Exploring public charging infrastructure development strategies with BBWM-mV integrated multi-viewpoint perspective
Vol 8, Issue 9, 2024
VIEWS - 1076 (Abstract)
Abstract
To achieve the electrification of private vehicles, it is urgent to develop public charging infrastructure. However, choosing the most beneficial type of public charging infrastructure for the development of a country or region remains challenging. The municipal decision’s implementation requires considering various perspectives. An important aspect of energy development involves effectively integrating and evaluating public charging infrastructure. While car charging facilities have been thoroughly studied, motorcycle charging facilities have been neglected despite motorcycles being a vital mode of transportation in many countries. The study created a hybrid decision-making model to evaluate electric motorcycle charging infrastructure. Firstly, a framework for evaluating electric motorcycle charging infrastructure was effectively constructed through a literature survey and expert experience. Secondly, decision-makers’ opinions were gathered and integrated using Bayesian BWM to reach a group consensus. Thirdly, the performance of the alternative solutions was evaluated by exploring the gaps between them and the aspiration level through modified VIKOR. An empirical analysis was conducted using examples of regions/countries with very high rates of motorcycle ownership worldwide. Finally, comparative and sensitivity analyses were conducted to demonstrate the practicality of the proposed model. The study’s findings will aid in addressing municipal issues and achieving low-carbon development objectives in the area.
Keywords
Full Text:
PDFReferences
- Agency, I. E. (2009). World energy outlook. OECD/IEA Paris.
- Ahmad, A., Khan, Z. A., Saad Alam, M., et al. (2017). A Review of the Electric Vehicle Charging Techniques, Standards, Progression and Evolution of EV Technologies in Germany. Smart Science, 6(1), 36–53. https://doi.org/10.1080/23080477.2017.1420132
- Akbari, M., Brenna, M., & Longo, M. (2018). Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm. Sustainability, 10(4), 1076. https://doi.org/10.3390/su10041076
- Allegre, A. L., Bouscayrol, A., & Trigui, R. (2009). Influence of control strategies on battery/supercapacitor hybrid Energy Storage Systems for traction applications. 2009 IEEE Vehicle Power and Propulsion Conference. https://doi.org/10.1109/vppc.2009.5289849
- Amiri, S. S., Jadid, S., & Saboori, H. (2018). Multi-objective optimum charging management of electric vehicles through battery swapping stations. Energy, 165, 549–562. https://doi.org/10.1016/j.energy.2018.09.167
- Aqidawati, E. F., Ramadhan, R. A., & Sutopo, W. (2021). Charging Station Network Design for E-Motorcycle: A Case Study. In: Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore; 7–11 March 2021.
- Barisa, A., Rosa, M., & Kisele, A. (2016). Introducing Electric Mobility in Latvian Municipalities: Results of a Survey. Energy Procedia, 95, 50–57. https://doi.org/10.1016/j.egypro.2016.09.015
- Campaña, M., & Inga, E. (2023). Optimal deployment of fast-charging stations for electric vehicles considering the sizing of the electrical distribution network and traffic condition. Energy Reports, 9, 5246–5268. https://doi.org/10.1016/j.egyr.2023.04.355
- Chen, C., & Hua, G. (2014). A New Model for Optimal Deployment of Electric Vehicle Charging and Battery Swapping Stations. International Journal of Control and Automation, 7(5), 247–258. https://doi.org/10.14257/ijca.2014.7.5.27
- Chiou, Y.-C., Wen, C.-H., Tsai, S.-H., et al. (2009). Integrated modeling of car/motorcycle ownership, type and usage for estimating energy consumption and emissions. Transportation Research Part A: Policy and Practice, 43(7), 665–684. https://doi.org/10.1016/j.tra.2009.06.002
- Chiu, Y.-C., & Tzeng, G.-H. (1999). The market acceptance of electric motorcycles in Taiwan experience through a stated preference analysis. Transportation Research Part D: Transport and Environment, 4(2), 127–146. https://doi.org/10.1016/S1361-9209(99)00001-2
- Christoforou, Z., de Bortoli, A., Gioldasis, C., et al. (2021). Who is using e-scooters and how? Evidence from Paris. Transportation Research Part D: Transport and Environment, 92, 102708. https://doi.org/10.1016/j.trd.2021.102708
- Communications, M. O. T. A. (2022). Motor vehicle registration number. Available online: https://stat.motc.gov.tw/mocdb/stmain.jsp?sys=100&funid=a3301 (accessed on 2 July 2024).
