A novel analytical method for optimal management of network congestion caused by electric vehicle charging stations

Abstract

Congestion management with the emergence of electric vehicle charging stations (EVCSs) can be considered as one of the challenges facing the network operator, whose incorrect management causes the price difference to increase and creates market power. In general, the effect of EVCSs on the congestion rent (CR) of grid lines has been studied in a few studies, which are considered a research gap. In this paper, the share of each EVCS to the variations in line CR and total congestion rent (TCR) is precisely determined. Also, the uncertainty regarding the capacity of the EVCSs is considered to make the problem more real. In addition, the share of other factors as well as marginal, expensive, and cheap units, grid loads, and congested lines are calculated on the CR of grid lines. The proposed method is divided into two parts, in which the share of the five factors to variations in the buses’ locational marginal price (LMP) and the flow of lines is determined in part 1. In part 2, the share of EVCSs to variations in the CR of lines and TCR is computed. The proposed method is implemented using the Kahn-Tucker condition method. This approach is implemented on an IEEE 24-bus system. The analysis of results indicate that the congestion of network lines in the best and worst cases of placing 3 EVCSs in the network increases by 0.0013 % (0.65 $/h) and 0.1 % (48.94 $/h), respectively. Therefore, determining the appropriate placement of the EVCS is of particular importance.