231 Hits in 6.6 sec

Non-Intrusive Load Monitoring for Residential Appliances with Ultra-Sparse Sample and Real-Time Computation

Minzheng Hu, Shengyu Tao, Hongtao Fan, Xinran Li, Yaojie Sun, Jie Sun
2021 Sensors  
A wavelet decomposition based standard deviation multiple (WDSDM) is first proposed to empower event detection of appliances with complex starting processes.  ...  The results indicate a false detection rate of only one out of sixteen samples and a time consumption of only 0.77 s.  ...  Performance Comparison of Event Detection Algorithms This section compares three different event detection algorithms, including the bilateral CUSUM algorithm, the SDM based event detection and the WDSDM  ... 
doi:10.3390/s21165366 pmid:34450806 pmcid:PMC8400964 fatcat:o2egmmsi3ffdnjsrc26bst7edi

A feature fusion technique for improved non-intrusive load monitoring

Raghunath Reddy, Vishal Garg, Vikram Pudi
2020 Energy Informatics  
Experimental results show that our proposed feature fusion based algorithms are more robust and outperform steady state and transient feature-based algorithms by at least +9% and +15% respectively.  ...  We propose a novel hybrid combination that has the advantage of being low-dimensional and can thus be easily integrated with existing classification models to improve load identification.  ...  Prabhakar, Senior Project Assistant at BSRC, IIIT-H for his help in establishing the NILM data collection setup.  ... 
doi:10.1186/s42162-020-00112-w fatcat:rgltwvbgqrblddsdg44tefpqje

A Survey on Non-Intrusive Load Monitoring Methodies and Techniques for Energy Disaggregation Problem [article]

Anthony Faustine, Nerey Henry Mvungi, Shubi Kaijage, Kisangiri Michael
2017 arXiv   pre-print
This is followed by the review of the state-of-the art NILM algorithms.  ...  Furthermore, we review several performance metrics used by NILM researcher to evaluate NILM algorithms and discuss existing benchmarking framework for direct comparison of the state of the art NILM algorithms  ...  A review on event detection algorithms used in the NILM literature is presented in [14] .  ... 
arXiv:1703.00785v3 fatcat:qw6gps5rjnaj7bauwommnovcfe

A Comprehensive Survey for Non-Intrusive Load Monitoring

2022 Turkish Journal of Electrical Engineering and Computer Sciences  
Different intellegent measurement applications and machine learning algorithms have been proposed for the measurement and control of electrical devices/loads used in buildings.  ...  NILM is a load monitoring method that uses a total power or current signal taken from a single point in residential and commercial buildings.  ...  Therefore, event detection algorithms' performance play a vital role in event based NILM methods. Some miss events or false events worsen NILM method's performance as expected.  ... 
doi:10.55730/1300-0632.3842 fatcat:cxx2snotsjbe5cj3rucbsbrzpy

Appliance Level Energy Characterization of Residential Electricity Demand: Prospects, Challenges and Recommendations

Rehan Liaqat, Intisar Ali Sajjad, Muhammad Waseem, Hassan Haes Alhelou
2021 IEEE Access  
This work will provide a one-stop source of information on ALEC and will open the doors of cooperation among various stakeholders of smart cities to achieve long-term SDGs.  ...  Various solutions for ALEC rely on sensors, smart plugs, smart appliances, smart meters and/or energy disaggregation algorithms but smart meters with built-in energy disaggregation algorithms seem to be  ...  Event detection based NILM, principal component analysis The novel feature based on trajectories used in this paper is proved suitable as it does not overlap among various types of appliances.  ... 
doi:10.1109/access.2021.3123196 fatcat:v6np5putqvcgfnbaagi3weqsdi

Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring [article]

Maria Kaselimi, Eftychios Protopapadakis, Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis
2022 arXiv   pre-print
A lot of publications and extensive research works are performed on energy disaggregation or NILM for the state-of-the-art methods to reach on the desirable performance.  ...  This review narrows the gap between the early immature NILM era and the mature one.  ...  Most common approaches to solve the NILM problem are based on unsupervised event detection in the aggregate signal, whereas supervised classifiers are used to assign known appliances to detected events  ... 
arXiv:2207.02009v1 fatcat:v2vhyovvxvcvrjawgqduabdlb4

Non-Intrusive Load Monitoring of Buildings Using Spectral Clustering

Muzzamil Ghaffar, Shakil R. Sheikh, Noman Naseer, Zia Mohy Ud Din, Hafiz Zia Ur Rehman, Muhammad Naved
2022 Sensors  
This work is a step forward in using graph signal processing for non-intrusive load monitoring (NILM) by proposing two novel techniques: the spectral cluster mean (SC-M) and spectral cluster eigenvector  ...  Therefore, the proposed techniques are suitable candidates for NILM.  ...  This study puts forward two different and novel algorithms based on the spectral clustering classification method, along with a detailed analysis.  ... 
doi:10.3390/s22114036 pmid:35684657 pmcid:PMC9185269 fatcat:xizzzun4effzxllsfn7ienrud4

A Scalable Real-Time Non-Intrusive Load Monitoring System for the Estimation of Household Appliance Power Consumption

