Charging station planning scheme by making efficient use of soft computing techniques for low carbon transition

References

• Tian S, Hua G, Cheng TCE. Optimal deployment of charging piles for electric vehicles under the indirect network effects. Asia Pac. J. Oper. Res. 2019;36(01):1950007. doi: 10.1142/S0217595919500076.
   Google Scholar
• Wang H, Zhao D, Cai Y, et al. A trajectory-based energy consumption estimation method considering battery degradation for an urban electric vehicle network. Transp Res Part D: transport Environ. 2019;74:142–153. ” doi: 10.1016/j.trd.2019.07.021.
   Web of Science ®Google Scholar
• Mingyu PAN, Xukun SUN, Xianglong LI, et al. Optimization of charging pile layout based on cost control and collective coverage model. Modern Electric Power. 2021;38(02):230–236.
   Google Scholar
• Chen Z, Wang W, Li Z, et al. Study on optimization of charging pile layout based on multi-factor constrained P-median model. J Beijing Jiaotong Univ. 2021;45(3):93–99.
   Google Scholar
• Kaur M, Kadam S, Hannoon N. Multi-level parallel scheduling of dependent-tasks using graph-partitioning and hybrid approaches over edge-cloud. Soft Comput. 2022;26(11):5347–5362. doi: 10.1007/s00500-022-07048-1.
   Web of Science ®Google Scholar
• Zhou G, Zhu Z, Luo S. Location optimization of electric vehicle charging stations: based on cost model and genetic algorithm. Energy. 2022;247:123437. doi: 10.1016/j.energy.2022.123437.
   Web of Science ®Google Scholar
• Kong W, Luo Y, Feng G, et al. Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid. Energy. 2019;186:115826. doi: 10.1016/j.energy.2019.07.156.
   Web of Science ®Google Scholar
• Jiang L, Sakhare SR, Kaur M. Impact of industrial 4.0 on environment along with correlation between economic growth and carbon emissions. Int J Syst Assur Eng Manag. 2022;13(S1):415–423. doi: 10.1007/s13198-021-01456-6.
   Google Scholar
• Kaur M. AI- and IoT-based energy saving mechanism by minimizing hop delay in multi-hop and advanced optical system based optical channels. Opt Quant Electron. 2023;55(7):635. doi: 10.1007/s11082-023-04882-x.
   Web of Science ®Google Scholar
• Wang T, Zhang F, Gu H, et al. A research study on new energy brand users based on principal component analysis (PCA) and fusion target planning model for sustainable environment of smart cities. Sust Energy Tech Assess. 2023;57:103262. doi: 10.1016/j.seta.2023.103262.
   Web of Science ®Google Scholar
• Yu G, Zhang X, Wang H, et al. Low carbon planning of PV-charging stations for self-sustained highway transportation energy system considering the retirement of gas stations. IEEE Trans. on Industry Appl. 2024;60(1):1208–1218. doi: 10.1109/TIA.2023.3282933.
   Web of Science ®Google Scholar
• Li Y, Tan Z, Yang S, et al. Multi-attribute feature fusion algorithm for blockchain communications in healthcare systems using machine intelligence. Soft Comput. 2023;27(22):17435–17445. doi: 10.1007/s00500-023-09192-8.
   Web of Science ®Google Scholar
• Roy S, Venu S, Sai Karthik KA, et al. An ecosystem blueprint for electric vehicle charging stations fed by a hybrid microgrid – a case study. In 2022 22nd National Power Systems Conf. (NPSC), New Delhi, India;2022 pp. 908–913. doi: 10.1109/NPSC57038.2022.10068987.
   Google Scholar
• Karmaker AK, Hossain MA, Pota HR, et al. "Energy management system for hybrid renewable energy-based electric vehicle charging station," in. IEEE Access. 2023;11:27793–27805. doi: 10.1109/ACCESS.2023.3259232.
   Web of Science ®Google Scholar
• Clairand J-M, González-Rodríguez M, Cedeño I, et al. A charging station planning model considering electric bus aggregators. Sustain. Energy, Grids Networks. 2022;30:100638. doi: 10.1016/j.segan.2022.100638.
