IDEAS home Printed from https://ideas.repec.org/r/gam/jeners/v12y2019i11p2203-d238540.html

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

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. André Eugenio Lazzaretti & Douglas Paulo Bertrand Renaux & Carlos Raimundo Erig Lima & Bruna Machado Mulinari & Hellen Cristina Ancelmo & Elder Oroski & Fabiana Pöttker & Robson Ribeiro Linhares & Luc, 2020. "A Multi-Agent NILM Architecture for Event Detection and Load Classification," Energies, MDPI, vol. 13(17), pages 1-35, August.
  2. Xi He & Heng Dong & Wanli Yang & Jun Hong, 2022. "A Novel Denoising Auto-Encoder-Based Approach for Non-Intrusive Residential Load Monitoring," Energies, MDPI, vol. 15(6), pages 1-15, March.
  3. 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.
  4. Sarra Houidi & Dominique Fourer & François Auger & Houda Ben Attia Sethom & Laurence Miègeville, 2021. "Comparative Evaluation of Non-Intrusive Load Monitoring Methods Using Relevant Features and Transfer Learning," Energies, MDPI, vol. 14(9), pages 1-28, May.
  5. Georgios Yiasoumas & Lazar Berbakov & Valentina Janev & Alessandro Asmundo & Eneko Olabarrieta & Andrea Vinci & Giovanni Baglietto & George E. Georghiou, 2023. "Key Aspects and Challenges in the Implementation of Energy Communities," Energies, MDPI, vol. 16(12), pages 1-24, June.
  6. Xiao-Yu Zhang & Stefanie Kuenzel & José-Rodrigo Córdoba-Pachón & Chris Watkins, 2020. "Privacy-Functionality Trade-Off: A Privacy-Preserving Multi-Channel Smart Metering System," Energies, MDPI, vol. 13(12), pages 1-30, June.
  7. 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.
  8. Patricia Franco & José M. Martínez & Young-Chon Kim & Mohamed A. Ahmed, 2022. "A Cyber-Physical Approach for Residential Energy Management: Current State and Future Directions," Sustainability, MDPI, vol. 14(8), pages 1-33, April.
  9. Dong, Ze & Zhang, Xiaohu & Cai, Shiyi & Yang, Yuhang & Jiang, Wei & Song, Yaqi & Zhao, Wenqing & Zhang, Dongyang, 2025. "Real-time NILM: A lightweight and low power approach," Energy, Elsevier, vol. 335(C).
  10. Yang, Chao & Liang, Gaoqi & Liu, Jinjie & Liu, Guolong & Yang, Hongming & Zhao, Junhua & Dong, Zhaoyang, 2023. "A non-intrusive carbon emission accounting method for industrial corporations from the perspective of modern power systems," Applied Energy, Elsevier, vol. 350(C).
  11. 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.
  12. Hari Prasad Devarapalli & Venkata Samba Sesha Siva Sarma Dhanikonda & Sitarama Brahmam Gunturi, 2021. "Demand-Side Management for Improvement of the Power Quality in Smart Homes Using Non-Intrusive Identification of Appliance Usage Patterns with the True Power Factor," Energies, MDPI, vol. 14(16), pages 1-19, August.
  13. Jiangang Lu & Ruifeng Zhao & Bo Liu & Zhiwen Yu & Jinjiang Zhang & Zhanqiang Xu, 2023. "An Overview of Non-Intrusive Load Monitoring Based on V-I Trajectory Signature," Energies, MDPI, vol. 16(2), pages 1-15, January.
  14. 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.
  15. Kimia Honari & Sara Rouhani & Nida E. Falak & Yuan Liu & Yunwei Li & Hao Liang & Scott Dick & James Miller, 2023. "Smart Contract Design in Distributed Energy Systems: A Systematic Review," Energies, MDPI, vol. 16(12), pages 1-28, June.
  16. 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.
  17. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
  18. Amitay Kligman & Arbel Yaniv & Yuval Beck, 2023. "Energy Disaggregation of Type I and II Loads by Means of Birch Clustering and Watchdog Timers," Energies, MDPI, vol. 16(7), pages 1-21, March.
  19. Abayomi A. Adebiyi & Mathew Habyarimana, 2025. "Systematic Review of Optimization Methodologies for Smart Home Energy Management Systems," Energies, MDPI, vol. 18(19), pages 1-28, October.
