Optimization models for the installation planning of offshore wind farms

Challenges posed by global warming motivate the increasing interest in green energy sources, such as wind energy. To make wind energy attractive from an economic viewpoint, the decision-making problems faced in designing, installing, and maintaining wind farms have to be optimized. In this paper, we focus on the problem of optimally planning the installation process of offshore wind farms, as faced by Vattenfall, a leading European energy company. We first formulate the deterministic version of this Installation Planning of Offshore Wind Farms (IPOWF) problem as a Mixed Integer Linear Programming (MILP) model. From this model, we then derive other MILPs that can provide lower and upper bounds to the optimal installation cost. To cope with weather uncertainty, we also provide a light-robust MILP. These models are tested on real-life instances corresponding to two wind farms that Vattenfall has recently built in Denmark and Germany. Computational results show that tight primal and dual solutions can be computed for the deterministic case with the proposed models and that the light-robust model yields solutions that are robust to weather uncertainty.