Electrical Engineering

, Volume 101, Issue 4, pp 1145–1162 | Cite as

A novel intervals-based algorithm for the distribution short-circuit calculation

  • Marko Z. ObrenićEmail author
  • Predrag M. Vidović
  • Luka V. Strezoski
Original Paper


In this paper, a novel intervals-based distribution short-circuit calculation algorithm is proposed. In distribution networks, there are various renewable energy-based generators (solar panels, wind generators, small hydro turbines, etc.), as well as loads with uncertain generation and consumption. Therefore, short-circuit calculation has to consider all these uncertainties. The algorithm proposed in this paper deals with above-mentioned uncertainties, as well as correlations among them. Algorithm testing is performed on two test examples of distribution networks, 6-bus and 1003-bus, for the verification of its robustness and efficiency on real-life, large-scale systems. The results demonstrate that the proposed algorithm provides highly accurate results and that it is able to solve real-life short-circuit problems with a higher precision than the traditional deterministic short-circuit calculation algorithms.


Distribution network Short circuit Uncertainty Interval arithmetic Correlation 



This work was supported by the Ministry of Education, Science and Technological Development, Serbia and Schneider Electric DMS NS, Serbia, under the Project III-42004.


  1. 1.
    Anderson PM (1995) Analysis of faulted power systems. IEEE Press, New YorkGoogle Scholar
  2. 2.
    Bergen AR, Vittal V (2000) Power system analysis, 2nd edn. Prentice Hall, Englewood CliffsGoogle Scholar
  3. 3.
    Strezoski VC, Bekut DD (1991) A canonical model for the study of faults in power systems. IEEE Trans Power Syst 4:1493–1499. CrossRefGoogle Scholar
  4. 4.
    Jabr RA, Dzafic I (2015) A Fortescue approach for real-time short circuit computation in multiphase distribution networks. IEEE Trans Power Syst 6:3276–3285. CrossRefGoogle Scholar
  5. 5.
    Lacroix JS, Kocar I, Belletête M (2013) Accelerated computation of multiphase short circuit summary for unbalanced distribution systems using the concept of selected inversion. IEEE Trans Power Syst 2:1515–1522. CrossRefGoogle Scholar
  6. 6.
    Tu DV, Chaitusaney S, Yokoyama A (2014) Maximum-allowable distributed generation considering fault ride-through requirement and reach reduction of utility relay. IEEE Trans Power Deliv 2:534–541. CrossRefGoogle Scholar
  7. 7.
    Strezoski LV, Prica MD (2016) Real-time short-circuit analysis of active distribution systems. In: IEEE power and energy conference at Illinois (PECI), Champagne, IL.
  8. 8.
    Strezoski VC, Vidović PM (2015) Power flow for general mixed distribution networks. Int Trans Electr Energy Syst 10:2455–2471. CrossRefGoogle Scholar
  9. 9.
    Shirmohammadi D, Hong HW, Semlyen A, Luo GX (1988) A compensation-based power flow method for weakly meshed distribution and transmission networks. IEEE Trans Power Syst 2:753–762. CrossRefGoogle Scholar
  10. 10.
    Zhang X, Soudi F, Shirmohammadi D, Cheng CS (1995) A distribution short circuit analysis approach using hybrid compensation method. IEEE Trans Power Syst 4:2053–2059. CrossRefGoogle Scholar
  11. 11.
    Lin WM, Ou TC (2011) Unbalanced distribution network fault analysis with hybrid compensation. IET Gener Transm Distrib 1:92–100. CrossRefGoogle Scholar
  12. 12.
    Sulla F, Svensson J, Samuelsson O (2011) Symmetrical and unsymmetrical short-circuit current of squirrel-cage and doubly-fed induction generators. Electr Power Syst Res 7:1610–1618. CrossRefGoogle Scholar
  13. 13.
    Howard DF, Smith TM, Starke M, Harley RG (2012) Short circuit analysis of induction machines—wind power application. In: IEEE transmission and distribution conference and exposition, Orlando, FL.
  14. 14.
    Joint Working Group (2015) Fault current contribution from wind plants. IEEE Power Energy Soc. CrossRefGoogle Scholar
  15. 15.
    Gao F, Iravani MR (2008) A control strategy for a distributed generation unit in grid-connected and autonomous modes of operation. IEEE Trans Power Deliv 2:850–859. CrossRefGoogle Scholar
  16. 16.
    IEC 60909-0:2016 (2016) Short-circuit currents in three-phase a. c. systems—part 0: calculation of currentsGoogle Scholar
