Optimal planning of PEV fast charging stations using an auction-based method

Abstract

In recent years, the plug-in electric vehicles (PEVs) have attracted a lot of attention. For integration of PEVs, proper planning of PEV charging stations is necessary. Location and size of fast charging stations (FCSs) are very important for distribution companies (DISCOs) and FCS investors. In this paper, FCS planning problem is modeled as a mixed-integer nonlinear programming (MINLP) from DISCO point of view. The proposed method is based on the dynamic auction, and a co-evolutionary genetic algorithm is used to solve the problem. FCS investors bid DISCO for energy in different locations. The DISCO, as the auctioneer, determines the location and size of FCSs based on the bids received at each location so that its profit is maximized. In the proposed model, capacitor and feeder installations are considered to satisfy the bus voltage limit and the apparent power capacity constraint of feeders, respectively. The effectiveness of the proposed method is demonstrated by numerical results. Our work shows that the proposed method can be used as a proper tool for fast FCS optimal planning in the presence of private investors of FCSs. Furthermore, in the new environment of power systems, dynamic auctions can be utilized in FCS planning. In addition, the capacitor and feeder installations can be effectively used for getting a better value of DISCO objective function.