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Parameter Identification of Asynchronous Load Nodes

Author

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  • Andrey Kryukov

    (Department of Transport Electric Power, Irkutsk State Transport University, 664074 Irkutsk, Russia
    Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia)

  • Konstantin Suslov

    (Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
    Department of Hydropower and Renewable Energy, National Research University “Moscow Power Engineering Institute”, 111250 Moscow, Russia)

  • Pavel Ilyushin

    (Department of Hydropower and Renewable Energy, National Research University “Moscow Power Engineering Institute”, 111250 Moscow, Russia
    Department of Research on the Relationship between Energy and the Economy, Energy Research Institute of the Russian Academy of Sciences, 117186 Moscow, Russia)

  • Azat Akhmetshin

    (Department of Power Engineering, Kazan State Power Engineering University, 420066 Kazan, Russia)

Abstract

Asynchronous loads (AL), because of their low negative-sequence resistance, produce the effect of reduced unbalance at their connection points. Therefore, proper modeling of unbalanced load flows in power supply systems requires properly accounting for AL. Adequate models of the induction motor can be realized in the phase frame of reference. The effective use of such models is possible only if accurate data on the parameters of induction motor equivalent circuits for positive and negative sequences are available. Our analysis shows that the techniques used to determine these parameters on the basis of reference data can yield markedly disparate results. It is possible to overcome this difficulty by applying parameter identification methods that use the phase frame of reference. The paper proposes a technique for parameter identification of models of individual induction motors and asynchronous load nodes. The results of computer-aided simulation allow us to conclude that by using parameter identification, we can obtain an equivalent model of an asynchronous load node, and such a model provides high accuracy for both balanced and unbalanced load flow analysis. By varying load flow parameters, we demonstrate that the model proves valid over a wide range of their values. We have proposed a technique for the identification of asynchronous load nodes with such asynchronous loads, including electrical drives equipped with static frequency converters. With the aid of the AL identification models proposed in this paper, it is possible to solve the following practical tasks of management of electric power systems: increasing the accuracy of modeling their operating conditions; making informed decisions when taking measures to reduce unbalance in power grids while accounting for the balancing adjustment effect of AL.

Suggested Citation

  • Andrey Kryukov & Konstantin Suslov & Pavel Ilyushin & Azat Akhmetshin, 2023. "Parameter Identification of Asynchronous Load Nodes," Energies, MDPI, vol. 16(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1893-:d:1068270
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    References listed on IDEAS

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    1. Yuri Bulatov & Andrey Kryukov & Konstantin Suslov, 2022. "Using Group Predictive Voltage and Frequency Regulators of Distributed Generation Plants in Cyber-Physical Power Supply Systems," Energies, MDPI, vol. 15(4), pages 1-20, February.
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    Cited by:

    1. Konstantin Suslov & Andrey Kryukov & Pavel Ilyushin & Aleksander Cherepanov & Aleksander Kryukov, 2023. "Modeling the Effects of Electromagnetic Interference from Multi-Wire Traction Networks on Pipelines," Energies, MDPI, vol. 16(10), pages 1-25, May.
    2. Zhaowen Liang & Yongqiang Liu & Lili Mo & Yan Zhang, 2024. "A Grouping and Aggregation Modeling Method of Induction Motors for Transient Voltage Stability Analysis," Energies, MDPI, vol. 17(17), pages 1-20, September.

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