DETERMINATION OF RATIONAL PARAMETERS FOR A NETWORK OF CHARGING STATIONS FOR ELECTRIC VEHICLES
Article Sidebar
Main Article Content
Abstract
This article examines the problem of determining rational parameters for a network of electric vehicle charging stations. The main factors influencing the placement of electric vehicle charging stations are analyzed. A multi-purpose model for choosing the location of charging stations has been developed. An algorithmic model is proposed to improve the sparrow search method, which is used as the basis for solving the problem of determining the rational parameters of a network of electric vehicle charging stations.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Zhao, F., Liu, X., Zhang, H. & Liu, Z. (2022). Automobile Industry under China’s Carbon Peaking and Carbon Neutrality Goals: Challenges, Opportunities, and Coping Strategies. Journal of Advanced Transportation, 2022(1), 1–13. DOI: 10.1155/2022/5834707
Martins, L.S., Guimarães, L.F., Junior, A.B.B., Tenório, J.A.S. & Espinosa, D.C.R. (2021). Electric Car Battery: An Overview on Global Demand, Recycling and Future Approaches Towards Sustainability. Journal of Environmental Management, (295), 113091. DOI: 10.1016/j.jenvman.2021.113091
Cao, L. (2020). Research on the Development and Application of Charging Piles Based on the Development of New Energy Vehicles. IOP Conference Series: Earth and Environmental Science, 565(1), 012001. DOI: 10.1088/1755-1315/565/1/012001
Pal, A., Bhattacharya, A. & Chakraborty, AK. (2021). Allocation of Electric Vehicle Charging Station Considering Uncertainties. Sustainable Energy, Grids and Networks, (25), 100422. DOI: 10.1016/j.segan.2020.100422
Bae, S. & Kwasinski, A. (2012). Spatial and Temporal Model of Electric Vehicle Charging Demand. IEEE Transactions on Smart Grid, 3(1), 394–403. DOI: 10.1109/TSG.2011.2159278
Xu, H. & Huang, Х. (2020). A Multi-Objective Coordinated Charging and Discharging Strategy for Electric Vehicles Based on Stackelberg Game. Energy and Power Engineering, 12(04), 63. DOI:10.4236/epe.2020.124B007
Mehrjerdi, H. & Hemmati, R. (2020). Stochastic model for electric vehicle charging station integrated with wind energy. Sustainable Energy Technologies and Assessments, (37), 157–177. DOI: 10.1016/j.seta.2019.100577
Liu, Z., Xiao, Z., Wu, Y., Hui, H., Tao, X., Qingyong, Z. & Changjun, X. (2020). Integrated optimal dispatching strategy considering power generation and consumption interaction. IEEE Access, (9), 1338–1349.
Wu, W., Lin, Y. & Liu, R. (2020). Online EV charge scheduling based on time-of-use pricing and peak load minimization: Properties and efficient algorithms. IEEE Transactions on Intelligent Transportation Systems, 23(1), 572–586. DOI: 10.1109/TITS.2020.3014088
Liu, J., Lin, G., Huang, S. & Zhou, Ya. (2020). Optimal EV charging scheduling by considering the limited number of chargers. IEEE Transactions on Transportation Electrification, 7(3), 1112–1122. DOI: 10.1109/TTE.2020.3033995
