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Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review

Yıl 2024, Cilt: 37 Sayı: 3, 1256 - 1285, 01.09.2024

Prabhakar Karthikeyan Shanmugam , Polly Thomas

https://doi.org/10.35378/gujs.1321572

Öz

Based on information from recent research, by 2045, Electric Vehicles (EV) will dominate the roads with presence of more than 80% of its kind. Hence, these vehicles' grid level penetration will increase proportionally, which challenges the existing grid infrastructure in terms of its reliability and energy management capabilities. New techniques to store and consume massive quantities of energy from the power grid, as well as infusing the captive energy within the EV in response to grid demands, are emerging with the advent of electric vehicles. Everything could be handled smoothly only if we schedule the EV operation (charging/discharging) more optimally and efficiently using scheduling algorithms. Despite the existence of many routings and charging schedule computations, nature-inspired optimization approaches might play a critical role in responding to such routing challenges. Researchers have created several optimum scheduling approaches, such as Dynamic Programming, Differential Evolutionary Optimization Techniques, Collaborative Optimization Scheduling, Two-stage optimal scheduling strategy, and so on. The optimum schedule review examines the operation of an EV fleet while considering uncertainty sources and varied EV operating circumstances by integrating heuristic and meta-heuristic techniques. This paper exhibits a deep review on the various EV optimal scheduling techniques and adopted algorithms which are the emerging best practices like predictive analytics, dynamic routing, user centric planning, multi-objective optimization, etc. that reflect the industry's focus on leveraging advanced technologies, data-driven decision-making, and collaborative approaches to enhance the efficiency and sustainability of electric vehicle routing and charging scheduling.

Anahtar Kelimeler

Electric vehicles Scheduling algorithms Optimal scheduling Grid integration

Destekleyen Kurum

Nil

Proje Numarası

Not applicable

Teşekkür

No funding support

Kaynakça

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Yıl 2024, Cilt: 37 Sayı: 3, 1256 - 1285, 01.09.2024

Prabhakar Karthikeyan Shanmugam , Polly Thomas

https://doi.org/10.35378/gujs.1321572

Öz

Proje Numarası

Not applicable

Kaynakça

  • [1] Singh, J., Tiwari, R., “Multi-objective optimal scheduling of electric vehicles in distribution system”, 20th National Power Systems Conference (NPSC), India, pp. 1-6, (2018).
  • [2] Liu, Z., Wu, Q., Ma, K., Shahidehpour M., Xue Y., Huang S., “Two-stage optimal scheduling of electric vehicle charging based on transactive control”, IEEE Transactions on Smart Grid, 10: 2948–2958, (2018).
  • [3] Babina, B.M., Shereef, R.M., “Optimal Scheduling of Electric Vehicles for Peak Clipping Services”, IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy, India, pp. 1–6 (2020).
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  • [75] Huang, X., Zhang, Y., Li, D., Han, L., “An optimal scheduling algorithm for hybrid EV charging scenario using consortium blockchains”, Future Generation Computer Systems. 91: 555–562, (2019).
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  • [77] Yucel, F., Akkaya, F., Bulut, E., “Efficient and privacy preserving supplier matching for electric vehicle charging”, Ad Hoc Networks, 90: 101730, (2019).
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  • [105] Malhotra, Binetti, G., Davoudi, A., Schizas, L.D., “Distributed power profile tracking for heterogeneous charging of electric vehicles”, IEEE Transactions on Smart Grid. 8: 2090–2099, (2017).
  • [106] Karfopoulos, K.L., Panourgias, K.A., “Hatziargyriou, Distributed coordination of electric vehicles providing V2G regulation services”, IEEE Transactions on Power Systems, 31: 2834–2846, (2016).
  • [107] Zhao, T., Ding, Z., “Distributed initialization-free cost-optimal charging control of plug-in electric vehicles for demand management”, IEEE Transactions on Industrial Information, 13: 2791–2801, (2017).
  • [108] Wang, C., Guo, C., Zuo, X., “Solving multi-depot electric vehicle scheduling problem by column generation and genetic algorithm”, Applied Soft Computing, 112: 107774, (2021).
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Toplam 109 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Elektrik Enerjisi Üretimi (Yenilenebilir Kaynaklar Dahil, Fotovoltaikler Hariç)
Bölüm Electrical & Electronics Engineering
Yazarlar

Prabhakar Karthikeyan Shanmugam 0000-0001-5539-0729

Polly Thomas 0000-0003-2414-6779

Proje Numarası Not applicable
Erken Görünüm Tarihi 30 Mart 2024
Yayımlanma Tarihi 1 Eylül 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 37 Sayı: 3

Kaynak Göster

APA Shanmugam, P. K., & Thomas, P. (2024). Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review. Gazi University Journal of Science, 37(3), 1256-1285. https://doi.org/10.35378/gujs.1321572
AMA Shanmugam PK, Thomas P. Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review. Gazi University Journal of Science. Eylül 2024;37(3):1256-1285. doi:10.35378/gujs.1321572
Chicago Shanmugam, Prabhakar Karthikeyan, ve Polly Thomas. “Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review”. Gazi University Journal of Science 37, sy. 3 (Eylül 2024): 1256-85. https://doi.org/10.35378/gujs.1321572.
EndNote Shanmugam PK, Thomas P (01 Eylül 2024) Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review. Gazi University Journal of Science 37 3 1256–1285.
IEEE P. K. Shanmugam ve P. Thomas, “Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review”, Gazi University Journal of Science, c. 37, sy. 3, ss. 1256–1285, 2024, doi: 10.35378/gujs.1321572.
ISNAD Shanmugam, Prabhakar Karthikeyan - Thomas, Polly. “Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review”. Gazi University Journal of Science 37/3 (Eylül 2024), 1256-1285. https://doi.org/10.35378/gujs.1321572.
JAMA Shanmugam PK, Thomas P. Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review. Gazi University Journal of Science. 2024;37:1256–1285.
MLA Shanmugam, Prabhakar Karthikeyan ve Polly Thomas. “Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review”. Gazi University Journal of Science, c. 37, sy. 3, 2024, ss. 1256-85, doi:10.35378/gujs.1321572.
Vancouver Shanmugam PK, Thomas P. Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review. Gazi University Journal of Science. 2024;37(3):1256-85.