  20. Yan, Zhongzong & Nardello, Matteo & Brunelli, Davide & Wen, He, 2026. "Reproducible non-intrusive load monitoring: A survey of open-source methods and practical challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PA).
  21. 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.
  22. Debnath, Ramit & Bardhan, Ronita & Misra, Ashwin & Hong, Tianzhen & Rozite, Vida & Ramage, Michael H., 2022. "Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models," Energy Policy, Elsevier, vol. 164(C).
  23. Mingzhi Yang & Yue Liu & Quanlong Liu, 2021. "Nonintrusive Residential Electricity Load Decomposition Based on Transfer Learning," Sustainability, MDPI, vol. 13(12), pages 1-11, June.
  24. Pusceddu, Gabriella & Manca, Simone & Massidda, Luca, 2025. "Fine-tuning non-intrusive load monitoring model through user interaction: A practical approach to appliance recognition with limited labeled data," Applied Energy, Elsevier, vol. 391(C).
  25. Hari Prasad Devarapalli & V. S. S. Siva Sarma Dhanikonda & Sitarama Brahmam Gunturi, 2020. "Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion," Energies, MDPI, vol. 13(18), pages 1-15, September.
  26. 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.
  27. Papageorgiou, Petros G. & Christoforidis, Georgios C. & Bouhouras, Aggelos S., 2025. "NILM in high frequency domain: A critical review on recent trends and practical challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 213(C).
  28. Christos Athanasiadis & Dimitrios Doukas & Theofilos Papadopoulos & Antonios Chrysopoulos, 2021. "A Scalable Real-Time Non-Intrusive Load Monitoring System for the Estimation of Household Appliance Power Consumption," Energies, MDPI, vol. 14(3), pages 1-23, February.
  29. Jennifer Günter & Lukas Fabri & Simon Wenninger & Can Kaymakci, 2025. "Developing a Smart Energy Service Canvas," Schmalenbach Journal of Business Research, Springer, vol. 77(1), pages 95-125, March.
  30. 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.
  31. Miltiadis D. Lytras & Kwok Tai Chui, 2019. "The Recent Development of Artificial Intelligence for Smart and Sustainable Energy Systems and Applications," Energies, MDPI, vol. 12(16), pages 1-7, August.
  32. Christian Pfeiffer & Markus Puchegger & Claudia Maier & Ina V. Tomaschitz & Thomas P. Kremsner & Lukas Gnam, 2020. "A Case Study of Socially-Accepted Potentials for the Use of End User Flexibility by Home Energy Management Systems," Sustainability, MDPI, vol. 13(1), pages 1-19, December.
  33. 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.
  34. 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.
  35. 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.
  36. Hariom Dhungana & Francesco Bellotti & Matteo Fresta & Pragya Dhungana & Riccardo Berta, 2025. "Assessing a Measurement-Oriented Data Management Framework in Energy IoT Applications," Energies, MDPI, vol. 18(13), pages 1-23, June.
  37. Yong Gao & Junwei Zhang & Mian Wang & Zhukui Tan & Minhang Liang, 2025. "A Lightweight Load Identification Model Update Method Based on Channel Attention," Energies, MDPI, vol. 18(11), pages 1-20, May.
  38. 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).
  39. Arsalan Ali Mujtaba, Sarmad Rafique, Gul Muhammad Khan, 2024. "An Aggregated Approach Towards NILM on ACS-F2 Using Machine Learning," International Journal of Innovations in Science & Technology, 50sea, vol. 6(5), pages 236-247, May.
  40. Andrea Mariscotti, 2022. "Non-Intrusive Load Monitoring Applied to AC Railways," Energies, MDPI, vol. 15(11), pages 1-27, June.
  41. Karol Bot & Samira Santos & Inoussa Laouali & Antonio Ruano & Maria da Graça Ruano, 2021. "Design of Ensemble Forecasting Models for Home Energy Management Systems," Energies, MDPI, vol. 14(22), pages 1-37, November.
  42. Inoussa Laouali & Isaías Gomes & Maria da Graça Ruano & Saad Dosse Bennani & Hakim El Fadili & Antonio Ruano, 2022. "Energy Disaggregation Using Multi-Objective Genetic Algorithm Designed Neural Networks," Energies, MDPI, vol. 15(23), pages 1-29, November.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.