Evaluating the Use of ANN Models for Short-Term Load Prediction

Abstract

The electrical short term load forecasting has been emerged as one of the most essential field of research for efficient and
reliable operation of power system in last few decades. It plays very significant role in the field of scheduling, contingency
analysis, load flow analysis, planning and maintenance of power system. This paper addresses a review on recently published
research work on different variants of artificial neural network in the field of short term load forecasting. In particular, the
hybrid networks which is a combination of neural network with stochastic learning techniques such as genetic algorithm(GA),
particle swarm optimization (PSO) etc. which has been successfully applied for short term load forecasting (STLF) is discussed
thoroughly.