A neural network short term load forecasting model for the Greek power system

被引：218

作者：

Bakirtzis, AG ^{[1
]}

Petridis, V ^{[1
]}

Klartzis, SJ ^{[1
]}

Alexiadis, MC ^{[1
]}

Maissis, AH ^{[1
]}

机构：

[1] PUBL POWER CORP GREECE,XANTHI,GREECE

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1996年 / 11卷 / 02期

关键词：

load forecasting; Artificial Neural Networks; holiday modeling;

D O I：

10.1109/59.496166

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 development of an Artificial Neural Network (ANN) based short-term load forecasting model for the Energy Control Center of the Creek Public Power Corporation (PPC). The model can forecast daily load profiles with a lead time of one to seven days. Attention was paid for the accurate modeling of holidays. Experiences gained during the development of the model regarding the selection of the input variables, the ANN structure, and the training data set are described in the paper. The results indicate that the load forecasting model developed provides accurate forecasts.

引用

页码：858 / 863

页数：6

共 20 条

[1] ROLE OF WEATHER INPUTS IN SHORT-TERM FORECASTING OF ELECTRIC-LOAD [J].