Wind3D Project

The WIND3D project explores innovative offshore wind farm designs by incorporating non-uniform wind turbines of varying heights. Traditional wind farms use identical turbines, limiting their efficiency and adaptability. This project investigates how optimizing turbine placement in three dimensions can enhance energy output, reduce wake effects, and improve cost efficiency.

A collaboration between the Energy Informatics Lab and the Bergen Offshore Wind Centre (BOW) at UiB, WIND3D integrates optimization, machine learning, and advanced simulation models to address complex design challenges. By leveraging machine learning for predictive modeling and multi-objective optimization, the project aims to develop novel strategies for maximizing offshore wind farm performance in dynamic environmental conditions.

This interdisciplinary research has the potential to redefine offshore wind energy design, contributing to more efficient, resilient, and cost-effective renewable energy solutions.

This research project is funded under the Akademiaavtalen. The background for Akademiaavtalen is to further develop the long-term research collaboration between UiB and Equinor.