Wind Farm Control Under Uncertainty

Project Overview

This research explores optimization under uncertainty applied to wind farm control strategies. Starting with yaw control optimization and expanding to comprehensive uncertainty quantification, we developed novel methods to account for real-world variability in wind farm operations. This work has been cited in over 100 research papers and two patents, becoming a popular approach for the "wake steering" control strategy.

Key Features

• Novel framework for optimizing wind farm control under uncertainty
• Pioneering work in yaw-based wake steering considering uncertainties
• Extensions to handle multiple sources of uncertainty including wind direction
• Implementation in industry-standard tools like TOPFARM and FLORIS

Technical Details

The research began by developing optimization under uncertainty (OUU) approaches for yaw-based wake steering, then expanded to include multiple uncertainty sources. We created frameworks for both single-parameter and multi-parameter uncertainty quantification, leading to more robust control strategies.

Results & Impact

This research established a new paradigm for wind farm control strategies by incorporating uncertainty quantification. The methods improved annual energy production by 0.5% while reducing extreme turbine yaw offsets - a critical balance between performance and reliability. The work has been cited in over one hundred research papers and has direct industrial relevance, as evidenced by its citation in industrial patents. Today, these uncertainty-aware control approaches are implemented in many experimental and commercial wind farm controllers.