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Multi-objective optimization of power, CO2 emission and exergy efficiency of a novel solar-assisted CCHP system using RSM and TOPSIS coupled method

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  • Mahdavi, Navid
  • Mojaver, Parisa
  • Khalilarya, Shahram

Abstract

In this study, the waste energy from exhausted gases of a gas turbine was recovered in a novel combined cooling, heating, and power system integrated of a gas turbine power plant, Kalina cycle, single-effect LiBr–H2O absorption chiller, parabolic trough collectors, heat recovery steam generator unit, and domestic hot water provision. This system utilized solar energy to preheat the air inlet to the combustion chamber and alleviated the emission of carbon dioxide resulted from consuming methane. An unparalleled algorithm was introduced to determine an optimum configuration of solar collectors. The results indicated that there were six optimum points with respect to maximum net power, minimum carbon dioxide emission and maximum exergy efficiency. The best optimum point was recognized using technique for order preferences by similarity to ideal solution method. The findings showed that compression ratio of 11.66, pinch point temperature difference in the air preheaters-1 of 11.96 K, inlet temperature of gas turbine-1 of 1470 K, and inlet temperature of combustion chamber of 900 K were the best multi-objective optimum conditions. In that condition, the net power, the system emission and the exergy efficiency were 61.73 MW, 52.87 g/MJ and 44.22%, respectively.

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  • Mahdavi, Navid & Mojaver, Parisa & Khalilarya, Shahram, 2022. "Multi-objective optimization of power, CO2 emission and exergy efficiency of a novel solar-assisted CCHP system using RSM and TOPSIS coupled method," Renewable Energy, Elsevier, vol. 185(C), pages 506-524.
    • Handle: RePEc:eee:renene:v:185:y:2022:i:c:p:506-524
    DOI: 10.1016/j.renene.2021.12.078
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    2. Nondy, J. & Gogoi, T.K., 2022. "Tri-objective optimization of two recuperative gas turbine-based CCHP systems and 4E analyses at optimal conditions," Applied Energy, Elsevier, vol. 323(C).
    3. Zhao, Xiangming & Guo, Jianxiang & He, Maogang, 2023. "Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification," Renewable Energy, Elsevier, vol. 217(C).
    4. Dezhdar, Ali & Assareh, Ehsanolah & Agarwal, Neha & Baheri, Alireza & Ahmadinejad, Mehrdad & Zadsar, Narjes & Fard, Ghazaleh Yeganeh & Ali bedakhanian, & Aghajari, Mona & Ghodrat, Maryam & Rahman, Moh, 2024. "Modeling, optimization, and economic analysis of a comprehensive CCHP system with fuel cells, reverse osmosis, batteries, and hydrogen storage subsystems Powered by renewable energy sources," Renewable Energy, Elsevier, vol. 220(C).
    5. Shakibi, Hamid & Shokri, Afshar & Assareh, Ehsanolah & Yari, Mortaza & Lee, Moonyong, 2023. "Using machine learning approaches to model and optimize a combined solar/natural gas-based power and freshwater cogeneration system," Applied Energy, Elsevier, vol. 333(C).
    6. Mahmoodi-Eshkaftaki, Mahmood & Dalvi-Isfahan, Mohsen, 2024. "Multiple exegetically optimization of ultrasonic pretreatment and substrate mixture for biohydrogen and biomethane improvement," Energy, Elsevier, vol. 292(C).
    7. Sun, Wen & Feng, Li & Abed, Azher M. & Sharma, Aman & Arsalanloo, Akbar, 2022. "Thermoeconomic assessment of a renewable hybrid RO/PEM electrolyzer integrated with Kalina cycle and solar dryer unit using response surface methodology (RSM)," Energy, Elsevier, vol. 260(C).

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