Research on charging strategy of electric vehicle considering user and load curve

Li Xincong,Xia Minhao,F. Song,Wang Jun,Wang Bing,M. Anpo,Xu Lin

doi:10.1051/e3sconf/202123602003

Abstract

With the increasing popularity of electric vehicles, the disordered charging of large-scale electric vehicles will have a great impact on the safe operation of regional distribution network. In order to solve the security problems that may occur in the power grid, this paper uses the time-sharing pricing time division method for EV charging to meet the needs of EV users. Based on this method, a multi-objective optimization model is established, which takes the electric vehicle charging capacity and power as the constraints, and based on the minimum user charging cost and the minimum load curve variance. Then, the model is solved by non-dominated sorting genetic algorithm (NSGA -Ⅱ), and the optimal compromise solution is extracted by using fuzzy set theory. Finally, the correctness of the proposed model is verified by the example.

Highlights

With the country's strong support for the development of electric vehicles and the increasing awareness of environmental protection, the number of electric vehicles will increase dramatically in the future
This paper takes the conventional charging methods of electric vehicle charging stations as the research object, comprehensively considers the economics of EV user charging and the safe operation of the power grid, and establishes a multi-objective charging optimization model based on the minimum user charging cost and the minimum variance of the load curve, and adopts The nondominated sorting genetic algorithm (NSGA-ჟ) solves the established model and obtains the Pareto solution set of the multi-objective optimization problem, and uses the partial fuzzy membership function to solve the Pareto solution set to obtain the optimal compromise solution
Charging optimization model this paper mainly studies the centralized charging station of electric vehicles

Summary

Introduction

With the country's strong support for the development of electric vehicles and the increasing awareness of environmental protection, the number of electric vehicles will increase dramatically in the future. The above research considers the interests of users or charging stations, it will increase the peak-to-valley difference of the power grid and affect the safe operation of the power grid. This paper takes the conventional charging methods of electric vehicle charging stations as the research object, comprehensively considers the economics of EV user charging and the safe operation of the power grid, and establishes a multi-objective charging optimization model based on the minimum user charging cost and the minimum variance of the load curve, and adopts The nondominated sorting genetic algorithm (NSGA-ჟ) solves the established model and obtains the Pareto solution set of the multi-objective optimization problem, and uses the partial fuzzy membership function to solve the Pareto solution set to obtain the optimal compromise solution. An example is given to verify the effectiveness of the proposed charging strategy

Electric vehicle charging time-sharing electricity price period division

Charging optimization model

Objective function

Model solving method based on NSGA-ɉ algorithm

Example analysis

Analysis of simulation results

Findings

Conclusion