摘要
对风电场风速进行较准确预测可以调整调度计划,有效减轻风电对整个电网的不利影响。文章将小波技术和神经网络相结合对风速进行短期预测。先对原始风速数据进行小波分解,再针对各小波分量分别建立BP神经网络模型进行预测,最后通过小波重构得到原始风速预测值。仿真结果表明,所提方法能够有效地提高风速预测精度。
Based on accurate forecasting of wind speed,the wind generating plan can be efficiently accommodated to mitigate the impaction from instable wind power on grids.A new forecasting method composed by wavelet technology and neural network is proposed in the paper.The original wind speed sequences are decomposed with wavelet analysis technology firstly.Then every wavelet components are separately forecasted with corresponding BP neural network models.Finally,the forecasting results of original wind speed series are achieved by using wavelet reconstruction.The simulation results prove that this method is capable of improving forecasting precision.
出处
《铜陵学院学报》
2012年第4期107-109,共3页
Journal of Tongling University
关键词
风速预测
神经网络
小波分解
预测精度
wind speed forecasting
neural network
wavelet decomposition
forecasting precision
