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Robust unit commitment with dispatchable wind power. / Morales-España, Germán; Lorca, Álvaro; de Weerdt, Mathijs M.

In: Electric Power Systems Research, Vol. 155, 02.2018, p. 58-66.

Research output: Scientific - peer-reviewArticle

Harvard

Morales-España, G, Lorca, Á & de Weerdt, MM 2018, 'Robust unit commitment with dispatchable wind power' Electric Power Systems Research, vol 155, pp. 58-66. DOI: 10.1016/j.epsr.2017.10.002

APA

Vancouver

Morales-España G, Lorca Á, de Weerdt MM. Robust unit commitment with dispatchable wind power. Electric Power Systems Research. 2018 Feb;155:58-66. Available from, DOI: 10.1016/j.epsr.2017.10.002

Author

Morales-España, Germán; Lorca, Álvaro; de Weerdt, Mathijs M. / Robust unit commitment with dispatchable wind power.

In: Electric Power Systems Research, Vol. 155, 02.2018, p. 58-66.

Research output: Scientific - peer-reviewArticle

BibTeX

@article{988182ea2e314dc390c1fbfe634eeb99,
title = "Robust unit commitment with dispatchable wind power",
keywords = "Dispatchable wind, Robust optimization, Stochastic optimization, Unit commitment, Wind curtailment",
author = "Germán Morales-España and Álvaro Lorca and {de Weerdt}, {Mathijs M.}",
year = "2018",
month = "2",
doi = "10.1016/j.epsr.2017.10.002",
volume = "155",
pages = "58--66",
journal = "Electric Power Systems Research",
issn = "0378-7796",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Robust unit commitment with dispatchable wind power

AU - Morales-España,Germán

AU - Lorca,Álvaro

AU - de Weerdt,Mathijs M.

PY - 2018/2

Y1 - 2018/2

N2 - The increasing penetration of uncertain generation such as wind and solar in power systems imposes new challenges to the unit commitment (UC) problem, one of the most critical tasks in power systems operations. The two most common approaches to address these challenges — stochastic and robust optimization — have drawbacks that restrict their application to real-world systems. This paper demonstrates that, by considering dispatchable wind and a box uncertainty set for wind availability, a fully adaptive two-stage robust UC formulation, which is typically a bi-level problem with outer mixed-integer program (MIP) and inner bilinear program, can be translated into an equivalent single-level MIP. Experiments on the IEEE 118-bus test system show that computation time, wind curtailment, and operational costs can be significantly reduced in the proposed unified stochastic–robust approach compared to both pure stochastic approach and pure robust approach, including budget of uncertainty.

AB - The increasing penetration of uncertain generation such as wind and solar in power systems imposes new challenges to the unit commitment (UC) problem, one of the most critical tasks in power systems operations. The two most common approaches to address these challenges — stochastic and robust optimization — have drawbacks that restrict their application to real-world systems. This paper demonstrates that, by considering dispatchable wind and a box uncertainty set for wind availability, a fully adaptive two-stage robust UC formulation, which is typically a bi-level problem with outer mixed-integer program (MIP) and inner bilinear program, can be translated into an equivalent single-level MIP. Experiments on the IEEE 118-bus test system show that computation time, wind curtailment, and operational costs can be significantly reduced in the proposed unified stochastic–robust approach compared to both pure stochastic approach and pure robust approach, including budget of uncertainty.

KW - Dispatchable wind

KW - Robust optimization

KW - Stochastic optimization

KW - Unit commitment

KW - Wind curtailment

UR - http://www.scopus.com/inward/record.url?scp=85031736479&partnerID=8YFLogxK

UR - http://resolver.tudelft.nl/uuid:988182ea-2e31-4dc3-90c1-fbfe634eeb99

U2 - 10.1016/j.epsr.2017.10.002

DO - 10.1016/j.epsr.2017.10.002

M3 - Article

VL - 155

SP - 58

EP - 66

JO - Electric Power Systems Research

T2 - Electric Power Systems Research

JF - Electric Power Systems Research

SN - 0378-7796

ER -

ID: 30556835