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An intelligent optimal charging stations placement on the grid system for the electric vehicle application

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  • Polisetty, S.P.R. Swamy
  • Jayanthi, R.
  • Sai Veerraju, M.

Abstract

In smart cities, electrified vehicle plays a vital role. Due to the number of electric vehicles increasing rate, the optimised deployment of the charging station without maximum loss and voltage imbalance is required. Many existing strategies studied for the optimal charging station deployment result in higher power utilisation, power loss, harmonic distortion and voltage imbalance. Therefore a novel Dove-based Recursive Deep Network (DbRDN) was planned to implement. The DG grid system is initially created by integrating hybrid wind, solar and hydropower sources. Subsequently, the DbRDN is designed for the optimal location for the placement of the EV charging station by analysing load and line data. Moreover, the efficiency of the developed system is evaluated at both the balanced and unbalanced conditions and the outcomes are computed in terms of power loss, harmonic distortion, voltage imbalance, error and accuracy. The results are compared with prevailing techniques to validate the improvement score.

Suggested Citation

  • Polisetty, S.P.R. Swamy & Jayanthi, R. & Sai Veerraju, M., 2023. "An intelligent optimal charging stations placement on the grid system for the electric vehicle application," Energy, Elsevier, vol. 285(C).
  • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223028943
    DOI: 10.1016/j.energy.2023.129500
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    References listed on IDEAS

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    1. Ajit Kumar Mohanty & Perli Suresh Babu & Surender Reddy Salkuti, 2022. "Fuzzy-Based Simultaneous Optimal Placement of Electric Vehicle Charging Stations, Distributed Generators, and DSTATCOM in a Distribution System," Energies, MDPI, vol. 15(22), pages 1-22, November.
    2. Ioakimidis, Christos S. & Thomas, Dimitrios & Rycerski, Pawel & Genikomsakis, Konstantinos N., 2018. "Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot," Energy, Elsevier, vol. 148(C), pages 148-158.
    3. Deb, Sanchari & Gao, Xiao-Zhi & Tammi, Kari & Kalita, Karuna & Mahanta, Pinakeswar, 2021. "A novel chicken swarm and teaching learning based algorithm for electric vehicle charging station placement problem," Energy, Elsevier, vol. 220(C).
    4. Nandini K. Krishnamurthy & Jayalakshmi N. Sabhahit & Vinay Kumar Jadoun & Dattatraya Narayan Gaonkar & Ashish Shrivastava & Vidya S. Rao & Ganesh Kudva, 2023. "Optimal Placement and Sizing of Electric Vehicle Charging Infrastructure in a Grid-Tied DC Microgrid Using Modified TLBO Method," Energies, MDPI, vol. 16(4), pages 1-27, February.
    5. Dong, Yingchao & Zhang, Hongli & Ma, Ping & Wang, Cong & Zhou, Xiaojun, 2023. "A hybrid robust-interval optimization approach for integrated energy systems planning under uncertainties," Energy, Elsevier, vol. 274(C).
    6. Nagaraju Dharavat & Suresh Kumar Sudabattula & Suresh Velamuri & Sachin Mishra & Naveen Kumar Sharma & Mohit Bajaj & Elmazeg Elgamli & Mokhtar Shouran & Salah Kamel, 2022. "Optimal Allocation of Renewable Distributed Generators and Electric Vehicles in a Distribution System Using the Political Optimization Algorithm," Energies, MDPI, vol. 15(18), pages 1-25, September.
    7. Carlos D. Zuluaga-Ríos & Alejandro Villa-Jaramillo & Sergio D. Saldarriaga-Zuluaga, 2022. "Evaluation of Distributed Generation and Electric Vehicles Hosting Capacity in Islanded DC Grids Considering EV Uncertainty," Energies, MDPI, vol. 15(20), pages 1-17, October.
    8. Hassan Shokouhandeh & Mehrdad Ahmadi Kamarposhti & Fariba Asghari & Ilhami Colak & Kei Eguchi, 2022. "Distributed Generation Management in Smart Grid with the Participation of Electric Vehicles with Respect to the Vehicle Owners’ Opinion by Using the Imperialist Competitive Algorithm," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
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