3.8 Article

Three-stage electric vehicle scheduling considering stakeholders economic inconsistency and battery degradationInspec keywordsOther keywords

期刊

出版社

WILEY
DOI: 10.1049/iet-cps.2017.0015

关键词

battery powered vehicles; cyber-physical systems; Internet; power engineering computing; cost reduction; power grids; power system economics; three-stage electric vehicle scheduling; stakeholder economic inconsistency; battery degradation; power grids; cyber-physical systems; CPS; energy internet; EV aggregator operation mechanism; residential community; EV charging-discharging operation behaviour; EV aggregator revenue; EV owners; aggregator-owner economic inconsistency issue; aggregator scheduling; self-scheduling; day-ahead charging cost minimization; DA aggregator revenue maximization; real-time scheduling strategy; optimal rebate value

资金

  1. 2016 NSFC Young Scientist Programme [61603306]
  2. Xi'an Jiaotong-Liverpool University [RDF-14-01-15]

向作者/读者索取更多资源

This study proposes an electric vehicle (EV) aggregator operation mechanism in a residential community. The EV charging and discharging operation behaviours are scheduled to maximise the EV aggregator revenue, while EV aggregator provides reserve service for the grid. This study not only considers the energy and information interactions between three stakeholders: EV aggregator, EV owners, and power grids, but also the economic interests of aggregator and owners are considered. The aggregator-owner economic inconsistency issue (EV owners get higher charging cost in aggregator scheduling than self-scheduling) is presented. In order to mediate this issue, a rebate factor is proposed. In the first stage, the objective is to minimise the day-ahead (DA) charging cost of EV owners. Then the second stage is to maximise DA aggregator revenue with different rebate values. Finally, in the third stage, a real-time scheduling strategy is proposed to maximise aggregator revenue using the optimal rebate value. In addition, the battery degradation in influencing scheduling is formulated. Scheduling results show the effectiveness of the proposed strategy, e.g. economic inconsistency of different parties can be mediated. Significant reduction of EV owners' cost from self-scheduling can be achieved while the revenue of EV aggregator is maximised under the proposed strategy.

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