基于交叉熵理论的风电功率组合预测方法

风电功率预测对电力系统的调度和安全稳定运行具有重要的意义。针对目前风电功率预测方法过分依赖参考样本的问题,利用信息融合技术,建立了一种基于交叉熵理论的风电功率组合预测方法,将风电功率组合预测看作信息融合问题,利用交叉熵理论判断各预测方法的相互交叉程度,按支撑度大小变化动态设置权重。阐述了所提方法的基本思想和主要实现方法,针对某实际风电场的算例结果表明,新方法能够有效识别预测方法交叉度,提高了风电功率预测精度。

A Combination Method for Wind Power Predication Based on Cross Entropy Theory

Wind power predication is significant for power system dispatching and safe-stable operation.For solving the issue that wind power prediction depends on reference samples deeply,a new combined method of wind power prediction based on cross entropy theory was proposed according to information fusion technique.In the method,wind power prediction was seen as information fusion,and the cross entropy theory was applied to judge the cross degrees among different prediction methods.The weights of different wind power prediction methods was dynamically set according to their cross levels.The basic idea and implementation details of the proposed method were presented.Application results in an actual wind farm show that the proposed method can effectively identify the cross degrees among different prediction methods and improve prediction precision.