Abstract: A method of adaptive persistence forecasting includes receiving historical load values for a site with at least one component that consumes energy; receiving historical temperature values corresponding to dates of the historical load values; evaluating the historical load values and the historical temperature values to determine a correlation coefficient; determining that there exists at least a threshold correlation between a load activity and temperature for the historical load values and the historical temperature values based on the correlation coefficient; in response to determining that there exists at least the threshold correlation, normalizing the historical load values based on a set temperature; and applying an adaptive seasonal persistence model to the normalized historical load values to output a forecast for use in controlling energy resources at the site.

Abstract: A multi-layer architecture for control of distributed energy resources (DER) includes a forecasting and optimization system and one or more site-level controllers. The forecasting and optimization system generates predictions of optimal set points and communicate the optimal set points to a site-level controller. The site-level controller includes stored instructions that, when executed, direct the site-level controller to perform a boundary check and a real-time static economic dispatch, which can include steps of receiving optimal set points from the forecasting and optimization system; comparing received optimal set points with local conditions; outputting dispatch commands for DER control according to the optimal set points when the optimal set points are within appropriate limits with respect to the local conditions; and when the optimal set points exceed the appropriate limits, generating adjusted dispatch commands and outputting the adjusted dispatch commands for the DER control.