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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
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Avg review time: 106 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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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.

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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: 427 | Views: 1,879

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

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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  «-- Click to see who has cited this paper

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[17] T. Tomisa, Z. Simic, D. Dedeic: Automated photovoltaic panel positioning device for solar radiation monitoring, MIPRO Computers in technical systems, 2011, pages 28-33

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[19] F. J. Toledo, J. M. Blanes, A. Garrigos, J. A. Martínez: Analytical resolution of the electrical four-parameters model of a photovoltaic module using small perturbation around the operating point, Journal of Renewable energy 43, 2012, pages 83-89

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[24] I. Petrovic, Z. Simic, M. Vrazic: Comparison of PV plant energy generation prediction tools with measured data, Journal of Przeglad Elektrotechniczny, june 2013., pages 121-124

[25] I. Petrovic, Z. Simic, M. Vrazic: Advancements in PV plant energy production prediction with model improvement based on measured data, Journal of International Review of Electrical Engineering (I.R.E.E.), Vol 8, Issue 2, april 2013, pages 832-838

References Weight

Web of Science® Citations for all references: 1,018 TCR
SCOPUS® Citations for all references: 1,219 TCR

Web of Science® Average Citations per reference: 39 ACR
SCOPUS® Average Citations per reference: 47 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 2018-01-22 10:56 in 58 seconds.

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

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