Structure Modeling of Power Plant Thermal Progress Using Bayesian Inferring and Evolutionary Algorithm

Instead of using traditional transfer function model, a Bayesian inferring model was proposed as the structure of the thermal progress. And the inferring thermal progress model are based on Bayesian inferring formula and evolutionary algorithms. The whole modeling procedure includes two steps, in which the Bayesian inferring model is first presented with its training algorithms combined with evolutionary optimization algorithms and then on-line prediction of thermal progress output is realized based on sliding window data driven method. The given Bayesian inferring modeling method is applied to some typical thermal progress and the simulation results show that the presented Bayesian inferring model for thermal progress provides the characteristics of ease realization and high on-line tracing ability.