The University of Texas at Arlington News Releases
Optimization of power grids in the United States, or increasing efficiency, reliability and security of the grid while reducing the cost of producing power, is a complex problem without an easy solution, but a University of Texas at Arlington researcher is hopeful that he can find a way to overcome the mathematical and physical barriers to make optimization a reality.
Ramtin Madani, an assistant professor in UTA’s Electrical Engineering Department, is pictured with students Edward Arthur Quarm, left, and Muhammad Adil. Madani was recently awarded a National Science Foundation grant to optimize power grids.
Ramtin Madani, an assistant professor in UTA’s Electrical Engineering Department, recently was awarded a $325,000 grant from the National Science Foundation to develop massively scalable computational methods for power scheduling. Ali Davoudi, an associate professor in the department, is the co-principal investigator.
Operating and upgrading the existing infrastructure is very expensive and ongoing debates between academia and industry have resulted in software that has not been upgraded for decades. However, both groups have shifted efforts toward software modernization in recent years. Optimization focuses on efficiency in producing and distributing power, security and reliability so that consumers aren’t hit with massive blackouts or cascading failures. Upgrading the nation’s power grids is an area that has been stressed by the National Academy of Engineers and the Federal Energy Regulatory Commission. The U.S. Department of Energy, National Science Foundation and others have dedicated resources to optimizing the grid.
The biggest challenge to optimization is scalability because even in the smallest grid, it is difficult to find a system to route power, find the proper on/off switches and determine what generators should operate the following day in the most efficient way possible. In fact, the number of possible solutions for any specific problem outnumbers current computational power.
Madani and Davoudi will cast the problems in …