scholarly journals Three Component Weather-Sensitive Load Forecast using Artificial Neural Network

2021 ◽  
Vol 26 (2) ◽  
pp. 143-149
Author(s):  
Yamama Al-Nasiri ◽  
Majid Al-Hafidh
2020 ◽  
Vol 39 (3) ◽  
pp. 860-870
Author(s):  
E.C. Ashigwuike ◽  
A.R.A. Aluya ◽  
J.E.C. Emechebe ◽  
S.A. Benson

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


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