Volume 2, Issue 1

A Comparative study on Short term load forecasting using BPNN and Extreme Learning Machine.

Author

J.C Pati1, K.K Mishra1, S.K Patnaik2

Abstract

Short term load forecasting plays a very important role in planning and
operation of electrical utilities. Accurate forecast of electrical load is highly
essential for Energy Management System. Neural network uses artificial
intelligence by adjusting weights and minimizing the error. The learning
speed of feed forward neural network is very slow mainly due to two
reasons :- i) slow gradient-based learning algorithms to train neural
networks, ii) all the parameters of the networks are tuned iteratively by
using such learning algorithms. This paper presents a comparative study of
back propagation algorithm and an extremely fast learning technique. A
final optimise set of weight are used for prediction of actual load with
greater accuracy and less time using ELM.

DOI

https://doi.org/10.62226/ijarst20130152

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