Online Decision Support for Offshore Wind Farm Installations

While existing models support strategic and tactical planning, there is a lack of effective decision support at the operational level. To close this gap, this book presents an innovative online scheduling methodology based on a Model Predictive Control scheme. Offshore wind farms are major contributors to sustainable energy generation. However, their installation is highly weather-dependent, making the planning of costly resources, like jack-up vessels or port spaces, challenging. While existing models support strategic and tactical planning, there is a lack of effective decision support at the operational level. To close this gap, this book presents an innovative online scheduling methodology based on a Model Predictive Control scheme. This approach combines Mixed-Integer scheduling models with control theory and a novel probabilistic method for integrating forecast uncertainty into operational planning. The resulting decision support system doesn't only enable reactive and weather-informed operational planning but also supports tactical and strategic decisions based on historical data. Simulation studies demonstrate significant potential: a reduction in variable costs of up to 9% and clear advantages over existing robust or control-based approaches in terms of planning reliability, cost efficiency, and responsiveness.