Utilities are in a constant state of asset capacity and distribution planning—a critical balancing act between having enough energy generation to support demand and optimizing existing grid infrastructure. Utilities must also continually predict future electricity demand, taking into account factors like population growth, weather patterns, and economic trends—a task known as load forecasting.
Although the standard approach to grid planning is a functional model, it’s not necessarily a scalable model—and, it doesn’t account for the mass deployment of DERs underway at homes across the country. For one, non-smart meters only provide utilities with data at an aggregate level. This lacks visibility into behind-the-meter assets, like a customer’s solar, battery storage, and energy-efficient appliances.
Smart meters offer an impressive amount of data, capturing energy consumption in 60-, 30- and sometimes even 15-minute intervals. Data is the foundation for knowledge, so the more data telling utilities about the energy flowing through the grid, the better able they are to evaluate and modify energy efficiency efforts. This in turn enables utilities to also measure with greater accuracy the results of these programs.
Not only does behind-the-meter data allow utilities to increase load forecasting accuracy, but utilities don’t have to depend on extrapolation anymore; they can “disaggregate” this data to gain greater visibility into DERs and appliances from every home under one given circuit, multiple circuits or even all the homes under their jurisdiction.