A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms

References

• Agancy, I. E. 2018. World energy outlook 2018. 23–28.
   Google Scholar
• Ahmad, A., S. A. R. Kashif, A. Nasir, A. Rasool, S. Liaquat, S. Padmanaban, and L. Mihet-Popa. 2021. Controller parameters optimization for multi-terminal DC power system using ant colony optimization. IEEE Access 9:59910–19. doi:10.1109/ACCESS.2021.3073491.
   Web of Science ®Google Scholar
• Alam, M., J. Ferreira, and J. Fonseca. 2016. Intelligent transportation systems: Dependable vehicular communications for improved road safety. Studies in Health Technology and Informatics 52:223–27.
   Google Scholar
• Alinia, B., M. H. Hajiesmaili, Z. J. Lee, N. Crespi, and E. Mallada, 2020. Online EV scheduling algorithms for adaptive charging networks with global peak constraints. IEEE Transactions on Sustainable Computing:1–1.
   Google Scholar
• Alvarez, J. G., M. Á. González, C. R. Vela, and R. Varela. 2018. Electric vehicle charging scheduling by an enhanced artificial bee colony algorithm. Energies 11 (10):1–19.
   Web of Science ®Google Scholar
• Amarani, S., 2018. Global electric vehicle market forecast 2018-2026 [online]. INK WOOD Research. https://inkwoodresearch.com/reports/electric-vehicle-market/#table-of-contents.
   Google Scholar
• Architecture, C. 2010. EN 302 665 - V1.0.0 - Intelligent Transport Systems (ITS). Communications Architecture:1–45.
   Google Scholar
• Awasthi, A., K. Venkitusamy, S. Padmanaban, R. Selvamuthukumaran, F. Blaabjerg, and A. K. Singh. 2017. Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm. Energy 133:70–78. doi:10.1016/j.energy.2017.05.094.
   Web of Science ®Google Scholar
• Cao, Y., J. Tao, O. Kaiwartya, H. Sun, H. Zhou, and R. Wang, 2021. Toward preempted EV charging recommendation through V2V based reservation system. IEEE transactions on systems, man, and cybernetics : systems 51(5): 3026-3039.
   Google Scholar
• Cho, M., L. Lai, and W. Xu. 2021. Distributed dual coordinate ascent in general tree networks and communication network effect on synchronous machine learning. IEEE Journal on Selected Areas in Communications 39 (7):2105–19. doi:10.1109/JSAC.2021.3078495.
   Web of Science ®Google Scholar
• Dahrouj, H., R. Alghamdi, H. Alwazani, S. Bahanshal, A. A. Ahmad, A. Faisal, R. Shalabi, R. Alhadrami, A. Subasi, M. T. Al-Nory, et al. 2021. An overview of machine learning-based techniques for solving optimization problems in communications and signal processing. IEEE Access 9:74908–38.
   Web of Science ®Google Scholar
• Das, S., A. Bhattacharya, and P. Acharjee, 2020. Charging scheduling of Electric Vehicles (EV) in probabilistic scenario considering Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G). 2020 IEEE Calcutta conference, CALCON 2020 - Proceedings, Kolkatta, 467–72.
   Google Scholar
• Davidov, S. 2020. Optimal charging infrastructure planning based on a charging convenience buffer. Energy 192: doi:10.1016/j.energy.2019.116655.
   Google Scholar
• Deb, S., X. Z. Gao, K. Tammi, K. Kalita, and P. Mahanta. 2019. Nature-Inspired Optimization Algorithms Applied for Solving Charging Station Placement Problem: Overview and Comparison. Archives of Computational Methods in Engineering 28, 91–106. https://doi.org/10.1007/s11831-019-09374-4
   Google Scholar
• Devendiran, R., P. Kasinathan, V. K. Ramachandaramurthy, U. Subramaniam, U. Govindarajan, and X. Fernando. 2021. Intelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks technique. International Journal of Intelligent Systems 36(10), 5816-5844.
   Web of Science ®Google Scholar
• Dorigo, M., and T. Stützle. 2010. Ant colony optimization: Overview and recent advances.
   Google Scholar
• García-Álvarez, J., M. A. González, and C. R. Vela. 2018. Metaheuristics for solving a real-world electric vehicle charging scheduling problem. Applied Soft Computing Journal 65:292–306. doi:10.1016/j.asoc.2018.01.010.
   Web of Science ®Google Scholar
• Ghotge, R., Y. Snow, S. Farahani, Z. Lukszo, and A. van Wijk. 2020. Optimized scheduling of EV charging in solar parking lots for local peak reduction under EV demand uncertainty. Energies 13 (5):1275. doi:10.3390/en13051275.
   Web of Science ®Google Scholar
• Guerrero-Ibáñez, J., S. Zeadally, and J. Contreras-Castillo. 2018. Sensor technologies for intelligent transportation systems. Sensors (Switzerland) 18 4:1–24
   Web of Science ®Google Scholar
• Hernández-Arauzo, A., J. Puente, R. Varela, and J. Sedano. 2015. Electric vehicle charging under power and balance constraints as dynamic scheduling. Computers and Industrial Engineering 85:306–15. doi:10.1016/j.cie.2015.04.002.
