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Well-being analysis of distribution network in the presence of electric vehicles

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  • Kheradmand-Khanekehdani, Habiballah
  • Gitizadeh, Mohsen

Abstract

Environmental concerns, limitations of fossil fuels and their pollution are among the most important challenges of societies today. To overcome these challenges, the penetration rate of electric vehicles and renewable energy resources has highly increased. But the use of plug-in hybrid electric vehicles with unmanaged charging exerts a negative impact on the electric grid reliability. The current study presents a comprehensive investigation of the reliability of distribution grid based on stochastic behavior of plug-in hybrid electric vehicles and renewable energy resources. Moreover, a new method is introduced for grid well-being management in the presence of plug-in hybrid electric vehicles. The proposed method includes the managed charging and vehicle to grid scenarios and is tested through improved of Roy Billinton test system bus 2. The presented method manages the plug-in hybrid electric vehicles charging and power injection to the grid using system well-being analysis. The simulation results indicate that adequacy of distribution grid is put at risk state in the presence of plug-in hybrid electric vehicles with unmanaged charging, whereas the use of the proposed method not only does not deteriorate the system reliability but also improves well-being criteria and adequacy indices.

Suggested Citation

  • Kheradmand-Khanekehdani, Habiballah & Gitizadeh, Mohsen, 2018. "Well-being analysis of distribution network in the presence of electric vehicles," Energy, Elsevier, vol. 155(C), pages 610-619.
    • Handle: RePEc:eee:energy:v:155:y:2018:i:c:p:610-619
    DOI: 10.1016/j.energy.2018.04.164
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    References listed on IDEAS

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    1. Kavousi-Fard, Abdollah & Khodaei, Amin, 2016. "Efficient integration of plug-in electric vehicles via reconfigurable microgrids," Energy, Elsevier, vol. 111(C), pages 653-663.
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    Cited by:

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    2. Hariri, Ali-Mohammad & Hashemi-Dezaki, Hamed & A. Hejazi, Maryam, 2020. "A novel generalized analytical reliability assessment method of smart grids including renewable and non-renewable distributed generations and plug-in hybrid electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    3. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    4. Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
    5. L. Alvarado-Barrios & A. Rodríguez del Nozal & A. Tapia & J. L. Martínez-Ramos & D. G. Reina, 2019. "An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes," Energies, MDPI, vol. 12(11), pages 1-23, June.
    6. Ji, Shou-feng & Zhao, Dan & Luo, Rong-juan, 2019. "Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles," Energy, Elsevier, vol. 189(C).

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