A new approach to load forecasting: using semi-parametric method and neural networks

Authors:
Abhisek Ukil;Jaco Jordaan
Affiliations:
Tshwane University of Technology, Pretoria, South Africa;Tshwane University of Technology, Pretoria, South Africa
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

Citing 1
Cited 1

Advanced Methods in Neural Computing

Advanced Methods in Neural Computing

Load forecasting with support vector machines and semi-parametric method

IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new approach to electrical load forecasting is investigated. The method is based on the semi-parametric spectral estimation method that is used to decompose a signal into a harmonic linear signal model and a non-linear part. A neural network is then used to predict the non-linear part. The final predicted signal is then found by adding the neural network predicted non-linear part and the linear part. The performance of the proposed method seems to be more robust than using only the raw load data.