Exergy diagnosis of coal fired CHP plant with application of neural and regression modelling

Abstract

Mathematical models of the processes, that proceed in energetic machines and devices, in many cases are very complicated. In such cases, the exact analytical models should be equipped with the auxiliary empirical models that describe those parameters which are difficult to model in a theoretical way. Regression or neural models identified basing on measurements are rather simple and are characterized by relatively short computation time. For this reason they can be effectively applied for simulation and optimization of steering and regulation processes, as well as, for control and thermal diagnosis of operation (eq. power plants or CHP plants). In the paper regression and neural models of thermal processes developed for systems of operation control of thermal plants are presented. Theoretical-empirical model of processes proceeding in coal fired CHP plant have been applied. Simulative calculations basing on these models have been carried out. Results of simulative calculations have been used for the exergetic evaluation of considered power plant. The diagnosis procedure let to investigate the formation of exergy costs in interconnected components of the system of CHP, as well as, investigate the influence of defects in operation of components on exergy losses and on the exergetic cost in other components.