Data Mining for Electrical Load Forecasting In Egyptian Electrical Network

Abstract

The paper presents the design of a model for forecasting long-term electricity load. The model uses data mining techniques. The paper defines the load forecast and the summary of the most important factors affecting the load forecast in Egyptian electricity network. The steps needed for the knowledge discovery process is implemented to the time series data. Preprocessing the data in order to detect the missing value, odd value, outliers and normalize data. The output from the preprocessing step is fed into multiple regression or neural network to predict the coefficient parameters. Comparison between different cases using different techniques is indicated