Modeling of Plug-in Hybrid Electric Vehicle Charging Demand in Probabilistic Power Flow Calculations

被引:325
|
作者
Li, Gan [1 ]
Zhang, Xiao-Ping [1 ]
机构
[1] Univ Birmingham, Sch Elect Elect & Comp Engn, Birmingham B15 2TT, W Midlands, England
关键词
Charging demand model; Cornish-Fisher expansion; cumulant method; plug-in hybrid electric vehicle; point estimate method; probabilistic power flow;
D O I
10.1109/TSG.2011.2172643
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
Millions of electric vehicles (EVs), especially plug-in hybrid EVs (PHEVs), will be integrated into the power grid in the near future. Due to their large quantity and complex charging behavior, the impact of substantial PHEVs charging on the power grid needs to be investigated. Since the charging behavior of PHEVs in a certain regional transmission network or a local distribution network is determined by different uncertain factors, their overall charging demand tends to be uncertain and in this situation probabilistic power flow (PPF) can be applied to analyze the impact of PHEVs charging on the power grid. However, currently there is no suitable model of the overall charging demand of PHEVs available for PPF calculations. In this paper, a methodology of modeling the overall charging demand of PHEVs is proposed. The proposed methodology establishes a single PHEV charging demand model, and then employs queuing theory to describe the behavior of multiple PHEVs. Moreover, two applications are given, i.e., modeling the overall charging demand of PHEVs at an EV charging station and in a local residential community, respectively. Comparison between PPF calculations and Monte Carlo simulation are made on a modified IEEE 30-bus system integrated with the two demand models proposed.
引用
收藏
页码:492 / 499
页数:8
相关论文
共 50 条
  • [31] Transient modeling of an integrated charger for a plug-in hybrid electric vehicle
    Zhao, Shuang
    Haghbin, Saeid
    Wallmark, Oskar
    Leksell, Mats
    Lundmark, Sonja
    Carlson, Ola
    PROCEEDINGS OF THE 2011-14TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE 2011), 2011,
  • [32] Hybrid Swarm Intelligence-Based Optimization for Charging Plug-in Hybrid Electric Vehicle
    Rahman, Imran
    Vasant, Pandian
    Singh, Balbir Singh Mahinder
    Abdullah-Al-Wadud, M.
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT II, 2015, 9012 : 22 - 30
  • [33] Microgrid operational energy management with plug-in hybrid electric vehicles charging demand
    Chakraborty, Amit
    Ray, Saheli
    ELECTRICAL ENGINEERING, 2024, 106 (03) : 2245 - 2263
  • [34] A New Model of Charging Demand Related to Plug-in Hybrid Electric Vehicles Aggregation
    Pouladi, Jaber
    Sharifian, Mohammad Bagher Bannae
    Soleymani, Soodabeh
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2017, 45 (09) : 964 - 979
  • [35] Scheduling for Charging Plug-in Hybrid Electric Vehicles
    Xu, Yunjian
    Pan, Feng
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 2495 - 2501
  • [36] A Bidirectional Power Charging Control Strategy for Plug-in Hybrid Electric Vehicles
    Mohammadi, Fazel
    Nazri, Gholam-Abbas
    Saif, Mehrdad
    SUSTAINABILITY, 2019, 11 (16)
  • [37] OR Forum-Modeling the Impacts of Electricity Tariffs on Plug-In Hybrid Electric Vehicle Charging, Costs, and Emissions
    Sioshansi, Ramteen
    OPERATIONS RESEARCH, 2012, 60 (03) : 506 - 516
  • [38] Stochastic Modeling of Plug-in Electric Vehicle Distribution in Power Systems
    Son, Hyeok Jin
    Kook, Kyung Soo
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2013, 8 (06) : 1276 - 1282
  • [39] A flexible distributed framework for realising electric and plug-in hybrid vehicle charging policies
    Stuedli, S.
    Crisostomi, E.
    Middleton, R.
    Shorten, R.
    INTERNATIONAL JOURNAL OF CONTROL, 2012, 85 (08) : 1130 - 1145
  • [40] An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems
    Li, Cheng
    Ding, Tao
    Liu, Xiyuan
    Huang, Can
    IEEE ACCESS, 2018, 6 : 27569 - 27578