Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms
In this study, a general description of geothermal power plants is provided, and the optimization methods used are summarized. Following the review of these optimization methods, the advantages of heuristic methods and the success of the developed models are demonstrated. The challenges in optimizin...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/1996-1073/18/2/311 |
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| author | Özgür Özer Harun Kemal Öztürk |
| author_facet | Özgür Özer Harun Kemal Öztürk |
| author_sort | Özgür Özer |
| collection | DOAJ |
| description | In this study, a general description of geothermal power plants is provided, and the optimization methods used are summarized. Following the review of these optimization methods, the advantages of heuristic methods and the success of the developed models are demonstrated. The challenges in optimizing geothermal systems, including the limitations due to their complexity and the use of multiple parameters, are discussed. Heuristic methods, particularly the widely used artificial neural networks and genetic algorithms, are explained in general terms. Recent studies highlight that the combined use of artificial neural networks and genetic algorithms can produce faster and more consistent results. This demonstrates the benefits of using advanced methods for geothermal resource utilization and power plant optimization. An innovative optimization method has been developed using the operational data of an ORC geothermal power plant in the city of Izmir. The computational method, using genetic algorithms with artificial neural networks as the fitness function, has identified the optimal operating conditions, achieving a 39.41% increase in net power output. The plant’s gross power generation has increased from 4943 kW to 6624 kW. |
| format | Article |
| id | doaj-art-b506ef7d7f8d4445a39c257e1126913a |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-b506ef7d7f8d4445a39c257e1126913a2025-01-24T13:30:59ZengMDPI AGEnergies1996-10732025-01-0118231110.3390/en18020311Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic AlgorithmsÖzgür Özer0Harun Kemal Öztürk1Department of Mechanical Engineering, Graduate School of Natural and Applied Sciences, Pamukkale University, 20160 Pamukkale, TürkiyeDepartment of Mechanical Engineering, Faculty of Engineering, Pamukkale University, 20160 Pamukkale, TürkiyeIn this study, a general description of geothermal power plants is provided, and the optimization methods used are summarized. Following the review of these optimization methods, the advantages of heuristic methods and the success of the developed models are demonstrated. The challenges in optimizing geothermal systems, including the limitations due to their complexity and the use of multiple parameters, are discussed. Heuristic methods, particularly the widely used artificial neural networks and genetic algorithms, are explained in general terms. Recent studies highlight that the combined use of artificial neural networks and genetic algorithms can produce faster and more consistent results. This demonstrates the benefits of using advanced methods for geothermal resource utilization and power plant optimization. An innovative optimization method has been developed using the operational data of an ORC geothermal power plant in the city of Izmir. The computational method, using genetic algorithms with artificial neural networks as the fitness function, has identified the optimal operating conditions, achieving a 39.41% increase in net power output. The plant’s gross power generation has increased from 4943 kW to 6624 kW.https://www.mdpi.com/1996-1073/18/2/311energygeothermaloptimizationefficiencyheuristic methods |
| spellingShingle | Özgür Özer Harun Kemal Öztürk Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms Energies energy geothermal optimization efficiency heuristic methods |
| title | Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms |
| title_full | Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms |
| title_fullStr | Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms |
| title_full_unstemmed | Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms |
| title_short | Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms |
| title_sort | innovative approaches of optimization methods used in geothermal power plants artificial neural networks and genetic algorithms |
| topic | energy geothermal optimization efficiency heuristic methods |
| url | https://www.mdpi.com/1996-1073/18/2/311 |
| work_keys_str_mv | AT ozgurozer innovativeapproachesofoptimizationmethodsusedingeothermalpowerplantsartificialneuralnetworksandgeneticalgorithms AT harunkemalozturk innovativeapproachesofoptimizationmethodsusedingeothermalpowerplantsartificialneuralnetworksandgeneticalgorithms |