Towards Automatic Identification of Activity Modes in Electricity Consumption Data for Small and Medium Sized Enterprises
Year: 2014
Type: conference-paper
Abstract: Small and Medium Sized Enterprises (SMEs) have a large share of the total electricity consumption in most countries and the efficiency of energy reduction efforts for SMEs by energy counselors depend on means for automatically identifying which SMEs are good candidates for energy reduction efforts.In this paper we propose a method based on statistics to identify activity modes in electricity consumption data of SMEs coarsegrained smart meter data.The method enables such automatic identification by computing a number of features on smart meter data including autocorrelation features.We also provide initial results for evaluating the method on a data set with smart meter data for 329 SMEs and identify options for further improving the method.Given the identification of the activity modes one can quantify the energy reduction potential of individual SMEs by comparing the load in the different activity modes and the variability of the load.
Authors: Emil Holmegaard, Mikkel Baun Kjærgaard
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2625595834