- Cong, X., Wang, L., Ma, L., et al. (2020). Exploring critical influencing factors for the site selection failure of waste-to-energy projects in China caused by the “not in my back yard” effect. Engineering, Construction and Architectural Management, 28(6), 1561–1592. https://doi.org/10.1108/ecam-12-2019-0709
- Das, H. S., Rahman, M. M., Li, S., et al. (2020). Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review. Renewable and Sustainable Energy Reviews, 120, 109618. https://doi.org/10.1016/j.rser.2019.109618
- Deveci, M., Erdogan, N., Pamucar, D., et al. (2023). A rough Dombi Bonferroni based approach for public charging station type selection. Applied Energy, 345, 121258. https://doi.org/10.1016/j.apenergy.2023.121258
- Dong, H., & Yang, K. (2021). Application of the entropy-DEMATEL-VIKOR multicriteria decision-making method in public charging infrastructure. PLOS ONE, 16(10), e0258209. https://doi.org/10.1371/journal.pone.0258209
- Eccarius, T., & Lu, C.-C. (2019). Powered two-wheelers for sustainable mobility: A review of consumer adoption of electric motorcycles. International Journal of Sustainable Transportation, 14(3), 215–231. https://doi.org/10.1080/15568318.2018.1540735
- Feng, J., Xu, S. X., & Li, M. (2021). A novel multi-criteria decision-making method for selecting the site of an electric-vehicle charging station from a sustainable perspective. Sustainable Cities and Society, 65, 102623. https://doi.org/10.1016/j.scs.2020.102623
- Funke, S. Á., Sprei, F., Gnann, T., et al. (2019). How much charging infrastructure do electric vehicles need? A review of the evidence and international comparison. Transportation Research Part D: Transport and Environment, 77, 224–242. https://doi.org/10.1016/j.trd.2019.10.024
- Gnann, T., Funke, S., Jakobsson, N., et al. (2018). Fast charging infrastructure for electric vehicles: Today’s situation and future needs. Transportation Research Part D: Transport and Environment, 62, 314–329. https://doi.org/10.1016/j.trd.2018.03.004
- Goussian, A., LeBel, F.-A., Trovão, J. P., et al. (2019). Passive hybrid energy storage system based on lithium-ion capacitor for an electric motorcycle. Journal of Energy Storage, 25, 100884. https://doi.org/10.1016/j.est.2019.100884
- Greenstone, M., Nilekani, J., Pande, R., et al. (2015). Lower pollution, longer lives: life expectancy gains if India reduced particulate matter pollution. Economic and Political Weekly, 40–46.
