Ir al contenido

Documat


Smart and sustainable scheduling of charging events for electric buses

  • Padraigh Jarvis [1] ; Laura Climent [2] ; Alejandro Arbelaez [2]
    1. [1] University College Cork

      University College Cork

      Irlanda

    2. [2] Universidad Autónoma de Madrid

      Universidad Autónoma de Madrid

      Madrid, España

  • Localización: Top, ISSN-e 1863-8279, ISSN 1134-5764, Vol. 32, Nº. 1, 2024, págs. 22-56
  • Idioma: inglés
  • DOI: 10.1007/s11750-023-00657-5
  • Enlaces
  • Resumen
    • This paper presents a framework for the efcient management of renewable energies to charge a feet of electric buses (eBuses). Our framework starts with the prediction of clean energy time windows, i.e., periods of time when the production of clean energy exceeds the demand of the country. Then, the optimization phase schedules charging events to reduce the use of non-clean energy to recharge eBuses while passengers are embarking or disembarking. The proposed framework is capable of overcoming the unstable and chaotic nature of wind power generation to operate the feet without perturbing the quality of service. Our extensive empirical validation with real instances from Ireland suggests that our solutions can signifcantly reduce non-clean energy consumed on large data sets.

  • Referencias bibliográficas
    • Arbelaez A, Climent L (2020) Transition to eBuses with minimal timetable disruptions. In: Thirteenth annual symposium on combinatorial search...
    • Arbelaez A, Hamadi Y, Sebag M (2012) Continuous search in constraint programming. In: Autonomous search. Springer, Berlin, pp 219–243
    • Balafrej A, Bessiere C, Paparrizou A (2015) Multi-armed bandits for adaptive constraint propagation. In: IJCAI Buenos Aires, Argentina, July...
    • Bengio Y, Lodi A, Prouvost A (2021) Machine learning for combinatorial optimization: a methodological tour d’horizon. Eur J Oper Res 290(2):405–421...
    • Box GE, Jenkins GM, Reinsel GC, Ljung GM (2015) Time series analysis: forecasting and control. Wiley, New York
    • Chand S, Hsu VN, Sethi S (2002) Forecast, solution, and rolling horizons in operations management problems: a classifed bibliography. Manuf...
    • Climent L, Wallace RJ, Salido MA, Barber F (2014) Robustness and stability in constraint programming under dynamism and uncertainty. J Artif...
    • Department of Communications, Climate Action and Environment (2019) National climate and energy plan 2021–2030. https://assets.gov.ie/94442/f3e50986-9fde-4d34-aa35-319af3bfac0c.pdf...
    • Desrochers M, Desrosiers J, Solomon M (1992) A new optimization algorithm for the vehicle routing problem with time windows. Oper Res 40(2):342–354...
    • Duque R, Arbelaez A, Díaz JF (2018) Online over time processing of combinatorial problems. Constraints Int J 23(3):310–334
    • Elmachtoub AN, Grigas P (2021) Smart “predict, then optimize’’. Manag Sci 68:9–26
    • Erdelic T, Caric T (2019) A survey on the electric vehicle routing problem: variants and solution approaches. J Adv Transp
    • Farindon P (2009) Synopsis of the lithium-ion battery markets. In: Lithium-ion batteries, chap 1. Springer, Berlin, pp 1–7
    • Feng C, Chartan EK, Hodge BMS, Zhang J (2017) Characterizing time series data diversity for wind forecasting. In: BDCAT, pp 113–119
    • Frade I, Ribeiro A, Gonçalves G, Antunes AP (2011) Optimal location of charging stations for electric vehicles in a neighborhood in Lisbon,...
    • Froger A, Mendoza JE, Jabali O, Laporte G (2019) Improved formulations and algorithmic components for the electric vehicle routing problem...
    • Funke S, Nusser A, Storandt S (2015) Placement of loading stations for electric vehicles: no detours necessary! J Artif Intell Res 53:633–658...
    • Funke S, Nusser A, Storandt S (2016) Placement of loading stations for electric vehicles: allowing small detours. In: Proceedings of the international...
