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FACTS & FIGURES

JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 105 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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MOST RECENT ISSUES

 Volume 17 (2017)
 
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FEATURED ARTICLE

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S.
Issue 3/2017

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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

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 "BigData - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

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.

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  1/2014 - 8

Advanced PV Plant Planning based on Measured Energy Production Results - Approach and Measured Data Processing

PETROVIC, I. See more information about PETROVIC, I. on SCOPUS See more information about PETROVIC, I. on IEEExplore See more information about PETROVIC, I. on Web of Science, SIMIC, Z. See more information about  SIMIC, Z. on SCOPUS See more information about  SIMIC, Z. on SCOPUS See more information about SIMIC, Z. on Web of Science, VRAZIC, M. See more information about VRAZIC, M. on SCOPUS See more information about VRAZIC, M. on SCOPUS See more information about VRAZIC, M. on Web of Science
 
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 (905 KB) | Citation | Downloads: 420 | Views: 1,791

Author keywords
energy capture, power control, power system analysis computing, power system measurements, photovoltaic cells

References keywords
energy(18), photovoltaic(17), renewable(7), solar(5), systems(4), simic(4), prediction(4), power(4), monitoring(4), assessment(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 49 - 54
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01008
Web of Science Accession Number: 000332062300008
SCOPUS ID: 84894611088

Abstract
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The objective of this research was to develop a model for a prototype measurement station built for recording data relevant for the production of electrical energy by PV modules in order to improve the modelling. The measured data for specific time period (annually), or periods (monthly or otherwise), was processed after measurement results are available, and allow better and more accurate planning of the PV plant. Therefore, data processing time is not significant since it is not used in real-time. Measurement station was designed in a way which allows for the total energy production to be quantified for various modes of operation (fixed, single-axis or dual-axis tracking). In this article energy production in weekly time periods is analyzed since data for short time periods is available and the main goal is to find the most accurate method in PV module characterization. Once the data are obtained, it will be possible to propose improvements of conventional analytical models when measured and modelled results are compared. These improvements will be specific for the location on which prototype measurement station is installed. The proposed improvements will allow upgrades in model estimations without the need for additional measurements by a prototype measurement station.


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Copyright ©2001-2017
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.

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