Research out to optimize
uncertain energy future
Posted March 26, 2013
When it comes to the power that keeps our lights on, our food cold and our computers and TVs operating, we don’t want to consider the what ifs: What if the power goes out? What if supply can’t keep up with demand?
“We all know that once you go into what ifs, it’s a big set of what ifs,” says Mihai Anitescu of Argonne National Laboratory. And uncertainties only multiply as utilities add renewable energy sources such as wind to an already enormous and complex power grid. Each wind turbine increases variability in the power supply. Utilities must address new questions like, What if wind energy suddenly increases in the Chicago area but drops off around St. Louis? What if we count on wind energy but it doesn’t come through?
“Once you go into all these branches, the problem grows big,” Anitescu says – so big that only high-performance computers can provide some answers. The research team he heads designs algorithms computers use to address optimization under uncertainty – a systematic way of asking what if to make the best decisions given randomly changing circumstances.
Anitescu, a computational mathematician at Argonne’s Laboratory for Advanced Numerical Software, builds algorithms with a range of uses. The Multifaceted Mathematics for Complex Energy Systems (M2ACS) project he heads takes a multipronged mathematical approach to operating the best possible power grid in the face of increasing demands and complexity. The project unites scientists from Argonne, Pacific Northwest and Sandia national laboratories and the universities of Wisconsin and Chicago. The team seeks computational ways to address permutations of that fundamental question: What if?
Electricity, as things stand now, can’t be stored on a large scale. Utilities and the regional transmission grids that deliver power over multiple states constantly perform a balancing act, keeping supply roughly in line with demand. Generate too little and you risk brownouts and blackouts. Generate too much and you’re wasting resources and money.