Scheduling strategy of electric vehicle charging considering different requirements of grid and users

WanJun Yin, ZhengFeng Ming and Tao Wen

Energy, 2021, vol. 232, issue C

Abstract: With the increasing penetration of electric vehicles(EVs) that has enormous scheduling potentials, if it can fully tap its dispatching potential, it can help the power grid improve system operation efficiency, on the user side, it can save charging costs and improve user satisfaction. In view of this, this paper designs a charging scheduling method for EVs that meets the actual situation, which can not only choose the optimization target, but also the control strategy. Firstly,a dynamic multi-objective optimization scheme with more reasonable optimization objectives in each time period is constructed, so that the optimization objectives can be changed according to the actual situation; then, the orderly charging control is realized by adjusting the charging start time strategy or the variable charging power strategy, which not only prolongs the battery life, but also helps to smooth the grid load fluctuations. Thirdly, to solve the problem, an improved multi-objective PSO(particle swarm optimization) algorithm is designed, the improved algorithm uses the maximum and minimum fitness function based on the dynamic crowding distance and the amount of change, and optimizes the inertia weight coefficient and the learning factor to improve the performance of the algorithm. Finally, the effectiveness of the model is verified by numerical examples.

Keywords: EVs; Charging load forecasting; Smart charging strategies; Distribution margin (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:232:y:2021:i:c:s0360544221013669

DOI: 10.1016/j.energy.2021.121118

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