Collaborative Research: CyberTraining: Pilot: PowerCyber: Computational Training for Power Engineering Researchers

The PowerCyber project aims to address the underutilization of advanced Cyberinfrastructure (CI) in the domain of power and energy engineering. Despite the significant advancements in CI, its adoption in power engineering has been limited due to a lack of quality training materials and the historical reliance on limited tools. This project seeks to fill the gap by creating an online, modular, and open-access training workshop tailored for researchers in power engineering. The project will democratize access to high-quality research training, benefit a diverse population, and foster collaborations between the power and CI communities. Also, the project is expected to equip the research workforce with an understanding of advanced CI software and hardware and help accelerate interdisciplinary research for the clean energy transition.

In this project, the investigators will develop an online, modular, and openly available PowerCyber training to prepare power engineering researchers with a comprehensive understanding of advanced CI software, hardware, and emerging CI technologies. The tasks include a) developing high-quality, interactive, and on-demand training modules to cover advanced CI in software, hardware, and emerging techniques and demonstrating, by research examples, their potential to transform power engineering research; b) offering virtual PowerCyber training workshops; and c) incorporating the training materials into the curricula at the home institution of the investigator. Upon the completion of this project, we expect to have demonstrated a pilot training workshop that provides researchers with advanced CI capabilities for solving power-domain problems.

This project is jointly funded by the Office of Advanced Cyberinfrastructure and the Established Program to Stimulate Competitive Research (EPSCoR).

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.

Award Number: 2603374
Principal Investigator: Xin Fang
Funds Obligated: $69,222
State: SC