Residential NMEC Back-Casting Assessment

Cloud-based software incorporates historical customer energy usage and demand data, in any interval available (i.e., bi-monthly, monthly, hourly or sub-hourly), and combines this with weather data, to create predictive models of weather-normalized energy usage for every premise. These models can then be used for multiple purposes, ranging from estimating savings from DSM programs to identifying savings potential in constrained load pockets to monitoring possible high bill instances for customers. The evaluation will determine the effectiveness of the project platform and explore its potential to provide insight into the performance of both programs, using hourly interval usage data from program participants and a non-participant control group. Analysis will be further informed by other available information streams, such as work papers, impact evaluation documents, and program tracking data.