Optimisation of vessel routing for offshore wind farm maintenance tasks

Kingsman, Toby and Boyacı, Burak (2019) Optimisation of vessel routing for offshore wind farm maintenance tasks. In: Wind Energy Science Conference 2019, 2019-06-17 - 2019-06-20, University College Cork.

Abstract

The rapid growth expected in the offshore wind sector means there is an increasing opportunity to find savings from conducting operations and maintenance activities more efficiently. The predicted increase in the size and quantity of offshore wind farms will require industry to have access to mathematical tools for scheduling maintenance activities in order to exploit potential savings fully. In order to complete a maintenance activity, a pre-specified combination of skilled personnel, equipment and vessel support is required for a specific duration at the location of the task. A heterogeneous fleet of vessels is typically responsible for transporting physical assets around the wind farm and conducting personnel transfers. Vessel movements must also satisfy any limitations in wind turbine accessibility, in conjunction with safety constraints imposed by offshore weather conditions. In this research, we have created a mathematical model of the problem that is capable of determining the best routes for vessel movements and the ideal times to undertake crew transfers. Our approach can compute high quality schedules that minimise the costs of performing both corrective and preventive maintenance tasks, whilst accounting for lost production. We illustrate our results on a test wind farm. Our solutions demonstrate the possible benefits from splitting pick-up and drop-off operations across different vessels and only performing a subset of tasks within a task intensive environment. It is possible to extend our model to incorporate a set of scenarios that represent the stochastic evolution of weather and sea conditions in future shifts. Solving the resulting model with a rolling horizon approach allows us to produce a detailed solution for the current shift, which contains actions informed by the relative likelihoods of future weather patterns.