   Web of Science ®Google Scholar
• Liu Z -f, Zhang W, Ji X, et al. Optimal Planning of charging station for electric vehicle based on particle swarm optimization. IEEE PES Innovative Smart Grid Technologies, Tianjin, China; 2012:1–5, doi: 10.1109/ISGT-Asia.2012.6303112.
   Google Scholar
• Abdel-Basset M, Gamal A, Hezam IM, et al. Sustainability assessment of optimal location of electric vehicle charge stations: a conceptual framework for green energy into smart cities. Environ Dev Sustain. 2023;26(5):11475–11513. doi: 10.1007/s10668-023-03373-z.
   Google Scholar
• Hou H, Tang J, Zhao B, et al. Optimal planning of electric vehicle charging station considering mutual benefit of users and power grid. WEVJ. 2021;12(4):244–255. doi: 10.3390/wevj12040244.
   Google Scholar
• de Lima TD, Franco JF, Lezama F, et al. Joint optimal allocation of electric vehicle charging stations and renewable energy sources including CO2 emissions. Energy Inform. 2021;4(S2):33. doi: 10.1186/s42162-021-00157-5.
   Google Scholar
• Zhang Y, Hua Y, Kang A, et al. Optimal and efficient planning of charging stations for electric vehicles in urban areas: formulation, complexity and solutions. Exp Sys. with App. 2023;230:120442. doi: 10.1016/j.eswa.2023.120442.
   Web of Science ®Google Scholar
• Elrais MT, Rezaii R, Batarseh I. Scalable GaN-Based EV Charging Station with Energy Storage. 2023 IEEE applied power electronics conference and exposition (APEC). Orlando, FL; 2023:pp. 1688–1692. doi: 10.1109/APEC43580.2023.10131300.
   Google Scholar
• Ahmed HY, Ali ZM, Refaat MM, et al. A multi-objective planning strategy for electric vehicle charging stations towards low carbon-oriented modern power systems. Sustainability. 2023;15(3):2819. doi: 10.3390/su15032819.
   Web of Science ®Google Scholar
• Mohammad S, Ali G-M. Fast-charging station for electric vehicles, challenges and issues: a comprehensive review. J. Energy Storage. 2022;49:104136.
   Web of Science ®Google Scholar
• Jaraniya D, Kumar S. PV charging station with VSS-IMSAF and SOSMCC disturbance observer based controls to enhance the distribution grid capability. IETE of Research. 2023;70(2):2166–2177. doi: 10.1080/03772063.2023.2169201.
   Web of Science ®Google Scholar
• Savari GF, Sathik MJ, Raman LA, et al. Assessment of charging technologies, infrastructure and charging station recommendation schemes of electric vehicles: a review. Ain Shams Eng J. 2023;14Issue(4):101938. doi: 10.1016/j.asej.2022.101938.
   Web of Science ®Google Scholar
• Alkawsi G, Baashar Y, Abbas U D, et al. Review of renewable energy-based charging Infrastructure for Electric Vehicles. Applied Sciences. 2021;11(9):3847. doi: 10.3390/app11093847.
   Google Scholar
• Raykar N, Khedkar G, Kaur M, et al. A novel traffic load balancing approach for scheduling of optical transparent antennas (OTAs) on mobile terminals. Opt Quant Electron. 2023;55(11):962. doi: 10.1007/s11082-023-05201-0.
   Web of Science ®Google Scholar
• Patil S, Kaur M, Rogulj K. Fairness-driven link scheduling approach for heterogeneous gateways for digital twin enabled industry 4.0. Int. J Intelligent Networks. 2023;4:162–170. doi: 10.1016/j.ijin.2023.06.001.
   Google Scholar
• Zavorka R, Paar MA. Focus on electromobility within smart city solutions—charging stations, renewable energy, and air quality monitoring. Sensors. 2022;22(20):7841. doi: 10.3390/s22207841.
   PubMed Web of Science ®Google Scholar
• Dillon R, Donnie B, Rean M. A techno-economic quantification of carbon reduction strategies in the Trinidad and Tobago power generation sector using carbon emission pinch analysis (cepa). Carbon Manage. 2023;14(1). doi: 10.1080/17583004.2023.2227159.
   Web of Science ®Google Scholar