Day-Ahead Short-Term Forecasting Electricity Load via Approximation

被引:4
|
作者
Khamitov, R. N. [1 ]
Gritsay, A. S. [1 ]
Tyunkov, D. A. [1 ]
Sinitsin, G. E. [2 ]
机构
[1] Omsk State Tech Univ, Omsk, Russia
[2] LLC Omsk Energy Retail Co, Elect Markets Dept, Omsk, Russia
关键词
NEURAL-NETWORK;
D O I
10.1088/1757-899X/189/1/012005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The method of short-term forecasting of a power consumption which can be applied to short-term forecasting of power consumption is offered. The offered model is based on sinusoidal function for the description of day and night cycles of power consumption. Function coefficients-the period and amplitude are set up is adaptive, considering dynamics of power consumption with use of an artificial neural network. The presented results are tested on real retrospective data of power supply company. The offered method can be especially useful if there are no opportunities of collection of interval indications of metering devices of consumers, and the power supply company operates with electrical supply points. The offered method can be used by any power supply company upon purchase of the electric power in the wholesale market. For this purpose, it is necessary to receive coefficients of approximation of sinusoidal function and to have retrospective data on power consumption on an interval not less than one year.
引用
收藏
页数:7
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