A framework for stochastic estimation of electric vehicle charging behavior for risk assessment of distribution networks

  • Salman HabibEmail author
  • Muhammad Mansoor Khan
  • Farukh Abbas
  • Muhammad Numan
  • Yaqoob Ali
  • Houjun Tang
  • Xuhui Yan
Research Article


Power systems are being transformed to enhance the sustainability. This paper contributes to the knowledge regarding the operational process of future power networks by developing a realistic and stochastic charging model of electric vehicles (EVs). Large-scale integration of EVs into residential distribution networks (RDNs) is an evolving issue of paramount significance for utility operators. Unbalanced voltages prevent effective and reliable operation of RDNs. Diversified EV loads require a stochastic approach to predict EVs charging demand, consequently, a probabilistic model is developed to account several realistic aspects comprising charging time, battery capacity, driving mileage, state-of-charge, traveling frequency, charging power, and time-of-use mechanism under peak and off-peak charging strategies. An attempt is made to examine risks associated with RDNs by applying a stochastic model of EVs charging pattern. The output of EV stochastic model obtained from Monte-Carlo simulations is utilized to evaluate the power quality parameters of RDNs. The equipment capability of RDNs must be evaluated to determine the potential overloads. Performance specifications of RDNs including voltage unbalance factor, voltage behavior, domestic transformer limits and feeder losses are assessed in context to EV charging scenarios with various charging power levels at different penetration levels. Moreover, the impact assessment of EVs on RDNs is found to majorly rely on the type and location of a power network.


electric vehicles (EVs) residential distribution networks (RDNs) voltage unbalance factor (VUF) state-of charge (SOC) time-of-use (TOU) 


