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Resilience Informed Integrity Management of Wind Turbine Parks

Author

Listed:
  • Jianjun Qin

    (Department of Civil Engineering, Aalborg University, 9220 Aalborg, Denmark)

  • Michael Havbro Faber

    (Department of Civil Engineering, Aalborg University, 9220 Aalborg, Denmark)

Abstract

A novel framework for resilience modeling of wind turbine parks is proposed in support of optimization of decisions on asset integrity management. The concept of resilience originating from natural and social sciences is adapted here to facilitate the joint optimization of decision alternatives related to design, with decision alternatives addressing organizational performance. The generic probabilistic systems representation framework by the Joint Committee on Structural Safety (JCSS) (2008) is utilized to establish a scenario-based modeling of how different types of disturbances may lead to damages and failures of systems and sub-systems of wind turbine parks, together with associated direct and indirect consequences. Special emphasis is directed on the consistent probabilistic representation of the uncertainties and the stochastic and causal dependencies within the wind turbine park system. The framework facilitates the identification of optimal asset integrity management decision alternatives that fulfill given requirements to resilience. The potentials associated with the use of the framework are highlighted by an example considering a wind turbine park with ten identical wind turbines, with each modelled as a system of mechanical, electrical, and structural sub-systems. The resilience performance characteristics of the wind turbine park, such as the expected value of generated service life benefits, the expected value of production down time, and the probability of resilience failure are modelled and quantified such as to support the ranking of decision alternatives relating to the design of the wind turbine sub-systems, the level of organizational preparedness, the percentage of the generated service life benefits to be kept to ensure sufficient economic capacity to deal with future disturbances, and the stock-keeping of essential spare parts.

Suggested Citation

  • Jianjun Qin & Michael Havbro Faber, 2019. "Resilience Informed Integrity Management of Wind Turbine Parks," Energies, MDPI, vol. 12(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2729-:d:249043
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    References listed on IDEAS

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    1. Pere Marti-Puig & Alejandro Blanco-M & Juan José Cárdenas & Jordi Cusidó & Jordi Solé-Casals, 2019. "Feature Selection Algorithms for Wind Turbine Failure Prediction," Energies, MDPI, vol. 12(3), pages 1-18, January.
    2. Mahmood Shafiee & Fateme Dinmohammadi, 2014. "An FMEA-Based Risk Assessment Approach for Wind Turbine Systems: A Comparative Study of Onshore and Offshore," Energies, MDPI, vol. 7(2), pages 1-24, February.
    3. Igor Linkov & Todd Bridges & Felix Creutzig & Jennifer Decker & Cate Fox-Lent & Wolfgang Kröger & James H. Lambert & Anders Levermann & Benoit Montreuil & Jatin Nathwani & Raymond Nyer & Ortwin Renn &, 2014. "Changing the resilience paradigm," Nature Climate Change, Nature, vol. 4(6), pages 407-409, June.
    4. John D. Sørensen & Henrik S. Toft, 2010. "Probabilistic Design of Wind Turbines," Energies, MDPI, vol. 3(2), pages 1-17, February.
    5. Kusiak, Andrew & Song, Zhe, 2010. "Design of wind farm layout for maximum wind energy capture," Renewable Energy, Elsevier, vol. 35(3), pages 685-694.
    6. Cutter Susan L. & Burton Christopher G. & Emrich Christopher T., 2010. "Disaster Resilience Indicators for Benchmarking Baseline Conditions," Journal of Homeland Security and Emergency Management, De Gruyter, vol. 7(1), pages 1-24, August.
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    Cited by:

    1. Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
    2. Liu, Min & Qin, Jianjun & Lu, Da-Gang & Zhang, Wei-Heng & Zhu, Jiang-Sheng & Faber, Michael Havbro, 2022. "Towards resilience of offshore wind farms: A framework and application to asset integrity management," Applied Energy, Elsevier, vol. 322(C).
    3. Rasool, Safdar & Muttaqi, Kashem M. & Sutanto, Danny & Hemer, Mark, 2022. "Quantifying the reduction in power variability of co-located offshore wind-wave farms," Renewable Energy, Elsevier, vol. 185(C), pages 1018-1033.
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    6. Pan, Yue & Qin, Jianjun, 2022. "A novel probabilistic modeling framework for wind speed with highlight of extremes under data discrepancy and uncertainty," Applied Energy, Elsevier, vol. 326(C).

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