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JCR Impact Factor: 0.459
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 644266260
doi: 10.4316/AECE


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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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LATEST NEWS

2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

2015-Dec-04
Starting with Issue 2/2016, the article processing charge is 300 EUR for each article accepted for publication. The charge of 25 EUR per page for papers over 8 pages will not be changed. Details are available in the For authors section.

2015-Jun-10
Thomson Reuters published the Journal Citations Report for 2014. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.529, and the JCR 5-Year Impact Factor is 0.476.

2015-Feb-09
Starting on the 9th of February 2015, we require all authors to identify themselves, when a submission is made, by entering their SCOPUS Author IDs, instead of the organizations, when available. This information will let us better know the publishing history of the authors and better assign the reviewers on different topics.

2015-Feb-08
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  1/2009 - 11

Clustering Techniques in Load Profile Analysis for Distribution Stations

BOBRIC, E. C., CARTINA, G., GRIGORAS, G.
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (501 KB) | Citation | Downloads: 930 | Views: 4,282

Author keywords
load profile, clustering techniques, data flow analysis, power consumption, distribution station

References keywords
power(5), load(5), clustering(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-02-03
Volume 9, Issue 1, Year 2009, On page(s): 63 - 66
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.01011
Web of Science Accession Number: 000264815300011
SCOPUS ID: 67749137135

Abstract
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Full text preview
The demand characteristic is the most important one in analyzing customer information. In a distribution network, there is in any moment certain degree of uncertainty about busses loads, and consequently, about load level of network, busses voltage level, and power losses. Therefore, it is very important to estimate first of all the load profiles of buses, using available data (measurements effectuated in distribution stations). The results obtained for various distribution stations demonstrate the effectiveness of the present method in overcoming the difficulties encountered in optimal planning and operation of distribution networks.


References | Cited By  «-- Click to see who has cited this paper

[1] Load profiles and their use in electricity settlement, Electricity Association, Publisher UKERC, 1997

[2] "Handbook of Applied Multivariate Statistics and Mathematical Modelling", Edited by: Howard E.A. Tinsley and Steven D. Brown ISBN: 978-0-12-691360-6 [PermaLink]

[3] Gh. Cartina, Gh. Grigoras., E.C. Bobric, "Clustering Techniques in Load Analyse", Proc. of the International Power Systems Conference, PSC'05, 2005, Timisoara, Romania, pp. 123-130

[4] R.F. Chang, C.N. Lu, "Load profiling and its applications in power market", Power Engineering Society General Meeting, 2003, IEEE Volume 2, 13-17 July 2003,
[CrossRef] [Web of Science Record]


[5] C. Nitu, A. S. Dobrescu, "The Role of Weather Indicators in Energy Consumption", Advances in Electrical and Computer Engineering, Suceava, Romania, ISSN 1582-7445, No 1/2008, volume 8, pp. 17-20
[CrossRef] [Full Text] [SCOPUS Times Cited 2]


[6] JMP Statistics and Graphics Guide: Version 3, SAS Institute Inc., Cary, NC, USA, 1999

[7] A.K. Jain, M.N. Murty, P.J. Flynn, Data Clustering: A Rewiew, ACM Computing Serveys, 31, 264-323, 1999
[CrossRef] [Web of Science Times Cited 3919] [SCOPUS Times Cited 6281]


[8] Clustering: An Introduction, Available: http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html

[9] Gh. Cartina, Gh. Grigoras, E.C. Bobric, "Clustering Techniques in Fuzzy Modeling. Power Systems Applications", Casa de Editura VENUS, Iasi, 2005

[10] P.E. Sinioros, C. Filote, A. Graur, M.G. Ioannides, "A New Real Time Method of the Instantaneous Active and Reactive Power Calculus", Advances in Electrical and Computer Engineering, Suceava, Romania ISSN 1582-7445, No. 1/2001, volume 1 (8), pp. 5-10

[11] M. Gavrilas, V.C. Sfintes, M.N. Filimon, "Identifying typical load profiles using neural-fuzzy models", 16th IEEE/PES Transmission and Distribution Conf. and Exposition, 2001, Atlanta, pp. 421-426
[CrossRef]


[12] M. Gavrilas, Gh. Cartina, Gh. Grigoras, O. Ivanov, "Modelarea sarcinilor din retelele electrice", Editura PIM, Iasi, 2006

[13] D. Gerbec, S. Gasperic, and F. Gubina, "Comparison of Different Classification Methods for the Consumers' Load Profile Determination", 17th International Conference on Electricity Distribution, CIRED, Barcelona, vol. Session 6, 2003.



References Weight

Web of Science® Citations for all references: 3,919 TCR
SCOPUS® Citations for all references: 6,283 TCR

Web of Science® Average Citations per reference: 280 ACR
SCOPUS® Average Citations per reference: 449 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2016-12-07 11:53 in 25 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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