    • Gallet M, Massier T, Hamacher T (2018) Estimation of the energy demand of electric buses based on real-world data for large-scale public transport...
    • Giebel G, Kariniotakis G, Brownsword R (2003) The state-of-the-art in short term prediction of wind power from a Danish perspective
    • Gopalakrishnan R, Biswas A, Lightwala A, Vasudevan S, Dutta P, Tripathi A (2016) Demand prediction and placement optimization for electric...
    • Häll CH, Ceder A, Ekström J, Quttineh NH (2019) Adjustments of public transit operations planning process for the use of electric buses. J...
    • Hulagu S, Çelikoglu HB (2019) A multiple objective formulation of an electric vehicle routing problem for shuttle bus feet at a university...
    • Ifrim G, O’Sullivan B, Simonis H (2012) Properties of energy-price forecasts for scheduling. In: CP Québec City, October 8–12, 2012, Lecture...
    • Jordán J, Palanca J, del Val E, Julian V, Botti V (2021) Localization of charging stations for electric vehicles using genetic algorithms....
    • Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980
    • Kotthof L, Gent IP, Miguel I (2012) An evaluation of machine learning in algorithm selection for search problems. AI Commun 25(3):257–270
    • Laporte G, Nobert Y (1987) Exact algorithms for the vehicle routing problem. In: North-Holland Mathematics Studies, vol 132. Elsevier, Amsterdam,...
    • Lim B, Zohren S (2021) Time-series forecasting with deep learning: a survey. Philos Trans R Soc A 379(2194):20200209
    • Lin J, Zhou W, Wolfson O (2016) Electric vehicle routing problem. Transportation Research Procedia, vol 12, pp 508–521. Tenth international...
    • Mandi J, Demirovic E, Stuckey PJ, Guns T (2020) Smart predict-and-optimize for hard combinatorial optimization problems. In: AAAI’20. AAAI...
    • Masuch N, Keiser J, Lützenberger M, Albayrak S (2012) Wind power-aware vehicle-to-grid algorithms for sustainable EV energy management systems....
    • Mora E, Cifuentes J, Marulanda G (2021) Short-term forecasting of wind energy: a comparison of deep learning frameworks. Energies 14(23):7943...
    • Olgun B, Koç Ç, Altiparmak F (2021) A hyper heuristic for the green vehicle routing problem with simultaneous pickup and delivery. Comput...
    • Pevec D, Babic J, Carvalho A, Ghiassi-Farrokhfal Y, Ketter W, Podobnik V (2020) A survey-based assessment of how existing and potential electric...
    • Prestwich SD, Fajemisin AO, Climent L, O’Sullivan B (2015) Solving a hard cutting stock problem by machine learning and optimisation. In:...
    • Prestwich SD, Freuder EC, O’Sullivan B, Browne D (2021) Classifer-based constraint acquisition. Ann Math Artif Intell 89(7):655–674
    • Sadeghi-Barzani P, Rajabi-Ghahnavieh A, Kazemi-Karegar H (2014) Optimal fast charging station placing and sizing. App Energy 125:289–299
    • Sangiorgio M, Dercole F (2020) Robustness of LSTM neural networks for multi-step forecasting of chaotic time series. Chaos Solit Fractals...
    • Schneider M, Stenger A, Goeke D (2014) The electric vehicle-routing problem with time windows and recharging stations. Transp Sci 48(4):500–520...
    • Shobana Devi A, Maragatham G, Boopathi K, Lavanya MC, Saranya R (2021) Long-term wind speed forecasting—a review. In: Artifcial intelligence...
    • Spliet R, Gabor AF (2015) The time window assignment vehicle routing problem. Transp Sci 49(4):721–731
    • Wang YW, Lin CC (2009) Locating road-vehicle refueling stations. Transp Res Part E Logist Transp Rev 45(5):821–829
    • Xu L, Hutter F, Hoos HH, Leyton-Brown K (2008) Satzilla: portfolio-based algorithm selection for SAT. J Artif Intell Res 32:565–606 Xu H,...
    • Zhang T, Chen W, Han Z, Cao Z (2013) Charging scheduling of electric vehicles with local renewable energy under uncertain electric vehicle...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno