Adaptive Electric Vehicle Charging Coordination on Distribution Network

被引:109
|
作者
Hua, Lunci [1 ]
Wang, Jia [1 ]
Zhou, Chi [1 ]
机构
[1] IIT, Dept Elect & Comp Engn, Chicago, IL 60616 USA
关键词
Demand coordination; distribution grid; electric vehicle (EV); optimization model; smart grid;
D O I
10.1109/TSG.2014.2336623
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Electric vehicles (EVs) with large battery charging demands may cause detrimental impact on distribution grid stability without EV charging coordination. This paper proposes an on-line adaptive EV charing scheduling (OACS) framework to optimize EV charging schedules and reduce flow limit, voltage magnitude limit, 3-phase voltage imbalance limit, and transformer capacity violations. EV user convenience is considered and EV charging cost is optimized. DC power flow based optimizations is proposed for EV charging scheduling approximation and parallel ac power flow verification is used to verify the scheduling results. Incremental feasibility improvement procedure is further proposed to correct the scheduling discrepancy between dc linear model and the ac model. Experiments are performed on a modified IEEE 34 14.7 kV distribution system with different EV penetration levels to demonstrate performance comparisons between different scheduling schemes. The result shows that our proposed OACS framework optimizes the EV charging coordination problem efficiently.
引用
收藏
页码:2666 / 2675
页数:10
相关论文
共 50 条
  • [31] Two-Stage Electric Vehicle Charging Coordination in Low Voltage Distribution Grids
    Bhattarai, Bishnu Prasad
    Bak-Jensen, Birgitte
    Pillai, Jaykrishnan R.
    Mahat, Pukar
    2014 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (IEEE PES APPEEC), 2014,
  • [32] Heterogeneous Electric Vehicle Charging Coordination: A Variable Charging Speed Approach
    Valogianni, Konstantina
    Ketter, Wolfgang
    Collins, John
    Adomavicius, Gediminas
    PROCEEDINGS OF THE 52ND ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES, 2019, : 3679 - 3688
  • [33] Optimal Online Adaptive Electric Vehicle Charging
    Guo, Linqi
    Erliksson, Karl F.
    Low, Steven H.
    2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2017,
  • [34] Consensus-Based Coordination of Electric Vehicle Charging
    Zou, Suli
    Hiskens, Ian
    Ma, Zhongjing
    Liu, Xiangdong
    IFAC PAPERSONLINE, 2017, 50 (01): : 8881 - 8887
  • [35] Two approaches for coordination of electric vehicle charging and the comparison
    Gong, X., 1600, Asian Network for Scientific Information (13):
  • [36] Coordination of Electric Vehicle Battery Charging with Photovoltaic Generation
    Tidey, H.
    Lyden, S.
    2017 AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE (AUPEC), 2017,
  • [37] Adaptive Charging Network for Electric Vehicles
    Lee, George
    Lee, Ted
    Low, Zhi
    Lowe, Steven H.
    Ortega, Christine
    2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP), 2016, : 891 - 895
  • [38] A REVIEW OF THE EFFECTS OF ELECTRIC VEHICLE CHARGING ON DISTRIBUTION NETWORK OPERATION AND POWER QUALITY
    Kutt, Lauri
    Saarijarvi, Eero
    Lehtonen, Matti
    Molder, Heigo
    Niitsoo, Jaan
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND CONTROL TECHNOLOGIES, 2013, : 162 - 167
  • [39] Impact Assessment of Residential Electric Vehicle Charging on the LV Distribution Network in Uganda
    Nambi, Ronella Faith
    Luwandaga, Shem Christopher
    Namaganda-Kiyimba, Jane
    Mulumba, Alvin Michael
    Serugunda, Jonathan
    2024 IEEE CONFERENCE ON TECHNOLOGIES FOR SUSTAINABILITY, SUSTECH, 2024, : 115 - 119
  • [40] Probabilistic Model of Electric Vehicle Charging Demand to Distribution Network Impact Analyses
    Cenky, Matej
    Bendik, Jozef
    Eleschova, Aneta
    Belan, Anton
    Cintula, Boris
    Janiga, Peter
    PROCEEDINGS OF THE 2019 20TH INTERNATIONAL SCIENTIFIC CONFERENCE ON ELECTRIC POWER ENGINEERING (EPE), 2019, : 53 - 58