基于改进教与学算法的配网多目标无功优化  

Multi-objective Reactive Power Optimization of Distribution Network Based on Improved Teaching-Learning Based Optimization

作　　者：李红伟[1] 蒋嘉焱 刘青卓 徐露 LI Hong-wei;LIU Qing-zhuo;JIANG Jia-yan;XU Lu(School of Electrical Engineering and Information,Southwest Petroleum University,Chengdu 610500,China;CSIC Haizhuang Windpower Co.,Ltd.,Chongqing 401122,China;Southwest Oil&Gas Field Co.,Ltd.,Chongqing 401220,China)

机构地区：[1]西南石油大学电气信息学院,四川成都610500 [2]中国船舶重工集团海装风电股份有限公司,重庆401122 [3]中国石油西南油气田分公司重庆气矿,重庆401220

出　　处：《控制工程》2020年第5期878-883,共6页Control Engineering of China

基　　金：国家重点基础研究发展计划(973计划)资助(2013CB228203);四川省教育厅重点项目(15ZA0058)。

摘　　要：配电网无功优化问题一直受到广泛关注,目前研究主要集中在单目标问题,或者将多目标问题通过权重法或惩罚函数转化为单目标。针对配电网无功优化优化问题,以网损最小和电压偏差最小为多目标函数,采用一种新颖的无需设置控制参数的教与学算法,基于Pareto最优解与拥挤度距离改进算法,应用非支配关系来构造非支配解集,降低多目标问题计算复杂度。并根据拥挤度距离排序提高解集的分布性,引入存储精英解集机制丰富非支配解集,并基于拥挤度距离的排序和裁剪求取最优解集,得到改进的多目标教与学算法。通过对IEEE-33节点系统进行仿真分析比较,结果验证了本文算法在多目标无功优化问题中的可行性和有效性。Reactive power optimization(RPO)problem of distribution power system has received extensive attention.Currently,it is mainly focused on single-objective problem,or transformed multi-objective problem into single-objective by weight method or penalty function.In this paper,aiming at the reactive power optimization,the minimization of the active network loss and voltage deviation were set as multi-objective functions,and a novel teaching-learning based optimization(TLBO)is proposed,which does not need to set the control parameters.Based on the Pareto optimal and the crowding distance,the non-dominated solution is constructed by applying the non-dominated relation,the computational complexity of the multi-objective problem can be reduced.The crowding distance sorting is used to improve the distribution of the solution,and the storage mechanism of elite solution set is introduced to enrich non-dominated solutions.Finally,the optimal solutions are obtained based on the crowding distance sorting and clipping of non-dominated solutions,so the improved multi-objective TLBO can be got.The IEEE 33-node system is adopted to test the algorithm,the results show the feasibility and effectiveness of the improved algorithm in multi-objective reactive power optimization.

关 键 词：配电网 多目标无功优化 教与学算法 PARETO最优解 拥挤度距离 

分 类 号：TP76[自动化与计算机技术—检测技术与自动化装置]