Optimizing Electric Vehicle Charging Stations and Distributed Generators in Smart Grids: A Multi-Objective Meta-Heuristic Approach
Keywords:
Distributed energy resources; Electric vehicle charging stations; Energy management; Electric vehicle; Metaheuristic algorithms; Multi-objective optimization; Power distribution systems;Smart grid planning.Abstract
The global transition towards electric mobility has significantly increased the demand for efficient and consumer-friendly Electric Vehicle Charging Stations (EVCSs). As electric vehicles (EVs) continue to penetrate transportation systems, optimal integration of EVCSs within power distribution infrastructure becomes critical, not only to ensure seamless user experience but also to maintain the reliability and efficiency of electrical networks. Traditionally, EVCS planning has been carried out solely within the context of Radial Distribution Networks (RDNs), neglecting key consumer-centric factors such as travel comfort and accessibility within the road network (RN). This paper proposes a novel, consumer-aware methodology for optimally placing EVCSs and Distributed Generators (DGs) in a combined RDN-RN framework. The objective is to minimize active power loss, voltage variation, and EV consumer cost, measured through two proposed indices, while accounting for realistic travel behavior and preferences. The proposed approach utilizes a Modified Weighted Teaching Learning Based - Particle Swarm Optimization Algorithm (MWTLB-PSA) and proceeds in three stages: EVCS site selection based on road network considerations, DG placement using predetermined EVCS locations, and a final stage of simultaneous optimization of both elements. To validate the approach, a standard IEEE 33-bus RDN integrated with a 25-node RN is employed as the test system. Results demonstrate that the joint optimization of DGs and EVCSs via the proposed method significantly enhances network performance and consumer convenience. Notably, the solution achieves a reduced active power loss of 57.75 kW and an EVCCI value of 0.3958, indicating a substantial improvement over existing hybrid TLBO and PSO-based techniques. Furthermore, the proposed method leads to installation cost savings ranging from 2.51% to 18.21% compared to earlier strategies, underscoring its practical value in smart grid planning and deployment.
Downloads
References
Knobloch, F., Hanssen, S., Lam, A. et al. Net emission reductions from electric cars and heat pumps in 59 world regions over time. Nat Sustain 3, 437–447 (2020). https://doi.org/10.1038/s41893-020-0488-7
Zhang, Runsen, and Shinichiro Fujimori. ”The role of transport electrification in global climate change mitigation scenarios.” Environmental Research Letters 15.3 (2020): 034019. DOI 10.1088/1748-9326/ab6658.
IEA (2018), Global EV Outlook 2018, IEA, Paris https://www.iea.org/reports/global-ev-outlook-2018, Licence: CC BY 4.0.
Saldan˜a, Gaizka, et al. ”Electric vehicle into the grid: Charging methodologies aimed at providing ancillary services considering battery degradation.”Energies 2019, 12(12), 2443; https://doi.org/10.3390/en12122443.
Solanke, Tirupati Uttamrao, et al. ”A review of strategic charging–discharging control of grid-connected electric vehicles.” Journal of Energy Storage 28 (2020): 101193. https://doi.org/10.1016/j.est.2020.101193.
Gupta, Rudraksh S., Arjun Tyagi, and S. Anand. ”Optimal allocation of electric vehicles charging infrastructure, policies and future trends.” Journal of Energy Storage 43 (2021): 103291.https://doi.org/10.1016/j.est.2021.103291.
Ghodusinejad, Mohammad Hasan, Younes Noorollahi, and Rahim Zahedi. ”Optimal site selection and sizing of solar EV charge stations.” Journal of Energy Storage 56 (2022): 105904.https://doi.org/10.1016/j.est.2022.105904.
Guo, Xiaogang, et al. ”Model predictive control considering scenario optimisation for microgrid dispatching with wind power and electric vehicle.” The Journal of Engineering 2017.13 (2017): 2539-2543. https://doi.org/10.1049/joe.2017.0785.
S. Deb, K. Tammi, K. Kalita and P. Mahanta, ”Charging Station Placement for Electric Vehicles: A Case Study of Guwahati City, India,” in IEEE Access, vol. 7, pp. 100270-100282, 2019, doi: 10.1109/AC- CESS.2019.2931055.
Zhu, Zhi-Hong, et al. ”Charging station location problem of plug-in electric vehicles.” Journal of Transport Geography 52 (2016): 11-22. https://doi.org/10.1016/j.jtrangeo.2016.02.002.
