风电场风能资源评估的测量—关联—预测方法综述

Overview of Wind Resource Measure-Correlate-Predict Methods for Wind Farms

风电场风能资源评估的重要目的是为了得到风电场测风塔在风电机组轮毂高度的长期风能资源储量,测量—关联—预测(MCP)是针对缺少测风塔长期实测数据所提出的用于预测风电场长期风速、风向的重要数学方法。文中首先阐述了MCP方法基本的原理、假设与步骤,详细地总结了MCP过程中所需要的风资源数据,分析了数据分组、参数选择、风切变、时间分辨率等因素对预测过程的影响。着重对几种典型MCP预测方法构建模型的基本思想及常见变形进行了分类和描述,并对各类方法的主要优缺点和适用条件进行了分析和评述,探讨了多参考站组合预测中的权重分配方式。最后,结合MCP的发展现状和需求,对未来MCP的发展提出了展望。

One of the primary goals of wind resource assessment is to obtaining long-term wind resource potential at the hub height of wind turbines.The measure-correlate-predict（MCP）method is an important mathematical method for estimating the long-term wind speed and direction where the long-term measuring data is not available.Firstly,the basic principle,assumptions and procedure of MCP method are introduced.The data required in the MCP process are summarized in detail.Then,the influences of the data grouping,parameter selection,wind shear,and time resolution on the prediction process are analyzed.Moreover,the basic logic and common transformations of several typical MCP methods are classified and described.The advantages and disadvantages and the applicability of different MCP methods are analyzed and evaluated.The weight distribution way in the multiple reference station combination forecast is discussed.Finally,future developments and further investigations of MCP methods are discussed.