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

随着英国和欧洲开展的众多测试/试点项目的启动，漂浮式海上风电已经成为人们关注的焦点。为了实现脱碳目标，浮动海上风电需要达到其全部容量，潜在的地点相当丰富。对于像EDF这样的公司来说，在确保对浮子和涡轮机等主要部件进行技术尽职调查的同时，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，这存在巨大的不确定性。浮式海上风电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，以及减少一线诊断/维修的人为干预的主要技术，将在确定合适的运维策略方面发挥重要作用。该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。电子和电气工程系（McMillan, Carroll）将提供先进的OPEX建模[2]和可靠性评估能力，以表征浮动风系统。船舶建筑、海洋和海洋工程系（Collu）将为[3]项目带来具体的浮动风和先进的流体动力学知识，这对于评估拟议的“拖上岸”运维案例的现实性至关重要。博士项目的具体目标：-评估油气行业在浮式支持方面的专业知识如何降低浮式海上风电站点的维护风险。-使用Strathclyde EEE和NAOME模型，建模和量化可以实现多少自动化来降低运营成本，并与行业密切合作，以确保有关自动化系统能力的任何假设都是现实的。-分析和评估在这种情况下将用于执行运维的船舶类型。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。-探索状态监测在浮动风的特定背景下的作用和潜在影响，并了解在海上风的背景下，剩余使用寿命（RUL）[1]的使用会发生什么变化（如果有的话）Hannon， Matthew和Topham， Eva和Dixon， James和McMillan， David和Collu， Maurizio（2019）海上风能，准备好漂浮吗？浮动式海上风电市场的全球和英国趋势。[报告]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）不同驱动系统配置的海上风力涡轮机的可用性、运行和维护成本。风能，20 (2). pp. 361-378。ISSN 1095-4244 https://doi.org/10.1002/we.2011[3] M Borg, A Shires, M Collu（2014）海上浮动垂直轴风力涡轮机，动态建模的艺术状态。James Carroll, Sofia Koukoura, Alasdair McDonald, Anastasis Charalambous, Stephan Weiss, Stephen McArthur（2018）基于机器学习技术的风力发电机齿轮箱故障和剩余使用寿命预测。风能（Wiley） 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