Energy, Power, Control, and Networks
🏛 U.S. National Science Foundation (NSF)
✓ Free, no account · Source: Grants.gov · Last verified Jul 15, 2026
Can you apply?
This grant is for research institutions and universities conducting fundamental and applied research in energy systems, power control, and networked systems.
U.S. academic institutions, national laboratories, and research organizations are eligible. Researchers must propose innovative work in control systems, power electronics, energy integration, or machine learning applications.
Research can focus on modeling, optimization, and control of multi-agent systems; renewable energy grid integration; power systems resilience; or neuromorphic computing. All work must advance emerging technologies in energy, transportation, robotics, or biomedical systems.
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Program description
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’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
Who can apply
Eligible applicants
How to apply
Application links
Required documents
- NSF PAPPG cover sheet (SF-424 or FastLane equivalent)
- Project narrative and research plan
- Budget and budget justification
- Biographical sketches of senior personnel
- Current and pending support documentation
- Institutional commitment letters (if applicable)
Program contact
- 👤 National Science Foundation
- 📧 grantsgovsupport@nsf.gov
- 📞 703-292-4261
Funding track record
Recent awards under CFDA 47.041 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
-
$41,946,862
-
$39,155,237
-
$38,277,956
-
$37,936,436
-
$36,940,111
-
$36,277,271
-
$36,183,087
-
$32,471,912
-
$32,414,114
-
$31,561,058
Top States by Funding
- TX 3 awards $90.6M
- CA 7 awards $85.0M
- IL 5 awards $83.9M
- AZ 2 awards $68.7M
- NC 2 awards $63.3M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 47.041). How funding has trended year over year.
| 2024 | $752,230,000 | |
| 2025 | $727,730,000 | |
| 2026 est. | $181,990,000 |
FAQ
Who is eligible to apply?
U.S. research universities, academic institutions, and national laboratories may apply. Researchers must have institutional affiliation and capability to conduct the proposed research.
What types of research does EPCN fund?
The program supports control systems, power electronics, renewable energy integration, machine learning, and their applications in energy and transportation sectors.
Is there a cost-sharing requirement?
No cost-sharing is required for this NSF program.
How competitive is this program?
EPCN is highly competitive. Strong proposals include novel theoretical contributions, clear technical merit, and potential real-world applications in energy or transportation.
What is the typical award size and duration?
NSF EPCN awards vary; contact program directors for current funding levels and typical project durations.
💡 Tips for applicants
- Contact relevant program directors early to confirm your research aligns with current program priorities and focus areas.
- Ground research in clear technical merit and demonstrate how it addresses real energy, transportation, or biomedical challenges.
- Connect fundamental theory to practical applications; emphasize interdisciplinary connections where relevant.
- Provide detailed methodology and measurable milestones for research progress evaluation.
- Address broader impacts explicitly: workforce development, commercialization potential, or public benefit of your research outcomes.
⚠️ Common mistakes
Proposals lack clear connection to energy systems, power, or networked control applications. Theoretical work without demonstrated relevance to EPCN focus areas gets rejected. Incomplete project plans fail to show concrete milestones and deliverables.
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