Details

Autor(en) / Beteiligte

• Huai-Dong, Yang
• Jie, Liu
• Xun, Li
• Chu-Yi, Li
• Yu-Guang, Luo
• Yun-Zhu, An

Titel

Research on Orderly Charging Strategy of Electric Vehicles Based on Improved Particle Swarm Optimization Algorithm

Ist Teil von

• 2023 International Conference on Cyber-Physical Social Intelligence (ICCSI), 2023, p.616-621

Ort / Verlag

IEEE

Erscheinungsjahr

2023

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• The current charging order of electric vehicles is chaotic. There are some shortcomings in disordered charging sequence, such as chaotic charging time, chaotic charging time, uncertain charging power. With the increase of the number of electric vehicles, this disorderly charging method will bring many disorderly load shocks to the power grid, which will pose a great challenge to the normal operation of the power grid. Aiming at the optimal strategy of orderly charging of electric vehicles, this paper proposes an intelligent charging control strategy for electric vehicles is proposed in this paper. The objective function is to minimize the optimal charging start time of each electric vehicle and the total load power of the power system. Considering the maximum load power allowed by the power system, the state of charge (SOC) of the electric vehicle battery and other constraint conditions. a multi-objective optimization model for the centralized charging of electric vehicles is established. The particle swarm optimization (PSO) algorithm is used to solve the optimization model, and the feasibility and effectiveness of the model are proved by the calculation results of MATLAB software. The influence of different values of charging systems in different states on the optimization results are analyzed, and relevant suggestions are given accordingly.