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PV based EV charging at universities using supplied historical PV output ramp

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  • Islam, Md Shariful
  • Mithulananthan, N.

Abstract

Optimal PV based EV charging is performed either by predicting or by measuring PV output. However, due to the uncertainties associated with the variables involved, both the charging methods are not only disposed to significant voltage limit violations but also may cause PV energy harvest reduction. Hence, a methodology is proposed in this paper, which utilizes the measured PV output of a given sample and the supplied historical ramp to predict the PV output of the immediate next sample using a non-iterative method. The charging rates of the EV population are, subsequently, adjusted in the interval between the successive samples based on the predicted PV output with the help of a proposed SOC based charging strategy. The proposed methodology has been tested at the University of Queensland (UQ)’s solar and parking facilities coupled with its electric grid. The results show that aside from reducing the probability of voltage limit violations (PVV), the proposed methodology can increase the PV energy harvest. Moreover, it is cost-effective as compared to the conventional method such as onsite battery energy storage deployment.

Suggested Citation

  • Islam, Md Shariful & Mithulananthan, N., 2018. "PV based EV charging at universities using supplied historical PV output ramp," Renewable Energy, Elsevier, vol. 118(C), pages 306-327.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:306-327
    DOI: 10.1016/j.renene.2017.11.009
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    References listed on IDEAS

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    1. Drude, Lukas & Pereira Junior, Luiz Carlos & Rüther, Ricardo, 2014. "Photovoltaics (PV) and electric vehicle-to-grid (V2G) strategies for peak demand reduction in urban regions in Brazil in a smart grid environment," Renewable Energy, Elsevier, vol. 68(C), pages 443-451.
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    5. Zhang, Qi & Tezuka, Tetsuo & Ishihara, Keiichi N. & Mclellan, Benjamin C., 2012. "Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan," Renewable Energy, Elsevier, vol. 44(C), pages 99-108.
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    Cited by:

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    4. Pei Huang & Xingxing Zhang & Benedetta Copertaro & Puneet Kumar Saini & Da Yan & Yi Wu & Xiangjie Chen, 2020. "A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)," Sustainability, MDPI, vol. 12(17), pages 1-37, August.
    5. Konara, K.M.S.Y. & Kolhe, Mohan & Sharma, Arvind, 2020. "Power flow management controller within a grid connected photovoltaic based active generator as a finite state machine using hierarchical approach with droop characteristics," Renewable Energy, Elsevier, vol. 155(C), pages 1021-1031.
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    7. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).

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