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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
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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  4/2021 - 1
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 HIGHLY CITED PAPER 

A Wind Energy Prediction Scheme Combining Cauchy Variation and Reverse Learning Strategy

WU, X. See more information about WU, X. on SCOPUS See more information about WU, X. on IEEExplore See more information about WU, X. on Web of Science, SHEN, X. See more information about  SHEN, X. on SCOPUS See more information about  SHEN, X. on SCOPUS See more information about SHEN, X. on Web of Science, ZHANG, J. See more information about  ZHANG, J. on SCOPUS See more information about  ZHANG, J. on SCOPUS See more information about ZHANG, J. on Web of Science, ZHANG, Y. See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on Web of Science
 
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Download PDF pdficon (1,966 KB) | Citation | Downloads: 1,799 | Views: 2,191

Author keywords
carbon emissions, cauchy mutation, long short-term memory, reverse learning, synchrosqueezed wavelet transforms

References keywords
wind(18), energy(18), speed(13), forecasting(11), prediction(9), term(8), short(8), model(7), zhao(6), novel(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-11-30
Volume 21, Issue 4, Year 2021, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.04001
Web of Science Accession Number: 000725107100001
SCOPUS ID: 85122245524

Abstract
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Modular multilevel converters (MMCs) can be a reliable solution since they have modular structure and high quality output waveform for permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS). Capacitor voltage balancing in nearest level modulation (NLM) is required to keep the capacitor voltage of each submodule of MMC constant. In this paper, an efficient capacitor voltage balancing scheme under NLM is proposed for PMSG based WECS with MMC topology. Through proposed control scheme, arm voltages are separately controlled and voltage ripple of around 1.5% is obtained. This result provides high quality output waveform at the point of common coupling (PCC). Furthermore, DC-link voltage control is achieved via hysteresis current control based proportional-integral controller. The ripple of DC-link voltage is obtained quite well as nearly 0.25%. In addition, load voltage control is accomplished using dq reference frame-based voltage control scheme for voltage and frequency stabilization at the PCC by regulating the voltage at its reference value. Simulation studies show that all proposed control schemes give satisfactory results for MMC based WECS under variable dynamic operation modes. Finally, experimental verification is performed using laboratory prototype to show the applicability of the proposed capacitor voltage balancing scheme.


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Cited-By CrossRef

[1] Impact of Photovoltaic Systems Allocation on Congestion in Distribution Network: Iraq Case Study, BADR, H. M., ALI, R. S., MAHMOOD, J. R., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 22, 2022.
Digital Object Identifier: 10.4316/AECE.2022.02010
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[2] A Novel Approach to Speech Enhancement Based on Deep Neural Networks, SALEHI, M., MIRZAKUCHAKI, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 22, 2022.
Digital Object Identifier: 10.4316/AECE.2022.02009
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[3] A Wireless Acoustic Emission Sensor System with ACMD-IGWO-XGBoost Algorithm for Living Tree Moisture Content Diagnosis, Yang, Zenan, Wu, Yin, Liu, Yanyi, Plants, ISSN 2223-7747, Issue 3, Volume 12, 2023.
Digital Object Identifier: 10.3390/plants12030601
[CrossRef]

[4] Thermographic fault diagnosis of electrical faults of commutator and induction motors, Glowacz, Adam, Engineering Applications of Artificial Intelligence, ISSN 0952-1976, Issue , 2023.
Digital Object Identifier: 10.1016/j.engappai.2023.105962
[CrossRef]

[5] A Metaheuristic Algorithm for Coverage Enhancement of Wireless Sensor Networks, Wang, Zhigang, Tian, Liqin, Wu, Wenxing, Lin, Lianhai, Li, Zongjin, Tong, Yinghua, Yuan, Xiaohui, Wireless Communications and Mobile Computing, ISSN 1530-8677, Issue , 2022.
Digital Object Identifier: 10.1155/2022/7732989
[CrossRef]

[6] Steady-state deduction methods of a power system based on the prediction of large-scale wind power clusters, Feng, Rongqiang, Yu, Haiping, Wu, Xueqiong, Huang, Chenxi, Du, Tianchi, Ding, Wei, Frontiers in Energy Research, ISSN 2296-598X, Issue , 2023.
Digital Object Identifier: 10.3389/fenrg.2023.1194415
[CrossRef]

[7] An integrated method with adaptive decomposition and machine learning for renewable energy power generation forecasting, Li, Guomin, Yu, Leyi, Zhang, Ying, Sun, Peng, Li, Ruixuan, Zhang, Yagang, Li, Gengyin, Wang, Pengfei, Environmental Science and Pollution Research, ISSN 1614-7499, Issue 14, Volume 30, 2023.
Digital Object Identifier: 10.1007/s11356-023-25194-3
[CrossRef]

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


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