Thermodynamic performance simulation and concise formulas for triple-pressure reheat HRSG of gas–steam combined cycle under off-design condition

Concise semi-theoretical, semi-empirical formulas are developed in this study to predict the off-design performance of the bottoming cycle of the gas–steam turbine combined cycle. The formulas merely refer to the key thermodynamic design parameters (full load parameters) of the bottoming cycle and off-design gas turbine exhaust temperature and flow, which are convenient in determining the overall performance of the bottoming cycle. First, a triple-pressure reheat heat recovery steam generator (HRSG) is modeled, and thermodynamic analysis is performed. Second, concise semi-theoretical, semi-empirical performance prediction formulas for the bottoming cycle are proposed through a comprehensive analysis of the heat transfer characteristics of the HRSG and the energy conversion characteristics of the steam turbine under the off-design condition. The concise formulas are found to be effective, i.e., fast, simple, and precise in obtaining the thermodynamic parameters for bottoming cycle efficiency, HRSG heat transfer capacity, HRSG efficiency, steam turbine power output, and steam turbine efficiency under the off-design condition. Accuracy is verified by comparing the concise formulas’ calculation results with the simulation results and practical operation data under different load control strategies. The calculation errors are within 1.5% (mainly less than 1% for both simulation and actual operation data) under combined cycle load (gas turbine load) ranging from 50% to 100%. However, accuracy declines sharply when the turbine exhaust temperature seriously deviates from the design value and several specific operation strategies are employed when the units operate at ultra-low load (50% less combined cycle load/gas turbine load). The prediction results can be utilized as a relative reference. To improve prediction accuracy, a corresponding correction factor can be introduced for modification based on operating experience.

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