LEAST SQUARE REGRESSION METHOD FOR LOAD MANAGEMENT IN ELECTRICITY DISTRIBUTION NETWORK OF A 33 KV FEEDER AT FEDERAL UNIVERSITY OF AGRICULTURE ABEOKUTA, NIGERIA

Authors

  • Adebisi O. I. Department of Electrical and Electronics Engineering, Moshood Abiola Polytechnic, Abeokuta, Ogun State, Nigeria Author
  • Adejumobi A. I. Department of Electrical and Electronics Engineering, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria Author
  • Okoye F. E. Department of Electrical and Electronics Engineering, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria Author
  • Jokojeje R. A. Department of Electrical and Electronics Engineering, Moshood Abiola Polytechnic, Abeokuta, Ogun State, Nigeria Author

Keywords:

Load management, Load forecasting, Least square regression, Adjusted coefficient of determination and Mean absolute percentage error, Nigeria

Abstract

A stabilized electricity power system requires that its demand matches its supply. However, in a developing nation such as Nigeria, demand for electric power is continuously growing without comminserate supply s need. Consequently, load management is used to manage this inadequacy. One credible alternative in addressing this shortfall is load forecasting. This research work presents the least square regression method for load management in electricity distribution network using the Federal University Abeokuta (FUNAAB) 33
kV feeder as a case study. Using the five years (2012-2016) load data collected from 132/33 kV Transmission Station at Gboniyi, Abeokuta, Ogun State on the sample network, a polynomial regression model was developed 

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Published

31-12-2018

How to Cite

LEAST SQUARE REGRESSION METHOD FOR LOAD MANAGEMENT IN ELECTRICITY DISTRIBUTION NETWORK OF A 33 KV FEEDER AT FEDERAL UNIVERSITY OF AGRICULTURE ABEOKUTA, NIGERIA. (2018). FULafia Journal of Science and Technology , 4(2), 87-93. https://lafiascijournals.org.ng/index.php/fjst/article/view/113

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