A WSU research team has received a $1.2 million U.S. Department of Education grant to train graduate students at the intersection of artificial intelligence (AI), data science, and engineering to address challenges of the future electric power grid.
Led by Assefaw Gebremedhin, associate professor in the School of Electrical Engineering and Computer Science, the Graduate Assistance in Areas of National Need (GAANN) grant aims to enhance teaching and research in areas of national need.
“AI and the closely related area of data science affect nearly everything that we do,” said Gebremedhin. “We need to have power engineers who speak both languages — who are trained to be good power engineers and are also able to do good data science.”
In recent years, the US power grid has been rapidly evolving from a network of centralized fossil fuel-powered generation plants to a system that includes more distributed generation and renewable resources. As power becomes more decentralized, traditional ideas about power grid operations have been changing.
Distributed assets need to be controlled and managed differently than in the past.
Climate change is also leading to an increase in extreme weather events, which means that the power system has to be more resilient and operate under fast-changing conditions, says Gebremedhin. Changes in technology are also allowing customers to be more actively and directly involved in controlling their energy use.
“These rapid transformations threaten power grid reliability,” he said.
The US power industry is increasingly adopting machine learning and data analytics technologies to improve its reliability, resiliency, and efficiency.
Meanwhile, software that gets developed in the power industry as well as in many other engineering applications is increasingly getting more complex. Software engineers of the future would not only need to know how to build and maintain complex software, but they would also need to know how to extract knowledge from massive amounts of data and adapt that knowledge to consider different human factors.
As part of the grant, a total of eight U.S. PhD students will receive training, focusing on the application of AI and data science to power engineering and software engineering.
“The new workforce needs to be trained in traditional topics on electric and power engineering along with having an understanding of data science and machine learning, information and communication technology, and control and automation,” he said.
With programs in power engineering, machine learning and AI, and software engineering, the School of EECS presents a unique opportunity to bridge the fields of computer science and power engineering.
“There are just a few schools in the country where you have these disciplines housed in the same school, which is a great asset,” he said.
The three-year program will focus on recruitment of students from underrepresented groups in engineering and computer science, including women, black and Hispanic students. In addition to Gebremedhin, the program is led by three women faculty members in electrical engineering and computer science, Anamika Dubey, Venera Arnaoudova, and Noel Schulz. The students will receive training in teaching and mentoring and will also have opportunities to participate in internships through the Pacific Northwest National Laboratory.