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Effects of charging battery electric vehicles on local grid regarding standardized load profile in administration sector

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  • Blasius, Erik
  • Wang, Zhenqi

Abstract

Integration of battery electric vehicles (BEV) as load could have an impact on the stability of local grids. With the experiment conducted in a research project, real-time metering data of the charging points was collected, with which the charging process, user behavior and furthermore modeling of default pattern on a working-place charging station park are presented and further discussed in this paper. The simultaneity of load peak from uncontrolled charging processes and from the local load profile could cause local grid bottleneck. A BEV pool model to generate random charging sessions on a workday, which conforms the real behavior in this research case, is proposed. Charging strategies were developed and considered as centralized or decentralized. The simulation shows the influence of delay charging start time and demonstrate the potential of peak load reduction from charging of several BEV and furthermore of a large-scale construction of charging infrastructure.

Suggested Citation

  • Blasius, Erik & Wang, Zhenqi, 2018. "Effects of charging battery electric vehicles on local grid regarding standardized load profile in administration sector," Applied Energy, Elsevier, vol. 224(C), pages 330-339.
    • Handle: RePEc:eee:appene:v:224:y:2018:i:c:p:330-339
    DOI: 10.1016/j.apenergy.2018.04.073
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    References listed on IDEAS

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    1. Godina, Radu & Rodrigues, Eduardo M.G. & Matias, João C.O. & Catalão, João P.S., 2016. "Smart electric vehicle charging scheduler for overloading prevention of an industry client power distribution transformer," Applied Energy, Elsevier, vol. 178(C), pages 29-42.
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    2. Chen, Jianhong & Zhang, Youlang & Li, Xinzhou & Sun, Bo & Liao, Qiangqiang & Tao, Yibin & Wang, Zhiqin, 2020. "Strategic integration of vehicle-to-home system with home distributed photovoltaic power generation in Shanghai," Applied Energy, Elsevier, vol. 263(C).
    3. Chitchai Srithapon & Prasanta Ghosh & Apirat Siritaratiwat & Rongrit Chatthaworn, 2020. "Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost," Energies, MDPI, vol. 13(2), pages 1-20, January.
    4. Michael von Bonin & Elias Dörre & Hadi Al-Khzouz & Martin Braun & Xian Zhou, 2022. "Impact of Dynamic Electricity Tariff and Home PV System Incentives on Electric Vehicle Charging Behavior: Study on Potential Grid Implications and Economic Effects for Households," Energies, MDPI, vol. 15(3), pages 1-28, February.
    5. Adrian Chmielewski & Piotr Piórkowski & Krzysztof Bogdziński & Jakub Możaryn, 2023. "Application of a Bidirectional DC/DC Converter to Control the Power Distribution in the Battery–Ultracapacitor System," Energies, MDPI, vol. 16(9), pages 1-40, April.
    6. Hong Zhao & Li Wang & Zonghai Chen & Xiangming He, 2019. "Challenges of Fast Charging for Electric Vehicles and the Role of Red Phosphorous as Anode Material: Review," Energies, MDPI, vol. 12(20), pages 1-23, October.
    7. Knüpfer, Kristina & Mäll, Martin & Esteban, Miguel & Shibayama, Tomoya, 2021. "Review of mixed-technology vehicle fleet evolution and representation in modelling studies: Policy contexts of Germany and Japan," Energy Policy, Elsevier, vol. 156(C).
    8. Makeen, Peter & Ghali, Hani A. & Memon, Saim & Duan, Fang, 2022. "Impacts of electric vehicle fast charging under dynamic temperature and humidity: Experimental and theoretically validated model analyses," Energy, Elsevier, vol. 261(PB).

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