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基于改进蜉蝣算法的一种新型无功优化补偿方法及其应用
引用本文:彭泽森,舒恺,高飞翎,余萃卓.基于改进蜉蝣算法的一种新型无功优化补偿方法及其应用[J].陕西电力,2022,0(12):41-47.
作者姓名:彭泽森  舒恺  高飞翎  余萃卓
作者单位:(1.福州大学电气工程与自动化学院,福建福州 350108;2.宁波市电力设计院有限公司,浙江宁波 315000)
摘    要:基于改进的蜉蝣算法提出了一种电力系统新型无功优化计算方法。首先以电力系统有功网损最小为目标函数,选择发电机端电压、可调变压器分接头以及并联静止电容器组数为控制变量,建立了无功优化的数学模型;提出将新型群搜索智能优化算法蜉蝣算法引入到无功优化问题中;针对基础蜉蝣算法易陷入局部最优解的缺陷,提出优化基础蜉蝣算法,将Levy飞行以及随机惯性权重系数引入蜉蝣算法的位置更新策略中,提高蜉蝣算法的全局搜索能力。最后,以IEEE30节点系统为测试对象,证明了改进的蜉蝣算法在电力系统无功优化问题中的有效性及优势。

关 键 词:无功优化  有功网损  蜉蝣算法  Levy飞行

A Novel Modified Mayfly Algorithm-based Reactive Power Optimization Compensation Method and Its Application
PENG Zesen,SHU Kai,GAO Feiling,YU Cuizhuo.A Novel Modified Mayfly Algorithm-based Reactive Power Optimization Compensation Method and Its Application[J].Shanxi Electric Power,2022,0(12):41-47.
Authors:PENG Zesen  SHU Kai  GAO Feiling  YU Cuizhuo
Affiliation:(1. College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China;2. Ningbo Electric Power Design Institute Co., Ltd., Ningbo 315000,China)
Abstract:Based on the modified mayfly algorithm, the paper proposes a new reactive power optimization method for power system. Firstly, the mathematical model of the reactive power optimization is established with the objective function of minimizing the active power loss in the power system, by selecting the generator terminal voltage, adjustable transformer tap and the groups of shunt static capacitors as the control variables. Then a new group search intelligent optimization algorithm, namely mayfly algorithm, is introduced into the reactive power optimization. Moreover, aiming at the defect that the basic mayfly algorithm is easy to fall into local optimal solution, the optimization basic mayfly algorithm is proposed, and Levy flight and random inertia weight coefficient is introduced into the position update strategy for the mayfly algorithm to improve its global search ability. Finally, taking the IEEE 30-bus system as the test object, the effectiveness and advantages of the modified mayfly algorithm in the reactive power optimization of the power system are proved.
Keywords:reactive power optimization  active network loss  mayfly algorithm  Levy flight
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