Dominion Virginia Power: Data and DSM
Analytics help utility achieve customer-related goals
I had an opportunity earlier this week to speak with Brandon Stites, director of energy conservation and advanced metering at Dominion Virginia Power, and he shared insights into how data analytics are serving myriad priorities at the utility.
Stites will serve on a customer analytics panel at the Utility Analytics Week, Sept. 18-20, 2012, in Arlington, Texas, next month. (The event is sponsored and run by Energy Central, parent of Intelligent Utility.)
First, I asked Stites how data analytics served demand side management at Dominion Virginia Power, which admittedly is a sprawling question.
The state of Virginia has set a voluntary goal for a 10 percent reduction in retail power consumption from 2006 levels by 2022—an "aggressive" goal, Stites said—through its Virginia Energy Plan of 2007.
"While it's a voluntary goal, we're doing our part to meet that goal," Stites told me. "So we introduced demand side management programs in 2010 and we've been growing those programs since that time to move towards that goal and give our customers a portfolio of DSM options to help them control their energy consumption."
In 2009 the utility began running a series of demonstration projects to validate the benefits that can be achieved through the deployment of advanced metering infrastructure (AMI), energy efficiency and demand response. Thus far those projects have shown promising results, according to Stites, and Dominion hopes to approach its regulators in Virginia and North Carolina in the near future with plans for full AMI deployment.
In Dominion's demonstrations, energy efficiency and AMI are tied-in to achieve, for instance, conservation voltage reduction (CVR), Stites said. The utility uses premise-level voltage data from interval meters to optimize voltage to the customer, which in the AMI demonstration areas has resulted in average energy savings of approximately 2.5 percent.
"With some distribution system improvements, we think we can get savings that approach 3.5 percent to 4 percent for customers," Stites said. "Conservation voltage reduction is a big part of what we plan to include in our DSM portfolio to meet that 10 percent energy reduction goal. That's where AMI and DSM meet."
Data analytics enable the utility to perform evaluation, measurement and verification (EM&V), which is a critical part of DSM—validating that you're actually achieving what you projected you would achieve, Stites said.
"Certainly as we grow our smart meter program, the interval data we get back from each premise will be helpful in that EM&V exercise," Stites said.
Analysis of historical data also will enable the utility to evaluate its circuits and prioritize those most likely to yield CVR savings. This helps target components of the distribution system where distribution infrastructure improvements could help optimize the CVR program.
"We're also looking to use analytics to improve the algorithms and analytical engine that run our CVR," Stites continued. "We're constantly looking at the lowest voltage points on a circuit and optimizing the voltage control. There are a lot of angles to that, but we're using the inputs from the AMI to optimize the CVR program."
And what is the role of IT architecture "under the hood" that enables data analysis? (Stites spent two years prior to his current role serving as chief architect and IT director at Dominion Virginia Power.)
"AMI feeds data to critical components of that architecture, and it integrates with a lot of other systems in order to make the entire system work," Stites said. "First off, our meter data management system (MDM) is the aggregator of meter data, and that ties into the customer information system (CIS) and our distribution SCADA (supervisory control and data acquisition) system. The SCADA system is actually running the engine and issuing the orders to the substation controls to achieve the proper voltage in the CVR program. All these systems are married together to achieve CVR."
The outputs of these integrated systems can serve utility personnel who need insights. Data from these systems also help "energy advisors"—formerly "customer service representatives"— assist customers with questions on their energy use and their bill, provide energy saving steps and explain rate options. The data can also provide customers with outage notification and restoration estimates to help them make decisions for their own benefit.
Teasing insights out of data is as old as the hills, but in the modern utility context, precisely how that is implemented, lessons learned along the way and best practices are worth their weight in gold. You'll be hearing more from speakers slated for Utility Analytics Week, but if you'd like to share specific uses at your utility, feel free to get in touch.
Intelligent Utility Daily