Classification of Electrical Home Appliances Based on Harmonic Analysis Using ANN

This paper proposes the study of different electrical parameters to identify the demand characteristics of several electrical home appliances. Voltage and current signals of various loads are collected with respect to time using Digital Storage Oscilloscope (DSO) connected with computer. Significant parameters of the loads containing different harmonics are calculated using Fourier Series Analysis (FSA). These parameters are then used to characterize the loads. The different electrical load identification models are prepared by processing these parameters with the implementation of Backpropagation Artificial Neural Network (BP-ANN). This identification of loads will help the utility to properly manage the usage of the energy by putting Time of Use tariff (TOU) for the electrical home appliances. Thus, a better demand-side management of electrical energy can be obtained.