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Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks

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  • Pol Olivella-Rosell

    (Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, EU d'Enginyeria Tècnica Industrial de Barcelona, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain)

  • Roberto Villafafila-Robles

    (Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, EU d'Enginyeria Tècnica Industrial de Barcelona, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain
    Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, ETS d'Enginyeria Industrial de Barcelona, Av. Diagonal, 647, Pl. 2. 08028 Barcelona, Spain)

  • Andreas Sumper

    (Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, EU d'Enginyeria Tècnica Industrial de Barcelona, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain
    Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, ETS d'Enginyeria Industrial de Barcelona, Av. Diagonal, 647, Pl. 2. 08028 Barcelona, Spain)

  • Joan Bergas-Jané

    (Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya, ETS d'Enginyeria Industrial de Barcelona, Av. Diagonal, 647, Pl. 2. 08028 Barcelona, Spain)

Abstract

Electric Vehicles (EVs) have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processes required to reach its destination. This methodology also permits to consider social and economic variables. Furthermore, the model is stochastic, in order to consider the random pattern of some variables. The model is applied to Barcelona’s (Spain) mobility pattern and uses the 37-node IEEE test feeder adapted to common distribution grid characteristics from Barcelona. The corresponding grid impact is analyzed in terms of voltage drop and four charging strategies are compared. The case study indicates that the variability in scenarios without control is relevant, but not in scenarios with control. Moreover, the voltages do not reach the minimum voltage allowed, but the MV/LV substations could exceed their capacities. Finally, it is determined that all EVs can charge during the valley without any negative effect on the distribution grid. In conclusion, it is determined that the methodology presented allows the EV charging demand to be calculated, considering different variables, to obtain better accuracy in the results.

Suggested Citation

  • Pol Olivella-Rosell & Roberto Villafafila-Robles & Andreas Sumper & Joan Bergas-Jané, 2015. "Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks," Energies, MDPI, vol. 8(5), pages 1-28, May.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:5:p:4160-4187:d:49393
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    References listed on IDEAS

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    1. Kelly, Jarod C. & MacDonald, Jason S. & Keoleian, Gregory A., 2012. "Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics," Applied Energy, Elsevier, vol. 94(C), pages 395-405.
    2. Grenier, Agathe & Page, Shannon, 2012. "The impact of electrified transport on local grid infrastructure: A comparison between electric cars and light rail," Energy Policy, Elsevier, vol. 49(C), pages 355-364.
    3. Loisel, Rodica & Pasaoglu, Guzay & Thiel, Christian, 2014. "Large-scale deployment of electric vehicles in Germany by 2030: An analysis of grid-to-vehicle and vehicle-to-grid concepts," Energy Policy, Elsevier, vol. 65(C), pages 432-443.
    4. João Soares & Bruno Canizes & Cristina Lobo & Zita Vale & Hugo Morais, 2012. "Electric Vehicle Scenario Simulator Tool for Smart Grid Operators," Energies, MDPI, vol. 5(6), pages 1-19, June.
    5. Qinglai Guo & Yao Wang & Hongbin Sun & Zhengshuo Li & Shujun Xin & Boming Zhang, 2012. "Factor Analysis of the Aggregated Electric Vehicle Load Based on Data Mining," Energies, MDPI, vol. 5(6), pages 1-18, June.
    6. Peng, Minghong & Liu, Lian & Jiang, Chuanwen, 2012. "A review on the economic dispatch and risk management of the large-scale plug-in electric vehicles (PHEVs)-penetrated power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1508-1515.
    7. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    8. Weiller, Claire, 2011. "Plug-in hybrid electric vehicle impacts on hourly electricity demand in the United States," Energy Policy, Elsevier, vol. 39(6), pages 3766-3778, June.
    9. Eduardo Valsera-Naranjo & Andreas Sumper & Roberto Villafafila-Robles & David Martínez-Vicente, 2012. "Probabilistic Method to Assess the Impact of Charging of Electric Vehicles on Distribution Grids," Energies, MDPI, vol. 5(5), pages 1-29, May.
    10. Amjad, Shaik & Neelakrishnan, S. & Rudramoorthy, R., 2010. "Review of design considerations and technological challenges for successful development and deployment of plug-in hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1104-1110, April.
    11. Lyon, Thomas P. & Michelin, Mark & Jongejan, Arie & Leahy, Thomas, 2012. "Is “smart charging” policy for electric vehicles worthwhile?," Energy Policy, Elsevier, vol. 41(C), pages 259-268.
    12. Wang, Jianhui & Liu, Cong & Ton, Dan & Zhou, Yan & Kim, Jinho & Vyas, Anantray, 2011. "Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power," Energy Policy, Elsevier, vol. 39(7), pages 4016-4021, July.
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