A Grouping Strategy and Day-ahead Scheduling Method of Electric Vehicles for Peak Shaving

Abstract

With the continuous development of electric vehicles (EVs), the charging load will exert more pressure on the regional power grid. The higher penetration may intensify the peak-valley difference and force the distribution transformer to be overloaded. This paper proposes a grouping strategy and day-ahead scheduling method of EVs participating in peak shaving. It fully considers the match between the resource characteristics of EVs and load regulation requirements of the grid to form a grouping method, in order to improve the performance as well as reduce the difficulty in plan generating process. Combined with the improved particle swarm algorithm, a day-ahead plan for EVs to participate in peak shaving is generated. Through the case studies, the strategy proposed is proved effective in optimizing the peak shaving performance and reducing the calculation amount of the plan generation process.