Multi-objective optimization of a geothermal-based multigeneration system for heating, power and purified water production purpose using evolutionary algorithm

• Published in: Energy conversion and management Vol. 223; p. 113476
• Main Authors: Ansarinasab, Hojat, Hajabdollahi, Hassan
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2020; Elsevier Science Ltd
• Subjects: Algorithms; Desalination; Desalination system; Design parameters; Evolutionary algorithms; Exergy; Genetic algorithm; Genetic algorithms; Geothermal energy; Heat exchangers; Heating; Liquefied natural gas; Multi-objective optimization; Multiple objective analysis; Natural gas; Optimization; Organic Rankine cycle; Parameter sensitivity; Rankine cycle engines; Sensitivity analysis; Stirling cycle; Stirling engines; Thermodynamics; Water purification; Multi-objective optimization; Stirling cycle; Genetic algorithm; Geothermal energy; Desalination system; Organic Rankine cycle
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2020.113476

•A new multi-generation system based on geothermal energy is developed.•An exergoeconomic optimization is implemented on the developed system.•Advanced exergy analysis is performed on the developed system at optimal point.•Exergy efficiency and total product unit cost of the developed system are 52.65% and 4.35 $/GJ. This study aims to develop a new multigeneration system based on geothermal energy and liquefied natural gas cold energy. The developed system includes dual fluid organic Rankine cycle and stirling engine to produce power, a desalination unit to produce purified water and a water heater to produce heating. Exergy and exergoeconomic analyses are carried out to determine the irreversibilities and the inefficient costs of each component of the developed process. The results show that the used heat exchanger (number 4), in liquefied natural gas regasification plant (26.72 $/h) and the used pump (number 3), in the desalination system (0.001 $/h), obtain the maximum and the minimum amount of exergy destruction cost. Moreover, multi-objective optimization is performed based on genetic algorithms. Achieved outcomes demonstrate that at the optimal point where exergy efficiency of the whole system as well as product cost rate are optimized, the corresponding values are 52.65% and 4.35 $/GJ, respectively. A sensitivity analysis is provided to assess the effects of design parameters on objective functions. Finally, advanced exergy analysis is performed on the most inefficient system components. Based on the avoidable endogenous part of irreversibility, heat exchangers (number 4) (843 kW), (number 3) (664 kW) and (number 1) (599 kW) should be modified first, respectively.