Wind Farm Modeling and Control Using Dynamic Mode Decomposition

Abstract

The objective of this paper is to construct a low-order model of a wind farm that can be used for control design and analysis. There is a potential to use wind farm control to increase power and reduce overall structural loads by properly coordinating the turbines in a wind farm. To perform control design and analysis, a model of the wind farm needs to be constructed that has low computational complexity, but retains the necessary dynamics. This paper uses an extension of dynamic mode decomposition (DMD) to extract the dominant spatial and temporal information from computational fluid dynamic simulations. Specifically, this extension of DMD includes input/output information and relies on techniques from the subspace identification literature. Using this information, a low-order model of a wind farm is constructed that can be used for control design.