This $300,000 Project Grant was awarded on January 1, 2025 by the National Science Foundation (NSF) under the Integrative Activities (IA) program (CFDA 47.083) to Mississippi State University (MSU). The project aims to develop a comprehensive federated learning framework for condition monitoring, secure data sharing, and automated maintenance of distributed wind energy systems (DWS) in rural areas. The key products and services to be delivered include:
Collaborative federated learning algorithms for privacy-preserving condition monitoring of DWS using SCADA data
A secure, tamper-resistant blockchain-based data sharing platform to improve auditability of DWS operational data
Blockchain-enabled smart contracts to streamline maintenance scheduling and decision-making for DWS
This interdisciplinary project combines MSU's renewable energy expertise with the University of Miami's competencies in AI, distributed systems, and cybersecurity. The goal is to reduce operating costs, enhance cybersecurity, and improve reliability of DWS to support wider adoption of this renewable energy technology in rural communities. No sub-awards are planned under this grant.