild
The intersection of energy and justice: Modeling the spatial,
racial/ethnic and socioeconomic patterns of urban residential heating
consumption and efficiency in Detroit, Michigan
∗
Dominic J. Bednar , Tony Gerard Reames, Gregory A. Keoleian
Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan, 440 Church St., Ann Arbor, MI 48109, United States
a r t i c l e i n f o a b s t r a c t
Article history: Residential energy conservation and efficiency programs are strategic interventions to reduce consump-
Received 18 August 2016
tion and increase affordability. However, the inability to identify and distinguish between high energy
Received in revised form 19 February 2017
consumers and highly energy inefficient households has led to ineffective program targeting. Addition-
Accepted 9 March 2017
ally, little is known about the spatial, racial and socioeconomic patterns of urban residential energy
Available online 12 March 2017
consumption and efficiency. Publicly available data from the U.S. Energy Information Administration
and the U.S. Census Bureau are used with bottom-up modeling and small-area estimation techniques to
Keywords:
predict mean annual heating consumption and energy use intensity (EUI), an energy efficiency proxy, at
Fuel poverty
the census block group level in Detroit (Wayne County), Michigan. Using geographic information sys-
Energy justice
tems, results illustrate spatial disparities in energy consumption and EUI. Bivariate analysis show no
Energy consumption
Energy efficiency statistical relationship between race/ethnicity and energy consumption; however, EUI is correlated with
−
Spatial analysis racial/ethnic makeup; percent White ( 0.28), African American (0.24) and Hispanic (0.16). Income and
Space heating housing tenure reveal inverse relationships with consumption and efficiency. Though areas with higher
Residential buildings
median incomes and homeownership exhibited higher consumption (0.28 and 0.56, respectively), they
−
had lower EUIs ( 0.48 and −0.38, respectively). This study provides evidence supporting approaches for
conservation and energy efficiency program targeting that recognizes the significance of race, ethnicity,
place and class.
© 2017 Elsevier B.V. All rights reserved.
1. Introduction low household incomes, rising energy costs and energy inefficient
homes [3].
Residential utility costs place a disproportionate burden on Amid solutions to alleviate fuel poverty, energy conservation
low-income households. Following the Great Recession, nearly 14 and efficiency retrofit programs have proven successful [5–8].
million American households had utility bills in arrears and 2.2 mil- However, the inability to identify and distinguish between house-
lion households experienced utility shutoffs [1]. Residential energy holds with high energy consumption compared to those that
burdens, or the percentage of annual income spent on energy costs are highly energy inefficient has halted interventions from utiliz-
are a major source of utility hardship. While the average American ing systematic approaches to appropriately and effectively target
household spends 7.2% of their annual income on residential energy energy conservation and efficiency programs.
costs, the average low-income household has an energy burden The need for more effective targeting is supported by previous
nearly double, spending 13.8% [2]. Energy burden disparities are studies exploring the spatial dynamics of energy consumption that
often expressed through the concept of fuel poverty, also referred find distinguishable spatial disparities in both consumption and
1
to as energy insecurity [3,4]. Fuel poverty reflects an inability of energy use intensity (EUI). For instance, Heiple and Sailor [9] using
a household to meet basic energy needs or to adequately heat or national data, building energy simulation and geospatial modeling
cool their home [3]. Fuel poverty results from the interplay between
1
According to the U.S. Department of Energy, “Declines in energy intensity are
a proxy for efficiency improvements, provided a) energy intensity is represented
∗
Corresponding author. at an appropriate level of disaggregation to provide meaningful interpretation, and
E-mail addresses: [email protected] (D.J. Bednar), [email protected] b) other explanatory and behavioral factors are isolated and accounted for” (DOEa)
(T.G. Reames), [email protected] (G.A. Keoleian). [52].
http://dx.doi.org/10.1016/j.enbuild.2017.03.028
0378-7788/© 2017 Elsevier B.V. All rights reserved. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16
Page 2 of 10
26 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34
techniques found variations in peak energy profiles for electricity best predictors to model energy consumption and efficiency, for
and natural gas across building types in Houston, Texas. Howard instance, energy characteristics of housing structure and a selection
et al. [10] built models from citywide data to estimate building sec- of householder characteristics; then, connect to matching spatial
tor EUI finding major differences in the magnitude of consumption data (i.e. census data).
and spatial variation across New York City. Santamouris et al. [11] A growing body of literature investigating geographical
conducted interviews on household and housing unit characteris- approaches to target fuel poverty in Europe have used this approach
tics finding higher costs per person and unit area for low-income [26–29]. Fahmy [26] developed regression models to predict the
residence in Athens. These studies provide rich information on incidence of fuel poverty in England using sample survey data and
the relationship between place and energy consumption; however, applied resultant weights to Census spatial data sets. Similarly,
their focus on both commercial and residential energy consump- Walker and Day [30] developed a small area fuel poverty risk index
tion makes it difficult to identify residential energy disparities for using environmental and socioeconomic variables via geographi-
program targeting. Moreover, few studies investigate correlations cal methods finding significant clusters of high and low-risk areas.
