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Thermodynamic Optimization of a Geothermal- Based Organic Rankine Cycle System Using an Artificial Bee Colony Algorithm

Author

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  • Osman Özkaraca

    (Department of Information Systems Engineering, Technology Faculty, Muğla Sıtkı Koçman University, 48000 Muğla, Turkey)

  • Pınar Keçebaş

    (Department of Energy, Graduate School of Natural and Applied Sciences, Muğla Sıtkı Koçman University, 48000 Muğla, Turkey)

  • Cihan Demircan

    (Department of Energy Systems Engineering, Graduate School of Natural and Applied Sciences, Süleyman Demirel University, 32260 Isparta, Turkey)

  • Ali Keçebaş

    (Department of Energy Systems Engineering, Technology Faculty, Muğla Sıtkı Koçman University, 48000 Muğla, Turkey)

Abstract

Geothermal energy is a renewable form of energy, however due to misuse, processing and management issues, it is necessary to use the resource more efficiently. To increase energy efficiency, energy systems engineers carry out careful energy control studies and offer alternative solutions. With this aim, this study was conducted to improve the performance of a real operating air-cooled organic Rankine cycle binary geothermal power plant (GPP) and its components in the aspects of thermodynamic modeling, exergy analysis and optimization processes. In-depth information is obtained about the exergy (maximum work a system can make), exergy losses and destruction at the power plant and its components. Thus the performance of the power plant may be predicted with reasonable accuracy and better understanding is gained for the physical process to be used in improving the performance of the power plant. The results of the exergy analysis show that total exergy production rate and exergy efficiency of the GPP are 21 MW and 14.52%, respectively, after removing parasitic loads. The highest amount of exergy destruction occurs, respectively, in condenser 2, vaporizer HH2, condenser 1, pumps 1 and 2 as components requiring priority performance improvement. To maximize the system exergy efficiency, the artificial bee colony (ABC) is applied to the model that simulates the actual GPP. Under all the optimization conditions, the maximum exergy efficiency for the GPP and its components is obtained. Two of these conditions such as Case 4 related to the turbine and Case 12 related to the condenser have the best performance. As a result, the ABC optimization method provides better quality information than exergy analysis. Based on the guidance of this study, the performance of power plants based on geothermal energy and other energy resources may be improved.

Suggested Citation

  • Osman Özkaraca & Pınar Keçebaş & Cihan Demircan & Ali Keçebaş, 2017. "Thermodynamic Optimization of a Geothermal- Based Organic Rankine Cycle System Using an Artificial Bee Colony Algorithm," Energies, MDPI, vol. 10(11), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1691-:d:116402
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    References listed on IDEAS

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    Cited by:

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    2. Shiqi Wang & Zhongyuan Yuan, 2020. "A Hot Water Split-Flow Dual-Pressure Strategy to Improve System Performance for Organic Rankine Cycle," Energies, MDPI, vol. 13(13), pages 1-21, June.
    3. Alfredo Gimelli & Massimiliano Muccillo, 2018. "The Key Role of the Vector Optimization Algorithm and Robust Design Approach for the Design of Polygeneration Systems," Energies, MDPI, vol. 11(4), pages 1-21, April.
    4. Çetin, Gürcan & Keçebaş, Ali, 2021. "Optimization of thermodynamic performance with simulated annealing algorithm: A geothermal power plant," Renewable Energy, Elsevier, vol. 172(C), pages 968-982.
    5. Gürbüz, Emine Yağız & Güler, Onur Vahip & Keçebaş, Ali, 2022. "Environmental impact assessment of a real geothermal driven power plant with two-stage ORC using enhanced exergo-environmental analysis," Renewable Energy, Elsevier, vol. 185(C), pages 1110-1123.
    6. Çetin, Gürcan & Özkaraca, Osman & Keçebaş, Ali, 2021. "Development of PID based control strategy in maximum exergy efficiency of a geothermal power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).

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