Return
A NILM algorithm with enhanced disaggregation scheme under harmonic current vectors
DOI:10.1016/j.enbuild.2018.11.013.png)
Abstract
En 中文
In the smart home context, one of the features that most users would desire is the knowledge of the operation of each electrical appliance without the need to install expensive smart plugs or measuring equipment at each outlet-appliance. The Non-Intrusive Load Monitoring (NILM) idea is an alternative method where only one meter is utilized. However, the accuracy and simplicity of NILM approaches are still under improvement and evolvement. In this paper we propose the development of load signatures by a limited number of harmonic current vectors. The rationale behind this is that simultaneously operating appliances may have opposite or displaced harmonic current vectors, which means that using only current amplitudes as load signatures will not result in reliable identification. Three alternative formations are examined aiming to highlight the contribution of the harmonic current phase angles to the robustness of the load signatures. The first formation considers only the current amplitude, the second takes into account the phase angles in the form of vector projection on the x-axis, and the third is based on harmonic current vectors. The respective disaggregation schemes are also proposed considering either amplitude summations or vector aggregations, in order to examine the correct appliance combination that matches the actual operating one. Measurements have been performed in a typical residential installation considering both stand-alone operation of appliances and scenarios with appliance combinations. The results indicate that disaggregation performance is significantly improved when relying on harmonic current vectors in respect to the case with only current amplitudes, which makes the methodology potentially suitable for the new smart meters that are expected to be widely installed. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
NILM
Load signatures
Load identification
Odd harmonic currents
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
1.6W
Citations:
6.8W
Organization
Cited Papers
Occupancy based household energy disaggregation using ultra wideband radar and electrical signature profiles
ENERGY AND BUILDINGS
IF7.1
Modelling the energy demand projection of the building sector in Greece in the 21st century
ENERGY AND BUILDINGS
IF7.1
Suitability analysis of modeling and assessment approaches in energy efficiency in buildings
ENERGY AND BUILDINGS
IF7.1
Denoising autoencoders for Non-Intrusive Load Monitoring: Improvements and comparative evaluation
ENERGY AND BUILDINGS
IF7.1
On the Bayesian optimization and robustness of event detection methods in NILM
ENERGY AND BUILDINGS
IF7.1

