Energy, Power, Control, and Networks

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems. The program emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid. The EPCN program also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. Some key areas of interest include: • 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) • 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