Wavelet Based Load Models from AMI Data

Abstract

A major challenge of using AMI data in power system analysis is the large size of the data sets. For rapid analysis that addresses historical behavior of systems consisting of a few hundred feeders, all of the AMI load data can be loaded into memory and used in a power flow analysis. However, if a system contains thousands of feeders then the handling of the AMI data in the analysis becomes more challenging. The work here seeks to demonstrate that the information contained in large AMI data sets can be compressed into accurate load models using wavelets. Two types of wavelet based load models are considered, the multi-resolution wavelet load model for each individual customer and the classified wavelet load model for customers that share similar load patterns. The multi-resolution wavelet load model compresses the data, and the classified wavelet load model further compresses the data. The method of grouping customers into classes using the wavelet based classification technique is illustrated.