Training Next Generation Power Engineers

With the increasing adoption of interconnected power and micro grid infrastructures, today's power engineering research professionals require broader knowledge and a more diverse skillset specializing in machine learning, control, communications, and smart grid cyberinfrastructure (CI).

Zhen Ni, Ph.D., assistant professor in the Department of Electrical Engineering & Computer Science, is working to integrate these advanced skills and frontier research into the educational curriculum and instruction materials to support advanced power engineering infrastructure. He was awarded a $299,876 grant from the National Science Foundation, as well as a $16,000 supplement, to establish a new, remotely-connected smart grid CI platform using a real-time digital simulator and sharing software licenses and hardware resources.

“This project enables students to practice the multi-disciplinary skills needed for the future power industry and prepares them to face the challenges in modern power systems,” Dr. Ni explained. “The advanced CI training experience helps extend their academic and research portfolios and strengthens their career competitiveness as smart grid CI professionals and CI users.”

The smart grid CI platform generates sample projects and experiments on topics such as renewable energy integration, cybersecurity, cascading failure, and home energy management. The data from these projects is generalized so it can be easily adapted by other institutions. In addition, Dr. Ni’s team collects heterogenous smart grid measurement data from the new CI to conduct real-time learning, event detection and data integrity, online optimization and multi-level decision making process of intelligent systems. Results will be integrated into existing undergraduate and graduate courses. The team also creates duplicable project templates with designated data and models from the remotely connected CI so other schools can easily adopt this educational model.

“With the modern information and communication technologies, as well as millions of newly deployed smart meters, the existing electric power industry is aware of the increasing importance of smart grid big data,” said Dr. Ni. “In addition to teaching traditional power system courses, universities need to incorporate new knowledge of information and communications technologies, policy, and economics.
The enhanced power engineering curriculum resulting from this project promotes the application of advanced CI techniques in power system monitoring, planning, operation and control. The remotely connected CI provides an ideal platform to advance the multi-interdisciplinary research and education of computational intelligence, machine learning, control, communication, and data analytics in the smart grid area.”