长江科学院院报2016，Vol.33Issue(8)：138-143,150,7.DOI:10.11988/ckyyb.20150482
基于混沌粒子群算法的水轮机调速系统参数辨识及建模试验
Parameters Identification of Hydro-turbine Governing System Based on Chaos Particle Swarm Optimization and Modeling Experiment
冯雁敏 1王湛 1张雪源 2张恩博 1刘春林1
作者信息
- 1. 国家电网辽宁省电力有限公司电力科学研究院，沈阳 110006
- 2. 东北电网有限公司，沈阳 110180
- 折叠
摘要
Abstract
To overcome the shortcomings of standard Particle Swarm Optimization (PSO), for example, prone to lo-cal optimum and slow later convergence and so on , shrinkage factor and chaos idea were adopted to improve stand-ard PSO in the study .A novel design method for satisfactory function of hydro-turbine governing system was put for-ward.Chaos PSO was applied to parameters identification of controlled object for governing system .Quality parame-ters, such as rise time, settling time, hydro-turbine’ s reverse peak power and reverse peak time , were directly measured , and the overall satisfaction level of system was taken as fitness function .On the basis of the new method , the control parameters of a hydro-turbine governor were measured in association with parameter identification of hy-droelectric turbine-conduit system .Test results show that the simulated data correctly reflect the response character-istics of cascade frequency disturbance for the unit load , and meet the requirements of power grid stability calcula-tion.Furthermore, under large interference , the algorithm still has accurate parameter identification and high con-vergence efficiency .关键词
水轮机调速器/建模/参数测试/满意度函数/参数辨识/混沌粒子群算法Key words
hydro turbine governor/modeling/parameter testing/satisfactory function/parameter identification/chaos particle swarm optimization分类
能源科技引用本文复制引用
冯雁敏,王湛,张雪源,张恩博,刘春林..基于混沌粒子群算法的水轮机调速系统参数辨识及建模试验[J].长江科学院院报,2016,33(8):138-143,150,7.
