Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2018.1429291
The price prediction for the energy market based on a new method
Homayoun Ebrahimian
; Department of Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Saeed Barmayoon
; Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Mohsen Mohammadi
; Department of Electrical Engineering, Payame Noor University (PNU), Tehran, Iran
Noradin Ghadimi
; Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Sažetak
Regarding the complex behaviour of price signalling, its prediction is
difficult, where an accurate forecasting can play an important role in
electricity markets. In this paper, a feature selection based on mutual
information is implemented for day ahead prediction of electricity prices,
which are so valuable for determining the redundancy and relevancy
of selected features. A combination of wavelet transform (WT) and a
hybrid forecast method is presented based on a neural network (NN).
Furthermore, an intelligent algorithm is considered for a prediction
process to set the proposed forecast engine free parameters based
NN. This optimisation process improved the accuracy of the proposed
model. To demonstrate the validity of this model, the Pennsylvania-New
Jersey-Maryland (PJM) electricity market is considered as a test case and
compared with some of the most recent price forecast methods. These
comparisons illustrate the effectiveness of the proposed strategy.
Ključne riječi
Feature selection; hybrid forecast engine; price forecast
Hrčak ID:
200675
URI
Datum izdavanja:
3.12.2018.
Posjeta: 2.051 *