MEDIUM TERM ELECTRICAL LOAD FORECAST OF ABUJA MUNICIPAL AREA COUNCIL USING ARTIFICIAL NEURAL NETWORK METHOD

Authors

  • AS Ashigwuike DEPARTMENT OF ELECTRICAL ELECTRONIC ENGINEERING, UNIVERSITY OF ABUJA, ABUJA FCT, NIGERIA
  • ARA Aluya TRANSMISSION COMPANY OF NIGERIA (TCN), OSOGBO, OSUN STATE, NIGERIA
  • JEC Emechebe FEDERAL RADIO CORPORATION OF NIGERIA, ABUJA FCT, NIGERIA
  • SA Benson DEPARTMENT OF ELECTRICAL ELECTRONIC ENGINEERING, UNIVERSITY OF ABUJA, ABUJA FCT, NIGERIA

Keywords:

Artificial Neural Network, Forecast, Load, Energy Demand, Capacity Allocation, Percentage error, Forecasting Accuracy.

Abstract

This paper presents a medium-term electric load forecast for Abuja Municipal Area Council (AMAC) distribution network based on Artificial Neural Network (ANN). The technique results are compared with that of a conventional method (Multiple Linear Regression method), for the same data. The ANN proposed method takes into account the effect of temperature, time, population growth rate and the activities of different regions of city areas regarding lifestyle and types of consumers. The data of monthly to annual peak values are collected for the period from 2012 to first quarter of 2018. Hence, the Artificial Neural Network method presented a result with average MAPE of 0.00197 while the multiple linear regression having an average MAPE of 0.004545. The R-Value deviation was 8.06% and 34.42% for ANN and MLR methods respectively.

 

http://dx.doi.org/10.4314/njt.v39i3.28

Published

2020-06-22

Issue

Section

Computer, Telecommunications, Software, Electrical & Electronics Engineering