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&rsquo;s goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices &amp; 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 &amp; economic structures and with consumer behavior. Areas managed by Program Directors (please contact Program Directors listed in the <a href="https://www.nsf.gov/staff/staff_list.jsp?orgId=5915&amp;subDiv=y&amp;org=ECCS&amp;from_org=ECCS">EPCN staff directory</a> for areas of interest): Control Systems <ul> <li>Distributed Control and Optimization</li> <li>Networked Multi-Agent Systems</li> <li>Stochastic, Hybrid, Nonlinear Systems</li> <li>Dynamic Data-Enabled Learning, Decision and Control</li> <li>Cyber-Physical Control Systems</li> <li>Applications (Biomedical, Transportation, Robotics)</li> </ul> Energy and Power Systems <ul> <li>Solar, Wind, and Storage Devices Integration with the Grid</li> <li>Monitoring, Protection and Resilient Operation of Grid</li> <li>Power Grid Cybersecurity</li> <li>Market design, Consumer Behavior, Regulatory Policy</li> <li>Microgrids</li> <li>Energy Efficient Buildings and Communities</li> </ul> Power Electronics Systems <ul> <li>Advanced Power Electronics and Electric Machines</li> <li>Electric and Hybrid Electric Vehicles</li> <li>Energy Harvesting, Storage Devices and Systems</li> <li>Innovative Grid-tied Power Electronic Converters</li> </ul> Learning and Adaptive Systems <ul> <li>Neural Networks</li> <li>Neuromorphic Engineering Systems</li> <li>Data analytics and Intelligent Systems</li> <li>Machine Learning Algorithms, Analysis and Applications</li> </ul>