TY - JOUR
T1 - Energy disaggregation based on smart metering data via semi-binary nonnegative matrix factorization
AU - Miyasawa, Ayumu
AU - Fujimoto, Yu
AU - Hayashi, Yasuhiro
N1 - Funding Information:
Part of this work was supported by the Japan Science and Technology Agency , CREST [ JPMJCR15K5 ]. We are deeply grateful to the staff members of Informetis Co., Ltd,. and wish to thank them for providing real data and discussing the evaluation index.
Publisher Copyright:
© 2018
PY - 2019/1/15
Y1 - 2019/1/15
N2 - The information measured by smart electricity meters in households enables consumers to understand the relationship between their behavior and the power consumption. This paper proposes an energy disaggregation method to estimate the individual-appliance power consumption utilizing the total power consumption data collected by smart meters without requiring additional sensors for supporting sustainable demand-side energy management. In addition, in order to enable appliance labeling and highly accurate estimation without submetered data of the target households, the utilization of auxiliary information such as consumer feedback is suggested. This scheme provides users the opportunity to explicitly point out incorrect current disaggregation results so as to improve forthcoming future decomposition accuracy. The accuracy of the proposed energy disaggregation framework is evaluated using real-world power consumption data sets.
AB - The information measured by smart electricity meters in households enables consumers to understand the relationship between their behavior and the power consumption. This paper proposes an energy disaggregation method to estimate the individual-appliance power consumption utilizing the total power consumption data collected by smart meters without requiring additional sensors for supporting sustainable demand-side energy management. In addition, in order to enable appliance labeling and highly accurate estimation without submetered data of the target households, the utilization of auxiliary information such as consumer feedback is suggested. This scheme provides users the opportunity to explicitly point out incorrect current disaggregation results so as to improve forthcoming future decomposition accuracy. The accuracy of the proposed energy disaggregation framework is evaluated using real-world power consumption data sets.
KW - Energy disaggregation
KW - Non-intrusive appliance load monitoring
KW - Non-negative matrix factorization
KW - Smart electricity meters
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U2 - 10.1016/j.enbuild.2018.10.030
DO - 10.1016/j.enbuild.2018.10.030
M3 - Article
AN - SCOPUS:85057469960
SN - 0378-7788
VL - 183
SP - 547
EP - 558
JO - Energy and Buildings
JF - Energy and Buildings
ER -
