For the California Energy Commission (CEC), we are developing dynamically updating electric end-use load shapes for 23 end-uses in the residential sector and up to 12 end-uses in 63 various nonresidential market subsectors, and in 13 distinct forecasting zones. The load profiles are different than traditional load shapes because they dynamically adapt to a number of historical or hypothetical conditions that can be specified for backcasting or forecasting purposes. This flexibility will allow Energy Commission forecasters to adapt load shapes as they perform scenario analysis.

Our approach to the development of dynamic load shape generators is to model anonymized and aggregated customer load profiles provided by Investor Owned Utilities in tools such as R-studio and Energy Plus, and the System Advisor Model.  The Energy Plus models, once calibrated to historical load profiles and conditions, can make predictive assessments of how load profiles may change as a function of specific saturations of energy efficient equipment, controls, building materials, and climatic or weather-related scenarios. Regression models for the industrial sector will consider economic parameters such as sector level employment and gross sector product to adapt load profiles.  The end result is that the load shapes will adapt in harmony with the actual forecasted annual energy usages for a wide variety of forecasting scenarios employed by the California Energy Commission Demand Analysis Office.