Artificial neural networks applied to short term load diagram prediction

被引：0

作者：

Hodzic, Nermin ^{[1
]}

Konjic, Tatjana ^{[2
]}

Miranda, Vladimiro ^{[3
]}

机构：

[1] Univ Tuzla, Univ Ctr Distance Educ Dev, Tuzla, Bosnia & Herceg

[2] Univ Tuzla, Fac Elect Engn, Tuzla, Bosnia & Herceg

[3] Univ Porto, Res Inst, Oporto, Portugal

来源：

NEUREL 2006: EIGHT SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, PROCEEDINGS | 2006年

关键词：

artificial neural networks; load diagram; short term load forecast;

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：

Neural networks have broad applicability to real power system problems. One of the areas in power system with huge interest in appliance of neural networks is load forecasting. In this paper the neural networks were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 44 day period. The artificial neural networks showed as a good nonlinear approximator, giving promising results. The main objective of the presented work is to interest power companies in the Region for possible practical implementations.

引用

页码：219 / +

页数：2

共 14 条

[1] Baumann T., 1994, P ISAP 94 MONTP, P445
[2] *CIGRE, 1992, ELECTRA, P69
[3] CZERNICHOW T, 1995, P ICNN 95, P89
[4] DEMUTH H, 1998, NEURAL NETWORKS TOOL
[5] KONJIC T, 2001, P 2 EUR C RISK MAN P
[6] KONJIC T, 2003, THESIS U TUZLA BIH
[7] KROSE B, 1996, INTRO NERUAL NETWORK
[8] MIRANDA V, 2001, IEEE PES 2001 WINT M
[9] ELECTRIC-LOAD FORECASTING USING AN ARTIFICIAL NEURAL NETWORK
PARK, DC
ELSHARKAWI, MA
MARKS, RJ
ATLAS, LE
DAMBORG, MJ
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1991, 6 (02) : 442 - 449
[10] Heterogeneous artificial neural network for short term electrical load forecasting
Piras, A
Buchenel, B
Jaccard, Y
Germond, A
Imhof, K
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1996, 11 (01) : 397 - 402

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