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Assessment of PV Hosting Capacity in a Small Distribution System by an Improved Stochastic Analysis Method

Author

Listed:
  • Yu-Jen Liu

    (Department of Electrical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan)

  • Yu-Hsuan Tai

    (Taiwan Power Company, Taipei 10016, Taiwan)

  • Yih-Der Lee

    (Nuclear Instrument Division, Institute of Nuclear Energy Research, Taoyuan 32546, Taiwan)

  • Jheng-Lung Jiang

    (Nuclear Instrument Division, Institute of Nuclear Energy Research, Taoyuan 32546, Taiwan)

  • Chen-Wei Lin

    (Taiwan Power Company, Taipei 10016, Taiwan)

Abstract

PV hosting capacity (PVHC) analysis on a distribution system is an attractive technique that emerged in recent years for dealing with the planning tasks on high-penetration PV integration. PVHC uses various system performance indices as judgements to find an available amount of PV installation capacity that can be accommodated on existing distribution system infrastructure without causing any violation. Generally, approaches for PVHC assessments are implemented by iterative power flow calculations with stochastic PV deployments so as to observe the operation impacts for PV installation on distribution systems. Determination of the stochastic PV deployments in most of traditional PVHC analysis methods is automatically carried out by the program that is using random selection. However, a repetitive problem that exists in these traditional methods on the selection of the same PV deployment for a calculation was not previously investigated or discussed; further, underestimation of PVHC results may occur. To assess PVHC more effectively, this paper proposes an improved stochastic analysis method that introduces an innovative idea of using repetitiveness check mechanism to overcome the shortcomings of the traditional methods. The proposed mechanism firstly obtains all PV deployment combinations for the determination of all possible PV installation locations. A quick-sorting algorithm is then used to remove repetitive PV deployments that are randomly selected during the solution procedure. Finally, MATLAB and OpenDSS co-simulations implemented on a small distribution feeder are used to validate the performance of the proposed method; in addition, PVHC enhancement by PV inverter control is investigated and simulated in this paper as well. Results show that the proposed method is more effective than traditional methods in PVHC assessments.

Suggested Citation

  • Yu-Jen Liu & Yu-Hsuan Tai & Yih-Der Lee & Jheng-Lung Jiang & Chen-Wei Lin, 2020. "Assessment of PV Hosting Capacity in a Small Distribution System by an Improved Stochastic Analysis Method," Energies, MDPI, vol. 13(22), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:5942-:d:444908
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    References listed on IDEAS

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    1. Ammar Arshad & Martin Lindner & Matti Lehtonen, 2017. "An Analysis of Photo-Voltaic Hosting Capacity in Finnish Low Voltage Distribution Networks," Energies, MDPI, vol. 10(11), pages 1-16, October.
    2. Ammar Arshad & Verner Püvi & Matti Lehtonen, 2018. "Monte Carlo-Based Comprehensive Assessment of PV Hosting Capacity and Energy Storage Impact in Realistic Finnish Low-Voltage Networks," Energies, MDPI, vol. 11(6), pages 1-14, June.
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    Cited by:

    1. Md Tariqul Islam & M. J. Hossain, 2023. "Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
    2. Yih-Der Lee & Wei-Chen Lin & Jheng-Lun Jiang & Jia-Hao Cai & Wei-Tzer Huang & Kai-Chao Yao, 2021. "Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm," Energies, MDPI, vol. 14(24), pages 1-22, December.

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