Electrical engineering faculty member recognized with CAREER Award

Bing Yan’s research will improve smart grid management through the integration of renewable alternative energy resources and increased storage capacity

Scott Hamilton/RIT

Bing Yan, an electrical engineering assistant professor, was recently recognized with a 2024 CAREER Award from the National Science Foundation for a project to improve smart grid management.

Bing Yan is working to make today’s energy grids easier to manage.

Yan, an assistant professor of electrical engineering at RIT, is building a more coordinated system to manage different variables affecting grid energy generation, storage, transmission, and distribution—from extreme weather events to the addition of solar and wind power. Results can streamline an involved and complex process to ensure resources are available, regardless of increased demands, and provide operators the flexibility to make real-time changes when situations call for more power.

“A low carbon grid is the future, but there remain some issues with the current grid. I am looking for a more sustainable, reliable, and resilient power grid and to make the best use of renewables and better energy storage,” said Yan, a faculty-researcher in RIT’s Kate Gleason College of Engineering.

Yan was recently honored with a National Science Foundation Faculty Early Career Development (CAREER) Award. The prestigious awards are given to faculty members who have the potential to serve as role models and mentors.

Her five-year research project focuses on carbon-free clean power systems and how higher storage capacity of renewable energy resources can be achieved. Yan will develop novel mathematical models and optimization methods to improve daily operations, a strategy to better integrate uncertain renewable generation as well as new energy storage resources. Yan’s outcomes will also be used as a comprehensive forecasting model to anticipate and meet fluctuating demands.

Yan, an expert in the operations and management of power and energy systems, leads the Intelligent Lab of Power and Manufacturing that focuses on the critical field of building a reliable and sustainable energy infrastructure. Todays’ facilities consist of transmission sites and equipment over an extensive network of energy resources that provide electricity to residential, commercial, and industrial sites.

Using machine learning and a variety of optimization methods, Yan will address how to balance system challenges, such as day-ahead scheduling, real-time dispatches, and contingency planning.

“We want to give the energy storage owners the freedom to make some decisions regarding resources available. This often comes back to operational challenges, because we are looking at a huge system with many generators and transmission lines involved. That type of modeling is very complicated,” she said.

Yan will be coordinating input from three types of collaborators: independent power system operators, including representatives from significant, regional energy consumers in the Northeast, Midwest, and California; scientists and researchers from Brookhaven National Laboratory; and the National Renewable Energy Laboratory. She also is consulting with companies that develop platforms for independent system operators.

Outcomes will range from training modules for independent and regional transmission operators, the first line of workers across the grid system, and content that can be generally incorporated into different power and manufacturing systems.

RIT has more than a dozen NSF CAREER award winners at the university. CAREER Awards are just one of several indicators of a university’s growing research initiatives, funding sources, and faculty innovation. The NSF receives thousands of proposals yearly, and only 14-20 percent across all directorates of the U.S. agency are funded. Its mission is to support high risk, high pay-off ideas—projects that are leading-edge, with intellectual merit as well as broader impacts. All are well-integrated into academia as a way to train next-generation scientists and engineers.

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