基于增强精英保留遗传算法的虚拟微网群动态划分及能量局域自治  

Dynamical Partitioning and Local Energy Autonomy of Virtual Microgrid Groups Based on Strengthen Elitist Genetic Algorithm

作　　者：华昊辰 翟家祥 陈星莺[1] 王博 余昆[1] 秦钰超 沈俊 丁一[4] 贺大玮 HUA Haochen;ZHAI Jiaxiang;CHEN Xingying;WANG Bo;YU Kun;QIN Yuchao;SHEN Jun;DING Yi;HE Dawei(College of Energy and Electrical Engineering,Hohai University,Nanjing 210098,Jiangsu Province,China;Department of Applied Mathematics and Theoretical Physics,University of Cambridge,Cambridge CB30WA,U.K;School of Mechanical Engineering,Beijing Institute of Technology,Haidian District,Beijing 100081,China;College of Electrical Engineering,Zhejiang University,Hangzhou 310027,Zhejiang Province,China;Sichuan Energy Internet Research Institute,Tsinghua University,Chengdu 610213,Sichuan Province,China)

机构地区：[1]河海大学能源与电气学院,江苏省南京市210098 [2]剑桥大学应用数学和理论物理系,英国剑桥CB30WA [3]北京理工大学机械与车辆学院,北京市海淀区100081 [4]浙江大学电气工程学院,浙江省杭州市310027 [5]清华四川能源互联网研究院,四川省成都市610213

出　　处：《中国电机工程学报》2024年第12期4652-4665,I0006,共15页Proceedings of the CSEE

基　　金：国家自然科学基金项目(52107089);中央高校基本科研业务费(B200201071);中国博士后基金项目(2021M700040,2022T150182)。

摘　　要：互联的多微网系统作为可再生能源利用的有效形式之一,随着“双碳”工作的推进越发受到重视。该文旨在研究基于海量可控设备的优化调节方法,以促进可再生能源充分就地消纳,提高多微网系统运行经济性。然而,对海量可控设备的全局控制将面临“维数灾难”的挑战。现有研究中基于地理分布的分区优化能够实现“降维控制”,但可再生能源出力的波动性与负荷在时间上的变化和空间上的迁移,都会导致固定分区的方法难以适用于多微网系统态势变迁下的能量动态管控。针对上述问题,首先建立微电网动态模型;进而提出通过增强精英保留遗传算法(strengthen elitist genetic algorithm,SEGA)将互联多微网场景划分为多个边界可动态调整的虚拟微网群,并进行能量“局域自治”优化;最后基于改进的IEEE-123节点模型进行仿真,结果显示1 h内动态边界虚拟微网群的总运行成本比固定边界虚拟微网群的总运行成本降低了13.6%,且所采用的SEGA的求解时间比传统遗传算法减少了7.09%。As one of the effective forms of renewable energy utilization,the multi-microgrid system has attracted much attention with the advancement of“carbon peaking and carbon Neutrality”.The purpose of this paper is to study the optimization method towards massive controllable equipment,so as to promote the local consumption of renewable energy and reduce the operation cost of the multi-microgrid system.However,the global control of massive controllable equipment will face the challenge of“curse of dimensionality”.In the existing research,the partitioning based on geographical distribution could achieve such control target via dimensional reduction.However,the fluctuation of renewable energy output,as well as the real-time power change and the migration in space of load will make it difficult for the fixed-boundary partitioning method to be applied in the dynamical energy management under the changing situation of multi-microgrid systems.In view of the above problems,this paper first establishes the system dynamic model for each individual microgrid.Then,the considered multi-microgrid system is divided into multiple virtual microgrid groups whose boundaries can be dynamically adjusted through the strengthen elitist genetic algorithm(SEGA),and the local autonomous energy optimization is implemented.Finally,a modified IEEE-123 node simulation model is built.The simulation results show that for one hour the operation cost of the virtual microgrid groups with dynamic boundary is 13.6%lower than that of the virtual microgrid with fixed boundary,and the time to obtain the solution via SEGA is 7.09%less than that via a conventional genetic algorithm.

关 键 词：多微网系统 虚拟微网群 动态分区 增强精英保留遗传算法(SEGA) 

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]