TY - JOUR
T1 - Robust energy disaggregation using appliance-specific temporal contextual information
AU - Schirmer, Pascal
AU - Mporas, Iosif
AU - Sheikh-Akbari, Akbar
PY - 2020/2/11
Y1 - 2020/2/11
N2 - An extension of the baseline non-intrusive load monitoring approach for energy disaggregation using temporal contextual information is presented in this paper. In detail, the proposed approach uses a two-stage disaggregation methodology with appliance-specific temporal contextual information in order to capture time-varying power consumption patterns in low-frequency datasets. The proposed methodology was evaluated using datasets of different sampling frequency, number and type of appliances. When employing appliance-specific temporal contextual information, an improvement of 1.5% up to 7.3% was observed. With the two-stage disaggregation architecture and using appliance-specific temporal contextual information, the overall energy disaggregation accuracy was further improved across all evaluated datasets with the maximum observed improvement, in terms of absolute increase of accuracy, being equal to 6.8%, thus resulting in a maximum total energy disaggregation accuracy improvement equal to 10.0%.
AB - An extension of the baseline non-intrusive load monitoring approach for energy disaggregation using temporal contextual information is presented in this paper. In detail, the proposed approach uses a two-stage disaggregation methodology with appliance-specific temporal contextual information in order to capture time-varying power consumption patterns in low-frequency datasets. The proposed methodology was evaluated using datasets of different sampling frequency, number and type of appliances. When employing appliance-specific temporal contextual information, an improvement of 1.5% up to 7.3% was observed. With the two-stage disaggregation architecture and using appliance-specific temporal contextual information, the overall energy disaggregation accuracy was further improved across all evaluated datasets with the maximum observed improvement, in terms of absolute increase of accuracy, being equal to 6.8%, thus resulting in a maximum total energy disaggregation accuracy improvement equal to 10.0%.
KW - Contextual temporal information
KW - Energy disaggregation
KW - Load monitoring
KW - Non-intrusive
KW - Two-stage energy disaggregation
UR - http://www.scopus.com/inward/record.url?scp=85079355966&partnerID=8YFLogxK
U2 - 10.1186/s13634-020-0664-y
DO - 10.1186/s13634-020-0664-y
M3 - Article
SN - 1687-6180
VL - 2020
JO - EURASIP Journal on Advances in Signal Processing
JF - EURASIP Journal on Advances in Signal Processing
IS - 1
M1 - 3
ER -