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Wind power forecasting uncertainty and unit commitment

delete2011-11-01
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PRE
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王娟 cover
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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Abstract

Abstract

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.
Keywords:
Electricity markets
Forecasting
Dispatch
Stochastic optimization
Unit commitment
Wind power
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Applied Energy cover
Applied Energy
IF:
11
Papers:
2.6W
Citations:
17.8W

Organization

A
Argonne National Laboratory
Scholars:
1.1W
Papers: 9.2K
Citations: 3.8W
U
united states department of energy (doe)
Scholars:
11.3W
Papers: 9.6W
Citations: 246
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