Energy, Power, Control and Networks
The summary for the Energy, Power, Control and Networks grant is detailed below.
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Energy, Power, Control and Networks: Recent advances in communications, computation, and sensing technologies offer unprecedented opportunities for the design of cyber-physical systems with increased responsiveness, interconnectivity and automation. To meet new challenges and societal needs, the Energy, Power, Control andNetworks (EPCN) Program invests in systems and control methods for analysis and design of cyber-physical systems to ensure stability, performance, robustness, and security. Topics of interest include modeling, optimization, learning, 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 adaptive dynamic programing, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN supports innovative proposals dealing with systems research in such areas as energy, transportation, and nanotechnology. EPCN places emphasis on electric power systems, including generation, transmission, storage, and integration of renewables; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory and economic structures and with consumer behavior. Also of interest are interdependencies of power and energy systems with other critical infrastructures. Topics of interest include energy scavenging and alternate energy technologies such as solar, wind, and hydrokinetic. The program also supports innovative tools and test beds, as well as curriculum development integrating research and education. In addition to single investigator projects, EPCN encourages cross-disciplinary proposals that benefit from active collaboration of researchers with complementary skills. Proposals for the EPCN program may involve collaborative research to capture the breadth of expertise needed for such multidisciplinary integrative activities. ECCS will consider supporting a limited number of small team proposals of three or more Investigators from different disciplines and/or universities. Areas covered by the EPCN Group (Abed, Baheti, and Werbos): Control Theory and Hybrid Dynamical Systems Networked Multi-agent Systems Cyber Physical Systems Modeling and Control System Theory for Biology and Medicine; Modeling of the Brain Control and Optimization in Buildings, Transportation, and Robotics Adaptive and Intelligent Systems; Neural Networks Energy Harvesting, Storage Devices and Systems Solar and Wind Energy and Integration of Renewables with Grid Monitoring, Protection and Cyber Security of Power Grid Advanced Power Electronics and Electric Machines Electric and Hybrid Vehicles; Integration with Grid Policy, Economics, Consumer Behavior and the Power Grid Quantum, Molecular and High Performance Modeling and Simulation for Devices and Systems (QMHP) (Paul Werbos)
Federal Grant Title: | Energy, Power, Control and Networks |
Federal Agency Name: | U.S. National Science Foundation (NSF) |
Grant Categories: | Science and Technology and other Research and Development |
Type of Opportunity: | Discretionary |
Funding Opportunity Number: | PD-13-7607 |
Type of Funding: | Grant |
CFDA Numbers: | 47.041 |
CFDA Descriptions: | Information not provided |
Current Application Deadline: | July 7th, 2025 |
Original Application Deadline: | July 7th, 2025 |
Posted Date: | June 6th, 2025 |
Creation Date: | June 6th, 2025 |
Archive Date: | June 7th, 2025 |
Total Program Funding: | |
Maximum Federal Grant Award: | |
Minimum Federal Grant Award: | |
Expected Number of Awards: | |
Cost Sharing or Matching: | No |
Last Updated: | June 6th, 2025 |
- Applicants Eligible for this Grant
- Unrestricted (i.e., open to any type of entity below), subject to any clarification in text field entitled "Additional Information on Eligibility"
- Link to Full Grant Announcement
- NSF Program Desccription PD-13-7607
- Grant Announcement Contact
- NSF grants.gov support
[email protected]
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