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Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse

Author

Listed:
  • Robert Małkowski

    (Department of Electrical Power Engineering, Faculty of Electrical and Control Engineering, Gdańsk University of Technology, 80-233 Gdańsk, Poland)

  • Michał Izdebski

    (Gdansk Division, Institute of Power Engineering, 80-870 Gdańsk, Poland)

  • Piotr Miller

    (Department of Power Engineering, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, 20-618 Lublin, Poland)

Abstract

The development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm. The possibilities of improving the quality of regulation, which can be found in the literature, most often include various methods of coordination of the operation of the transformer regulator with various devices operating in the Medium-Voltage (MV) network. This coordination can be decentralized or centralized. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. The goal of the authors was to create an algorithm that extends the functionality of typical transformer control algorithms. The proposed solution allows for reducing the risk of voltage collapse. The performance of the proposed algorithm was validated using multivariate computer simulations and tests with the use of a physical model of the distribution network. The DIgSILENT PowerFactory environment was used to develop the simulation model of the proposed algorithm. Then, tests were conducted on real devices installed in the LINTEˆ2 Laboratory at the Gdańsk University of Technology, Poland. Selected test results are included in this paper. All results have shown that the proposed algorithm makes it possible to increase the reserve of the voltage stability of the node, in which it is applied, thus mitigating the risk of a voltage collapse occurring. The proposed algorithm does not require complex and costly technical solutions. Owing to its simplicity, it has a high potential for practical application, as confirmed by the real-time control experiment in the laboratory.

Suggested Citation

  • Robert Małkowski & Michał Izdebski & Piotr Miller, 2020. "Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse," Energies, MDPI, vol. 13(20), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5403-:d:429051
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    References listed on IDEAS

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    Cited by:

    1. Paweł Pijarski & Piotr Kacejko & Piotr Miller, 2023. "Advanced Optimisation and Forecasting Methods in Power Engineering—Introduction to the Special Issue," Energies, MDPI, vol. 16(6), pages 1-20, March.
    2. Paweł Pijarski & Piotr Kacejko & Marek Wancerz, 2022. "Voltage Control in MV Network with Distributed Generation—Possibilities of Real Quality Enhancement," Energies, MDPI, vol. 15(6), pages 1-22, March.
    3. Marcin Łuszczyk & Adam Sulich & Barbara Siuta-Tokarska & Tomasz Zema & Agnieszka Thier, 2021. "The Development of Electromobility in the European Union: Evidence from Poland and Cross-Country Comparisons," Energies, MDPI, vol. 14(24), pages 1-18, December.
    4. Michał Izdebski & Robert Małkowski & Piotr Miller, 2022. "New Performance Indices for Power System Stabilizers," Energies, MDPI, vol. 15(24), pages 1-23, December.
    5. Łukasz Mazur & Zbigniew Kłosowski, 2023. "A New Approach to the Use of Energy from Renewable Sources in Low-Voltage Power Distribution Networks," Energies, MDPI, vol. 16(2), pages 1-29, January.
    6. Bartłomiej Mroczek & Paweł Pijarski, 2021. "DSO Strategies Proposal for the LV Grid of the Future," Energies, MDPI, vol. 14(19), pages 1-19, October.
    7. Paweł Pijarski & Piotr Kacejko, 2021. "Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations," Energies, MDPI, vol. 14(4), pages 1-21, February.
    8. Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.

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