Stochastic Transactive Control for Electric Vehicle Aggregators Coordination: A Decentralized Approximate Dynamic Programming Approach
IEEE Transactions on Smart Grid(2020)
摘要
With the increasing penetration of renewable energy sources and electric vehicles (EVs), coordinated operation of EV aggregator (EVA) and distribution system operation (DSO) becomes a complex multistage and multidimensional stochastic problem. The motivation behind this paper is to develop a decentralized mechanism to offer a computationally efficient and almost optimal on-line policy for such problem under the framework of transactive energy control (TEC). First, a heterogeneous decomposition-based TEC is designed by utilizing the heterogeneous interactions between DSO and EVA. Then, a decentralized approximate dynamic programming-based algorithm is proposed to offer almost optimal dynamic TEC policies. A decentralized value function approximation approach with temporal difference learning is further employed for entities to learn how to utilize the flexibilities of their resources in response to the stochastic exogenous information. Case studies demonstrate the effectiveness of the proposed algorithm in terms of optimality, robustness, computation efficiency, and scalability.
更多查看译文
关键词
Electric vehicle,transactive energy control,heterogeneous decomposition,decentralized optimization,stochastic optimization,approximate dynamic programming
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络