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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 81 days


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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: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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-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.

Read More »


    
 

  3/2017 - 12

Novel TPPO Based Maximum Power Point Method for Photovoltaic System

ABBASI, M. A. See more information about ABBASI, M. A. on SCOPUS See more information about ABBASI, M. A. on IEEExplore See more information about ABBASI, M. A. on Web of Science, ZIA, M. F. See more information about ZIA, M. F. on SCOPUS See more information about ZIA, M. F. on SCOPUS See more information about ZIA, M. F. on Web of Science
 
Click to see author's profile in 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 (2,227 KB) | Citation | Downloads: 255 | Views: 653

Author keywords
DC-DC power converters, maximum power point trackers, photovoltaic cells, solar energy, solar power generation

References keywords
optimization(18), algorithm(18), artificial(13), colony(12), comput(8), jasoc(6), swarm(5), soft(5), search(5), jins(5)
No common words between the references section and the paper title.

About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 95 - 100
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03012
Web of Science Accession Number: 000410369500012
SCOPUS ID: 85028570193

Abstract
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Photovoltaic (PV) system has a great potential and it is installed more when compared with other renewable energy sources nowadays. However, the PV system cannot perform optimally due to its solid reliance on climate conditions. Due to this dependency, PV system does not operate at its maximum power point (MPP). Many MPP tracking methods have been proposed for this purpose. One of these is the Perturb and Observe Method (P&O) which is the most famous due to its simplicity, less cost and fast track. But it deviates from MPP in continuously changing weather conditions, especially in rapidly changing irradiance conditions. A new Maximum Power Point Tracking (MPPT) method, Tetra Point Perturb and Observe (TPPO), has been proposed to improve PV system performance in changing irradiance conditions and the effects on characteristic curves of PV array module due to varying irradiance are delineated. The Proposed MPPT method has shown better results in increasing the efficiency of a PV system.


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

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References Weight

Web of Science® Citations for all references: 29,772 TCR
SCOPUS® Citations for all references: 14,682 TCR

Web of Science® Average Citations per reference: 992 ACR
SCOPUS® Average Citations per reference: 489 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 2018-12-14 01:59 in 177 seconds.




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


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