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Stochastic performance evaluation method of wind power DC bus voltage control system

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  • Meng, Qingwei
  • Sun, Hao
  • Fang, Fang

Abstract

The stochastic fluctuation of DC bus voltage of wind power grid-connected system is related to the safe and stable of power system, and the stochastic performance evaluation is an important means for early warning system. In order to evaluate stochastic performance of control system, this paper proposes a stochastic performance evaluation method based on minimum variance theory. A dual closed loop control model of wind power grid-connected converter DC bus voltage is established, the stochastic performance evaluation indicator is derived by time-series analysis and Diophantine decomposition, and the method to solve the indicator through operation data is given. The effectiveness of the proposed method is verified by FAST-MATLAB co-simulation platform. And the results show that the stochastic performance of the system can be improved by optimizing the parameters of the controller and the DC bus voltage.

Suggested Citation

  • Meng, Qingwei & Sun, Hao & Fang, Fang, 2023. "Stochastic performance evaluation method of wind power DC bus voltage control system," Renewable Energy, Elsevier, vol. 219(P1).
    • Handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123013265
    DOI: 10.1016/j.renene.2023.119411
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    References listed on IDEAS

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    1. Yanhui Qiao & Yongqian Liu & Yang Chen & Shuang Han & Luo Wang, 2022. "Power Generation Performance Indicators of Wind Farms Including the Influence of Wind Energy Resource Differences," Energies, MDPI, vol. 15(5), pages 1-25, February.
    2. Pengfei Zhang & Zuoxia Xing & Shanshan Guo & Mingyang Chen & Qingqi Zhao, 2022. "A New Wind Turbine Power Performance Assessment Approach: SCADA to Power Model Based with Regression-Kriging," Energies, MDPI, vol. 15(13), pages 1-15, July.
    3. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    4. Kong, Xiaobing & Ma, Lele & Wang, Ce & Guo, Shifan & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2022. "Large-scale wind farm control using distributed economic model predictive scheme," Renewable Energy, Elsevier, vol. 181(C), pages 581-591.
    5. Al kez, Dlzar & Foley, Aoife M. & McIlwaine, Neil & Morrow, D. John & Hayes, Barry P. & Zehir, M. Alparslan & Mehigan, Laura & Papari, Behnaz & Edrington, Chris S. & Baran, Mesut, 2020. "A critical evaluation of grid stability and codes, energy storage and smart loads in power systems with wind generation," Energy, Elsevier, vol. 205(C).
    6. Henok Ayele Behabtu & Thierry Coosemans & Maitane Berecibar & Kinde Anlay Fante & Abraham Alem Kebede & Joeri Van Mierlo & Maarten Messagie, 2021. "Performance Evaluation of Grid-Connected Wind Turbine Generators," Energies, MDPI, vol. 14(20), pages 1-19, October.
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