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Non-Intrusive Load Monitoring for Smart Grids: A Deployment-Oriented Review

https://doi.org/10.2139/ssrn.7214158
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.22876openalex-snapshot
Recent trends of smart nonintrusive load monitoring in buildings: A review, open challenges, and future directions
inferredcites →https://doi.org/10.1007/s12053-014-9306-2openalex-snapshot
Nonintrusive load monitoring (NILM) performance evaluation
inferredcites →https://doi.org/10.1007/s12559-020-09764-yopenalex-snapshot
A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks
inferredcites →https://doi.org/10.1016/j.apenergy.2016.10.040openalex-snapshot
A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1016/j.apenergy.2017.01.050openalex-snapshot
Towards non-intrusive thermal load Monitoring of buildings: BES calibration
inferredcites →https://doi.org/10.1016/j.apenergy.2017.03.010openalex-snapshot
Dynamic time warping based non-intrusive load transient identification
inferredcites →https://doi.org/10.1016/j.apenergy.2017.08.094openalex-snapshot
Non-intrusive load monitoring under residential solar power influx
inferredcites →https://doi.org/10.1016/j.apenergy.2017.08.203openalex-snapshot
Non-intrusive load monitoring by using active and reactive power in additive Factorial Hidden Markov Models
inferredcites →https://doi.org/10.1016/j.apenergy.2019.01.167openalex-snapshot
Implementation of a robust real-time non-intrusive load monitoring solution
inferredcites →https://doi.org/10.1016/j.applthermaleng.2016.07.133openalex-snapshot
Electrical-end-use data from 23 houses sampled each minute for simulating micro-generation systems
inferredcites →https://doi.org/10.1016/j.comnet.2016.11.019openalex-snapshot
Occupancy-aided energy disaggregation
inferredcites →https://doi.org/10.1016/j.dib.2017.11.084openalex-snapshot
Dataset on information strategies for energy conservation: A field experiment in India
inferredcites →https://doi.org/10.1016/j.egypro.2017.07.400openalex-snapshot
The Building Data Genome Project: An open, public data set from non-residential building electrical meters
inferredcites →https://doi.org/10.1016/j.enbuild.2012.02.050openalex-snapshot
Measured end-use electric load profiles for 12 Canadian houses at high temporal resolution
inferredcites →https://doi.org/10.1016/j.enbuild.2015.03.021openalex-snapshot
Time series distance-based methods for non-intrusive load monitoring in residential buildings
inferredcites →https://doi.org/10.1016/j.enbuild.2016.06.050openalex-snapshot
Non-intrusive fault identification of power distribution systems in intelligent buildings based on power-spectrum-based wavelet transform
inferredcites →https://doi.org/10.1016/j.enbuild.2017.06.042openalex-snapshot
Comprehensive feature selection for appliance classification in NILM
inferredcites →https://doi.org/10.1016/j.enbuild.2018.03.074openalex-snapshot
Power disaggregation of combined HVAC loads using supervised machine learning algorithms
inferredcites →https://doi.org/10.1016/j.enbuild.2018.04.049openalex-snapshot
Admittance-based load signature construction for non-intrusive appliance load monitoring
inferredcites →https://doi.org/10.1016/j.enbuild.2018.05.007openalex-snapshot
Linking building energy consumption with occupants’ energy-consuming behaviors in commercial buildings: Non-intrusive occupant load monitoring (NIOLM)
inferredcites →https://doi.org/10.1016/j.enbuild.2018.06.058openalex-snapshot
Interactive visualization for NILM in large buildings using non-negative matrix factorization
inferredcites →https://doi.org/10.1016/j.enbuild.2018.07.060openalex-snapshot
