Energy, Power, Control, and Networks

The summary for the Energy, Power, Control, and Networks grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the National Science Foundation, which is the U.S. government agency offering this grant.
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=";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>
Federal Grant Title: Energy, Power, Control, and Networks
Federal Agency Name: National Science Foundation (NSF)
Grant Categories: Science and Technology
Type of Opportunity: Discretionary
Funding Opportunity Number: PD-18-7607
Type of Funding: Grant
CFDA Numbers: 47.041
CFDA Descriptions: Information not provided
Current Application Deadline: November 1st, 2018
Original Application Deadline: November 1st, 2018
Posted Date: February 23rd, 2018
Creation Date: February 23rd, 2018
Archive Date: December 3rd, 2025
Total Program Funding:
Maximum Federal Grant Award:
Minimum Federal Grant Award:
Expected Number of Awards:
Cost Sharing or Matching: No
Last Updated: February 23rd, 2018
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-18-7607
Grant Announcement Contact
NSF support

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