dc.rights.license |
DOAJ Gold, Green Published |
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dc.date.accessioned |
2021-06-03T08:20:48Z |
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dc.date.available |
2021-06-03T08:20:48Z |
|
dc.date.issued |
2020 |
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dc.identifier.uri |
www.doi.org/10.3390/en13184721 |
|
dc.identifier.uri |
https://hdl.handle.net/20.500.12619/95255 |
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dc.description |
Bu yayın 06.11.1981 tarihli ve 17506 sayılı Resmî Gazete’de yayımlanan 2547 sayılı Yükseköğretim Kanunu’nun 4/c, 12/c, 42/c ve 42/d maddelerine dayalı 12/12/2019 tarih, 543 sayılı ve 05 numaralı Üniversite Senato Kararı ile hazırlanan Sakarya Üniversitesi Açık Bilim ve Açık Akademik Arşiv Yönergesi gereğince açık akademik arşiv sistemine açık erişim olarak yüklenmiştir. |
|
dc.description.abstract |
In this paper, energy management and control of a microgrid is developed through supervisor and adaptive neuro-fuzzy wavelet-based control controllers considering real weather patterns and load variations. The supervisory control is applied to the entire microgrid using lower-top level arrangements. The top-level generates the control signals considering the weather data patterns and load conditions, while the lower level controls the energy sources and power converters. The adaptive neuro-fuzzy wavelet-based controller is applied to the inverter. The new proposed wavelet-based controller improves the operation of the proposed microgrid as a result of the excellent localized characteristics of the wavelets. Simulations and comparison with other existing intelligent controllers, such as neuro-fuzzy controllers and fuzzy logic controllers, and classical PID controllers are used to present the improvements of the microgrid in terms of the power transfer, inverter output efficiency, load voltage frequency, and dynamic response. |
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dc.description.sponsorship |
Scientific and Technological Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [5190011]; Bavarian Government; Deutsche Forschungsgemeinschaft (DFG)German Research Foundation (DFG) [350746631]; Spanish Ministry of Science, Innovation, and Universities [RTI2018-095720-B-C32] |
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dc.language |
English |
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dc.language.iso |
İngilizce |
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dc.publisher |
MDPI |
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dc.relation.isversionof |
10.3390/en13184721 |
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dc.rights |
info:eu-repo/semantics/openAccess |
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dc.subject |
PHOTOVOLTAIC SYSTEMS |
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dc.subject |
GRID INTEGRATION |
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dc.subject |
NETWORK |
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dc.subject |
SYNCHRONIZATION |
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dc.subject |
RECTIFIER |
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dc.subject |
inverter |
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dc.subject |
supervisory control |
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dc.subject |
adaptive control |
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dc.subject |
photovoltaic |
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dc.subject |
ultra-capacitor |
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dc.title |
Novel Improved Adaptive Neuro-Fuzzy Control of Inverter and Supervisory Energy Management System of a Microgrid |
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dc.type |
Article |
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dc.contributor.authorID |
Fernandez-Ramirez, Luis M./0000-0002-4898-0680 |
|
dc.contributor.authorID |
Peric, Vedran/0000-0002-6044-4813 |
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dc.identifier.volume |
13 |
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dc.relation.journal |
ENERGIES |
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dc.identifier.issue |
18 |
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dc.identifier.wos |
WOS:000580415000001 |
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dc.identifier.doi |
10.3390/en13184721 |
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dc.identifier.eissn |
1996-1073 |
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dc.contributor.author |
Kamal, Tariq |
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dc.contributor.author |
Karabacak, Murat |
|
dc.contributor.author |
Peric, Vedran S. |
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dc.contributor.author |
Hassan, Syed Zulqadar |
|
dc.contributor.author |
Fernandez-Ramirez, Luis M. |
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dc.relation.publicationcategory |
Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı |
|