Anomalous STLF for Indonesia power system using Artificial Neural Network

This paper presents the research results of Short Term Load Forecasting (STLF) on the power distribution systems in the West Java, Indonesia. Forecasting is executed using Artificial Neural Network (ANN), with back propagation algorithms. Experiments conducted on the data load holidays (anomalous load). To obtain optimal prediction accuracy, then conducted the experiment by changing the number of input learning and learning rate value. The simulation results verify that the ANN method performs more accurate than the conventional method used Indonesia Power Company. Results of this study are expected to be used as an alternative method based on soft computing.