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Operational strategy analysis of electric vehicle battery swapping stations

Operational strategy analysis of electric vehicle battery swapping stations

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Business models for battery swapping stations (BSS) have been emerging as influenced by the increased attention to electric vehicles (EVs) and the deregulation of the electricity market. BSS may also provide support mechanisms for a sustainable EV ecosystem, but swapping stations are still at an early stage and viewed as being risky without a widely accepted prediction of financial return. Although different BSS operational strategies have been proposed, an integrated model that considers battery life, lifecycle cost, EV consumer behaviour, and supplementary grid services is still missing. A two-level hierarchical model is proposed where the unit model follows a transition-based battery allocation technique and the station model provides a system-view platform. Based on the designed hierarchical model, the strict grid scheduling strategy and grid scheduling with battery reservation strategy are evaluated in terms of profit and average battery life using New South Wales and South Australia electricity demand profiles. Results suggest that trading short-term grid services profitability in the grid scheduling with battery reservation strategy led to overall increased profit and also longer service life for batteries.

References

    1. 1)
      • 1. Zulkarnain, L.P., Kinnunen, T., Kess, P.: ‘The electric vehicles ecosystem model: construct, analysis and identification of key challenges’, Managing Global Transitions, 2014, 12, (3), pp. 253277.
    2. 2)
      • 2. Adepetu, A., Keshav, S., Arya, V.: ‘An agent-based electric vehicle ecosystem model: San Francisco case study’, Transp. Policy, 2016, 46, pp. 109122.
    3. 3)
      • 3. Kang, Q., Wang, J., Zhou, M., et al: ‘Centralized charging strategy and scheduling algorithm for electric vehicles under a battery swapping scenario’, IEEE Trans. Intell. Transp. Syst., 2016, 17, (3), pp. 659669.
    4. 4)
      • 4. Nepal, R., Foster, J.: ‘Testing for market integration in the Australian national electricity market’, Energy J., 2016, 37, (4), pp. 215237.
    5. 5)
      • 5. Mikkola, J., Lund, P.D.: ‘Modeling flexibility and optimal use of existing power plants with large-scale variable renewable power schemes’, Energy, 2016, 112, pp. 364375.
    6. 6)
      • 6. Craig, J.D.: ‘Motivations for market restructuring: evidence from U.S. electricity deregulation’, Energy Econ., 2016, 60, pp. 162167.
    7. 7)
      • 7. Momoh, J.: ‘Smart grid architectural designs’ (John Wiley & Sons, 2012).
    8. 8)
      • 8. Mah, D., Hills, P.J., Li, V.O.K., et al: ‘Smart grid applications and developments’ (Springer, 2014).
    9. 9)
      • 9. Darabi, Z., Ferdowsi, M.: ‘Aggregated impact of plug-in hybrid electric vehicles on electricity demand profile’, IEEE Trans. Sustain. Energy, 2011, 2, (4), pp. 501508.
    10. 10)
      • 10. Yang, S., Yao, J., Kang, T., et al: ‘Dynamic operation model of the battery swapping station for EV (electric vehicle) in electricity market’, Energy, 2014, 65, (Suppl. C), pp. 544549.
    11. 11)
      • 11. Zheng, Y., Dong, Z.Y., Xu, Y., et al: ‘Electric vehicle battery charging/swap stations in distribution systems: comparison study and optimal planning’, IEEE Trans. Power Syst., 2014, 29, (1), pp. 221229.
    12. 12)
      • 12. Sarker, M.R., Pandzic, H., Ortega-Vazquez, M.A.: ‘Optimal operation and services scheduling for an electric vehicle battery swapping station’, IEEE Trans. Power Syst., 2015, 30, (2), pp. 901910.
    13. 13)
      • 13. Markel, T., Simpson, A.: ‘Cost-benefit analysis of plug-in hybrid electric vehicle technology’, World Electric Veh. J., 2007, 1, (1), pp. 294301.
    14. 14)
      • 14. Dai, Q., Cai, T., Duan, S., et al: ‘Stochastic modeling and forecasting of load demand for electric bus battery-swap station’, IEEE Trans. Power Deliv., 2014, 29, (4), pp. 19091917.
    15. 15)
      • 15. Wei, Q., Liu, D., Liu, Y., et al: ‘Optimal constrained self-learning battery sequential management in microgrid via adaptive dynamic programming’, IEEE/CAA J. Autom. Sin., 2017, 4, (2), pp. 168176.
    16. 16)
      • 16. Ma, Y., Li, B., Li, G., et al: ‘A nonlinear observer approach of Soc estimation based on hysteresis model for lithium-Ion battery’, IEEE/CAA J. Autom. Sin., 2017, 4, (2), pp. 195204.
    17. 17)
      • 17. Guo, W., Healy, W.M., Zhou, M.C.: ‘Battery discharge characteristics of wireless sensors in building applications’. Proc. 2012 9th IEEE Int. Conf. Networking, Sensing and Control, 2012.
    18. 18)
      • 18. Saxena, S., Le Floch, C., MacDonald, J., et al: ‘Quantifying EV battery end-of-life through analysis of travel needs with vehicle powertrain models’, J. Power Sources, 2015, 282, pp. 265276.
    19. 19)
      • 19. Viswanathan, V.V., Kintner-Meyer, M.: ‘Second use of transportation batteries: maximizing the value of batteries for transportation and grid services’, IEEE Trans. Veh. Technol., 2011, 60, (7), pp. 29632970.
    20. 20)
      • 20. Strickland, D., Chittock, L., Stone, D.A., et al: ‘Estimation of transportation battery second life for use in electricity grid systems’, IEEE Trans. Sustain. Energy, 2014, 5, (3), pp. 795803.
    21. 21)
      • 21. Pasaoglu, G., Fiorello, D., Zani, L., et al: ‘Projections for electric vehicle load profiles in Europe based on travel survey data’ (European Commission Institute of Energy and Transport, 2013).
    22. 22)
      • 22. Paevere, P., Higgins, A., Ren, Z., et al: ‘Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load’, Sustain. Sci., 2013, 9, (1), pp. 6176.
    23. 23)
      • 23. Ma, Y., Houghton, T., Cruden, A., et al: ‘Modeling the benefits of vehicle-to-grid technology to a power system’, IEEE Trans. Power Syst., 2012, 27, (2), pp. 10121020.
    24. 24)
      • 24. Australian Energy Market Operator NSW Electricity Price and Demand. Available at https://www.aemo.com.au/Electricity/National-Electricity-Market-NEM/Data, accessed January 2017.
    25. 25)
      • 25. Australian Energy Market Operator. South Australian Electricity Report. Available at https://www.aemo.com.au/media/Files/Electricity/Planning/Reports/SAER/2015/2015_SAER.pdf, accessed February 2017.
    26. 26)
      • 26. Owens, J.C.: ‘Tesla motors to try out battery-swap station’ (Bay Area News Group, Oakland Tribune, 2014).
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