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A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring

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  1. Younghoon Kwak & Jihyun Hwang & Taewon Lee, 2018. "Load Disaggregation via Pattern Recognition: A Feasibility Study of a Novel Method in Residential Building," Energies, MDPI, vol. 11(4), pages 1-22, April.
  2. Qian Wu & Fei Wang, 2019. "Concatenate Convolutional Neural Networks for Non-Intrusive Load Monitoring across Complex Background," Energies, MDPI, vol. 12(8), pages 1-17, April.
  3. Song, Chunhe & Jing, Wei & Zeng, Peng & Yu, Haibin & Rosenberg, Catherine, 2018. "Energy consumption analysis of residential swimming pools for peak load shaving," Applied Energy, Elsevier, vol. 220(C), pages 176-191.
  4. María Isabel Berenguer & Manuel Ruiz Galán, 2022. "An Iterative Algorithm for Approximating the Fixed Point of a Contractive Affine Operator," Mathematics, MDPI, vol. 10(7), pages 1-10, March.
  5. Liu, Yu & Liu, Wei & Shen, Yiwen & Zhao, Xin & Gao, Shan, 2021. "Toward smart energy user: Real time non-intrusive load monitoring with simultaneous switching operations," Applied Energy, Elsevier, vol. 287(C).
  6. 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.
  7. 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.
  8. Shi, Xin & Ming, Hao & Shakkottai, Srinivas & Xie, Le & Yao, Jianguo, 2019. "Nonintrusive load monitoring in residential households with low-resolution data," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
  9. Yan, Lei & Tian, Wei & Han, Jiayu & Li, Zuy, 2022. "Event-driven two-stage solution to non-intrusive load monitoring," Applied Energy, Elsevier, vol. 311(C).
  10. Chao Min & Guoquan Wen & Zhaozhong Yang & Xiaogang Li & Binrui Li, 2019. "Non-Intrusive Load Monitoring System Based on Convolution Neural Network and Adaptive Linear Programming Boosting," Energies, MDPI, vol. 12(15), pages 1-23, July.
  11. Ahir, Rajesh K. & Chakraborty, Basab, 2021. "A meta-analytic approach for determining the success factors for energy conservation," Energy, Elsevier, vol. 230(C).
  12. Liu, Yu & Liu, Congxiao & Ling, Qicheng & Zhao, Xin & Gao, Shan & Huang, Xueliang, 2021. "Toward smart distributed renewable generation via multi-uncertainty featured non-intrusive interactive energy monitoring," Applied Energy, Elsevier, vol. 303(C).
  13. Wang, Shuangyuan & Li, Ran & Evans, Adrian & Li, Furong, 2020. "Regional nonintrusive load monitoring for low voltage substations and distributed energy resources," Applied Energy, Elsevier, vol. 260(C).
  14. Liu, Chao & Akintayo, Adedotun & Jiang, Zhanhong & Henze, Gregor P. & Sarkar, Soumik, 2018. "Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network," Applied Energy, Elsevier, vol. 211(C), pages 1106-1122.
  15. Moreno Jaramillo, Andres F. & Laverty, David M. & Morrow, D. John & Martinez del Rincon, Jesús & Foley, Aoife M., 2021. "Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks," Renewable Energy, Elsevier, vol. 179(C), pages 445-466.
  16. Huijuan Wang & Wenrong Yang & Tingyu Chen & Qingxin Yang, 2019. "An Optimal Load Disaggregation Method Based on Power Consumption Pattern for Low Sampling Data," Sustainability, MDPI, vol. 11(1), pages 1-16, January.
  17. Ce Peng & Guoying Lin & Shaopeng Zhai & Yi Ding & Guangyu He, 2020. "Non-Intrusive Load Monitoring via Deep Learning Based User Model and Appliance Group Model," Energies, MDPI, vol. 13(21), pages 1-19, October.
  18. 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.
  19. Jiang, Zhanhong & Liu, Chao & Akintayo, Adedotun & Henze, Gregor P. & Sarkar, Soumik, 2017. "Energy prediction using spatiotemporal pattern networks," Applied Energy, Elsevier, vol. 206(C), pages 1022-1039.
  20. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Robust event-based non-intrusive appliance recognition using multi-scale wavelet packet tree and ensemble bagging tree," Applied Energy, Elsevier, vol. 267(C).
  21. Hwan Kim & Sungsu Lim, 2021. "Temporal Patternization of Power Signatures for Appliance Classification in NILM," Energies, MDPI, vol. 14(10), pages 1-17, May.
  22. Schmidt, Mischa & Åhlund, Christer, 2018. "Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 742-756.
  23. Tekler, Zeynep Duygu & Low, Raymond & Zhou, Yuren & Yuen, Chau & Blessing, Lucienne & Spanos, Costas, 2020. "Near-real-time plug load identification using low-frequency power data in office spaces: Experiments and applications," Applied Energy, Elsevier, vol. 275(C).
  24. Anthony Faustine & Lucas Pereira, 2020. "Improved Appliance Classification in Non-Intrusive Load Monitoring Using Weighted Recurrence Graph and Convolutional Neural Networks," Energies, MDPI, vol. 13(13), pages 1-15, July.
  25. Welikala, Shirantha & Thelasingha, Neelanga & Akram, Muhammed & Ekanayake, Parakrama B. & Godaliyadda, Roshan I. & Ekanayake, Janaka B., 2019. "Implementation of a robust real-time non-intrusive load monitoring solution," Applied Energy, Elsevier, vol. 238(C), pages 1519-1529.
  26. Sara Tavakoli & Kaveh Khalilpour, 2021. "A Practical Load Disaggregation Approach for Monitoring Industrial Users Demand with Limited Data Availability," Energies, MDPI, vol. 14(16), pages 1-27, August.
  27. Bisaga, Iwona & Puźniak-Holford, Nathan & Grealish, Ashley & Baker-Brian, Christopher & Parikh, Priti, 2017. "Scalable off-grid energy services enabled by IoT: A case study of BBOXX SMART Solar," Energy Policy, Elsevier, vol. 109(C), pages 199-207.
  28. Tomasz Jasiński, 2020. "Modelling the Disaggregated Demand for Electricity in Residential Buildings Using Artificial Neural Networks (Deep Learning Approach)," Energies, MDPI, vol. 13(5), pages 1-16, March.
  29. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction," Applied Energy, Elsevier, vol. 279(C).
  30. Pascal A. Schirmer & Iosif Mporas & Akbar Sheikh-Akbari, 2020. "Energy Disaggregation Using Two-Stage Fusion of Binary Device Detectors," Energies, MDPI, vol. 13(9), pages 1-17, May.
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