Fernandez, G.S., Krishnasamy, V., Kuppusamy, S., Jagabar, S. Ali, Ziad, M. Ali, El-Shahat, A. & Abdel Aleem, Shady H.E. (2020). Optimal dynamic scheduling of electric vehicles in a parking lot using particle swarm optimization and shuffled frog leaping algorithm. Energies, 13(23), 6384. DOI: 10.3390/en13236384
Abdullah-Al-Nahid, S., Khan, T.A., Taseen, M.A. & Taskin, J. (2022). A novel consumer-friendly electric vehicle charging scheme with vehicle to grid provision supported by genetic algorithm based optimization. Journal of Energy Storage, (50), 104655. DOI:10.1016/j.est.2022.104655
Rahmani-Andebili, M., Bonamente, M. & Miller, J.A. (2020). Mobility Analysis of Plug-in Electric Vehicles in San Francisco Applying Monte Carlo Markov Chain. IEEE Kansas Power and Energy Conference (KPEC) [Manhattan, KS, USA (13–14 July 2020], 1–6. DOI: 10.1109/KPEC47870.2020.9167668
Betancur, D., Duarte, L.F., Revollo, J., Restrepo, C., Diez, A.E., Isaac, I.A. … Gonzalez, J.W. (2021). Methodology to evaluate the impact of electric vehicles on electrical networks using Monte Carlo. Energies, 14(5), 1300. DOI: 10.3390/en14051300
Anand, M.P., Bagen, B. & Rajapakse, A. (2020). Probabilistic reliability evaluation of distribution systems considering the spatial and temporal distribution of electric vehicles. International Journal of Electrical Power & Energy Systems, (117). 105609. DOI: 10.1016/j.ijepes.2019.105609
Meng, Z. & Pan, J.S. (2018). QUasi-Affine TRansformation Evolution with External ARchive (QUATRE-EAR): an enhanced structure for differential evolution. Knowledge-Based Systems, (155), 35–53. DOI: 10.1016/j.knosys.2018.04.034
Mirjalili, S. & Lewis, A. (2016). The whale optimization algorithm. Advances in engineering software, (95), 51–67. DOI: 10.1016/j.advengsoft.2016.01.008
Du, S., Zhang, J., Wang, Y. & Li, Z. (2024). Integration of Computer Vision and IOT Into an Automatic Driving Assistance System for “Electric Vehicles”. IEEE Transactions on Industrial Informatics, 20(3), 4765–4772.
Kathiroli, P. & Selvadurai, K. (2022). Energy efficient cluster head selection using improved Sparrow Search Algorithm in Wireless Sensor Networks. Journal of King Saud University-Computer and Information Sciences, 34(10), 8564–8575. DOI: 10.1016/j.jksuci.2021.08.031
Zhang, G. & Zhang, E. (2021). A random opposition-based sparrow search algorithm for Path Planning Problem. Artificial Intelligence: First CAAI International Conference [CICAI 2021, Hangzhou, China, June 5–6, 2021], Part II 1, 408–418. DOI: 10.1007/978-3-030-93049-3_34
Yang, X.S. & Deb, S. (2010). Engineering optimization by cuckoo search. J. Math. Modell. Numer. Optim, 1(4), 330–343. DOI: 10.48550/arXiv.1005.2908
Ghamami, M., Nie, Y. & Zockaie, A. (2016). Planning charging infrastructure for plug-in electric vehicles in city centers. International Journal of Sustainable Transport, (10), 343–353. DOI: 10.1080/15568318.2014.937840
Mirjalili, S. (2016). SCA: a sine cosine algorithm for solving optimization problems. Knowledge-Based Syst, (96), 120–133.
