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Energy, Power, Control, and Networks (EPCN)

Important Information for Proposers

Any proposal submitted in response to this funding opportunity should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable version of the PAPPG. Submitting a proposal prior to a specified deadline does not negate this requirement.

Supports research in modeling, optimization, learning, adaptation and control of networked multi-agent systems; higher-level decision making; and dynamic resource allocation and risk management.


The Energy, Power, Control, and Networks (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

Program contacts

Eyad Abed
eabed@nsf.gov (703)292-8339 ENG/ECCS
Aranya Chakrabortty
achakrab@nsf.gov (703) 292-8113 ENG/ECCS
Mahesh Krishnamurthy
mkrishna@nsf.gov (703)292-8339 ENG/ECCS
Anthony Kuh
akuh@nsf.gov (703) 292-8339 ENG/ECCS

Awards made through this program

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Map of recent awards made through this program