FLoating Offshore wind REpair & Novel Concept cost Estimates (FLORENCE)

问题陈述漂浮海上风能现已在英国和欧洲推出了许多试验/试点项目[1]。为了确保脱碳目标，海上漂浮风能需要达到最大产能，而且潜在地点相当丰富。对于像EDF这样的公司来说，在确保浮子和涡轮机等主要部件的技术尽职调查的同时，对于应该使用哪种运维策略和技术来最大限度地降低运营成本，存在巨大的不确定性。漂浮的海上风能提供了在现场进行维护或将整个设备拖到港口的可能性-围绕天气风险的不确定性，围绕哪些维护活动优先进行的决策，以及减少人为干预的主要技术将在确定合适的运维战略方面发挥重要作用。这个博士项目将利用斯特拉斯克莱德大学两个部门的专业知识。电子和电气工程部(McMillan，Carroll)将提供先进的OPEX模型[2]和可靠性评估能力，以表征浮风系统。海军建筑、海洋和海洋工程系(COLU)将为该项目带来特定的浮风和先进的水动力知识[3]，这将是评估拟议的“拖到岸边”运维案例的现实性的关键。博士项目的具体目标：-评估O&G行业在漂浮支持方面的专业知识如何降低海上漂浮风场的维护风险。-使用Strathclyde EEE和Naome模型模拟和量化可以在多大程度上实施自动化以降低运营成本，并与工业界密切合作，确保对此类系统自动化能力的任何假设都是现实的。-分析和评估在此情况下将用于进行操作和维护的船舶类型。与船舶供应商密切合作，了解能力和限制，并将其嵌入技术和经济模型中。-探索状态监测在特定的浮风环境中的作用和潜在影响，并了解在海上风能环境中剩余使用寿命(RUL)[4]会发生什么变化(如果有的话)。[1]Hannon，Matthew和Topham，Eva和Dixon，James和McMillan，David and Collu，Maurizio(2019)离岸风能，准备好漂浮了吗？漂浮离岸风能市场的全球和英国趋势。[报告]https://doi.org/10.17868/69501[2]Carroll，詹姆斯和麦克唐纳，阿拉斯代尔和丁伍迪，伊恩和麦克米兰，大卫和里维，马修和拉扎基斯，伊拉克利斯(2017年)不同传动系配置的海上风力涡轮机的可用性、运营和维护成本。风能，20(2)。第361-378页。ISSN1095-4244 https://doi.org/10.1002/we.2011[3]M Borg，A Shires，M Collu(2014)离岸浮动垂直轴风力涡轮机，动力学建模技术的现状。可再生能源和可持续能源评论第39、1214年至1225年https://doi.org/10.1016/j.rser.2014.07.096[4]詹姆斯·卡罗尔、索菲亚·库库拉、阿拉斯代尔·麦克唐纳、阿纳斯塔西·查拉兰博斯、斯蒂芬·韦斯、斯蒂芬·麦克阿瑟(2018年)使用机器学习技术预测风力涡轮机变速箱故障和剩余使用寿命。风能(威利)https://doi.org/10.1002/we.2290

Problem StatementFloating offshore wind has now come to prominence with the launch of numerous test/pilot projects in the UK and Europe [1]. In order to secure the decarbonisation targets, floating offshore wind needs to reach its full capacity and the potential sites are quite abundant. For companies such as EDF, while ensuring the technical due diligence on the major components like the floater and turbine, there is a huge uncertainty as to which O&M strategy and technologies should be used to minimise OPEX costs.Floating offshore wind offers the possibility to perform maintenance in-situ or to tow the whole device to a port - the uncertainties around weather risk, decision making around which maintenance activities to prioritise and also the main technologies to reduce human enable intervention for first line diagnostics/repair will play a major part in defining a suitable O&M strategy.This PhD project will leverage expertise from two Univeristy of Strathclyde departments. Electronics and Electrical Engineering dept (McMillan, Carroll) will provide the advanced OPEX modelling [2] and reliability assessment capability to characterise the floating wind system. Dept of Naval Architecture, Ocean and Marine Engineering (Collu) will bring specific floating wind and advanced hydrodynamic knowledge to the project [3], which will be crucial in assessing the realism of proposed 'tow to shore' O&M cases.Specific objectives of the PhD project:- Assess how expertise of the O&G industry in floating support can de-risk maintenance for floating offshore wind sites.- Model and quantify, using Strathclyde EEE and NAOME models, how much automation can be implemented to reduce OPEX costs, and work closely with industry to ensure any assumptions made regarding the capability of automating such systems are realistic.- Analyse and evaluate the type of vessels which would be used to perform O&M in this context. Work closely with the vessel supply to understand capabilities and limitations and embed these within the technical and economic models.- Explore the role and potential impact of condition monitoring in the specific context of floating wind and understand what (if anything) would change about the use of Remaining useful life (RUL) [4] in the context of offshore wind.[1] Hannon, Matthew and Topham, Eva and Dixon, James and McMillan, David and Collu, Maurizio (2019) Offshore Wind, Ready to Float? Global and UK Trends in the Floating Offshore Wind Market. [Report] https://doi.org/10.17868/69501[2] Carroll, James and McDonald, Alasdair and Dinwoodie, Iain and McMillan, David and Revie, Matthew and Lazakis, Iraklis (2017) Availability, operation and maintenance costs of offshore wind turbines with different drive train configurations. Wind Energy, 20 (2). pp. 361-378. ISSN 1095-4244 https://doi.org/10.1002/we.2011[3] M Borg, A Shires, M Collu (2014) Offshore floating vertical axis wind turbines, dynamics modelling state of the art. Renewable and Sustainable Energy Reviews 39, 1214-1225 https://doi.org/10.1016/j.rser.2014.07.096[4] James Carroll, Sofia Koukoura, Alasdair McDonald, Anastasis Charalambous, Stephan Weiss, Stephen McArthur (2018) Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques. Wind Energy (Wiley) https://doi.org/10.1002/we.2290