Supply Function Game Based Energy Management Between Electric Vehicle Charging Stations and Electricity Distribution System Considering Quality of Service

• Published in: IEEE transactions on industry applications Vol. 56; no. 5; pp. 5932 - 5943
• Main Authors: Li, Yuanzheng, Ni, Zhixian, Zhao, Tianyang, Zhong, Tianwei, Liu, Yun, Wu, Lei, Zhao, Yong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer simulation; Constraints; Electric power distribution; Electric vehicle charging; Electric vehicles; Electric vehicles charging stations; electricity distribution system; Energy management; equilibrium; Evolutionary algorithms; Evolutionary computation; Game theory; Games; Optimization; Quality of service; Sociology; Stations; Statistics
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2020.2988196

In recent years, electric vehicle charging stations (EVCSs) have been deployed very fast, which offer a platform for the energy coordination between electric vehicles (EVs) and the electricity distribution system (DS). This paper presents an energy management method for the operation of EVCSs and DS while considering their interaction. In this method, we first use a quality-of-service constrained decision model for EVCSs, which is formulated based on the network calculus theory. Then, the DS aims to maximize its utility by scheduling charging plans for EVCSs. Afterwards, a game based on the supply function equilibrium (SFE) model is adopted to analyze the energy interaction, in which each EVCS is regarded as the leader, and the DS as the follower. In this way, an optimization problem with equilibrium constraints is established. Moreover, a hybrid optimization algorithm based on differential evolution and interior point method is used to obtain the equilibrium solution of the SFE game. Finally, simulation studies verify the effectiveness of proposed interactive energy management method.