This paper reports a method of dynamic simulation parameter tuning for a coal-fired power plant using genetic algorithms (GA). GA is a search algorithm based on the mechanics of natural selection and natural genetics. GA is one of the effective methods for optimization problems and it requires a formalization of problems and a fitness function definition. Because the dynamic simulation can be repeated and the error between real data and simulation results is defined by a fitness function, it is reasonable to consider genetic operations. In order to satisfy the environmental laws and regulations, the control of NO, emission is important in the field of power plant. We have, therefore, made a NOs analytical model and used the model for the dynamic simulation at the change of loads, the kind of coal, and so on. In this paper, the optimal parameters for the simulation are determined by GA.
This paper reports a method of dynamic simulation parameter tuning for a coal‐fired power plant using genetic algorithms (GA). GA is a search algorithm based on the mechanics of natural selection and natural genetics. GA also is one of the effective methods for optimization problems and it requires a formalization of problems and a fitness function definition. Because the dynamic simulation can be repeated and the error between real data and simulation results is defined by a fitness function, it is reasonable to consider genetic operations.
To satisfy environmental laws and regulations, the control of NOx emission is important for the operation of power plants. Therefore, an NOx analytical model is designed and used for the dynamic simulation at the change of loads, the kind of coal, and so on. In this paper, the optimal parameters for the simulation are determined by GA.
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