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Wind power forecasting uncertainty and unit commitment

delete2011-11-01
delete279
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王娟 封面图
王娟 (Jun Wang) *
A
Audun Botterud
R
Ricardo J. Bessa
H
Hrvoje Keko
L
Leonel Carvalho
D
Diego Issicaba
J
Jean Sumaili
M
Miranda, V.
DOI:10.1016/j.apenergy.2011.04.011delete
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摘要

摘要

En 中文
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.
Keyword:
Electricity markets
Forecasting
Dispatch
Stochastic optimization
Unit commitment
Wind power
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期刊

Applied Energy 封面图
Applied Energy
IF:
11
论文数:
2.6W
被引数:
17.8W

机构

A
Argonne National Laboratory
学者数:
1.1W
论文数: 9.2K
被引数: 3.8W
U
united states department of energy (doe)
学者数:
11.3W
论文数: 9.6W
被引数: 246
引用论文

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