Clustering based short term load forecasting using artificial neural network

Abstract

A novel clustering based Short Term Load Forecasting (STLF) using Artificial Neural Network (ANN) to forecast the 48 half hourly loads for next day is presented in this paper. The proposed architecture uses the historical load and temperature to forecast the next day load. It is trained using back propagation algorithm and tested. The daily average load of each day for all the training patterns and testing patterns is calculated and the patterns are clustered using a threshold value between the daily average load of the testing pattern and the daily average load of the training patterns. The results obtained from neural network are presented and the results show that the clustering based approach is more accurate. ©2009 IEEE.