Offshore Wind Farms (OWFs) have rising importance for energy provision of many regions worldwide. However, their harsh environment leads to considerably higher failure rates and degradation compared to its onshore counterparts. Consequently, OWFs require well-established maintenance processes in order to provide required operational availability of all wind turbines. Amongst the several factors impacting these processes the personnel plays an important role, bearing in mind that no maintenance is possible without having access to technicians or seamen operating the required vessel. This work proposes a comprehensive model for evaluating the actual impact the personnel availability has on the corrective maintenance processes of an OWF and, consequently, its energy production. Therefore, maintenance processes and WT failure rates based on reported data are considered. Furthermore, a pandemic model is employed in order to elaborate the possible impact a health crisis can have on the operational availability of an OWF. Results indicate that the monthly energy production can drop by up to 74% in case of a constant reduction of the personnel by 50%, while a worst case pandemic scenario results in a 23% lower energy production over the whole year.

This article discusses the aspect of modeling weather conditions in marine environment for implementation in the offshore wind farm domain. It is clear that harsh sea weather conditions influence many characteristics of any offshore installation. The accessibility to the infrastructure, maintenance procedures, failure ratios of components, energy provision levels, or utilization of vessels—are the examples of weather-related issues connected to the offshore wind industry. Regarding the growing popularity of digital twin methodology, authors present a novel view to generate weather data with copula-based method. The results obtained are compared to selected historical data and implemented into the maintenance model. The selected indicators of maintenance service are used for usability assessment of proposed copula-based method.

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