Matching theory based travel plan aware charging algorithms in V2G smart grid networks

Ming Zeng, Supeng Leng (Lead / Corresponding author), Jianhua He, Yan Zhang, Guanhua Qiao

    Research output: Chapter in Book/Report/Conference proceedingChapter

    5 Citations (Scopus)
    154 Downloads (Pure)


    The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.
    Original languageEnglish
    Title of host publication2016 IEEE/CIC International Conference on Communications in China, ICCC 2016
    Number of pages6
    ISBN (Electronic)9781509021437
    ISBN (Print)9781509021444
    Publication statusPublished - 24 Oct 2016


    • on-line scheduling
    • stable matching
    • traveling plan aware
    • vehicle-to-grid
    • Computer Networks and Communications
    • Signal Processing


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