Robust Unit Commitment Considering the Temporal and Spatial Correlations of Wind Farms Using a Data-Adaptive Approach

Yipu Zhang, Xiaomeng Ai, Jinyu Wen, Jiakun Fang, Cheng Luo

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1 Citationer (Scopus)

Abstrakt

In robust optimization problems, building a proper uncertainty set for the stochastic variables plays an important role. Due to the restricted mathematical formulations of the uncertainty sets, the results derived from conventional two-stage robust optimization are usually over conservative. In this paper, a novel data-adaptive robust optimization method for the unit commitment is proposed for the power system with wind farms integrated. The extreme scenario extraction and the two stage robust optimization are combined in the proposed method. The data-adaptive set consisting of a few extreme scenarios is derived to reduce the conservativeness by considering the temporal and spatial correlations of multiple wind farms. Numerical results demonstrate that the proposed data-adaptive robust optimization algorithm is less conservative than the current two-stage optimization approaches while maintains the same level of robustness of the solution.
OriginalsprogEngelsk
TitelProceedings of IEEE Power and Energy Society General Meeting (PESGM)
Antal sider5
ForlagIEEE
Publikationsdatoaug. 2018
Sider1-5
ISBN (Trykt)978-1-5386-7704-9
ISBN (Elektronisk)978-1-5386-7703-2
DOI
StatusUdgivet - aug. 2018
BegivenhedIEEE Power and Energy Society General Meeting (PESGM) - Portland, USA
Varighed: 5 aug. 20189 aug. 2018

Konference

KonferenceIEEE Power and Energy Society General Meeting (PESGM)
LandUSA
ByPortland
Periode05/08/201809/08/2018
NavnIEEE Power and Energy Society General Meeting
ISSN1944-9925

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