基于LHS与BR的风电出力场景分析研究

Scenario analysis of wind power output based on LHS and BR

为了有效分析风电出力的场景特征,文中基于风速的不确定特性,构建基于拉丁超立方抽样(LHS)与后向缩减法(BR)的场景分析模型,为快速分析任意时段的风电出力提供重要依据。文中首先分析风速特征,阐述风速符合的威布尔(Weibull)分布;其次拟合各时刻Weibull分布的参数值,提出基于LHS的场景生成方法;然后构建BR场景缩减模型,使得到的若干条曲线能够更大程度表征原始场景的变化特征;最后,通过算例分析验证文中所提方法在紧密性(CP)、间隔性(SP)以及戴维森堡丁指数(DBI)上均优于传统的K-means聚类算法,即缩减后的场景能更好地代替原始场景。

In order to effectively analyze the scenario characteristics of wind power output,scenario analysis model based on Latin hypercube sampling(LHS)and backward reduction(BR)for the uncertain characteristics of wind speed is constructed.The model provides an important basis for rapid analysis of wind power output at any time.Firstly,wind speed characteristics are analyzed,and Weibull distribution of wind speed is introduced.Secondly,the parameter values of the Weibull distribution at each moment are calculated and a set of scenario generation methods based on LHS are proposed.Thirdly,the model of BR is used to reduce the scenarios,so that the several curves obtained can represent the change characteristics of the original scenario to greater extent.Finally,the example analysis proves that the proposed method is better than the traditional K-means clustering algorithm in compactness(CP),separation(SP)and Davies-Bouldin index(DBI),which means that the reduced scenario can better replace the original scenario.