基于分层深度强化学习的电动汽车实时充电引导策略OA

To realize the real-time charging guidance of electric vehicles and improve the charging efficiency of charging stations,a real-time charging guidance strategy for electric vehicles based on hierarchical deep reinforcement learning was proposed.Considering the mutual coupling characteristics of vehicle-station-road multiple agents,a double-layer electric vehicle charging navigation model was constructed based on the characteristic information of electric vehicles,charging stations,distribution networks and transportation networks.The above-mentioned model was decoupled into a two-layer finite Markov decision process network architecture,the upper network evaluated and recommended charging stations,and the optimal selection result were passed to the lower network.The lower network planed the driving path for the user.The deep Q-network algorithm based on rainbow framework was used to solve the above-mentioned two-layer decision-making process.Finally,the simulation results in a specific urban area show that compared with the disorderly guidance method,the proposed method can reduce the user time cost and save the user cost,and ensure the safe operation of the distribution network.