Limitations and Opportunities in PHM for Offshore Wind Farms: A Socio-Technical-Ecological System Perspective
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
The burgeoning importance of offshore wind farms (OWFs) in the transition to sustainable energy systems underscores the need for effective Prognostics and Health Management (PHM) strategies. While the current PHM framework demonstrates its prowess in enhancing the reliability and operational efficiency of OWFs, this paper contends that its potential remains largely untapped due to certain inherent limitations. This study casts a comprehensive spotlight on the limitations and untapped opportunities within the PHM framework for OWFs from a Socio-Technical-Ecological Systems (SETS) perspective.
The limitations, as identified, are threefold. First, the existing framework exhibits an over-reliance on technical factors, thus prioritizing maximization of Remaining Useful Life and cost minimization. This emphasis disregards crucial Non-Technological Factors (such as community impacts, stakeholder engagement, Human and Organization Factors (HOFs)) and uncertainty arising from them, which can exert significant influences on OWF’s health and performance. Second, the PHM approach often adopts a component-centric view, with focus on dominant degradation modes, thus undermining the intricate interdependencies among diverse components and failure modes. This lack of a System Level Perspective (SLP) and Multi-Modal Degradation (MMD) hampers a comprehensive understanding of how component degradation cascades through the entire system. Third, the current framework largely ignores the ecological considerations, despite compelling evidence that the current monitoring, assessment, and maintenance activities has significant ecological consequences.
By addressing the identified limitations and leveraging the opportunities together with AI, the PHM framework for OWFs can evolve into a more comprehensive, inclusive, and resilient approach. The proposed paradigm shift resonates deeply with the contemporary drive towards sustainability, not only in terms of technical efficacy but also in terms of social acceptance and ecological compatibility.
How to Cite
##plugins.themes.bootstrap3.article.details##
Prognostics and Health Management, Offshore Wind Farm, Socio-Techincal-Ecological System
Branny, A., Møller, M. S., Korpilo, S., McPhearson, T., Gulsrud, N., Olafsson, A. S., Raymond, C. M., & Andersson, E. (2022). Smarter greener cities through a social-ecological-technological systems approach. Current Opinion in Environmental Sustainability, 55, 101168.
Breteler, D., Kaidis, C., Tinga, T., & Loendersloot, R. (2015). Physics based methodology for wind turbine failure detection, diagnostics & prognostics. In A. Rosmi (Ed.), EWEA 2015 (pp. 1-9). European Wind Energy Association.
Cao, L., Qian, Z., Zareipour, H., Wood, D., Mollasalehi, E., Tian, S., & Pei, Y. (2018, November 28). Prediction of Remaining Useful Life of Wind Turbine Bearings under Non-Stationary Operating Conditions. Energies, 11(12), 3318.
Clifton, A., Barber, S., Bray, A., Enevoldsen, P., Fields, J., Sempreviva, A. M., Williams, L., Quick, J., Purdue, M., Totaro, P., & Ding, Y. (2023). Grand challenges in the digitalisation of wind energy. Wind Energy Science, 8(6), 947–974.
Colléony, A., & Shwartz, A. (2019). Beyond Assuming Co-Benefits in Nature-Based Solutions: A Human-Centered Approach to Optimize Social and Ecological Outcomes for Advancing Sustainable Urban Planning. Sustainability, 11(18), 4924.
Durán, Y., Gómez-Valenzuela, V., & Ramírez, K. (2023). Socio-technical transitions and sustainable agriculture in Latin America and the Caribbean: a systematic review of the literature 2010–2021. Frontiers in Sustainable Food Systems, 7.
Elforjani, M., & Shanbr, S. (2018, July). Prognosis of Bearing Acoustic Emission Signals Using Supervised Machine Learning. IEEE Transactions on Industrial Electronics, 65(7), 5864–5871.
Equinor. (2022). Hywind Tampen. https://www.equinor.com/energy/hywind-tampen (accessed June. 15, 2023).
European Commission. (2020). An EU strategy to harness the potential of offshore renewable energy for a climate neutral 28.
Galparsoro, I., Menchaca, I., Garmendia, J. M., Borja, N., Maldonado, A. D., Iglesias, G., & Bald, J. (2022). Reviewing the ecological impacts of offshore wind farms. Npj Ocean Sustainability, 1(1).
