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Towards the Flexible Distribution Networks Design Using the Reliability Performance Metric

Author

Listed:
  • Ilia Shushpanov

    (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)

  • Pavel Ilyushin

    (Department of Research on the Relationship between Energy and the Economy, Energy Research Institute of the Russian Academy of Sciences, 117186 Moscow, Russia)

  • Denis N. Sidorov

    (Baikal School of BRICS, Irkutsk National Research Technical University, 664074 Irkutsk, Russia
    Energy Systems Institute of Siberian Branch of Russian Academy of Sciences, 664000 Irkutsk, Russia)

Abstract

At present, the entire world is moving towards digitalization, including in the electric power industry. Digitalization is in its heyday and a lot of articles and reports are devoted to this topic. At the same time, the least digitalized of the electrical networks are distribution networks that account for a very large share in electric power systems. The article proposes a methodology for creating a flexible distribution network based on the use of digital technology. Additionally, we elaborate a methodology with the identification and collection of the necessary information to create digital networks, develop ways to adapt the required equipment, and suggest methods of recognition of some short circuits. Furthermore, we address the issue of reliability of the information obtained from digital devices, develop a technique for arranging the devices to cover the entire network as required to improve the power system protection of electrical power distribution networks. The above measures make it possible to ensure the flexibility of the active distribution network, as well as to adjust the parameters of the actuation of power system protection depending on changes in external conditions and in the event of emergencies. We propose a technique for controlling the distribution network, based on the factoring-in of the type of damage during an emergency in real time, as well as a technique for arranging the measuring devices and the creation of an information and communication network. We provide recommendations for the design and operation of electric power distribution networks with digital network control technology.

Suggested Citation

  • Ilia Shushpanov & Konstantin Suslov & Pavel Ilyushin & Denis N. Sidorov, 2021. "Towards the Flexible Distribution Networks Design Using the Reliability Performance Metric," Energies, MDPI, vol. 14(19), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6193-:d:645294
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    References listed on IDEAS

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    1. Mokryani, Geev & Hu, Yim Fun & Pillai, Prashant & Rajamani, Haile-Selassie, 2017. "Active distribution networks planning with high penetration of wind power," Renewable Energy, Elsevier, vol. 104(C), pages 40-49.
    2. Ghadi, Mojtaba Jabbari & Rajabi, Amin & Ghavidel, Sahand & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    5. Mokryani, Geev & Hu, Yim Fun & Papadopoulos, Panagiotis & Niknam, Taher & Aghaei, Jamshid, 2017. "Deterministic approach for active distribution networks planning with high penetration of wind and solar power," Renewable Energy, Elsevier, vol. 113(C), pages 942-951.
    6. McDonald, Jim, 2008. "Adaptive intelligent power systems: Active distribution networks," Energy Policy, Elsevier, vol. 36(12), pages 4346-4351, December.
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    Cited by:

    1. Yuriy Leonidovich Zhukovskiy & Margarita Sergeevna Kovalchuk & Daria Evgenievna Batueva & Nikita Dmitrievich Senchilo, 2021. "Development of an Algorithm for Regulating the Load Schedule of Educational Institutions Based on the Forecast of Electric Consumption within the Framework of Application of the Demand Response," Sustainability, MDPI, vol. 13(24), pages 1-26, December.
    2. Nataliia Shamarova & Konstantin Suslov & Pavel Ilyushin & Ilia Shushpanov, 2022. "Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-18, September.
    3. Dmitriy Karamov & Pavel Ilyushin & Ilya Minarchenko & Sergey Filippov & Konstantin Suslov, 2023. "The Role of Energy Performance Agreements in the Sustainable Development of Decentralized Energy Systems: Methodology for Determining the Equilibrium Conditions of the Contract," Energies, MDPI, vol. 16(6), pages 1-12, March.
    4. Pavel Ilyushin & Vladislav Volnyi & Konstantin Suslov & Sergey Filippov, 2023. "State-of-the-Art Literature Review of Power Flow Control Methods for Low-Voltage AC and AC-DC Microgrids," Energies, MDPI, vol. 16(7), pages 1-35, March.
    5. Pavel Ilyushin & Vladislav Volnyi & Konstantin Suslov & Sergey Filippov, 2022. "Review of Methods for Addressing Challenging Issues in the Operation of Protection Devices in Microgrids with Voltages of up to 1 kV That Integrates Distributed Energy Resources," Energies, MDPI, vol. 15(23), pages 1-22, December.
    6. Pavel Ilyushin & Sergey Filippov & Aleksandr Kulikov & Konstantin Suslov & Dmitriy Karamov, 2022. "Intelligent Control of the Energy Storage System for Reliable Operation of Gas-Fired Reciprocating Engine Plants in Systems of Power Supply to Industrial Facilities," Energies, MDPI, vol. 15(17), pages 1-21, August.
    7. Pavel Ilyushin & Aleksandr Kulikov & Konstantin Suslov & Sergey Filippov, 2022. "An Approach to Assessing Spatial Coherence of Current and Voltage Signals in Electrical Networks," Mathematics, MDPI, vol. 10(10), pages 1-15, May.
    8. Dmitriy N. Karamov & Pavel V. Ilyushin & Konstantin V. Suslov, 2022. "Electrification of Rural Remote Areas Using Renewable Energy Sources: Literature Review," Energies, MDPI, vol. 15(16), pages 1-13, August.
    9. Insu Kim & Beopsoo Kim & Denis Sidorov, 2022. "Machine Learning for Energy Systems Optimization," Energies, MDPI, vol. 15(11), pages 1-8, June.
    10. Yuriy Zhukovskiy & Anastasia Koshenkova & Valeriya Vorobeva & Daniil Rasputin & Roman Pozdnyakov, 2023. "Assessment of the Impact of Technological Development and Scenario Forecasting of the Sustainable Development of the Fuel and Energy Complex," Energies, MDPI, vol. 16(7), pages 1-23, March.

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