Imagine you are one of the largest energy utilities in the United States with solar capacity and you are tasked with revolutionizing the way your utility does business. Where do you start?
Three years ago, Kim Wagie, Director Digital Transformation & Continuous Improvement for Arizona Public Service – APS, came across the same challenge – the need for Data Agility in forecasting energy analytics. Kim knew that to disrupt the marketplace and create new revenue streams and value for APS, they needed to better understand three things: 1) consumer behavior, 2) customer’s changing needs, and 3) the impact of distributed energy resources on their aging infrastructure.
“AMI is the most valuable data we have, and we are underutilizing it.”
Kim Wagie, Director Digital Transformation & Continuous Improvement at APS
APS used Innowatts’ Core Analytics to combine their smart meter data with weather data, program participation information, and third-party demographic data, giving APS a 360⁰ view of their customers. The resulting customer insights were valuable information for Kim’s team, as well many other business units across the company, including marketing and public relations, trading, the Distributed Energy Resources division, consumer technology, and the regulatory department.
Taking A Bottoms-up Approach To Energy Management
As the third largest utility in the US for solar capacity, with 7% tied to residential rooftop solar, APS knew the boom in customer rooftop solar installation would not slow down anytime soon. The two-way flow of power added stress to a grid that was not originally designed for this type of power flow. Knowing the impact that distributed energy resources had on their infrastructure and the risk it posed to their portfolio, APS needed predictive intelligence at a disaggregated level. This insight supported their ability to adapt and prepare for future changes in consumer behavior, grid structure, and market changes.
Once APS fully integrated their AMI data with the Innowatts platform, Kim recognized that their previous top-down model performed well, but saw there were opportunities to improve their Mean Absolute Percentage Error (MAPE) using a bottom-up approach. Utilities aim for a 0% MAPE because every percentage reduction could mean millions of dollars in reduced cost and risk. Using Innowatts’ bottom-up approach empowered APS to analyze usage at each designated control area level, by meter, and then further drive analytics based on defined customer segments.
Energy Analytics – Enhancing The Customer’s Lifetime Value
A strong believer that energy forecasting is the foundation of the utility’s transformation, Kim’s team turned to Innowatts to gain full visibility into consumer behavior and align that behavior with meaningful product and service recommendations. Innowatts’ energy forecasting software provided an unparalleled level of granularity, that, when combined with customer demographics, unlocked new revenue streams for APS with the introduction of the Product Suitability feature and a Product Marketplace.
Using meter-level disaggregated load data, APS identified customers with weather-sensitive load and suggested smart thermostats as a way to better manage their usage. For customers with rooftop solar, APS suggested battery back up to ease the transition from distributed energy resources (DER) to grid supply in the evening when solar production waned. Innowatts helped APS identify which meters likely had rooftop solar, even if they did not self-identify as having DER.
Paving The Way For Distributed Energy Resource Management
Distributed energy resources (DER) is a large and significant portion of APS’s generation portfolio. From a grid resilience program point of view, customers need affordable and reliable energy from their utility. In order to deliver, APS’ key responsibilities lie in grid resilience and power quality. A deep understanding of how and when customers consume energy, helped APS on the engineering planning side. Insight into this data meant that if APS could successfully change consumer behavior, they could then prolong large capital investments in their infrastructure.
Validating their data changed the way APS participated in the marketplace. Using the energy analytics tools to perform long-term scenario analysis, APS segmented their market, prepared load forecasts, and evaluated rate-case base changes. These types of analysis meant that internally, before APS makes a fundamental change in the framework or structure, they could use the tool to understand and predict what the impact would be on their business.
Deploying Innowatts’ Product Suitability features enabled APS to: 1) create a new revenue stream, 2) help them identify homes with DER, and 3) significantly improved the efficacy of APS’ marketing investment. Armed with insight into how and when their customers used power, APS is now better equipped to understand their customers and to provide regulators with better recommendations for rate structures for target customer segments that could benefit from government funding.