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Impact of Electric Vehicle Charging Station Load on Distribution Network

Author

Listed:
  • Sanchari Deb

    (Centre for Energy, Indian Institute of Technology, Guwahati 781039, Assam, India)

  • Kari Tammi

    (Department of Mechanical Engineering, Aalto University, 02150 Espoo, Finland)

  • Karuna Kalita

    (Department of Mechanical Engineering, Indian Institute of Technology, Guwahati 781039, Assam, India)

  • Pinakeshwar Mahanta

    (Department of Mechanical Engineering, Indian Institute of Technology, Guwahati 781039, Assam, India)

Abstract

Recent concerns about environmental pollution and escalating energy consumption accompanied by the advancements in battery technology have initiated the electrification of the transportation sector. With the universal resurgence of Electric Vehicles (EVs) the adverse impact of the EV charging loads on the operating parameters of the power system has been noticed. The detrimental impact of EV charging station loads on the electricity distribution network cannot be neglected. The high charging loads of the fast charging stations results in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. Further, the penalty paid by the utility for the degrading performance of the power system cannot be neglected. This work aims to investigate the impact of the EV charging station loads on the voltage stability, power losses, reliability indices, as well as economic losses of the distribution network. The entire analysis is performed on the IEEE 33 bus test system representing a standard radial distribution network for six different cases of EV charging station placement. It is observed that the system can withstand placement of fast charging stations at the strong buses up to a certain level, but the placement of fast charging stations at the weak buses of the system hampers the smooth operation of the power system. Further, a strategy for the placement of the EV charging stations on the distribution network is proposed based on a novel Voltage stability, Reliability, and Power loss (VRP) index. The results obtained indicate the efficacy of the VRP index.

Suggested Citation

  • Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeshwar Mahanta, 2018. "Impact of Electric Vehicle Charging Station Load on Distribution Network," Energies, MDPI, vol. 11(1), pages 1-25, January.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:178-:d:126875
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    References listed on IDEAS

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    1. Md Morshed Alam & Saad Mekhilef & Mehdi Seyedmahmoudian & Ben Horan, 2017. "Dynamic Charging of Electric Vehicle with Negligible Power Transfer Fluctuation," Energies, MDPI, vol. 10(5), pages 1-20, May.
    2. Da Zhu & Dominic Pasquale Patella & Roland Steinmetz & Pajnapa Peamsilpakulchorn, 2016. "The Bhutan Electric Vehicle Initiative," World Bank Publications - Books, The World Bank Group, number 23735, December.
    3. Sehar, Fakeha & Pipattanasomporn, Manisa & Rahman, Saifur, 2017. "Demand management to mitigate impacts of plug-in electric vehicle fast charge in buildings with renewables," Energy, Elsevier, vol. 120(C), pages 642-651.
    4. Blesl, Markus & Das, Anjana & Fahl, Ulrich & Remme, Uwe, 2007. "Role of energy efficiency standards in reducing CO2 emissions in Germany: An assessment with TIMES," Energy Policy, Elsevier, vol. 35(2), pages 772-785, February.
    5. Qiang Wang & Rongrong Li & Rui Jiang, 2016. "Decoupling and Decomposition Analysis of Carbon Emissions from Industry: A Case Study from China," Sustainability, MDPI, vol. 8(10), pages 1-17, October.
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