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Integration of Large Scale PV-Based Generation into Power Systems: A Survey

Author

Listed:
  • Elyas Rakhshani

    (Department of Electrical Sustainable Energy, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands)

  • Kumars Rouzbehi

    (Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Sevilla, Spain)

  • Adolfo J. Sánchez

    (Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Sevilla, Spain)

  • Ana Cabrera Tobar

    (Department of Electrical Engineering, Universidad Técnica del Norte, Av. 17 de julio s/n, 100150 Ibarra, Ecuador)

  • Edris Pouresmaeil

    (Department of Electrical Engineering and Automation, Aalto University, Maarintie 8, 02150 Espoo, Finland)

Abstract

This paper reports a general overview of current research on analysis and control of the power grid with grid scale PV-based power generations as well as of various consequences of grid scale integration of PV generation units into the power systems. Moreover, the history of PV renewable growth, deregulation of power system and issues related to grid-connected PV systems considering its contribution to various responsibilities like frequency control, virtual inertia capabilities and voltage regulation are discussed. Moreover, various outcomes of the high-penetrated grid with PV power plants such as power quality, active and reactive power control, protection, balancing and reliability under various loading conditions are reviewed and discussed.

Suggested Citation

  • Elyas Rakhshani & Kumars Rouzbehi & Adolfo J. Sánchez & Ana Cabrera Tobar & Edris Pouresmaeil, 2019. "Integration of Large Scale PV-Based Generation into Power Systems: A Survey," Energies, MDPI, vol. 12(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1425-:d:222554
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    References listed on IDEAS

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    Cited by:

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    8. Mohammed Ali Khan & Ahteshamul Haque & Frede Blaabjerg & Varaha Satya Bharath Kurukuru & Huai Wang, 2021. "Intelligent Transition Control between Grid-Connected and Standalone Modes of Three-Phase Grid-Integrated Distributed Generation Systems," Energies, MDPI, vol. 14(13), pages 1-21, July.
    9. Tomasz Sikorski & Michal Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyla & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2020. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects," Energies, MDPI, vol. 13(12), pages 1-30, June.
    10. Aqachmar, Zineb & Campana, Pietro Elia & Bouhal, Tarik & El Qarnia, Hamid & Outzourhit, Abdelkader & Alami Ibnouelghazi, El & Mouak, Said & Aqachmar, Atman, 2022. "Electrification of Africa through CPV installations in small-scale industrial applications: Energetic, economic, and environmental analysis," Renewable Energy, Elsevier, vol. 197(C), pages 723-746.
    11. Yeuntae Yoo & Gilsoo Jang & Jeong-Hwan Kim & Iseul Nam & Minhan Yoon & Seungmin Jung, 2019. "Accuracy Improvement Method of Energy Storage Utilization with DC Voltage Estimation in Large-Scale Photovoltaic Power Plants," Energies, MDPI, vol. 12(20), pages 1-15, October.
    12. Minli Wang & Peihong Wang & Tao Zhang, 2022. "Evidential Extreme Learning Machine Algorithm-Based Day-Ahead Photovoltaic Power Forecasting," Energies, MDPI, vol. 15(11), pages 1-25, May.
    13. Jäger-Waldau, Arnulf & Kougias, Ioannis & Taylor, Nigel & Thiel, Christian, 2020. "How photovoltaics can contribute to GHG emission reductions of 55% in the EU by 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    14. Hiyam Farhat & Coriolano Salvini, 2022. "Novel Gas Turbine Challenges to Support the Clean Energy Transition," Energies, MDPI, vol. 15(15), pages 1-17, July.
    15. Wieland Van De Sande & Omid Alavi & Philippe Nivelle & Jan D’Haen & Michaël Daenen, 2020. "Thermo-Mechanical Stress Comparison of a GaN and SiC MOSFET for Photovoltaic Applications," Energies, MDPI, vol. 13(22), pages 1-17, November.
    16. Kaloop, Mosbeh R. & Bardhan, Abidhan & Kardani, Navid & Samui, Pijush & Hu, Jong Wan & Ramzy, Ahmed, 2021. "Novel application of adaptive swarm intelligence techniques coupled with adaptive network-based fuzzy inference system in predicting photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    17. Yaser I. Alamin & Mensah K. Anaty & José Domingo Álvarez Hervás & Khalid Bouziane & Manuel Pérez García & Reda Yaagoubi & María del Mar Castilla & Merouan Belkasmi & Mohammed Aggour, 2020. "Very Short-Term Power Forecasting of High Concentrator Photovoltaic Power Facility by Implementing Artificial Neural Network," Energies, MDPI, vol. 13(13), pages 1-16, July.

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