Estimation Load Forecasting Based on the Intelligent Systems

  • Hanan A.R. Akkar Department of Electrical Engineering, University of Technology, Baghdad, IRAQ
  • Wissam H. Ali Department of Electrical Engineering, University of Technology, Baghdad, IRAQ
Keywords: Short term Load Forecasting, Artificial Intelligent AI, Neural network, Genetic

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.

Published
2018-04-22
How to Cite
Akkar, H., & Ali, W. (2018). Estimation Load Forecasting Based on the Intelligent Systems. Al-Nahrain Journal for Engineering Sciences, 21(2), 285-291. https://doi.org/10.29194/NJES21020285