Optimal Placement Of Mono-Facial PV With EVCS In Distribution Systems Using Grey Wolf Optimization
DOI:
https://doi.org/10.29284/cxeb6374Keywords:
Electric Vehicle Charging Stations , Power distribution system , Particle Swarm Optimization algorithm , Grey Wolf Optimization algorithm, Optimization, Monofacial PV, IEEE 33-bus System.Abstract
This study proposes a novel Grey Wolf Optimization (GWO) strategy for optimal Electric Vehicle Charging Station (EVCS) placement in power distribution systems to minimize losses and improve voltage stability. Evaluated on the IEEE 33-bus benchmark against Particle Swarm Optimization (PSO), GWO demonstrates superior performance in reducing power losses and enhancing voltage profiles within operational limits. A probabilistic analysis further validates its robustness under uncertain EV charging patterns, offering distribution operators a reliable approach to integrate growing EV fleets while cutting costs and ensuring grid reliability.
References
[1] N. Himabindu, S. Hampannavar, B. Deepa, and M. Swapna, “Analysis of microgrid integrated Photovoltaic (PV) Powered Electric Vehicle Charging Stations (EVCS) under different solar irradiation conditions in India: A way towards sustainable development and growth,” Energy Reports, vol. 7, 2021, doi: 10.1016/j.egyr.2021.10.103.
[2] T. D. de Lima, J. F. Franco, F. Lezama, J. Soares, and Z. Vale, “Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions,” Energy Informatics, vol. 4, 2021, doi: 10.1186/s42162-021-00157-5.
[3] M. H. Cedillo, H. Sun, J. Jiang, and Y. Cao, “Dynamic pricing and control for EV charging stations with solar generation,” Appl. Energy, vol. 326, 2022, doi: 10.1016/j.apenergy.2022.119920.
[4] K. Sayed, A. G. Abo-Khalil, and A. S. Alghamdi, “Optimum resilient operation and control DC microgrid based electric vehicles charging station powered by renewable energy sources,” Energies, vol. 12, no. 22, 2019, doi: 10.3390/en12224240.
[5] A. K. Podder et al., “Feasibility assessment of hybrid solar photovoltaic‐biogas generator based charging station: A case of easy bike and auto rickshaw scenario in a developing nation,” Sustain., vol. 14, no. 1, 2022, doi: 10.3390/su14010166.
[6] M. Ahmadi, H. J. Kaleybar, M. Brenna, F. Castelli-dezza, and M. S. Carmeli, “Integration of distributed energy resources and EV fast-charging infrastructure in high-speed railway systems,” Electron., vol. 10, no. 20, 2021, doi: 10.3390/electronics10202555.
[7] G. Valdmanis, M. Rieksta, I. Luksta, and G. Bazbauers, “Solar Energy Based Charging for Electric Vehicles at Fuel Stations,” Environ. Clim. Technol., vol. 26, no. 1, 2022, doi: 10.2478/rtuect-2022-0088.
[8] P. M. De Quevedo, G. Munoz-Delgado, and J. Contreras, “Impact of Electric Vehicles on the Expansion Planning of Distribution Systems Considering Renewable Energy, Storage, and Charging Stations,” IEEE Trans. Smart Grid, vol. 10, no. 1, 2019, doi: 10.1109/TSG.2017.2752303.
[9] A. Khan, S. Memon, and T. P. Sattar, “Analyzing Integrated Renewable Energy and Smart-Grid Systems to Improve Voltage Quality and Harmonic Distortion Losses at Electric-Vehicle Charging Stations,” IEEE Access, vol. 6, 2018, doi: 10.1109/ACCESS.2018.2830187.
[10] M. A. Mohamed and F. A. Mohamed, “Design and Simulate an Off-Grid PV System with a Battery Bank for EV Charging,” Univers. J. Electr. Electron. Eng., vol. 7, no. 5, 2020, doi: 10.13189/ujeee.2020.070502.
[11] A. Hassoune, M. Khafallah, A. Mesbahi, L. Benaaouinate, and T. Bouragba, “Control strategies of a smart topology of EVs charging station based grid tied RES-battery,” Int. Rev. Electr. Eng., vol. 13, no. 5, 2018, doi: 10.15866/iree.v13i5.15520.
