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文章摘要
基于人工鱼群算法的电动汽车优化充电策略
Optimal charging strategy of electric vehicles based on artificial fish swarm algorithm
Received:June 01, 2020  Revised:June 01, 2020
DOI:10.19753/j.issn1001-1390.2023.07.005
中文关键词: 电动汽车  有序充电  人工鱼群算法  优化策略  多目标优化模型
英文关键词: electric vehicles, orderly charging, artificial fish swarm algorithm, optimal strategy, multi-objective optimization model
基金项目:智慧能源服务系统关键技术研究与示范应用
Author NameAffiliationE-mail
WANG Tianyun* State Grid Electric Power Research Institute, NARI Group Co., Ltd. 649575621@qq.com 
ZHANG Hao State Grid Electric Power Research Institute, NARI Group Co., Ltd. zhanghao8@sgepri.sgcc.com.cn 
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中文摘要:
      为了缓解电动汽车大规模未经引导的充电行为对电网造成的压力,维持电网的安全稳定运行,文中提出了一种电动汽车的优化充电策略,通过分时电价制定充电计划,将电动汽车移动至平时段和谷时段进行充电。该算法以用户充电费用最少和电网峰谷差最小为目标函数,建立多目标优化的数学模型。针对现场调度规模大、实时性要求高的问题,采用人工鱼群算法对模型进行优化求解。此外,算法优化了充电的连续性,可以有效地防止负荷曲线突变,并保护充电设施。通过MATLAB仿真验证了算法的有效性和稳定性。
英文摘要:
      In order to relieve the pressure of power grid which is caused by massive unguided charging behavior of electric vehicles, as well as maintains the safe and stable operation of the power grid, this paper presents an optimal charging strategy for electric vehicles. The main idea of this strategy is to make charging plan through time-of-use electricity price, and the electric vehicle can be moved to normal period and valley period for charging. The objective function of the algorithm is to minimize the charging cost and the peak-valley difference, based on this system, this paper builds a mathematic model of multi-objective optimization. Aiming at the problem of large-scale and high real-time requirement, the artificial fish swarm algorithm is used to solve the model.In addition,the algorithm optimizes charging continuity,which can effectively prevent load curve mutation and protect charging facilities. The simulation results in MATLAB verify the validity and stability of charging strategy.
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