Research on Forecasting Method of GIC Caused by Gradual Commencement Magnetic Storm

Author

Pengyang Zhou ; Ying Wang ; Lianguang Liu

Author_Institution

Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China

fYear

2013

fDate

21-23 June 2013

Firstpage

1975

Lastpage

1978

Abstract

The mechanism of power grid GIC is complex and has multiple factors. The geomagnetic activity is one of the main factors. In this paper, by using the wavelet neural network, a forecasting model for GIC caused by gradual commencement magnetic storm is introduced. The GIC data and geomagnetic data monitored during the magnetic storms are the basic data of the model. The GIC data collected in Ling´ao nuclear power station, April 2006, is tested to detect the accuracy of the trained model. The analysis of forecasting results shows that the model can provide a comparatively accurate result for GIC in power grid.

Keywords

magnetic storms; neural nets; nuclear power stations; power engineering computing; power grids; wavelet transforms; GIC forecasting method; Lingao nuclear power station; geomagnetic activity; geomagnetic induced current; gradual commencement magnetic storm; power grid GIC mechanism; wavelet neural network; Autoregressive processes; Data models; Forecasting; Monitoring; Power grids; Predictive models; Storms; GIC; forecast; geomagnetically induced current; wavelet neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.516

Filename

6643435