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Modelling dynamic demand response for plug-in hybrid electric vehicles based on real-time charging pricing

Modelling dynamic demand response for plug-in hybrid electric vehicles based on real-time charging pricing

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Based on the benefits of real-time pricing both to individual users and the society as a whole, this study introduces a real-time charging price (RTCP) mechanism supported by an intelligent charging management module into plug-in hybrid electric vehicles (PHEVs) charging environment. The optimal RTCP is executed by a distributed algorithm using a utility model to maximise the whole charging system welfare. The willingness-to-charge parameter is derived to reflect the charging preferences of PHEV users and their different responses to the RTCP. Several scenarios are established to discuss the effect of both the RTCP and willingness-to-charge on charging load. The simulation results show that reasonable charging will be realised based on the optimal RTCP mechanism.

References

    1. 1)
      • 1. Hausman, E.D., Tabors, R.D.: ‘The role of demand under scheduling in the California energy crisis’. IEEE Int. Conf. on System Sciences, 2004.
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • 6. Mohsenian-Rad, A.H., Wong, V., Jatskevich, J., et al: ‘Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid’. IEEE PES Innovative Smart Grid Technologies (ISGT), 2010.
    7. 7)
    8. 8)
    9. 9)
      • 9. Yu, R., Yang, W., Rahardja, S.: ‘Optimal real-time price based on a statistical demand elasticity model of electricity’, Smart Grid Modeling and Simulation (SGMS), 2011.
    10. 10)
      • 10. Samadi, P., Mohsenian-Rad, A.H., Schober, R., et al: ‘Optimal real-time pricing algorithm based on utility maximization for smart grid’. IEEE Int. Conf. Smart Grid Communications (SmartGridComm), 2010, pp. 415420.
    11. 11)
      • 11. Tarasak, P.: ‘Optimal real-time pricing under load uncertainty based on utility maximization for smart grid’, IEEE SmartGridComm, 2011, pp. 321326.
    12. 12)
    13. 13)
      • 13. Asadi, G., Gitizadeh, M., Roosta, A.: ‘Welfare maximization under real-time pricing in smart grid using PSO algorithm’. Iranian Conf. on Electrical Engineering (ICEE), 2013, pp. 17.
    14. 14)
      • 14. Weckx, S., Driesen, J., D'hulst, R.: ‘Optimal real-time pricing for unbalanced distribution grids with network constraints’. IEEE Power and Energy Society General Meeting (PES), 2013, pp. 15.
    15. 15)
      • 15. Meng, F., Zeng, X., Qian, M.: ‘Learning customer behaviour under real-time pricing in the smart grid’. IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC), 2013, pp. 31863191.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
    20. 20)
    21. 21)
    22. 22)
      • 22. Ma, Z., Callaway, D., Hiskens, I.: ‘Decentralized charging control for large populations of plug-in electric vehicles: application of the nash certainty equivalence principle’. Proc. of IEEE Int. Conf. on Control, 2010.
    23. 23)
      • 23. Mas-Colell, A., Whinston, M.D., Green, J.R., et al: ‘Microeconomic theory’, Oup Catalogue, 1995, 44, (4), pp. 370372.
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