ZigBee-Based Real-Time Energy Disaggregation System Using Factorial Hidden Markov Model

Abstract

Energy consumption data of individual appliances at home can be obtained by nonintrusive appliance load monitoring (NILM) which aims at disaggregating total amount of power consumption into that of each appliance. NILM can be implemented utilizing pattern recognition algorithms, one of which is Factorial Hidden Markov Model (FHMM) that was employed in previous researches. In spite of the known importance of real-time disaggregation system, it has not been actively studied compared to the batch system. This study suggests a prototype of real-time NILM system via ZigBee smart plug and FHMM algorithm.