Wind power forecasting uncertainty and unit commitment

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Jianhui Wang (Author) FEUP; Audun Botterud (Author) FEUP; Ricardo Jorge Bessa (Author) FEUP; Hrvoje Keko (Author) FEUP; Leonel Magalhães Carvalho (Author) Other; Diego Issicaba (Author) Other; Jean Sumaili (Author) Other; Vladimiro Miranda (Author) FEUP

Journal

Title: Applied Energy

Vol. 88 No. 11

Pages: 4014-4023

ISSN: 0306-2619

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 223 Citations

ISI Web of Science

Scopus - 252 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering > Electrical engineering

Other information

Authenticus ID: P-002-KD0

DOI: 10.1016/j.apenergy.2011.04.011

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10