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JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Nov 2024
Next issue: Feb 2025
Avg review time: 57 days
Avg accept to publ: 60 days
APC: 300 EUR


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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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  1/2014 - 8

 HIGHLY CITED PAPER 

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
 
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Download PDF pdficon (905 KB) | Citation | Downloads: 1,047 | Views: 4,153

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.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 4
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Cited-By CrossRef

[1] Modeling and Control of Grid-Connected Photovoltaic Power Plant With Fault Ride-Through Capability, Al-Shetwi, Ali Q., Sujod, Muhamad Zahim, Journal of Solar Energy Engineering, ISSN 0199-6231, Issue 2, Volume 140, 2018.
Digital Object Identifier: 10.1115/1.4038591
[CrossRef]

Updated 2 days ago

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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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