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Supplementary material

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  1. 1.
    Tabari M, Yazdani A. An energy management strategy for a DC distribution system for power system integration of plug-in electric vehicles. IEEE Transactions on Smart Grid, 2016, 7(2): 659–668Google Scholar
  2. 2.
    Habib S, Khan M M, Abbas F, Sang L, Shahid M U, Tang H. A comprehensive study of implemented international standards, technical challenges, impacts and prospects for electric vehicles. IEEE Access: Practical Innovations, Open Solutions, 2018, 6: 13866–13890Google Scholar
  3. 3.
    Habib S K, Khan M M, Abbas F, Tang H. Assessment of electric vehicles concerning impacts, charging infrastructure with unidirectional and bidirectional chargers, and power flow comparisons. International Journal of Energy Research, 2018, 42(11): 3416–3441Google Scholar
  4. 4.
    Irle R. EV-volumes—the electric vehicle world sales database. 2018-11-22, available at websiteGoogle Scholar
  5. 5.
    Wu D, Aliprantis D C, Gkritza K. Electric energy and power consumption by light-duty plug-in electric vehicles. IEEE Transactions on Power Systems, 2011, 26(2): 738–746Google Scholar
  6. 6.
    Lopes J A P, Soares F J, Almeida P M R. Integration of electric vehicles in the electric power system. Proceedings of the IEEE, 2011, 99(1): 168–183Google Scholar
  7. 7.
    Clement-Nyns K, Haesen E, Driesen J. The impact of charging plugin hybrid electric vehicles on a residential distribution grid. IEEE Transactions on Power Systems, 2010, 25(1): 371–380Google Scholar
  8. 8.
    Steen D, Tuan L A, Carlson O, Bertling L. Assessment of electric vehicle charging scenarios based on demographical data. IEEE Transactions on Smart Grid, 2012, 3(3): 1457–1468Google Scholar
  9. 9.
    Deilami S, Masoum A S, Moses P S, Masoum M A S. Paper presentation—real-time coordination of plug-in electric vehicle charging in smart grids to minimize power losses and improve voltage profile. IEEE Transactions on Smart Grid, 2011, 2(3): 456–467Google Scholar
  10. 10.
    Richardson P, Flynn D, Keane A. Optimal charging of electric vehicles in low-voltage distribution systems. IEEE Transactions on Power Systems, 2012, 27(1): 268–279Google Scholar
  11. 11.
    Wang X, Karki R. Exploiting PHEV to augment power system reliability. IEEE Transactions on Smart Grid, 2017, 8(5): 2100–2108Google Scholar
  12. 12.
    Almutairi A, Bin Humayd A, Salama M M A. Quantifying the impact of PEV charging loads on the reliability performance of generation systems. In: IEEE Power & Energy Society General Meeting, Boston, MA, USA, 2016Google Scholar
  13. 13.
    Hou K, Xu X, Jia H, Yu X, Jiang T, Zhang K, Shu B. A reliability assessment approach for integrated transportation and electrical power systems incorporating electric vehicles. IEEE Transactions on Smart Grid, 2018, 9(1): 88–100Google Scholar
  14. 14.
    Falvo M C, Graditi G, Siano P. Electric vehicles integration in demand response programs. In: International Symposium on Power Electronics Electrical Drives Automation & Motion, 2014, 548–553Google Scholar
  15. 15.
    Di Silvestre M L, Riva Sanseverino E, Zizzo G, Graditi G. An optimization approach for efficient management of EV parking lots with batteries recharging facilities. Journal of Ambient Intelligence and Humanized Computing, 2013, 4(6): 641–649Google Scholar
  16. 16.
    Zhou Y, Li Z, Song Z, et al. The charging and discharging power prediction for electric vehicles. In: IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, Florence, Italy, 2016, 4014–4019Google Scholar
  17. 17.
    Di Somma M, Graditi G, Heydarian-Forushani E, Shafie-khah M, Siano P. Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects. Renewable Energy, 2018, 116: 272–287Google Scholar
  18. 18.
    Liu Z, Wang D, Jia H, Djilali N, Zhang W. Aggregation and bidirectional charging power control of plug-in hybrid electric vehicles: generation system adequacy analysis. IEEE Transaction on Renewable Energy, 2015, 6(2): 325–335Google Scholar
  19. 19.
    Li G, Zhang X P. Modeling of plug-in hybrid electric vehicle charging demand in probabilistic power flow calculations. IEEE Transactions on Smart Grid, 2012, 3(1): 492–499Google Scholar
  20. 20.
    Yang Z, Li K, Foley A. Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review. Renewable & Sustainable Energy Reviews, 2015, 51: 396–416Google Scholar
  21. 21.
    Hu J, You S, Lind M, Ostergaard J. Coordinated charging of electric vehicles for congestion prevention in the distribution grid. IEEE Transactions on Smart Grid, 2014, 5(2): 703–711Google Scholar
  22. 22.
    Hua L, Wang J, Zhou C. Adaptive electric vehicle charging coordination on distribution network. IEEE Transactions on Smart Grid, 2014, 5(6): 2666–2675Google Scholar
  23. 23.
    de Hoog J, Alpcan T, Brazil M, Thomas D A, Mareels I. Optimal charging of electric vehicles taking distribution network constraints into account. IEEE Transactions on Power Systems, 2015, 30(1): 365–375Google Scholar
  24. 24.
    Quirós-Tortós J, Ochoa L F, Alnaser S W, Butler T. Control of EV charging points for thermal and voltage management of LV networks. IEEE Transactions on Power Systems, 2016, 31(4): 3028–3039Google Scholar
  25. 25.
    Navarro-Espinosa A, Ochoa L F. Probabilistic impact assessment of low carbon technologies in LV distribution systems. IEEE Transactions on Power Systems, 2016, 31(3): 2192–2203Google Scholar
  26. 26.
    Humayd A S B, Bhattacharya K. A novel framework for evaluating maximum PEV penetration into distribution systems. IEEE Transactions on Smart Grid, 2018, 9(4): 2741–2751Google Scholar
  27. 27.
    Sachan S, Adnan N. Stochastic charging of electric vehicles in smart power distribution grids. Sustainable Cities and Society, 2018, 40: 91–100Google Scholar
  28. 28.
    Misra R, Paudyal S, Ceylan O, Mandal P. Harmonic distortion minimization in power grids with wind and electric vehicles. Energies, 2017, 10(7): 932Google Scholar
  29. 29.
    Alhazmi Y A, Salama M M A. Economical staging plan for implementing electric vehicle charging stations. Sustainable Energy, Grids and Networks, 2017, 10: 12–25Google Scholar
  30. 30.
    Sehar F, Pipattanasomporn M, Rahman S, Rahman S. Demand management to mitigate impacts of plug-in electric vehicle fast charge in buildings with renewables. Energy, 2017, 120: 642–651Google Scholar
  31. 31.
    Garcia-Villalobos J, Zamora I, Knezović K, Marinelli M. Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks. Applied Energy, 2016, 180: 155–168Google Scholar
  32. 32.
    Muratori M. Impact of uncoordinated plug-in electric vehicle charging on residential power demand. Nature Energy, 2018, 3(3): 193–201Google Scholar
  33. 33.
    National Household Travel Survey, US. NHTS datasets. 2018-06-06, available at websiteGoogle Scholar
  34. 34.
    Godina R, Rodrigues EMG, Matias J C O, Catalão J P S. Smart electric vehicle charging scheduler for overloading prevention ofan industry client power distribution transformer. Applied Energy, 2016, 178: 29–42Google Scholar
  35. 35.
    National Transmission and Despatch Company Limited (NTDC), Pakistan. PMS Load Forecast. 2018-04-23, available at websiteGoogle Scholar
  36. 36.
    DIgSILENT GmbH Germany. DIgSILENT Power System Software and Engineering. 2014, available at websiteGoogle Scholar
  37. 37.
    IEEE Power and Energy Society. IEEE PES AMPS DSAS Test Feeder Working Group. 2018-04-17, available at websiteGoogle Scholar
  38. 38.
    Penido D R R, de Araujo L R, Carneiro S, Pereira J L R, Garcia P A N. Three-phase power flow based on four-conductor current injection method for unbalanced distribution networks. IEEE Transactions on Power Systems, 2008, 23(2): 494–503Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Salman Habib
    • 1
    • 2
    Email author
  • Muhammad Mansoor Khan
    • 1
  • Farukh Abbas
    • 1
  • Muhammad Numan
    • 1
  • Yaqoob Ali
    • 1
  • Houjun Tang
    • 1
  • Xuhui Yan
    • 3
  1. 1.Key Laboratory of Control of Power Transmission and Transformation of the Ministry of Education, School of Electronic, Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Electrical EngineeringUniversity of Engineering and TechnologyLahorePakistan
  3. 3.State Grid Liyang Power Supply CompanyLiyangChina

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