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Comparative analysis of recent metaheuristic algorithms for maximum power point tracking of solar photovoltaic systems under partial shading conditions

International Journal of Applied Power Engineering (IJAPE) · Vol. 12 No. 2 (2023) · hlm. 196–217

DOI
10.11591/ijape.v12.i2.pp196-217
ISSN
2722-2624, 2252-8792
Terbit
2023-06-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

The photovoltaic (PV) system comprises one or more solar panels, a converter/inverter, controllers, and other mechanical and electrical elements that utilize the generated electrical energy by the PV modules. The PV systems are ranged from small roofs or transportable units to massive electric utility plants. The maximum power point tracking (MPPT) controller has been used in PV systems to get the maximum power available. In addition, the MPPT controller is much essential for PV systems to protect the battery devices or direct loads from the power fluctuations received from solar PV panels. There are several MPPT control mechanisms available right now. The most common and commonly applied approaches under constant irradiance are perturb and observe (P&O) and incremental conductance (INC). But such methods show variations in the maximum power point. In this sense, this paper analyses and utilizes two recent metaheuristic algorithms called artificial rabbit optimization (ARO) and the most valuable player (MVP) algorithm for MPPT applications. The performance comparisons are made with the most preferred traditional algorithms, such as P&O and INC. Based on the result obtained, this study recommends that ARO perform better in standard testing conditions than all the other algorithms, but in partially shaded conditions, the MVP algorithm performs better in terms of efficiency and tracking speed.

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  • Universitas Negeri Surabaya
  • Chouaib Doukkali University
  • Dayananda Sagar College of Engineering
  • Université Hassan 1er
  • GMR Institute of Technology
  • Al al-Bayt University
  • National Institute of Technology Tiruchirappalli
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Rekan penulisOrganisasiArtikel bersama
Widi AribowoUniversitas Negeri Surabaya4
R. SowmyaNational Institute of Technology Tiruchirappalli3
Diego A. OlivaUniversidad de Guadalajara3
Aliyu SaboNigerian Defence Academy3
G. Saikiran ReddyDayananda Sagar College of Engineering3
Toufik MziliChouaib Doukkali University2
Abeer A. AljohaniTaibah University2
Ahmed AbatalUniversité Hassan 1er1
Mourad MziliChouaib Doukkali University1
Zakaria BenlaliaChouaib Doukkali University1
Hajar KhalloukiUniversité Hassan 1er1
Mohammed El Kaim BillahChouaib Doukkali University1
Mutasem K. AlsmadiImam Abdulrahman Bin Faisal University1
Ghaith M. JaradatAmman Arab University1
Mohamad I. Al‐WidyanJordan University of Science and Technology1
Ayusta Lukita WardaniUniversitas Negeri Surabaya1
Aditya PrapancaUniversitas Negeri Surabaya1
Reza RahmadianUniversitas Negeri Surabaya1
Mahendra WidyartonoUniversitas Negeri Surabaya1
Chandrasekaran KumarBannari Amman Institute of Technology1
Kanagarathinam KarthickAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijape.iaescore.com/index.php/IJAPE/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Comparative analysis of recent metaheuristic algorithms for maximum power point tracking of solar photovoltaic systems under partial shading conditions</dc:title>
	<dc:creator>Ravi, Suraj</dc:creator>
	<dc:creator>Premkumar, Manoharan</dc:creator>
	<dc:creator>Abualigah, Laith</dc:creator>
	<dc:subject xml:lang="en-US">boost converter; metaheuristic algorithm; MPPT algorithms; partial shading conditions</dc:subject>
	<dc:description xml:lang="en-US">The photovoltaic (PV) system comprises one or more solar panels, a converter/inverter, controllers, and other mechanical and electrical elements that utilize the generated electrical energy by the PV modules. The PV systems are ranged from small roofs or transportable units to massive electric utility plants. The maximum power point tracking (MPPT) controller has been used in PV systems to get the maximum power available. In addition, the MPPT controller is much essential for PV systems to protect the battery devices or direct loads from the power fluctuations received from solar PV panels. There are several MPPT control mechanisms available right now. The most common and commonly applied approaches under constant irradiance are perturb and observe (P&amp;amp;O) and incremental conductance (INC). But such methods show variations in the maximum power point. In this sense, this paper analyses and utilizes two recent metaheuristic algorithms called artificial rabbit optimization (ARO) and the most valuable player (MVP) algorithm for MPPT applications. The performance comparisons are made with the most preferred traditional algorithms, such as P&amp;amp;O and INC. Based on the result obtained, this study recommends that ARO perform better in standard testing conditions than all the other algorithms, but in partially shaded conditions, the MVP algorithm performs better in terms of efficiency and tracking speed.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2023-06-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijape.iaescore.com/index.php/IJAPE/article/view/20592</dc:identifier>
	<dc:identifier>10.11591/ijape.v12.i2.pp196-217</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Applied Power Engineering (IJAPE); Vol 12, No 2: June 2023; 196-217</dc:source>
	<dc:source>2722-2624</dc:source>
	<dc:source>2252-8792</dc:source>
	<dc:source>10.11591/ijape.v12.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijape.iaescore.com/index.php/IJAPE/article/view/20592/13062</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Suraj R, Premkumar M</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>