Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation. (September 2019)

• Record Type: Journal Article
• Authors: Zheng, Yanchong; Niu, Songyan; Shang, Yitong; Shao, Ziyun; Jian, Linni
• Is Part Of: Renewable & sustainable energy reviews. Volume 112(2019)
• Page Start: 424
• Page End: 439
• Publication Date: 2019-09
• Subjects: Coordinated charging/discharging -- Electric vehicle -- Power grid -- Smart grid -- Vehicle-to-grid; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2019.05.059
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: The vehicle-to-grid (V2G) technology is an effective and economic solution to enable the integration of electric vehicles (EVs) into power grids. As an effort to present the state of the art in relevant fields, the power interaction mode between EVs and power grids, and the scheduling methodology for the V2G implementation are overviewed comprehensively in this paper. To be specific, technical requirements, grid impacts and battery degradations regarding each power interaction mode are discussed; the operating processes of centralized and decentralized scheduling approaches are introduced and compared. More importantly, it is noted that few attentions are given to the solving algorithms of programming models used for optimizing the scheduling strategy of EVs and few works examine their feasibilities to acquire the optimal charging strategies especially for a large number of EVs. In this context, this paper also illuminates the mathematical foundation on optimization techniques for the optimal V2G strategy, and provides new insights for evaluating these models. Highlights: A review in the aspect of the EV-grid integration is made including power interaction mode and mainstream scheduling method. Mathematical foundation on optimization techniques for the V2G strategy is given. New insights are provided to make an overall evaluation on the existing methods.