Thermo-environmental and economic analysis of simple and regenerative gas turbine cycles with regression modeling and optimization

• Published in: Energy conversion and management 2013-12, Vol.76, p.852-864
• Main Authors: Memon, Abdul Ghafoor, Harijan, Khanji, Uqaili, Mohammad Aslam, Memon, Rizwan Ahmed
• Format: Article
• Language: English
• Subjects: Applied sciences; Energy; Energy. Thermal use of fuels; Engines and turbines; Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc; Exact sciences and technology; Exergy analysis; Gas turbine; Optimization; Regression analysis
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2013.07.076

•Thermodynamic models of simple and regenerative cycles are defined.•Exergy destruction rate of different components was determined.•Impact of important operating parameters on cycles’ characteristics was determined.•Multiple polynomial regression models were developed.•Optimization for optimal operating parameters was performed. In this paper, thermo-environmental, economic and regression analyses of simple and regenerative gas turbine cycles are exhibited. Firstly, thermodynamic models for both cycles are defined; exergy destruction rate of different components is determined and parametric study is carried out to investigate the effects of compressor inlet temperature, turbine inlet temperature and compressor pressure ratio on the parameters that measure cycles’ performance, environmental impact and costs. Subsequently, multiple polynomial regression (MPR) models are developed to correlate important response variables with predictor variables and finally optimization is performed for optimal operating conditions. The results of parametric study have shown a significant impact of operating parameters on the performance parameters, environmental impact and costs. According to exergy analysis, the combustion chamber and exhaust stack are two major sites where largest exergy destruction/losses occur. Also, the total exergy destruction in the regenerative cycle is relatively lower; thereby resulted in a higher exergy efficiency of the cycle. The MPR models are also appeared as good estimator of the response variables since appended with very high R2 values. Finally, these models are used to determine the optimal operating parameters, which maximize the cycles’ performance and minimize CO2 emissions and costs.