Deadline differentiated pricing in practice: marketing EV charging in car parks

Special Issue Paper

Abstract

Electric vehicle charging is considered as a prime case of load flexibility in future smart grids. We examine a scenario where electric vehicles are charged in a car park with local photovoltaic (PV) generation. In this setting, temporal charging flexibility can be leveraged to increase utilization of local generation. To incentivize flexible loads we apply a deadline differentiated pricing scheme. Prices are set by the car park operator in a profit-maximizing manner in settings with varying PV capacity and costs of conventional generation. This allows us to assess the value of flexibility passed on to customers in form of discounts. Furthermore, we determine the minimum flexibility level qualifying for this discount. By and large, absolute price levels and flexibility discounts are mainly driven by the cost of conventional generation. On the other hand, the minimum flexibility requirements are affected by both the costs of conventional generation as well as the local PV capacity: higher costs of conventional generation as well as larger PV capacities will decrease this threshold.

Keywords

Deadline differentiated pricing Deferable loads Electric vehicles Car park 

References

  1. 1.
    Albadi MH, El-Saadany E (2008) A summary of demand response in electricity markets. Electr Power Syst Res 78(11):1989–1996CrossRefGoogle Scholar
  2. 2.
    Palensky P, Dietrich D (2011) Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans Ind Inform 7(3):381–388Google Scholar
  3. 3.
    Shao S, Pipattanasomporn M, Rahman S (2011) Demand response as a load shaping tool in an intelligent grid with electric vehicles. IEEE Trans Smart Grid 2(4):624–631CrossRefGoogle Scholar
  4. 4.
    Goebel C, Jacobsen H-A, Razo V, Doblander C, Rivera J, Ilg J, Flath C, Schmeck H, Weinhardt C, Pathmaperuma D, Appelrath H-J, Sonnenschein M, Lehnhoff S, Kramer O, Staake T, Fleisch E, Neumann D, Strüker J, Erek K, Zarnekow R, Ziekow H, Lässig J (2014) Energy Informatics. Bus Inf Syst Eng 6(1):25–31. doi:10.1007/s12599-013-0304-2
  5. 5.
    Bitar E, Low S (2012) Deadline differentiated pricing of deferrable electric power service. In: 2012 IEEE 51st IEEE conference on decision and control (CDC), pp 4991–4997, Dec 2012Google Scholar
  6. 6.
    Watson RT, Boudreau M-C, Chen AJ (2010) Information systems and environmentally sustainable development: energy informatics and new directions for the is community. Manag Inf Syst Q 34(1):23–38Google Scholar
  7. 7.
    Bitar E, Xu Y (2013) On incentive compatibility of deadline differentiated pricing for deferrable demand. In: Decision and control (CDC), 2013 IEEE 52nd annual conference on, 2013, pp 5620–5627Google Scholar
  8. 8.
    Flath CM (2013) An optimization approach for the design of time-of-use rates. IECON 2013—39th annual conference of the IEEE industrial electronics society, pp 4727–4732, Nov 2013Google Scholar
  9. 9.
    Eberle U, von Helmolt R (2010) Sustainable transportation based on electric vehicle concepts: a brief overview. Energy Environ Sci 3(6):689–699CrossRefGoogle Scholar
  10. 10.
    Nayyar A, Negrete-Pincetic M, Poolla K, Varaiya P (2014) Duration-differentiated services in electricity. 2014. arXiv:1404.1112.
  11. 11.
    Siddiqi SN, Baughman ML (1993) Reliability differentiated real-time pricing of electricity. IEEE Trans Power Syst 8(2):548–554CrossRefGoogle Scholar
  12. 12.
    Dütschke E, Paetz A-G (2013) Dynamic electricity pricing—which programs do consumers prefer? Energy Policy 59:226–234CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Economics and Business EngineeringKarlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Department of Business ManagementUniversity of WürzburgWürzburgGermany

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