You are in:Home/Publications/" Long Term Load Forecasting for The Egyptian Network Using ANN And Regression Models " ,21st International Conference on Electricity Distribution CIRED conference , 6 - 9 June, Frankfurt , Paper no. 0043, 2011

Prof. Wagdy Mohamed Mansour :: Publications:

Title:
" Long Term Load Forecasting for The Egyptian Network Using ANN And Regression Models " ,21st International Conference on Electricity Distribution CIRED conference , 6 - 9 June, Frankfurt , Paper no. 0043, 2011
Authors: W. M. Mansour, Mohamed M. Salama, Hassan M. Mahmoud, Ahmed T. Gharib
Year: 2011
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available
Abstract:

The major concern for every electrical utility is the ability to provide reliable and uninterrupted service to their customers The challenge becomes more significant with the fast and sharp increasing need for electric energy in the fast developing countries such as Egypt. Load forecasting is mandatory for planning, operation and control of power system. This paper concerns with long term load forecasting. This study presents a comparison between two models when applied to the Egyptian unified network, these models are Artificial Neural Network (ANN) model and regression model. To improve forecasting accuracy of the model we apply data preprocessing techniques. Forecasting capability of each approach is evaluated by calculating two separate statistical evaluations of the Mean Absolute Percentage Error (MAPE) and the Average Absolute Percentage Error (AAVE) .

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus