A two-stage electric vehicles scheduling strategy to address economic inconsistency issues of stakeholders

Bing Han, Shaofeng Lu, Fei Xue, Lin Jiang, Huaiying Zhu

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

6 Citations (Scopus)

Abstract

As a promising mobility tool in future transportation systems, Electric Vehicle (EV) has environment-friendly benefits compared with traditional internal-combustion-engine vehicle. However, uncoordinated charging of mass EVs bring huge burden to power grids. To tackle this problem, a coordinated charging strategy of EVs is necessary. EV aggregator could play as a coordinator between EV owner and power grids, both meeting owner driving requirements and power grids operation requirements. However, a owner-Aggregator economic inconsistency issue appears, that is EV owner get a higher charging cost in aggregator scheduling than self scheduling. In order to mediate owner-Aggregator economic inconsistency issue, this paper designed a centralized two-stage EVs charging/discharging scheduling strategy in a residential community within 24 hours from the viewpoint of two stakeholders: EV owners (to minimize each EV owner charging cost) and aggregator (to maximize aggregator revenue). In the first-stage, EVs operation are scheduled from EV owners viewpoint, to obtain the minimal charging cost for each EV owner. Then, in the second-stage, the scheduling results in the first-stage are involved as constraints. The objective in the second-stage is to maximize aggregator revenue, without sacrificing each EV owner's economic benefit (no charging cost increment). A rebate factor is introduced in this model, which is the pay back for each EV owner provided by aggregator. Case study shows the effectiveness of the proposed scheduling strategy: The aggregator revenue is maximized without sacrificing each EV owner's economic benefit so that owner-Aggregator economic inconsistency issue is mediated. The impact parameter of rebate factor in aggregator revenue in analyzed.

Original languageEnglish
Title of host publicationIV 2017 - 28th IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1904-1909
Number of pages6
ISBN (Electronic)9781509048045
DOIs
Publication statusPublished - 28 Jul 2017
Event28th IEEE Intelligent Vehicles Symposium, IV 2017 - Redondo Beach, United States
Duration: 11 Jun 201714 Jun 2017

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Conference

Conference28th IEEE Intelligent Vehicles Symposium, IV 2017
Country/TerritoryUnited States
CityRedondo Beach
Period11/06/1714/06/17

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