IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v219y2023ip1s0960148123013265.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123013265
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2023.119411?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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).
    3. 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.
    4. 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).
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khasanzoda, Nasrullo & Safaraliev, Murodbek & Zicmane, Inga & Beryozkina, Svetlana & Rahimov, Jamshed & Ahyoev, Javod, 2022. "Use of smart grid based wind resources in isolated power systems," Energy, Elsevier, vol. 253(C).
    2. Zhu, Xiaoxun & Liu, Ruizhang & Chen, Yao & Gao, Xiaoxia & Wang, Yu & Xu, Zixu, 2021. "Wind speed behaviors feather analysis and its utilization on wind speed prediction using 3D-CNN," Energy, Elsevier, vol. 236(C).
    3. Boyle, James & Littler, Timothy & Foley, Aoife, 2020. "Battery energy storage system state-of-charge management to ensure availability of frequency regulating services from wind farms," Renewable Energy, Elsevier, vol. 160(C), pages 1119-1135.
    4. Wang, Hao & Wang, Tongguang & Ke, Shitang & Hu, Liang & Xie, Jiaojie & Cai, Xin & Cao, Jiufa & Ren, Yuxin, 2023. "Assessing code-based design wind loads for offshore wind turbines in China against typhoons," Renewable Energy, Elsevier, vol. 212(C), pages 669-682.
    5. Arabgolarcheh, Alireza & Rouhollahi, Amirhossein & Benini, Ernesto, 2023. "Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions," Renewable Energy, Elsevier, vol. 208(C), pages 546-560.
    6. Cardo-Miota, Javier & Trivedi, Rohit & Patra, Sandipan & Khadem, Shafi & Bahloul, Mohamed, 2024. "Data-driven approach for day-ahead System Non-Synchronous Penetration forecasting: A comprehensive framework, model development and analysis," Applied Energy, Elsevier, vol. 362(C).
    7. Tee, Wei Hown & Gan, Chin Kim & Sardi, Junainah, 2024. "Benefits of energy storage systems and its potential applications in Malaysia: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    8. Kong, Xiaobing & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2023. "Stable feedback linearization-based economic MPC scheme for thermal power plant," Energy, Elsevier, vol. 268(C).
    9. Karijadi, Irene & Chou, Shuo-Yan & Dewabharata, Anindhita, 2023. "Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method," Renewable Energy, Elsevier, vol. 218(C).
    10. Sang, Meiyue & Shen, Liyin, 2024. "An international perspective on carbon peaking status between a sample of 154 countries," Applied Energy, Elsevier, vol. 369(C).
    11. Aya M. Moheb & Enas A. El-Hay & Attia A. El-Fergany, 2022. "Comprehensive Review on Fault Ride-Through Requirements of Renewable Hybrid Microgrids," Energies, MDPI, vol. 15(18), pages 1-30, September.
    12. Abdoos, Ali Akbar & Abdoos, Hatef & Kazemitabar, Javad & Mobashsher, Mohammad Mehdi & Khaloo, Hooman, 2023. "An intelligent hybrid method based on Monte Carlo simulation for short-term probabilistic wind power prediction," Energy, Elsevier, vol. 278(PA).
    13. Di, Kaisheng & Chen, Weidong & Shi, Qiumei & Cai, Quanling & Liu, Sichen, 2024. "Analysing the impact of coupled domestic demand dynamics of green and low-carbon consumption in the market based on SEM-ANN," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    14. Guzović, Zvonimir & Duic, Neven & Piacentino, Antonio & Markovska, Natasa & Mathiesen, Brian Vad & Lund, Henrik, 2022. "Recent advances in methods, policies and technologies at sustainable energy systems development," Energy, Elsevier, vol. 245(C).
    15. Jing, Hang & Li, Yan & Brandsema, Matthew J. & Chen, Yousu & Yue, Meng, 2024. "HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids," Applied Energy, Elsevier, vol. 361(C).
    16. Pasquale Marcello Falcone, 2023. "Sustainable Energy Policies in Developing Countries: A Review of Challenges and Opportunities," Energies, MDPI, vol. 16(18), pages 1-19, September.
    17. Hampton, Harrison & Foley, Aoife M. & Del Rio, Dylan Furszyfer & Sovacool, Benjamin, 2022. "Developing future retail electricity markets with a customer-centric focus," Energy Policy, Elsevier, vol. 168(C).
    18. Hemant Ahuja & Arika Singh & Sachin Sharma & Gulshan Sharma & Pitshou N. Bokoro, 2022. "Coordinated Control of Wind Energy Conversion System during Unsymmetrical Fault at Grid," Energies, MDPI, vol. 15(13), pages 1-15, July.
    19. Sun, Kang & Xu, Zifei & Li, Shujun & Jin, Jiangtao & Wang, Peilin & Yue, Minnan & Li, Chun, 2023. "Dynamic response analysis of floating wind turbine platform in local fatigue of mooring," Renewable Energy, Elsevier, vol. 204(C), pages 733-749.
    20. Sinhara M. H. D. Perera & Ghanim Putrus & Michael Conlon & Mahinsasa Narayana & Keith Sunderland, 2022. "Wind Energy Harvesting and Conversion Systems: A Technical Review," Energies, MDPI, vol. 15(24), pages 1-34, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123013265. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.