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Investigating and Optimizing the Operation of Microgrids with Intelligent Algorithms

Journal of Robotics and Control (JRC) · Vol. 3 No. 3 (2022) · hlm. 279–288

DOI
10.18196/jrc.v3i3.14772
ISSN
2715-5072, 2715-5056
Terbit
2022-05-01
Penerbit
Universitas Muhammadiyah Yogyakarta
Bahasa
eng

Abstrak

Microgrids need optimization to reduce economic problems and human losses. Scattered resources in power systems and microgrids have led to many environmental, economic and human, and animal losses. The most important part of these problems is related to voltage and frequency fluctuations when possible occurrences such as extreme load changes or errors in microgrids. These problems lead to microgrid collapse. Therefore, providing optimal solutions that can solve these challenges is essential. For this purpose, the present study has tried to provide a high-performance control structure in the time of internal and external disturbances based on short-term planning. The proposed approach is the use of an evolutionary neuro-fuzzy network. Perhaps the main reason for using this approach can be due to uncertainty in the distribution and distribution of loads in microgrids and power systems. Simulation has been performed in MATLAB and Simulink environments, and the results show that the optimal load distribution has been done evolution in microgrids.

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  • Mehran University of Engineering and Technology
  • Islamic Azad University, Tehran
  • Université Hassan 1er
  • Muhammadiyah University of Yogyakarta
  • Universitas Muhammadiyah Palembang
  • Islamic Azad University Yasuj
  • Universitas Trunodjoyo Madura
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Rekan penulisOrganisasiArtikel bersama
Alfian Ma’arifUniversitas Ahmad Dahlan6
Mahmoud A. MossaMinia University2
Ferydon GharadaghiAfiliasi tidak diketahui2
Farnaz JahanbinIslamic Azad University, Mashhad2
Nima ShafaghatianUniversity of Zanjan2
Hossein HarasiiIslamic Azad University, Tehran1
Hamed PourderogarIslamic Azad University, Tehran1
Robbi RahimUniversiti Malaysia Perlis1
Yaya FinayaniAfiliasi tidak diketahui1
Jassim O. AlhamidWashington State University Tri-Cities1
Ahmed Ramadhan Al‐ObaidiMustansiriyah University1
Yosi AprianiUniversitas Muhammadiyah Palembang1
Wiwin Armoldo OktavianiUniversitas Muhammadiyah Palembang1
Anish PandeyKIIT University1
Dhiya Uddin RijalusalamMuhammadiyah University of Yogyakarta1
Nia Maharani RaharjaMuhammadiyah University of Yogyakarta1
Sugiyarta SugiyartaAfiliasi tidak diketahui1
Galang P. N. HakimMercu Buana University1
Diah SeptiyanaUniversitas Muhammadiyah Tangerang1
Mahmoud ZadehbagheriIslamic Azad University Yasuj1
Rahim IldarabadiHakim Sabzevari University1
Mehdi AnsarifardIslamic Azad University Yasuj1
Zuha AnjumMehran University of Engineering and Technology1
Saifullah SamoMehran University of Engineering and Technology1
Arbab Nighat KhizerMehran University of Engineering and Technology1
Akhtar Un NisaMehran University of Engineering and Technology1
Muhammad Ali SoomroMehran University of Engineering and Technology1
Wahyu CaesarendraUniversiti Brunei Darussalam1
Faikul UmamUniversitas Trunodjoyo Madura1
Muhammad FuadUniversitas Trunodjoyo Madura1
Azeddine LoulijatUniversité Hassan 1er1
Abdellah BoulalUniversité Hassan 1er1
Sarah AbboudUniversité Hassan 1er1
El Alami SemmaUniversité Hassan 1er1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.umy.ac.id/index.php/jrc/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Investigating and Optimizing the Operation of Microgrids with Intelligent Algorithms</dc:title>
	<dc:creator>Kadhim Hado, Ahmed</dc:creator>
	<dc:creator>S. Bashar, Bashar</dc:creator>
	<dc:creator>Maher Abdul Zahra, Musaddak</dc:creator>
	<dc:creator>Alayi, Reza</dc:creator>
	<dc:creator>Ebazadeh, Yaser</dc:creator>
	<dc:creator>Suwarno, Iswanto</dc:creator>
	<dc:subject xml:lang="en-US">Microgrids</dc:subject>
	<dc:subject xml:lang="en-US">Short-term planning</dc:subject>
	<dc:subject xml:lang="en-US">Power systems</dc:subject>
	<dc:subject xml:lang="en-US">Optimal load distribution</dc:subject>
	<dc:subject xml:lang="en-US">Neuro-Fuzzy Network</dc:subject>
	<dc:description xml:lang="en-US">Microgrids need optimization to reduce economic problems and human losses. Scattered resources in power systems and microgrids have led to many environmental, economic and human, and animal losses. The most important part of these problems is related to voltage and frequency fluctuations when possible occurrences such as extreme load changes or errors in microgrids. These problems lead to microgrid collapse. Therefore, providing optimal solutions that can solve these challenges is essential. For this purpose, the present study has tried to provide a high-performance control structure in the time of internal and external disturbances based on short-term planning. The proposed approach is the use of an evolutionary neuro-fuzzy network. Perhaps the main reason for using this approach can be due to uncertainty in the distribution and distribution of loads in microgrids and power systems. Simulation has been performed in MATLAB and Simulink environments, and the results show that the optimal load distribution has been done evolution in microgrids.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Yogyakarta</dc:publisher>
	<dc:date>2022-05-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.umy.ac.id/index.php/jrc/article/view/14772</dc:identifier>
	<dc:identifier>10.18196/jrc.v3i3.14772</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Robotics and Control (JRC); Vol. 3 No. 3 (2022): May; 279-288</dc:source>
	<dc:source>2715-5072</dc:source>
	<dc:source>2715-5056</dc:source>
	<dc:source>10.18196/jrc.v3i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.umy.ac.id/index.php/jrc/article/view/14772/7372</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Reza Alayi, Ahmed Kadhim Hado, Bashar S. Bashar, Musaddak Maher Abdul Zahra, Yaser Ebazadeh, Iswanto Suwarno</dc:rights>
</oai_dc:dc>