Multi-Objective Optimization of EV Charging and Discharging for Different Stakeholders

Shaofeng Lu, Bing Han*, Fei Xue, Lin Jiang, Kejun Qian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


As a dynamic energy storage system, electric vehicles (EV) play important roles in future power grids. In this paper, a model for EV aggregator participation in the electricity market has been built with a focus on the feasibility issue of the model arising from economic interest inconsistencies between different stakeholders: EV owners and aggregator. In the model, the EV aggregator attends day-ahead energy and reserve markets for profit maximization by scheduling charging and discharging behaviors of EVs. This issue exists since different stakeholders have different interests which are not necessarily consistent, e.g. profit maximization leads to increasing EV owners' charging fee. To investigate the economic relationship between the two stakeholders, two multi-objective optimization methods (weighted sum and Ε-constraint methods) are proposed to take the aggregator profit and EV owners' charging fee into account in the model. A sensitivity analysis is applied to examine the aggregator profit under different price scenarios, which reveals the internal relationship between EV owners' charging fees and aggregator profit. The proposed EV charging and discharging strategy in this paper could be used to determine the settlement price between the aggregator and owners to ensure the feasibility of participation from both EV owners and stakeholders in electricity markets.

Original languageEnglish
Pages (from-to)2301-2308
Number of pages8
JournalCSEE Journal of Power and Energy Systems
Issue number6
Publication statusPublished - 1 Nov 2023


  • Aggregator
  • EV
  • EV owners
  • economic inconsistency issue
  • electricity market
  • multi-objective optimization


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