A simulated model for a once-through boiler by parameter adjustment based on genetic algorithms

In this paper based on the physical rules, thermodynamics principles and energy mass balance, the simulation models are developed and applied to electrical power generating plants in order to characterize the essential dynamic behavior of the boiler subsystems and to use the corresponding models for the power plant processes. These models are developed for a sub-critical once through Benson type boiler based on the experimental data obtained from a complete set of field experiments. An optimization approach based on genetic algorithm (GA) is executed to estimate the model parameters and fit the models response on the real system dynamics. Comparison between the responses of the corresponding models with the response of the real plants validates the accuracy and performance of modeling approach. A similar comparison between the responses of these models with linear parametric models shows the effectiveness and feasibility of the developed model in term of more accurate and less deviation between the responses of the models and the corresponding subsystems.