LEAST SQUARE REGRESSION METHOD FOR LOAD MANAGEMENT IN ELECTRICITY DISTRIBUTION NETWORK OF A 33 KV FEEDER AT FEDERAL UNIVERSITY OF AGRICULTURE ABEOKUTA, NIGERIA
Mots-clés :
Load management, Load forecasting, Least square regression, Adjusted coefficient of determination and Mean absolute percentage error, NigeriaRésumé
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
##plugins.themes.default.displayStats.downloads##
##plugins.themes.default.displayStats.noStats##
Téléchargements
Publiée
2018-12-31
Numéro
Rubrique
Engineering
Comment citer
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
