Consumer Segmentation: Improving Energy Demand Management through Households Socio-Analytics

Demand-response (DR) and energy savings programs are tailored based on users' electricity consumption patterns, discovered from the smart meter data, but do not comprehensively take into account the socio-demographics, socio-economic, dwelling characteristics and occupant energy consumption behavior. These factors can have a significant influence over electricity consumption within households and can supplement comprehensive understanding of consumer energy consumption behavior when combined with load analysis. This paper proposes a data analytics mechanism that couples socio-demographics, socio-economic, dwelling and occupant behavioral characteristics represented by electricity consumption patterns to derive consumer segmentation for targeted demand-management programs. The results of this paper show that generated segments can enable various applications such as improved load and peak load predictions, consumer specific DR programs, usage-specific tariff plans, theft-detection etc.