Associate professor of electrical and computer engineering and IEEE senior member Xingpeng Li, Ph.D., has received a Grainger Foundation Frontiers of Engineering Grant for the Advancement of Interdisciplinary Research by the National Academy of Engineering (NAE).
This grant, available only to attendees of the 2024 Grainer Foundation Frontiers of Engineering Symposium, provides seed funding for Li’s collaborative project titled “Electrical Grid Congestion: Analysis, Implications and Enhancement,” which he undertakes alongside Satyajith Amaran of Dow.
Frontiers of Engineering is an NAE program that brings together highly accomplished early-career engineers from industry, academia, and government to discuss pioneering technical work and leading-edge research in various engineering fields and industry sectors.
Li has had a particular focus on power engineering and power systems since he was a bachelor’s student. He also completed both his master’s degree and Ph.D. in power systems and automation, with a Ph.D. focus on real-time power system operations.
After joining the University of Houston in 2018, his research expanded to include power system control, reliability, and resilience, as well as small-scale power systems known as micro-grid systems, such as those that serve a single community or a university or business campus.
Now, Li and Amaran’s project “aims to analyze electrical network congestion and its implications for industry entities and grid operators through three tasks: assessing network congestion and electricity price contours under different scenarios, developing a novel hierarchical machine learning (ML) model for predicting congestion and electricity prices, and simulating the impact of demand response from large consumers.”
“For this particular project, we want to analyze electrical network congestion so that we can figure out the impacts of congestion and how it affects wholesale electricity prices, and how that affects the larger industry consumers who want to avoid high or peak pricing,” said Li.
For example: large-scale consumers shifting their equipment use windows from higher-price hours to lower-price hours; this consumption shift is considered a demand response from the grid perspective. In this case, Dow will provide input as a large industry entity.
The project’s outcomes “are expected to benefit the public by enabling better-informed operational decisions for large industry entities and thus reducing peak demand on the grid, which will alleviate power grid congestion, improve system operational efficiency and reliability, and facilitate the growth of clean energy generation in the grid.”
“This research may potentially affect some real-world industry operations,” said Li. “If large companies with large-scale manufacturing plants can better forecast wholesale electric prices and are able to shift their large load electricity consumption from peak hours to off-peak hours, this will help relieve electric grid congestion and mitigate price spikes as well as this potentially helping reduce unnecessary curtailment of clean renewable energy.”
Li added that this impact has the potential to benefit all other consumers in addition to the targeted large-scale energy customers.