基于自适应遗传算法的PID调速系统参数优化  

Optimal Hydraulic Turbogenerators PID Governor Tuning with Genetic Algorithm for Self Adaptation, Symmetry and Congruity

作　　者：万星[1] 李伟[1] 乐丰[1] 

机构地区：[1]重庆交通大学

出　　处：《水力发电》2009年第3期61-64,共4页Water Power

基　　金：重庆市科委自然科学基金(CSTC2007BB6431);重庆市教委自然科学基金(Kj080414)

摘　　要：针对遗传算法(SGA)存在求解精度与收敛速度间的矛盾,提出了一种自适应对称调和遗传算法(IASHGA),并将该算法应用于水轮发电机组PID调速系统参数的优化设计,以系统的上升时间和超调量指标作为改进遗传算法的适应度函数。以四川某水电站的真实数据对经过优化后的遗传算法PID控制规律进行计算机仿真,仿真结果表明,改进的算法与常规遗传算法(SGA)和粒子群优化算法(PSO)相比较,不但提高了全局的搜寻能力,而且有效避免了早熟收敛问题,为水轮机调速器PID参数优化研究提供了新途径。In view of the conflict of precision and convergence speed in genetic algorithm, this paper puts forward a genetic algorithm for self adaptation, symmetry and congruity and applies it to optimize the PID parameters of hydro-generating unit. The rise time and overshoot volume targets was taken as the fitness function of the IASHGA algorithm. The real data from a hydropower plant in Sichuan were used to simulate the PID control law of optimized genetic algorithm. The results showed that the improved algorithm not only has better ability to converge to the global optimum than the simple genetic algorithm （GSA） and the PSO, but also can avoid the premature convergence effectively, which provides a new way for the study on the PID parameter optimization of speed governor of turbine.

关 键 词：对称调和 遗传算法 水轮发电机组 调速器 PID参数优化 

分 类 号：TM919[电气工程—电力电子与电力传动]