A generative model for non-Intrusive load monitoring in commercial buildings
inferredcites →https://doi.org/10.1016/j.enbuild.2018.11.013openalex-snapshot
A NILM algorithm with enhanced disaggregation scheme under harmonic current vectors
inferredcites →https://doi.org/10.1016/j.enbuild.2019.05.028openalex-snapshot
A hybrid model for appliance classification based on time series features
inferredcites →https://doi.org/10.1016/j.enbuild.2019.06.046openalex-snapshot
MO-NILM: A multi-objective evolutionary algorithm for NILM classification
inferredcites →https://doi.org/10.1016/j.procs.2016.07.111openalex-snapshot
A Survey on Feature Selection
inferredcites →https://doi.org/10.1016/j.procs.2021.02.030openalex-snapshot
Home energy efficiency evaluation based on NILM
inferredcites →https://doi.org/10.1016/j.scs.2020.102411openalex-snapshot
Energy management using non-intrusive load monitoring techniques – State-of-the-art and future research directions
inferredcites →https://doi.org/10.1016/s0378-7788(99)00007-9openalex-snapshot
Using a pattern recognition approach to disaggregate the total electricity consumption in a house into the major end-uses
inferredcites →https://doi.org/10.1049/el.2018.5331openalex-snapshot
Phase noise as power characteristic of individual appliance for non‐intrusive load monitoring
inferredcites →https://doi.org/10.1109/5.192069openalex-snapshot
Nonintrusive appliance load monitoring
inferredcites →https://doi.org/10.1109/access.2018.2871343openalex-snapshot
Improving Event-Based Non-Intrusive Load Monitoring Using Graph Signal Processing
inferredcites →https://doi.org/10.1109/access.2019.2960465openalex-snapshot
Energy Disaggregation of Appliances Consumptions Using HAM Approach
inferredcites →https://doi.org/10.1109/access.2022.3194674openalex-snapshot
Simultaneous Estimation of Behind-the-Meter Solar and Wind Power at the Bulk Supply Point
inferredcites →https://doi.org/10.1109/icassp.2019.8683792openalex-snapshot
Evaluation of Non-intrusive Load Monitoring Algorithms for Appliance-level Anomaly Detection
inferredcites →https://doi.org/10.1109/icbest.2015.7435865openalex-snapshot
OPLD: Towards improved non-intrusive office plug load disaggregation
inferredcites →https://doi.org/10.1109/icrera.2017.8191254openalex-snapshot
Interpolation of intra-hourly electricity consumption and production data
inferredcites →https://doi.org/10.1109/jiot.2019.2909038openalex-snapshot
SSIM—A Deep Learning Approach for Recovering Missing Time Series Sensor Data
inferredcites →https://doi.org/10.1109/jiot.2019.2926815openalex-snapshot
An Efficient and Accurate Nonintrusive Load Monitoring Scheme for Power Consumption
inferredcites →https://doi.org/10.1109/jsen.2014.2379113openalex-snapshot
EMF Signature for Appliance Classification
inferredcites →https://doi.org/10.1109/jsen.2017.2713645openalex-snapshot
Sustainable Homecare Monitoring System by Sensing Electricity Data
inferredcites →https://doi.org/10.1109/jsen.2021.3127322openalex-snapshot
DeepDFML-NILM: A New CNN-Based Architecture for Detection, Feature Extraction and Multi-Label Classification in NILM Signals
inferredcites →https://doi.org/10.1109/jsen.2022.3155883openalex-snapshot
Adaptive Non-Intrusive Load Monitoring Based on Feature Fusion
inferredcites →https://doi.org/10.1109/mim.2020.9153467openalex-snapshot
NILM dashboard: Actionable feedback for condition-based maintenance
inferredcites →https://doi.org/10.1109/sbesc.2018.00045openalex-snapshot
Designing a Novel Dataset for Non-intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/smartgridcomm.2014.7007698openalex-snapshot
GREEND: An energy consumption dataset of households in Italy and Austria
inferredcites →https://doi.org/10.1109/smartgridcomm.2014.7007707openalex-snapshot
