A new method for pattern recognition in load profiles to support decision-making in the management of the electric sector

Abstract

This work presents a method for the selection, typification and clustering of load curves (STCL) capable of recognizing consumption patterns in the electricity sector. The algorithm comprises four steps that extract essential features from the load curve of residential users with an emphasis on their seasonal and temporal profile, among others. The method was successfully implemented and tested in the context of an energy efficiency program carried out by the Energy Company of Maranhão (Brazil). This program involved the replacement of refrigerators in low-income consumers’ homes in several towns located within the state of Maranhão (Brazil). The results were compared with a well known time series clustering method already established in the literature, Fuzzy CMeans (FCM). The results reveal the viability of the STCL method in recognizing patterns and in generating conclusions coherent with the reality of the electricity sector. The proposed method is also useful to support decision-making at management level.