Optimized Scheduling of Plug-In Hybrid Electric Vehicles with Distributed Generation: Adapting to Various Vehicle Trip Models
Keywords:
Plug-in Hybrid Electric Vehicles (PHEVs), Distributed Generation, Energy Management, Smart Grid, Renewable Energy Integration
Abstract
This study presents a novel approach for optimizing the scheduling of plug-in hybrid electric vehicles (PHEVs) integrated with distributed generation systems. As PHEVs gain importance in the transition to sustainable transportation, effective energy management strategies are critical for maximizing their benefits. This research introduces an optimization model that considers various vehicle trip profiles, including daily commuting, long-distance travel, and variable trip frequencies. The model integrates distributed generation sources such as solar and wind energy to enhance charging efficiency and minimize operational costs. The performance of the proposed scheduling strategy was evaluated across different trip scenarios, focusing on key metrics such as energy utilization, cost savings, and emissions reduction using simulations. Results indicate that tailoring PHEV scheduling to specific trip profiles significantly enhances overall system efficiency, particularly when combined with renewable energy sources. This study contributes to the advancement of smart grid applications and highlights the importance of dynamic scheduling in fostering the adoption of PHEVs within sustainable energy systems.Downloads
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References
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[8] Tesla. Tesla Official Website. 2019. Available online: https://www.tesla.com/en_EU/supercharger (accessed on 21 February 2021).
[9] Berjoza, D.; Jurgena, I. Effects of change in the weight of electric vehicles on their performance characteristics. Agron. Res. 2017, 15, 952–963.
[10] Yong, J.Y.; Ramachandaramurthy, V.K.; Tan, K.M.; Mithulananthan, N. A review of the state-of-the-art technologies of electric vehicles, its impacts and prospects. Renew. Sustain. Energy Rev. 2015, 49, 365–385. [CrossRef]
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[12] Liu, L.; Kong, F.; Liu, X.; Peng, Y.; Wang, Q. A review on electric vehicles interacting with renewable energy in smart grid. Renew. Sustain. Energy Rev. 2015, 51, 648–661. [CrossRef]
[13] Vasant, P.; Marmolejo, J.A.; Litvinchev, I.; Aguilar, R.R. Nature-inspired meta-heuristics approaches for charging the plug-in hybrid electric vehicle. Wirel. Netw. 2019, 26, 4753–4766. [CrossRef]
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[16] Hu, J.; Morais, H.; Sousa, T.; Lind, M. Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects. Renew. Sustain. Energy Rev. 2016, 56, 1207–1226. [CrossRef]
[17] Mahmud, K.; Town, G.E.; Morsalin, S.; Hossain, M. Integration of electric vehicles and management in the internet of energy. Renew. Sustain. Energy Rev. 2018, 82, 4179–4203. [CrossRef]
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[19] Li, Y.; Liu, K.; Foley, A.M.; Zülke, A.; Berecibar, M.; Nanini-Maury, E.; Van Mierlo, J.; Hoster, H.E. Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review. Renew. Sustain. Energy Rev. 2019, 113, 109254. [CrossRef]
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[21] Thakur, Alka, S. Wadhwani, and A. K. Wadhwani. Motor current signature analysis as a tool for induction machine fault diagnosis. International Journal of Computer Science and Information Technology Research 3.3 (2015): 309-313.
[22] Parsai, Neha, Alka Thakur, and M. dan Tech. , PV Curve-Approach for Voltage Stability Analysis., International Journal of Information Technology and Electrical Engineering 4.2 (2015):
a. 46-52.
[23] Thakur, Alka, Sulochana Wadhwani, and Vandana Sondhiya. Health monitoring of rotating electrical machine using soft computing techniques: A Review., International Journal of Scientific and Research Publications 3.11 (2013): 1-3.
[24] Alka Thakur, S. Wadhwani and A.K. Wadhwani A Review On Induction Motor Fault Diagnostic Techniques Elixir International Journal 93C (2016) 39829-39833 Accepted: 25 April 2016;.
[25] Alonso, M, Amaris, H, Germain, J.G, and Galan, JM 2014, ‘Optimal charging scheduling of electric vehicles in smart grids by heuristic algorithms’, Energies, vol. 7, no.4, pp. 2449
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[27] Pallonetto, F, Oxizidis, S, Milano, F and Finn, D 2016, ‘The effect of time-of-use tariffs on the demand response flexibility of an all-electric smart- grid-ready dwelling’, Energy Building, vol. 128, pp. 56-67.
Published
2024-11-30
How to Cite
Kamat, A. K., & Thakur, A. (2024). Optimized Scheduling of Plug-In Hybrid Electric Vehicles with Distributed Generation: Adapting to Various Vehicle Trip Models. International Journal of Advanced Computer Technology, 13(2), 1-14. Retrieved from https://ijact.org/index.php/ijact/article/view/149
Section
Articles
