基于改进蜣螂优化算法的含电动汽车微电网优化调度  

Optimization Scheduling of Microgrid with Electric Vehicles Based on Improved Dung Beetle Optimizer Algorithm

作　　者：匡洪海[1] 徐雨淏 李子龙 KUANG Honghai;XU Yuhao;LI Zilong(College of Electrical and Information Engineering,Hunan University of Technology,Zhuzhou 412007,China)

机构地区：[1]湖南工业大学电气与信息工程学院,湖南株洲412007

出　　处：《电力科学与工程》2024年第8期10-17,共8页Electric Power Science and Engineering

基　　金：湖南省自然科学基金资助项目(2023JJ50176);湖南省教育厅重点项目资助(23A0441)。

摘　　要：将电动汽车接入微电网可以更好地平衡电网的供需,提高可再生能源利用率。电动汽车充电随机性大,这对微电网运行经济性会产生影响。提出了一种改进的蜣螂优化算法,对含有电动汽车的微电网经济调度进行优化。针对蜣螂优化算法种群分布不均、全局搜索能力较弱且容易陷入局部最优的问题,采用准对立学习初始化种群,用人工兔算法的行为替换蜣螂算法的滚球行为,再使用t分布扰动变异对偷盗行为做出改进。算例分析表明,所提改进蜣螂算法求解的最大值、最小值和平均值皆优于原始蜣螂算法,对模型经济性求解具有有效性与优越性。Integrating electric vehicles into microgrid can better balance the supply and demand of power grid,improving the utilization of renewable energy.The randomness of electric vehicle charging significantly impacts the economic operation of microgrid.An improved dung beetle optimizer algorithm is proposed to optimize the economic dispatch of microgrid with electric vehicles.In response to the problems of uneven population distribution,weak global search capability,and easy falling into local optimum in dung beetle optimizer algorithm,quasi-oppositional-based learning is used to initialize the population,the rolling behavior of the dung beetle algorithm is replaced with the behavioral strategy of the artificial rabbit algorithm,and t-distribution perturbation mutation is applied to improve the stealing behavior.Case analysis shows that the maximum,minimum,and average values obtained by the improved dung beetle algorithm are better than those of the original algorithm,demonstrating its effectiveness and superiority in solving the economic model.

关 键 词：电动汽车 微电网 优化调度 蜣螂算法 人工兔算法 

分 类 号：TM734[电气工程—电力系统及自动化]