Short Term Load Forecasting Solution Methodologies: Literature Review 2013 Survey Paper

This paper presents the comprehensive study of the solution methodologies used so for the for Short Term Load Forecasting, these methodologies characterized by the methods and models as classical and artificial intelligent techniques .Statistical Technique includes Similar day approach, Linear regression, Time series method ,State space and intelligent techniques includes Artificial Neural Network (ANN),SVM(Support Vector Machine Regression), Fuzzy logic, SO(Particle Swarm Optimization),GA(Genetic Algorithm),ACA(Ant Colony Algorithm) and also there are hybrid techniques like Fuzzy and ANN, Adaptive neural fuzzy interface system, LS-SVM Optimized by Bacterial Colony Chemotax is Algorithm and GA based SVM and the last one is the Machine From this survey we show the importance of the short term load forecasting in operation and control and we conclude that the more promising method used for STFL is ANN(Artificial Neural Network) And A novel network Support Vector Machine and Ada Boost Regression techniques has great potential for the