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Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method

by Firas M. Tuaimah, Huda M. Abdul Abass
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 1
Year of Publication: 2014
Authors: Firas M. Tuaimah, Huda M. Abdul Abass
10.5120/17492-8011

Firas M. Tuaimah, Huda M. Abdul Abass . Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method. International Journal of Computer Applications. 100, 1 ( August 2014), 41-45. DOI=10.5120/17492-8011

@article{ 10.5120/17492-8011,
author = { Firas M. Tuaimah, Huda M. Abdul Abass },
title = { Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 1 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number1/17492-8011/ },
doi = { 10.5120/17492-8011 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:28:49.879497+05:30
%A Firas M. Tuaimah
%A Huda M. Abdul Abass
%T Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 1
%P 41-45
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper an investigation for the short term (up to 24 hours) load forecasting of the demand for the Iraqi Power System would be presented, using a Multiple Linear Regression (MLR) method. After a brief analytical discussion of the technique, the usage of mathematical models and the steps to compose the MLR model will be explained. As a case study, historical data consisting of hourly load demand, humidity, wind speed and temperatures of Iraqi electrical system will be used, to forecast the short term load. Two models will be presented; one for winter and the second for summer season. Algorithms implementing this forecasting technique have been programmed using MATLAB and applied to the case study. This study uses the linear static parameter estimation technique as they apply to the twenty four hour off-line forecasting problem.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Short Term Load forecasting (STLF) Multiple Linear Regression (MLR) Weather parameters.

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