Short-term load forecasting in an autonomous power system using artificial neural networks

被引：33

作者：

Kiartzis, SJ

Zoumas, CE

Theocharis, JB

Bakirtzis, AG

Petridis, V

机构：

[1] Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1997年 / 12卷 / 04期

关键词：

artificial neural networks; short-term load forecasting;

D O I：

10.1109/59.627863

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 based short-term load forecasting model for an autonomous power system. Problems encountered in data preparation, network structure definition and model's sensitivity to temperature, and suggested solutions are discussed. The proposed model can provide next week's load forecasts. Experiences obtained during the application of the model to predict daily load curves in the autonomous power system of the Greek island of Crete are presented.

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页码：1591 / 1596

页数：6

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