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针对火电机组冷端系统的影响因素进行全面的分析,获得以供电煤耗率最小为目标函数,以循环水流量、循环水温度、凝汽器过冷度、凝汽器结垢、漏空气等客观条件为变量的优化模型。运用遗传算法对机组多因素进行了优化,得到最小煤耗及其对应的各参数优化条件。通过比较发现运用遗传算法不仅能快速准确地对冷端系统进行优化,而且还能通过参数的自动调整对由于某些参数缺陷所造成的经济性下降进行补偿,以获得最佳的运行方式,实现最大的经济效益。
According to the comprehensive analysis of the influencing factors of the cold end system of thermal power unit, the objective function of minimizing the coal consumption rate is obtained. With the objective of circulating water flow, circulating water temperature, condenser subcooling, condenser fouling and air leakage, The condition is a variable optimization model. The genetic algorithm is used to optimize the multi-factors of the unit, and the minimum coal consumption and the corresponding optimization parameters are obtained. By comparison, it is found that the genetic algorithm can not only optimize the cold-end system quickly and accurately, but also can compensate for the economic decline caused by some parameter defects through the automatic adjustment of parameters in order to obtain the best operation mode and achieve The biggest economic benefits.