基于神经网络和混合遗传算法的凝汽器真空优化控制

Optimizing Control of the Vacuum in Power Plant Based on the Neural Network and the Hybrid Genetic Algorithms

利用人工神经网络进行凝汽器真空建模,然后采用混合遗传算法对运行工况寻优,以获得各种工况下凝汽器的最佳运行方式。通过对某电厂的300MW机组现场热态试验与计算,表明该方法可以指导运行人员进行凝汽器真空的优化调整。

A hybrid genetic algorithm and compound form method is employed to perform a search to determine the optimum solution of neural network model, which is used to set up a vacuum model, so as to obtain currently optimum combustion adjustment mode of vacuum. In this paper,a 300MW power plant is taken as an example to show the procedure of the computation and optimization, which was able to be transformed into practicable engineering guidance and the problem in optimal operation of the circulating water system which has puzzled power plants for a long time was settled.