The location optimization of electric vehicle charging stations considering charging behavior

Abstract

The electric vehicle is seen as an effective way to alleviate the current energy crisis and environmental problems. However, the lack of supporting charging facilities is still a bottleneck in the development of electric vehicles in the Chinese market. In this paper, the cloud model is used to first predict drivers’ charging behavior. An optimization model of charging stations is proposed, which is based on waiting time. The target of this optimization model is to minimize the time cost to electric vehicle drivers. We use the SCE-UA algorithm to solve the optimization model. We apply our method to Dalian, China to optimize charging station locations. We also analyze the optimized result with or without behavior prediction, the optimized result of different numbers of electric vehicles, and the optimized result of different cost constraints. The analysis shows the feasibility and advantages of the charging station location optimization method proposed in this paper.

Keywords

Behavior prediction cloud mode optimization of charging station location SCE-UA algorithm waiting time

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