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MPC Based Coordinated Active and Reactive Power Control Strategy of DFIG Wind Farm with Distributed ESSs

Author

Listed:
  • Hesong Cui

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Xueping Li

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Gongping Wu

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Yawei Song

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Xiao Liu

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Derong Luo

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

Suggested Citation

  • Hesong Cui & Xueping Li & Gongping Wu & Yawei Song & Xiao Liu & Derong Luo, 2021. "MPC Based Coordinated Active and Reactive Power Control Strategy of DFIG Wind Farm with Distributed ESSs," Energies, MDPI, vol. 14(13), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:3906-:d:584821
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    References listed on IDEAS

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    1. Mohseni, Mansour & Islam, Syed M., 2012. "Review of international grid codes for wind power integration: Diversity, technology and a case for global standard," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3876-3890.
    2. Perveen, Rehana & Kishor, Nand & Mohanty, Soumya R., 2014. "Off-shore wind farm development: Present status and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 780-792.
    3. Diogo Menezes & Mateus Mendes & Jorge Alexandre Almeida & Torres Farinha, 2020. "Wind Farm and Resource Datasets: A Comprehensive Survey and Overview," Energies, MDPI, vol. 13(18), pages 1-24, September.
    4. Baohua Zhang & Weihao Hu & Peng Hou & Jin Tan & Mohsen Soltani & Zhe Chen, 2017. "Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm," Energies, MDPI, vol. 10(7), pages 1-17, June.
    5. Da, Zhang & Xiliang, Zhang & Jiankun, He & Qimin, Chai, 2011. "Offshore wind energy development in China: Current status and future perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4673-4684.
    6. Shahram Hanifi & Xiaolei Liu & Zi Lin & Saeid Lotfian, 2020. "A Critical Review of Wind Power Forecasting Methods—Past, Present and Future," Energies, MDPI, vol. 13(15), pages 1-24, July.
    7. Georgios Gasparis & Wai Hou Lio & Fanzhong Meng, 2020. "Surrogate Models for Wind Turbine Electrical Power and Fatigue Loads in Wind Farm," Energies, MDPI, vol. 13(23), pages 1-15, December.
    8. Schönleber, Kevin & Collados, Carlos & Pinto, Rodrigo Teixeira & Ratés-Palau, Sergi & Gomis-Bellmunt, Oriol, 2017. "Optimization-based reactive power control in HVDC-connected wind power plants," Renewable Energy, Elsevier, vol. 109(C), pages 500-509.
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    Cited by:

    1. Habib Benbouhenni & Nicu Bizon, 2021. "Advanced Direct Vector Control Method for Optimizing the Operation of a Double-Powered Induction Generator-Based Dual-Rotor Wind Turbine System," Mathematics, MDPI, vol. 9(19), pages 1-36, September.
    2. Liang Bu & Song Han & Jinling Feng, 2021. "Short-Circuit Fault Analysis of the Sen Transformer Using Phase Coordinate Model," Energies, MDPI, vol. 14(18), pages 1-19, September.

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