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

Abstract: To overcome the shortcomings of standard Particle Swarm Optimization(PSO), for example, prone to local optimum and slow later convergence and so on, shrinkage factor and chaos idea were adopted to improve standard PSO in the study. A novel design method for satisfactory function of hydro-turbine governing system was put forward. Chaos PSO was applied to parameters identification of controlled object for governing system. Quality parameters, 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 hydroelectric turbine-conduit system. Test results show that the simulated data correctly reflect the response characteristics of cascade frequency disturbance for the unit load, and meet the requirements of power grid stability calculation. Furthermore, under large interference, the algorithm still has accurate parameter identification and high convergence efficiency.

Key words: hydro turbine governor, modeling, parameter testing, satisfactory function, parameter identification, chaos particle swarm optimization