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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: 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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  3/2022 - 4

Different Concepts of Grid-Connected Microgrids with a PV System, Battery Energy Storage, Feed-in Tariff, and Load Management Using Fuzzy Logic

ZEC, L. See more information about ZEC, L. on SCOPUS See more information about ZEC, L. on IEEExplore See more information about ZEC, L. on Web of Science, MIKULOVIC, J. See more information about MIKULOVIC, J. on SCOPUS See more information about MIKULOVIC, J. on SCOPUS See more information about MIKULOVIC, J. on Web of Science
 
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Download PDF pdficon (1,657 KB) | Citation | Downloads: 735 | Views: 1,397

Author keywords
batteries, fuzzy logic, load management, microgrids, photovoltaic systems

References keywords
energy(32), management(18), power(12), fuzzy(12), system(10), microgrid(10), grid(10), systems(9), control(9), renewable(8)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2022-08-31
Volume 22, Issue 3, Year 2022, On page(s): 33 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2022.03004
Web of Science Accession Number: 000861021000004
SCOPUS ID: 85137727458

Abstract
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This paper presents different variants of smart grid-connected microgrids consisting of a photovoltaic (PV) system and batteries. Based on ten-minute data on the consumption of the distribution system, the estimation of the consumption diagram of one household was performed, as well as the determination of its unmanageable and manageable part. The fuzzy logic controller and algorithm for energy flow management were applied to manage the consumption of one household. The proposed load management provides a continuous power supply to a consumer from his PV system, batteries, and distribution grid, enabling the energy exchange with the grid and achieving financial gain. The input data for the fuzzy logic controller are the difference between the PV system power production and the household power consumption, the variation of the price of electricity on the market to its average value, and the state of charge of the battery. The output data from the fuzzy logic controller are the probabilities of engaging home appliances. The presented analysis was done for a period of one year for the city of Belgrade.


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Cited-By CrossRef

[1] Load management design and techno-economic analysis for an islanded hybrid Pv-Teg microgrid, MUHI, Firas Hasan Muhi, GÜÇYETMEZ, Mehmet, Energy Reports, ISSN 2352-4847, Issue , 2024.
Digital Object Identifier: 10.1016/j.egyr.2024.05.037
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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