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JCR Impact Factor: 0.825
JCR 5-Year IF: 0.752
SCOPUS CiteScore: 2.5
Issues per year: 4
Current issue: Nov 2022
Next issue: Feb 2023
Avg review time: 74 days
Avg accept to publ: 48 days
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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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LATEST NEWS

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 in 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

2021-Apr-15
Release of the v3 version of AECE Journal website. We moved to a new server and implemented the latest cryptographic protocols to assure better compatibility with the most recent browsers. Our website accepts now only TLS 1.2 and TLS 1.3 secure connections.

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  2/2010 - 4

 HIGHLY CITED PAPER 

Development of Reliability Model for Wind Farm Power Generation

NEMES, C. See more information about NEMES, C. on SCOPUS See more information about NEMES, C. on IEEExplore See more information about NEMES, C. on Web of Science, MUNTEANU, F. See more information about MUNTEANU, F. on SCOPUS See more information about MUNTEANU, F. on SCOPUS See more information about MUNTEANU, F. on Web of Science
 
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Download PDF pdficon (738 KB) | Citation | Downloads: 1,471 | Views: 5,416

Author keywords
electric power system, probability, wind power generation

References keywords
wind(10), energy(6), power(5), reliability(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-05-31
Volume 10, Issue 2, Year 2010, On page(s): 24 - 29
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.02004
Web of Science Accession Number: 000280312600004
SCOPUS ID: 77954636326

Abstract
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Full text preview
The objective of the present paper is to estimate the electric power distribution of a wind farm using the output power distribution and the probability of simultaneously running of wind turbines. In this paper, a methodology for the electric power distribution of a wind turbine, using the characteristic output power-wind and the Weibull distribution of wind speed was given first. The methodology was applied to a region from north-east of Romania, and finally, the analytic distributions were compared to Monte-Carlo simulation.


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

[1] Ackermann T., "Wind Power in Power Systems", Ed. John Wiley & Sons 2005. [PermaLink]

[2] Endrenyi J., "Reliability modeling in electric power systems", Wiley and Sons, New York, 1978. [PermaLink]

[3] Manwell J. F., McGowan J. G, Rogers A. L., "Wind energy explained : theory, design and application", Ed. Wiley & Sons 2002. [PermaLink]

[4] Isaac Y. F. Lun, Joseph C. Lam, "A study of Weibull parameters using long-term wind observations", Renewable Energy Journal, Volume 20, Issue 2, June 2000, pp. 145-153.

[5] Carta J. A., Ramirez P., "A review of wind speed probability distributions used in wind energy analysis. Case studies in the Canary Islands", Renewable and Sustainable Energy Reviews, Volume 13, Issue 5, June 2009, Pages 933-955. Available: Temporary on-line reference link removed - see the PDF document

[6] Al-Fawzan M. A. , "Algorithms for Estimating the Parameters of the Weibull Distribution", Interstat journal. October 2000. Available: Temporary on-line reference link removed - see the PDF document

[7] Nemes C., Munteanu F., "New techniques for availability analysis", Ed. Politehnium Iasi, sept. 2008;

[8] Tina G., Gagliano S., Raiti S., "Hybrid solar/wind power system probabilistic modeling for long-term performance assessment", Elsevier Ltd. Solar Energy, Volume 80, Issue 5, May 2006, pp. 578-588.
[CrossRef] [Web of Science Times Cited 255] [SCOPUS Times Cited 338]


[9] Available: Temporary on-line reference link removed - see the PDF document

[10] Holmstrom, N. Barberis Negra1, "Survey of Reliability of Large Offshore Wind Farms", European Wind Energy Conference, Milan, Italy, 7-10 May 2007.

[11] Fotuhi-Firuzabad M., Salehi Dobakhshari A., "Reliability-based Selection of Wind Turbines for Large-Scale Wind Farms", World Academy of Science, Engineering and Technology volume 49, January 2009, pp. 734-740.

[12] Billinton R., "Reliability assessment of electric power systems using Monte Carlo methods", Plenum Press, 1994. [PermaLink]

References Weight

Web of Science® Citations for all references: 255 TCR
SCOPUS® Citations for all references: 338 TCR

Web of Science® Average Citations per reference: 21 ACR
SCOPUS® Average Citations per reference: 28 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 2022-12-04 04:15 in 9 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2022
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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