基于灰狼优化算法的燃气轮机自抗扰控制参数整定研究

Study on Active Disturbance Rejection Control Parameters of Gas Turbine based on Grey Wolf Optimization Algorithm

为了优化负载突变情况下燃气轮机性能,基于灰狼优化算法对燃气轮机自抗扰控制进行了参数整定,并在燃气轮机0.2额定工况范围内发生负载突变情况下进行了半物理仿真实验。仿真结果表明:与传统PID参数控制结果相比,负载由0.6额定工况突增至0.8额定工况和由0.8额定工况突降至0.6工况情况下,动力涡轮转速上升时间分别缩短1.28 s、1.07 s,调节时间缩短11 s,最大超调量分别减少了0.25%、0.3%。

In order to optimize the performance of gas turbine under sudden load changes,parameter tuning of gas turbine active disturbance rejection control(ADRC)was carried out based on the grey wolf optimization(GWO)algorithm,and the semi-physical simulation experiments were conducted under 0.2 rated condition of gas turbine sudden load change.The simulation results show that compared with traditional PID parameter control results,when the load suddenly increases from 0.6 rated condition to 0.8 rated condition,and the load suddenly decreases from 0.8 rated condition to 0.6 rated condition,the rise time of the power turbine rotating speeds are shortened by 1.28 s and 1.07 s respectively,the adjustment time is shortened by 11 s,and the maximum overshoot is reduced by 0.25%and 0.3%respectively.