直接空冷机组凝汽器动态系统参数辨识

Parameter Identification of Condenser Dynamic System of Direct Air-cooled Unit

直接空冷机组凝汽器是受机组负荷与自然风扰动的复杂热力系统,准确预测直接空冷机组汽轮机背压的动态响应特性,对于背压控制器的优化设计尤为重要。以一660 MW直接空冷机组实际运行数据为参数样本,基于惯性权重自适应的粒子群优化算法对空冷机组背压动态系统模型进行参数辨识,验证变工况动态模型的鲁棒性,进而设计前馈控制器,以快速响应机组负荷对背压的扰动。结果表明:在不同工况下,基于惯性权重自适应调节的粒子群优化算法辨识出的参数模型可以准确描述直接空冷机组的负荷、空冷风机转速指令与汽轮机背压之间的动态过程特性;前馈控制可有效减小机组负荷对汽机背压的不利扰动,提高控制系统调节快速性。

The condenser of a direct air-cooled unit is a complex thermal system disturbed by unit load and natural wind.Accurately predicting the dynamic response characteristics of the turbine back pressure of a direct air-cooled unit is particularly important for the optimal design of the back pressure controller.Taking the actual operating data of a 660 MW direct air-cooled unit as a parameter sample,based on the inertial weight adaptive particle swarm optimization algorithm,this paper parameterized the air-cooled unit back pressure dynamic system model to verify the robustness of the variable-condition dynamic model,and then design the feedforward controller to respond quickly to the disturbance of the unit load to the back pressure.The results show that under different working conditions,the parameter model identified by the particle swarm optimization algorithm based on the adaptive adjustment of inertial weight can accurately describe the dynamic process characteristics of the direct air-cooled unit load,the air-cooled fan speed command and the steam turbine back pressure;feedforward control can effectively reduce the unfavorable disturbance of unit load to turbine back pressure and improve the speed of control system adjustment.