Convolutional Sequence to Sequence Non-intrusive Load Monitoring

Chen, Kunjin, Wang, Qin, He, Ziyu, Chen, Kunlong, Hu, Jun, He, Jinliang

arXiv.org Machine Learning 

Non-intrusive load monitoring (NILM) refers to the technique of estimating the power demand of a single appliance from the combined demand of multiple appliances in a household measured by a single meter [1]. It is suggested in [2] that electricity consumption feedback that includes appliancespecific breakdown is more likely to promote electricity conservation for residential consumers. Electricity providers can have more detailed and in-depth understanding of their customers and provide better services. Thus, both electricity consumers and electricity providers can benefit from the information provided by accurate disaggregation of wholehome power demands. Comprehensive reviews of various NILM methods can be found in [3, 4].

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