Abstract: 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.
M. Sheeba Santha Kumari, A.P. Shanthi and V. Uma Maheswari, 2014. Mining Residential Electricity Consumption Patterns to Generate Tailored Baselines. Asian Journal of Information Technology, 13: 375-381.