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Journal Article 2

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2022 1

2019 1

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load disaggregation 2

k-nearest neighbor (k-NN) 1

Kalman filtering 1

Labeled hIgh-Frequency daTaset for Electricity Disaggregation (LIFTED) 1

factorial hidden Markov model (FHMM) 1

multi-stage classification algorithm 1

nonintrusive load monitoring (NILM) 1

online load disaggregation 1

principal component analysis (PCA) 1

voltage-current (V-I) trajectory 1

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State identification of home appliance with transient features in residential buildings

Frontiers in Energy 2022, Volume 16, Issue 1, Pages 130-143 doi: 10.1007/s11708-022-0822-z

Abstract: The use of transient features can achieve fast state inference and it is suitable for online load disaggregationmethod was tested on a high-resolution data set such as Labeled hIgh-Frequency daTaset for Electricity Disaggregation

Keywords： nonintrusive load monitoring (NILM) load disaggregation online load disaggregation Kalman filtering factorial hidden Markov model (FHMM) Labeled hIgh-Frequency daTaset for Electricity Disaggregation

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A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumer

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

Frontiers in Energy 2019, Volume 13, Issue 2, Pages 386-398 doi: 10.1007/s11708-017-0497-z

Abstract: To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodologyNon-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregatesIn this study, load disaggregation is performed through voltage and current waveform, known as the -The novelty of this paper is to establish a systematic approach of load disaggregation through - trajectory-based

Keywords： load disaggregation voltage-current (V-I) trajectory multi-stage classification algorithm