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

Abstract

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 short term load forecasting other methods are also used for STFL.

An Experimental Fuzzy Inference System for Global Grid Electricity Peak Power Load Forecasting Third Core Module of First Console on G2P3S

“…Literature review summary (more than 5 studies in color background) In this review, it was understood that forecasting studies on the electrification systems were usually grouped according to their time horizons in four groups (i.e. real time/very short term [24], short term [25], medium term [26] and long term [27]) studies (see [28]). There were more than 40 documents in the long term electricity demand (e.g.…”

G<sup>2</sup>EDPS's First Module & Its First Extension Modules

“…Moreover, the power systems forecasting horizons in the literature were diversified as the real time/very short term (minutes to a day) (e. g. [36]), the short term (a day to a week) (e. g. [37]), the medium term (a week to a year) (e. g. [38]) and the long term (more than a year often upto ten years) (e. g. [39]) (see [40]). Hence, only the long term studies were investigated in detail in this review.…”