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Risk Based Maintenance in the Hydroelectric Power Plants

Author

Listed:
  • Evrencan Özcan

    (Department of Industrial Engineering, Faculty of Engineering, Kırıkkale University, 71450 Kırıkkale, Turkey)

  • Rabia Yumuşak

    (Department of Industrial Engineering, Faculty of Engineering, Kırıkkale University, 71450 Kırıkkale, Turkey)

  • Tamer Eren

    (Department of Industrial Engineering, Faculty of Engineering, Kırıkkale University, 71450 Kırıkkale, Turkey)

Abstract

In this study, maintenance planning problem is handled in one of the hydroelectric power plants which directly affect Turkey’s energy supply security with a fifth share in the total generation. In this study, a result is obtained by taking into consideration the multi-objective and multi-criteria structure of the maintenance planning in the hydroelectric power plants with thousands of complex equipment and the direct effect of this equipment on uninterrupted and low-cost electricity generation. In the first stage, the risk levels of the equipment in terms of the power plant are obtained with the combination of AHP (Analytical Hierarchy Process) and TOPSIS (technique for order preference by similarity to ideal solution) which are frequently used in the literature due to their advantages. Department-based maintenance plans of all equipment for periodic and revision maintenance strategies are formed by integrating these values into the time allocated for maintenance and the number of employees constraints. As a result of the application of this methodology which is designed for the first time in the literature with the integration of multi-criteria decision-making methods for the maintenance planning problem in a hydroelectric power plant, all elements that prevent the sustainable energy supply in the power plant are eliminated.

Suggested Citation

  • Evrencan Özcan & Rabia Yumuşak & Tamer Eren, 2019. "Risk Based Maintenance in the Hydroelectric Power Plants," Energies, MDPI, vol. 12(8), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1502-:d:224658
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    References listed on IDEAS

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    1. Doostparast, Mohammad & Kolahan, Farhad & Doostparast, Mahdi, 2014. "A reliability-based approach to optimize preventive maintenance scheduling for coherent systems," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 98-106.
    2. Özcan, Evren Can & Ünlüsoy, Sultan & Eren, Tamer, 2017. "A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1410-1423.
    3. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    4. Dhanisetty, V.S. Viswanath & Verhagen, W.J.C. & Curran, Richard, 2018. "Multi-criteria weighted decision making for operational maintenance processes," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 152-164.
    5. Zhang, Chen & Gao, Wei & Guo, Sheng & Li, Youliang & Yang, Tao, 2017. "Opportunistic maintenance for wind turbines considering imperfect, reliability-based maintenance," Renewable Energy, Elsevier, vol. 103(C), pages 606-612.
    6. Froger, Aurélien & Gendreau, Michel & Mendoza, Jorge E. & Pinson, Éric & Rousseau, Louis-Martin, 2016. "Maintenance scheduling in the electricity industry: A literature review," European Journal of Operational Research, Elsevier, vol. 251(3), pages 695-706.
    7. Chareonsuk, Chaichan & Nagarur, Nagen & Tabucanon, Mario T., 1997. "A multicriteria approach to the selection of preventive maintenance intervals," International Journal of Production Economics, Elsevier, vol. 49(1), pages 55-64, March.
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    Cited by:

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    3. Carpitella, Silvia & Mzougui, Ilyas & Benítez, Julio & Carpitella, Fortunato & Certa, Antonella & Izquierdo, Joaquín & La Cascia, Marco, 2021. "A risk evaluation framework for the best maintenance strategy: The case of a marine salt manufacture firm," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
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    5. Philip Mayer & Christopher Stephen Ball & Stefan Vögele & Wilhelm Kuckshinrichs & Dirk Rübbelke, 2019. "Analyzing Brexit: Implications for the Electricity System of Great Britain," Energies, MDPI, vol. 12(17), pages 1-27, August.

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