GA-optimized FOPID control for LVRT enhancement in PV–EV integrated power systems

Authors

Article ID: 753
132 Views

DOI:

https://doi.org/10.18686/cest753

Keywords:

electric vehicle charging; photovoltaic integration; low-voltage ridethrough; fractional-order PID; genetic algorithm optimization; PSS®E; WECC generic models; Kundur two-area system

Abstract

Rapid growth in electric vehicle (EV) deployment, combined with high photovoltaic (PV) penetration, is reshaping the dynamic behavior of transmission networks. As PV inverters displace synchronous machines, the resulting loss of rotational inertia heightens vulnerability to fault-induced voltage sags and oscillatory instability. Co-located EV charging loads further stress weakened voltage profiles, increasing the risk of failing low-voltage ride-through (LVRT) requirements. This paper proposes a genetic algorithm (GA)-optimized fractional-order PID (FOPID) controller with five tunable parameters (Kp, Ki, Kd, λ, μ) to regulate the voltage/reactive-power output of an EV aggregator at a critical load bus. A conventional three-gain PID controller optimized by the same GA under identical cost function and constraints serves as the benchmark. Both controllers are evaluated on the Kundur two-area system in PSS®E, where Buses 1 and 3 host PV plants supplying 50% of generation while Buses 2 and 4 retain synchronous excitation. The EV aggregator at Bus 7 is modeled using WECC second-generation generic converter modules with a negative-generation sign convention, and the FOPID action is discretized via Grünwald–Letnikov recursion. Under a solid three-phase fault on the Bus 7–8 tie-line cleared after 100 ms, the GA-FOPID controller recovers Bus 7 voltage to the 0.9–1.1 pu band within 250 ms and maintains 95% in-band operation over the 4 s post-fault window. The GA-PID controller fails to stabilize the system, causing interconnection separation, while the uncontrolled case collapses entirely. Inter-area rotor-angle traces confirm GA-FOPID confines the first post-fault swing and damps subsequent oscillations, whereas neither alternative maintains synchronism, demonstrating that fractional-order parameters measurably improve LVRT compliance and transient damping in PV–EV co-located systems.

Downloads

Published

2026-03-27

How to Cite

Altarjami, I. A. (2026). GA-optimized FOPID control for LVRT enhancement in PV–EV integrated power systems. Clean Energy Science and Technology, 4(2). https://doi.org/10.18686/cest753

Issue

Vol. 4 No. 2 (2026)

Section

Article

License

Copyright (c) 2026 Ibrahim A. Altarjami

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

1. Saha S, Saleem MI, Roy TK. Impact of high penetration of renewable energy sources on grid frequency behaviour. International Journal of Electrical Power & Energy Systems. 2023; 145: 108701. DOI: https://doi.org/10.1016/j.ijepes.2022.108701

2. Lei S, Zhang Y, Shahidehpour M, et al. Guest editorial: operational and structural resilience of power grids with high penetration of renewables. IET Renewable Power Generation. 2024; 18(7): 1055–1059. DOI: https://doi.org/10.1049/rpg2.13002

3. Maghami MR, Thang KF, Mutambara AG, et al. Optimized planning of electric vehicle charging infrastructure for grid performance improvement. Discover Sustainability. 2025; 6(1): 706. DOI: https://doi.org/10.1007/s43621-025-01522-0

4. Srivastava A, Manas M, Dubey RK. Electric vehicle integration’s impacts on power quality in distribution network and associated mitigation measures: A review. Journal of Engineering and Applied Science. 2023; 70(1): 32. DOI: https://doi.org/10.1186/s44147-023-00193-w

5. Nguyen HNT, Zhang C, Zhang J. Dynamic demand control of electric vehicles to support the power grid with a high penetration level of renewable energy. IEEE Transactions on Transportation Electrification. 2016; 2(4): 361–370. doi: 10.1109/TTE.2016.2519821 DOI: https://doi.org/10.1109/TTE.2016.2519821

6. Nguyen HNT, Zhang C, Mahmud MA. Optimal coordination of G2V and V2G to support power grids with high penetration of renewable energy. IEEE Transactions on Transportation Electrification. 2015; 1(1): 100–109. doi: 10.1109/TTE.2015.2430288 DOI: https://doi.org/10.1109/TTE.2015.2430288

