Operation Strategy of EV Aggregators Considering EV Driving Model and Distribution System Operation in Integrated Power and Transportation Systems

Recently, the penetration of electric vehicle (EV) has increased, and several motor companies have declared a paradigm shift to EVs. However, most existing studies focusing on EV charging scheduling in power system operations neglect integrated operation transportation distribution systems. Because EVs affect both systems, it is necessary consider grid individual EV’s preferences (charging cost time) simultaneously. In this study, an power-transportation structure algorithms are developed analyze impact system. addition, study proposes optimal driving model that consists two patterns: routine long-distance driving. For patterns, Markov chain implemented considering mileage conditions Subsequently, patterns select route through reinforcement learning. aggregator stations can effectively predict local charge demands perform control real-time. An using IEEE RBTS architecture MATLAB. It utilizes ACOPPF function MATPOWER evaluate systematic stability derive DLMP (Distributed Locational Marginal Price). This conducts performance verification various scenarios, confirming effect aggregators stability, loss reduction (50kWh), entire