基于河马优化算法的电动汽车有序充电策略

doi:10.3969/j.issn.1008-0198.2026.01.010

湖南电力 ›› 2026, Vol. 46 ›› Issue (1): 76-83.doi: 10.3969/j.issn.1008-0198.2026.01.010

基于河马优化算法的电动汽车有序充电策略

唐轩逸¹, 刘平², 兰征¹, 唐明斌², 胡思阳¹

1.湖南工业大学交通与电气工程学院,湖南株洲 412007;
2.湖南大学电气与信息工程学院,湖南长沙 410082

收稿日期:2025-09-15 修回日期:2025-11-09 出版日期:2026-02-25 发布日期:2026-03-10
通信作者: 唐轩逸（2001）,男,硕士,主要研究方向为电动汽车有序充电。
作者简介:刘平（1983）,男,博士,副教授,研究方向为电力电子与电驱系统性能综合优化与可靠性。兰征（1985）,男,博士,副教授,研究方向为电力电子变换器控制技术、新能源并网与微电网运行。唐明斌（1999）,男,博士,研究方向为电动汽车能量管理。胡思阳（1999）,男,硕士,研究方向为电动汽车充电机宽范围充电。
基金资助:
福建省自然科学基金项目（2022J01529）

Orderly Charging Strategy for Electric Vehicles Based on Hippopotamus Optimization Algorithm

TANG Xuanyi¹, LIU Ping², LAN Zheng¹, TANG Mingbin², HU Siyang¹

1. College of Trasportation and Electrical Engineering, Hunan University of Technology,Zhuzhou 412007, China;
2. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Received:2025-09-15 Revised:2025-11-09 Online:2026-02-25 Published:2026-03-10

摘要/Abstract

摘要： 为缓解电动汽车无序充电对电网的影响,提高用户充电体验,提出一种基于河马优化算法的有序充电策略。首先,通过蒙特卡洛法模拟电动汽车的无序充电负荷;其次,以电网负荷峰谷差率与用户充电成本最小化为优化目标,建立电动汽车有序充电模型;最后,通过河马优化算法对模型进行求解。仿真结果表明,与无序充电相比,电网负荷峰谷差率降低了23个百分点,用户充电成本减少了38%,所提策略在降低电网负荷峰谷差率与用户充电成本方面均具有显著效果。

关键词: 电动汽车, 有序充电, 蒙特卡洛模拟, 河马优化算法, 充电成本

Abstract: To mitigate the impact of disorderly EV charging on the power grid and enhance user charging experiences, an orderly charging strategy based on the hippopotamus optimization algorithm is proposed. Firstly, the disorderly charging load of electric vehicles is simulated using the Monte Carlo method. Subsequently, an orderly charging model is established with the dual objectives of minimizing the grid load peak-to-valley difference rate and user charging costs. Finally, the hippopotamus optimization algorithm is employed to solve this model. Simulation results demonstrate that compared with disorderly charging, the grid load peak-to-valley difference rate is reduced by 23%, while user charging costs is decreased by 38%. Consequently, the proposed strategy exhibits significant effectiveness in both reducing the grid load peak-to-valley difference rate and user charging costs.

Key words: electric vehicle, orderly charging, Monte Carlo simulation, hippopotamus optimization algorithm, charging cost

中图分类号:

TM715

唐轩逸, 刘平, 兰征, 唐明斌, 胡思阳. 基于河马优化算法的电动汽车有序充电策略[J]. 湖南电力, 2026, 46(1): 76-83.

TANG Xuanyi, LIU Ping, LAN Zheng, TANG Mingbin, HU Siyang. Orderly Charging Strategy for Electric Vehicles Based on Hippopotamus Optimization Algorithm[J]. Hunan Electric Power, 2026, 46(1): 76-83.

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基于河马优化算法的电动汽车有序充电策略

Orderly Charging Strategy for Electric Vehicles Based on Hippopotamus Optimization Algorithm

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