A Novel Approach Based on Finite-State Machines with Fuzzy Transitions for Nonintrusive Home Appliance Monitoring

Recent studies have highlighted that a significant part of the electrical energy consumption in residential buildings is caused by an improper use of home appliances. The development of low-cost systems for profiling the consumption of electric appliances can play a key role in stimulating the users to adopt adequate policies for energy saving. In this paper, we describe a novel methodology for extracting the power consumption of each appliance deployed in a domestic environment from the aggregate measures collected by a single smart meter. In order to coarsely describe how each type of appliance works, we use finite-state machines (FSMs) based on fuzzy transitions. An ad-hoc disaggregation algorithm exploits a database of these FSMs for, at each meaningful variation in real and reactive aggregate powers, hypothesizing possible configurations of active appliances. This set of configurations is concurrently managed by the algorithm which, whenever requested, outputs the configuration with the highest confidence with respect to the sequence of detected events. We implemented a prototype of a monitoring system based on the proposed methodology and installed it in a real domestic scenario. We discuss an experiment in which 11 appliances were connected to the same circuit and the aggregate power consumption was measured by a smart meter for approximately 12 h. At the end of the experiment, only two possible configurations were outputs from the system, including the correct one.