Emissions Due to Plug-in Hybrid Electric Vehicle Charging in High Wind Systems Allison Weis Roger Leuken Jeremy Michalek Paulina Jaramillo Carnegie Mellon University USAEE Annual Meeting July 29, 2013

Carnegie Mellon University Motivation Electric vehicles are forecasted to make up 2%-15% of vehicle fleet by 2025 Significant wind generation is expected in states with Renewable Portfolio Standards –Fluctuations in wind generation will require additional grid flexibility, some of which could come from controlled electric vehicle charging Electricity sector emissions are key to understanding if electric vehicles cause lower emissions overall compared to gasoline vehicles

Carnegie Mellon University Related Work Operational emissions studies with a simplified model for the electricity system –Stephan and Sullivan –McCarthy and Yang Operational emissions studies with dispatch assuming controlled charging and existing electricity grid –Sioshansi and Denholm –Sioshansi and Miller Full life cycle analysis studies with a simplified model for the electricity system –Michalek et. al. –Hawkins et. al. –Argonne National Lab

Carnegie Mellon University Research Questions Can controlled charging reduce the impact of having electric vehicles on the grid compared to uncontrolled charging? –Cost –Emissions –Damages from emissions How does a high wind penetration change the impacts of electric vehicles and controlled charging?

Carnegie Mellon University System Overview Conventional Power Plants Non-vehicle Load Plug-in Vehicles Energy Balance Wind Power All Vehicles

Carnegie Mellon University Power Grid Data 2010 PJM power plants and 2010 fuel prices by state 5 transmission regions with power limited connections Region 1 TI1-5 Region 3 Region 5 Region 4 Region 2

Carnegie Mellon University Wind Plant Data  Eastern Wind Integration and Transmission Study on-shore production data at a 10-minute resolution  Added by capacity factor (high to low) within PJM region until wind plants capable of producing 20% of the load 7

Carnegie Mellon University Electric Vehicle Profiles Driving profiles from National Household Travel Survey –Charge at home at the end of the day Uncontrolled charging based on all passenger vehicles Controlled charging based on 20 representative profiles 16 kWh battery PHEV (Chevy Volt) 10% of passenger vehicles in PJM (2.4 million) Aggregated Optimized 20

Carnegie Mellon University Unit Commitment and Economic Dispatch Subject to: Generation = Load Spinning reserves Power plant constraints o Minimum and maximum generations levels o Ramp-rate limits o Minimum runtime and downtime Vehicle battery charging o Battery state of charge o Charge rate limits Mixed Integer Linear Program:

Carnegie Mellon University Controlled charging significantly reduces the cost of PHEV charging Controlled Charging Annual Cost Savings Net Savings% of System Costs% of Vehicle Costs PJM Base Wind$127 million0.72%41% 20% Wind$144 million1.05%52%

Carnegie Mellon University Controlled charging of PHEVs increases generation from coal plants Coal Wind Combined Cycle Combustion Turbine Combined Cycle Nuclear Oil/Gas Steam Combustion Turbine Nuclear PJM Base Wind 20% Wind

Carnegie Mellon University Increased wind resources help keep controlled charging from increasing emissions Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled Controlled Uncontrolled

Carnegie Mellon University SO2 CO2 PM25 NOX SO2 VOC Damages due to emissions increase with controlled charging, even with large wind resources Marginal monetary health damages calculated using the APEEP (Air Pollution Emission Experiments and Policy) model CO 2 damages from $35/metric ton social cost of carbon Increase due to SO 2 damages PJM Base Wind 20% Wind

Carnegie Mellon University Key Findings Controlled Charging Cuts the costs of integrating EVs by 40%-50% Reduces energy consumption by about 8% by reducing use of inefficient storage Increases the utilization of low cost plants (particularly coal) Change in Emissions –higher CO 2, PM, SO 2 and NO X emissions –lower VOC and NH 3 emissions Increases damages from EV- integration emissions. 20% RPS Slightly decreases costs of integrating EVs Greatly reduces emissions damages of EV integration With controlled charging –higher wind utilization –lower CO 2, PM, VOC, NO X and NH 3 emissions –higher SO 2 emissions Controlled charging still increases damages

Carnegie Mellon University Future Work Optimize controlled charging using full social costs by including emission prices in objective function Evaluate the emissions and damages from the full life cycle of the vehicles and compare to gasoline vehicles Emissions given future fuel prices and power plant fleet

Carnegie Mellon University Acknowledgements Funding by: Doris Duke Charitable Foundation Richard King Mellon Foundation Electric Power Research Institute Heinz Endowment National Energy Technology Laboratory National Science Foundation CAREER Award # Toyota Motor Corporation National Science Foundation Graduate Research Fellowship Program Carnegie Mellon Electricity Industry Center through the RenewElec project

Carnegie Mellon University Thank you!

Carnegie Mellon University

Unit Commitment and Economic Dispatch Subject to: Generation = Load Minimum and maximum generations levels Ramp-rate limits Minimum runtime and downtime Vehicle battery charging