W. Yao et al., ”A Multi-Objective Collaborative Planning Strategy for Integrated Power Distribution and Electric Vehicle Charging Systems,” in IEEE Transactions on Power Systems, vol. 29, no. 4, pp. 1811-1821, July 2014, doi: 10.1109/TPWRS.2013.2296615.
Rawa, Muhyaddin, et al. ”Economical-technical-environmental operation of power networks with wind-solar-hydropower generation using analytic hierarchy process and improved grey wolf algorithm.” Ain Shams Engineering Journal 12.3 (2021): 2717-2734. https://doi.org/10.1016/j.asej.2021.02.004.
Clairand, Jean-Michel, et al. ”Optimal siting and sizing of electric taxi charging stations considering transportation and power system requirements.” Energy 256 (2022): 124572. https://doi.org/10.1016/j.energy.2022.124572.
D. B. R and V. M, ”Allocation of EV Charging Stations in a Micro- grid,” 2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG), Wollongong, Australia, 2023, pp. 1-6, doi: 10.1109/ETFG55873.2023.10408134.
A. Pal, A. Bhattacharya and A. K. Chakraborty, ”Allocation of EV Fast Charging Station with V2G Facility in Distribution Network,” 2019 8th International Conference on Power Systems (ICPS), Jaipur, India, 2019,pp. 1-6, doi: 10.1109/ICPS48983.2019.9067574.
Babu, P. V. K., & Swarnasri, K. (2020). ”Optimal integration of different types of DGs in radial distribution system by using Harris hawk optimization algorithm.” Cogent Engineering, 7(1). https://doi.org/10.1080/23311916.2020.1823156.
Lakshmi, G.V.N., Jayalaxmi, A. & Veeramsetty, V. ”Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm.” Technol Econ Smart Grids Sustain Energy 6, 9 (2021). https://doi.org/10.1007/s40866-021-00107-w.
Prasad, C.H., Subbaramaiah, K. & Sujatha, P. ”Cost–benefit analysis for optimal DG placement in distribution systems by using elephant herding optimization algorithm.” Renewables 6, 2 (2019). https://doi.org/10.1186/s40807-019-0056-9.
Memarzadeh, Gholamreza, and Farshid Keynia. ”A new index-based method for optimal DG placement in distribution networks.” Engineering Reports 2.10 (2020): e12243. https://doi.org/10.1002/eng2.12243.
Kumar, A., Verma, R., Choudhary, N. K., & Singh, N. (2023). “Optimal placement and sizing of distributed generation in power distribution system: a comprehensive review.” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45(3), 7160–7185. https://doi.org/10.1080/15567036.2023.2216167.
Haider, Waseem, et al. ”Voltage profile enhancement and loss minimization using optimal placement and sizing of distributed generation in reconfigured network.” Machines 2021, 9, 20. https://doi.org/10.3390/machines9010020.
Selim, Ali, et al. ”Optimal allocation of multiple types of distributed generations in radial distribution systems using a hybrid technique. ”Sustainability 2021, 13(12), 6644; https://doi.org/10.3390/su13126644.
ZABIHIA, Alireza; PARHAMFARB, Mohammad. Empowering the grid: toward the integration of electric vehicles and renewable energy in power systems. International Journal of Energy Security and Sustainable Energy, 2024, 2.1: 1-14. https://doi.org/10.5281/zenodo.12751722.
Parhamfar, Mohammad and Zabihi, Alireza, Decentralized Energy Solutions: The Impact of Smart Grid-Enabled EV Charging Stations. http://dx.doi.org/10.2139/ssrn.4961812
Zabihi, Alireza, and Mohammad Parhamfar. "Decentralized energy solutions: The impact of smart grid-enabled EV charging stations." Heliyon (2025). https://doi.org/10.1016/j.heliyon.2025.e41815
B. V. Kumar and A. F. M A, "Optimal Integration of EV Charging Stations and Capacitors for Net Present Value Maximization in Distribution Network," in IEEE Latin America Transactions, vol. 23, no. 3, pp. 239-250, March 2025, doi: 10.1109/TLA.2025.10879176
Ponnam, Venkata K. Babu, and K. Swarnasri. ”Multi-objective optimal allocation of electric vehicle charging stations and distributed generators in radial distribution systems using metaheuristic optimization algorithms.” Engineering, Technology & Applied Science Research 10.3 (2020): 5837-5844. https://doi.org/10.48084/etasr.3517.
