An expert system for startup optimization of combined cycle power plants under NOx emission regulation and machine life management

This paper proposes an expert system which optimizes the startup schedule for gas and steam turbine combined cycle power plants. The speed-up and load-up pattern of the plant is automatically optimized through an iterative process. Plant dynamics models representing quantitative knowledge and fuzzy rules representing qualitative knowledge are alternately used in the optimization process to modify the schedule parameters. The rules represent expertise on causal relations between modification rates of the schedule parameters and operational margins for constraints, i.e. NO_x emission and machine thermal stresses. Simulation analysis with a three pressure staged reheat type 235.7 MW rated capacity plant shows that the system provides quick and economical plant startup under NO_x emission regulation and reliable machine life management. Startup energy loss is reduced due to the reduction in startup time. Furthermore, optimum operating conditions are quickly reached with the expert system