NSF Award
2219701
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>The demand for clean power is on the rise globally. The United States Department of Energy has projected that the percentage of clean electricity generated by solar power will increase to 33% to compete with the ever-growing electricity demand in the United States (US) by the year 2050. To minimize the upgradation of the existing substation and source infrastructure, it is favorable to integrate a solar energy source aided with battery storage system at the distribution level. The combination of these energy sources can be managed efficiently to behave like a "single utility-scale power station”. This is the concept of Virtual Power Plant (VPP). This project aims to address the implementation of cyber-secure pole mounted solar and battery systems equipped with smart controllers to provide a framework to remotely control and optimize the system to provide a solution to the growing power demands. Furthermore, by employing and mentoring students from underrepresented backgrounds in STEM, this project will aim at bridging the gap in institutions across the US. It will train the next generation of scholars from minority serving universities and marginalized communities in the fields of cybersecurity, utilization of renewable resources, and machine learning to address the pressing problems of this age.<br/><br/>The technical aspect of the project aims to design and implement a 5G-enabled, cyber resilient smart Artificial Intelligence (AI) based microinverter for a pole-mounted solar power system with an energy storage system connected to the low-voltage distribution networks to operate as a VPP. The data collected from the smart microinverter will be used to train a predictive model to better manage the system for improved performance. A secure and privacy-preserving 5G based communication protocol will allow uninterrupted and secure data flow between the photovoltaic and the battery system, the smart microinverter, and the Supervisory Control and Data Acquisition (SCADA) system. Hence, a security framework based on Machine Learning (ML) models will be designed and it will be based on prior cyber-attack datasets and will include continuous learning using the data collected from smart controllers and the SCADA system used to detect cyber-attacks and exploring mitigation solutions for 5G-enabled SCADA-controlled VPP network system. Guidelines and procedures will be designed to help secure the physical systems while ensuring privacy and data protection by alerting administrators regarding security compromises of the VPP network to mitigate the risks and attacks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