Ahmad, F., Iqbal, A., Ashraf, I., Marzband, M., & Khan, I. (2022). ”Placement of electric vehicle fast charging stations in distribution network considering power loss, land cost, and electric vehicle population. Energy Sources,” Part A: Recovery, Utilization, and Environmental Effects, 44(1), 1693–1709. https://doi.org/10.1080/15567036.2022.2055233.
Bilal, Mohd, Fareed Ahmad, and M. Rizwan. ”Techno-economic assessment of grid and renewable powered electric vehicle charging stations in India using a modified metaheuristic technique.” Energy Conversion and Management 284 (2023): 116995. https://doi.org/10.1016/j.enconman.2023.116995.
R. Chakraborty, D. Das and P. Das, ”Optimal Placement of Electric Vehicle Charging Station with V2G Provision using Symbiotic Organisms Search Algorithm,” 2022 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), BHOPAL, India, 2022, pp. 1-6, doi: 10.1109/SCEECS54111.2022.9740988.
Hariri, Ali-Mohammad, Maryam A. Hejazi, and Hamed Hashemi-Dezaki. ”Reliability optimization of smart grid based on optimal allocation of protective devices, distributed energy resources, and electric vehicle/plug-in hybrid electric vehicle charging stations.” Journal of power sources 436 (2019): 226824. https://doi.org/10.1016/j.jpowsour.2019.226824.
Vijay, V., Venkaiah, C.,& Mallesham, V. (2022). ”Meta Heuristic Algorithm Based Multi Objective Optimal Planning of Rapid Charging Stations and Distribution Generators in a Distribution System Coupled with Transportation Network.” Advances in Electrical and Electronic Engineering, 20(4), 493-504. doi:10.15598/aeee.v20i4.4594.
Asghari Rad, Hamid, Meysam Jafari-Nokandi, and Seyed Mehdi Hosseini. "Optimal Allocation of Plug-in Electric Vehicle Parking Lots for Maximum Serviceability and Profit in the coupled distribution and transportation networks." Scientia Iranica 31.14 (2024): 1178-1196. https://doi.org/10.24200/sci.2022.58500.5768.
Shukla, Akanksha, Kusum Verma, and Rajesh Kumar. "Multi‐objective synergistic planning of EV fast‐charging stations in the distribution system coupled with the transportation network." IET Generation, Transmission & Distribution 13.15 (2019): 3421-3432. https://doi.org/10.1049/iet-gtd.2019.0486
Skaloumpakas, Panagiotis, et al. "A multi-criteria approach for optimizing the placement of electric vehicle charging stations in highways." Energies 15.24 (2022): 9445. https://doi.org/10.3390/en15249445
Amini, M. Hadi, Mohsen Parsa Moghaddam, and Orkun Karabasoglu. "Simultaneous allocation of electric vehicles’ parking lots and distributed renewable resources in smart power distribution networks." Sustainable cities and society 28 (2017): 332-342.https://doi.org/10.1016/j.scs.2016.10.006.
Unterluggauer, Tim, et al. "Electric vehicle charging infrastructure planning for integrated transportation and power distribution networks: A review." ETransportation 12 (2022): 100163. https://doi.org/10.1016/j.etran.2022.100163
Kawambwa, S., Mwifunyi, R., Mnyanghwalo, D. et al. An improved backward/forward sweep power flow method based on network tree depth for radial distribution systems. Journal of Electrical Systems and Inf Technol 8, 7 (2021). https://doi.org/10.1186/s43067-021-00031-0.
Ermis¸, S. (2023). ”Multi-Objective Optimal Power Flow Using a Modified Weighted Teaching-Learning Based Optimization Algorithm”. Electric Power Components and Systems, 51(20), 2536–2556. https://doi.org/10.1080/15325008.2023.2239237.
G. Wang, Z. Xu, F. Wen and K. P. Wong, "Traffic-Constrained Multiobjective Planning of Electric-Vehicle Charging Stations," in IEEE Transactions on Power Delivery, vol. 28, no. 4, pp. 2363-2372, Oct. 2013, doi: 10.1109/TPWRD.2013.226914.
Zou, Feng, Debao Chen, and Jiangtao Wang. "An Improved Teaching‐Learning‐Based Optimization with the Social Character of PSO for Global Optimization." Computational intelligence and neuroscience 2016.1 (2016): 4561507.https://doi.org/10.1155/2016/4561507.
