Artificial Neural Network based Monthly Load Curves Forecasting

被引：0
|
作者：
Barbulescu, Constantin [1 ]
Kilyeni, Stefan [1 ]
Deacu, Antheia [1 ]
Turi, Gabriel Mihai [1 ]
Moga, Mirela [1 ]
机构：
[1] Politehn Univ Timisoara, Power Syst Dept, Power Syst Anal & Optimizat Res Ctr, Timisoara, Romania
来源：
2016 IEEE 11TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI) | 2016年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The monthly load curve forecasting problem is discussed, being tackled using artificial neural networks (ANN). Authors are proposing an enhanced algorithm that includes nonlinear optimization techniques, such as the conjugate gradient. Thus, a software-tool has been developed. Case study refers to a real distribution network operator from the Western part of Romanian Power System.
引用
收藏
页码：237 / 242
页数：6
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