Coordinated Learning for Wind Farm Optimization

Abstract

Optimal efficiency and loads alleviation in a dynamic environment necessitates a wind farm controller that can anticipate and quickly adapt to changing wind and wake conditions. In this work, we explore several strategies for collective learning and optmization, first using a high-level parametric wake model, and then a more complex approach, i.e. Large Eddy Simulation (LES) coupled to a wind turbine model