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FACTS & FIGURES

JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 2017
Avg review time: 78 days


PUBLISHER

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: 643243560
doi: 10.4316/AECE


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FEATURED ARTICLE

Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016

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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "Big Data - " before the paper title in OpenConf.

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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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.

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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: 944 | Views: 4,468

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
Quick view
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

Cited-By ISI Web of Science

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Cited-By CrossRef

SCOPUS® Times Cited: 17
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Cited-By CrossRef

[1] Strategies for Power/Energy Saving in Distribution Networks, GRIGORAS, G., CARTINA, G., BOBRIC, E. C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 10, 2010.
Digital Object Identifier: 10.4316/aece.2010.02010
[CrossRef] [Full text]

[2] Statistical models for disaggregation and reaggregation of natural gas consumption data, Brabec, M., Konár, O., Malý, M., Kasanický, I., Pelikán, E., Journal of Applied Statistics, ISSN 0266-4763, Issue 5, Volume 42, 2015.
Digital Object Identifier: 10.1080/02664763.2014.993365
[CrossRef]

[3] Two-Stage Load Pattern Clustering Using Fast Wavelet Transformation, Mets, Kevin, Depuydt, Frederick, Develder, Chris, IEEE Transactions on Smart Grid, ISSN 1949-3053, Issue 5, Volume 7, 2016.
Digital Object Identifier: 10.1109/TSG.2015.2446935
[CrossRef]

[4] The Impact of the Load Side Parameters on PC Cluster's Harmonics Emission, KATIC, V. A., MUJOVIC, S. V., RADULOVIC, V. M., RADOVIC, J. S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 11, 2011.
Digital Object Identifier: 10.4316/AECE.2011.01017
[CrossRef] [Full text]

[5] A Mobile-based Platform for Big Load Profiles Data Analytics in Non-Advanced Metering Infrastructures, Moussa, Sherin, Mastorakis, N., Mladenov, V., Bulucea, A., MATEC Web of Conferences, ISSN 2261-236X, Issue , 2016.
Digital Object Identifier: 10.1051/matecconf/20167604023
[CrossRef]

[6] Robust Real-Time Load Profile Encoding and Classification Framework for Efficient Power Systems Operation, Varga, Ervin D., Beretka, Sandor F., Noce, Christian, Sapienza, Gianluca, IEEE Transactions on Power Systems, ISSN 0885-8950, Issue 4, Volume 30, 2015.
Digital Object Identifier: 10.1109/TPWRS.2014.2354552
[CrossRef]

[7] Optimal Clustering of Time Periods for Electricity Demand-Side Management, Rogers, David F., Polak, George G., IEEE Transactions on Power Systems, ISSN 0885-8950, Issue 4, Volume 28, 2013.
Digital Object Identifier: 10.1109/TPWRS.2013.2252373
[CrossRef]

[8] Least Squares Modeling of Voltage Harmonic Distortion Due to PC Cluster Operation, MUJOVIC, S., DJUKANOVIC, S., RADULOVIC, V., KATIC, V., RASOVIC, M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.04022
[CrossRef] [Full text]

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


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