Adaptive Virtual Inertia in Doubly Fed Induction Generators for Enhanced Frequency Regulation

The integration of large-scale renewable energy sources, such as wind and photovoltaic power, into the electrical grid significantly reduces system inertia, thereby diminishing the grid’s capability to resist frequency deviations. During the frequency regulation process, the fixed virtual inertia provided by Doubly Fed Induction Generators is inadequate to support the system inertia requirements under large-scale integration of renewable energy. To address this issue, it is necessary to enhance the virtual inertia control of Doubly Fed Induction Generators by developing a fuzzy adaptive virtual control strategy. Under varying wind speeds and frequency fluctuations, the wind turbine is capable of adaptively adjusting the virtual inertia coefficient, enabling the renewable energy system to actively and adaptively participate in frequency regulation. Moreover, the pitch control strategy in the high wind speed region can be employed to provide additional frequency regulation power for wind turbines. During the frequency regulation process, the output relationship between the wind power system and the energy storage system should be carefully considered to achieve coordinated operation between the two systems. The whale optimization algorithm is utilized to determine the optimal output ratio, ensuring enhanced coordination and regulation performance. In a wind-storage frequency domain system model developed using MATLAB/Simulink simulation software, this strategy improves performance by at least 30% across different wind speed intervals compared to traditional control strategies, with enhancements of 38%, 24%, and 17% under various step loads. This approach effectively enhances the frequency characteristics of renewable energy systems.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3555443
Citations
5
Primary Topic
Wind Turbine Control Systems
Type
article
Field-Weighted Citation Impact
3.65
Controls
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article

Adaptive Virtual Inertia in Doubly Fed Induction Generators for Enhanced Frequency Regulation

Xiuping Ding, Yihong Zhang
5 citations
IEEE Access
Wind Turbine Control Systems
3.65
article

Adaptive Virtual Inertia in Doubly Fed Induction Generators for Enhanced Frequency Regulation

Xiuping Ding, Yihong Zhang
article en
5 citations

Abstract

The integration of large-scale renewable energy sources, such as wind and photovoltaic power, into the electrical grid significantly reduces system inertia, thereby diminishing the grid’s capability to resist frequency deviations. During the frequency regulation process, the fixed virtual inertia provided by Doubly Fed Induction Generators is inadequate to support the system inertia requirements under large-scale integration of renewable energy. To address this issue, it is necessary to enhance the virtual inertia control of Doubly Fed Induction Generators by developing a fuzzy adaptive virtual control strategy. Under varying wind speeds and frequency fluctuations, the wind turbine is capable of adaptively adjusting the virtual inertia coefficient, enabling the renewable energy system to actively and adaptively participate in frequency regulation. Moreover, the pitch control strategy in the high wind speed region can be employed to provide additional frequency regulation power for wind turbines. During the frequency regulation process, the output relationship between the wind power system and the energy storage system should be carefully considered to achieve coordinated operation between the two systems. The whale optimization algorithm is utilized to determine the optimal output ratio, ensuring enhanced coordination and regulation performance. In a wind-storage frequency domain system model developed using MATLAB/Simulink simulation software, this strategy improves performance by at least 30% across different wind speed intervals compared to traditional control strategies, with enhancements of 38%, 24%, and 17% under various step loads. This approach effectively enhances the frequency characteristics of renewable energy systems.

IEEE AccessVol. 13
Donghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 7%
Wind Turbine Control Systems
3.65
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