基于混合灰狼算法的虚拟电厂经济优化调度  

Economic Optimization Scheduling of Virtual Power Plants Based on Hybrid Grey Wolf Optimization Algorithm

作　　者：钟婷婷 田邓新宇 吴婷 杨帆 陈磊 ZHONG Tingting;TIAN Dengxinyu;WU Ting;YANG Fan;CHEN Lei(State Grid Hubei Electric Power Co.,Ltd.Jingmen Power Supply Company,Jingmen 448000,China)

机构地区：[1]国网湖北省电力有限公司荆门供电公司,湖北荆门448000

出　　处：《安徽电气工程职业技术学院学报》2025年第1期85-93,共9页Journal of Anhui Electrical Engineering Professional Technique College

摘　　要：为了提升虚拟电厂(virtual power plant,VPP)的经济效益,促进风、光等清洁能源的消纳,文章设计了一种基于混合灰狼(hybrid grey wolf optimization,HGWO)算法的VPP经济调度模型。将VPP运行成本最小作为目标函数,利用HGWO算法对目标函数进行最优值搜索,算例结果显示,HGWO算法收敛时的进化代数和收敛时间分别为55代和12.15 s,获得的VPP最小运行成本为57.36万元,以及HGWO算法的各项性能指标均优于文章所列出的其他3种算法;同时也表明了通过科学调度VPP内部的各类分布式电源,不仅满足了VPP负荷需求,而且使风电场和光伏电站的输出电能得到了充分利用,进而提升了VPP的经济性。In order to improve the economic benefits of the virtual power plant(VPP)and promote the consumption of clean energy such as wind and solar power,this paper designs a VPP economic scheduling model based on the hybrid grey wolf optimization(HGWO)algorithm.The objective function is to minimize the operating cost of VPP,and the HGWO algorithm is used to search for the optimal value of the objective function.Simulation results show that the evolutionary algebra and convergence time of the HGWO algorithm are 55 times and 12.15 seconds,respectively,and the minimum operating cost of VPP obtained is 573600 yuan.The performance indicators of the HGWO algorithm are superior to the other three comparative methods.It also shows that by scientifically scheduling various distributed power sources within VPP,not only is the load demand of VPP met,but also the output energy of wind farms and photovoltaic power plants is fully utilized,thereby improving the economy of VPP.

关 键 词：虚拟电厂 调度 混合灰狼算法 运行成本 目标函数 

分 类 号：TM73[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]