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Using Smart Grid Data to Improve Planning, Analytics and Operations A Utility Perspective
Presented by: Karen Lefkowitz Vice President, Business Transformation July 29, 2014 Pepco Holdings, Inc. Quick Facts • Incorporated in 2002 • Service territory: 8,340 square miles • Customers served – Atlantic City Electric: • 545,000 – electric – Delmarva Power: • 503,000 – electric • 125,000 – natural gas – Pepco: • 793,000 – electric • Total population served: 5.6 million Smart Grid Devices and Technologies
Customer Meter Collector Substation Central Operations PJM
Home Intelligence Feeder Automation Substation Automation Transmission Automation
Advanced Metering • Smart Meter Infrastructure
• Automatic Sectionalizing & • Automatic Circuit Reclosers (ACRs) Restoration (ASR) scheme • Automatic Sectionalizing and Tie • Substation Local Area Network Switches • Microprocessor, or ‘Smart’ Relays Distribution • Advanced Voltage Control • Application Servers Automation • VAR Control / Capacitors • Smart Monitoring & Controls • Network Protector Monitoring & Control • Distributed Smart Remote Terminal • Network Cable / Vault Monitoring Units (RTUs) • Smart Remote Terminal Units (RTUs) • Voltage Control, Substation-Level by • Fault Detectors Smart Relays or EMS
• Synchrophasor • Motor Operated Disconnect (MOD) Transmission • Dynamic Ratings Automation • State Estimation • High Voltage Direct Current (HVDC) • Static VAR Compensator (SVC)
Demand Response • Smart Thermostat (DLC & Dynamic • In-Home Display Rates) • Plug-In Hybrids
Distributed • Micro-generation (solar, wind) • Upgrades to monitor DG • Upgrades to monitor DG Generation • Electric Vehicles/Vehicle-to-Grid
• Smart Appliances Energy Efficiency • Weatherization 4 Analytics in Progress/Planned
• Grid Analytics Conservation Voltage Reduction Remote Disconnect/Reconnect Outage Detection/Restoration Verification Enhanced Revenue Protection Volt/Var Management and Control High Temperature Detection EV Charging Evaluation/Detection
• Reliability Analytics Dynamic SAIDI and SAIFI Improved Distributed Generation Integration
Focus is shifting from installing the infrastructure to implementing new uses for the customer and improving operational efficiency
Analytics: AMI Data to Information – Successful Results Achieved During Derecho Event . AMI meters sent “last gasp” messages, which were processed by the OMS similar to a customer call . “Last gasp” messages help predict the location and extent of outages . Company personnel can determine if there is line side power at the customer’s meter by “pinging” the meter . 3300 events were closed through the use of pinging . Assists in optimizing crew dispatch
AMI outage detection continues to meet our expectations; further integration into the restoration process planned. 6 Analytics In Progress/Planned
• Asset Management Analytics o Increase Asset Monitoring (sensors) o Transformer Loading o Enhanced Maintenance/Replacement Practices
• Customer Analytics o Critical Peak Rebates - Peak Energy Savings Credit (PESC) o Enhanced Demand Response
• Load Analytics o Load Forecasting o Load Profiling o Load Settlement
Peak Energy Savings Credit Program Introduces a new rate structure with a credit option designed to incent customers to reduce consumption during Peak Energy Periods 1 Peak Energy Savings Credit Enrollment 2 Initiate Peak Energy Period / Notify Customers
Active Notifications
. PHI defaults a customer to Text
PESC rate E-mail
. Voice Customer sets notification . PHI Power Procurement initiates a preferences or opts-out of the Customers have three options – Peak Energy Period for the next phone, text or email – but they may Dynamic Pricing rate (through business day only choose 2 out of the 3 My Account or a CSR) . Customer receives notifications based on his preferences
3 Customer Views Peak Energy Period Results 4 Customer Receives Dynamic Pricing Bill
Load Analysis Module (LAM) . A Dynamic Pricing customer will see interval information in the meter section, a Peak Energy Credit table with event information and Peak Energy Credit savings . Event results are information visible to the customer on the Aclara modules, accessed through My Account 2013 PESC Program Performance Delmarva Power Delaware Event 1 Event 2
Total DSM Reduction (KWh) 684,857 572,285 Average Per Hour Reduction (KWh) 171,214 143,071 Average Rebate $5.38 $5.42 % of Customers Participating 65% 56%
Pepco Maryland Event 1 Event 2
Total DSM Reduction (KWh) 1,588,513 718,924 Average Per Hour Reduction (KWh) 397,128 179,731 Average Rebate $5.96 $4.99 % of Customers Participating 81% 59%
Customers saved 3.5 million kWh and $4.5 million in bill credits; 76% said they would participate in the future Preliminary Analytics on Distribution Transformers Local Distribution System Impact
Transformer Overload Conditions Identified • Potential overload condition identified. • Drill down data analytics may identify potential source of overload. • Field assessment required to assess transformer loading conditions.
Transformer Loading Approaching 90% of
Max Capacity • Possible overload condition identified. • Continuous monitoring required to assess probability of future overloads.
No Overload Conditions Identified • No signs of transformer overloading identified. • Continuous monitoring but no immediate need for preventative assessment. Unmanaged EV charging can create reliability problems for utilities….. Local Distribution System Impact
2 EV = 1 • EV load is equivalent to ½ of full home load, so adding EVs house’s load may overload local transformers • Older, more established neighborhoods with higher Residential concentrations of EVs will be particularly at risk) Washington, DC1 Local Peak Load Increase
297 Vehicles • Most drivers will return home and plug in between 4-8 PM, resulting in an increase to the normal afternoon peak • Uncontrolled charging will create the need for additional Infrastructure and result in longer and higher peak demand • Potential for Impact to Distribution System reliability
Residential Operational Needs San Diego, CA1 725 Vehicles • Metering EVSE as separate load for Innovative Rates • Back-office integration of EVSE for control, billing • Remote diagnostics for lower maintenance costs • Ability to manage charging in pockets to prevent stress on the Distribution System • Need to validate the accuracy of on-board metering in EVSE in order to eliminate the need for a second AMI meter
The EV Project Report, Q1 2013, US DOE1 11
Near-Term Opportunities & Some Possibilities
• Customer to Transformer Validation • Phase Balancing • Customer Phase Connectivity Validation • Distributed Cap Bank Management • Circuit Configuration/Load Balancing • Geo-location Corrections • Smart Appliance Interface & Monitoring • Customized pricing programs
12 Approaching the New Analytics
• Develop a Clear Vision – Increase the Role of Real time Data into the Planning, Construction and Operation of the Grid
• Develop an Analytics Roadmap – Use Case Development
• Transformation of the ‘Department’ based View to an ‘Enterprise’ View – Stakeholder Enrollment with Effective Change Management
Traditional Thinking Must Change . Old ownership model needs to change . Data must become information . Integration of information becomes the new normal
Skill sets are changing . Transactional must become transformational . Data Scientists will be increasingly important . Integration of utility data with outside data will become the norm