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Optimal location and sizing of renewable distributed generations and electric vehicle charging stations

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  • Guindi, Marina
  • Kamel, Rashad M.

Abstract

Many countries are aiming to replace gasoline-based vehicles with electric vehicles (EVs). The increasing adoption of EVs has led to a surge in the number of charging stations, significantly impacting the electrical grid with issues such as power quality degradation, increased losses, and voltage fluctuations. In response to these challenges, there is a growing interest in integrating distributed generation from unconventional and renewable sources into the grid to power EV Charging Stations (EVCSs). However, this integration poses new complexities, including increased power losses and voltage instability. Consequently, the optimal allocation and sizing of Renewable Distributed Generations (RDGs) and EVCSs have become critical planning considerations. This paper addresses these issues by formulating a multi-objective optimization problem aimed at minimizing power losses and improving the voltage profile of distribution systems. The study introduces several constraints, including the placement of EVCSs and RDGs at separate buses, and employs particle swarm optimization and cuckoo search algorithm to simultaneously determine the optimal locations and sizes of the RDGs and the optimal locations of the EVCSs. The effectiveness of the proposed techniques is demonstrated through simulations on IEEE 33 radial and meshed distribution systems, illustrating their capability to identify optimal configurations for integrating RDGs and EVCSs.

Suggested Citation

  • Guindi, Marina & Kamel, Rashad M., 2024. "Optimal location and sizing of renewable distributed generations and electric vehicle charging stations," Renewable Energy, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:renene:v:235:y:2024:i:c:s0960148124013405
    DOI: 10.1016/j.renene.2024.121272
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    References listed on IDEAS

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    1. Rezaee Jordehi, Ahmad, 2016. "Allocation of distributed generation units in electric power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 893-905.
    2. Saksit Deeum & Tossaporn Charoenchan & Natin Janjamraj & Sillawat Romphochai & Sergej Baum & Hideagi Ohgaki & Nadarajah Mithulananthan & Krischonme Bhumkittipich, 2023. "Optimal Placement of Electric Vehicle Charging Stations in an Active Distribution Grid with Photovoltaic and Battery Energy Storage System Integration," Energies, MDPI, vol. 16(22), pages 1-26, November.
    3. Eshan Karunarathne & Jagadeesh Pasupuleti & Janaka Ekanayake & Dilini Almeida, 2021. "The Optimal Placement and Sizing of Distributed Generation in an Active Distribution Network with Several Soft Open Points," Energies, MDPI, vol. 14(4), pages 1-20, February.
    4. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    5. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
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    1. Sumeet Sahay & Saubhagya Ranjan Biswal & Gauri Shankar & Amitkumar V. Jha & Deepak Kumar Gupta & Sarita Samal & Alin-Gheorghita Mazare & Nicu Bizon, 2025. "Optimal Integration of New Technologies and Energy Sources into Radial Distribution Systems Using Fuzzy African Vulture Algorithm," Sustainability, MDPI, vol. 17(4), pages 1-25, February.
    2. He, Li & Wu, Zhixin, 2024. "Advancing sustainable EV charging infrastructure: A hybrid solar-wind fast charging station with demand response," Renewable Energy, Elsevier, vol. 237(PC).

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