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With the increase of Distributed Energy Resources (DERs) and Electric Vehicles (EVs), it is necessary to reasonably site and size DERs and EV charging stations in distribution networks (DNs), to make better use of energy and improve DN operation performances. Considering the obvious characteristics of DER output and EV charging demand with respect to time, the joint siting and sizing of DERs and EV charging stations in DNs may achieve better performances by making use of such characteristics. The problem is a difficult optimization with mixed discrete and continuous decision variables, and is difficult to be directly solved by using traditional mathematical programming methods. This paper presents a model of joint siting and sizing of DERs and EV charging stations with the objective of minimizing charging station investments and DN performance indices. The model is solved in two stages: first, siting of EV charging stations is determined by using Particle Swarm Optimization (PSO) algorithm, and second, siting and sizing of DERs are solved by using Second-order Cone Programming (SOCP). Numerical examples on the IEEE 33-bus network are presented to demonstrate effectiveness of our method.

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Joint Siting and Sizing of Distributed Energy Resources and Electric Vehicle Charging Stations in Distribution Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Liqiang Wang,
  • Qi Wang,
  • Yu Liu,
  • Yu Cong

摘要

With the increase of Distributed Energy Resources (DERs) and Electric Vehicles (EVs), it is necessary to reasonably site and size DERs and EV charging stations in distribution networks (DNs), to make better use of energy and improve DN operation performances. Considering the obvious characteristics of DER output and EV charging demand with respect to time, the joint siting and sizing of DERs and EV charging stations in DNs may achieve better performances by making use of such characteristics. The problem is a difficult optimization with mixed discrete and continuous decision variables, and is difficult to be directly solved by using traditional mathematical programming methods. This paper presents a model of joint siting and sizing of DERs and EV charging stations with the objective of minimizing charging station investments and DN performance indices. The model is solved in two stages: first, siting of EV charging stations is determined by using Particle Swarm Optimization (PSO) algorithm, and second, siting and sizing of DERs are solved by using Second-order Cone Programming (SOCP). Numerical examples on the IEEE 33-bus network are presented to demonstrate effectiveness of our method.