Title of article :
LONG TERM LOAD FORECASTING OF EGYPTIAN POWER NETWORK BY COMPUTATIONAL INTELLIGENCE
Author/Authors :
Othman, S. AI-Azhar University - Faculty of Engineering, Egypt , Mahmoud, H. Egyptian Electricity Hold Company, Egypt , Eldestawy, K.H. Ministry of Electricity and Energy, Egypt
Abstract :
load forecasting has influence on security and efficiency for electric power systems. This paper describes electrical load forecasting using computational intelligence Methods such as Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS), the data must be treated before applied, and the inconsistent attributes will be excluding. From the experimental results the two methods are suitable for forecasting peak load but ANFIS method is better than ANN. .
Journal title :
Journal of Al Azhar University Engineering Sector (JAUES)
Journal title :
Journal of Al Azhar University Engineering Sector (JAUES)