A Dynamic Approach to Wind Farm Power Output Estimation and Control

 

Abstract:

The continuing rapid global growth of wind energy has the potential to transform our electric power system. However, the full potential cannot be efficiently realized within the current operating paradigms that treat wind farms as niche suppliers that are not required to contribute to grid services in the same manner as conventional generators. This talk introduces a suite of wind farm models that take steps toward enabling better wind farm power output prediction over a range of conditions. We demonstrate that our control-oriented approach to modeling can enable participation in grid services by embedding our dynamic wake model within a model-based receding horizon control framework designed to track a time-varying power signal. We then present numerical studies of a controlled wind farm that qualifies to participate in US markets for correcting short-term supply-demand imbalances on the power grid (frequency regulation). Our approach accounts for the aerodynamic interactions between turbines, which is shown to enable improved efficiency over prevailing approaches in terms of less power curtailment (lower revenue losses in the bulk power market associated with the provision of this grid service).

 

Biography:

Dennice F. Gayme is an Associate Professor in Mechanical Engineering and the Carol Croft Linde Faculty Scholar at Johns Hopkins University. She earned her B. Eng. & Society from McMaster University in 1997 and an M.S. from the University of California at Berkeley in 1998, both in Mechanical Engineering. She received her Ph.D. in Control and Dynamical Systems in 2010 from the California Institute of Technology, where she was a recipient of the P.E.O. scholar award and the James Irvine Foundation Graduate Fellowship. Her research interests are in modeling, analysis and control for spatially distributed and large-scale networked systems in applications such as wall-bounded turbulent flows, wind farms, power grids and vehicular networks. She was a recipient of the JHU Catalyst Award in 2015, ONR Young Investigator and NSF CAREER awards in 2017, a JHU Discovery Award in 2019 and a Whiting School of Engineering Johns Hopkins Alumni Association Excellence in Teaching Award in 2020.