Frequency-Constrained Robust Unit Commitment Model Considering Virtual Inertia Control of Wind Farms

As the penetration of renewable energy sources (RES) in modern power systems increases, the resulting reduction in inertia and inherent uncertainty pose significant challenges to traditional frequency response strategies. To address these challenges and maintain frequency stability during severe contingencies, this paper presents a frequency-constrained robust unit commitment model that incorporates virtual inertia control (VIC) from wind farms. The model accounts for wind power prediction errors by defining a specific uncertainty set for the real-time equivalent virtual inertia of the wind farms. By integrating primary frequency response with the calculated virtual inertia, a day-ahead scheduling approach is developed under this robust framework. The effectiveness of the enhanced frequency regulation capability of wind farms is demonstrated through application of the proposed model on a modified IEEE 39-Bus test system.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/appeec61255.2024.10922577
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.17
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article

Frequency-Constrained Robust Unit Commitment Model Considering Virtual Inertia Control of Wind Farms

Yongkang Xu, Kun Xu, Nian X. Sun, Haixiang Xie et al.
1 citations
Power Systems and Renewable Energy
0.17
article

Frequency-Constrained Robust Unit Commitment Model Considering Virtual Inertia Control of Wind Farms

Yongkang Xu, Kun Xu, Nian X. Sun, Haixiang Xie, Honglei Xu, Jingjing Cao
article en
1 citations

Abstract

As the penetration of renewable energy sources (RES) in modern power systems increases, the resulting reduction in inertia and inherent uncertainty pose significant challenges to traditional frequency response strategies. To address these challenges and maintain frequency stability during severe contingencies, this paper presents a frequency-constrained robust unit commitment model that incorporates virtual inertia control (VIC) from wind farms. The model accounts for wind power prediction errors by defining a specific uncertainty set for the real-time equivalent virtual inertia of the wind farms. By integrating primary frequency response with the calculated virtual inertia, a day-ahead scheduling approach is developed under this robust framework. The effectiveness of the enhanced frequency regulation capability of wind farms is demonstrated through application of the proposed model on a modified IEEE 39-Bus test system.

NARI Group (China) (CN), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 39%
Power Systems and Renewable Energy
0.17
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