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Multiple Spatiotemporal Characteristics-Based Zonal Voltage Control for High Penetrated PVs in Active Distribution Networks

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  • Chuanliang Xiao

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
    Anhui Provincial Laboratory of Renewable Energy Utilization and Energy Saving, Hefei University of Technology, Hefei 230009, China)

  • Lei Sun

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
    Anhui Provincial Laboratory of Renewable Energy Utilization and Energy Saving, Hefei University of Technology, Hefei 230009, China)

  • Ming Ding

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
    Anhui Provincial Laboratory of Renewable Energy Utilization and Energy Saving, Hefei University of Technology, Hefei 230009, China)

Abstract

The penetration of photovoltaic (PV) outputs brings great challenges to optimal operation of active distribution networks (ADNs), especially leading to more serious overvoltage problems. This study proposes a zonal voltage control scheme based on multiple spatiotemporal characteristics for highly penetrated PVs in ADNs. In the spatial domain, a community detection algorithm using a reactive/ active power quality function was introduced to partition an ADN into sub-networks. In the time domain, short-term zonal scheduling (SZS) with 1 h granularity was drawn up based on a cluster. The objective was to minimize the supported reactive power and the curtailed active power in reactive and active power sub-networks. Additionally, a real-time zonal voltage control scheme (RZVC) with 1 min granularity was proposed to correct the SZS rapidly by choosing and controlling the key PV inverter to regulate the supported reactive power and the curtailed active power of the inverters to prevent the overvoltage in each sub-network. With the time domain cooperation, the proposed method could achieve economic control and avoid overvoltage caused by errors in the forecast data of the PVs. For the spatial domain, zonal scheduling and zonal voltage control were carried out in each cluster, and the short-term scheduling and voltage controlling problem of the ADN could then be decomposed into several sub-problems. This could simplify the optimization and control which can reduce the computing time. Finally, an actual 10kV, 103-node network in Zhejiang Province of China is employed to verify the effectiveness and feasibility of the proposed approach.

Suggested Citation

  • Chuanliang Xiao & Lei Sun & Ming Ding, 2020. "Multiple Spatiotemporal Characteristics-Based Zonal Voltage Control for High Penetrated PVs in Active Distribution Networks," Energies, MDPI, vol. 13(1), pages 1-21, January.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:1:p:249-:d:304983
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    References listed on IDEAS

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    1. Anna Rita Di Fazio & Mario Russo & Michele De Santis, 2019. "Zoning Evaluation for Voltage Optimization in Distribution Networks with Distributed Energy Resources," Energies, MDPI, vol. 12(3), pages 1-28, January.
    2. Chuanliang Xiao & Bo Zhao & Ming Ding & Zhihao Li & Xiaohui Ge, 2017. "Zonal Voltage Control Combined Day-Ahead Scheduling and Real-Time Control for Distribution Networks with High Proportion of PVs," Energies, MDPI, vol. 10(10), pages 1-23, September.
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    Cited by:

    1. Jean-François Toubeau & Bashir Bakhshideh Zad & Martin Hupez & Zacharie De Grève & François Vallée, 2020. "Deep Reinforcement Learning-Based Voltage Control to Deal with Model Uncertainties in Distribution Networks," Energies, MDPI, vol. 13(15), pages 1-15, August.
    2. Wenwen Sun & Guoqing He, 2023. "Cluster Partition-Based Voltage Control Combined Day-Ahead Scheduling and Real-Time Control for Distribution Networks," Energies, MDPI, vol. 16(11), pages 1-13, May.
    3. Xingye Deng & Canwei Liu & Hualiang Liu & Lei Chen & Yuyan Guo & Heding Zhen, 2023. "Enhanced Density Peak-Based Power Grid Reactive Voltage Partitioning," Energies, MDPI, vol. 16(17), pages 1-24, August.
    4. Bashir Bakhshideh Zad & Jean-François Toubeau & François Vallée, 2021. "Chance-Constrained Based Voltage Control Framework to Deal with Model Uncertainties in MV Distribution Systems," Energies, MDPI, vol. 14(16), pages 1-16, August.
    5. Antonio T. Alexandridis, 2020. "Modern Power System Dynamics, Stability and Control," Energies, MDPI, vol. 13(15), pages 1-8, July.

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