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Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability

Author

Listed:
  • Shafie-khah, M.
  • Heydarian-Forushani, E.
  • Golshan, M.E.H.
  • Siano, P.
  • Moghaddam, M.P.
  • Sheikh-El-Eslami, M.K.
  • Catalão, J.P.S.

Abstract

Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significantly affect the approaching smart grids. Indeed, Demand Response (DR) brings a positive effect on the uncertainties of renewable energy sources, improving market efficiency and enhancing system reliability. This paper proposes a multi-stage stochastic model of a PEV aggregation agent to participate in day-ahead and intraday electricity markets. The stochastic model reflects several uncertainties such as the behaviour of PEV owners, electricity market prices, and activated quantity of reserve by the system operator. For this purpose, appropriate scenarios are utilized to realize the uncertain feature of the problem. Furthermore, in the proposed model, the PEV aggregation agents can update their bids/offers by taking part in the intraday market. To this end, these aggregation agents take part in Demand Response eXchange (DRX) markets designed in the intraday session by employing DR resources. The numerical results show that DR provides a perfect opportunity for PEV aggregation agents to increase the profit. In addition, the results reveal that the PEV aggregation agent not only can increase its profit by participating in the DRX market, but also can become an important player in the mentioned market.

Suggested Citation

  • Shafie-khah, M. & Heydarian-Forushani, E. & Golshan, M.E.H. & Siano, P. & Moghaddam, M.P. & Sheikh-El-Eslami, M.K. & Catalão, J.P.S., 2016. "Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability," Applied Energy, Elsevier, vol. 162(C), pages 601-612.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:601-612
    DOI: 10.1016/j.apenergy.2015.10.134
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    9. Gehbauer, Christoph & Black, Douglas R. & Grant, Peter, 2023. "Advanced control strategies to manage electric vehicle drivetrain battery health for Vehicle-to-X applications," Applied Energy, Elsevier, vol. 345(C).
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    12. Subramanian, Vignesh & Das, Tapas K., 2019. "A two-layer model for dynamic pricing of electricity and optimal charging of electric vehicles under price spikes," Energy, Elsevier, vol. 167(C), pages 1266-1277.
    13. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Operational scheduling of electric vehicles parking lot integrated with renewable generation based on bilevel programming approach," Energy, Elsevier, vol. 139(C), pages 422-432.
    14. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
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    16. Perez-Diaz, Alvaro & Gerding, Enrico & McGroarty, Frank, 2018. "Coordination and payment mechanisms for electric vehicle aggregators," Applied Energy, Elsevier, vol. 212(C), pages 185-195.
    17. Will, Christian & Zimmermann, Florian & Ensslen, Axel & Fraunholz, Christoph & Jochem, Patrick & Keles, Dogan, 2023. "Can electric vehicle charging be carbon neutral? Uniting smart charging and renewables," Working Paper Series in Production and Energy 69, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    18. Shuang Gao & Jianzhong Wu & Bin Xu, 2019. "Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables," Energies, MDPI, vol. 12(8), pages 1-20, April.
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    20. Homa Rashidizadeh-Kermani & Hamid Reza Najafi & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2018. "Optimal Decision-Making Strategy of an Electric Vehicle Aggregator in Short-Term Electricity Markets," Energies, MDPI, vol. 11(9), pages 1-20, September.
    21. Tang, Yanyan & Zhang, Qi & Wen, Zongguo & Bunn, Derek & Martin, Jesus Nieto, 2022. "Optimal analysis for facility configuration and energy management on electric light commercial vehicle charging," Energy, Elsevier, vol. 246(C).
    22. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).
    23. Sharifi, R. & Fathi, S.H. & Vahidinasab, V., 2017. "A review on Demand-side tools in electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 565-572.

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