[12] F. Lo Franco, M. Ricco, R. Mandrioli, and G. Grandi, “Electric vehicle aggregate power flow prediction and smart charging system for distributed renewable energy self-consumption optimization,” Energies, vol. 13, no. 18, 2020, doi: 10.3390/en13195003.
[13] S. Bansal, Y. Zong, S. You, L. Mihet-Popa, and J. Xiao, “Technical and economic analysis of one-stop charging stations for battery and fuel cell EV with renewable energy sources,” Energies, vol. 13, no. 11, 2020, doi: 10.3390/en13112855.
[14] V. J. Vijayalakshmi, P. Arumugam, A. Ananthi Christy, and R. Brindha, “Simultaneous allocation of EV charging stations and renewable energy sources: An Elite RERNN-m2MPA approach,” Int. J. Energy Res., vol. 46, no. 7, 2022, doi: 10.1002/er.7780.
[15] G. P. Shirsat, “Simulation of grid connected ev charging station with renewable energy source,” Int. J. Adv. Trends Comput. Sci. Eng., vol. 8, no. 1.4 S1, 2019, doi: 10.30534/ijatcse/2019/6481.42019.
[16] Nouri, A.; Lachheb, A.; El Amraoui, L. Optimizing efficiency of Vehicle-to-Grid system with intelligent management and ANN-PSO algorithm for battery electric vehicles. Electr. Power Syst. Res. 2024, 226, 109936.
[17] Huy, T.H.B.; Dinh, H.T.; Kim, D. Multi-objective framework for a home energy management system with the integration of solar energy and an electric vehicle using an augmented ε-constraint method and lexicographic optimization. Sustain. Cities Soc. 2023, 88, 104289.
[18] Bibak, B.; Bai, L. An optimization approach for managing electric vehicle and reused battery charging in a vehicle to grid system under an electricity rate with demand charge. Sustain. Energy Grids Netw. 2023, 36, 101145.
[19] Allouhi, A.; Rehman, S. Grid-connected hybrid renewable energy systems for supermarkets with electric vehicle charging platforms: Optimization and sensitivity analyses. Energy Rep. 2023, 9, 3305–3318.
[20] Metwly, M.Y.; Ahmed, M.; Hamad, M.S.; Abdel-Khalik, A.S.; Hamdan, E.; Elmalhy, N.A. Power management optimization of electric vehicles for grid frequency regulation: Comparative study. Alex. Eng. J. 2023, 65, 749–760.
[21] Hassan, S.U.; Yousif, M.; Khan, S.N.; Kazmi, S.A.A.; Imran, K. A decision-centric approach for techno-economic optimization and environmental assessment of standalone and grid-integrated renewable-powered electric vehicle charging stations under multiple planning horizons. Energy Convers. Manag. 2023, 294, 117571.
[22] Liu, J.; Wu, H.; Huang, H.; Yang, H. Renewable Energy Design and Optimization for a Net-Zero Energy Building Integrating Electric Vehicles and Battery Storage Considering Grid Flexibility. Available online: www.elsevier.com/locate/enconman (accessed on 21 October 2023).
[23] Abdullah-Al-Nahid, S.; Khan, T.A.; Taseen, M.A.; Jamal, T.; Aziz, T. A novel consumer-friendly electric vehicle charging scheme with vehicle to grid provision supported by genetic algorithm based optimization. J. Energy Storage 2022, 50, 104655.
[24] Taha, H.A.; Alham, M.H.; Youssef, H.K.M. Multi-Objective Optimization for Optimal Allocation and Coordination of Wind and Solar PVs, BESSs and Capacitors in Presence of Demand Response. IEEE Access 2022, 10, 16225–16241.
[25] S. Deb, K. Tammi, X. -Z. Gao, K. Kalita and P. Mahanta, "A Hybrid Multi-Objective Chicken Swarm Optimization and Teaching Learning Based Algorithm for Charging Station Placement Problem," in IEEE Access, vol. 8, pp. 92573-92590, 2020. doi: 10.1109/ACCESS.2020.2994298.
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

