My research activities span all branches of control theory with applications to electric power systems. At NC State I am a part of the NSF FREEDM Systems Center, currently investigating several system and control-theoretic research problems for the US power grid using Wide-area Measurement Systems (WAMS), or Synchrophasor technology, its cyber-physical implementation via service-oriented wide-area communication networks, and its integration with renewable energy sources such as wind and solar energy.
As of Fall 2021, I have graduated 12 PhD students and 5 postdocs, and currently supervise 6 PhD students. Some specific topics of research that my group is currently looking into are:
1. Reinforcement Learning based Control of Multi-Agent Networks – Adaptive and optimal strategies for designing distributed model-free controllers for network dynamic systems, combining model reduction theory with learning-based control for real-time control of extreme-scale networks, Carlemann approximation methods for model-free nonlinear control
2. Data-driven Wide-area Monitoring and Control of Power Systems – Adaptive and optimal strategies for wide-area control of power systems using PMU data under high levels of model uncertainties
3. Co-designing Wide-area Communications and Control – Cyber-physical challenges for wide-area communications, co-designing sparse controllers using information about network delays
4. Hierarchical Control of DERs – Multi-stage optimization and control of next-generation grid with millions of new control points from inverter-based distributed energy resources
5. Optimization and Control of Power Distribution Systems – Over the past two years, my research has also broadened to new problems on dynamics, optimization and controls at distribution-level power systems arising due to large-scale integration of electric vehicle charging and power electronic converters such as Solid State Transformers (SST), coupled with wind and solar generation.