Hexagonal P-Median: Um modelo para alocação de pontos de recarga para caminhões elétricos
Resumo
A elaboração de soluções que viabilizem uso de meios de transporte com energia elétrica tornou-se importante, devido aos impactos ambientais causados pelos gases emitidos por queima de combustíveis fósseis. No entanto, para que esse tipo de veículo seja adotado, é preciso investir na infraestrutura rodoviária, tal como pontos de recarga elétrica. Este trabalho apresenta o Hexagonal P-Median, um modelo de alocação de pontos de recarga que atende às trajetórias dos caminhoneiros brasileiros. O modelo proposto foi comparado com um algoritmo guloso e um modelo de cobertura de conjuntos por meio de uma simulação com dados reais de 44,5 milhões de registros de localização de 3,086 motoristas. O modelo proposto apresenta, aproximadamente, 230% e 276% a mais de cobertura que o algoritmo guloso e o modelo de cobertura de conjuntos, respectivamente, considerando o cenário de 10 km de desvio.Referências
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Xiong, Y., An, B., and Kraus, S. (2021). Electric vehicle charging strategy study and the application on charging station placement. Autonomous Agents and Multi-Agent Systems, 35(1):1–19.
Xiong, Y., Gan, J., An, B., Miao, C., and Bazzan, A. L. (2017). Optimal electric vehicle fast charging station placement based on game theoretical framework. IEEE Transactions on Intelligent Transportation Systems, 19(8):2493–2504.
Zafar, U., Bayram, I. S., and Bayhan, S. (2021). A gis-based optimal facility location framework for fast electric vehicle charging stations. In 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), pages 1–5. IEEE.
Andrade, J., Ochoa, L. F., and Freitas, W. (2020). Regional-scale allocation of fast charging stations: travel times and distribution system reinforcements. IET Generation, Transmission & Distribution, 14(19):4225–4233.
Bayram, I. S., Zafar, U., and Bayhan, S. (2022). Could petrol stations play a key role in transportation electrification? a gis-based coverage maximization of fast ev chargers in urban environment. IEEE Access, 10:17318–17329.
Bi, R., Xiao, J., Pelzer, D., Ciechanowicz, D., Eckhoff, D., and Knoll, A. (2017). A simulation-based heuristic for city-scale electric vehicle charging station placement. In 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), pages 1–7.
Brey, J. J., Brey, R., Carazo, A. F., Ruiz-Montero, M. J., and Tejada, M. (2016). Incorporating refuelling behaviour and drivers’ preferences in the design of alternative fuels infrastructure in a city. Transportation Research Part C: Emerging Technologies, 65:144–155.
Church, R. L. (2018). Tobler’s law and spatial optimization: Why bakersfield? International Regional Science Review, 41(3):287–310.
Church, R. L., Murray, A., et al. (2018). Location covering models. Advances in Spatial Science.
Cui, Q., Weng, Y., and Tan, C.-W. (2019). Electric vehicle charging station placement method for urban areas. IEEE Transactions on Smart Grid, 10(6):6552–6565.
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische mathematik, 1(1):269–271.
Feng, X., Barcelos, G., Gaboardi, J. D., Knaap, E., Wei, R., Wolf, L. J., Zhao, Q., and Rey, S. J. (2022). spopt: a python package for solving spatial optimization problems in pysal. Journal of Open Source Software, 7(74).
Hakimi, S. L. (1965). Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Operations research, 13(3):462–475.
He, S. Y., Kuo, Y.-H., and Wu, D. (2016). Incorporating institutional and spatial factors in the selection of the optimal locations of public electric vehicle charging facilities: A case study of beijing, china. Transportation Research Part C: Emerging Technologies, 67:131–148.
Hosseini, M., MirHassani, S. A., and Hooshmand, F. (2017). Deviation-flow refueling location problem with capacitated facilities: Model and algorithm. Transportation Research Part D: Transport and Environment, 54:269–281.
Hu, X., Lei, H., Deng, D., Bi, Y., Zhao, J., and Wang, R. (2024). A two-stage approach to siting electric bus charging stations considering future-current demand. Journal of Cleaner Production, 434:139962.
Iravani, H. (2022). A multicriteria gis-based decision-making approach for locating electric vehicle charging stations. Transportation Engineering, 9:100135.
Jahangir, H., Gougheri, S. S., Vatandoust, B., Golkar, M. A., Golkar, M. A., Ahmadian, A., and Hajizadeh, A. (2022). A novel cross-case electric vehicle demand modeling based on 3d convolutional generative adversarial networks. IEEE Transactions on Power Systems, 37(2):1173–1183.
Kchaou-Boujelben, M. (2021). Charging station location problem: A comprehensive review on models and solution approaches. Transportation Research Part C: Emerging Technologies, 132:103376.
Lam, A. Y. S., Leung, Y.-W., and Chu, X. (2014). Electric vehicle charging station placement: Formulation, complexity, and solutions. IEEE Transactions on Smart Grid, 5(6):2846–2856.
Liimatainen, H., van Vliet, O., and Aplyn, D. (2019). The potential of electric trucks – an international commodity-level analysis. Applied Energy, 236:804–814.
Machado, C. A. S., Takiya, H., Yamamura, C. L. K., Quintanilha, J. A., and Berssaneti, F. T. (2020). Placement of infrastructure for urban electromobility: A sustainable approach. Sustainability, 12(16):6324.
Omohundro, S. M. (1989). Five balltree construction algorithms. International Computer Science Institute.
Speth, D., Plötz, P., Funke, S., and Vallarella, E. (2022). Public fast charging infrastructure for battery electric trucks—a model-based network for germany. Environmental Research: Infrastructure and Sustainability, 2(2):025004.
Tobler, W. R. (1970). A computer movie simulating urban growth in the detroit region. Economic geography, 46(sup1):234–240.
Viswanathan, V., Zehe, D., Ivanchev, J., Pelzer, D., Knoll, A., and Aydt, H. (2016). Simulation-assisted exploration of charging infrastructure requirements for electric vehicles in urban environments. Journal of Computational Science, 12:1–10.
Wu, J., Powell, S., Xu, Y., Rajagopal, R., and Gonzalez, M. C. (2024). Planning charging stations for 2050 to support flexible electric vehicle demand considering individual mobility patterns. Cell Reports Sustainability, 1(1).
Xiong, Y., An, B., and Kraus, S. (2021). Electric vehicle charging strategy study and the application on charging station placement. Autonomous Agents and Multi-Agent Systems, 35(1):1–19.
Xiong, Y., Gan, J., An, B., Miao, C., and Bazzan, A. L. (2017). Optimal electric vehicle fast charging station placement based on game theoretical framework. IEEE Transactions on Intelligent Transportation Systems, 19(8):2493–2504.
Zafar, U., Bayram, I. S., and Bayhan, S. (2021). A gis-based optimal facility location framework for fast electric vehicle charging stations. In 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), pages 1–5. IEEE.
Publicado
20/05/2024
Como Citar
SANTOS, Germano B. dos; MELOS, Guilherme C.; FIGUEIREDO, Leonardo J. A. S.; SILVA, Fabrício A.; SILVA, Thais R. M. B.; LOUREIRO, Antonio A. F..
Hexagonal P-Median: Um modelo para alocação de pontos de recarga para caminhões elétricos. In: WORKSHOP DE COMPUTAÇÃO URBANA (COURB), 8. , 2024, Niterói/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 169-182.
ISSN 2595-2706.
DOI: https://doi.org/10.5753/courb.2024.3278.
