Case study of Short Term Load Forecasting for weekends

Abstract

This paper presents the Short Term Load Forecasting (STLF) to predict the demand in the future. STLF is a method used to predict a day ahead, 24 hours load demand. Two factors were considered in this forecasting: time and also the temperature of the day. The main objective of this project is to analyze the profile or pattern of the forecasted load and also to predict the load demand during weekends. Artificial Neural Network (ANN) in MATLAB software was used in solving the forecasting problem. The percentage of average error was determined by using the Mean Absolute Percentage Error (MAPE).