Projects sprout in the United States and overseas, pushing the limits of grid capacity, turbine manufacturers and available sites.
Merchant power plants are emerging en masse to address...
the result? At one plant, the company saw a $250,000 revenue increase, just by ramping up and ramping down more quickly.
Not too shabby during a downturn.
Cinergy, too, is trying to maximize its existing investment in technology, says CTO Gaines. The emphasis has shifted from replacing customer management, billing, and financial systems with more robust applications. Instead, the name of the game, Gaines says, "is to take the best those applications still have to offer, and utilize those, but look at data as the thing you need to manage and change more effectively."
How will he do it? "We were making a tremendous investment, building these applications silo project by project. Now, we think about how that integrates not only on the front-end side, but on the back-end side, via the technology of a data warehouse," Gaines says.
The most important aspect of a data warehouse, from Gaines' perspective, is not the placement of information inside a single silo. Rather, the crucial feature is having a way to index common data elements across the business. Sounds easy, but in reality, it's not. Gaines gives the example of a customer. "In any business [a customer] probably has 20 definitions. When you look at it from a data standpoint, depending on whether you're talking at the customer level, paying their bill, or on a 10-Q, as it relates to the number of customers we have, regulated or unregulated, it has a completely different context. From the data side, though, if you're talking about integrating your business, it has to all fit together."
One upside of Cinergy's data warehouse, Gaines says, is that the company has created a fairly robust set of analytics in reporting that help it make better decisions. For example, Cinergy's traders have more visibility, more timely information, and are able to be more responsive to managing the assets in light of market conditions.
ERCOT also has spent a great deal of time, effort, and money on building a data warehouse. As Shoquist points out, "We have an incredible amount-and very detailed-data about our market. Getting access to that large amount of data is a chore and a challenge."
Shoquist compares ERCOT's information needs to MasterCard, where he worked for a number of years. A data warehouse for ERCOT is one way, Shoquist says, of eliminating seams between ERCOT and its market participants. Instead of sending ERCOT a transaction and duplicating data, he says, market participants can simply use ERCOT's data, and also update ERCOT's data with their own. "Instantaneously, [data is] spread to those who need to know it, throughout the marketplace. It's more of a real-time transaction management flow than a batch transaction flow," Shoquist notes.
The stakes for good data management are pretty high. As Shoquist points out, "If you were to look at ERCOT, and describe what we have, we are in essence like a New York Stock Exchange that happens to have a huge power grid attached to it. We have the reality of the financial transactions, coupled with the reality of turning the lights out