LAPSE:2021.0270
Published Article
LAPSE:2021.0270
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages
April 29, 2021
Due to the harmful effects and depletion of non-renewable 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 high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively.
Keywords
Genetic Algorithm, geothermal cycle, Optimization, organic Rankine cycle
Suggested Citation
Ehyaei MA, Ahmadi A, Rosen MA, Davarpanah A. Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages. (2021). LAPSE:2021.0270
Author Affiliations
Ehyaei MA: Department of Mechanical Engineering, Pardis Branch, Islamic Azad University, Pardis New City 1468995513, Iran
Ahmadi A: Department of Energy Systems, School of New Technologies, Iran University of Science and Technology, Tehran 1584743311, Iran [ORCID]
Rosen MA: Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, ON L1G 0C5, Canada [ORCID]
Davarpanah A: Department of Mathematics, Aberystwyth University, Aberystwyth SY23 3FL, UK [ORCID]
Journal Name
Processes
Volume
8
Issue
10
Article Number
E1277
Year
2020
Publication Date
2020-10-12
Published Version
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr8101277, Publication Type: Journal Article
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LAPSE:2021.0270
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doi:10.3390/pr8101277
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Apr 29, 2021
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CC BY 4.0
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Apr 29, 2021
 
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Original Submitter
Calvin Tsay
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