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Estimation Load Forecasting Based on the Intelligent Systems

Hanan A.R. Akkar --- Wissam H. Ali

AL-NAHRAIN JOURNAL FOR ENGINEERING SCIENCES مجلة النهرين للعلوم الهندسية
ISSN: 25219154 / eISSN 25219162 Year: 2018 Volume: 21 Issue: 2 Pages: 285-291
Publisher: Al-Nahrain University جامعة النهرين

Abstract

The daily peak load forecasting for the next day is the basic operation of generation scheduling. The approach of using ANN methodology alone is limited which has generated interest to explore hybrid system. In this paper a search of genetic programming to a short term load forecasting is presented. A genetic architecture with the fitness normalization has been used to find as optimum data peak load of Baghdad city. The optimize data applied to the ANN to be trained and tested to estimate the daily peak load of Baghdad city. Different cases for load forecasting are considered with the aid of MATLAB 7 package to get the estimation of the next day. So an improvement method of genetic optimization is proposed to get a better solution for the load estimation rather than artificial neural network.

Keywords

Short term Load Forecasting --- Artificial Intelligent AI --- Neural network --- Genetic