Power grid optimization problems are known to be computationally extensive, but researchers at The University of Texas at Arlington are designing new algorithms to address these challenges.
Ramtin Madani, an assistant professor in the Electrical Engineering Department, recently was awarded a $325,000 grant from the National Science Foundation to develop massively scalable computational methods for power system scheduling. Associate Professor Ali Davoudi is co-principal investigator.
"This new grant will address a crucial component of how our national energy infrastructure is used and managed in the future."
Since upgrading the existing infrastructure can be expensive, academics and industry experts have shifted efforts toward software modernization. One of the most important challenges is to improve the scalability of algorithms for solving power system operational problems.
Power grid problems can be formulated in the language of mathematical optimization. From there, algorithmic tools and techniques from the area of optimization theory are used to address those problems.
Drs. Madani and Davoudi are aiming at developing far more enhanced optimization algorithms to improve the efficiency and reliability of power grid operations. These algorithms can be used to address practical, everyday problems in the area of power. Advanced optimization algorithms enable operators to incorporate further renewable energy sources, which are highly unpredictable.
"Madani and Davoudi's research is an example of Global Environmental Impact, a theme of UTA’s Strategic Plan 2020," says Jonathan Bredow, chair of the Electrical Engineering Department. "Efficient power distribution and energy grids have long been a research strength at UTA, and this new grant will address a crucial component of how our national energy infrastructure is used and managed in the future."