  17. 17.
    Strezoski LV, Prica MD, Loparo KA (2017) Generalized Δ-circuit concept for integration of distributed generators in online short-circuit calculations. IEEE Trans Power Syst 4:3237–3245. CrossRefGoogle Scholar
  18. 18.
    Zhang N, Kang C, Duan C, Tang X, Huang J, Lu Z, Wang W, Qi J (2010) Simulation methodology of multiple wind farms operation considering wind speed correlation. Int J Power Energy Syst 4:264–273. CrossRefGoogle Scholar
  19. 19.
    Zhang N, Kang C, Xu Q, Jiang C, Chen Z, Liu J (2013) Modelling and simulating the spatio-temporal correlations of clustered wind power using copula. J Electr Eng Technol 6:1615–1625. CrossRefGoogle Scholar
  20. 20.
    Maya KN, Jasmin EA (2016) Optimal integration of distributed generation (DG) resources in unbalanced distribution system considering uncertainty modelling. Int Trans Electr Energy Syst 1:e2248. CrossRefGoogle Scholar
  21. 21.
    Ruiz-Rodriguez FJ, Hernández JC, Jurado F (2017) Voltage behaviour in radial distribution systems under the uncertainties of photovoltaic systems and electric vehicle charging loads. International Transactions on Electrical Energy Systems 2:e2490. CrossRefGoogle Scholar
  22. 22.
    Carmona MC, Behnike RP, Estevez GJ (2010) Fuzzy arithmetic for the DC load flow. IEEE Trans Power Syst 1:206–214. CrossRefGoogle Scholar
  23. 23.
    Weng Z, Shi L, Xu Z, Lu Q, Yao L, Ni Y (2014) Fuzzy power flow solution considering wind power variability and uncertainty. Int Trans Electr Energy Syst 3:547–572. CrossRefGoogle Scholar
  24. 24.
    Bijwe PR, Raju GKV (2006) Fuzzy distribution power flow for weakly meshed systems. IEEE Trans Power Syst 4:1645–1652. CrossRefGoogle Scholar
  25. 25.
    Yu H, Rosehart WD (2012) An optimal power flow algorithm to achieve robust operation considering load and renewable generation uncertainties. IEEE Trans Power Syst 4:1808–1817. CrossRefGoogle Scholar
  26. 26.
    Bagheri A, Monsef H, Lesan H (2015) Evaluating the effects of renewable and nonrenewable DGs on DNEP from the reliability, uncertainty, and operational points of view by employing hybrid GA and OPF. Int Trans Electr Energy Syst 12:3304–3328. CrossRefGoogle Scholar
  27. 27.
    Wang Y, Zhang N, Chen Q, Yang J, Kang C, Huang J (2016) Dependent discrete convolution based probabilistic load flow for the active distribution system. IEEE Trans Sustain Energy 3:1000–1009. CrossRefGoogle Scholar
  28. 28.
    Vidović PM, Sarić AT (2017) A novel correlated intervals-based algorithm for distribution power flow calculation. Int J Electr Power Energy Syst 90:245–255. CrossRefGoogle Scholar
  29. 29.
    Piegat A, Landowski M (2012) Is the conventional interval arithmetic correct? J Theor Appl Comput Sci 2:27–44Google Scholar
  30. 30.
    Piegat A, Landowski M (2013) Two interpretations of multidimensional RDM interval arithmetic-multiplication and division. Int J Fuzzy Syst 4:488–496MathSciNetGoogle Scholar
  31. 31.
    Moore RE (1966) Interval analysis. Prentice-Hall, Englewood CliffszbMATHGoogle Scholar
  32. 32.
    Begović MM (2013) Electrical transmission systems and smart grids. Springer, New YorkCrossRefGoogle Scholar
  33. 33.
    Ranković A, Maksimović BM, Sarić AT, Lukič U (2014) ANN-based correlation of measurements in micro-grid state estimation. Int Trans Electr Energy Syst 10:2181–2202. CrossRefGoogle Scholar
  34. 34.
    Garcia PAN, Pereira JLR, Carneiro S Jr, da Costa VM, Martins N (2000) Three-phase power flow calculations using the current injection method. IEEE Trans Power Syst 2:508–514. CrossRefGoogle Scholar
  35. 35.
    Strezoski LV, Katic V, Dumnic B, Prica MD (2016) Short-circuit modeling of inverter based distributed generators considering the FRT requirements. In: IEEE North American power symposium (NAPS), Denver, CO, USA, Sept 18–20, 2016.
  36. 36.
    Luo GX, Semlyen A (1990) Efficient load flow for large weekly meshed networks. IEEE Trans Power Syst 4:1309–1316. CrossRefGoogle Scholar
  37. 37.
    Rodgers JL, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42:59–66. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Technical SciencesUniversity of Novi SadNovi SadSerbia
  2. 2.Faculty of Technical SciencesUniversity of Novi SadNovi SadSerbia

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