基于空间相关法的风电场风速多步预测模型  

Multi-step Ahead Wind Speed Forecasting Model Based on Spatial Correlation and Support Vector Machine

作　　者：陈妮亚[1] 钱政[1] 孟晓风[1] 孟凯峰 

机构地区：[1]北京航空航天大学仪器科学与光电工程学院,北京100191 [2]中能电力科技开发有限公司,北京100191

出　　处：《电工技术学报》2013年第5期15-21,共7页Transactions of China Electrotechnical Society

基　　金：国家自然基金创新群体项目资助(61121003)

摘　　要：风电场风速的准确预测对于评估风电场接入电网的安全性与经济性有重要意义。本文基于空间相关法与支持向量机方法,提出了一种新的风速多步预测混合模型。文中首先提出使用相关系数作为判据的方法,选择模型的最优输入参数,以建立精确的分风向空间相关模型。在详细分析风向对预测精度的影响后,结合支持向量机(SVM)方法,以消除风向变化对空间相关模型的不利影响,最终得到预测精度高、性能稳定的混合模型。文中使用某风电场的实测数据进行建模验证,并与几种经典的风速预测算法相比较,结果证实该混合模型的预测精度有显著提高。Accurate wind speed forecasting is necessary for evaluating the safety and economy of the large scale wind farm integration.In this paper,a new multi-step ahead wind speed forecasting model is presented based on spatial correlation and support vector machine（SVM） method.First,a wind direction oriented spatial correlation model is established,of which the optimized input vectors are determined by correlation coefficient.Then in order to eliminate the influence of variable wind direction,SVM method is applied to combine with the former spatial correlation model based on an accurate analysis of how forecast error depends on wind direction.The calculation results,which are obtained by measured data from a wind farm,indicate that the proposed spatial-SVM model has a better performance in forecasting accuracy comparing to the basic SVM model and other classical forecasting models.

关 键 词：风速预测 空间相关 支持向量机 混合模型 

分 类 号：TM614[电气工程—电力系统及自动化]