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Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution Network

Author

Listed:
  • Sharmistha Nandi

    (School of Electrical Engineering, KIIT Deemed to be University, Bhubaneswar 751024, India)

  • Sriparna Roy Ghatak

    (School of Electrical Engineering, KIIT Deemed to be University, Bhubaneswar 751024, India)

  • Parimal Acharjee

    (Electrical Engineering Department, National Institute of Technology, Durgapur 713209, India)

  • Fernando Lopes

    (National Laboratory of Energy and Geology, 1649-038 Lisbon, Portugal)

Abstract

In the present work, a strategic multi-scenario EV ultra-fast charging station (CS) planning framework is designed to provide advantages to charging station owners, Distribution Network Operators, and EV owners. Locations of CSs are identified using zonal division and the Voltage Stability Index strategy. The number of chargers is determined using the Harris Hawk Optimization (HHO) technique while minimizing the installation, operational costs of CS, and energy loss costs considering all the power system security constraints. To ensure a realistic planning model, uncertainties in EV charging behavior and electricity prices are managed through the 2m-Point Estimate Method. This method produces multiple scenarios of uncertain parameters, which effectively represent the actual dataset, thereby facilitating comprehensive multi-scenario planning. This study incorporates annual EV and system load growth in a long-term planning model of ten years, ensuring the distribution network meets future demand for sustainable transportation infrastructure. The proposed research work is tested on a 33-bus distribution network and a 51-bus real Indian distribution network. To evaluate the financial and environmental benefits of the planning, a cost-benefit analysis in terms of the Return-on-Investment index and a carbon emission analysis are performed, respectively. Furthermore, to prove the efficacy of the HHO technique, the results are compared with several existing algorithms.

Suggested Citation

  • Sharmistha Nandi & Sriparna Roy Ghatak & Parimal Acharjee & Fernando Lopes, 2024. "Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution Network," Energies, MDPI, vol. 17(17), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4204-:d:1462232
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    References listed on IDEAS

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    1. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    2. Sunoh Kim & Jin Hur, 2020. "A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis," Energies, MDPI, vol. 13(20), pages 1-13, October.
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