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Dynamic electricity pricing for electric vehicles using stochastic programming

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  • Soares, João
  • Ghazvini, Mohammad Ali Fotouhi
  • Borges, Nuno
  • Vale, Zita

Abstract

Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs' demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty.

Suggested Citation

  • Soares, João & Ghazvini, Mohammad Ali Fotouhi & Borges, Nuno & Vale, Zita, 2017. "Dynamic electricity pricing for electric vehicles using stochastic programming," Energy, Elsevier, vol. 122(C), pages 111-127.
    • Handle: RePEc:eee:energy:v:122:y:2017:i:c:p:111-127
    DOI: 10.1016/j.energy.2016.12.108
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    7. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2017. "Integrating renewable energy sources by electric vehicle fleets under uncertainty," Energy, Elsevier, vol. 141(C), pages 2145-2153.
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    9. Phillip K. Agbesi & Rico Ruffino & Marko Hakovirta, 2023. "The development of sustainable electric vehicle business ecosystems," SN Business & Economics, Springer, vol. 3(8), pages 1-59, August.
    10. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    11. Bagherzade, Shima & Hooshmand, Rahmat-Allah & Firouzmakan, Pouya & Khodabakhshian, Amin & Gholipour, Mehdi, 2019. "Stochastic parking energy pricing strategies to promote competition arena in an intelligent parking," Energy, Elsevier, vol. 188(C).
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