Optimizing operations and maintenance strategies in offshore wind farms: translating real-world operations into state-of-the-art simulations

This paper presents an application of a new method to recreate the factual logistical demand for operations and maintenance (O&M) in an offshore wind farm (OWF) based on turbine SCADA data, daily progress reports (DPRs) from vessels and helicopters, and vessel tracking data. This O&M demand is translated into a high-resolution simulation of offshore logistics and OWF operations. With this interface, O&M scenarios can be evaluated retrospectively, in order to investigate various aspects of O&M strategies. SCADA data and DPRs from several OWFs in the German North Sea were used to develop this method. With the combination of these two datasets, a failure catalog can be created as a tool to describe the historical demand for repairs. This failure catalog contains entries for each SCADA failure message, including information if vessels and technicians were deployed to resolve the failure and how the failure affected the turbine’s power generation. Based on this dataset, a collection of conducted O&M tasks is created, which specifies the amount of work time and the involved vessel types that are related to each individual entry in the failure catalog. This information is then fed into the O&M simulation software OffshoreTIMES. Usually driven by a stochastic model of technical reliabilities, the time-discrete simulation of offshore logistics and OWF operations in OffshoreTIMES is now provided with real-world O&M situations as input. An exemplary application of the method showcases the added benefit of fast gangway operations during the summer inspection campaign, and a real case of helicopter-based crew logistics is evaluated. Vessel-sharing strategies between neighbouring OWFs are investigated as well, and the simulation shows how a single SOV can be sufficient for corrective maintenance tasks in both OWFs.