Control is the conscious impact on a process in order to realize specific goals. When controlling complex industry processes, the most frequent control method is based on a layered structure (hierarchical), which includes a layer of regulation and protection and a layer of optimization. The optimization layer is used to identify the most cost-effective levels for the regulation layer. This includes the use of process static models that must be structurally simple and quick at calculating, while maintaining a high level of accuracy. The most frequent method of model designing involves experimental analysis called process identification. However, we can develop models that result from the laws of physics with additional use of empirical relationships. This article presents a simulation model of a double-pressure heat recovery steam generator (HRSG) in gas turbine combined cycle power plant. The model was developed based on the equations of mass and energy balances and the empirical relationships describing the process of heat transfer and pressure drop of working fluid in the heat exchanger. Unknown values of empirical coefficients were estimated based on the operating data with the least-squares method. The model allows the calculation of nonmeasured operating parameters and energy assessment indicators. An important benefit of the developed model is that it has the capability of adapting to the changing technical conditions of the HRSG. The results of calculations were compared to the results of measurements. Model predictive quality was verified with the use of the determination factor and root mean square error.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.