A Multi-objective Yaw-control System for Wind Farm Optimisation Based on Novel 3D Wake Model

Principle Investigator: 
Ir Prof. YANG Hongxing, Professor, Department of Building Environment and Energy Engineering

This digital yaw optimisation system is designed for large-scale wind farms. It combines an innovative 3D yaw wake model with a machine learning module to accurately calculate power and loads based on given yaw angles. The system then uses multi-objective optimisation strategies to balance energy output and structural loads. Currently, it is at Technology Readiness Level 6.

For the 60-turbine Princess Amalia Wind Farm, located offshore of IJmuiden in the Netherlands, our system can increase power production by up to 8.79% in the main wind direction. It is effective for both upgrading the performance of existing wind farms, and in the early design phase of new wind farms, enabling optimised wind turbine locations and energy capture from the outset.

Our invention improves the operational efficiency and reliability of wind farms, offering significant economic and social benefits for wind power.