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

Dapeng Chen, Zhaoxia Jing and Huijuan Tan
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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

Energies, 2019, vol. 12, issue 7, 1-19

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.

Keywords: aggregator; business model; bidding strategy; plug-in electric vehicle (PEV); stochastic optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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