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Toward Zero-Emission Hybrid AC/DC Power Systems with Renewable Energy Sources and Storages: A Case Study from Lake Baikal Region

Author

Listed:
  • Denis Sidorov

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Daniil Panasetsky

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Nikita Tomin

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Dmitriy Karamov

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Aleksei Zhukov

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Ildar Muftahov

    (Energy Systems Institute, Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia)

  • Aliona Dreglea

    (Baikal School of BRICS, Irkutsk National Research Technical University, 664033 Irkutsk, Russia)

  • Fang Liu

    (School of Automation, Central South University, Changsha 410083, China)

  • Yong Li

    (School of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

Tourism development in ecologically vulnerable areas like the lake Baikal region in Eastern Siberia is a challenging problem. To this end, the dynamical models of AC/DC hybrid isolated power system consisting of four power grids with renewable generation units and energy storage systems are proposed using the advanced methods based on deep reinforcement learning and integral equations. First, the wind and solar irradiance potential of several sites on the lake Baikal’s banks is analyzed as well as the electric load as a function of the climatic conditions. The optimal selection of the energy storage system components is supported in online mode. The approach is justified using the retrospective meteorological datasets. Such a formulation will allow us to develop a number of valuable recommendations related to the optimal control of several autonomous AC/DC hybrid power systems with different structures, equipment composition and kind of AC or DC current. Developed approach provides the valuable information at different stages of AC/DC hybrid power systems projects development with stand-alone hybrid solar-wind power generation systems.

Suggested Citation

  • Denis Sidorov & Daniil Panasetsky & Nikita Tomin & Dmitriy Karamov & Aleksei Zhukov & Ildar Muftahov & Aliona Dreglea & Fang Liu & Yong Li, 2020. "Toward Zero-Emission Hybrid AC/DC Power Systems with Renewable Energy Sources and Storages: A Case Study from Lake Baikal Region," Energies, MDPI, vol. 13(5), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1226-:d:329481
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    References listed on IDEAS

    as
    1. Pineda, Salvador & Bock, Andreas, 2016. "Renewable-based generation expansion under a green certificate market," Renewable Energy, Elsevier, vol. 91(C), pages 53-63.
    2. Zamfir, Andreea & Colesca, Sofia Elena & Corbos, Razvan-Andrei, 2016. "Public policies to support the development of renewable energy in Romania: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 87-106.
    3. Cornélusse, Bertrand & Savelli, Iacopo & Paoletti, Simone & Giannitrapani, Antonio & Vicino, Antonio, 2019. "A community microgrid architecture with an internal local market," Applied Energy, Elsevier, vol. 242(C), pages 547-560.
    4. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    5. Timilsina, Govinda R. & Shah, Kalim U., 2016. "Filling the gaps: Policy supports and interventions for scaling up renewable energy development in Small Island Developing States," Energy Policy, Elsevier, vol. 98(C), pages 653-662.
    6. Ying Ji & Jianhui Wang & Jiacan Xu & Xiaoke Fang & Huaguang Zhang, 2019. "Real-Time Energy Management of a Microgrid Using Deep Reinforcement Learning," Energies, MDPI, vol. 12(12), pages 1-21, June.
    7. Bertrand Corn'elusse & Iacopo Savelli & Simone Paoletti & Antonio Giannitrapani & Antonio Vicino, 2018. "A Community Microgrid Architecture with an Internal Local Market," Papers 1810.09803, arXiv.org, revised Feb 2019.
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    Cited by:

