Modernize the energy grid software

style=”color:blue”>Grid Optimization (GO) Competition. The competition was announced last summer, and comprises a series of challenges meant to modernize grid software in key areas such as the optimal utilization of conventional and emerging technologies, management of dynamic grid operations, and management of distributed energy resources. The ultimate goal is to develop a more flexible, resilient, cost-effective grid.

The first challenge is to develop an algorithm that can address the grid’s security-constrained optimal power flow, or SCOPF, problem.

It’s a uniquely difficult optimization problem. There’s a huge number of variables—power generation, voltages, phase angles, transformer power limits—and many difficult constraints.

“You’re basically using physical equations to describe what happens on these lines, and they’re relatively complicated mathematical expressions of how power flows,” says Curtis. “But what really makes the competition difficult is this idea of accounting for each contingency. You have to figure out, ‘Okay, if I lost this line or this generator, how would it affect all of my variables? How would that affect every decision I’ve made?’ For every contingency you consider, it basically multiplies the size of the problem.”

The challenge, which started in November 2018, brings together teams from other top institutions such as Georgia Tech, Penn State, Northwestern University and the University of California, Berkeley; national laboratories including Argonne, Lawrence Berkeley, and Lawrence Livermore; and private-sector companies.

Teams must submit their code in April for the first of two trial events, and they will be judged on how quickly their algorithms can solve a hypothetical problem with multiple contingencies.

“The whole competition is, How do you get the best answer you can in a limited amount of time that works well for various types of networks?” says Curtis.

ARPA-E will release more data sets between now and August that will help teams further refine their code. The agency will hold the final evaluation event in November, after which they’ll announce the top 10 finishers in multiple divisions. Those teams will get a share of $4 million in prize money.

Awards are great, but the problem itself is enticing.

“This type of optimal power flow problem is fairly well-known in the optimization community as a challenging problem to solve, which is exciting,” says Curtis. “And while I’m not an expert when it comes to the power grid, I’m definitely in favor of renewable energy. But I can see the challenges in making them more of a reality, so the idea of being able to contribute something to that work is also pretty exciting.”