Energy Management of the Distribution Network Considering Electric Vehicles Connected to the Grid

Articles in Press

Document Type : Research paper

Authors

Department of Electrical and Biomedical Engineering, Mazandaran University of Science and Technology, Babol, Iran.

Abstract

Given the growing trend in the electric vehicle industry and the increasing use of electric vehicles (EVs), the management and control of EV charging in electric distribution networks are becoming crucial. The widespread presence of electric vehicles has led to an increased load on the distribution network. This increase in electrical load can cause problems during peak hours and in specific network locations. To prevent these issues and improve the efficiency of the power grid, controlling the charging of electric vehicles is essential. By utilizing electric vehicle charging management systems, it is possible to intelligently control vehicle charging during times of lower electrical demand on the grid. These systems can initiate EV charging when the grid load is low and suspend it during peak load periods. This improvement in electric vehicle charging scheduling contributes to enhanced power grid efficiency and reduces issues related to electrical load. In this article, the charging and discharging management of electric vehicles in a standard sample microgrid, considering a load response program, is analyzed. The CPLEX solver in MATLAB is used for solving the optimization problem. To achieve this, an appropriate objective function is defined based on the load response program in the microgrid. Then, using the proposed CPLEX approach and considering operational constraints, optimal energy management of the microgrid is performed. Simulation results indicate that without proper planning for electric vehicle charging in the microgrid, the utilization of the microgrid leads to an 18% increase in costs.

