Energy, Power, Control, and Networks

The Energy, Power, Control, andNetworks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN’s goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

Areas managed by Program Directors (please contact Program Directors listed in the EPCN staff directory for areas of interest):

Control Systems

Distributed Control and Optimization

Networked Multi-Agent Systems

Stochastic, Hybrid, Nonlinear Systems

Dynamic Data-Enabled Learning, Decision and Control

Cyber-Physical Control Systems

Applications (Biomedical, Transportation, Robotics)

Energy and Power Systems

Solar, Wind, and Storage Devices Integration with the Grid

Monitoring, Protection and Resilient Operation of Grid

Power Grid Cybersecurity

Market design, Consumer Behavior, Regulatory Policy

Microgrids

Energy Efficient Buildings and Communities

Power Electronics Systems

Advanced Power Electronics and Electric Machines

Electric and Hybrid Electric Vehicles

Energy Harvesting, Storage Devices and Systems

Innovative Grid-tied Power Electronic Converters

Learning and Adaptive Systems

Neural Networks

Neuromorphic Engineering Systems

Data analytics and Intelligent Systems

Machine Learning Algorithms, Analysis and Applications