Application of Genetic Algorithm Solution Approach to Voltage Drop Issues on 33 kV/11 kV Injection Feeders: A Case Study of Ogbomoso, South West, Nigeria

Okelola, M. Olajide and Olabode, E. O. (2019) Application of Genetic Algorithm Solution Approach to Voltage Drop Issues on 33 kV/11 kV Injection Feeders: A Case Study of Ogbomoso, South West, Nigeria. In: Current Research in Science and Technology Vol. 1. B P International, pp. 18-30. ISBN 978-93-89246-65-0

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Abstract

The place of good quality and quantity of electricity supply by electric power provider in national
growth cannot be underestimated. But, sadly the quantity and quality of electricity in most third world
countries such as Nigeria is plagued by quite a number of power quality disturbances and technical
losses inherent within the system. Voltage drop affects the quantity of available electricity and it is a
major concern of electric power providers as it challenged their sole responsibility of supplying
customers with the required voltage level at all times. Surprisingly, the causes and effects of voltages
drops on 33kV/11kV transmission systems have not been extensively looked at in Nigeria. This paper
presents application of genetic algorithm solution approach to voltage drop issues on 33kV/ 11kV
Injection feeders: A case study of Ogbomoso, South West, Nigeria. The result of the analysis showed
that the receiving end voltage is of low proportion compared to the sending end voltage. The
parametric modeling of voltage drop revealed several causes of voltage drop in the study area.
Different cable sizes were used to mitigate the effect voltage drop, it was discovered that, to attain
minimum voltage drop in this station, the 65 mm2 cable used has to be augmented to 85 mm2 or
reduce to 50 mm2 while the number of the injection stations should be increase.

Item Type: Book Section
Subjects: Academic Digital Library > Multidisciplinary
Depositing User: Unnamed user with email info@academicdigitallibrary.org
Date Deposited: 18 Nov 2023 05:35
Last Modified: 18 Nov 2023 05:35
URI: http://publications.article4sub.com/id/eprint/2857

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