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Vol. 161, Issue 12, December 2013, pp. 241-246

 

Bullet

 

Study on Wind Power Forecasting Based on ISODATA
 
1 Gu Bo, 2 An Chao, 1 Ren Yan, 1 Li Yanpin

1 School of electric power, North China University of Water Conservancy and Electric Power, Zhengzhou, Henan, 450011, China

2 Yellow River Engineering Consulting Co., Ltd, Zhengzhou, Henan, 450003, China
Tel.: 13592597463
E-mail:gb1982@ncwu.edu.cn

 

Received: 17 August 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems

 

Abstract: The short-term prediction of wind power generation is of great significance to the security and stability of grid-connected wind power system. the principle and calculation steps of iterative self-organizing data analysis (ISODATA) is presented, which is used for clustering numerical weather prediction data (NWP) in history, in order to gather weather prediction data with numerical similarity to a class. According to the numerical weather prediction data, a BP neural network model has been constructed, to train the BP neural network and to predict wind power, with both clustered and raw data. The predicted results show that, the predictive accuracy of the BP neural network model which employs the clustering algorithm of ISODATA is better than that of itself.

 

Keywords: Wind power prediction, Numerical Weather Prediction (NWP), Iterative Self-organizing Data Analysis (ISODATA), BP neural network.

 

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