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Infrastructure Working Council Meeting: Presentations Day One Infrastructure Working Council Meeting: Presentations Day One June 2014 E3 Higher RPS Study Briefing for EPRI IWG June 18, 2014 Key Study Question What are the requirements, operational challenges, potential solutions, costs and consequences of integrating 50% RPS by 2030 in California? Incremental Renewable Energy to meet… 50% RPS (27 TWh) 46 TWh 40% RPS (19 TWh) 33% RPS (4 TWh) Renewable generation needed to meet 33% RPS by 2020 (85 TWh) 2 50% RPS is a New Challenge California still does not have operating experience at 33% RPS No other country or state has achieved an equivalent RPS above 30% anywhere in the world • Germany: 22% renewables in 2012 • 7.4% wind, 4.5% solar • Spain: 24% renewables in 2012 • 18% wind, 4% solar • Denmark: 30% wind in 2012 • Assisted by interconnections with Germany & Norway • Norway, New Zealand & British Columbia achieve higher renewable penetrations with large hydroelectric resources which do not count towards RPS in California 3 Sizing up the famous duck chart The CAISO duck chart illustrates operational challenges at 33% RPS It shows just a single day in March as renewables rise to 33% E3’s study looks at thousands of potential operating days as renewables rise to 50% Core question: How serious and pervasive are operating challenges as renewable penetration rises above 33%? Dog days and duck days: Managing Net Load will be the challenge Sweltering Summer Day Delightful Spring Day High Variable Renewable Penetration Stresses the Grid in New Ways “Dog Days” “Duck Days” Highest Load Day Highest Ramp Day Historical system planning challenge: Historically an easy day to manage meet gross peak load on hottest days Emerging system planning challenge: High renewable penetration makes net manage diurnal swings in net load peak lower and later Need enough flexibility Need enough generating capacity Example Day in April: 33%, 40% and 50% RPS E3’s REFLEX model simulates how the system operator dispatches available resources to manage net load Overgeneration • Occurs when system cannot absorb all renewable energy without risking an outage. • Shown in red Overgeneration increases above 33% • Can be very high under the 50% Large Solar case • Diversifying the renewable portfolio reduces overgeneration • Fossil generation is reduced to minimum levels needed for reliability 7 Overgeneration is extensive and can occur in any month Average overgeneration (MW) by month-hour, 50% Large Solar Case: Hour of the Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Overgeneration, MW Jan 12,000 Feb 10,000 Mar Apr 8,000 May Jun 6,000 Jul Aug 4,000 Sep Oct 2,000 Nov Dec 0 8 E3 investigated several potential solutions Potential solutions: • Diversified portfolio (more wind and geothermal, less solar) • Enhanced regional coordination • Conventional demand response (down only) • Advanced demand response (down and up) • Energy storage PEVs not modeled explicitly, but managed charging is similar to advanced DR and energy storage Solutions considered individually (each @ 5000 MW) Solutions may be combined: • Further study needed to identify optimal combination • Best mix of solutions depends on renewable portfolio 9 Potential Integration Solution: Advanced Demand Response PEVS are a potential source of flexible load Charge during day at work and late at night at home V2G provides an extra boost (discharge early evening) 10 Potential Integration Solution: Energy Storage Case Adding 5,000 MW of diurnal energy storage in CA reduces overgeneration Storage charges during the day & discharges at night. PEVs can do this! Example April day 11 Some implications for PEVs Value proposition for PEVs shifting away from managing system peak load toward helping manage daily swings in solar generation Frequency regulation will be less important From a grid perspective PEVs represent a huge and growing reservoir of low cost energy storage Requires pervasive workplace charging, cars plugged in throughout the day TOU as we know it will become irrelevant and dynamic pricing/DR will be more important Aggregation and automation are the key: consistent standards, communications, metering are essential for PEVs to be a true grid resource 12 Implications of high renewable penetration differ by region: depends on renewable resource mix Projected Capacity and Generation Mix by Region in 2050 NREL Incremental Technology Improvement 80% Renewable Scenario Onshore Wind Dominates Offshore Wind Dominates Solar Dominates Mostly Biomass and PV Source: National Renewable Energy Laboratory, Renewable Electricity Futures Study, p. 3.6 http://www.nrel.gov/docs/fy12osti/52409-1.pdf Thank You! Nancy E. Ryan Director, Policy and Strategy Energy + Environmental Economics (E3) [email protected] http://www.ethree.com/public_projects/renewables_portfolio_standard.php Supplemental Slides REFLEX uses a novel simulation approach to analyze 2030 integration challenges The Renewable Energy Flexibility (REFLEX) approach uses stochastic production simulation to understand grid