Energy Conservation And Optimization Of Milling System In Coal-fired Power Plants

This paper has been optimized and analyzed the milling system focusing on a thermal power plant in Baoding. By transforming the fans and adjusting the milling system parameter, the consumption of milling system can be reduced and the energy can be saved.The thermal power plant uses a fan with variable pitch blades, we can install inverter system on it, so that fans can be at different loads remaining high efficiency; By establishing a probability distribution function, we can get the best steel ball gradation and balls filling system;The power of this system is influenced by many factors which interact with each other. If all factors are involved in the neural network, the calculation of model will be very large. So we use the analytic hierarchy process based on the Uniform incidence degree to weigh the weight and analyze of the correlation between the coal output and each parameter by its gray correlation, picking out a greater impact on the milling unit consumption as the auxiliary variables of modeling (mill speed, the amount of primary air, primary air temperature). Through establishing different neural network algorithm, we established a function between the coal output and the milling various factors. Then the lowest figure was found under different milling output power conditions by using genetic algorithm. The final figure was the best solution.