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Reseach Article

Investigation of One Day Ahead Load Forecasting for Iraqi Power System

by Mohammed Abdulla Abdulsada, Mohanad Azeez Joodi, Firas M. Tuaimah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 1
Year of Publication: 2017
Authors: Mohammed Abdulla Abdulsada, Mohanad Azeez Joodi, Firas M. Tuaimah

Mohammed Abdulla Abdulsada, Mohanad Azeez Joodi, Firas M. Tuaimah . Investigation of One Day Ahead Load Forecasting for Iraqi Power System. International Journal of Computer Applications. 163, 1 ( Apr 2017), 24-29. DOI=10.5120/ijca2017913450

@article{ 10.5120/ijca2017913450,
author = { Mohammed Abdulla Abdulsada, Mohanad Azeez Joodi, Firas M. Tuaimah },
title = { Investigation of One Day Ahead Load Forecasting for Iraqi Power System },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 1 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 24-29 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2017913450 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:08:59.077941+05:30
%A Mohammed Abdulla Abdulsada
%A Mohanad Azeez Joodi
%A Firas M. Tuaimah
%T Investigation of One Day Ahead Load Forecasting for Iraqi Power System
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 1
%P 24-29
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

Power stations must supply the electrical load demands to achieve optimal power system operation. To meet the future load, the power system dispatcher use load forecasting techniques to schedule unit generation resources. In this paper the short term load forecasting (STLF) using feed forward Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) techniques for Iraqi power system (IPS) is presented. The ANN and MLR techniques are used to forecast one day ahead load for summer and winter season. The ANN gives a very small mean absolute percentage error (MAPE) compared with MLR but it takes a longer time for training process.

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Index Terms

Computer Science
Information Sciences


Short Term Load Forecasting Artificial Neural Network Multiple Linear Regression Mean Absolute Percentage Error.