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基于过热汽温的分布参数模型,采用高阶惯性传递函数进行逼近。为分析串级回路中导前区、惰性区模型阶次对辨识精度的影响和得到高阶惯性传递函数的动态参数,根据电厂实际运行的数据,采用多目标遗传算法对模型参数进行优化和仿真。通过分析仿真可知,阶次在合理的范围时阶次越高时帕累托前锋面越靠前,辨识具有更高的精确度。考虑实际需求与精度的要求,建立该机组过热汽温系统的串级模型。
Based on the distribution parameter model of superheated steam temperature, the high-order inertial transfer function is used to approximate. In order to analyze the influence of order of lead zone and inert zone on identification accuracy and get the dynamic parameters of high-order inertial transfer function, the multi-objective genetic algorithm is used to optimize and simulate the model parameters according to the actual operation data of power plant. . By analyzing the simulation, it can be seen that the higher the order is, the higher the order is and the higher the Pareto front is, the higher the accuracy is. Considering the requirements of actual demand and accuracy, a cascade model of superheated steam temperature system of the unit was established.