Heidari, A.A., Mirjalili, S., Faris, H. & Mafarja, M. (2019). Harris hawks optimization: Algorithm and applications. Future Generat. Comput. Syst., (97), 849–872. DOI: 10.1016/j.future.2019.02.028
Jain, M., Singh, V. & Rani, A. (2019). A novel nature-inspired algorithm for optimization: Squirrel search algorithm. Swarm Evoluti. Comput., (44), 148–175. DOI: 10.1016/j.swevo.2018.02.013
Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. & Tavakkoli-Moghaddam, R. (2020). Red deer algorithm (RDA): a new nature-inspired meta-heuristic. Soft Comput, (24), 14637–14665. DOI: 10.1007/s00500-020-04812-z
Gimenez-Gaydou, D.A., Ribeiro, A.N., Gutierrez, J. & Antunes, A.P. (2016). Optimal location of battery electric vehicle charging stations in urban areas: A new approach. International Journal of Sustainable Transport, (10), 393–405. DOI: 10.1080/15568318.2014.961620
Braik, M., Sheta, A. & Al-Hiary, H. (2021). A novel meta-heuristic search algorithm for solving optimization problems: capuchin search algorithm. Neural Comput. Appli., (33), 2515–2547. DOI: 10.1007/s00521-020-05145-6
Abualigah, L., Yousri, D., Abd, Elaziz M., Ewees, A.A., Al-qaness, Mohamed A.A. & Gandomi, Amir H. (2021). Aquila optimizer: a novel metaheuristic optimization algorithm. Comput. Indust. Engin., (157), 107250. DOI:10.1016/j.cie.2021.107250
Braik, M.S. (2021). Chameleon Swarm Algorithm: A bio-inspired optimizer for solving engineering design problems. Expert Syst. Appl., (174), 114685. DOI:10.1016/j.eswa.2021.114685
Yang, Z., Deng, L., Wang, Y. & Liu, J. (2021). Aptenodytes forsteri optimization: Algorithm and applications. Knowledge-Based Syst., (232), 107483. DOI:10.1016/j.knosys.2021.107483
Frade, I., Ribeiro, A., Goncalves, G. & Antunes, A. (2011). Optimal Location of Charging Stations for Electric Vehicles in a Neighborhood in Lisbon, Portugal. Transportation Research Record, (2), 91–98. DOI:10.3141/2252-12
Du, Sizhuo, Kapski, D.V. & Lobashov, A.O. (2024). Analiz preimucshestv i nedostatkov vospolneniya energii dlya zaryadnych stanciy elctromobiley. Sovremenye technologii v transportnoy otrasly: electron. sb. st. Mezdunar. nauch.-techn. konf. [Novopolotsk, 25-26 apr. 2024 g.], 122–124. (In Russ.)
Most read articles by the same author(s)
- S. ERMILOV, M. ZHILEVICH, D. KAPSKI, STUDY OF THE DYNAMICS OF THE BRAKE DRIVE WITH AN ANTI-LOCK BRAKING SYSTEM FOR A PARTICULARLY HEAVY-DUTY VEHICLE, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 1 (2024)
- A. LOBASHOV, D. KAPSKY, S. SEMCHENKOV, PATTERNS OF SPEED CHANGES TRAFFIC FLOWS IN CITIES, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 1 (2024)
- D. KAPSKI, D. KHODOSKIN, IMPROVING THE METHOD FOR CALCULATING POTENTIAL DANGEROUS IN THE CONFLICT ZONE FOR COMMON TRAFFIC FLOW THROUGH CLARIFICATION OF REDUCTION COEFFICIENTS FOR THE SEVERITY OF ROAD ACCIDENTS, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 2 (2024)
- D. KAPSKI, S. BOGDANOVICH, ИНТЕГРАЦИЯ МЕТОДОВ КОГНИТИВНОГО АНАЛИЗА В СИСТЕМУ ОЦЕНКИ БЕЗОПАСНОСТИ ДОРОЖНОЙ ИНФРАСТРУКТУРЫ, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 2 (2024)
- R. LAGEREV, D. KAPSKI, V. IVANOV, T. VIGERINA, MANAGEMENT OF THE ENTRY FLOW OF CARS ON HIGH-SPEED ROADS OF THE HIGHEST CATEGORY, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 11 (2017)
- D. KAPSKI, D. MOZOLEVSKY, V. KUZMENKO, A. POLKHOVSKY’S, A. KORZOVA, N. KISILEVICH, N. ERMAKOVA, E. GORELIK, TRAFFIC MANAGEMENT WHEN CHANGING OBJECTS GRAVITY IN THE AREA OF VEHICLE ASSEMBLY FORMED BY MAIN STREETS CITYWIDE IMPORTANCE IN MINSK, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 11 (2015)
- D. KAPSKI, D. MOZOLEVSKY, V. KUZMENKO, A. POLKHOVSKY’S, A. KORZOVA, N. KISILEVICH, N. ERMAKOVA, E. GORELIK, DECISION MAKING ON TRANSPORT PLANNING AND MAINTENANCE OF LARGE ROAD JUNCTIONS, Vestnik of Polotsk State University. Part B. Industry. Applied Sciences: No. 11 (2015)