Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method
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10.5120/17492-8011 |
Firas M Tuaimah and Huda Abdul M Abass. Article: Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method. International Journal of Computer Applications 100(1):41-45, August 2014. Full text available. BibTeX
@article{key:article,
author = {Firas M. Tuaimah and Huda M. Abdul Abass},
title = {Article: Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {100},
number = {1},
pages = {41-45},
month = {August},
note = {Full text available}
}
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.
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