“For years we have expected the energy transition to be built largely with increased renewable energy production. The reality is our greatest weapon rests with smarter energy,” said Jen Szaro, President and CEO, AESP (Association of Energy Services Professionals). “Bidgely’s milestone is proof that having detailed analysis of real-time usage directly leads to smarter consumption and deployment, creating a cleaner environment for all.”
The Advanced Data Science Driving Efficiency Amplification
Every customer has their own unique DSM value. Understanding how to optimize each customer’s maximum savings potential is the key to achieving targets. Bidgely’s Analytics Workbench tool provides utilities with an in-depth understanding of every household’s unique load fingerprint -– i.e. what appliances are in use, the size and time of their consumption and/or demand, and how customers should be best targeted and incentivized to take savings actions.
Applying AI-powered analytics to meter data empowers utilities to target each customer with programs best suited to achieve behavior change to achieve the energy savings that the grid needs. Using these insights, utilities can meet customers where they are by providing personalized messaging based on that customer’s needs — treating customers as individuals, with individual energy savings and load shift opportunities.
For example, Analytics Workbench reveals whether a customer has an inefficient appliance, such as an AC unit that should be repaired or replaced, or an appliance that is healthy but being used inefficiently, and a smart thermostat could assist. Similarly, Analytics Workbench pinpoints pool pump usage, including both time of use and speed of the pump, enabling utilities to target specific customers with programs to replace single speed units with more efficient variable speed models, and/or run the pump in off-peak hours.
Maximizing efficiency savings also requires extending efficiency programs to all customers – not only those in the highest consuming homes. Using Bidgely’s patented disaggregation technology, Analytics Workbench identifies variables beyond high consumption to create superior treatment groups with the highest propensity to save. Maximum savings is determined by a combination of consumption, appliance usage, energy lifestyle, and behaviors — a customer profile that Bidgely’s advanced data science is better able to define.
The difference between legacy DSM approaches and Bidgely’s AI-informed practical, simple and personally relevant efficiency recommendation approach is significant, with an average 3% energy savings per household. With millions of households, this adds up.
Insights informed by granular household energy use data can empower utilities to make essential and immediate progress toward their ambitious energy efficiency goals.
As Krystal Maxwell, Research Director, Guidehouse asserts, “Machine learning, AI, and smart meter data enable highly targeted, strategic implementation of energy efficiency programs. This approach provides distributed energy resources (DER) integration, grid optimization, and increased energy efficiency to provide relief to a utility’s energy grid, while simultaneously providing bill savings to utility customers.”