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A cost-effective and optimized maximum powerpoint tracking system for the photovoltaic model

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 5 (2023)

DOI
10.11591/ijece.v13i5.pp4942-4949
ISSN
2722-2578, 2088-8708
Published
2023-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Solar energy is naturally available from sun, and it can be extracted by using a photovoltaic (PV) cell. However, solar energy extraction entirely depends on the climatic conditions and angle of rays falling on PV cells. Hence, maximum powerpoint tracking (MPPT) is considered in most areas under variable climatic conditions, which acts as a controller unit for PV cells. MPPT can enhance the efficiency of PV cells. However, designing an MPPT model is challenging as different uncertainties in the climatic condition may lead to more fluctuations in voltage and current in PV cells. Under the shaded condition, the PV cell may have other MPPT points that lead to the PV cell’s low efficiency in analyzing maximum power. Hence, this paper introduces a cost-effective and optimized system for the PV model that can find optimal power and improve PV cells’ efficiency. The proposed system achieves better computational performance with ~35% and ~42% than existing MPPT techniques. The improved particle swarm optimization (PSO) is smoother due to the enhanced form of MPP tracking. Hence, improved PSO takes 0.038 sec while the existing PSO technique takes 0.045 sec to obtain the MPP tracking.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • R.V. College of Engineering
  • Affiliation unknown
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>A cost-effective and optimized maximum powerpoint tracking system for the photovoltaic model</dc:title><dc:creator>Puttalingaiah, Yoganandini Arehalli</dc:creator><dc:creator>Shesadri, Anitha Gowda</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Solar energy is naturally available from sun, and it can be extracted by using a photovoltaic (PV) cell. However, solar energy extraction entirely depends on the climatic conditions and angle of rays falling on PV cells. Hence, maximum powerpoint tracking (MPPT) is considered in most areas under variable climatic conditions, which acts as a controller unit for PV cells. MPPT can enhance the efficiency of PV cells. However, designing an MPPT model is challenging as different uncertainties in the climatic condition may lead to more fluctuations in voltage and current in PV cells. Under the shaded condition, the PV cell may have other MPPT points that lead to the PV cell’s low efficiency in analyzing maximum power. Hence, this paper introduces a cost-effective and optimized system for the PV model that can find optimal power and improve PV cells’ efficiency. The proposed system achieves better computational performance with ~35% and ~42% than existing MPPT techniques. The improved particle swarm optimization (PSO) is smoother due to the enhanced form of MPP tracking. Hence, improved PSO takes 0.038 sec while the existing PSO technique takes 0.045 sec to obtain the MPP tracking.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v13i5.pp4942-4949</dc:identifier><dc:identifier>10.11591/ijece.v13i5.pp4942-4949</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 5 (2023); 4942</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/25526/16798</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>