TY - GEN
T1 - A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK
AU - Batra, Nipun
AU - Kukunuri, Rithwik
AU - Pandey, Ayush
AU - Malakar, Raktim
AU - Kumar, Rajat
AU - Krystalakos, Odysseas
AU - Zhong, Mingjun
AU - Meira, Paulo
AU - Parson, Oliver
PY - 2019/11/13
Y1 - 2019/11/13
N2 - Non-intrusive load monitoring (NILM) or energy disaggregation involves separating the household energy measured at the aggregate level into constituent appliances. The NILM toolkit (NILMTK) was introduced in 2014 towards making NILM research reproducible. NILMTK has served as the reference library for data set parsers and reference benchmark algorithm implementations. However, few publications presenting algorithmic contributions within the field went on to contribute implementations back to the toolkit. This work presents a demonstration of a new version of NILMTK [2] which has a rewrite of the disaggregation API and a new experiment API which lower the barrier to entry for algorithm developers and simplify the definition of algorithm comparison experiments. This demo also marks the release of NILMTK-contrib: a new repository containing NILMTK-compatible implementations of 3 benchmarks and 9 recent disaggregation algorithms. The demonstration covers an extensive empirical evaluation using a number of publicly available data sets across three important experiment scenarios to showcase the ease of performing reproducible research in NILMTK.
AB - Non-intrusive load monitoring (NILM) or energy disaggregation involves separating the household energy measured at the aggregate level into constituent appliances. The NILM toolkit (NILMTK) was introduced in 2014 towards making NILM research reproducible. NILMTK has served as the reference library for data set parsers and reference benchmark algorithm implementations. However, few publications presenting algorithmic contributions within the field went on to contribute implementations back to the toolkit. This work presents a demonstration of a new version of NILMTK [2] which has a rewrite of the disaggregation API and a new experiment API which lower the barrier to entry for algorithm developers and simplify the definition of algorithm comparison experiments. This demo also marks the release of NILMTK-contrib: a new repository containing NILMTK-compatible implementations of 3 benchmarks and 9 recent disaggregation algorithms. The demonstration covers an extensive empirical evaluation using a number of publicly available data sets across three important experiment scenarios to showcase the ease of performing reproducible research in NILMTK.
KW - Energy disaggregation
KW - Non-intrusive load monitoring
KW - Smart meters
UR - http://www.scopus.com/inward/record.url?scp=85077293639&partnerID=8YFLogxK
U2 - 10.1145/3360322.3360999
DO - 10.1145/3360322.3360999
M3 - Published conference contribution
AN - SCOPUS:85077293639
T3 - BuildSys 2019 - Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
SP - 358
EP - 359
BT - BuildSys 2019 - Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
PB - Association for Computing Machinery, Inc
T2 - 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2019
Y2 - 13 November 2019 through 14 November 2019
ER -
