This post was originally published on Tendril’s website. Tendril is now Uplight.
A little over 5 months ago Tendril acquired EEme. Their ability to detect which household appliances are being used from a single electric meter’s data is a game changer for utilities, making it a perfect addition to the Tendril Analytics platform. It’s just one example of how two innovative technologies work better together, and we’re excited to share initial results.
There’s no question that EV adoption is growing with a predicted 18.7 million EVs on U.S. roads by 2030. With each new EV comes new demand for electricity. In response, many utilities are encouraging EV owners to charge their vehicles during non-peak hours via TOU rates and other incentives. But how do they identify EV owners to begin with? Because without knowing who EV owners are, it’s almost impossible to message to them.
Tendril’s advanced analytics platform, combined with cutting-edge disaggregation technology, leverages AMI data to identify EV owners based on unique electric load and time-of-use characteristics. To supercharge EEme’s detection tech, we retooled the model to also leverage Tendril’s nationwide socioeconomic and building stock data catalog. For example, if a home looks like it might have an EV, but is located in a large multi-family building, we can identify that household as having a low likelihood of EV ownership. This allows us to minimize false-positives far better than other load-only disaggregation techniques on the market.
Once a utility identifies a customer with an EV, they can then deliver a targeted, personalized offer for a time-of-use rate and a recommendation to charge during lower-cost off-peak hours. This messaging is delivered over their channel of choice––such as a Home Energy Report, their MyAccount portal, email, and others. Best of all, customers can see a view of all of their energy usage and confirm that they have an EV, creating a smart feedback loop.
One large utility in the southeast is launching Tendril’s EV detection functionality this summer, adding personalized recommendations to their HERs. We’ve identified more than 20,000 vehicles in the utility’s territory, and that number is growing rapidly. These customers will receive more relevant insights – ensuring all future communication is catered to their profile and nurtures them, rather than shaming them for increased electricity usage. This type of precision messaging has been well-received, resulting in measurable increases in customer engagement and satisfaction.
And EV detection can also help utilities plan for the future. By knowing how many EVs there are and where they are located, utilities can plan for new charging stations and power needs as they better understand the market. Using enrichment data from third-party sources, we can also predict who is a good candidate for an EV, project regional adoption, and establish where tomorrow’s charging stations will need to be to best meet consumers’ needs.
Best of all, current Tendril clients can see immediate benefits from these platform enhancements. EV detection is now available for all Home Energy Analytics customers with AMI data, along with load profile characteristics and base load disaggregation as well.
EV detection is just one use case that we are exploring with these new capabilities. Advanced disaggregation technology enables us to inject new insights across the entire Tendril product portfolio. Stay tuned for more updates from our work with AMI-based device detection and disaggregation and contact us to learn more!