stresses in 2030 resulting from 50% RPS (+7000 MW of solar PV) • Grid dispatch for hundreds of simulated days • 63 years of load conditions, 42 years of hydro, 3 years of solar, 3 years of wind • 24 hours of time-sequential operations in day-ahead, hour-ahead and five- minute time-steps Calculates the likelihood, magnitude, duration and cost of flexibility violations to inform solutions 10000 80000 5000 8000 4000 60000 6000 3000 40000 4000 2000 Load (MW) Load 20000 2000 1000 Power (MW) Solar Wind Power (MW) Power Wind 0 0 0 0 10 20 0 10 20 0 10 20 Hour of Day Hour of Day Hour of Day Load Wind Solar 16 Four related planning challenges 1. Downward ramping capability 3. Upward ramping capability Thermal resources operating to serve loads at Thermal resources must ramp up quickly from night must be ramped downward and potentially minimum levels during the daytime hours and new shut down to make room for a significant influx of units may be required to start up to meet a high net solar energy after the sun rises. peak demand that occurs shortly after sundown. 2. Minimum generation flexibility 4. Peaking capability Overgeneration may occur during hours with high The system will need enough resources to meet the VER production even if thermal resources and highest peak loads with sufficient reliability imports are reduced to their minimum levels. A system with more flexibility to reduce thermal generation will incur less overgeneration. 17 Overgeneration Statistics Overgeneration is minimal at 33% RPS, but increases to nearly 9% of available renewable energy under the 50% RPS Large Solar scenario 50% RPS Overgeneration Statistics 33% RPS 40% RPS Large Solar Total Overgeneration GWh/yr. 190 2,000 12,000 % of available RPS energy 0.2% 1.8% 8.9% Overgeneration frequency Hours/yr. 140 750 2,000 Percent of hours 1.6% 8.6% 23% Extreme Overgeneration Events 99th Percentile (MW) 610 5,600 15,000 Maximum Observed (MW) 6,300 14,000 25,000 18 Smart Grid Integration into the Internet of Things Benefits of a bigger picture June 18, 2014/EPRI IWC Slav Berezin, General Motors 1 So, what is the “Internet of Things”? IoT Source: IEEE Standards Association June 18, 2014/EPRI IWC Slav Berezin, General Motors 2 Global Energy Demand Source: U.S. EIA (Energy Information Administration) Electricity consumption rising, as global population increases, even in a slowly growing global economy (from 20,300 TWh in 2008 to 33,000 TWh in 2030) June 18, 2014/EPRI IWC Slav Berezin, General Motors 3 Smart Grid “Big Bang” … Efficient Energy Generation and Distribution combined with Advanced Monitoring and Control Source: STMicroelectronics June 18, 2014/EPRI IWC Slav Berezin, General Motors 4 Smart Technology “Universes” … Beyond Smart Grid one, they exist for home automation/entertainment, remote patient monitoring, etc. Source: STMicroelectronics June 18, 2014/EPRI IWC Slav Berezin, General Motors 5 How did we get there? WOW! By combining various features/functionality onto a single platform and allowing others to develop applications for it… Plus the “Wow” factor of course! June 18, 2014/EPRI IWC Slav Berezin, General Motors 6 So where is the “common ground”? Where the majority Public of charging is taking place nowadays Source: Global Sustainable Lifestyle Network, Inc Workplace Observe customer’s behavior Residential Predict customer’s needs Anticipate “the next big thing” June 18, 2014/EPRI IWC Slav Berezin, General Motors 7 Home as the Center of IoT ‘Universe’ for Smart Grid Solar Panel Home Controller & Lighting control Multimedia Gateway Vehicle to Grid Smart Appliances & load management Smart Meter June 18, 2014/EPRI IWC Slav Berezin, General Motors Source: STMicroelectronics 8 Applications vs. Communication Pathways 1) The use cases (application) for EV to Grid Communications have driven development and standardization of the link’s PHY layer (PLC) The immediate implementation of this link is delayed due to presently weak business case 2) Nevertheless, new applications can be developed which could be found attractive to interested consumers 1 2 Bundling Smart Grid related services may help to improve the business case 3) Integration of a smart grid applications suite as a whole into a much broader marketplace is more likely to lead to the acceleration of developments for overall customer needs around the home, including EVs! June 18, 2014/EPRI IWC Slav Berezin, General Motors 9 Hybrid Home Networking . IEEE 1905.1 defines an abstraction layer that provides a common interface for the most compelling and deployed home networking technologies in the market. A broad base of industry-leading chipmakers, equipment manufacturers and service providers collaborated to publish the Standard in 2013. Great for the industry--enhances user experience and enables next generation connected services for consumers. June 18, 2014/EPRI IWC Slav Berezin, General Motors 10 Future Hybrid Home Networking . IEEE 1905.1a Standard for a Convergent Digital Home Network for Heterogeneous Technologies Amendment: Support of new MAC/PHYs and enhancements.
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