Non-Intrusive Signature Extraction for Major Residential Loads

TL;DR

This paper introduces a novel non-intrusive method for extracting individual appliance signatures from total household power demand, enabling better energy management and demand response without extensive training.

Contribution

It proposes a new signature extraction technique utilizing entire operating windows and an automated appliance registration device, reducing the need for prior training.

Findings

Successfully deployed in real houses

Accurately tracks appliances with complex processes

Automates signature database creation

Abstract

The data collected by smart meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances.The results will enable homeowners to make sound decisions on how to save energy and how to participate in demand response programs. This paper presents a new method to breakdown the total power demand measured by a smart meter to those used by individual appliances. A unique feature of the proposed method is that it utilizes diverse signatures associated with the entire operating window of an appliance for identification. As a result, appliances with complicated middle process can be tracked. A novel appliance registration device and scheme is also proposed to automate the creation of appliance signature database and to eliminate the need of massive training before identification. The software and system have been developed and deployed to real houses in order to verify the proposed method.