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Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility

Author

Listed:
  • Yu Zhang

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

  • Xiaohui Song

    (China Electric Power Research Institute Co., Ltd., Beijing 100192, China)

  • Yong Li

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

  • Zilong Zeng

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

  • Chenchen Yong

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

  • Denis Sidorov

    (Energy Systems Institute, Russian Academy of Sciences, 664033 Irkutsk, Russia
    Industrial Maths Lab of Irkutsk National Research Technical University, 664033 Irkutsk, Russia)

  • Xia Lv

    (Zhuhai Powint Electric Co. Ltd., Zhuhai 519085, China)

Abstract

A high proportion of renewable energy connected to the power grid has caused power quality problems. Voltage-sensitive loads are extremely susceptible to voltage fluctuations, causing power system safety issues and economic losses. Considering the uncertainty factor and the time-varying characteristic, a linearized random ZIP model (constant impedance (Z), constant current (I), and constant power (P)) with time-varying characteristics was proposed. In order to improve the voltage quality of the voltage-sensitive loads in the day-here stage in an active distribution network (ADN), a linearized two-stage active and reactive power coordinated stochastic optimization model was established. The day-ahead active and reactive power coordination optimization was to smooth the large voltage fluctuation and develop a reserve plan to eliminate the unbalanced power caused by the prediction error in the day-here optimization. In the day-here real-time redispatch, the voltage was further improved by the continuous reactive power compensation device. Finally, the simulation results on the IEEE-33 bus system showed that the control strategy could better eliminate the unbalanced power caused by the prediction error and obviously improve the voltage of sensitive loads in the real-time stage on the premise of maintaining economic optimality.

Suggested Citation

  • Yu Zhang & Xiaohui Song & Yong Li & Zilong Zeng & Chenchen Yong & Denis Sidorov & Xia Lv, 2020. "Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility," Energies, MDPI, vol. 13(22), pages 1-13, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:5922-:d:444499
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    References listed on IDEAS

    as
    1. Fei Chen & Dong Liu & Xiaofang Xiong, 2017. "Research on Stochastic Optimal Operation Strategy of Active Distribution Network Considering Intermittent Energy," Energies, MDPI, vol. 10(4), pages 1-23, April.
    2. Jin-Xin Ou-Yang & Xiao-Xuan Long & Xue Du & Yan-Bo Diao & Meng-Yang Li, 2019. "Voltage Control Method for Active Distribution Networks Based on Regional Power Coordination," Energies, MDPI, vol. 12(22), pages 1-23, November.
    3. Nikolaos Koutsoukis & Pavlos Georgilakis, 2019. "A Chance-Constrained Multistage Planning Method for Active Distribution Networks," Energies, MDPI, vol. 12(21), pages 1-19, October.
    4. Pengwei Cong & Wei Tang & Lu Zhang & Bo Zhang & Yongxiang Cai, 2017. "Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors," Energies, MDPI, vol. 10(9), pages 1-20, August.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Ahmed M. Abd-El Wahab & Salah Kamel & Mohamed H. Hassan & Mohamed I. Mosaad & Tarek A. AbdulFattah, 2022. "Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm," Mathematics, MDPI, vol. 10(3), pages 1-26, January.
    2. Lenin Kanagasabai, 2022. "Novel Western Jackdaw search, antrostomus swarm and Indian ethnic vedic teaching: inspired optimization algorithms for real power loss diminishing and voltage consistency growth," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2895-2919, December.
    3. Yu Shen & Wei Hu & Yaoyao Xiao & Ganghua Zhang & Mingyu Han & Fan Yang & Wenping Zuo, 2021. "Mechanical Switch Based Adaptive Fault Ride-through Strategy for Power Quality Improvement Device," Energies, MDPI, vol. 14(20), pages 1-19, October.
    4. Lu, Jun & Liu, Tianqi & He, Chuan & Nan, Lu & Hu, Xiaotong, 2021. "Robust day-ahead coordinated scheduling of multi-energy systems with integrated heat-electricity demand response and high penetration of renewable energy," Renewable Energy, Elsevier, vol. 178(C), pages 466-482.
    5. Insu Kim & Beopsoo Kim & Denis Sidorov, 2022. "Machine Learning for Energy Systems Optimization," Energies, MDPI, vol. 15(11), pages 1-8, June.

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