Mathematical Modelling and Optimisation of Operating Parameters for Enhanced Energy Generation in Gas Turbine Power Plant with Intercooler
This study developed an optimal model for gas turbine power plants (GTPPs) with intercoolers, focusing on the challenges related to power output, thermal efficiency and specific fuel consumption. The study combined response surface methodology (RSM) and central composite design (CCD) with advanced m...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/1/174 |
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| Summary: | This study developed an optimal model for gas turbine power plants (GTPPs) with intercoolers, focusing on the challenges related to power output, thermal efficiency and specific fuel consumption. The study combined response surface methodology (RSM) and central composite design (CCD) with advanced metaheuristic algorithms, including ANFIS, ANFIS PSO and ANFIS GA, to model nonlinear interactions of key parameters, including the pressure ratio, ambient temperature, turbine inlet temperature and the effectiveness of the intercooler. Optimal values of thermal efficiency (47.8%), power output (165 MW) and specific fuel consumption (0.16 kg/kWh) were attained under conditions of a pressure ratio of 25, an ambient temperature 293 K, a turbine inlet temperature of 1550 K and 95% intercooler effectiveness. The RSM, being the initial model, was able to predict but lacked precision when compared with the nonlinear influences that were modelled by ANFIS PSO and ANFIS GA, with power output, thermal efficiency and specific fuel consumption (sfc) having corresponding R<sup>2</sup> values of 0.979, 0.987 and 0.972. The study demonstrated the potential of extending metaheuristic algorithms to provide sustainable solutions to energy system problems and reduced emissions through gas turbine power plant (GTPP) optimisation. |
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| ISSN: | 2227-7390 |