- Guerra, E. (2019). Electric vehicles, air pollution, and the motorcycle city: A stated preference survey of consumers’ willingness to adopt electric motorcycles in Solo, Indonesia. Transportation Research Part D: Transport and Environment, 68, 52–64. https://doi.org/10.1016/j.trd.2017.07.027
- Hardman, S., Jenn, A., Tal, G., et al. (2018). A review of consumer preferences of and interactions with electric vehicle charging infrastructure. Transportation Research Part D: Transport and Environment, 62, 508–523. https://doi.org/10.1016/j.trd.2018.04.002
- Huang, S.-W., Liou, J. J. H., Chuang, H.-H., et al. (2021). Using a Modified VIKOR Technique for Evaluating and Improving the National Healthcare System Quality. Mathematics, 9(12), 1349. https://doi.org/10.3390/math9121349
- Huang, S.-W., Liou, J. J. H., Tang, W., et al. (2020). Location Selection of a Manufacturing Facility from the Perspective of Supply Chain Sustainability. Symmetry, 12(9), 1418. https://doi.org/10.3390/sym12091418
- Huang, S. K., Kuo, L., & Chou, K.-L. (2018). The impacts of government policies on green utilization diffusion and social benefits – A case study of electric motorcycles in Taiwan. Energy Policy, 119, 473–486. https://doi.org/10.1016/j.enpol.2018.04.061
- Huang, X., & Ge, J. (2019). Electric vehicle development in Beijing: An analysis of consumer purchase intention. Journal of Cleaner Production, 216, 361–372. https://doi.org/10.1016/j.jclepro.2019.01.231
- Ibanez, F. M., Beizama Florez, A. M., Gutierrez, S., et al. (2019). Extending the Autonomy of a Battery for Electric Motorcycles. IEEE Transactions on Vehicular Technology, 68(4), 3294–3305. https://doi.org/10.1109/tvt.2019.2896901
- Jones, L. R., Cherry, C. R., Vu, T. A., et al. (2013). The effect of incentives and technology on the adoption of electric motorcycles: A stated choice experiment in Vietnam. Transportation Research Part A: Policy and Practice, 57, 1–11. https://doi.org/10.1016/j.tra.2013.09.003
- Kabli, M., Quddus, M. A., Nurre, S. G., et al. (2020). A stochastic programming approach for electric vehicle charging station expansion plans. International Journal of Production Economics, 220, 107461. https://doi.org/10.1016/j.ijpe.2019.07.034
- Kannan, A. S. K., Balamurugan, S. A. A., & Sasikala, S. (2021). A Customized Metaheuristic Approaches for Improving Supplier Selection in Intelligent Decision Making. IEEE Access, 9, 56228–56239. https://doi.org/10.1109/access.2021.3071454
- Kim, S., Na, D., Choi, Y., & Jung, H. (2021). Trends on Postal Vehicles in World-wide 10 Postal Agencies. Electronics and Telecommunications Trends, 36(3), 145–160.
- Liu, H.-C., Yang, M., Zhou, M., et al. (2019). An Integrated Multi-Criteria Decision Making Approach to Location Planning of Electric Vehicle Charging Stations. IEEE Transactions on Intelligent Transportation Systems, 20(1), 362–373. https://doi.org/10.1109/tits.2018.2815680
- Lo, H.-W., Liou, J. J. H., Huang, C.-N., et al. (2019). A novel failure mode and effect analysis model for machine tool risk analysis. Reliability Engineering & System Safety, 183, 173–183. https://doi.org/10.1016/j.ress.2018.11.018
- Luo, M., Du, B., Klemmer, K., et al. (2022). Deployment Optimization for Shared e-Mobility Systems with Multi-Agent Deep Neural Search. IEEE Transactions on Intelligent Transportation Systems, 23(3), 2549–2560. https://doi.org/10.1109/tits.2021.3125745
- Mardani, A., Zavadskas, E., Govindan, K., et al. (2016). VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications. Sustainability, 8(1), 37. https://doi.org/10.3390/su8010037
- Mehar, S., & Senouci, S. M. (2013). An optimization location scheme for electric charging stations. 2013 International Conference on Smart Communications in Network Technologies (SaCoNeT). https://doi.org/10.1109/saconet.2013.6654565
- Mohammadi, M., & Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega, 96, 102075. https://doi.org/10.1016/j.omega.2019.06.001
- Mouli, G. R. C., Venugopal, P., & Bauer, P. (2017). Future of electric vehicle charging. 2017 International Symposium on Power Electronics (Ee). https://doi.org/10.1109/pee.2017.8171657
