Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages
Due to the harmful effects and depletion of nonrenewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geoth...
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doajedbfeabf6b0942189113dfccd7b3fa6620201125T02:44:52ZengMDPI AGProcesses222797172020100181277127710.3390/pr8101277Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two StagesM. A. Ehyaei0A. Ahmadi1Marc A. Rosen2Afshin Davarpanah3Department of Mechanical Engineering, Pardis Branch, Islamic Azad University, Pardis New City 1468995513, IranDepartment of Energy Systems, School of New Technologies, Iran University of Science and Technology, Tehran 1584743311, IranFaculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, ON L1G 0C5, CanadaDepartment of Mathematics, Aberystwyth University, Aberystwyth SY23 3FL, UKDue to the harmful effects and depletion of nonrenewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the hightemperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively.https://www.mdpi.com/22279717/8/10/1277geothermal cycleorganic Rankine cycleoptimizationgenetic algorithm 
collection 
DOAJ 
language 
English 
format 
Article 
sources 
DOAJ 
author 
M. A. Ehyaei A. Ahmadi Marc A. Rosen Afshin Davarpanah 
spellingShingle 
M. A. Ehyaei A. Ahmadi Marc A. Rosen Afshin Davarpanah Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages Processes geothermal cycle organic Rankine cycle optimization genetic algorithm 
author_facet 
M. A. Ehyaei A. Ahmadi Marc A. Rosen Afshin Davarpanah 
author_sort 
M. A. Ehyaei 
title 
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages 
title_short 
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages 
title_full 
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages 
title_fullStr 
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages 
title_full_unstemmed 
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages 
title_sort 
thermodynamic optimization of a geothermal power plant with a genetic algorithm in two stages 
publisher 
MDPI AG 
series 
Processes 
issn 
22279717 
publishDate 
20201001 
description 
Due to the harmful effects and depletion of nonrenewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the hightemperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively. 
topic 
geothermal cycle organic Rankine cycle optimization genetic algorithm 
url 
https://www.mdpi.com/22279717/8/10/1277 
work_keys_str_mv 
AT maehyaei thermodynamicoptimizationofageothermalpowerplantwithageneticalgorithmintwostages AT aahmadi thermodynamicoptimizationofageothermalpowerplantwithageneticalgorithmintwostages AT marcarosen thermodynamicoptimizationofageothermalpowerplantwithageneticalgorithmintwostages AT afshindavarpanah thermodynamicoptimizationofageothermalpowerplantwithageneticalgorithmintwostages 
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