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An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grids

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  • Rahbari, Omid
  • Vafaeipour, Majid
  • Omar, Noshin
  • Rosen, Marc A.
  • Hegazy, Omar
  • Timmermans, Jean-Marc
  • Heibati, Seyedmohammadreza
  • Bossche, Peter Van Den

Abstract

This study proposes a practical solution to deal with challenges of integrating renewable energy sources and electric vehicles into the electric grid, considering generation source intermittency and energy usage inconsistency, via a new adaptive intelligent controller. The present research describes a smart grid consisting of power plants and distributed generation, fueled via photovoltaic panels and wind turbines, and augmented with electric vehicles as power storage devices. Employing a parking lot to deal with challenges such as low penetration of the electric vehicles embedded with Vehicle-to-Grid functionalities encounters two difficulties: where they should be installed, and modeling of bi-directional power flow between electric vehicles, the grid, and the distributed generation system. In this regard, a nonlinear multi-objective problem is designed and solved via employing the Non-dominated Sorting Genetic Algorithm-II, and the forward and backward substitution method. In addition, Newton-Raphson Power Flow is adopted and modified to calculate the power flow of the distribution network. The results related to optimal placement and sizing of hybrid renewable energy systems show that bus 16 of the studied grid is the best place to integrate a parking lot – equipped with 117 photovoltaic and 10 wind turbine units - to the tested IEEE-26 buses. Furthermore, this study suggests that the aforementioned grid could employ a complex versatile control unit able to optimize the operating point, scheduling charging and discharging for a large number of electric vehicles while considering the technical aspects (total active power loss and voltage deviation). In this regard, a new hybrid control approach based on Particle Swarm Optimization-Adaptive Neuro-Fuzzy Inference System tuned via utilizing the optimal power flow problem is proposed. The controller's superiority to handle grid-to-vehicle and vehicle-to-grid services is discussed and compared to other studies.

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  • Rahbari, Omid & Vafaeipour, Majid & Omar, Noshin & Rosen, Marc A. & Hegazy, Omar & Timmermans, Jean-Marc & Heibati, Seyedmohammadreza & Bossche, Peter Van Den, 2017. "An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grids," Energy, Elsevier, vol. 134(C), pages 1053-1067.
    • Handle: RePEc:eee:energy:v:134:y:2017:i:c:p:1053-1067
    DOI: 10.1016/j.energy.2017.06.007
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    3. Sharma, S. & Jain, Prerna, 2023. "Risk-averse integrated DR and dynamic V2G scheduling of parking lot operator for enhanced market efficiency," Energy, Elsevier, vol. 275(C).
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    6. Jiménez-Castillo, G. & Muñoz-Rodriguez, F.J. & Rus-Casas, C. & Talavera, D.L., 2020. "A new approach based on economic profitability to sizing the photovoltaic generator in self-consumption systems without storage," Renewable Energy, Elsevier, vol. 148(C), pages 1017-1033.
    7. Tran, Dai-Duong & Vafaeipour, Majid & El Baghdadi, Mohamed & Barrero, Ricardo & Van Mierlo, Joeri & Hegazy, Omar, 2020. "Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
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    9. Jenn, Alan PhD & Brown, Austin PhD, 2021. "Green Charging of Electric Vehicles Under a Net-Zero Emissions Policy Transition in California," Institute of Transportation Studies, Working Paper Series qt2rv3h345, Institute of Transportation Studies, UC Davis.
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    11. Omid Rahbari & Noshin Omar & Joeri Van Mierlo & Marc A. Rosen & Thierry Coosemans & Maitane Berecibar, 2019. "Electric Vehicle Battery Lifetime Extension through an Intelligent Double-Layer Control Scheme," Energies, MDPI, vol. 12(8), pages 1-24, April.
    12. Jenn, Alan, 2023. "Emissions of electric vehicles in California’s transition to carbon neutrality," Applied Energy, Elsevier, vol. 339(C).
    13. Rahbari, Omid & Omar, Noshin & Firouz, Yousef & Rosen, Marc A. & Goutam, Shovon & Van Den Bossche, Peter & Van Mierlo, Joeri, 2018. "A novel state of charge and capacity estimation technique for electric vehicles connected to a smart grid based on inverse theory and a metaheuristic algorithm," Energy, Elsevier, vol. 155(C), pages 1047-1058.
    14. Sidra Mumtaz & Saima Ali & Saghir Ahmad & Laiq Khan & Syed Zulqadar Hassan & Tariq Kamal, 2017. "Energy Management and Control of Plug-In Hybrid Electric Vehicle Charging Stations in a Grid-Connected Hybrid Power System," Energies, MDPI, vol. 10(11), pages 1-21, November.
    15. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
    16. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2017. "The feasibility of solar parking lots for electric vehicles," Energy, Elsevier, vol. 140(P1), pages 1182-1197.
    17. Xiaoxu Yang & Yuming Liu & Kai Liu & Guangzhong Hu & Xi Zhao, 2022. "Research on Promotion and Application Strategy of Electric Equipment in Plateau Railway Tunnel Based on Evolutionary Game," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    18. Stavros Lazarou & Vasiliki Vita & Christos Christodoulou & Lambros Ekonomou, 2018. "Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables’ Production," Energies, MDPI, vol. 11(9), pages 1-15, September.
    19. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    20. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Optimal scheduling of distributed energy resources in smart grids: A complementarity approach," Energy, Elsevier, vol. 141(C), pages 2135-2144.
    21. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    22. Mostafa Rezaeimozafar & Mohsen Eskandari & Mohammad Hadi Amini & Mohammad Hasan Moradi & Pierluigi Siano, 2020. "A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids," Energies, MDPI, vol. 13(7), pages 1-25, April.
    23. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    24. Mahyar Alinejad & Omid Rezaei & Reza Habibifar & Mahdi Azimian, 2022. "A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    25. Ji, Shou-feng & Zhao, Dan & Luo, Rong-juan, 2019. "Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles," Energy, Elsevier, vol. 189(C).

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