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Multi-temporal assessment of wind, solar, and hydropower resources for off-grid microgrid

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 4 (2024)

DOI
10.11591/ijece.v14i4.pp3755-3767
ISSN
2722-2578, 2088-8708
Published
2024-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

For a proposed multi-source all-renewable microgrid in Nigeria’s Middle-belt region, this paper presents a multi-temporal approach to the investigation of the uncertainty in the potential of renewable energy resources. The wind, solar, and hydropower resources for a proposed multi-source all-renewable off-grid community microgrid are considered using an array of probabilistic techniques. The peculiar variances in the location’s climate throughout the year make the more common method of annual models of renewable resources unsuitable for power system planning. Consequently, a more granular model of its renewable resources over time is needed. Therefore, for the chosen location, for each renewable resource, a composite multitemporal maximum-likelihood estimation-based (MLE) probabilistic model for characterization is developed. A total of 39 probabilistic models are developed. Up to 40% improvement in the accuracy of the statistical measures for renewable resource uncertainty was observed. Multi-temporal approach provides more accurate information for power system planning over time than the conventional approach of single aggregate models, especially for hydropower, which is strongly affected by the relatively sporadic occurrence of rainfall. The study shows that solar energy is promising, hydropower potential is seasonal and complementary, and wind potential is low at the location considered in this study.

Collaboration network of the authors

12 authors · 26 co-authorship links · 16 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Ekiti State University
  • Landmark University
  • Ladoke Akintola University of Technology
  • Ekiti State Polytechnic
  • Federal University of Technology and Environmental Sciences
  • Federal University of Technology
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Oluwumi AdetanEkiti State University1
Bankole AdebanjiEkiti State University1
Gafari Abiola AdepojuLadoke Akintola University of Technology1
Taiwo FasinaEkiti State University1
Temitope AkinyedeEkiti State Polytechnic1
Josephine Adenike AkinyedeFederal University of Technology and Environmental Sciences1
Emmanuel Taiwo FasinaEkiti State University1
Temitope Adewale OlominuFederal University of Technology1

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>Multi-temporal assessment of wind, solar, and hydropower resources for off-grid microgrid</dc:title><dc:creator>Odetoye, Oyinlolu Ayomidotun</dc:creator><dc:creator>Kehinde Olulope, Paul</dc:creator><dc:creator>Olabisi Olanrewaju, Matthew</dc:creator><dc:creator>Olusola Alimi, Adeleke</dc:creator><dc:description>&lt;jats:p&gt;For a proposed multi-source all-renewable microgrid in Nigeria’s Middle-belt region, this paper presents a multi-temporal approach to the investigation of the uncertainty in the potential of renewable energy resources. The wind, solar, and hydropower resources for a proposed multi-source all-renewable off-grid community microgrid are considered using an array of probabilistic techniques. The peculiar variances in the location’s climate throughout the year make the more common method of annual models of renewable resources unsuitable for power system planning. Consequently, a more granular model of its renewable resources over time is needed. Therefore, for the chosen location, for each renewable resource, a composite multitemporal maximum-likelihood estimation-based (MLE) probabilistic model for characterization is developed. A total of 39 probabilistic models are developed. Up to 40% improvement in the accuracy of the statistical measures for renewable resource uncertainty was observed. Multi-temporal approach provides more accurate information for power system planning over time than the conventional approach of single aggregate models, especially for hydropower, which is strongly affected by the relatively sporadic occurrence of rainfall. The study shows that solar energy is promising, hydropower potential is seasonal and complementary, and wind potential is low at the location considered in this study.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2024-08-01</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.v14i4.pp3755-3767</dc:identifier><dc:identifier>10.11591/ijece.v14i4.pp3755-3767</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 14 No 4 (2024); 3755</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/29839/17495</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>