TY  - JOUR
T1  - Mining Residential Electricity Consumption Patterns to Generate Tailored Baselines
AU - Kumari, M. Sheeba Santha AU - Shanthi, A.P. AU - Maheswari, V. Uma 
JO  - Asian Journal of Information Technology
VL  - 13
IS  - 7
SP  - 375
EP  - 381
PY  - 2014
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2014.375.381
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2014.375.381
KW  - :Data mining
KW  -pattern recognition
KW  -conceptual clustering
KW  -residential power consumption
KW  -tailored baselines
KW  -tailored baselines
AB  - Residential electric power consumption plays an important 
  role in economical decision making process. It is beneficial to have residential 
  consumers who are better aware of their consumption pattern so that they are 
  more responsible in usage of power. Normally, they rely on their long term bill 
  and do not have any insight into their pattern of consumption which can hinder 
  efforts to reduce electricity consumption. Emergence of smart grid with advanced 
  metering devices and data mining technique facilitates power consumers to perform 
  efficient power management. Behaviour modification initiatives and tailor made 
  suggestions can be generated by examining the consumption patterns, enabling 
  consumers to control load, participate in demand response programs and to help 
  suppliers fix time dependent tariff rates. This study intends to generate typical 
  load patterns of a household highlighting the usage pattern using a Conceptual 
  Hierarchical Clustering Method. A real data set is used for the study.
ER  -