A simple model-driven approach to energy disaggregation
inferredcites →https://doi.org/10.1109/smartgridcomm.2017.8340657openalex-snapshot
AMBAL: Realistic load signature generation for load disaggregation performance evaluation
inferredcites →https://doi.org/10.1109/tc.2021.3130402openalex-snapshot
A Decentralized Mechanism Based on Differential Privacy for Privacy-Preserving Computation in Smart Grid
inferredcites →https://doi.org/10.1109/tcc.2021.3051766openalex-snapshot
Computational Cost Analysis and Data-Driven Predictive Modeling of Cloud-Based Online-NILM Algorithm
inferredcites →https://doi.org/10.1109/tce.2011.5735484openalex-snapshot
Nonintrusive appliance load monitoring: Review and outlook
inferredcites →https://doi.org/10.1109/tce.2018.2843292openalex-snapshot
Nonintrusive Load Monitoring Algorithm Using Mixed-Integer Linear Programming
inferredcites →https://doi.org/10.1109/tce.2019.2918922openalex-snapshot
Non-Intrusive Load Monitoring and Classification of Activities of Daily Living Using Residential Smart Meter Data
inferredcites →https://doi.org/10.1109/tce.2021.3129356openalex-snapshot
Appliance-Level Anomaly Detection in Nonintrusive Load Monitoring via Power Consumption-Based Feature Analysis
inferredcites →https://doi.org/10.1109/tce.2021.3135423openalex-snapshot
Identification of Electrical Appliances Using Their Virtual Description and Data Selection for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tce.2023.3236452openalex-snapshot
A Context-Aware Multi-Event Identification Method for Nonintrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tetc.2020.2993177openalex-snapshot
Detecting Activities of Daily Living and Routine Behaviours in Dementia Patients Living Alone Using Smart Meter Load Disaggregation
inferredcites →https://doi.org/10.1109/tia.2013.2283318openalex-snapshot
Power-Spectrum-Based Wavelet Transform for Nonintrusive Demand Monitoring and Load Identification
inferredcites →https://doi.org/10.1109/tia.2016.2533487openalex-snapshot
Feature Extraction-Based Hellinger Distance Algorithm for Nonintrusive Aging Load Identification in Residential Buildings
inferredcites →https://doi.org/10.1109/tia.2021.3128469openalex-snapshot
Feature Selection Method for Nonintrusive Load Monitoring With Balanced Redundancy and Relevancy
inferredcites →https://doi.org/10.1109/tia.2022.3144244openalex-snapshot
Joint Energy Disaggregation of Behind-the-Meter PV and Battery Storage: A Contextually Supervised Source Separation Approach
inferredcites →https://doi.org/10.1109/tii.2014.2361288openalex-snapshot
Nonintrusive Load Monitoring: A Temporal Multilabel Classification Approach
inferredcites →https://doi.org/10.1109/tii.2016.2590359openalex-snapshot
Improving Nonintrusive Load Monitoring Efficiency via a Hybrid Programing Method
inferredcites →https://doi.org/10.1109/tii.2017.2776300openalex-snapshot
Toward Energy-Awareness Smart Building: Discover the Fingerprint of Your Electrical Appliances
inferredcites →https://doi.org/10.1109/tii.2018.2843770openalex-snapshot
NILM Dashboard: A Power System Monitor for Electromechanical Equipment Diagnostics
inferredcites →https://doi.org/10.1109/tii.2019.2916213openalex-snapshot
New Appliance Detection for Nonintrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tii.2019.2955470openalex-snapshot
Semisupervised Multilabel Deep Learning Based Nonintrusive Load Monitoring in Smart Grids
inferredcites →https://doi.org/10.1109/tii.2020.2975810openalex-snapshot
An Appliance Load Disaggregation Scheme Using Automatic State Detection Enabled Enhanced Integer Programming
inferredcites →https://doi.org/10.1109/tii.2020.2983212openalex-snapshot
