A non-intrusive load monitoring approach for very short-term power predictions in commercial buildings
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DOI: 10.1016/j.apenergy.2021.116860
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- Luan, Wenpeng & Wei, Zun & Liu, Bo & Yu, Yixin, 2022. "Non-intrusive power waveform modeling and identification of air conditioning load," Applied Energy, Elsevier, vol. 324(C).
- Tan Ngoc Dinh & Gokul Sidarth Thirunavukkarasu & Mehdi Seyedmahmoudian & Saad Mekhilef & Alex Stojcevski, 2023. "Energy Consumption Forecasting in Commercial Buildings during the COVID-19 Pandemic: A Multivariate Multilayered Long-Short Term Memory Time-Series Model with Knowledge Injection," Sustainability, MDPI, vol. 15(17), pages 1-18, August.
- Yang, Wangwang & Shi, Jing & Li, Shujian & Song, Zhaofang & Zhang, Zitong & Chen, Zexu, 2022. "A combined deep learning load forecasting model of single household resident user considering multi-time scale electricity consumption behavior," Applied Energy, Elsevier, vol. 307(C).
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Keywords
Non-intrusive load monitoring; Energy disaggregation; Power prediction; Unsupervised learning; Neural networks;All these keywords.
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