Evaluating the grid impact of plug-in electric vehicles using dynamic commuting profiles

摘要

We analyze the actual commuting profiles of vehicles in the US and develop a statistical model to fit the observed data. Subsequently, this model is leveraged in a simulation framework to simulate the behavior of fleets of Plug-in Electric Vehicles (PEV), analyze their impact on the grid and, compute the effective load carrying capacity (ELCC) contributed by PEVs. We develop methodologies to quantify ELCC impact of various scenarios, including (1) restrictions on when PEVs can be charged or discharged, and (2) how the commuting times are distributed throughout the day. The model is run with 4-year actual load data from New York City (NYC) and PEV performance specifications of Chevy Volt to obtain ELCC contribution figures for PEV fleet sizes going up to 50% penetration. Our results show that up to 7% of peak capacity in NYC can be supplied by PEVs at a 25% penetration level.