Methods and Prospects for Probabilistic Forecasting of Wind Power

被引：0

作者：

Wu W. ^{[1
,2
]}

Qiao Y. ^{[1
,2
]}

Lu Z. ^{[1
,2
]}

Wang N. ^{[3
]}

Zhou Q. ^{[3
]}

机构：

[1] Department of Electrical Engineering, Tsinghua University, Beijing

[2] State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing

[3] Wind Power Technology Center of Gansu Electric Power Company, Lanzhou

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2017年 / 41卷 / 18期

关键词：

Modeling of forecasting error; Probabilistic forecasting; Uncertainty; Wind power forecasting;

D O I：

10.7500/AEPS20160914002

中图分类号：

学科分类号：

摘要：

Prediction intervals or distribution functions of wind power in the future can be provided through probabilistic forecasting of wind power. Relevant research in China is still at the early stage. This paper gives a comprehensive review on the basic approaches, typical patterns and key problems in probabilistic forecasting of wind power. Firstly, the definition of probabilistic forecasting is presented and its applicable problems are summarized. Secondly, two different classification methods are introduced: conditional classification method and parametric classification method. New algorithms and evaluation indices used in probabilistic forecasting are also described. Finally, according to the-state-of-the-art of probabilistic forecasting, the shortcomings of error analysis and the insufficiency of probabilistic forecasting in combining with the power system, the future key issues and the research content which needs further exploration are summarized. © 2017 Automation of Electric Power Systems Press.

引用

页码：167 / 175

页数：8

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