Wind power forecasting uncertainty and unit commitment

被引：269

作者：

Wang, J. ^{[1
]}

Botterud, A. ^{[1
]}

Bessa, R. ^{[2
,3
]}

Keko, H. ^{[2
,3
]}

Carvalho, L. ^{[2
,3
]}

Issicaba, D. ^{[2
,3
]}

Sumaili, J. ^{[2
,3
]}

Miranda, V. ^{[2
,3
]}

机构：

[1] Argonne Natl Lab, Argonne, IL 60439 USA

[2] Univ Porto, Fac Engn, INESC Porto, P-4200465 Oporto, Portugal

[3] Univ Porto, Fac Engn, FEUP, P-4200465 Oporto, Portugal

来源：

APPLIED ENERGY | 2011年 / 88卷 / 11期

关键词：

Electricity markets; Forecasting; Dispatch; Stochastic optimization; Unit commitment; Wind power; SECURITY;

D O I：

10.1016/j.apenergy.2011.04.011

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：

In this paper, we investigate the representation of wind power forecasting (WPF) uncertainty in the unit commitment (UC) problem. While deterministic approaches use a point forecast of wind power output, WPF uncertainty in the stochastic UC alternative is captured by a number of scenarios that include cross-temporal dependency. A comparison among a diversity of UC strategies (based on a set of realistic experiments) is presented. The results indicate that representing WPF uncertainty with wind power scenarios that rely on stochastic UC has advantages over deterministic approaches that mimic the classical models. Moreover, the stochastic model provides a rational and adaptive way to provide adequate spinning reserves at every hour, as opposed to increasing reserves to predefined, fixed margins that cannot account either for the system's costs or its assumed risks. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：4014 / 4023

页数：10

共 27 条

[1] A new spinning reserve requirement forecast method for deregulated electricity markets [J].