Limitations and Opportunities in PHM for Offshore Wind Farms: A Socio-Technical-Ecological System Perspective

Arvind Keprate
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 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.","PeriodicalId":91951,"journal":{"name":"Proceedings of the Annual Conference of the Prognostics and Health Management Society. Prognostics and Health Management Society. Conference","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Annual Conference of the Prognostics and Health Management Society. Prognostics and Health Management Society. Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36001/phmconf.2023.v15i1.3697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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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.
海上风电场PHM的限制和机遇:社会-技术-生态系统视角
海上风电场(owf)在向可持续能源系统转型中的重要性日益凸显,需要有效的预测和健康管理(PHM)策略。虽然目前的PHM框架在提高owf的可靠性和运行效率方面表现出了强大的实力,但本文认为,由于某些固有的局限性,它的潜力在很大程度上仍未得到开发。本研究从社会-技术-生态系统(set)的角度全面关注了owf PHM框架内的局限性和未开发的机会。所确定的限制有三个方面。首先,现有框架表现出对技术因素的过度依赖,从而优先考虑剩余使用寿命的最大化和成本的最小化。这种强调忽视了关键的非技术因素(如社区影响、利益相关者参与、人与组织因素(hof))以及由此产生的不确定性,这些因素会对OWF的健康和绩效产生重大影响。其次,PHM方法通常采用以组件为中心的观点,关注主要的退化模式,从而破坏了不同组件和失效模式之间复杂的相互依赖关系。缺乏系统级视角(SLP)和多模态退化(MMD)阻碍了对组件退化如何在整个系统中级联的全面理解。第三,目前的框架在很大程度上忽略了生态方面的考虑,尽管有令人信服的证据表明,目前的监测、评估和维护活动具有显著的生态后果。 通过解决已确定的限制并利用与人工智能一起的机会,owf的PHM框架可以演变成更全面、更包容、更有弹性的方法。所提出的模式转变与当代对可持续发展的追求产生了深刻的共鸣,不仅在技术效率方面,而且在社会接受度和生态兼容性方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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