The Optimization of a Pulverizing System Based on Genetic Algorithm and Neural Network
The economical operation of pulverized system directly influences the economical operation of thermal power unit. During the operation, power station should try its best to improve the output of pulverized system and reduce the electric consumption of pulverized system on the safe operation. Pulverized system’s optimize operation is a multivariable, non-linear and time-varying system. The factors included in the system coupled into each other seriously and the whole system can’t be simulated by quadratic equations. This paper advance an algorithm combined genetic algorithm and neural network. Neural network can be used to predict system’s practical operation and genetic algorithm is used to optimize the operation condition and its parameters. In genetic algorithm’s application, import penitentiary function and transform the restriction functions restricted in a certain bound to restriction functions with no bound. Simulation result indicates that the adopted neural network can predict the practical operation of pulverized system well and the optimized operation used the method using genetic algorithm based on neural network is better than before.
Neural network Genetic algorithm Penitentiary function Pulverized system
Ao Liu Yan Fen Liao Xiao Qian Ma
Electric Power College, South China University of Technology, Guangzhou, 510640, China
国际会议
2007杭州国际动力工程会议(The International Conference on Power Engineering 2007)
杭州
英文
2007-10-23（万方平台首次上网日期，不代表论文的发表时间）