How SOA could change the way you buy electricity

Researchers at the US Department of Energy's Pacific Northwest National Laboratory (PNNL) in Richmond, Washington, decided to find out, with IBM as a partner.

What if IT could be used to eliminate the US West Coast's notorious rolling blackouts or huge regional power outages like those experienced by the Northeast and Midwest in 2003?

Researchers at the US Department of Energy's Pacific Northwest National Laboratory (PNNL) in Richmond, Washington, decided to find out. With IBM as a partner, they built a demonstration network called GridWise that showed how an event-driven service-oriented architecture (SOA) can be used to build a power marketplace that lets residential and commercial customers change their electricity consumption nearly in real time, based on price and other factors. During the yearlong, Energy Department-sponsored marketplace demonstration, customers spent less money on power, and utilities easily accommodated spikes in demand without affecting service levels.

The marketplace, an SOA application ran on an IBM WebSphere Application Server at PNNL and received data in real time from various Web services about electricity's current wholesale price and most recent closing price, as well as whether those prices were trending up or down. It communicated with specialized, "smart" appliances at participants' sites via IBM-developed middleware built within what IBM calls its event-driven architecture (EDA) framework and running on the WebSphere server. The EDA middleware provided the link between the transaction-oriented marketplace and the more physical world of the controls-based appliances.

"We found that through this system, we could influence people's loads in a very rapid fashion," says Rob Pratt, program manager for the GridWise project. "And that really helps out some of the more difficult tasks in managing fluctuations and potential outages in the power grid." In addition, customers saved an average of 10 percent on their electric bills.

How it worked

GridWise served Washington's Olympic Peninsula, a region that relies primarily on electricity for power and heat. It began in January 2006 with 100 residential customers, one commercial building and one water-pumping station.

For the marketplace trial, customers received new electric meters, as well as thermostats, water heaters and other smart appliances, from Invensys Controls. The meters and appliances communicated their settings every five minutes to a central Invensys gateway at each customer location.

The gateway, in turn, sent signals over a ZigBee-based, wireless-sensor network to the appliances to adjust their settings based on customer-defined temperature preferences. Customers set those preferences -- 72 degrees during the day and 65 degrees at night, for example -- via a Web portal.

They also could set thresholds for raising or lowering their thermostat settings based on the cost of electricity: If the price of electricity rose, some customers were willing to pay the higher cost to keep comfortable, while others decided to adjust their thermostats to a lower setting to save on their bills. "We put customers in control of their energy consumption," Pratt says. "They'd get on their computer to program their thermostat and set their preferences, and they could just set it and forget it."

But the Invensys appliances could not understand pricing and consumer preferences -- information needed to submit bids to the PNNL marketplace -- so the controls-based EDA middleware was critically important. Virtual thermostat and water-heater Java objects in the middleware added the intelligence about pricing and could interpret a user's preset preferences.

"Using event-based programming, we bridged between the control-systems world and the SOA-transaction world," says Ron Ambrosio, manager of Internet-scale control systems at IBM. "It let us build applications that are more control-like."

Via Web services, the virtual thermostats would bid a certain price into the marketplace based on the current temperature in the house, what the user's preferences were, and how responsive they wanted to be to changing prices.

Every five minutes, the marketplace would take those bids and determine a new clearing price for electricity. The new price would then flow out from the SOA marketplace through an event bus to all the virtual devices, kicking off their reaction.

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