Short term load forecasting investigations of Egyptian electrical network using ANNs

被引：2
|
作者：
Salama, H. A.
El-Gawad, A. F. Abd
Mahmoud, H. M.
Mohamed, E. A.
Saker, S. M.
机构：
来源：
2007 42ND INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, VOLS 1-3 | 2007年
关键词：
short-term load forecasting; ANN and load curve;
D O I：
10.1109/UPEC.2007.4469008
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Load forecasting is the one of the most essential role of electric power systems as it absolutely shares the system opportunity. It is responsible for repairing the planning for future. Artificial Neural Network's (ANNs) models have implemented to produce accurate results for short-term load forecasting with time lead being few minutes, hour, 24 hours of a day extending to a week. In this paper, load forecasting situation of Egyptian Power Utility has been investigated to define its problems and specify the most applicable method of load forecasting suitable for its load curve growth. Extensive studies have been done to improve the performance of the proposed ANN. The results are compared with the forecasted loads calculated with other techniques by the Egyptian Electrical Utility.
引用
收藏
页码：550 / 555
页数：6
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