Artificial neural networks applied to short term load diagram prediction
被引:0
作者:
Hodzic, Nermin
论文数: 0引用数: 0
h-index: 0
机构:
Univ Tuzla, Univ Ctr Distance Educ Dev, Tuzla, Bosnia & HercegUniv Tuzla, Univ Ctr Distance Educ Dev, Tuzla, Bosnia & Herceg
Hodzic, Nermin
[1
]
Konjic, Tatjana
论文数: 0引用数: 0
h-index: 0
机构:
Univ Tuzla, Fac Elect Engn, Tuzla, Bosnia & HercegUniv Tuzla, Univ Ctr Distance Educ Dev, Tuzla, Bosnia & Herceg
Konjic, Tatjana
[2
]
Miranda, Vladimiro
论文数: 0引用数: 0
h-index: 0
机构:
Univ Porto, Res Inst, Oporto, PortugalUniv Tuzla, Univ Ctr Distance Educ Dev, Tuzla, Bosnia & Herceg
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.
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页码:219 / +
页数:2
相关论文
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[11]
SACHDEO MS, 1977, IEEE T POWER APPARAT, V90, P697