FHMM Based Industrial Load Disaggregation
Fan Yang, Bo Liu, Wenpeng Luan, Bochao Zhao, Zishuai Liu, Xiao Xiao, Ruiqi Zhang
Abstract
Non-Intrusive Load Monitoring (NILM) is an efficient way for energy disaggregation, as it can identify and monitor power consumption of downstream appliances or equipment from the aggregated data acquired from a single electricity metering point. There are many researches and applications of NILM in residential load disaggregation, but very few are applied on industrial load so far. This paper studies the industrial load disaggregation via NILM based on on-situ monitoring energy consumption data from one factory. The factorial hidden Markov model (FHMM) is applied for load disaggregation of five industrial equipment in the factory with the active power and reactive power data synchronously sampled at the rate of 1 Hz. This is the first attempt of using FHMM with both active power and reactive power as outputs for modeling industrial load in this field of NILM, and the promising results demonstrate its effectiveness for industrial load disaggregation.