面向时变电价的电池充电功率与用户分配联合调度算法

doi:10.11896/jsjkx.240200018

Abstract

Abstract: With the global proliferation of electric motorcycles,battery-swapping stations have gained widespread attention due to their advantages,such as swift replenishment,convenience,and safety.Nonetheless,a predominant challenge most stations face is the elevated cost of charging.It is derived from the charging strategies for battery and user behavior during battery swaps.Leve-raging the adjustable charging power of batteries at swapping stations and the idle time of numerous batteries during the charging process is anticipated to reduce charging costs judiciously.Hence,this paper concentrates on the batteries and users within the battery swapping industry,specifically delving into the intricacies of adjusting the charging power of batteries and the allocation of users in battery swapping stations.The primary challenges encompass the dual influence of time-varying electricity prices and user allocation on battery charging power adjustment strategies.Furthermore,the battery and user allocation schemes must cater to users' battery swapping requirements across different time periods while also consider the charging costs incurred by individual batteries under varying charging power adjustment strategies.Consequently,adjusting battery charging power and user allocation are interlinked and form a mutually dependent problem.To this end,we propose a comprehensive scheduling algorithm for adjusting battery charging power and user allocation,taking into account the time-varying electricity prices.Firstly,a greedy strategy is initially applied to formulate a charging power adjustment plan for each battery.Then,considering the charging costs and the energy swapped out by individual batteries,an algorithm based on genetic characteristics is utilized to match batteries with optimal users,thereby minimizing the overall charging costs of the battery swapping station.Finally,the proposed method undergoes a thorough evaluation using a large-scale dataset from 44 battery swapping stations and 7 334 batteries in Chengdu,spanning two years.Experimental results demonstrate that,on average,the total charging costs of the proposed algorithm are reduced by 20.8% compared to the three baselines.

Key words: Battery swapping stations, Charging costs, Power regulation, Genetic characteristics, User allocation

CLC Number:

TP393

WAN Desheng, CHEN Hao, CHENG Wenhui, GAO Yunlong. Joint Scheduling Algorithm of Battery Charging Power and User Allocation for Time-varyingElectricity Prices[J].Computer Science, 2025, 52(2): 242-252.

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