Energy Disaggregation of Type I and II Loads by Means of Birch Clustering and Watchdog Timers

Amitay Kligman, Arbel Yaniv*, Yuval Beck

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A non-intrusive load monitoring (NILM) process is intended to allow for the separation of individual appliances from an aggregated energy reading in order to estimate the operation of individual loads. In the past, electricity meters specified only active power readings, for billing purposes, thus limiting NILM capabilities. Recent progress in smart metering technology has introduced cost-effective, household-consumer-grade metering products, which can produce multiple features with high accuracy. In this paper, a new method is proposed for applying a BIRCH (balanced iterative reducing and clustering using hierarchies) algorithm as part of a multi-dimensional load disaggregation solution based on the extraction of multiple features from a smart meter. The method uses low-frequency meter reading and constructs a multi-dimensional feature space with adaption to smart meter parameters and is useful for type I as well as type II loads with the addition of timers. This new method is described as energy disaggregation in NILM by means of multi-dimensional BIRCH clustering (DNB). It is simple, fast, uses raw meter sampling, and does not require preliminary training or powerful hardware. The algorithm is tested using a private dataset and a public dataset.

Original languageEnglish
Article number3027
Issue number7
StatePublished - Apr 2023


  • balanced iterative reducing and clustering using hierarchies (BIRCH)
  • clustering algorithms
  • load-disaggregation
  • non-intrusive load monitoring (NILM)
  • smart grid
  • smart metering


Dive into the research topics of 'Energy Disaggregation of Type I and II Loads by Means of Birch Clustering and Watchdog Timers'. Together they form a unique fingerprint.

Cite this