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A new biogas-fueled bi-evaporator electricity/cooling cogeneration system: Exergoeconomic optimization

Gholizadeh, T ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1016/j.enconman.2019.06.053
  3. Publisher: Elsevier Ltd , 2019
  4. Abstract:
  5. An innovative bi-evaporator electricity/cooling cogeneration system fueled by biogas is introduced. The plausibility of the introduced integrated power plant is examined from thermodynamic and economic vantage points. Later, single- and multi-objective optimization of the reckoned system are achieved by selecting appropriate parameters as decision variables and thermal and exergy efficiencies and total unit product cost (TUPC) of the system as objective functions. Four optimum modes of thermal efficiency optimum design (TEOD), exergy efficiency optimum design (EEOD), cost optimum design (COD), and multi-objective optimum design (MOOD) are selected for optimization and the attained results are compared with each other. In MOOD mode, it was found that the recommended system could generate optimum overall cooling load and net electricity of 641.7 kW and 1137 kW, respectively, achieving thermal efficiency of 62.69%, exergy efficiency of 38.75%, and TUPC of 7.75 $/GJ. It was substantiated that integrating the introduced cogeneration system with biogas-fueled gas turbine (GT) cycle could improve the thermal and exergy efficiencies up to 67.33% and 19.15% in the base mode and 77.84% and 15.94% in the optimum mode (MOOD mode), respectively. In MOOD mode, the TUPC of the integrated system is around 32.69% lower than that value in the GT cycle. The outcomes of the 2nd law evaluation portrayed that among all components, the combustion chamber attributes as the utmost destructive part of the system, followed by the vapor generator. Also, to examine how the introduced set-up reacts to any external fluctuations, a thoroughgoing sensitivity examination based upon given parameters was fulfilled. © 2019 Elsevier Ltd
  6. Keywords:
  7. Bi-evaporator ; Genetic algorithm ; Biogas ; Cogeneration plants ; Combustion chambers ; Efficiency ; Evaporators ; Exergy ; Gas turbines ; Genetic algorithms ; Optimization ; Cogeneration systems ; Cost optimum designs ; Exergoeconomic ; Exergoeconomic optimization ; Exergy efficiencies ; Multi-objective optimum designs ; Objective functions ; Recommended systems ; Multiobjective optimization
  8. Source: Energy Conversion and Management ; Volume 196 , 2019 , Pages 1193-1207 ; 01968904 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0196890419307241