between residential energy consumption, efficiency, race/ethnicity “The underlying idea is that there are higher probabilities of fuel
and socioeconomic status for a more holistic understanding of poverty in particular areas and/or housing types” [31].
urban residential energy dynamics. Reames [12] developed a model In the U.S., Min et al. [32] applied this approach for spatially
estimating urban residential heating EUI and found positive rela- modeling national residential energy consumption end uses. Com-
tionships with areas with higher percentages of racial minorities bining regression models based on national data from the U.S.
and lower socioeconomics. Albeit some exploration, little remains Energy Information Administration’s (EIA) Residential Energy Con-
known about the spatial, racial and socioeconomic differences sumption Survey (RECS) with U.S. Census data, they mapped energy
between residential energy consumption and efficiency. consumption estimates for space heating, cooling, water heating
To this end, this paper develops models for residential heat- and all other electrical uses at the zip code level. Reames [12] used
ing consumption and efficiency at the census block group level both the RECS and Census data to explore racial and socioeconomic
and explores the spatial patterns alongside racial and socioeco- disparities in the spatial distribution of urban heating EUI. Both
nomic relationships in Detroit (Wayne County), Michigan. The studies found that significant predictors of energy consumption
remainder of this paper is structured as follows. Section 2 presents and EUI included age of housing unit, type of housing unit, number
background information on modeling energy consumption, effi- of rooms, type of heating fuel and household income.
ciency and disparities. Section 3 describes the study area, data
and methodological framework for first developing two regression
3. Data and methodology
models to estimate residential heating energy consumption and
heating EUI, then secondly, using small area estimation techniques
3.1. Description of study area
to predict consumption and EUI in the study area. Section 4 presents
results of the regression models, spatial distributions of results
Detroit (Wayne County) is the largest urban area in the State
mapped using geographic information systems (GIS) and bivariate
of Michigan and represents nearly 20% of the state population.
analysis of the relationship between predicted energy consump-
According to the 2010 decennial census, the county had a total pop-
tion and efficiency with selected racial and socioeconomic block
ulation of 1,820,584 residents in 821,693 housing units. Michigan
group characteristics. Section 5 discusses key results, policy impli-
homes are typically older than homes in other states. Nearly three-
cations and study limitations. Lastly, concluding remarks and areas
quarters of housing stock in Detroit (Wayne County) was built
of future research are presented in Section 6.
before 1970. Fig. 1 illustrates the distribution of housing stock age,
displaying the median year built for block group housing structures.
Socioeconomic characteristics vary in the study area. Detroit
2. Background
exhibits a high and increasing level of residential segregation by
income. The Pew Research on Social and Demographic Trends found
To understand the factors that impact energy consumption,
that the Detroit metropolitan area’s RISI score increased from 43
scholars apply two general frameworks: the physical-technical- 2
in 1980–54 in 2010 [33]. Fig. 2 displays the spatial distribution
economic model (PTEM) and the lifestyle and social-behavioral
of block group median household incomes, ranging from $6833 to
tradition (LSB) [13–23]. In 1993, Lutzenhiser proposed the PTEM
$183,462 per year. Households in the Detroit metropolitan were
tradition arguing that the physical characteristics of buildings,
hit particularly hard during the economic recession and recovery.
investment in technical energy efficiency, energy prices and envi-
A survey of Detroit metropolitan area households found that 1 in 2
ronmental factors are integral to understanding and managing
respondents reported experiencing some type of material hardship
energy consumption. On the other hand, the LSB tradition con-
[34]. While roughly 14% of high-income households fell behind on
tends that these factors alone can only offer minimal explanation
utility payments, nearly 40% of low-income households reported
of energy consumption in the built environment and draws atten-
being behind and were seven times more likely to have a utility
tion to the importance of human occupants of the building, such
shutoff [34].
as, social (noneconomic), behavioral, cultural and lifestyle factors
Detroit has long been the most segregated metropolitan area
[13,14,17–20,24,25]. The models developed for this study include
in the nation, having a majority African American and Hispanic
variables merging the PTEM and LSB modeling traditions for a more
city population and a majority White suburban population [35].
holistic understanding of residential energy consumption and effi-
This segregation is evident in Fig. 3, a dot density map illustrating
ciency.
