Consumer Segmentation and Knowledge Extraction from Smart Meter and Survey Data
Many electricity suppliers around the world are deploying smart meters to gather fine-grained spatiotemporal consumption data and to effectively manage the collective demand of their consumer base. In this paper, we introduce a structured framework and a discriminative index that can be used to segment the consumption data along multiple contextual dimensions such as locations, communities, seasons, weather patterns, holidays, etc. The generated segments can enable various higher-level applications such as usagespecific tariff structures, theft detection, consumer-specific demand response programs, etc. Our framework is also able to track consumers' behavioral changes, evaluate different temporal aggregations, and identify main characteristics which define a cluster.
Keywords: smart meters ; consumer segmentation ; clustering ; knowledge extraction ; survey data ; discriminative index ; energy consumption behavior ; clustering consistency index ; smart meter data analytics
Record created on 2014-01-26, modified on 2016-08-09