|3/2016 - 10|
Spatiotemporal Data Mining for Distribution Load ExpansionARANGO, H. G. , LAMBERT-TORRES, G. , de MORAES, C. H. V. , BORGES DA SILVA, L. E.
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (1,253 KB) | Citation | Downloads: 275 | Views: 1,344|
data mining, intelligent systems, load modeling, power distribution, urban areas
urban(9), power(9), economic(7), torres(6), systems(6), silva(6), economics(6), data(6), spatial(5), mining(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 65 - 72
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03010
Web of Science Accession Number: 000384750000010
SCOPUS ID: 84991087193
The load spatial forecasting is fundamental for the electric energy distribution systems planning. Several methods using different conceptions have been proposed to determine the future configuration of the electric markets. This paper proposes a dynamic model of load expansion, based on concepts of local analysis using ideas and applications from urban poles theory. Thus, the load expansion is simulated in a dynamic way, maintaining a continuous change in the conditions for localization of a new load unit. An algorithm generating a snapshot that represents the distribution system configuration at that instant determines the geometry of the market in a given instant. The proposed dynamic model, based on the urban poles theory, has the capacity for summing up the information from economic variables sets, expressed in terms of interchange flow laws, which are modeled by distance and transportation functions. This supplies the model with the capacity for being used even though the number of available explanatory variables is reduced.
Web of Science® Times Cited: 2 [View]
View record in Web of Science® [View]
View Related Records® [View]
SCOPUS® Times Cited: 2
View record in SCOPUS® [Free preview]
 Modified imperialist competitive optimization to high resolution spatial electric load demand forecasting, Grilo, Marcel Mendonça, de Moraes, Carlos Henrique Valério, Costa, Claudio Inácio de Almeida, Lambert-Torres, Germano, Journal of Intelligent & Fuzzy Systems, ISSN 1064-1246, Issue 5, Volume 35, 2018.
Digital Object Identifier: 10.3233/JIFS-171971 [CrossRef]
 A Behavioral Economics Approach to Residential Electricity Consumption, Siebert, Luciano, Sbicca, Adriana, Aoki, Alexandre, Lambert-Torres, Germano, Energies, ISSN 1996-1073, Issue 6, Volume 10, 2017.
Digital Object Identifier: 10.3390/en10060768 [CrossRef]
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.