Individual housing unit energy data is often not readily avail-
able for exploring residential energy dynamics at various spatial
2
scales. Thus, the absence of detailed information on residential The Pew Research Center developed a single Residential Income Segregation
energy use presents an impediment to spatially identifying fuel Index (RISI) score for the nation’s top 30 metropolitan areas. The score is cal-
culated by summing the share of lower-income households living in a majority
poor households and developing strategic conservation and effi-
lower-income tract and the share of upper-income households living in a major-
ciency program targeting. As a result, scholars have employed
ity upper-income tract. The maximum possible RISI score is 200, indicating that
small area estimation statistical techniques to spatially explore
100% of lower-income and 100% of upper-income households would be situated in
residential energy patterns. This approach requires finding the a census tract where most households were in their same income bracket. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16
Page 3 of 10
D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34 27
Fig. 1. Block group median structure year built.
the spatial distribution of residents by race/ethnicity. The house- households were surveyed to represent the state’s 4.5 million occu-
hold racial/ethnic composition included 52.3% White, 40.5% African pied housing units. Since the scope of this study focuses on annual
American and 5.2% Hispanic households. Historically marginalized space heating, six of the total 274 observations were removed from
communities of color in Detroit experience higher rates of arrears the sample because of missing heating data, resulting in 268 total
3
and shutoffs. For instance, African Americans were almost twice as observations for this study.
likely as non-African Americans to report being behind on utilities Spatial data for modeling and mapping the study area were
payments and more than three times more likely to experience a obtained from U.S. Census Bureau 2006–2010 American Commu-
utility service shutoff than non-blacks [34]. nity Survey (ACS) [37,38] 5-year estimates. This survey is issued
Michigan households experience harsher winters increasing the each year to provide current information about social and eco-
average household demand for space heating to 55% of total energy nomic needs of the community. Households are sampled randomly
consumption compared to 41% nationally [2]. Consequently, Michi- in each state, including Puerto Rico to provide a representative sam-
gan households also consume 38% more energy and spend six ple. The census block group was used as the unit of analysis, as the
percent more than the average U.S. household [2]. Thus, space most appropriate spatial resolution for household and housing unit
heating is the ideal energy end use for investigating patterns and characteristics data [12]. A GIS data layer of Wayne County cen-
disparities in consumption and efficiency. sus block groups was created by clipping the U.S. Census Bureau
TIGER/Line Shapefile with demographic and economic data from
the 2006–2010 ACS [37,38] 5-year estimates. Block groups were
3.2. Data
only retained if both population and number of occupied housing
units were greater than zero. Subsequently, 1808 of 1822 block
In the absence of detailed individual energy data for every
groups were included in this analysis.
household in the study area, the EIA’s RECS provides household-
The RECS microdata set can be used to develop a bottom up
level data for a representative sample of occupied, primary
statistical model. These models have been used to explore rela-
residences at the state-level. First conducted in 1978, RECS
tionships between household energy consumption and various
collected data on energy consumption, annual expenditure,
exogenous variables [39,40,32,12,41]. Statistical models also allow
energy-related behavior, household demographics and housing
for capturing consumption variations due to demographic and
unit characteristics. Using a multi-stage, area probability design,
carefully controlled at specific levels of precision, the 2009 RECS
microdata set (released in 2013) has a sample size of 12,083 hous-
3
For a 95 percent confidence interval, a sample size of 246 RECS observations are
ing units representing the U.S. Census Bureau’s statistical estimate
needed to prove statistical significance. For geographic domain estimation purposes,
of 113.6 million occupied primary residences [36]. The RECS allows
base sampling w(YˆHeat ) or (YˆEUI ).eights were applied to each housing unit. Each
for state-level analysis with the collection of representative sam-
sampling weight value was used as a weighting factor in the weighted regression
ples in 12 states, including Michigan. A sample of 274 Michigan model. U-20471 Official Exhibits of Soulardarity Exhibit SOU-16
Page 4 of 10
28 D.J. Bednar et al. / Energy and Buildings 143 (2017) 25–34
Fig. 2. Block group median household income.
socioeconomic characteristics. Similar variables found in both the the predictor variables, housing unit characteristics (age of home,
RECS and ACS allow relationships derived from statistical models type of heating fuel, type of home and size of home) and control-
using RECS, known as direct estimates, to be applied to block group ling for household characteristics (household ownership, number
level ACS spatial data as indirect estimators for constructing small- of household members and household income). Dependent vari-
area estimates with the assumption that the small area exhibits the ables were natural log values of per-household final consumption
same characteristics as the large area [42]. The next section clarifies and EUI for heating. The models are formulated as:
this methodological framework.
ln(Y ) = ˇ + ˇ ∗ + ˇ ∗ , (1) Heat 0 Housing unit Household RECS RECS
Y
ln( ) = ˇ + ˇ ∗ + ˇ ∗ (2)
EUI 0 Housing unit RECS Household RECS
3.3. Methodological framework for estimating block group
heating consumption and efficiency where:
YHeat is energy consumption in MJ,
2
The goal of this study is to explore residential heating con- YEUI is EUI in MJ/m ,
ˇ
sumption and efficiency at a geographic domain smaller than the 0 is the regression intercept,
ˇ
RECS microdata, which is collected with adequate precision at a HousingUnit is the resultant weight for housing unit characteris-
state-level scale. Fig. 4 displays a schematic of the methodological tics,
ˇ
framework for estimating heating energy consumption and EUI at Household is the resultant weight for household characteristics,