During operation, the system receives a set of input signals containing electrical usage data from a set of smart meters, which gather electrical usage data from customers of the utility system. The system uses the set of input signals and a projection technique to produce projected loadshapes, which are associated with electricity usage in the utility system. Next, the system identifies a closest time period in a database containing recent empirically obtained load-related parameters for the utility system, wherein the load-related parameters in the closest time period are closest to a present set of load-related parameters for the utility system. The system then iteratively adjusts the projected loadshapes based on changes indicated by the load-related parameters in the closest time period until a magnitude of adjustments falls below a threshold. Finally, the system predicts electricity demand for the utility system based on the projected loadshapes.