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Optimization of Vehicle-to-Grid, Grid-to-Vehicle, and Vehicle-to-Everything Systems Using Artificial Bee Colony Optimization

Author

Listed:
  • Sairoel Amertet Finecomess

    (High School of Automation and Robotics, Peter the Great Saint Petersburg Polytechnic University, 195220 Saint Petersburg, Russia)

  • Girma Gebresenbet

    (Department of Energy and Technology, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden)

  • Wogen Yigebahal Zada

    (High School of Nuclear and Heat Power Engineering, Peter the Great Saint Petersburg Polytechnic University, 195220 Saint Petersburg, Russia)

  • Yohannes Mulugeta

    (Department of Mechanical Engineering, Mizan Tepi University, Tepi P.O. Box 120, Ethiopia)

  • Aleme Addisie

    (Department of Mechanical Engineering, Dilla University, Dilla P.O. Box 419, Ethiopia)

Abstract

The integration of vehicle-to-grid (V2G), grid-to-vehicle (G2V), and vehicle-to-everything (V2X) systems into an energy ecosystem represents a transformative approach. These systems enable bidirectional energy flow between electric vehicles (EVs), power grids, and other entities. In this study, the energy sources for the V2G, G2V, and V2X systems were derived from green and blue energies, emphasizing sustainability. The primary objective of this research is to optimize V2G, G2V, and V2X systems, focusing on enhancing their performance. The novel contribution of this work lies in the application of advanced optimization techniques, specifically Artificial Bee Colony Optimization (ABCO), to improve system efficiency and stability. The system was simulated in MATLAB, where ABCO achieved a 64.5% improvement in reactive power optimization over Brain Emotional Intelligent Control (BEIC ). This result underscores the effectiveness of ABCO in optimizing energy exchange within the V2G, G2V, and V2X systems, confirming its suitability for these applications. These findings highlight the potential of ABCO to enhance the performance of V2G, G2V, and V2X systems, contributing to a more sustainable, resilient, and efficient energy ecosystem.

Suggested Citation

  • Sairoel Amertet Finecomess & Girma Gebresenbet & Wogen Yigebahal Zada & Yohannes Mulugeta & Aleme Addisie, 2025. "Optimization of Vehicle-to-Grid, Grid-to-Vehicle, and Vehicle-to-Everything Systems Using Artificial Bee Colony Optimization," Energies, MDPI, vol. 18(8), pages 1-30, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2046-:d:1636007
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