TY - GEN
T1 - Extraction of basic patterns of household energy consumption
AU - Shen, Haoyang
AU - Hino, Hideitsu
AU - Murata, Noboru
AU - Wakao, Shinji
PY - 2011
Y1 - 2011
N2 - Solar power, wind power, and co-generation (combined heat and power) systems are possible candidate for household power generation. These systems have their advantages and disadvantages. To propose the optimal combination of the power generation systems, the extraction of basic patterns of energy consumption of the house is required. In this study, energy consumption patterns are modeled by mixtures of Gaussian distributions. Then, using the symmetrized Kullback-Leibler divergence as a distance measure of the distributions, the basic pattern of energy consumption is extracted by means of hierarchical clustering. By an experiment using the Annex 42 dataset, it is shown that the proposed method is able to extract typical energy consumption patterns.
AB - Solar power, wind power, and co-generation (combined heat and power) systems are possible candidate for household power generation. These systems have their advantages and disadvantages. To propose the optimal combination of the power generation systems, the extraction of basic patterns of energy consumption of the house is required. In this study, energy consumption patterns are modeled by mixtures of Gaussian distributions. Then, using the symmetrized Kullback-Leibler divergence as a distance measure of the distributions, the basic pattern of energy consumption is extracted by means of hierarchical clustering. By an experiment using the Annex 42 dataset, it is shown that the proposed method is able to extract typical energy consumption patterns.
KW - Gaussian mixture model
KW - KL-divergence
KW - energy consumption pattern
KW - hierarchical clustering
UR - http://www.scopus.com/inward/record.url?scp=84857890836&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857890836&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2011.68
DO - 10.1109/ICMLA.2011.68
M3 - Conference contribution
AN - SCOPUS:84857890836
SN - 9780769546070
T3 - Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
SP - 275
EP - 280
BT - Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
T2 - 10th International Conference on Machine Learning and Applications, ICMLA 2011
Y2 - 18 December 2011 through 21 December 2011
ER -