The smart grid is a technology infrastructure that adds intelligent capabilities to the electricity distribution system. When you apply analytics to the smart grid data, you can automate and  improve operations, maintenance, planning and customer satisfaction - among other processes.

As utilities continue to upgrade meters, transformers, and add new sensors and equipment, expectations increase about the benefits that can be derived from the data in the smart grid. From a utility perspective, potential benefits range from managing the grid and equipment more efficiently while also improving customer satisfaction.  From a customer perspective, the smart grid should make using power, regardless of its source (traditional or renewable), easier and possibly less expensive.

From a big picture view, the smart grid is the foundation that will help make the internet of things and the services associated with it work. That's a lot of expectations. However, utilities and other companies are making strides in all of these areas, and advanced analytics is essential for creating new value from the big data being generated and collected by the smart grid.

What strategies can utilities use to realize value? Consider some of these analytics examples that other utilities have had success implementing with smart grid technology:

• Replace spreadsheets to better forecast power supply. This customer built an enterprise system to replace a spreadsheet approach that used limited data.  The upgrade made it possible to use more factors from multiple data sources, including newer sensor data, retail sales, population trends, and daily weather. Now, the utility can also run more forecasting scenarios in a shorter period of time.  Read more about a successful implementation of this strategy.
• Analyze smart grid data to reduce theft and improve on-time payments. One utility we work with established an analytic center of excellence to implement these projects using smart grid technology and analytics. The result? They increased collection efficiency and recovered lost profits by developing predictive models that profiled usage patterns based on smart meter data. Read the case study on page 2 of this solution brief for more details.
• Identify and target energy customers with ideal programs.  When you can better understand customer behavior - and how they react to feedback from the smart grid, you can increase the value your customer base as a whole by creating and promoting targeted programs for customers. Read how several utilities have successfully implemented this strategy here.

Applying analytics to smart grid data is still a new endeavor for most utility companies. More than 70 North American utility executives responded to a survey devised to gauge how utilities are defining, conceptualizing and understanding both big data and analytics. Read a detailed overview of the survey's findings.