7. Esther S, Singh SK, Goswami A, et al. Recent challenges in vehicle-to-grid integrated renewable energy systems: A review. In: Proceedings of the 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS); 14–15 June 2018; Madurai, India. pp. 161–166. doi: 10.1109/ICCONS.2018.8663031 DOI: https://doi.org/10.1109/ICCONS.2018.8663031

8. Rajendran A, Krishnan S, Hany S, et al. A review of the prospects of electric vehicles to improve the dynamics of renewable energy-rich power systems. AIP Conference Proceedings. 2021; 2391(1): 020016. doi: 10.1063/5.0066323 DOI: https://doi.org/10.1063/5.0066323

9. Bartolini A, Comodi G, Salvi D, et al. Renewables self-consumption potential in districts with high penetration of electric vehicles. Energy. 2020; 213: 118653. doi: 10.1016/j.energy.2020.118653 DOI: https://doi.org/10.1016/j.energy.2020.118653

10. Pina A, Ioakimidis CS, Ferrao P. Introduction of electric vehicles in an island as a driver to increase renewable energy penetration. In: Proceedings of the 2008 IEEE International Conference on Sustainable Energy Technologies; 24–27 November 2008; Singapore. pp. 1108–1113. doi: 10.1109/ICSET.2008.4747172 DOI: https://doi.org/10.1109/ICSET.2008.4747172

11. Kadurek P, Ioakimidis C, Ferrao P. Electric Vehicles and their impact to the electric grid in isolated systems. In: Proceedings of the 2009 International Conference on Power Engineering, Energy and Electrical Drives; 18–20 March 2009; Lisbon, Portugal. pp. 49–54. doi: 10.1109/POWERENG.2009.4915218 DOI: https://doi.org/10.1109/POWERENG.2009.4915218

12. Ezzat M, Benbouzid M, Muyeen SM, et al. Low-voltage ride-through techniques for DFIG-based wind turbines: state-of-the-art review and future trends. In: Proceedings of the IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society; 10–13 November 2013; Vienna, Austria. pp. 7681–7686. doi: 10.1109/IECON.2013.6700413 DOI: https://doi.org/10.1109/IECON.2013.6700413

13. Muhamad Zahim Sujod, Muhammad Muttaqin A. Rahim, Nor Azwan Mohamed Kamari, et al. Performance Analysis of Photovoltaic and Wind Turbine Grid-Connected Systems under LVRT Conditions. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences. 2024; 115(1): 143–155. doi: 10.37934/arfmts.115.1.143155 DOI: https://doi.org/10.37934/arfmts.115.1.143155

14. Rini Ann Jerin A, Kaliannan P, Subramaniam U, et al. Review on FRT solutions for improving transient stability in DFIG‐WTs. IET Renewable Power Generation. 2018; 12(15): 1786–1799. doi: 10.1049/iet-rpg.2018.5249 DOI: https://doi.org/10.1049/iet-rpg.2018.5249

15. Rini Ann Jerin A, Prabaharan N, Palanisamy K, et al. A Review on Low Voltage Ride Through capability in wind turbines of India and challenges in implementation. In: Proceedings of the 1st International Conference on Large-Scale Grid Integration of Renewable Energy in New Delhi, India; 6–8 September 2017; Delhi, India.

16. Ntuli WK, Kabeya M, Moloi K. Review of Low Voltage Ride-Through Capabilities in Wind Energy Conversion System. Energies. 2024; 17(21): 5321. doi: 10.3390/en17215321 DOI: https://doi.org/10.3390/en17215321

17. Rabie A, Ghanem A, Kaddah SS, et al. Electric vehicles based electric power grid support: A review. International Journal of Power Electronics and Drive Systems (IJPEDS). 2023; 14(1): 589–605. doi: 10.11591/ijpeds.v14.i1.pp589-605 DOI: https://doi.org/10.11591/ijpeds.v14.i1.pp589-605

18. Tavakoli A, Saha S, Arif MT, et al. Impacts of grid integration of solar PV and electric vehicle on grid stability, power quality and energy economics: A review. IET Energy Systems Integration. 2020; 2(3): 243–260. doi: 10.1049/iet-esi.2019.0047 DOI: https://doi.org/10.1049/iet-esi.2019.0047

19. Tabassum S, Babu ARV, Dheer DK. Adaptive energy management strategy for sustainable xEV charging stations in hybrid microgrid architecture. Science and Technology for Energy Transition. 2025; 80: 22. DOI: https://doi.org/10.2516/stet/2025002

