xiaoou liu

Dr. xiaoou liu

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 March 2020 in IEEE Access
Verified
Journal Article
Open access
XLxiaoou liu
xiaoou liu
In view of the existing problems that multiple vehicles interaction in the selection of fast charging stations for electric vehicles (EVs) and the equalizing the service capability by multiple stations game in station-EVs interaction, a dynamic response strategy of fast charging station-EVs considering interaction of multiple vehicles is proposed. According to this, the charging scheme of EVs and the dynamic service fee of charging stations are decided. Firstly, the charging guidance framework of station-EVs interaction is proposed to describe the information flow relationship for vehicle, station, road and intelligent transportation system (ITS). Secondly, in order to meet the diversified needs of car owners in charging selection, a charging navigation model is established. Considering the impact of dynamic path travel time, a dynamic path selection model of urban road network is established based on the road segment transmission model. Thirdly, in order to accurately analyze the interaction process between vehicles, a charging decision-making method is proposed considering the dynamic evolution of EVs, which reflects the station selection probability of different positions during driving. Fourthly, according to the queuing time of the charging station, the service fee of the charging station is dynamically adjusted to optimize the service capacity of the charging station, and the multi-agent stackelberg game model is established by combining the charging station selection of EVs with the dynamic service fee of charging station. Finally, Sioux Falls urban road network system is used as an example to analyze the path selection, dynamic decision of charging station selection and service fee, and station-EVs interaction strategy. The results show that this method improves the efficiency of electric vehicle charging station searching, guides EVs in the road network to charge orderly, balances the charging load between charging stations and optimizes the service capacit...

28 June 2023 in Electric Power Systems Research
Verified
Journal Article
Closed access
JPJun Pan
Jun Pan
XLxiaoou liu
xiaoou liu
JHJingjing Huang
Jingjing Huang

10 June 2020 in IEEE Access
Verified
Journal Article
Open access
XLxiaoou liu
xiaoou liu
High penetration of renewable energy brings economic and environmental benefits to the grid, but also causes challenges to the distribution system flexibility due to its uncertainty. As a new variable load, electric vehicles (EVs) can increase system's flexibility through interactions with the grid and promote the consumption of renewable energy. This paper studies the flexibility evaluation of distribution system considering the interaction between EVs and the grid. Firstly, the charging and discharging control strategies of EVs have been analyzed to reduce the impact of renewable energy output fluctuations on the distribution system flexibility, such as the G2V (Grid to vehicle) and V2G (Vehicle to grid) modes. Secondly, the battery capacity, driving plan, and transportation network are modeled to study the impact of the EVs connected to the grid on the distribution system flexibility. Thirdly, the flexibility evaluation method of distribution network is proposed based on the feasibility analysis of uncertain region. Finally, the analyses of the example show that the proposed method can realize the evaluation of the time series flexibility of the distribution system, which proves the effectiveness of the method proposed in this paper.