A novel approach for residential load identification based on dynamic time warping

Abstract

This paper proposes a new approach for load identification using a combination of fast Fourier transform (FFT) and dynamic time warping (DTW) techniques. In this approach, first, the current signals of each load device are measured individually and in various combinations to generate reference signals. FFT is then used to obtain meaningful features from the measured signals, while DTW is employed to classify the loads. This is the first known study to use the DTW algorithm for residential load identification in this structure. The proposed approach is constructed in two ways: supervised (DTW-SUP) and semi-supervised (DTW-SEM). In DTW-SEM, the reference signals for the load combinations are generated by summing the sample measurements of the individual loads, while in DTW-SUP, the actual sample measurements are used. The approach has been tested on six loads, including different load combinations. It has achieved high accuracy levels of over 90% in identifying single loads and load combinations using the error metrics Precision, Recall, and F-score. The proposed approach can potentially facilitate the implementation of energy-saving strategies in residential buildings and improve energy efficiency.