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

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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.