Personalized Residential Energy Usage Recommendation System Based on Load Monitoring and Collaborative Filtering
inferredcites →https://doi.org/10.1109/tii.2021.3060450openalex-snapshot
Charging Load Pattern Extraction for Residential Electric Vehicles: A Training-Free Nonintrusive Method
inferredcites →https://doi.org/10.1109/tii.2021.3060898openalex-snapshot
An Adaptive Machine Learning Framework for Behind-the-Meter Load/PV Disaggregation
inferredcites →https://doi.org/10.1109/tii.2021.3065934openalex-snapshot
Unsupervised Domain Adaptation for Nonintrusive Load Monitoring Via Adversarial and Joint Adaptation Network
inferredcites →https://doi.org/10.1109/tii.2021.3078186openalex-snapshot
Trimming Feature Extraction and Inference for MCU-Based Edge NILM: A Systematic Approach
inferredcites →https://doi.org/10.1109/tii.2021.3118101openalex-snapshot
Real-Time Estimation Frameworks for Feeder-Level Load Disaggregation and PEVs’ Charging Behavior Characteristics Extraction
inferredcites →https://doi.org/10.1109/tii.2021.3130416openalex-snapshot
An Energy Disaggregation Approach Based on Deep Neural Network and Wavelet Transform
inferredcites →https://doi.org/10.1109/tim.2008.917179openalex-snapshot
Nonintrusive Load Monitoring and Diagnostics in Power Systems
inferredcites →https://doi.org/10.1109/tim.2013.2278596openalex-snapshot
Electrical Signal Source Separation Via Nonnegative Tensor Factorization Using On Site Measurements in a Smart Home
inferredcites →https://doi.org/10.1109/tim.2017.2700987openalex-snapshot
Event-Based Energy Disaggregation Algorithm for Activity Monitoring From a Single-Point Sensor
inferredcites →https://doi.org/10.1109/tim.2020.3035193openalex-snapshot
A New Convolutional Neural Network-Based System for NILM Applications
inferredcites →https://doi.org/10.1109/tim.2021.3095093openalex-snapshot
An Improved Load Feature Extraction Technique for Smart Homes Using Fuzzy-Based NILM
inferredcites →https://doi.org/10.1109/tim.2021.3135321openalex-snapshot
Power Monitoring Beyond Radial Distribution Networks
inferredcites →https://doi.org/10.1109/tnnls.2019.2921952openalex-snapshot
Energy Disaggregation via Deep Temporal Dictionary Learning
inferredcites →https://doi.org/10.1109/tnnls.2020.3042434openalex-snapshot
Spatiotemporal Behind-the-Meter Load and PV Power Forecasting via Deep Graph Dictionary Learning
inferredcites →https://doi.org/10.1109/tnse.2021.3132309openalex-snapshot
A Single-to-Multi Network for Latency-Free Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tpwrd.2009.2033799openalex-snapshot
Load Signature Study—Part I: Basic Concept, Structure, and Methodology
inferredcites →https://doi.org/10.1109/tpwrd.2021.3112287openalex-snapshot
Non-Intrusive Load Monitoring Based on the Graph Least Squares Reconstruction Method
inferredcites →https://doi.org/10.1109/tpwrs.2014.2337872openalex-snapshot
Artificial-Intelligence-Based Methodology for Load Disaggregation at Bulk Supply Point
inferredcites →https://doi.org/10.1109/tpwrs.2017.2660246openalex-snapshot
Non-Intrusive Energy Disaggregation Using Non-Negative Matrix Factorization With Sum-to-k Constraint
inferredcites →https://doi.org/10.1109/tpwrs.2018.2800535openalex-snapshot
Real-Time Energy Disaggregation of a Distribution Feeder's Demand Using Online Learning
inferredcites →https://doi.org/10.1109/tpwrs.2019.2953225openalex-snapshot
Scale- and Context-Aware Convolutional Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2011.2163950openalex-snapshot
Residential Appliances Identification and Monitoring by a Nonintrusive Method
inferredcites →https://doi.org/10.1109/tsg.2013.2271282openalex-snapshot
