The conventional wisdom about utility spending is correct, but key factors affecting customer satisfaction aren't obvious—and are tricky to control.
Distribution management at the smart grid frontier.
when the next major storm hits.
“It’s all about understanding close to real-time what’s going on, and having enough time to adjust and optimize well ahead of a projected event,” Vujovic says.
Being Kind to the Grid
Effective demand reduction and grid optimization are promising ADMS features. In the past, on summer days so hot that the pavement would seem to melt, utilities would see an overload on a circuit and transfer part of that circuit to an adjacent one nearby. But on such days all circuits might be near their peak capacity, so this practice could create a domino effect of overloads.
“We used to call it ‘chasing the amps around the system’ during those hottest days of the year,” says Brad Williams, vice president of products management for Oracle Utilities. Earlier in his career, Williams directed T&D asset management at PacifiCorp.
Instead of chasing amps, Williams says ADMS capabilities will allow utilities to simulate the optimal solution with the fewest number of switching operations needed to relieve an overload condition. “In some cases where there’s remote-controlled switchgear, we actually can carry it out automatically just by pushing a button,” he says.
The trick is using information technology to tie grid operations together quickly, efficiently, and effectively in real time, Geisler says. This can involve highly granular data, down to the level of individual transformers and circuits. On that hot summer day, for example, a transformer can be overloaded to about 150 percent of its design rating without blowing it up. After two hours, the load has come down, but the overload can have lasting consequences for equipment on the system. “I’m out of trouble, but I’ve just aged that transformer beyond its normal wear,” Geisler says. “That information is useful.” A truly advanced DMS would identify what’s happened to that particular transformer and push the information to both the utility’s maintenance centers and asset centers. The maintenance schedule for that piece of equipment would change accordingly. After the transformer is checked and an asset calculation done, it might become apparent that the temporary overload accelerated its degradation, and that information gets communicated to the operations side.
“Maybe we want to go back through the operations guys and tell them, ‘You need to de-rate this particular transformer, and we’re going to move it up in the queue for replacement,’” Geisler says. “That analysis and that information could be integrated. It could happen automatically.”
Capabilities at this level of granularity also can serve to raise system efficiency and reduce load overall. In advance of its full DMS rollout, OG&E installed ABB’s volt-VAR control module. The initial plan is to put volt-VAR optimization on 400 circuits with the goal of achieving a 75-MW demand reduction. In summer 2010, OG&E tested the system and saw demand fall by between 0.8 percent and 2.4 percent, depending on the circuit. “It doesn’t sound like a lot, but when you add it up, we’ve reached our goal,” Milanowski says, citing a 200-kW reduction on average per circuit. Multiply that times 400 circuits and the result is 80