IDEAS home Printed from https://ideas.repec.org/a/vrs/foeste/v23y2023i1p228-245n14.html
   My bibliography  Save this article

Reliability of Renewable Power Generation using the Example of Offshore Wind Farms

Author

Listed:
  • Soszyńska-Budny Joanna

    (Sopot University of Applied Sciences, Poland)

  • Chmielewski Mariusz

    (University of Gdansk, Faculty of Management, Poland)

  • Pioch Joanna

    (Sopot University of Applied Sciences, Poland)

Abstract

Research background The issue of reliability and the cost of failure or maintenance costs of renewable energy sources, including wind farms, is becoming increasingly important, especially as the volume of electricity supply from such installations increases. Purpose The purpose of the paper is to evaluate the development of wind energy in European countries between 2010 and 2020. Evaluating the reliability of wind farm components and ensuring that wind farm infrastructure is available at a high level is crucial to the stability of the electricity supply system. Therefore, the paper presents, as a case study, a reliability estimation of one of the wind farms operating in the North Sea. The analysis is carried out on the basis of empirical data obtained from experts involved in the maintenance of this wind farm. The estimated reliability function is an important reliability indicator for users of this system. On the basis of the evaluated reliability function, for example, the system availability can be improved, and the maintenance costs of the system can be optimised. Research methodology Mathematical modelling was used to analyse system reliability. Further, in the developed reliability models, it was assumed that the system components have the multistate Weibull reliability functions with various parameters in their different reliability state subsets. Novelty Original study with literature review. In the context of the requirements for the transformation of the Polish energy sector, the presented approach can be used in the practical implementation of RES projects, taking into account the reliability of offshore wind farm installations.

Suggested Citation

  • Soszyńska-Budny Joanna & Chmielewski Mariusz & Pioch Joanna, 2023. "Reliability of Renewable Power Generation using the Example of Offshore Wind Farms," Folia Oeconomica Stetinensia, Sciendo, vol. 23(1), pages 228-245, June.
  • Handle: RePEc:vrs:foeste:v:23:y:2023:i:1:p:228-245:n:14
    DOI: 10.2478/foli-2023-0012
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/foli-2023-0012
    Download Restriction: no

    File URL: https://libkey.io/10.2478/foli-2023-0012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
    2. Martin, Rebecca & Lazakis, Iraklis & Barbouchi, Sami & Johanning, Lars, 2016. "Sensitivity analysis of offshore wind farm operation and maintenance cost and availability," Renewable Energy, Elsevier, vol. 85(C), pages 1226-1236.
    3. Scheu, Matti Niclas & Kolios, Athanasios & Fischer, Tim & Brennan, Feargal, 2017. "Influence of statistical uncertainty of component reliability estimations on offshore wind farm availability," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 28-39.
    4. Sebastian Pfaffel & Stefan Faulstich & Kurt Rohrig, 2017. "Performance and Reliability of Wind Turbines: A Review," Energies, MDPI, vol. 10(11), pages 1-27, November.
    5. Pinar Pérez, Jesús María & García Márquez, Fausto Pedro & Tobias, Andrew & Papaelias, Mayorkinos, 2013. "Wind turbine reliability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 463-472.
    6. Jia, Xiaodong & Jin, Chao & Buzza, Matt & Wang, Wei & Lee, Jay, 2016. "Wind turbine performance degradation assessment based on a novel similarity metric for machine performance curves," Renewable Energy, Elsevier, vol. 99(C), pages 1191-1201.
    7. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cevasco, D. & Koukoura, S. & Kolios, A.J., 2021. "Reliability, availability, maintainability data review for the identification of trends in offshore wind energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    2. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    3. Koukoura, Sofia & Scheu, Matti Niclas & Kolios, Athanasios, 2021. "Influence of extended potential-to-functional failure intervals through condition monitoring systems on offshore wind turbine availability," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    4. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
    5. Wang, Anqi & Pei, Yan & Qian, Zheng & Zareipour, Hamidreza & Jing, Bo & An, Jiayi, 2022. "A two-stage anomaly decomposition scheme based on multi-variable correlation extraction for wind turbine fault detection and identification," Applied Energy, Elsevier, vol. 321(C).
    6. 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).
    7. Lin, Zi & Cevasco, Debora & Collu, Maurizio, 2020. "A methodology to develop reduced-order models to support the operation and maintenance of offshore wind turbines," Applied Energy, Elsevier, vol. 259(C).
    8. Jing, Bo & Qian, Zheng & Pei, Yan & Zhang, Lizhong & Yang, Tingyi, 2020. "Improving wind turbine efficiency through detection and calibration of yaw misalignment," Renewable Energy, Elsevier, vol. 160(C), pages 1217-1227.
    9. Davide Astolfi & Raymond Byrne & Francesco Castellani, 2020. "Analysis of Wind Turbine Aging through Operation Curves," Energies, MDPI, vol. 13(21), pages 1-21, October.
    10. Ioannou, Anastasia & Angus, Andrew & Brennan, Feargal, 2018. "A lifecycle techno-economic model of offshore wind energy for different entry and exit instances," Applied Energy, Elsevier, vol. 221(C), pages 406-424.
    11. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
    12. Li, He & Diaz, H. & Guedes Soares, C., 2021. "A developed failure mode and effect analysis for floating offshore wind turbine support structures," Renewable Energy, Elsevier, vol. 164(C), pages 133-145.
    13. Wang, Feng & Chen, Jincheng & Xu, Bing & Stelson, Kim A., 2019. "Improving the reliability and energy production of large wind turbine with a digital hydrostatic drivetrain," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    14. Siddiqui, Muhammad Omer & Feja, Paul Robert & Borowski, Philipp & Kyling, Hans & Nejad, Amir R. & Wenske, Jan, 2023. "Wind turbine nacelle testing: State-of-the-art and development trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    15. Hans Olav Vogt Myklebust & Jo Eidsvik & Iver Bakken Sperstad & Debarun Bhattacharjya, 2020. "Value of Information Analysis for Complex Simulator Models: Application to Wind Farm Maintenance," Decision Analysis, INFORMS, vol. 17(2), pages 134-153, June.
    16. Kevin Leahy & Colm Gallagher & Peter O’Donovan & Dominic T. J. O’Sullivan, 2019. "Issues with Data Quality for Wind Turbine Condition Monitoring and Reliability Analyses," Energies, MDPI, vol. 12(2), pages 1-22, January.
    17. 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).
    18. Sebastian Pfaffel & Stefan Faulstich & Kurt Rohrig, 2017. "Performance and Reliability of Wind Turbines: A Review," Energies, MDPI, vol. 10(11), pages 1-27, November.
    19. uit het Broek, Michiel A.J. & Veldman, Jasper & Fazi, Stefano & Greijdanus, Roy, 2019. "Evaluating resource sharing for offshore wind farm maintenance: The case of jack-up vessels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 619-632.
    20. Eryilmaz, Serkan & Bulanık, İrem & Devrim, Yilser, 2021. "Reliability based modeling of hybrid solar/wind power system for long term performance assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).

    More about this item

    Keywords

    Reliability; failure costs; maintenance costs; renewable power; RES; offshore wind farm efficiency;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • B16 - Schools of Economic Thought and Methodology - - History of Economic Thought through 1925 - - - Quantitative and Mathematical
    • B49 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Other
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:foeste:v:23:y:2023:i:1:p:228-245:n:14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.