[1]左士伟,杨胡萍,张扬,等.基于改进遗传算法的电力系统无功优化[J].郑州大学学报(工学版),2015,36(06):66.[doi:10.3969/j. issn.1671 -6833.2015.06.013]
　YANG Huping,Ll Weiren,ZUO Shiwei,et al.Reactive Power Optimization by Improved Genetic Algorithm Method[J].Journal of Zhengzhou University (Engineering Science),2015,36(06):66.[doi:10.3969/j. issn.1671 -6833.2015.06.013]
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基于改进遗传算法的电力系统无功优化()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36
期数:
2015年06期
页码:
66
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Reactive Power Optimization by Improved Genetic Algorithm Method
作者:
左士伟; 杨胡萍; 张扬; 蔡孝文; 李威仁
1.南昌大学信息工程学院,江西南昌330031;2.国网浙江省电力公司金华供电公司,浙江金华321017;3.国网江西省电力公司信息通信分公司,江西南昌330096;4.国网江西省电力公司检修分公司,江西南昌330096
Author(s):
YANG Huping1; Ll Weiren1; ZUO Shiwei1; ZHANG Yang1; CAI Xiaowen1
1. School of Information Engineering，Nanchang University，Nanchang 330031，China;2.State Grid Zheijiang Eletric PowerCompany Jimhua Power Supply Company，Jimhua 321017，China;3.State Grid Jiangxi Electric Power Company Information andCommunications Branch，Nanchang 330096，China;4.State Grid Jiangxi Electric Power CompanyMaintenance Branch，Nan-chang 330096，China
关键词:
电力系统; 无功优化; 遗传算法
Keywords:
power system; reactive power optimization;  genetic algorithm
分类号:
TM731
DOI:
10.3969/j. issn.1671 -6833.2015.06.013
文献标志码:
A
摘要:
应用遗传算法求解电力系统无功优化问题,建立以无功补偿设备的投入容量、发电机端电压、可调变压器变比为控制变量,以综合效益最大为目标函数的电力系统无功优化数学模型.所建模型中，控制中心取离散值的变量,采用十进制整数编码提高了计算效率,应用混合选择算子和自适应调整交叉/变异率改善了收敛性能.在IEEE 14节点系统上进行500次的无功优化,验证了方法的正确性和有效性.
Abstract:
Reactive power optimization using improved genetic algorithm is studied in this paper.A mathemat-ical model of reactive power optimization for power system is established，which treats the voltage of the gener-ator，capacity of reactive power compensation equipment，ratio of adjustable transformers as control variables,aiming at maximizing the comprehensive benefits which takes the economics and power system performance intoaccount. The proposed model takes decimal integer encoding strategy to improve the computational efficiencyfor the discrete variables in control center，applies comprehensive selection operator and adaptive crossovermutation rate to improve the convergence performance.The correctness and effectiveness of the proposed meth-od are validated by simulation results of IEEE 14-bus system for 500 times.

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