Volume 4: Innovative Solutions for Energy Transitions: Part III

Research on Optimization Scheduling Strategy of Distribution Network Congestion with Electric Vehicles Dan Wang, Dongdong Sun, Yunchao Song, Qiuyi Huo

Abstract

Large-scale centralized charging of electric vehicles is likely to cause congestion phenomena such as line overload and voltage drop. A scheduling optimization scheduling strategy for distribution network congestion management considering electric vehicles charging load is proposed. Establish a multi-objective optimization model of three stakeholders including grid center, electric vehicle aggregator and electric vehicle user, and design the objective function according to their actual operating conditions. The non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve the Pareto non-dominated solution set, and the Topsis method is used to determine the optimal solution. The case analysis part of the article proves that the proposed strategy can eliminate congestion by comparing the response results before and after optimization. The cost-benefit analysis proves that the strategy can reduce the running cost and increase the profit to some extent.

Keywords electric vehicle, distribution network congestion, multi-objective optimization, NSGA-II, Topsis