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Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles


  • Wang, Mingshen
  • Mu, Yunfei
  • Jia, Hongjie
  • Wu, Jianzhong
  • Yu, Xiaodan
  • Qi, Yan


Considering the travelling behaviours of electric vehicles (EVs), an efficient power plant model of EVs (E-EPP) is developed for the active power regulation of the power system with large-scale wind farms. Based on the EV data base provided by the EU MERGE project, a generic V2G model (GVGM) is established. The Monte Carlo Simulation (MCS) method is implemented within the E-EPP to obtain the available response capacity of the EVs. A new active power regulation strategy based on the E-EPP is developed. A modified IEEE 118-bus system integrated with large-scale wind farms is used to verify the E-EPP model with the active power regulation strategy under different charging scenarios (dumb charging, smart charging and hybrid charging). The simulation results show that the E-EPP can improve the operating security and stability of the power system. The operation cost and the carbon emission are decreased by introducing large-scale wind farms.

Suggested Citation

  • Wang, Mingshen & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2017. "Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1673-1683.
  • Handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:1673-1683
    DOI: 10.1016/j.apenergy.2016.02.008

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    References listed on IDEAS

    1. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    2. Weis, Allison & Jaramillo, Paulina & Michalek, Jeremy, 2014. "Estimating the potential of controlled plug-in hybrid electric vehicle charging to reduce operational and capacity expansion costs for electric power systems with high wind penetration," Applied Energy, Elsevier, vol. 115(C), pages 190-204.
    3. Dupont, B. & Dietrich, K. & De Jonghe, C. & Ramos, A. & Belmans, R., 2014. "Impact of residential demand response on power system operation: A Belgian case study," Applied Energy, Elsevier, vol. 122(C), pages 1-10.
    4. Anandarajah, Gabrial & Gambhir, Ajay, 2014. "India’s CO2 emission pathways to 2050: What role can renewables play?," Applied Energy, Elsevier, vol. 131(C), pages 79-86.
    5. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    6. Brouwer, Anne Sjoerd & van den Broek, Machteld & Seebregts, Ad & Faaij, André, 2015. "Operational flexibility and economics of power plants in future low-carbon power systems," Applied Energy, Elsevier, vol. 156(C), pages 107-128.
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    Cited by:

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    6. repec:eee:appene:v:229:y:2018:i:c:p:96-110 is not listed on IDEAS
    7. repec:eee:appene:v:222:y:2018:i:c:p:608-620 is not listed on IDEAS


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