20. Shrestha RR, Zhou Z, Barua L, et al. Smart charging impact analysis using clustering methods and real-world distribution feeders. In: Proceedings of the 2025 IEEE Power & Energy Society General Meeting (PESGM); 27–31 July 2025; Austin, TX, USA. DOI: https://doi.org/10.1109/PESGM52009.2025.11225552

21. Juma SA, Ayeng’o SP, Kimambo CZ. A review of control strategies for optimized microgrid operations. IET Renewable Power Generation. 2024; 18(14): 2785–2818. DOI: https://doi.org/10.1049/rpg2.13056

22. Bouderres N, Kerdoun D, Djellad A, et al. Optimization of fractional order PI controller by PSO algorithm applied to a grid-connected photovoltaic system. Journal Européen des Systèmes Automatisés. 2022; 65(4). DOI: https://doi.org/10.18280/jesa.550401

23. Mohamed KA, Alyazidi NM, Eltayeb A, et al. Enhancing load frequency control in single-area power systems: A comparative study of PID, FOPID, GA, and PSO-based optimization techniques. In: Proceedings of the 2025 IEEE 22nd International Multi-Conference on Systems, Signals & Devices; 17–20 February 2025; Monastir, Tunisia. pp. 988–993. DOI: https://doi.org/10.1109/SSD64182.2025.10989904

24. İnci M, Çelik Ö, Lashab A, et al. Power system integration of electric vehicles: a review on impacts and contributions to the smart grid. Applied Sciences. 2024; 14(6): 2246. doi: 10.3390/app14062246 DOI: https://doi.org/10.3390/app14062246

25. Umair M, Hidayat NM, Nik Ali NH, et al. The effect of vehicle-to-grid integration on power grid stability: A review. IOP Conference Series: Earth and Environmental Science. 2023; 1281(1): 012070. doi: 10.1088/1755-1315/1281/1/012070 DOI: https://doi.org/10.1088/1755-1315/1281/1/012070

26. Painuli S, Rawat M, Rayudu DR. A comprehensive review of electric vehicles operation, development, and grid stability. In: Proceedings of the 2018 International Conference on Power Energy, Environment and Intelligent Control (PEEIC); 13–14 April 2018; Greater Noida, India. pp. 265–269. doi: 10.1109/PEEIC.2018.8665643 DOI: https://doi.org/10.1109/PEEIC.2018.8665643

27. Dharmakeerthi CH, Mithulananthan N, Saha TK. Overview of the impacts of plug-in electric vehicles on the power grid. In: Proceedings of the 2011 IEEE PES Innovative Smart Grid Technologies; 13–16 November 2011; Perth, Australia. pp. 1–6. doi: 10.1109/ISGT-ASIA.2011.6167115 DOI: https://doi.org/10.1109/ISGT-Asia.2011.6167115

28. Kundur P, Paserba J, Ajjarapu V, et al. Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions. IEEE Transactions on Power Systems. 2004; 19(3): 1387–1401. doi: 10.1109/TPWRS.2004.82598 DOI: https://doi.org/10.1109/TPWRS.2004.825981

29. Mohamed MJ, Khashan A. Comparison between PID and FOPID controllers based on particle swarm optimization. In: Proceedings of the Second Engineering Conference of Control, Computers and Mechatronics Engineering; 25–27 February 2014; Baghdad, Iraq.

30. Elgezouli DE, Eltayeb H, Abdoon MA. Novel GPID: Grünwald–Letnikov fractional PID for enhanced adaptive cruise control. Fractal and Fractional. 2024; 8(12): 751. DOI: https://doi.org/10.3390/fractalfract8120751

31. Haupt RL, Haupt SE. Practical Genetic Algorithms, 2nd ed. John Wiley & Sons; 2004. DOI: https://doi.org/10.1002/0471671746

32. Illinois Center for a Smarter Electric Grid. Available online: https://icseg.iti.illinois.edu/power-cases/ (accessed on 1 January 2026).

33. Electric Power Research Institute. Model User Guide for Generic Renewable Energy System Models. Electric Power Research Institute; 2023.

34. Hasan R, Masud MS, Haque N, et al. Frequency control of nuclear-renewable hybrid energy systems using optimal PID and FOPID controllers. Heliyon. 2022; 8(11). DOI: https://doi.org/10.1016/j.heliyon.2022.e11770