基于遗传算法和模糊推理优化的单元机组负荷控制系统

Load Control System of Thermal Power Sets Based on Genetic Algorithm and Fuzzy Reasoning

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。

For the problem of the weak load adaptability of the conventional control strategy of thermal power sets, and in condition of frequency and peakload modulation, the system will be difficult to maintain the automatic operation, a novel design method for the load control system of thermal power sets is proposed based on the genetic algorithm and the fuzzy reasoning. The PID controller parametres of the load control system are tunned under specified load level based on the genetic algorithm. The PID controller parametres are regulated online using the fuzzy reasoning under varying load levels. The realtime adjustment of PID controller parameters is realized, and works on the optimum control effect of the load control system is obtained. Simulations in load contro! system of thermal power sets show that the novel design method has better control performance and stronger adaptability than the traditional design method.