Methodologies and simulation tools to support Operations and Maintenance (O&M) strategies and lifetime reliability assessment of Offshore Renewable En

在过去的几十年里，随着水深的增加(预计高达1,000米)，全球海上风能技术迅速发展，从浅水(60米以下)的固定底部支撑结构发展到浮动的子结构。涡轮机的设计已经从1991年0.45兆瓦的小功率发展到今天的巨型西门子Gamesa-14兆瓦涡轮机，将于2024年上市。海上可再生能源技术的这些进步将继续降低成本，同时也有助于满足日益增长的能源需求。2019年6月，根据《巴黎协定》，英国《2008年气候变化法》制定了到2050年实现净零碳排放目标的路线图。截至2019年底，英国海上风电发电量达到32TWh，占英国混合能源发电量的10%。此外，英国拥有约40个海上风电场和2200多台涡轮机，总装机容量为9.7千兆瓦(GW)，4.4千兆瓦正在建设中或最终投资决定已确定[1]，是海上风电行业的世界领先者。在全球范围内，固定底部技术的装机容量超过27GW，浮式海上风力发电机组的装机容量超过82兆瓦。海上可再生能源技术将在世界未来的能源转型中发挥关键作用。未来十年，欧洲、亚太地区和美国的海上风电项目都有发展规划和市场机会。然而，海上风能的部署仍然面临着巨大的挑战，如安装物流、大部件更换战略以及运营和维护(O&M)成本，所有这些都对能源成本(LCOE)产生了重大影响。例如，海上固定海底和浮风技术的运营和维护总成本分别占总成本的34%和31.3%[2]。此外，海上风电场的运营支出(OpEx)在其整个生命周期内是可变的。技术和地理因素影响运营成本，例如从风电场到陆上设施的距离、海洋条件以及关键部件的意外故障等。因此，提高开发项目和现有资产运营成本估算的准确性和减少不确定性是人们高度关注的问题。例如，学术界、研究机构、产业界和政府实体合作开发先进的技术解决方案和工具，以推动运营和维护成本的降低，并提高ORE系统的可靠性和效率。罗密欧[3]和DTOcean Plus[4]项目就是这种情况。事实上，有几个分析模型和工具可以计算安装和运营成本，以及估计设计寿命内矿石项目的年度可用性[5][6]。然而，需要进一步的研究来改进这些运行与维护模型，以从基本预防转变为基于条件的维护(CBM)，如下所述。

Over the last few decades, global offshore wind technology has rapidly evolved from fixed-bottomsupport structures in shallow waters (below 60 meters) to floating substructures, as water depthincreases (expected up to 1,000 meters). Turbine designs have grown from small power capacity of0.45 megawatts (MW) in 1991, up to today's giant Siemens Gamesa-14MW turbine that will becommercially available in 2024. These advances in offshore renewable technology will continue todecrease its costs, while also contributing to meeting the growing demand of energy.In June 2019, in line with the Paris Agreement, the UK's Climate Change Act 2008 set out the roadmapto net-zero carbon emissions target by 2050. At the end of 2019, the UK's offshore wind electricityproduction reached 32TWh, which accounted for 10% of its total mix energy production. Furthermore,with around 40 offshore wind farms and over 2,200 turbines operating for a total installed capacity of9.7 gigawatts (GW), and 4.4GW under construction or with a final investment decision confirmed [1],the UK is the world leader in the offshore wind sector. Globally, there are over 27GW installed in thefixed-bottom technology and 82MW with floating offshore wind turbines.Offshore renewable technologies will play a key role in the world's future energy transition. In the nextten years, there are development plans and market opportunities for offshore wind projects in Europe,Asia-Pacific and the US. However, offshore wind energy deployment is still facing big challenges, suchas installation logistics, large component replacement strategy, and operations and maintenance (O&M)costs, all of them having a significant impact on the levelised cost of energy (LCoE). For instance,overall O&M costs make up 34% and 31.3% of the total LCoE for offshore fixed-bottom and floatingwind technologies, respectively [2]. Moreover, the operational expenditure (OpEx) of an offshore windfarm is variable throughout its lifetime. Technical and geographical factors affect the OpEx, such as thedistance from the wind farm to the onshore facilities, the metocean conditions, and the unexpectedfailures of critical components, among others.Therefore, there is a high interest in increasing accuracy and reducing uncertainty in OpEx estimatesfor both development projects and existing assets. For instance, there are collaborative works betweenacademia, research institutions, industry, and governmental entities to develop advanced technologicalsolutions and tools to drive the reduction of O&M costs and to improve the reliability and efficiency ofORE systems. Such is the case of ROMEO [3] and DTOcean Plus [4] projects.In fact, there are several analytic models and tools to calculate the installation and O&M costs as wellas to estimate the annual availability of ORE projects over the designed lifetime [5][6]. However, furtherresearch is required to improve those O&M models to move from basic preventive to condition-basedmaintenance (CBM), as discussed below.