[1]刘宪林,乔云飞..基于人工鱼群算法的电力系统稳定器参数优化研究[J].郑州大学学报(工学版),2013,34(05):68-73.[doi:10.3969/j.issn.1671-6833.2013.05.015]
　LIU Xian-in,QIAO Yun-fei.Study on PSS Parameter Optimization Based on Artificial Fish-swarm Algorithm[J].Journal of Zhengzhou University (Engineering Science),2013,34(05):68-73.[doi:10.3969/j.issn.1671-6833.2013.05.015]
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基于人工鱼群算法的电力系统稳定器参数优化研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
34
期数:
2013年05期
页码:
68-73
栏目:
出版日期:
2013-09-10

文章信息/Info

Title:
Study on PSS Parameter Optimization Based on Artificial Fish-swarm Algorithm
作者:
刘宪林; 乔云飞.
郑州大学电气工程学院,河南郑州,450001, 郑州大学电气工程学院,河南郑州,450001
Author(s):
LIU Xian-in; QIAO Yun-fei
School of Electric Engineering,Zhengzhou University,Zhengzhou 450001,China
关键词:
人工鱼群算法;  电力系统稳定器;  优化;  小扰动稳定性分析
Keywords:
artificial fish-swarm algorithm;  power system stabilizer;  optimization;  small signal stability analy-sis
分类号:
TM712
DOI:
10.3969/j.issn.1671-6833.2013.05.015
摘要:
为提高电网的动态稳定性,有效地抑制低频振荡,对电力系统稳定器进行优化研究和算法改进.在本研究中,将全部PSS的参数配置处理成一个优化问题,用人工鱼群算法求出各个PSS的最佳参数整定值.以所有机电模式的最小阻尼比最大为优化目标函数,以PSS参数为待优化变量,以基于K阵等值法设计的PSS参数作为人工鱼群算法初始种群的选取基准.与传统PSS配置方法相比,该方法可以使多机系统所有机电模式都能得到良好的阻尼.算例结果与预期基本相符,表明了所设计的优化算法是切实有效的.
Abstract:
In order to improve the dynamic stability of power grid and restrain low frequency oscillations effec-tively,research on optimization and improvements of the algorithm is developed for power system stabilizer. Inthis paper, all PSS parameters are conducted as an optimization problem,the best PSS parameters are figuredout by artificial fish-swarm algorithm.Maximizing the minimum damping ratio of all electromechanical mode ischosen for the optimal objective function. PSS parameters are chosen for optimal variable,design of PSsS pa-rameters based on the equivalence method of K matrix is used as the benchmark for initial population selectionof artificial fish-swarm algorithm. Good damping can be got for all electromechanical modes of the multima-chine system when using this method,compared with the conventional PSS configuration method. Calculatedresults are consistent with the expected results basically,which shows that the designed optimal algorithm is ef-fective.

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更新日期/Last Update: 1900-01-01