Electricity price short-term forecasting using artificial neural networks

被引：335

作者：

Szkuta, BR ^{[1
]}

Sanabria, LA ^{[1
]}

Dillon, TS ^{[1
]}

机构：

[1] La Trobe Univ, Appl Comp Res Inst, Melbourne, Vic, Australia

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1999年 / 14卷 / 03期

关键词：

artificial neural networks; system marginal price; electricity market;

D O I：

10.1109/59.780895

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents the System Marginal Price (SMP) short-term forecasting implementation using the Artificial Neural Networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with backpropagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP.

引用

页码：851 / 857

页数：7