Christos Athanasiadis, Dimitrios Doukas, Theofilos Papadopoulos, Antonios Chrysopoulos
2021 Energies  
., an event detection algorithm, a convolutional neural network classifier and a power estimation algorithm.  ...  The scope of the proposed NILM algorithm is to detect the turning-on of a target appliance by processing the measured active power transient response and estimate its consumption in real-time.  ...  Conclusions In this paper, a novel real-time event-based energy disaggregation methodology is introduced.  ... 
doi:10.3390/en14030767 fatcat:uyiizb3xjjenvjnwhslqfmrt7u

Fault Detection and Efficiency Assessment for HVAC Systems Using Non-Intrusive Load Monitoring: A Review

Amir Rafati, Hamid Reza Shaker, Saman Ghahghahzadeh
2022 Energies  
Non-Intrusive Load Monitoring (NILM), which is a software-based tool, has been a popular research area over the last few decades.  ...  to improve or develop NILM-based FDD methods to deal with real-world challenges.  ...  The load disaggregation algorithms rely on two main strategies to identify appliances: event-based and non-event-based approaches.  ... 
doi:10.3390/en15010341 fatcat:25tztg42obfv3h5cbfqyh6fy44

NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review

Antonio Ruano, Alvaro Hernandez, Jesus Ureña, Maria Ruano, Juan Garcia
2019 Energies  
The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes  ...  As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.  ...  Figure 3 presents a general overview of blocks involving such event-based NILM algorithms.  ... 
doi:10.3390/en12112203 fatcat:kvwy37rhkjethenc25i7kmc3ya

Trimming Feature Extraction and Inference for MCU-based Edge NILM: a Systematic Approach

Enrico Tabanelli, Davide Brunelli, Andrea Acquaviva, Luca Benini
2021 IEEE Transactions on Industrial Informatics  
We compare four supervised learning techniques on different classification scenarios and characterize the overall NILM pipeline's implementation on a MCU-based Smart Measurement Node.  ...  State-of-the-Art approaches are based on Machine Learning methods and exploit the fusion of time- and frequency-domain features from current and voltage sensors.  ...  We thus identified the most relevant time-and frequency-domain features in disaggregating load profiles depending on the classification scenarios.  ... 
doi:10.1109/tii.2021.3078186 fatcat:wkf2lj3itjh37paqbejrf5rsga

Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey

Ahmed Zoha, Alexander Gluhak, Muhammad Imran, Sutharshan Rajasegarar
2012 Sensors  
This paper provides a comprehensive overview of NILM system and its associated methods and techniques used for disaggregated energy sensing.  ...  Non-Intrusive Load Monitoring (NILM) is an attractive method for energy disaggregation, as it can discern devices from the aggregated data acquired from a single point of measurement.  ...  EP/I000232/1) under the Digital Economy Programme run by Research Councils UK-A cross council initiative led by EPSRC and contributed to by AHRC, ESRC, and MRC. This research is done during S.  ... 
doi:10.3390/s121216838 pmid:23223081 pmcid:PMC3571813 fatcat:3kfnjwysi5gxpeicygvc73gp4e

The ECO data set and the performance of non-intrusive load monitoring algorithms

Christian Beckel, Wilhelm Kleiminger, Romano Cicchetti, Thorsten Staake, Silvia Santini
2014 Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings - BuildSys '14  
of NILM algorithms; (3) describing the design and implementation of a framework that significantly eases the evaluation of NILM algorithms using different data sets and parameter configurations; (4) demonstrating  ...  This paper contributes to the solution of this problem by: (1) outlining the key dimensions of the design space of NILM algorithms; (2) presenting a novel, comprehensive data set to evaluate the performance  ...  Since each run is performed on a separate Matlab instance, NILM-Eval scales over many experiments (e.g., by running it on a computing cluster).  ... 
doi:10.1145/2674061.2674064 dblp:conf/sensys/BeckelKCSS14 fatcat:gvbn5mfhvzfzfamnyzokyjohfy

A comparative study of low sampling non intrusive load dis-aggregation

Kaustav Basu, Ahmad Hably, Vincent Debusschere, Seddik Bacha, Geert Jan Driven, Andres Ovalle
2016 IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society  
The models are trained for 20 houses in the Netherlands and tested for a period of 4-weeks.  ...  The state of the art applications typically runs once per day and reports the detected appliances.  ...  The main objective of this work is to compare NILM techniques for both 10 second and 15 minutes data.The proposed algorithm at 10-second sampling is a novel event based algorithm which improves the existing  ... 
doi:10.1109/iecon.2016.7793294 dblp:conf/iecon/BasuHDBDO16 fatcat:vcw2l4fr4jeajj7biijqgqm6zu

A Generic Optimisation-based Approach for Improving Non-intrusive Load Monitoring

Kanghang He, Dusan Jakovetic, Bochao Zhao, Vladimir Stankovic, Lina Stankovic, Samuel Cheng
2019 IEEE Transactions on Smart Grid  
Motivated by minimising the latter difference without losing the benefits of existing NILM algorithms, we propose novel post-processing approaches for improving the accuracy of existing NILM.  ...  Most NILM algorithms disaggregate one appliance at a time, remove the estimated appliance contribution from the total load, and then move on to disaggregate the next appliance.  ...  Event-based NILM approaches [25] , [26] , [27] , on the other hand, are based on detecting the event of appliance being switched on or off, and then classifying the extracted features, where each class  ... 
doi:10.1109/tsg.2019.2906012 fatcat:tr7v3frz4bhvtb5367gkysw6mu
« Previous Showing results 1 — 15 out of 231 results