火电厂自动电压控制系统的优化研究

Optimization of Thermal Power Plant automatic voltage control system

针对火电厂自动电压控制(Automatic voltage control,AVC)在实际运行过程中会出现电压振荡、不调、过调和不能快速跟踪偏差等问题,以及考虑到系统阻抗的影响,为提高其控制品质,本文提出了自适应遗传算法在线整定PID控制的优化策略。该方法利用自适应遗传算法对PID控制器参数实现在线寻优与整定,选择种群中自适应度大的个体所对应的PID控制器参数,作为当前仿真时间下的PID控制最优参数。利用已建立的云南某火电厂AVC系统模型进行仿真,结果表明该算法大大提高了响应速度,有效抑制了超调,使得控制过程更加平稳,控制效果更好。

Thermal Power Plant automatic voltage control （Automatic voltage control, AVC） in actual operation there will be voltage oscillations, not adjusted, overshoot and can not fast-track deviation and other issues, to address the problem, and taking into account the impact of the system impedance, in order to improve its control quality, the paper proposes an adaptive genetic algorithm optimization strategy online tuning PID control. The method uses adaptive genetic algorithm PID controller parameters for online optimization and tuning, select populations of individual adap-tive degree corresponding PID controller parameters, current simulation time as PID control under optimal parameters. The use of a thermal power plant in Yunnan AVC system established model simulation results show that the algorithm greatly improves the speed of response, effectively suppresses overshoot, so that the control process more smooth, controlled better..