Human and Organisational Factors (HOF). (2019, November 14). European Union Agency for Railways. https://www.era.europa.eu/domains/safety-management/human-and-organisational-factors-hof_enfuture. Eur. Comm., p. 3.
International Energy Agency. (2019). Offshore Wind Outlook.
Interreg IVB North Sea Region Programme 2007-2013. (2015, May 18). Interreg IVB North Sea Region Programme 2007-2013. http://archive.northsearegion.eu/ivb/home/
IRENA. (2019). Future of Wind: deployment, investment, technology, grid integration and socio-economic aspects,” A Global Energy Transformation Paper.
Jansen, M., Staffell, I., Kitzing, L., Quoilin, S., Wiggelinkhuizen, E., Bulder, B., Riepin, I., & Müsgens, F. (2020, July 27). Offshore wind competitiveness in mature markets without subsidy. Nature Energy, 5(8), 614–622.
Mai, T., Lantz, E., Mowers, M., and Wiser, R. (2017). The value of wind technology innovation: Implications for the U.S. power system, wind industry, electricity consumers, and environment. Tech. Rep. NREL/TP-6A20-70032, NREL, USA.
McMorland, J., Flannigan, C., Carroll, J., Collu, M., McMillan, D., Leithead, W., & Coraddu, A. (2022). A review of operations and maintenance modelling with considerations for novel wind turbine concepts. Renewable and Sustainable Energy Reviews, 165, 112581.
McPhearson, T., Cook, E. M., Berbés-Blázquez, M., Cheng, C., Grimm, N. B., Andersson, E., Barbosa, O., Chandler, D. G., Chang, H., Chester, M. V., Childers, D. L., Elser, S. R., Frantzeskaki, N., Grabowski, Z., Groffman, P., Hale, R. L., Iwaniec, D. M., Kabisch, N., Kennedy, C.,Troxler, T. G. (2022). A social-ecological-technological systems framework for urban ecosystem services. One Earth, 5(5), 505–518.
Norwegian Government. (2022). Ambitious offshore wind initiative.https://www.regjeringen.no/en/aktuelt/ambitious-offshore-wind-power-initiative/id2912297/ (accessed June. 15, 2023).
Norwegian Government. (2022). Regjeringen går videre i sin satsing på havvind. https://www.regjeringen.no/no/aktuelt/regjeringen-gar-videre-i-sin-satsing-pa-havvind/id2949762/(accessed June. 15, 2023).
Partelow, S. (2018). A review of the social-ecological systems framework: applications, methods, modifications, and challenges. Ecology and Society, 23(4).
Rinaldi, G., Thies, P. R., & Johanning, L. (2021). Current Status and Future Trends in the Operation and Maintenance of Offshore Wind Turbines: A Review. Energies, 14(9), 2484.
Rotmans, J., Kemp, R., & van Asselt, M. (2001). More evolution than revolution: transition management in public policy. Foresight, 3(1), 15–31.
Sarker, B. R., & Faiz, T. I. (2016). Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy. Renewable Energy, 85, 104–113.
Sheng, S. (2017). Prognostics and Health Management of Wind Turbines—Current Status and Future Opportunities. Probabilistic Prognostics and Health Management of Energy Systems, 33–47.
Soukissian, T., Reizopoulou, S., Drakopoulou, P., Axaopoulos, P., Karathanasi, F., Fraschetti, S., Bray, L., Foglini, F., Papadopoulos, A., De Leo, F., Kyriakidou, C., Voukouvalas, E., Papathanassiou, E., & Boero, F. (2016). Greening offshore wind with the Smart Wind Chart evaluation tool. Web Ecology, 16(1), 73–80.
United Nations. (2016). Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators.
Wang, P., Long, Z., & Wang, G. (2020). A hybrid prognostics approach for estimating remaining useful life of wind turbine bearings. Energy Reports, 6.
Zhang, W., Vatn, J., & Rasheed, A. (2022). A review of failure prognostics for predictive maintenance of offshore wind turbines. Journal of Physics: Conference Series, 2362(1), 012043.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.