基于广义自回归条件异方差偏度峰度模型的风电功率预测方法  

Wind Power Forecasting Method Based on Generalized Autoregressive Conditional Heteroskedasticity With Skewness and Kurtosis Model

作　　者：陈昊 高山[2] 王玉荣[2] 张建忠[2] 

机构地区：[1]国网江苏省电力公司,江苏省南京市211102 [2]东南大学电气工程学院,江苏省南京市210096

出　　处：《中国电机工程学报》2017年第12期3456-3461,共6页Proceedings of the CSEE

基　　金：国家自然科学基金项目(51507031;51577025)~~

摘　　要：通过对风电功率时间序列条件偏度、条件峰度时变性的分析,提出一种基于广义自回归条件异方差偏度峰度模型的风电功率预测新方法。针对风电时间序列高阶条件矩时变性的检验问题,提出链式检验新方法。结合模型参数估计,提出一种实用化参数约束处理方法,提升了参数估计效率。基于江苏某风电场的实际数据,分析该风电时间序列的时变条件矩,并使用修正Gram–Charlier级数的拟极大似然估计获取GARCHSK模型参数。风电功率预测结果表明所提方法的可行性和有效性。By analyzing the time varying characteristics in the conditional skewness and kurtosis of wind power time series, the generalized auto-regressive conditional heteroskedasticity with skewness and kurtosis （GARCHSK） model was proposed as a novel wind power forecasting method. To test the time varying characteristics in the conditional moments of wind power time series, an efficient test, chain test, was proposed. By combining the parameter estimate of GARCHSK model, the practical processing method for parameter constraint was presented and the estimate efficiency was improved. Based on the historical practical wind power data of wind farms in Jiangsu province, the proposed GARCHSK wind power forecasting model was carried out and the time-varying conditional moments of wind power time series were analyzed. Employing the Quasi Conditional Maximum Likelihood Estimation （QCMLE） based on Gram-Charlier series, the parameters of GARCHSK were estimated. The forecasting result of GARCHSK wind power forecasting model shows the feasibility and effectiveness of the proposed method.

关 键 词：GARCHSK模型 时变偏度 时变峰度 链式检验 风电功率预测 

分 类 号：TM71[电气工程—电力系统及自动化]