- Quayson, M., Bai, C., Sun, L., et al. (2023). Building blockchain‐driven dynamic capabilities for developing circular supply chain: Rethinking the role of sensing, seizing, and reconfiguring. Business Strategy and the Environment, 32(7), 4821–4840. Portico. https://doi.org/10.1002/bse.3395
- Rao, R., Zhang, X., Xie, J., et al. (2015). Optimizing electric vehicle users’ charging behavior in battery swapping mode. Applied Energy, 155, 547–559. https://doi.org/10.1016/j.apenergy.2015.05.125
- Raqabi, Er. M., & Li, W. (2023). An Electric Vehicle Transitioning Framework for Public Fleet Planning. Transportation Research Part D: Transport and Environment, 118, 103732. https://doi.org/10.1016/j.trd.2023.103732
- Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
- Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126–130. https://doi.org/10.1016/j.omega.2015.12.001
- Rezaei, J., Kothadiya, O., Tavasszy, L., et al. (2018). Quality assessment of airline baggage handling systems using SERVQUAL and BWM. Tourism Management, 66, 85–93. https://doi.org/10.1016/j.tourman.2017.11.009
- Ribeiro, R. G., Junior, J. R. C., Cota, L. P., et al. (2020). Unmanned Aerial Vehicle Location Routing Problem with Charging Stations for Belt Conveyor Inspection System in the Mining Industry. IEEE Transactions on Intelligent Transportation Systems, 21(10), 4186–4195. https://doi.org/10.1109/tits.2019.2939094
- Risso, C., Cintrano, C., Toutouh, J., & Nesmachnow, S. (2021). Exact approach for electric vehicle charging infrastructure location: a real case study in málaga, spain. Ibero-American Congress of Smart Cities.
- Sadrani, M., Najafi, A., Mirqasemi, R., et al. (2023). Charging strategy selection for electric bus systems: A multi-criteria decision-making approach. Applied Energy, 347, 121415. https://doi.org/10.1016/j.apenergy.2023.121415
- Sandhya, P., & Nisha, G. (2022). Review of Battery Charging Methods for Electric Vehicle. In: Proceedings of the 2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES).
- Schroeder, A., & Traber, T. (2012). The economics of fast charging infrastructure for electric vehicles. Energy Policy, 43, 136–144. https://doi.org/10.1016/j.enpol.2011.12.041
- Sonar, H. C., & Kulkarni, S. D. (2021). An Integrated AHP-MABAC Approach for Electric Vehicle Selection. Research in Transportation Business & Management, 41, 100665. https://doi.org/10.1016/j.rtbm.2021.100665
- Sun, B., Sun, X., Tsang, D. H. K., et al. (2019). Optimal battery purchasing and charging strategy at electric vehicle battery swap stations. European Journal of Operational Research, 279(2), 524–539. https://doi.org/10.1016/j.ejor.2019.06.019
- Trappey, A. J. C., Trappey, C., Hsiao, C. T., et al. (2012). An evaluation model for low carbon island policy: The case of Taiwan’s green transportation policy. Energy Policy, 45, 510–515. https://doi.org/10.1016/j.enpol.2012.02.063
- Yeung, J. S., Wong, Y. D., & Secadiningrat, J. R. (2015). Lane-harmonised passenger car equivalents for heterogeneous expressway traffic. Transportation Research Part A: Policy and Practice, 78, 361–370. https://doi.org/10.1016/j.tra.2015.06.001
- Yogesh, A., & Radhakrishna, K. (2021). A review on fast wireless charging methods for Electric Vehicles. International Research Journal of Engineering and Technology, 9(8), 1821-1826.
- Zhu, H., Liu, G., Zhou, M., et al. (2019). Dandelion Algorithm with Probability-Based Mutation. IEEE Access, 7, 97974–97985. https://doi.org/10.1109/access.2019.2927846
- Zhu, L., Song, Q., Sheng, N., et al. (2019). Exploring the determinants of consumers’ WTB and WTP for electric motorcycles using CVM method in Macau. Energy Policy, 127, 64–72. https://doi.org/10.1016/j.enpol.2018.12.004
DOI: https://doi.org/10.24294/jipd.v8i9.6495
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Sun-Weng Huang, Yu-Hsuan Liao, Ju-Min Liao, James J. H. Liou
License URL: https://creativecommons.org/licenses/by/4.0/
This site is licensed under a Creative Commons Attribution 4.0 International License.