Optimal aggregated charging analysis for PEVs based on driving pattern model

Large-scale deployment of plug-in electric vehicles (PEVs) will have a significant impact on the power grid due to the increase in electricity consumption. In this paper, daily driving pattern models are provided and the profile of minimum-cost-least-fluctuation (MCLF) charging load is achieved to evaluate the impact of PEVs on the regional distribution grid. In the daily driving pattern models, four major elements including departure time, arrival time, number of daily trips and trip distance, which have a great influence on charging behavior, are considered. Driving distance of each trip is well approximated by a truncated power-law. Based on these daily driving pattern models, an optimal aggregated charging strategy, which ensures the least fluctuation of charging load at the lowest cost under TOU price, can be established through a two-level optimization model. The two major factors which affect the lower bound of maximum charging load are analyzed. The results show that 7 hours may be a reasonable length of off-peak time to limit the impact of PEV charging.