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针对采用常规控制策略控制下的单元机组负荷控制系统负荷适应能力差、机组调频调峰时难以自动运行这一难题,提出了一种基于遗传算法和模糊推理的单元机组负荷控制系统设计新方案。首先利用遗传算法整定出某一负荷下单元机组负荷控制系统中PID控制器参数,再采用模糊推理不断修正变负荷时的PID控制器参数,实现PID参数的实时调整,使控制系统达到最佳控制效果。通过对火电单元机组负荷控制系统的设计和仿真研究,证明了用这种方法设计的单元机组负荷控制系统具有更好的控制效果和更强的适应能力。
Aiming at the problem of load adaptability of unit load control system under the control of conventional control strategy and difficulty of automatic operation when unit frequency modulation and peak regulation is difficult, a new scheme of unit load control system design based on genetic algorithm and fuzzy inference is proposed. Firstly, the parameters of PID controller in unit load control system under certain load are set by genetic algorithm, then the parameters of PID controller at variable load are modified by fuzzy inference to realize the real-time adjustment of PID parameters and achieve the best control of the control system effect. Through the design and simulation of load control system of thermal power unit, it is proved that the unit load control system designed by this method has better control effect and stronger adaptability.