An Empirical Investigation of V-I Trajectory Based Load Signatures for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2015.2442225openalex-snapshot
Electric Load Classification by Binary Voltage–Current Trajectory Mapping
inferredcites →https://doi.org/10.1109/tsg.2015.2484258openalex-snapshot
Residential Appliance Identification Based on Spectral Information of Low Frequency Smart Meter Measurements
inferredcites →https://doi.org/10.1109/tsg.2016.2532885openalex-snapshot
Non-Intrusive Load Monitoring Using Semi-Supervised Machine Learning and Wavelet Design
inferredcites →https://doi.org/10.1109/tsg.2016.2584581openalex-snapshot
Toward Non-Intrusive Load Monitoring via Multi-Label Classification
inferredcites →https://doi.org/10.1109/tsg.2016.2598872openalex-snapshot
Non-Intrusive Load Disaggregation Using Graph Signal Processing
inferredcites →https://doi.org/10.1109/tsg.2016.2626389openalex-snapshot
A Hierarchical Hidden Markov Model Framework for Home Appliance Modeling
inferredcites →https://doi.org/10.1109/tsg.2017.2666220openalex-snapshot
Deep Sparse Coding for Non–Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2017.2743760openalex-snapshot
Incorporating Appliance Usage Patterns for Non-Intrusive Load Monitoring and Load Forecasting
inferredcites →https://doi.org/10.1109/tsg.2017.2743763openalex-snapshot
Analysis Co-Sparse Coding for Energy Disaggregation
inferredcites →https://doi.org/10.1109/tsg.2018.2815763openalex-snapshot
Simultaneous Detection of Multiple Appliances From Smart-Meter Measurements via Multi-Label Consistent Deep Dictionary Learning and Deep Transform Learning
inferredcites →https://doi.org/10.1109/tsg.2018.2826844openalex-snapshot
A Cloud-Based On-Line Disaggregation Algorithm for Home Appliance Loads
inferredcites →https://doi.org/10.1109/tsg.2018.2865702openalex-snapshot
Residential Household Non-Intrusive Load Monitoring via Graph-Based Multi-Label Semi-Supervised Learning
inferredcites →https://doi.org/10.1109/tsg.2018.2871620openalex-snapshot
Modified Cross-Entropy Method for Classification of Events in NILM Systems
inferredcites →https://doi.org/10.1109/tsg.2018.2886849openalex-snapshot
Frequency Invariant Transformation of Periodic Signals (FIT-PS) for Classification in NILM
inferredcites →https://doi.org/10.1109/tsg.2018.2888581openalex-snapshot
Non-Intrusive Load Monitoring by Voltage–Current Trajectory Enabled Transfer Learning
inferredcites →https://doi.org/10.1109/tsg.2019.2892841openalex-snapshot
Estimation of Target Appliance Electricity Consumption Using Background Filtering
inferredcites →https://doi.org/10.1109/tsg.2019.2906012openalex-snapshot
A Generic Optimisation-Based Approach for Improving Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2019.2909931openalex-snapshot
Non-Intrusive Load Monitoring Using Additive Factorial Approximate Maximum a Posteriori Based on Iterative Fuzzy $c$ -Means
inferredcites →https://doi.org/10.1109/tsg.2019.2918330openalex-snapshot
A Practical Solution for Non-Intrusive Type II Load Monitoring Based on Deep Learning and Post-Processing
inferredcites →https://doi.org/10.1109/tsg.2019.2924862openalex-snapshot
A Hybrid Event Detection Approach for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2019.2938068openalex-snapshot
Transfer Learning for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2019.2938090openalex-snapshot
Non-Intrusive Load Monitoring via Multi-Label Sparse Representation-Based Classification
inferredcites →https://doi.org/10.1109/tsg.2020.2967220openalex-snapshot
Separating Feeder Demand Into Components Using Substation, Feeder, and Smart Meter Measurements
inferredcites →https://doi.org/10.1109/tsg.2020.2974347openalex-snapshot
Context Aware Energy Disaggregation Using Adaptive Bidirectional LSTM Models
