This past week, we gave you a sneak peek of our forthcoming Utility Analytics Institute database with a case study on customer analytics. And like the movie trailers that never seem to end, we thought we’d give you another preview of our database work. However, this time we’re changing it up to focus on the grid side of analytics.
If you have a great story about the analytics work you've done at your utility -- or know a client who has done some great work -- we'd love to hear from you. Interested in accessing these stories? Just let us know, and we'll be happy to get you more information about the database.
Also, if you can’t get enough of stories like the one below, I’d encourage you to participate in our newly launched Institute working groups. These groups will give you the opportunity to hear stories from other utilities about their analytics efforts, as well as engage in real-time with them through phone calls and online collaboration. We are forming groups right now around key analytics topics, including meter data analytics, customer marketing and segmentation, analytics personnel, data quality and integration, and asset optimization. If you’d like more information about these groups, please don’t hesitate to contact me.
Alrighty then, enough of my digressions, let’s get on to the good stuff.
Case study background and introduction
This regulated utility serves 30,000 square miles in the Midwest U.S. As it continues its advanced metering infrastructure (AMI) rollout in, the utility is now embarking on two efforts tied to grid optimization that incorporate analytics: volt/VAR optimization (VVO) and conservation voltage reduction (CVR).
The company’s goal for CVR is to reduce real power demand on its system enough to avoid adding new peak capacity. In order to achieve this goal, the utility plans to deploy CVR on 400 circuits for a total demand reduction of 75 MW by 2017. The process is underway, and the utility is on track to achieve its goal of 52 circuits completed and 8 MW of load reduction by the end of summer 2012. Results vary circuit to circuit, with some circuits achieving five to six percent demand reductions while others achieve almost none, with average reductions of around two percent of demand.
The utility has a compelling business case for its VVO and CVR initiatives. This is evidenced by the greater than $280M 15-year net present value the utility has estimated for using CVR to avoid the addition of new peak generation capacity. The company is on track to achieve this goal, and expects to have more than 10 percent of its 75 MW of targeted real power demand reduction in place by the end of summer 2012. The amount of reduction the utility is achieving on each of the upgraded circuits is consistent with its original estimates, in the range of two percent of demand on average, and ranging from no improvement up to five to six percent on a single circuit.
The utility’s experience is proving out the feasibility of the approach as well as the idea that improved efficiency can be profitable for utilities. Even greater efficiency improvements should be possible once the utility is able to integrate its AMI data with its SCADA system to provide feedback on voltage levels directly from meters on the circuits. This will enable the company to more finely tune voltage levels and get more demand reduction out of its investment.
Overall, the utility views the initiatives as great successes to-date, and feels it is just scratching the surface of the potential provided by analytics used for grid optimization. The ability to better analyze the benefits of automated switching, carry out what-if analysis for operators in the distribution management system (DMS), optimizing switch order, and other capabilities are expected to emerge from the increased use of analytics and greater access to data about grid characteristics and its performance, all of which could bring great benefits to the utility.
The primary business process impact of the utility’s VVO and CVR initiatives has occurred in the control room running VVO, as it has to track which circuits have VVO and CVR capabilities, track whether one of those processes or both is running at any given moment, set the parameters that determine how they are run, carry out manual checks of voltage at bellwether meters through AMI, and carry out other tasks associated with the processes. It also impacts maintenance operations. For example, the company has historically carried out maintenance and repairs on variable capacitor banks once a year in the spring. But now those banks must be kept running, so the company had to create a process to repair them immediately when they fail.
Additionally, in order to effectively manage its expanded communications and control infrastructure related to its AMI and distribution automation activities, the company has reorganized part of its IT group, forming a new group called real-time operations in IT. This group manages the utility’s DMS, providing on-site IT staff support and reducing the barriers between traditionally siloed IT and business groups.
The utility’s network operating center (NOC) was reorganized as the integrated operating center (IOC), which now operates a company-wide communications network incorporating microwave, WiMAX, AMI, and mesh radio in addition to the corporate WAN traditionally managed by the NOC. The IOC is located next to the utility’s distribution control center, so that the two groups can coordinate efforts to ensure the communications network and the distribution system are operating effectively together.
These changes were not required to implement VVO or CVR, but they make the implementation easier and faster by improving coordination between the communications and distribution control sides of the utility. Both of these groups are critical to the successful achievement of the goals the utility is trying to achieve through its VVO and CVR initiatives.
The utility has a corporate level strategic objective to build analytical strength around information gathered from new and existing technologies, customer databases and other sources. This information can be used to improve the customer experience, reduce the company’s costs and improve system reliability, among other benefits.
The reorganization of the IT group and the closer relationship between IT and operations as discussed above are part of a comprehensive strategy that supports initiatives related to analytics and grid optimization. VVO and CVR are great examples of initiatives that benefit from strong links between IT and operations, as both initiatives consume technical information about distribution circuits collected through communications infrastructure managed by the IT group, and use that information to take action that improves efficiency and lowers costs of distribution networks managed by the operations group.
At a more detailed level, the demand reduction associated with CVR is intended to allow the utility to avoid building new generation capacity, which results in direct savings for the utility. The company has calculated a 15-year net present value of $287M for the avoided generation costs.
Another component of the utility’s strategy as it relates to analytics and grid optimization is that early initiatives both provide information that helps the utility identify new opportunities for improvements, and provide the capabilities required to carry out those new improvements. For example, both the AMI deployment and the VVO efforts laid the foundations for CVR, as CVR relies on voltage data from AMI and achieves higher savings through VVO. As additional data is made available from the distribution system, and the system becomes more controllable and reliable, the company expects additional opportunities for improvements to materialize.
Internally, the VVO and CVR efforts role up under the director of grid intelligence, whose team for these initiatives includes a technical project manager and roughly six full-time equivalents of engineers. The utility has over 100 employees supporting its smart grid initiatives, some of which enable or enhance VVO and CVR as described above.
So that's a taste of our forthcoming utility analytics project database. If you'd like to learn more about the database and how to get involved, please don't hesitate to reach out to me at email@example.com.
Thanks for reading!
H. Christine Richards is the director of knowledge services for the Utility Analytics Institute, a division of Energy Central. You may reach her at firstname.lastname@example.org.