Electric appliance type detection: Approach for estimating residential energy consumption

Abstract

Non-intrusive appliance load monitoring (NIALM) systems are essential to assess real-time energy consumption and provide accurate analysis of the area, device and use. By dividing the information obtained from the total consumption of electricity into individual devices, it may raise clients' understanding of the energy consumed by the house, develops the economic behavior of energy and provides a general energy oversight for residential buildings. NIALM systems are aimed to reduce our energy expenses while increasing our comfort. It can detect which devices are used by signaling the individual energy consumed by each. This may indicate behaviors, such as routine hours when no one is at home, or embarrassing or illegal behavior of residents. To solve this problem, several studies propose new monitoring strategies to reduce the waste of energy in buildings, but they present a significant computation time and a complexity of algorithms. In addition, they ignore the problem of energy estimation. This article proposes an NIALM approach based on elementary loads detection and device types classification. It shows the accuracy of the event classification for each device as well as the correctly assigned energies.