NILM in high frequency domain: A critical review on recent trends and practical challenges
Author
Abstract
Suggested Citation
DOI: 10.1016/j.rser.2025.115497
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Dinesh, Chinthaka & Welikala, Shirantha & Liyanage, Yasitha & Ekanayake, Mervyn Parakrama B. & Godaliyadda, Roshan Indika & Ekanayake, Janaka, 2017. "Non-intrusive load monitoring under residential solar power influx," Applied Energy, Elsevier, vol. 205(C), pages 1068-1080.
- Mohamed Aymane Ahajjam & Daniel Bonilla Licea & Chaimaa Essayeh & Mounir Ghogho & Abdellatif Kobbane, 2020. "MORED: A Moroccan Buildings’ Electricity Consumption Dataset," Energies, MDPI, vol. 13(24), pages 1-22, December.
- Douglas Paulo Bertrand Renaux & Fabiana Pottker & Hellen Cristina Ancelmo & André Eugenio Lazzaretti & Carlos Raiumundo Erig Lima & Robson Ribeiro Linhares & Elder Oroski & Lucas da Silva Nolasco & Lu, 2020. "A Dataset for Non-Intrusive Load Monitoring: Design and Implementation," Energies, MDPI, vol. 13(20), pages 1-35, October.
- Krzysztof Dowalla & Piotr Bilski & Robert Łukaszewski & Augustyn Wójcik & Ryszard Kowalik, 2022. "Application of the Time-Domain Signal Analysis for Electrical Appliances Identification in the Non-Intrusive Load Monitoring," Energies, MDPI, vol. 15(9), pages 1-20, May.
- Netzah Calamaro & Moshe Donko & Doron Shmilovitz, 2021. "A Highly Accurate NILM: With an Electro-Spectral Space That Best Fits Algorithm’s National Deployment Requirements," Energies, MDPI, vol. 14(21), pages 1-37, November.
- Gernaat, David E.H.J. & de Boer, Harmen-Sytze & Dammeier, Louise C. & van Vuuren, Detlef P., 2020. "The role of residential rooftop photovoltaic in long-term energy and climate scenarios," Applied Energy, Elsevier, vol. 279(C).
- Patrick Huber & Alberto Calatroni & Andreas Rumsch & Andrew Paice, 2021. "Review on Deep Neural Networks Applied to Low-Frequency NILM," Energies, MDPI, vol. 14(9), pages 1-34, April.
- Antonio Ruano & Alvaro Hernandez & Jesus Ureña & Maria Ruano & Juan Garcia, 2019. "NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review," Energies, MDPI, vol. 12(11), pages 1-29, June.
- Mahfoud Drouaz & Bruno Colicchio & Ali Moukadem & Alain Dieterlen & Djafar Ould-Abdeslam, 2021. "New Time-Frequency Transient Features for Nonintrusive Load Monitoring," Energies, MDPI, vol. 14(5), pages 1-11, March.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Everton Luiz de Aguiar & André Eugenio Lazzaretti & Bruna Machado Mulinari & Daniel Rodrigues Pipa, 2021. "Scattering Transform for Classification in Non-Intrusive Load Monitoring," Energies, MDPI, vol. 14(20), pages 1-20, October.
- İsmail Hakkı Çavdar & Vahit Feryad, 2021. "Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid," Energies, MDPI, vol. 14(15), pages 1-21, July.
- Yini Ni & Yanghong Xia & Zichen Li & Qifan Feng, 2023. "A Non-Intrusive Identification Approach for Residential Photovoltaic Systems Using Transient Features and TCN with Attention Mechanisms," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
- Netzah Calamaro & Moshe Donko & Doron Shmilovitz, 2021. "A Highly Accurate NILM: With an Electro-Spectral Space That Best Fits Algorithm’s National Deployment Requirements," Energies, MDPI, vol. 14(21), pages 1-37, November.
- Mazen Bouchur & Andreas Reinhardt, 2025. "Synergistic Non-Intrusive Load Monitoring: Dual-Model Training and Inference for Improved Load Disaggregation Prediction," Energies, MDPI, vol. 18(3), pages 1-15, January.
- Andreas Reinhardt & Lucas Pereira, 2021. "Special Issue: “Energy Data Analytics for Smart Meter Data”," Energies, MDPI, vol. 14(17), pages 1-3, August.
- Inoussa Laouali & Antonio Ruano & Maria da Graça Ruano & Saad Dosse Bennani & Hakim El Fadili, 2022. "Non-Intrusive Load Monitoring of Household Devices Using a Hybrid Deep Learning Model through Convex Hull-Based Data Selection," Energies, MDPI, vol. 15(3), pages 1-22, February.
- Hao Ma & Juncheng Jia & Xinhao Yang & Weipeng Zhu & Hong Zhang, 2021. "MC-NILM: A Multi-Chain Disaggregation Method for NILM," Energies, MDPI, vol. 14(14), pages 1-14, July.
- Gonzalez-Carreon, Karla M. & García Kerdan, Iván, 2025. "Optimising large-scale solar-based distributed energy generation systems in high-density urban areas: An integrated approach using geospatial and techno-economic modelling," Energy, Elsevier, vol. 327(C).
- A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
- Yan, Lei & Tian, Wei & Wang, Hong & Hao, Xing & Li, Zuyi, 2023. "Robust event detection for residential load disaggregation," Applied Energy, Elsevier, vol. 331(C).
- Fang, Lei & He, Bin, 2023. "A deep learning framework using multi-feature fusion recurrent neural networks for energy consumption forecasting," Applied Energy, Elsevier, vol. 348(C).
- Cristina Puente & Rafael Palacios & Yolanda González-Arechavala & Eugenio Francisco Sánchez-Úbeda, 2020. "Non-Intrusive Load Monitoring (NILM) for Energy Disaggregation Using Soft Computing Techniques," Energies, MDPI, vol. 13(12), pages 1-20, June.
- Krzysztof Dowalla & Piotr Bilski & Robert Łukaszewski & Augustyn Wójcik & Ryszard Kowalik, 2022. "Application of the Time-Domain Signal Analysis for Electrical Appliances Identification in the Non-Intrusive Load Monitoring," Energies, MDPI, vol. 15(9), pages 1-20, May.
- Sun, Xiaoqin & Lin, Yian & Zhu, Ziyang & Li, Jie, 2022. "Optimized design of a distributed photovoltaic system in a building with phase change materials," Applied Energy, Elsevier, vol. 306(PA).
- Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
- Veronica Piccialli & Antonio M. Sudoso, 2021. "Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network," Energies, MDPI, vol. 14(4), pages 1-16, February.
- Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
- Gengsheng He & Yu Huang & Ying Zhang & Yuanzhe Zhu & Yuan Leng & Nan Shang & Jincan Zeng & Zengxin Pu, 2025. "Hybrid Transformer–Convolutional Neural Network Approach for Non-Intrusive Load Analysis in Industrial Processes," Energies, MDPI, vol. 18(10), pages 1-17, May.
- Yichao Xie & Bowen Zhou & Zhenyu Wang & Bo Yang & Liaoyi Ning & Yanhui Zhang, 2023. "Industrial Carbon Footprint (ICF) Calculation Approach Based on Bayesian Cross-Validation Improved Cyclic Stacking," Sustainability, MDPI, vol. 15(19), pages 1-35, September.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:213:y:2025:i:c:s1364032125001704. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.