Multi-agent approach to modeling and simulation of microgrid operation with vehicle-to-grid system

被引:21
作者
Egbue O. [1 ]
Uko C. [2 ]
机构
[1] Department of Informatics and Engineering Systems, University of South Carolina Upstate, 800 University Way, Spartanburg, 29303, SC
[2] Department of Electrical Engineering, University of South Carolina, 301 Main St., Columbia, 29208, SC
来源
Egbue, Ona (egbueo@uscupstate.edu) | 1600年 / Elsevier Inc.卷 / 33期
关键词
Agent-based modeling; Microgrid; Plug-in electric vehicles; Simulation; Vehicle-to-grid;
D O I
10.1016/j.tej.2020.106714
中图分类号
学科分类号
摘要
This study presents the modeling and simulation of a vehicle-to-grid (V2G) system within a microgrid considering the requirements of various components of the microgrid system such as distributed renewable energy resources (DERs), plug-in electric vehicles (PEVs) and non-PEV loads. The system modeling is carried out using an agent-based methodology where components of the microgrid are modeled as agents. The use of PEV car batteries collectively as a virtual power plant (VPP) enables PEVs to not only act as loads but as energy sources alongside DERs such as wind and solar power generation. The smart control and scheduling of the charging and discharging of the PEVs by the charging station can be used to achieve sustainable integration of a high number of PEVs in the microgrid power system. In addition to simulating a microgrid operation, results of this study show how agents’ behavior change based on factors such as penetration of renewable energy, penetration of PEVs, travel pattern of PEV drivers and price of energy generation. © 2020
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  • [1] Aluisio B., Conserva A., Dicorato M., Forte G., Trovato M., Optimal operation planning of V2G-equipped Microgrid in the presence of EV aggregator, Electr. Power Syst. Res., 152, pp. 295-305, (2017)
  • [2] Bright Star Solar, Common Sizes of Solar Panels, (2014)
  • [3] Daina N., Polak J.W., Hazard based modelling of electric vehicles charging patterns, Paper Presented at the 2016 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), (2016)
  • [4] Deshmukh M., Deshmukh S., Modeling of hybrid renewable energy systems, Renewable Sustainable Energy Rev., 12, 1, pp. 235-249, (2008)
  • [5] Egbue O., Uko C., Agent-based modeling and simulation of microgrid operation considering plug-in electric vehicle integration (extended abstract), Paper Presented at the International Joint Conference on Industrial Engineering and Operations Management, Novi Sad, Serbia, (2019)
  • [6] EVVolumes.com, USA Plug-in Vehicle Sales for 2017 Q4 and Full Year, (2018)
  • [7] Faddel S., Aldeek A., Al-Awami A.T., Sortomme E., Al-Hamouz Z., Ancillary services bidding for uncertain bidirectional V2G using fuzzy linear programming, Energy, 160, pp. 986-995, (2018)
  • [8] Ge Y., MacKenzie D., Modeling Vehicle Choices and Charging Behavior of Plug-In Electric Vehicle Owners Jointly Using Dynamic Discrete Choice Model, (2018)
  • [9] Hintz A.S., Prasanna U.R., Rajashekara K., Hybrid multi-agent based resilient control for EV connected micro grid system, Paper Presented at the 2014 IEEE Transportation Electrification Conference and Expo (ITEC), (2014)
  • [10] Imani M.H., Yousefpour K., Ghadi M.J., Andani M.T., Simultaneous presence of wind farm and V2G in security constrained unit commitment problem considering uncertainty of wind generation, Paper Presented at the 2018 IEEE Texas Power and Energy Conference (TPEC), (2018)