Keywords

Main Subjects

References

  1. M. Megrini, A. Gaga, and Y. Mehdaoui, “Review of electric vehicle traction motors, control systems, and various implementation cards,” J. Oper. Autom. Power Eng., vol. 13, no. 3, pp. 238–247, 2025.
  2. E. Littwitz and O. Ayalon, “Feasibility analysis of storage and renewable energy ancillary services for grid operations,” Energies, vol. 18, no. 11, p. 2836, 2025.
  3. S. Mohammad and A. Ghasemi-Marzbali, “Fast-charging station for electric vehicles, challenges and issues: A comprehensive review,” J. Energy Storage, vol. 49, p. 104136, 2022.
  4. M. A. El-Meligy, M. Sharaf, K. A. Alnowibet, and A. E. Abdelgawad, “A second-order cone programming-based microgrid bidding strategy considering real-time market price correlation,” Electr. Eng., pp. 1–14, 2025.
  5. M. Farhoumandi, S. Bahramirad, M. Shahidehpour, and A. Alabdulwahab, “Blockchain for peer-to-peer energy trading in electric vehicle charging stations with constrained power distribution and urban transportation networks,” Energy Internet, vol. 2, no. 1, pp. 28–44, 2025.
  6. S. Chinnaperumal, S. K. Raju, A. H. Alharbi, S. Kannan, D. S. Khafaga, M. Periyasamy, M. M. Eid, and E.-S. M. ElKenawy, “Decentralized energy optimization using blockchain with battery storage and electric vehicle networks,” Sci. Rep., vol. 15, no. 1, p. 5940, 2025.
  7. S. Kumar, K. C. Ramaswamy, S. R. Mathiyalagan, J. Giri, and M. Kanan, “An efficient battery management system for electric vehicles using IoT and blockchain,” Results Eng., p. 106284, 2025.
  8. M. C. Kintner-Meyer, S. Sridhar, C. Holland, A. Singhal,
    K. E. Wolf, C. J. Larimer, C. R. McGrath, A. A. Bleeker, and R. E. Murali, “Electric vehicles at scale–phase II–distribution systems analysis,” Tech. Rep. PNNL-32460, Pacific Northwest National Lab. (PNNL), Richland, WA, USA, 2022.
  9. S. Gupta, A. Maulik, D. Das, and A. Singh, “Coordinated stochastic optimal energy management of grid-connected microgrids considering demand response, plug-in hybrid electric vehicles, and smart transformers,” Renew. Sustain. Energy Rev., vol. 155, p. 111861, 2022.
  10. Z. Yang, F. Yang, H. Min, H. Tian, W. Hu, J. Liu, and N. Eghbalian, “Energy management programming to reduce distribution network operating costs in the presence of electric vehicles and renewable energy sources,” Energy, vol. 263, p. 125695, 2023.
  11. S. Rahman, I. A. Khan, A. A. Khan, A. Mallik, and M. F. Nadeem, “Comprehensive review and impact analysis of integrating projected electric vehicle charging load to the existing low voltage distribution system,” Renew. Sustain. Energy Rev., vol. 153, p. 111756, 2022.
  12. K. Bakht, S. A. R. Kashif, M. S. Fakhar, I. A. Khan, and G. Abbas, “Accelerated particle swarm optimization algorithms coupled with analysis of variance for intelligent charging of plug-in hybrid electric vehicles,” Energies, vol. 16, no. 7, p. 3210, 2023.
  13. J. Hu, D. Liu, C. Du, F. Yan, and C. Lv, “Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition,” Energy, vol. 198, p. 117298, 2020.
  14. H. F. Gharibeh, A. S. Yazdankhah, and M. R. Azizian, “Energy management of fuel cell electric vehicles based on working condition identification of energy storage systems, vehicle driving performance, and dynamic power factor,” J. Energy Storage, vol. 31, p. 101760, 2020.
  15. B. Xu, D. Rathod, D. Zhang, A. Yebi, X. Zhang, X. Li, and Z. Filipi, “Parametric study on reinforcement learning optimized energy management strategy for a hybrid electric vehicle,” Appl. Energy, vol. 259, p. 114200, 2020.
  16. X. Hou, J. Wang, T. Huang, T. Wang, and P. Wang, “Smart home energy management optimization method considering energy storage and electric vehicle,” IEEE Access, vol. 7, pp. 144010–144020, 2019.
  17. C. Yang, M. Zha, W. Wang, K. Liu, and C. Xiang, “Efficient energy management strategy for hybrid electric vehicles and plug-in hybrid electric vehicles: review and recent advances under intelligent transportation system,” IET Intell. Transp. Syst., vol. 14, no. 7, pp. 702–711, 2020.
  18. A. M. Fernandez, M. Kandidayeni, L. Boulon, and H. Chaoui, “An adaptive state machine based energy management strategy for a multi-stack fuel cell hybrid electric vehicle,” IEEE Trans. Veh. Technol., vol. 69, no. 1, pp. 220–234, 2019.
  19. H. Dang, Y. Han, Y. Hao, P. Sun, and Z. Chen, “Energy management optimization of plug-in hybrid electric vehicle in microgrid with information-physics-traffic coupling,” Electr. Power Syst. Res., vol. 238, p. 111194, 2025.
  20. A. B. Etemesi, T. F. Megahed, H. Kanaya, and D. E. A. Mansour, “IoT-based energy management of smart microgrid considering electric vehicle integration,” Energy, p. 136405, 2025.
  21. K. Kioumarsi and A. Bolurian, “Optimal energy management for electric vehicle charging parking lots considering renewable energy resources and accurate battery characteristic modeling,” J. Energy Storage, vol. 107, p. 114914, 2025.
  22. T. Hai, N. S. S. Singh, and F. Jamal, “Energy management of a microgrid with integration of renewable energy sources considering energy storage systems with electricity price,” J. Energy Storage, vol. 110, p. 115191, 2025.
  23. L. Wang, Q. Sun, X. Wang, T. Shi, X. Yang, and H. Xu, “Low carbon planning of flexible distribution network considering orderly charging and discharging of electric vehicles,” Electr. Power Syst. Res., vol. 244, p. 111546, 2025.
  24. S. Abdullah-Al-Nahid, T. A. Khan, M. A. Taseen, T. Jamal, and T. Aziz, “A novel consumer-friendly electric vehicle charging scheme with vehicle-to-grid provision supported by genetic algorithm-based optimization,” J. Energy Storage, vol. 50, p. 104655, 2022.
  25. X. Hu, C. Zou, X. Tang, T. Liu, and L. Hu, “Cost-optimal energy management of hybrid electric vehicles using fuel cell and battery health-aware predictive control,” IEEE Trans. Power Electron., vol. 35, no. 1, pp. 382–392, 2019.
  26. M. A. Mohamed, H. M. Abdullah, M. A. El-Meligy, M. Sharaf, A. T. Soliman, and A. Hajjiah, “A novel fuzzy cloud stochastic framework for energy management of renewable microgrids based on maximum deployment of electric vehicles,” Int. J. Electr. Power Energy Syst., vol. 129, p. 106845, 2021.
  27. Y. Zhou, H. Li, A. Ravey, and M.-C. Péra, “An integrated predictive energy management for light-duty range-extended plug-in fuel cell electric vehicle,” J. Power Sources, vol. 451, p. 227780, 2020.
  28. M. A. Babajani-Chari and A. Ghasemi-Marzbali, “Stochastic optimization of a multi-carrier energy system with the participation of renewable energy sources and integrated demand response programs,” Sci. Iran, 2025.
  29. S. A. Mansouri, A. Ahmarinejad, E. Nematbakhsh, M. S. Javadi, A. R. Jordehi, and J. P. Catalao, “Energy management in microgrids including smart homes: A multi-objective approach,” Sustain. Cities Soc., p. 102852, 2021.
Journal of Operation and Automation in Power Engineering

Articles in Press, Corrected Proof
Available Online from 18 July 2026

Files

History

  • Receive Date: 31 December 2024
  • Revise Date: 14 September 2025
  • Accept Date: 22 September 2025
  • First Publish Date: 18 July 2026

Share

How to cite

Statistics