Chris has expertise in the design of control and optimization algorithms, with specific applications to wind plants, building energy systems, and the grid. Chris is also a core developer of FLORIS, the steady-state flow modeling tool developed by NREL. Since joining NREL, he has researched topics such as distributed optimal control for wind plants, wind turbine layout optimization, and model predictive control of energy systems. He is currently focused on wind plant control, hybrid system optimization, and resilient energy systems.

Research Interests

Optimization and control

Wind energy

Buildings

Education

Ph.D., Mechanical Engineering, Texas A&M University

M.S. and B.S., Mechanical Engineering, University of Colorado Boulder

Professional Experience

Post-doctoral Researcher, NREL (2018–Present)

Post-doctoral Researcher, Colorado School of Mines (2017–2018)

Post-doctoral Researcher, University of Colorado Boulder (2017–2018)

Associations and Memberships

Member, American Society of Mechanical Engineers

Member, American Institute of Aeronautics and Astronautics

Featured Work

Towards Flow Control: An Assessment of the Curled Wake Model in the FLORIS Framework, Journal of Physics: Conference Series (2020)

Steady-State Predictive Optimal Control of Integrated Building Energy Systems Using a Mixed Economic and Occupant Comfort Focused Objective Function, Energies (2020)

A Framework for Autonomous Wind Farms: Wind Direction Consensus, Wind Energy Science (2019)

Flow Control Leveraging Downwind Rotors for Improved Wind Power Plant Operation, American Control Conference (2019)

Active Power Control for Wind Farms Using Distributed Model Predictive Control and Nearest Neighbor Communication, American Control Conference (2018)