An Improved Simulated Annealing for Ball Mill Pulverizing System Optimization of Thermal Power Plant

This paper proposes an improved simulated annealing for ball mill pulverizing system optimization of thermal power plan. The proposed algorithm combines the simulated annealing and Tabu search and for the annealing operations, the current calculated solution is evaluated according to the neighborhood of the values in Tabu list. Moreover, some rules for the generation of the neighborhood solution are presented based on the characteristics of the ball mill pulverizing system. The proposed algorithm is performed on the real field data. The results of the experiments verify that the proposed algorithm could determine the optimal values of process variables correctly and has faster convergence speed. In addition, the proposed algorithm has been put into practice and the statistic data show that the working time of ball mill pulverizing system is decreased and the energy consumption would be reduced.

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