inferredcites →https://doi.org/10.1109/tsg.2020.3010621openalex-snapshot
Adaptive Weighted Recurrence Graphs for Appliance Recognition in Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2020.3027491openalex-snapshot
A Microgrid Energy Management System Based on Non-Intrusive Load Monitoring via Multitask Learning
inferredcites →https://doi.org/10.1109/tsg.2020.3038757openalex-snapshot
Privacy Preserving in Non-Intrusive Load Monitoring: A Differential Privacy Perspective
inferredcites →https://doi.org/10.1109/tsg.2020.3047712openalex-snapshot
Fully-Convolutional Denoising Auto-Encoders for NILM in Large Non-Residential Buildings
inferredcites →https://doi.org/10.1109/tsg.2021.3066547openalex-snapshot
Time–Frequency Mask Estimation Based on Deep Neural Network for Flexible Load Disaggregation in Buildings
inferredcites →https://doi.org/10.1109/tsg.2021.3066570openalex-snapshot
Toward Load Identification Based on the Hilbert Transform and Sequence to Sequence Long Short-Term Memory
inferredcites →https://doi.org/10.1109/tsg.2021.3078695openalex-snapshot
TraceGAN: Synthesizing Appliance Power Signatures Using Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/tsg.2021.3082622openalex-snapshot
Generalizability Improvement of Deep Learning-Based Non-Intrusive Load Monitoring System Using Data Augmentation
inferredcites →https://doi.org/10.1109/tsg.2021.3112341openalex-snapshot
Temporal and Spectral Feature Learning With Two-Stream Convolutional Neural Networks for Appliance Recognition in NILM
inferredcites →https://doi.org/10.1109/tsg.2021.3114087openalex-snapshot
Multi-Label Deep Blind Compressed Sensing for Low-Frequency Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2021.3115904openalex-snapshot
A Privacy-Preserving Federated Learning Method for Probabilistic Community-Level Behind-the-Meter Solar Generation Disaggregation
inferredcites →https://doi.org/10.1109/tsg.2021.3115910openalex-snapshot
Deep Domain Adaptation for Non-Intrusive Load Monitoring Based on a Knowledge Transfer Learning Network
inferredcites →https://doi.org/10.1109/tsg.2021.3139395openalex-snapshot
SAMNet: Toward Latency-Free Non-Intrusive Load Monitoring via Multi-Task Deep Learning
inferredcites →https://doi.org/10.1109/tsg.2022.3152147openalex-snapshot
Mixed-Integer Nonlinear Programming for State-Based Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2022.3179440openalex-snapshot
The Balanced Window-Based Load Event Optimal Matching for NILM
inferredcites →https://doi.org/10.1109/tsg.2022.3191908openalex-snapshot
Multilabel Appliance Classification With Weakly Labeled Data for Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/wosspa.2013.6602387openalex-snapshot
Appliance consumption signature database and recognition test protocols
inferredcites →https://doi.org/10.1145/2602044.2602051openalex-snapshot
NILMTK
inferredcites →https://doi.org/10.1145/2674061.2674070openalex-snapshot
An in depth study into using EMI signatures for appliance identification
inferredcites →https://doi.org/10.1145/2750858.2807538openalex-snapshot
Household occupancy monitoring using electricity meters
inferredcites →https://doi.org/10.1145/2821650.2821672openalex-snapshot
Neural NILM
inferredcites →https://doi.org/10.1145/3208903.3208939openalex-snapshot
EMBED
inferredcites →https://doi.org/10.1145/3307772.3328317openalex-snapshot
PRECON
inferredcites →https://doi.org/10.1145/3307772.3331017openalex-snapshot
The NextGen Energy Storage trial in the ACT, Australia
inferredcites →https://doi.org/10.3390/s121216838openalex-snapshot
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
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