Abstract
Maintenance operations at offshore wind farms are challenging due to the offshore element; maintenance technicians and spare parts need to be transported from an onshore port or offshore station to the individual wind farm components in need of maintenance. The vessel resources needed to support these maintenance tasks constitute a major part of the total maintenance costs, and hence up-keeping an optimal vessel fleet and corresponding deployment is essential to reduce cost-of-energy. This paper introduces a metaheuristic solution method to determine cost-efficient vessel fleets to support maintenance tasks at offshore wind farms under uncertainty. It considers weather conditions and failures leading to corrective maintenance tasks as stochastic parameters, and evaluates candidate solutions by a simulation program. The solution method has been incorporated in a decision support tool. Computational experiments, including comparison of results with an exact solution method, illustrate that the decision support tool can be used to provide near-optimal solutions within acceptable computational time.