   Web of Science ®Google Scholar
• Iacobucci, R., B. McLellan, and T. Tezuka 2019. Optimization of shared autonomous electric vehicles operations with charge scheduling and vehicle-to-grid. Transportation Research Part C: Emerging Technologies 100:34–52. January. doi:10.1016/j.trc.2019.01.011.
   Web of Science ®Google Scholar
• Jin, J., Y. Xu, and Z. Yang. 2020. Optimal deadline scheduling for electric vehicle charging with energy storage and random supply. Automatica 119:109096. doi:10.1016/j.automatica.2020.109096.
   Web of Science ®Google Scholar
• Kabir, M. E., C. Assi, M. H. K. Tushar, and J. Yan. 2020. Optimal scheduling of EV charging at a solar power-based charging station. IEEE Systems Journal 14(3):4221–4231. doi:10.1109/JSYST.2020.2968270.
   Web of Science ®Google Scholar
• Karthik, M., S. Usha, K. Venkateswaran, M. S. Hitesh Panchal, V. Priya, and K. K. Hinduja. 2020. Evaluation of electromagnetic intrusion in brushless DC motor drive for electric vehicle applications with manifestation of mitigating the electromagnetic interference. International Journal of Ambient Energy. doi:10.1080/01430750.2020.1839546.
   Web of Science ®Google Scholar
• Lim, Y., H. M. Kim, S. Kang, and T. H. Kim. 2012. Vehicle-to-grid communication system for electric vehicle charging. Integrated Computer-Aided Engineering 19 (1):57–65. doi:10.3233/ICA-2012-0391.
   Web of Science ®Google Scholar
• Luo, Y., G. Feng, S. Wan, S. Zhang, V. Li, and W. Kong. 2020. Charging scheduling strategy for different electric vehicles with optimization for convenience of drivers, performance of transport system and distribution network. Energy 194:116807. doi:10.1016/j.energy.2019.116807.
   Web of Science ®Google Scholar
• Luo, Y., T. Zhu, S. Wan, S. Zhang, and K. Li. 2016. Optimal charging scheduling for large-scale EV (Electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems. Energy 97:359–68. doi:10.1016/j.energy.2015.12.140.
   Web of Science ®Google Scholar
• Mirjalili, S., S. M. Mirjalili, and A. Lewis. 2014. Grey Wolf Optimizer. Advances in Engineering Software 69:46–61. doi:10.1016/j.advengsoft.2013.12.007.
   Web of Science ®Google Scholar
• Rewadkar, D., and D. Doye. 2018. FGWSO-TAR: Fractional glowworm swarm optimization for traffic aware routing in urban VANET. International Journal of Communication Systems 31 (1):1–22. doi:10.1002/dac.3430.
   Web of Science ®Google Scholar
• Shadravan, S., H. R. Naji, and V. K. Bardsiri 2019a. The Sailfish Optimizer: A novel nature-inspired metaheuristic algorithm for solving constrained engineering optimization problems. Engineering Applications of Artificial Intelligence 80:20–34. January. doi: 10.1016/j.engappai.2019.01.001.
   Web of Science ®Google Scholar
• Shadravan, S., H. R. Naji, and V. K. Bardsiri. 2019b. The Sailfish Optimizer: A novel nature-inspired metaheuristic algorithm for solving constrained engineering optimization problems. Engineering Applications of Artificial Intelligence 80:20–34.
   Web of Science ®Google Scholar
• Tang, J., G. Liu, and Q. Pan. 2021. A review on representative swarm intelligence algorithms for solving optimization problems: Applications and trends. IEEE/CAA Journal of Automatica Sinica 8 (10):1627–43. doi:10.1109/JAS.2021.1004129.
   Google Scholar
• Triviño-Cabrera, A., J. A. Aguado, and S. D. L. Torre. 2019. Joint routing and scheduling for electric vehicles in smart grids with V2G. Energy 175:113–22. doi:10.1016/j.energy.2019.02.184.
   Web of Science ®Google Scholar
• Vehicular Communications. 2010. Vehicular Communications part 3. Network Architecture 1:1–23.
   Google Scholar
• Wang, T., B. Yang, and C. Chen. 2020. Double-layer game based wireless charging scheduling for electric vehicles. IEEE Vehicular Technology Conference, May. https://doi.org/10.1109/VTC2020-Spring48590.2020.9129228
   Google Scholar
• Yang, W., H. Wang, Z. Wang, X. Fu, P. Ma, Z. Deng, and Z. Yang. 2020. Optimization strategy of electric vehicles charging path based on ‘traffic-price-distribution’ mode. Energies 13 (12):1–26. https://doi.org/10.3390/en13123208
   Web of Science ®Google Scholar
• Zhang, W., D. Zhang, B. Mu, L. Y. Wang, Y. Bao, J. Jiang, and H. Morais. 2017. Decentralized electric vehicle charging strategies for reduced load variation and guaranteed charge completion in regional distribution grids. Energies 10 (2):1–19. https://doi.org/10.3390/en10020147
   Web of Science ®Google Scholar