引用本文: | 赵超,付斌,林立.基于改进樽海鞘算法的含电动汽车微电网经济优化调度[J].控制理论与应用,2025,42(1):167~180.[点击复制] |
ZHAO Chao,FU Bin,LIN Li.Economic dispatch of microgrid with electric vehicles based on improved salp swarm algorithm[J].Control Theory and Technology,2025,42(1):167~180.[点击复制] |
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基于改进樽海鞘算法的含电动汽车微电网经济优化调度 |
Economic dispatch of microgrid with electric vehicles based on improved salp swarm algorithm |
摘要点击 3270 全文点击 20 投稿时间:2022-08-10 修订日期:2024-12-02 |
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DOI编号 10.7641/CTA.2023.20714 |
2025,42(1):167-180 |
中文关键词 电动汽车 微电网 经济调度 樽海鞘算法 Tent混沌映射 重心反向学习 |
英文关键词 electric vehicles microgrid economic dispatch salp swarm algorithm Tent Chaotic Map centroid-opposition based learning |
基金项目 国家自然科学基金项目(83420033), 科技部国家重点研发计划项目(83921029)资助. |
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中文摘要 |
电动汽车接入可再生能源微电网有利于减少环境污染, 改善能源结构. 但是电动汽车充电负荷的随机波动性为微电网运行优化调度带来很大的困难. 为了实现微电网的高效稳定运行, 本文提出一种基于改进樽海鞘算法 (ISSA)的含电动汽车的可再生能源微电网优化调度方法. 针对基本樽海鞘算法在进化后期由于种群多样性的缺失而易出现局部收敛或算法早熟的问题, 改进算法首先利用Tent混沌序列产生初始种群, 以增强种群的多样性; 其次, 通过设置动态控制参数来调节算法的全局探索与局部开发之间的平衡, 提高算法的收敛性; 同时, 引入正交重心反向学习策略改进樽海鞘个体的位置信息更新, 从而, 强化算法的全局寻优能力以克服算法早熟收敛, 以避免陷入局部极值, 从而全面提高算法的优化性能; 最后, 将该算法用于求解含电动汽车微电网经济优化问题, 在孤岛和并网两种模式下分别进行仿真实验, 并与其他算法的优化结果进行比较. 仿真结果表明, 基于ISSA算法的优化结果均优于其他方法, 两种模式下运行成本最大降幅分别为29.1%和20.0%, 证明了所提算法的可行性和实用性. |
英文摘要 |
Connecting electric vehicles (EV) to the renewable energy microgrid is conducive to reduce environmental pollution and improve energy structure. However, the random volatility of EV charging load may increase the difficulty of economic dispatch of the microgrid. In order to achieve a cost effective and reliable hybrid generation system, an optimal scheduling method of microgrids with electric vehicles based on an improved salp swarm algorithm (ISSA) is studied. As the traditional salp swarm algorithm (SSA) algorithm has the disadvantages of premature convergence and getting stuck in local optimum, the proposed ISSA algorithm used Tent chaos map to generate the initial population, which can increase the diversity of the population. Then, a dynamic control parameter is added to maintain a better balance between global search and local search of the algorithm. At the same time, orthogonal centroid-opposition based learning strategy (OCOBL) is introduced to update the position information of each salp. This scheme can increase the global search ability and prevent the algorithm from falling into local optimum. Finally, the ISSA algorithm is applied for optimal dispatch of the microgrid with electric vehicles in the grid-connected and islanded modes, and the simulation confirm the efficacy of the ISSA technique compared with other meta-heuristic algorithms. The results also show that the operating cost in two operation models are respectively reduced up to 29.1% and 20.0% under the proposed algorithm, which demonstrates the effectiveness and applicability of the proposed method. |
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