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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: Aug 2024
Next issue: Nov 2024
Avg review time: 55 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

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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  4/2014 - 4

Incentive Driven Distributed Generation Planning with Renewable Energy Resources

KAUR, S. See more information about KAUR, S. on SCOPUS See more information about KAUR, S. on IEEExplore See more information about KAUR, S. on Web of Science, KUMBHAR, G. B. See more information about KUMBHAR, G. B. on SCOPUS See more information about KUMBHAR, G. B. on SCOPUS See more information about KUMBHAR, G. B. on Web of Science
 
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Download PDF pdficon (837 KB) | Citation | Downloads: 1,015 | Views: 3,528

Author keywords
distributed power generation, heuristic algorithms, optimization, power generation planning, sustainable development

References keywords
power(10), energy(10), planning(9), optimization(9), generation(9), distributed(9), distribution(8), systems(6), system(6), search(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 21 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04004
Web of Science Accession Number: 000348772500004
SCOPUS ID: 84921651204

Abstract
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Renewable DGs may not be economically viable due to the stochastic generation and huge capital investment, but are an inevitable choice for sustainable energy development and future planning. An appropriate incentive scheme for clean Distributed Generation (DG) technologies is able to address this issue in an economical manner and is considered in proposed distributed generation planning model. The proposed model minimizes the annualized cost with Emission Offset Incentive (EOI) and the penalty for Green-house Gas (GHG) emissions. A meta-heuristic approach with dynamic tuning of control parameters is adopted to improve the success and the convergence rate of optimal solutions. The algorithm provides the optimal solution in terms of type, size, and location of DG. The proposed technique is implemented on IEEE 33-bus system. Proposed model helps the Distribution Network Operators (DNOs) to decide the proper DG technology from an economic prospective for eco-friendly energy planning.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 3
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Cited-By CrossRef

[1] Real Measure of a Transmission Line Data with Load Fore-cast Model for The Future, YILMAZ, Musa, Balkan Journal of Electrical and Computer Engineering, ISSN 2147-284X, Issue 2, Volume 6, 2018.
Digital Object Identifier: 10.17694/bajece.419646
[CrossRef]

[2] A novel generation and capacitor integration technique for today's distribution systems, ÖZGÖNENEL, Okan, KARAGÖL, Serap, TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, ISSN 1300-0632, Issue , 2017.
Digital Object Identifier: 10.3906/elk-1602-197
[CrossRef]

[3] A hybrid approach for promoting low carbon technologies in distributed generation planning, Kaur, Sandeep, Kaur, Manmeet, Kumbhar, Ganesh, Khanna, Rintu, 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC), ISBN 978-1-5386-0504-2, 2017.
Digital Object Identifier: 10.1109/ICSGSC.2017.8038555
[CrossRef]

[4] An integrated approach for power loss reduction in primary distribution system, Pawar, Badopant, Kaur, Sandeep, Kumbhar, G. B., 2016 IEEE 6th International Conference on Power Systems (ICPS), ISBN 978-1-5090-0128-6, 2016.
Digital Object Identifier: 10.1109/ICPES.2016.7584049
[CrossRef]

Updated 2 days, 2 hours ago

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


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