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Optimal scheduling and techno-economic analysis of electric vehicles by implementing solar-based grid-tied charging station

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  • Ullah, Zia
  • Wang, Shaorong
  • Wu, Guan
  • Hasanien, Hany M.
  • Rehman, Anis Ur
  • Turky, Rania A.
  • Elkadeem, Mohamed R.

Abstract

The integration of Electric Vehicles (EVs) and Photovoltaics (PVs) into the electric power distribution system is rising worldwide due to the environmental concerns and the rapid depletion of fossil fuels. However, the simultaneous integration of EVs and PVs in the power system poses challenges of uncertain power penetration, charging, and dynamic loading conditions, which requires a suitable control design and scheduling optimization to keep the modified electric system stable. This paper proposes a solar-based grid-tied charging station (SGTCS) that optimizes EV charging by enabling the scheduling technique resulting in maximum utilization of PV power. The proposed model also identifies and considers seasonal variation effects of power generation and EV charging connectivity. The SGTCS is implemented using HOMER Grid, and a case study of a practical locality in Islamabad was investigated; the conducted detailed analysis comprises the annual cost estimation, energy costs, EV scheduling, main grid power usage reduction, and the impact of environmental changes. Examining the integration of small and big EVs in the grid-tied solar-integrated charging system, a brief scheduling strategy of 250 sessions per day is analyzed. The resultant techno-economic implications are presented, depicting the proposed study's relevance and applicability.

Suggested Citation

  • Ullah, Zia & Wang, Shaorong & Wu, Guan & Hasanien, Hany M. & Rehman, Anis Ur & Turky, Rania A. & Elkadeem, Mohamed R., 2023. "Optimal scheduling and techno-economic analysis of electric vehicles by implementing solar-based grid-tied charging station," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034478
    DOI: 10.1016/j.energy.2022.126560
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    References listed on IDEAS

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    Cited by:

    1. Li, Da & Zhang, Lei & Zhang, Zhaosheng & Liu, Peng & Deng, Junjun & Wang, Qiushi & Wang, Zhenpo, 2023. "Battery safety issue detection in real-world electric vehicles by integrated modeling and voltage abnormality," Energy, Elsevier, vol. 284(C).
    2. Ullah, Zia & Rehman, Anis Ur & Wang, Shaorong & Hasanien, Hany M. & Luo, Peng & Elkadeem, Mohamed R. & Abido, Mohammad A., 2023. "IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration," Energy, Elsevier, vol. 282(C).
    3. Sheeraz Iqbal & Nahar F. Alshammari & Mokhtar Shouran & Jabir Massoud, 2024. "Smart and Sustainable Wireless Electric Vehicle Charging Strategy with Renewable Energy and Internet of Things Integration," Sustainability, MDPI, vol. 16(6), pages 1-25, March.
    4. Rehman, Anis Ur & Shafiq, Aqib & Ullah, Zia & Iqbal, Sheeraz & Hasanien, Hany M., 2023. "Implications of smart grid and customer involvement in energy management and economics," Energy, Elsevier, vol. 276(C).
    5. Rehman, Anis Ur & Ullah, Zia & Shafiq, Aqib & Hasanien, Hany M. & Luo, Peng & Badshah, Fazal, 2023. "Load management, energy economics, and environmental protection nexus considering PV-based EV charging stations," Energy, Elsevier, vol. 281(C).

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