基于免疫PSO的新能源配电网无功多目标模糊优化

doi:10.11930/j.issn.1004-9649.201702017

中国电力 ›› 2018, Vol. 51 ›› Issue (2): 90-98.DOI: 10.11930/j.issn.1004-9649.201702017

基于免疫PSO的新能源配电网无功多目标模糊优化

司徒友¹, 吴杰康², 郭清元¹, 吴长元², 王正卿¹, 徐宏海¹

1. 广东电网有限责任公司东莞供电局, 广东东莞 523008;
2. 广东工业大学自动化学院, 广东广州 510006

收稿日期:2017-02-17 修回日期:2017-09-09 出版日期:2018-02-05 发布日期:2018-02-11
作者简介:司徒友(1974—),男,广东东莞人,高级工程师,从事配电系统运行与控制研究,E-mail:situyou22336006@163.com。
基金资助:
国家自然科学基金资助项目（50767001）；广东省公益研究与能力建设专项资金项目（2014A010106026）；中国南方电网有限责任公司科技项目（031900KK52150047）。

Multi-Objective Fuzzy Optimization for Reactive Power of Distribution Network Based on Immune Particle Swarm Optimization Algorithm

SITU You¹, WU Jiekang², GUO Qingyuan¹, WU Changyuan², WANG Zhengqing¹, XU Honghai¹

1. Dongguan Power Supply Bureau, Guangdong Power Grid Corporation, Dongguan 523008, China;
2. School of Automation, Guangdong University of Technology, Guangzhou 510006, China

Received:2017-02-17 Revised:2017-09-09 Online:2018-02-05 Published:2018-02-11
Supported by:
This work is supported by National Natural Science Foundation of China (No. 50767001); Guangdong Special Fund for Public Welfare Study and Ability Construction(No. 2014A010106026); Science & Technology Projects of China Southern Power Grid Co., Ltd.(No. 031900KK52150047).

摘要/Abstract

摘要： 考虑分布式能源的间歇性和随机性对配电网电压的影响，用模糊数表征分布式电源出力不确定性和负荷功率的波动性，构建配电网多目标模糊无功优化模型，提出分布式电源和无功补偿装置输出无功功率的协同优化方法。以有功网损最小和电压偏差最小为目标函数，并将目标函数和约束条件模糊化，根据其隶属度函数形成模糊适应度函数，再将两目标通过最大满意度法转化为单目标，最后利用免疫粒子群算法进行求解，从而确定在负荷功率模糊波动下具有不同模糊出力水平的分布式电源和具有不同运行方式的无功补偿装置输出无功功率的最优值。以IEEE33配电网系统为算例，验证了所提出的模型和算法的可行性和有效性。

关键词: 配电网, 无功多目标模糊优化, 分布式电源, 免疫粒子群优化算法

Abstract: Considering the influence of intermittent and randomness of distributed energy on the voltage of distribution network, the fuzzy power is used to characterize the fluctuation of distributed power output and load power. The multi-objective fuzzy and reactive power optimization model of distribution network is proposed in this paper. Besides, the coordinated optimization method is introduced for the output reactive power of distributed generations and reactive power compensation devices. By taking the minimum loss of power network and the smallest voltage deviation as objective function, the objective function and the constraint conditions are fuzzified, and the fuzzy fitness function is formed according to the membership function. Then, the multi-objective optimization problem is transformed into the single objective optimization by the maximum satisfaction method. Finally, the immune particle swarm optimization algorithm is used to determine the optimal value of the output reactive power of the distributed generations with different fuzzy output levels and the reactive power compensation device with different operating modes under fuzzy fluctuations of the load powers. By taking the IEEE33 distribution system as an example, the feasibility and validity of the proposed model and algorithm are verified.

Key words: distribution networks, multi-objective fuzzy optimization of reactive power, distributed generation, immune particle swarm optimization algorithm

中图分类号:

TM721

司徒友, 吴杰康, 郭清元, 吴长元, 王正卿, 徐宏海. 基于免疫PSO的新能源配电网无功多目标模糊优化[J]. 中国电力, 2018, 51(2): 90-98.

SITU You, WU Jiekang, GUO Qingyuan, WU Changyuan, WANG Zhengqing, XU Honghai. Multi-Objective Fuzzy Optimization for Reactive Power of Distribution Network Based on Immune Particle Swarm Optimization Algorithm[J]. Electric Power, 2018, 51(2): 90-98.

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https://www.electricpower.com.cn/CN/Y2018/V51/I2/90

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基于免疫PSO的新能源配电网无功多目标模糊优化

Multi-Objective Fuzzy Optimization for Reactive Power of Distribution Network Based on Immune Particle Swarm Optimization Algorithm

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基于免疫PSO的新能源配电网无功多目标模糊优化

Multi-Objective Fuzzy Optimization for Reactive Power of Distribution Network Based on Immune Particle Swarm Optimization Algorithm

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