Validating The Smart Grid

By Chuck Ross | Jan 15, 2013




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While the smart grid has been the topic of much conversation lately, specifics on what this supposed technical marvel will do, cost or look like in actual utility installations have been notably lacking. The largest smart grid demonstration project to date has just gone live in the Pacific Northwest to provide those specifics. It could establish a framework for other regions to follow as next-generation equipment is deployed across the nation’s electrical infrastructure.

In essence, the “smart grid” describes a combined transmission and distribution system capable of responding to specified inputs along the full range of supply and demand resources. But developers haven’t always agreed on what data should be passed back and forth and how it should determine system operations. This demonstration, led by the Pacific Northwest National Laboratory (PNNL), is taking a market-based approach, using the cost of electricity at every point in the delivery chain as a means for automating operations and encouraging end-users to match their demand to current and projected supplies and conditions.

Eleven utilities in Idaho, Montana, Oregon, Washington and Wyoming have joined with PNNL to test the use of these “transactive control signals.” The $178 million effort is equally funded by federal stimulus money and the participating utilities. (The utilities had to match at least 50 percent of the money received.)

“Roughly $100 million of that is spent by the utilities to install smart grid devices and technology,” said Ron Melton, PNNL project manager, adding that the remainder is for developing and implementing techniques and interpreting the data, along with managing the overall program.

This demonstration work has its roots in a 2006–2007 research project using market-based rates to control operation of distributed generation resources and some customer end-use equipment. The current demonstration project focuses at the point where transmission and distribution systems meet and adds multiple layers of complexity to the communication of cost signals down the chain, from large-scale generation resources to distribution-level transformers. 

Now, participating utilities are installing and testing new switchgear, battery storage systems, transformers and other equipment. They also will be connecting to systems predicting renewable-power availability in increments from five minutes to a day or more. This is especially important in this service territory, where wind capacity is anticipated to climb from a current 4,000 megawatts (MW) to as high as 12,000 MW over the next several years. It’s important to note that these utilities range from large investor-owned companies to municipal utilities and rural electric cooperatives.

“That diversity is important because we’re addressing interoperability,” Melton said. 

However, because the majority of the region’s electricity is generated by the Bonneville Power Authority through bilateral agreements—instead of open-market trading, as is the case in the Midwest and along the East Coast—program developers had to address fewer pricing variables than might have been the case elsewhere.

The transactive control system has three basic components: the transactive control node, a transactive incentive signal and a transactive feedback signal. The nodes are, essentially, devices that can receive and transmit communications in either direction, up or down the electricity supply and demand chain. Those communications take the form of incentive signals, which pass updated pricing information down the chain, and feedback signals, which indicate projected demand back up that chain. Decisions can be made at each node down the chain to increase the incentive value (i.e., lower electricity rates) as less load is needed below that point or to decrease that value as demand rises. 

By enabling this kind of distributed communications, utilities may be better able to take site-specific equipment considerations into account in balancing overall grid operations. For example, consider a pole-mounted transformer serving a small neighborhood that’s home to multiple electric vehicle-­owning households. If all the vehicles were to start charging at the same time, the transformer could overload. Transformer-level signaling could adjust pricing as more users plugged in their vehicles, encouraging staggered charging that would aid grid operations. 

In all, utilities have developed 90 different test cases to explore over the next two years, with 40 of those focused specifically on transactive control scenarios. In the process, they have installed some 80,000 smart-grid-enabling assets, such as smart meters, and 12,000 smart grid-responsive assets, ranging from water heater load controllers up to large backup generators. 

Melton said future efforts building on this project’s results could move forward in a number of directions. 

The technology would be a natural basis for estimating a market for renewable integration or working with BPA—or other generators—to look at bulk power systems, he said, noting one possibility. 

“Another would be working with utilities to push it down their distribution systems,” Melton said. 

Regardless, he added, any future work would continue the real-world emphasis this current project has established.

“Our basic role is to keep pushing the envelope with things that engage the industry directly and to do real things in the field,” he said.

About The Author

ROSS has covered building and energy technologies and electric-utility business issues for more than 25 years. Contact him at [email protected].






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