Short Term Operation & Maintenance Planning of Offshore Wind Farms: Holistic Development of a Digital Twin

The costs associated with maintenance activities in Offshore Wind Farms are significant, and particularly for preventive operations. These activities are calendarized according to the farm operator's strategy and may thus be optimized to maximize profit. However, calendarization depends directly on weather conditions, and thus on weather forecasts. The present abstract presents a digital twin application aimed at optimizing the scheduling of maintenance activities for offshore wind farms. The application incorporates the real-time weather forecast with the farm and vessel fleet characteristics and electricity price to schedule the optimal sequence of maintenance interventions. We present the development of the application, including the advances in the implementation of the optimization algorithm and additional functionalities, namely the employment a machine-learning technique for enhancing the weather forecast's accuracy and the extension to different geographies.