Published March 30, 2025 | Version CC-BY-NC-ND 4.0
Journal article Open

Enhancing Grid Stability-Bi-Directional V2G Integration in IEEE Distribution Networks with PSO

Authors/Creators

  • 1. Department of Electrical and Electronics Engineering, University of Bahrain, College of Engineering, Arad (Muharraq), Bahrain.

Contributors

  • 1. Department of Electrical and Electronics Engineering, University of Bahrain, College of Engineering, Arad (Muharraq), Bahrain.
  • 2. Assistant Professor, Department of Electrical and Electronics Engineering, University of Bahrain, College of Engineering, Arad (Muharraq), Bahrain.

Description

Abstract: This paper investigates the integration of bidirectional Vehicle-to-Grid (V2G) technology into the IEEE 33- bus distribution network to enhance grid stability, voltage regulation, and peak load management. V2G technology enables electric vehicles (EVs) to act as distributed energy resources, contributing to reactive power compensation and supporting voltage levels within the acceptable range of 0.95–1.05 p.u. Using a Particle Swarm Optimization (PSO) algorithm, the study identifies the optimal placement and sizing of EV batteries based on a 24-hour load forecast, emphasizing high-demand scenarios. The methodology incorporates load flow analysis, system constraints, and the dynamic interplay of EV charging and discharging cycles. The results demonstrate that strategically placed V2G-enabled EVs can significantly reduce peak demand by discharging energy during high-load periods, thereby decreasing the reliance on additional generation capacity. Additionally, EV integration enhances voltage stability and minimizes infrastructure stress, contributing to more resilient grid operations. However, the PSO algorithm exhibited certain limitations, including sensitivity to parameter settings and a tendency toward premature convergence, which may impact the optimization’s accuracy. These findings highlight the potential for hybrid optimization approaches to address such limitations and refine system performance. This research presents a scalable and practical framework for integrating V2G technology into modern power systems, aligning with the growing demand for renewable energy and sustainable energy management. By addressing critical challenges in EV deployment and grid stability, this study provides actionable insights for grid operators and paves the way for future advancements in optimization techniques and real-time control strategies for high-EV-penetration networks.

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Additional details

Identifiers

DOI
10.35940/ijrte.F8200.13060325
EISSN
2277-3878

Dates

Accepted
2025-03-15
Manuscript received on 26 December 2024 | Revised Manuscript received on 02 January 2025 | Second Revised Manuscript received on 28 January 2025 | Manuscript Accepted on 15 March 2025 | Manuscript published on 30 March 2025.

