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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. Abdelfattah, Wael & Abdelhamid, Ahmed Sayed & Hasanien, Hany M. & Rashad, Basem Abd-Elhamed, 2024. "Smart vehicle-to-grid integration strategy for enhancing distribution system performance and electric vehicle profitability," Energy, Elsevier, vol. 302(C).

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