Featuring of Electricity Consumption Behavior towards Big-Data Applications
Year: 2018
Type: article
Abstract: There is growing interest in discerning behaviors of electricity users in both the residential and commercial sectors. With the advent of high-resolution time-series power demand data through advanced metering. Large volumes of smart meter data gives opportunity for load serving entities to improve their knowledge on customers electricity consumption behavior via load profiling. This paper implements a novel approach for clustering of electricity consumption behavior dynamics.first for each individual customer symbolic aggregate approximation(SAX) to reduce the scale of the data set,and time based Markov model is applied to model the dynamics of electricity consumption, transforming the large set of load curves to several state transition matrixes. A density-based clustering technique, CFSFDP, is performed to discover the typical dynamics of electricity consumption and segment customers into different groups.
Authors: T. Kavitha, Kessamsetti . Thejaswi, C. Sushama
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3185750634