Characterization and Classification of Daily Electricity Consumption Profiles: Shape Factors and k-Means Clustering Technique

Mora Alvarez Milton, Contreras Ortiz Pedro, Serrano Guerrero Xavier, Escrivá Escriva Guillermo

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

This paper exposes a method to classify the electric consumption profiles of different types of consumers, based on patterns given. The direct characteristics method is used in this paper, this method is also known as shape factors deduction (SFs) to easily define consumption profiles by using the load patterns resulting from measurements in the time domain, considering weekdays and time ranges. After the characterization of load profiles, k-means clustering technique is applied to SFs. The SFs are segmented in such a way that, in each group similar SFs are gathered. The characterization and classification of electric profiles has important applications, such as the application of specific tariffs according the consumer type, determination of optimal location of generation resources in electrical distribution systems, detection of anomalies in transmission and distribution of electricity or classify geographical areas according to electricity consumption and perform an optimum balance of feeders in electrical substations.

Original languageEnglish
Article number08004
JournalE3S Web of Conferences
Volume64
DOIs
StatePublished - 27 Nov 2018
Event3rd International Conference on Power and Renewable Energy, ICPRE 2018 - Berlin, Germany
Duration: 21 Sep 201824 Sep 2018

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