👋🏽 Hi there, I’m Joel!
I am a postdoctoral researcher with the Department of Electrical, Computer, and Energy Engineering at Arizona State University, working with Lalitha Sankar and Oliver Kosut. I did my PhD at the University of Florida in beautiful Gainesville with Sean Meyn on the distributed control of flexible loads for balancing the electricity grid: Dissertation
My research interests are at the intersection of control, optimization, and reinforcement learning, with an emphasis on applications to power systems. The range of technical topics includes deterministic reinforcement learning in continuous time, control of Markov processes, model predictive control, and numerical optimization. I am particularly interested in decision making across different timescales driven by forecast information for resource allocation in the electricity grid.
During my PhD, I performed multiple internships at Electric Power Engineers, LLC in Austin, Texas, with a particular focus on the development of a general deep learning framework for load forecasting across different timescales and regions: the software tool showed remarkable accuracy in forecasting on time horizons ranging from a few hours to a month, as well as across different distribution networks.
Following the winter storm and the subsequent blackouts in Texas in February 2021, my colleagues and I wrote an op-ed in Utility Dive warning against the blind application of real-time and surge pricing in the power grid.
Research Interests
- Smart Electricity Grids
- Regulation and dispatch of distributed energy resources
- Optimization and control for grid reliability and renewable energy integration
- Energy policy and power systems economics
- Control theory
- Stochastic and deterministic optimal control
- Reinforcement learning and data-driven control
- Model predictive control
- Robust control
- Markov chains