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A Markov model of generator performance at the Kainji hydro-power station in Nigeria

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 4 (2023)

DOI
10.11591/ijece.v13i4.pp3585-3592
ISSN
2722-2578, 2088-8708
Published
2023-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The Kainji hydropower station is a seven turbo-alternator station that for many years served as the base load supply for the Nigerian power grid. Over 200,000 pieces of data about the performance of the machines were used to estimate values of the failure and repair rates for each machine and a Markov steady-state model of the plant was constructed to determine the probability output of the turbines. This result showed that Kaplan turbine (KT) 12 is prone to failure compared to any other KT unit in the hydropower plant. Also, the clusters of probability that define the system state due to the different output capacities of the units show that the hydropower plant has not performed to its maximum capacity, further evaluation shows that 60% of the KT machine units are operating which is consistent with the observed robustness of the output. The model not only conforms to observations but reasonably provide a means of studying the effects of different actions that may be taken to improve the performance of hydropower plant.

Collaboration network of the authors

8 authors · 18 co-authorship links · 15 across different organisations

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  • University of Ilorin
  • Federal University of Technology
  • Kwara State University
  • Achievers University
  • Federal University of Petroleum Resource Effurun
  • Landmark University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Olalekan OgunbiyiKwara State University1
Cornelius T. ThomasAchievers University1
Oludare Y. OgundepoFederal University of Petroleum Resource Effurun1
Isaac O. A. OmeizaLandmark University1
Jimoh AkanniUniversity of Ilorin1

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 Markov model of generator performance at the Kainji  hydro-power station in Nigeria</dc:title><dc:creator>Ale, Thomas Olabode</dc:creator><dc:creator>Olufeagba, Benjamin Jimi</dc:creator><dc:creator>Oyeleye, Mathew Olayinka</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;The Kainji hydropower station is a seven turbo-alternator station that for many years served as the base load supply for the Nigerian power grid. Over 200,000 pieces of data about the performance of the machines were used to estimate values of the failure and repair rates for each machine and a Markov steady-state model of the plant was constructed to determine the probability output of the turbines. This result showed that Kaplan turbine (KT) 12 is prone to failure compared to any other KT unit in the hydropower plant. Also, the clusters of probability that define the system state due to the different output capacities of the units show that the hydropower plant has not performed to its maximum capacity, further evaluation shows that 60% of the KT machine units are operating which is consistent with the observed robustness of the output. The model not only conforms to observations but reasonably provide a means of studying the effects of different actions that may be taken to improve the performance of hydropower plant.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-08-01</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.v13i4.pp3585-3592</dc:identifier><dc:identifier>10.11591/ijece.v13i4.pp3585-3592</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 4 (2023); 3585</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/27595/16642</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>