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Optimal Bidding/Offering Strategy for EV Aggregators under a Novel Business Model

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  • Dapeng Chen

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Zhaoxia Jing

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Huijuan Tan

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

Abstract

Realizing the full potential of plug-in electric vehicle (PEVs) in power systems requires the development of business models for PEV owners and electric vehicle aggregators (EVAs). Most business models neglect the significant economic potential of PEV demand response. This paper addresses this challenge by proposing a novel business model to optimize the charging energy of PEVs for maximizing the owners’ profits. The proposed business model aims to overcome the opportunity cost neglect for PEV owners, whose charging energy and charging profiles are optimized with full consideration of the demand curves and market conditions. Lagrangian relaxation technology is used for the relaxation of the constraint of satisfying the charging demand, and as a result, the optimization potential becomes greater. The bidding/offering strategy is formulated as a two-stage stochastic optimization problem, considering the different market prices and initial and target state of energy (SOE) of the PEVs. By case studies and analyses, we demonstrate that the proposed business model can effectively overcome the opportunity cost neglect and increase the PEV owners’ profits. Furthermore, we demonstrate that the proposed business model is incentive-compatible. The PEV owners will be attracted by the proposed business model.

Suggested Citation

  • Dapeng Chen & Zhaoxia Jing & Huijuan Tan, 2019. "Optimal Bidding/Offering Strategy for EV Aggregators under a Novel Business Model," Energies, MDPI, vol. 12(7), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1384-:d:221529
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    References listed on IDEAS

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    Cited by:

    1. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    3. António Sérgio Faria & Tiago Soares & Tiago Sousa & Manuel A. Matos, 2020. "Participation of an EV Aggregator in the Reserve Market through Chance-Constrained Optimization," Energies, MDPI, vol. 13(16), pages 1-12, August.

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