Pricing iterative optimization for multi‐agent simulation of setting electric vehicle charging model in public parking lots - Zhenyu Mei; Yi Liu; Jinhuan Zhao; Zhengyi Cai (IET Intelligent Transport Systems)
Abstract Despite the increasing scale of the electric vehicle market in recent years, in view of the long charging time of EVs (Electric Vehicles), the accessibility of charging facilities is still an obstacle to the rapid development of EVs. Therefore, the Chinese government has promulgated a one‐size‐fits‐all construction strategy which means constructing charging piles in parking lots with a fixed proportion. This paper mainly simulates the actual demand and adjusts the charging price of charging stations to reduce the uneven spatial distribution of charging demand. In particular, this paper constructs a multi‐agent system of the road network, vehicle, and charging station to simulate the charging behaviour in the mixed scenario of EVs and traditional fuel vehicles. The impact of charging pricing adjustment on individuals and charging stations is fed back in real‐time by using the characteristics of agents to respond to dynamic changes and make intelligent decisions. This paper proposes an iterative optimization method to obtain the optimal pricing strategy for charging stations to reduce the imbalance of charging demand. Taking the Wulin Square business district in Hangzhou as an example, the results show that the proposed pricing optimization method can improve the overall utility.