Conditional probabilistic modeling of wind power forecast error

被引：0

作者：

Ye, Yida ^{[1
]}

Lu, Zongxiang ^{[1
]}

Qiao, Ying ^{[1
]}

Ye, Xi ^{[1
]}

Hu, Wei ^{[2
]}

Wang, Ruoyang ^{[3
]}

Wu, Linlin ^{[3
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

[2] Hainan Elect Power Corp, Haikou 570203, Peoples R China

[3] State Grid Jibei Elect Power Co Ltd, Res Inst, Beijing 100045, Peoples R China

来源：

2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM) | 2016年

关键词：

Wind power; forecast error; conditional probabilistic model;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The increasing penetration of new variable generations in power systems necessitates the modeling of the stochastic and variable characteristics, especially the modeling of wind power forecast error. A conditional probabilistic dependent method of modeling wind power forecast error of one single wind farm and multiple wind farms is presented in this paper, providing a range of potential forecast error for a given confidence level. Furthermore, a distribution generation algorithm of power forecast error based on Monte Carlo algorithm and genetic algorithm is proposed by applying the historical data and rank correlation of forecast error in multiple wind farms. Finally, the proposed method is verified in the case study by comparison of the conditional probabilistic model and the unconditional probabilistic model.

引用

页数：5

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