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Wind turbine operations and maintenance: a tractable approximation of dynamic decision making

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  • Eunshin Byon

Abstract

Timely decision making for least-cost maintenance of wind turbines is a critical factor in reducing the total cost of wind energy. The current models for the wind industry as well as other industries often involve solving computationally expensive algorithms such as dynamic programming. This article presents a tractable approximation of the dynamic decision-making process to alleviate the computational burden. Based upon an examination of decision rules in stationary weather conditions, a new set of decision rules is developed to incorporate dynamic weather changes. Since the decisions are made with a set of If–Then rules, the proposed approach is computationally efficient and easily integrated into the simulation framework. It can also benefit actual wind farm operations by providing implementable control. Numerical studies using field data mainly from the literature demonstrate that the proposed method provides practical guidelines for reducing operational costs as well as enhancing the marketability of wind energy. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for detailed proofs.]

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  • Eunshin Byon, 2013. "Wind turbine operations and maintenance: a tractable approximation of dynamic decision making," IISE Transactions, Taylor & Francis Journals, vol. 45(11), pages 1188-1201.
    • Handle: RePEc:taf:uiiexx:v:45:y:2013:i:11:p:1188-1201
    DOI: 10.1080/0740817X.2012.726819
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    Cited by:

    1. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.
    2. Abdollahzadeh, Hadi & Atashgar, Karim & Abbasi, Morteza, 2016. "Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups," Renewable Energy, Elsevier, vol. 88(C), pages 247-261.
    3. Zhu, Wenjin & Castanier, Bruno & Bettayeb, Belgacem, 2019. "A dynamic programming-based maintenance model of offshore wind turbine considering logistic delay and weather condition," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    4. Juan Izquierdo & Adolfo Crespo Márquez & Jone Uribetxebarria & Asier Erguido, 2019. "Framework for Managing Maintenance of Wind Farms Based on a Clustering Approach and Dynamic Opportunistic Maintenance," Energies, MDPI, vol. 12(11), pages 1-17, May.
    5. Erguido, A. & Crespo Márquez, A. & Castellano, E. & Gómez Fernández, J.F., 2017. "A dynamic opportunistic maintenance model to maximize energy-based availability while reducing the life cycle cost of wind farms," Renewable Energy, Elsevier, vol. 114(PB), pages 843-856.
    6. Shafiee, Mahmood & Sørensen, John Dalsgaard, 2019. "Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    7. Nguyen, Thi Anh Tuyet & Chou, Shuo-Yan, 2019. "Improved maintenance optimization of offshore wind systems considering effects of government subsidies, lost production and discounted cost model," Energy, Elsevier, vol. 187(C).
    8. Wang, Jinhe & Zhang, Xiaohong & Zeng, Jianchao & Zhang, Yunzheng, 2020. "Joint external and internal opportunistic optimisation for wind turbine considering wind velocity," Renewable Energy, Elsevier, vol. 159(C), pages 380-398.
    9. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    10. Moghaddass, Ramin & Sheng, Shuangwen, 2019. "An anomaly detection framework for dynamic systems using a Bayesian hierarchical framework," Applied Energy, Elsevier, vol. 240(C), pages 561-582.
    11. Nguyen, Thi-Anh-Tuyet & Chou, Shuo-Yan & Yu, Tiffany Hui-Kuang, 2022. "Developing an exhaustive optimal maintenance schedule for offshore wind turbines based on risk-assessment, technical factors and cost-effective evaluation," Energy, Elsevier, vol. 249(C).

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