A novel combination model for wind power forecasting with error evaluation parameter based on cross entropy theory

作者：Yi Tang; Qian Sha; Ning Chen; Lingzhi Zhu

来源：2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, CYBER 2012, 2012-05-27 to 2012-05-31.

DOI：10.1109/CYBER.2012.6392559

• Combination models
• Cross entropy theories
• Error evaluation
• Power predications
• Prediction precision
• Safety and stabilities
• Wind power forecasting
• Wind power predictions

Wind power predication is significant for the safety and stability of power system operation. Due to the power forecasting single model or combination model without considering the information fusion and the influence of forecasting error on power dispatching, forecasting results are not accurate enough. In the paper, a novel combination model for wind power forecasting with error evaluation parameter based on cross entropy theory is proposed. Wind power prediction is seen as information fusion, and the weights of different wind power prediction methods is set according to their cross levels. Besides, an error evaluation parameter is also proposed to estimate the different influences of positive and negative error on power scheduling. Application results in an actual wind farm show that the cross levels of different wind power prediction methods can be identified effectively and prediction precision is improved by the proposed method.

• 出版日期2012
• 单位东南大学