An Improved Method for Load Taxonomy Using Sample Shifting Technique and Signature Analysis

This paper illustrates an improved method of classification of electrical appliances, particularly for domestic loads, to construct load taxonomy on the basis of their signature analysis. Each electrical load is characterized by its own distinct signature and hence load signature analysis is useful in monitoring the health of the equipment, power quality, in determining individual energy usage etc. type of services. On the other hand, load taxonomy classifies these loads in several clusters on the basis of some features extracted from their signatures. In traditional methods of construction of load taxonomy, different signature patterns based on power metrics, V-I trajectories, Eigen vectors, etc. In this proposed method, with the adoption of sample shifting technique the required number of feature extraction is reduced to a lower value to find out various signature patterns than those are required in traditional load taxonomies. Moreover, a better taxonomy, having well separated groups of loads is achieved with lower number of extracted features.