References

  • W. Kempton and J. Tomic, "Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy," J. Power Sources, vol. 144, no. 1, pp. 280–294, 2005. DOI: https://doi.org/10.1016/j.jpowsour.2004.12.022
  • K. M. Tan, V. K. Ramachandaramurthy, and J. Y. Yong, "Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques," Renew. Sustain. Energy Rev., vol. 53, pp. 720–732, 2016. DOI: https://doi.org/10.1016/j.rser.2015.09.012
  • H. Lund and W. Kempton, "Integration of renewable energy into the transport and electricity sectors through V2G," Energy Policy, vol. 36, no. 9, pp. 3578–3587, 2008. DOI: https://doi.org/10.1016/j.enpol.2008.06.007
  • Md. R. H. Mojumder et al., "Electric Vehicle-to-Grid (V2G) Technologies: Impact on the Power Grid and Battery," Sustainability, vol. 14, no. 21, p. 13856, 2022. DOI: https://doi.org/10.3390/su142113856
  • S. Giannelos et al., "Vehicle-to-Grid: Quantification of its Contribution to Security of Supply through the F-Factor Methodology," Sustain. Energy Res., vol. 11, no. 32, 2024. DOI: https://doi.org/10.1186/s40807- 024-00125-z
  • J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proc. ICNN'95 - Int. Conf. Neural Networks, Perth, WA, Australia, 1995, pp. 1942–1948. DOI: https://doi.org/10.1109/ICNN.1995.488968
  • C. Guille and G. Gross, "Aconceptual framework for the vehicle-to-grid (V2G) implementation," Energy Policy, vol. 37, no. 11, pp. 4379–4390, 2009. DOI: https://doi.org/10.1016/j.enpol.2009.05.053
  • M. Escoto et al., "Optimization Challenges in Vehicle-to-Grid (V2G) Systems and Artificial Intelligence Solving Methods," Applied Sciences, vol. 14, no. 12, p. 5211, 2024. DOI: https://doi.org/10.3390/app14125211
  • M. J. Khan and Y. Kumar, "Optimal Power Flow (OPF) formulation and Reactive Power Optimization of Power Systems Using Conventional Optimization Technique (Interior Point Method)", International Journal of Mathematics Research. ISSN 0976-5840 Volume 8, Number 3 (2016), pp. 251-263 © International Research Publication House. http://www.irphouse.com/ijmr16/ijmrv8n3_11.pdf
  • N. Ghanbari and S. Bhattacharya, "SoC Balancing of Different Energy Storage Systems in DC Microgrids Using Modified Droop Control," 2005. DOI: https://doi.org/10.1109/IECON.2018.8592890
  • M. E. Elnozahy, A. M. S. Youssef, and M. M. Abdel-Akher, "Optimal Sizing and Operation Strategy of Hybrid PV-Wind-Diesel-Battery Systems," Renew. Energy, vol. 78, pp. 527–531, Sept. 2015. DOI: https://doi.org/10.1016/j.renene.2015.01.030
  • G. Celli, E. Ghiani, S. Mocci, and F. Pilo, "A multiobjective evolutionary algorithm for the sizing and siting of distributed generation," IEEE Trans. Power Syst., vol. 20, no. 2, pp. 750–757, May 2005. DOI: https://doi.org/10.1109/TPWRS.2005.846219
  • C. Wang and P. B. Luh, "A Fast and Efficient Algorithm for Power Network Reconfiguration in the Presence of Distributed Generation," IEEE Trans. Power Syst., vol. 29, no. 4, pp. 1742–1749, Jul. 2014. DOI: https://doi.org/10.1109/TPWRS.2014.2307091
  • Y. Shi and R. Eberhart, "Parameter Selection in Particle Swarm Optimization," in Evolutionary Programming VII, New York, NY, USA: Springer, 1998, pp. 591–600. DOI: https://doi.org/10.1007/BFb0040810
  • H. G. Beyer and H. P. Schwefel, "Evolution Strategies – A Comprehensive Introduction," Natural Computing, vol. 1, pp. 3–52, Mar. 2002. DOI: https://doi.org/10.1023/A:1015059928466
  • M. E. Baran and F. F. Wu, "Network reconfiguration in distribution systems for loss reduction and load balancing," IEEE Trans. Power Delivery, vol. 4, no. 2, pp. 1401–1407, Apr. 1989. DOI: https://doi.org/10.1109/61.25627
  • IEEE Std 399-1997, "IEEE Recommended Practice for Industrial and Commercial Power Systems Analysis." DOI: https://doi.org/10.1109/IEEESTD.1998.88568
  • IEEE Std 1547-2018, "IEEE Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces." DOI: https://doi.org/10.1109/IEEESTD.2018.8332112
  • IEEE Std 1159-2019, "IEEE Recommended Practice for Monitoring Electric Power Quality." DOI: https://doi.org/10.1109/IEEESTD.2019.8796486
  • J. H. DeCarolis et al., "Optimal placement of electric vehicle charging stations for sustainable operation," IEEE Trans. Smart Grid, vol. 9, no. 6, pp. 6285–6294, Nov. 2018. DOI: https://doi.org/10.3390/en16227628
  • M. A. Z. Choudhury et al., "Smart charging strategies for electric vehicles to improve grid reliability," IEEE Trans. Power Syst., vol. 34, no. 3, pp. 1862–1870, May 2019. DOI: https://doi.org/10.1109/TPWRS.2018.2858741
  • C. W. Tan et al., "Impact of electric vehicle charging on grid performance and strategies for load management," IEEE Access, vol. 8, pp. 102367–102378, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2993921
  • J. H. DeCarolis, "Vehicle-to-grid technology and its potential impact on energy storage," IEEE Trans. Smart Grid, vol. 8, no. 5, pp. 2434– 2441, Sept. 2017. https://ieeexplore.ieee.org/document/9030787
  • M. A. Z. Choudhury et al., "Smart charging and vehicle-to-grid for enhancing the reliability of the electricity grid," IEEE Trans. Power Syst., vol. 34, no. 3, pp. 1880–1889, May 2019. https://changingtransport.org/wp content/uploads/2021_Smart_Charging_Strategies_and_technologies_f or_Electric_Vehicles.pdf
  • C. W. Tan et al., "Impact of EV and V2G technology on peak shaving in power systems," IEEE Access, vol. 8, pp. 102367–102378, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2993921
  • N.Janaki, R.Krishna Kumar, Enhanced ‗BDABDC-DC' System for Vehicle To Grid Technology. (2019). In International Journal of Recent Technology and Engineering (Vol. 8, Issue 2S11, pp. 4021–4025). DOI: https://doi.org/10.35940/ijrte.B1548.0982S1119
  • Sri, R. S., Laditya, U., Ram, D. R., & Kiran, K. V. D. (2019). Lightweight Security and Privacy Safeguard strategies for Smart Grid management in Client-side Networks. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 2, pp. 917–923). DOI: https://doi.org/10.35940/ijitee.B7143.129219
  • Gupta, S. K. (2022). Smart Grid System in India. In Indian Journal of Energy and Energy Resources (Vol. 1, Issue 4, pp. 5–6). DOI: https://doi.org/10.54105/ijeer.C1018.081422
  • Sharma, T., & Sharma, R. (2024). Smart Grid Monitoring: Enhancing Reliability and Efficiency in Energy Distribution. In Indian Journal of Data Communication and Networking (Vol. 4, Issue 2, pp. 1–4). DOI: https://doi.org/10.54105/ijdcn.D7954.04020224
  • Sattenapalli, S., & Manohar, V. J. (2019). Research on Single-Phase Grid Connected PV Systems. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 2, pp. 5549–5555). DOI: https://doi.org/10.35940/ijeat.B5159.129219