Data Requirements for Applying Machine Learning to Energy Disaggregation
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- Carrie Armel, K. & Gupta, Abhay & Shrimali, Gireesh & Albert, Adrian, 2013. "Is disaggregation the holy grail of energy efficiency? The case of electricity," Energy Policy, Elsevier, vol. 52(C), pages 213-234.
- Rashid, Haroon & Singh, Pushpendra & Stankovic, Vladimir & Stankovic, Lina, 2019. "Can non-intrusive load monitoring be used for identifying an appliance’s anomalous behaviour?," Applied Energy, Elsevier, vol. 238(C), pages 796-805.
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- 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.
- 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.
- Muhammad Asif Ali Rehmani & Saad Aslam & Shafiqur Rahman Tito & Snjezana Soltic & Pieter Nieuwoudt & Neel Pandey & Mollah Daud Ahmed, 2021. "Power Profile and Thresholding Assisted Multi-Label NILM Classification," Energies, MDPI, vol. 14(22), pages 1-18, November.
- Bartłomiej Gawin & Robert Małkowski & Robert Rink, 2023. "Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?," Energies, MDPI, vol. 16(5), pages 1-26, February.
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Keywords
energy disaggregation; nonintrusive load monitoring (NILM); machine learning; data requirements;All these keywords.
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