    1. Dogga Raveendhra & Rajana Poojitha & Beeramangalla Lakshminarasaiah Narasimharaju & Aliona Dreglea & Fang Liu & Daniil Panasetsky & Mukesh Pathak & Denis Sidorov, 2023. "Part-I: State-of-the-Art Technologies of Solar Powered DC Microgrid with Hybrid Energy Storage Systems-Architecture Topologies," Energies, MDPI, vol. 16(2), pages 1-21, January.
    2. Denis Sidorov & Aleksandr Tynda & Ildar Muftahov & Aliona Dreglea & Fang Liu, 2020. "Nonlinear Systems of Volterra Equations with Piecewise Smooth Kernels: Numerical Solution and Application for Power Systems Operation," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    3. Harri Aaltonen & Seppo Sierla & Rakshith Subramanya & Valeriy Vyatkin, 2021. "A Simulation Environment for Training a Reinforcement Learning Agent Trading a Battery Storage," Energies, MDPI, vol. 14(17), pages 1-20, September.
    4. Cui, Zhenhua & Kang, Le & Li, Liwei & Wang, Licheng & Wang, Kai, 2022. "A hybrid neural network model with improved input for state of charge estimation of lithium-ion battery at low temperatures," Renewable Energy, Elsevier, vol. 198(C), pages 1328-1340.
    5. Simin Aghaei Amirkhizi & Yaghoub Mahmoudi & Ali Salimi Shamloo, 2022. "Legendre polynomials approximation method for solving Volterra integral equations of the first kind with discontinuous kernels," Indian Journal of Pure and Applied Mathematics, Springer, vol. 53(2), pages 492-504, June.
    6. Zafar, Muhammad Hamza & Khan, Noman Mujeeb & Houran, Mohamad Abou & Mansoor, Majad & Akhtar, Naureen & Sanfilippo, Filippo, 2024. "A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature," Energy, Elsevier, vol. 292(C).
    7. Kailun Wang & Qiang Song & Shukai Xu, 2022. "Analysis and Design of the Energy Storage Requirement of Hybrid Modular Multilevel Converters Using Numerical Integration and Iterative Solution," Energies, MDPI, vol. 15(3), pages 1-18, February.
    8. Sergey Zhironkin & Fares Abu-Abed & Elena Dotsenko, 2023. "The Development of Renewable Energy in Mineral Resource Clusters—The Case of the Siberian Federal District," Energies, MDPI, vol. 16(9), pages 1-28, April.
    9. Félix Dubuisson & Miloud Rezkallah & Hussein Ibrahim & Ambrish Chandra, 2021. "Real-Time Implementation of the Predictive-Based Control with Bacterial Foraging Optimization Technique for Power Management in Standalone Microgrid Application," Energies, MDPI, vol. 14(6), pages 1-15, March.
    10. Taghavifar, Hadi & Zomorodian, Zahra Sadat, 2021. "Techno-economic viability of on grid micro-hybrid PV/wind/Gen system for an educational building in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    11. Alexander N. Kozlov & Nikita V. Tomin & Denis N. Sidorov & Electo E. S. Lora & Victor G. Kurbatsky, 2020. "Optimal Operation Control of PV-Biomass Gasifier-Diesel-Hybrid Systems Using Reinforcement Learning Techniques," Energies, MDPI, vol. 13(10), pages 1-20, May.
    12. Gaurav Chaudhary & Jacob J. Lamb & Odne S. Burheim & Bjørn Austbø, 2021. "Review of Energy Storage and Energy Management System Control Strategies in Microgrids," Energies, MDPI, vol. 14(16), pages 1-26, August.
    13. Vibha Kamaraj & N. Chellammal & Bharatiraja Chokkalingam & Josiah Lange Munda, 2020. "Minimization of Cross-Regulation in PV and Battery Connected Multi-Input Multi-Output DC to DC Converter," Energies, MDPI, vol. 13(24), pages 1-29, December.
    14. Aleksandr N. Tynda & Denis N. Sidorov, 2022. "Inverse Problem for the Integral Dynamic Models with Discontinuous Kernels," Mathematics, MDPI, vol. 10(21), pages 1-9, October.
    15. 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.
    16. Denis Sidorov & Fang Liu & Yonghui Sun, 2020. "Machine Learning for Energy Systems," Energies, MDPI, vol. 13(18), pages 1-6, September.

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