access icon free Total supply capability considering distribution network reconfiguration under N − k transformer contingency and the decomposition method

© The Institution of Engineering and Technology
Received 13/07/2016, Accepted 14/11/2016, Revised 19/10/2016, Published 21/12/2016

To guarantee reliability and resilience of distribution systems, total supply capability (TSC) under N − 1 security has become an important consideration in distribution system planning. In this study, TSC is expanded to cover N − k contingency, and a robust N − k TSC evaluation is proposed, while considering the effect of topology reconfiguration. In addition, the single commodity flow constraint is put forward to guarantee the topology radiality. To address this mix integer non-convex optimisation problem, the second-order cones are employed to relax the non-convex constraints so that the model can be efficiently solved, then a decomposition method is applied to solve the two-stage robust TSC model. In the case study, the proposed method is tested by a 94-bus test system and its effectiveness is validated. Numerical results show that the proposed method outperforms the traditional methods.

Inspec keywords: optimisation; power distribution planning; power distribution reliability

Other keywords: distribution network; mix integer non-convex optimisation; 94-bus test system; total supply capability; transformer; distribution system planning

Subjects: Optimisation techniques; Reliability; Distribution networks

References

    1. 1)
      • 28. Cooke, D.W.: ‘The resilience of the electric power delivery system in response to terrorism and natural disasters: summary of a workshop’ (National Research Council, 2013).
    2. 2)
      • 25. Chen, K., Wu, W., Zhang, B., et al: ‘A method to evaluate total supply capability of distribution systems considering network reconfiguration and daily load curves’, IEEE Trans. Power Syst., 2015, PP, (99), pp. 1–9.
    3. 3)
      • 34. Ding, T., Bo, R., Li, F., et al: ‘A bi-level branch and bound method for economic dispatch with disjoint prohibited zones considering network losses’, IEEE Trans. Power Syst., 2015, 30, (6), pp. 2841–2855.
    4. 4)
      • 12. Baran, M.E., Wu, F.F.: ‘Network reconfiguration in distribution systems for loss reduction and load balancing’, IEEE Trans. Power Deliv., 1989, 4, (2), pp. 1401–1407.
    5. 5)
      • 13. Civanlar, S., Grainger, J.J., Yin, H., et al: ‘Distribution feeder reconfiguration for loss reduction’, IEEE Trans. Power Deliv., 1988, 3, (3), pp. 1217–1223.
    6. 6)
      • 33. Ding, T., Sun, K., Bie, Z., et al: ‘Mixed integer linear programming based splitting strategies for power system islanding operation considering network connectivity’, IEEE Syst. J., 2015, PP, (99), pp. 1–10.
    7. 7)
      • 24. Xiao, J., Zu, G., He, Q., et al: ‘Influence mechanism of feeder links on total supply capability for distribution networks’, Autom. Electr. Power Syst., 2015, 52, (8), pp. 38–44.
    8. 8)
      • 14. Enacheanu, B., Raison, B., Caire, R., et al: ‘Radial network reconfiguration using genetic algorithm based on the Matroid theory’, IEEE Trans. Power Syst., 2008, 23, (1), pp. 186–195.
    9. 9)
      • 6. Liu, H., Han, J., Ge, S., et al: ‘Improved analytical method of power supply capability on distribution systems’, Int. J. Electr. Power Energy Syst., 2014, 63, (1), pp. 97–104.
    10. 10)
      • 7. Ge, S., Han, J., Liu, H., et al: ‘Power supply capability determination considering constraints of transformer overloading and tie-line capacity’, Proc. CSEE, 2011, 31, (25), pp. 97–103.
    11. 11)
      • 36. Hu, X., Murgovski, N., Johannesson, L.M., et al: ‘Optimal dimensioning and power management of a fuel cell/battery hybrid bus via convex programming’, IEEE/ASME Trans. Mechatronics, 2015, 20, (1), pp. 457–468.
    12. 12)
      • 32. Ding, T., Sun, H., Sun, K., et al: ‘Graph theory based splitting strategies for power system islanding operation’. Power & Energy Society General Meeting, 2015, 2015, pp. 1–5.
    13. 13)
      • 18. Srinivasa Rao, R., Narasimham, S.V.L., Ramalinga Raju, M., et al: ‘Optimal network reconfiguration of large-scale distribution system using harmony search algorithm’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 1080–1088.
    14. 14)
      • 40. Ding, T., Zhao, C.: ‘Robust optimal transmission switching with the consideration of corrective actions for N−k contingencies’, IET. Gener. Transm. Distrib., 2016, 10, (13), pp. 3288–3295.
    15. 15)
      • 20. Lee, C., Liu, C., Mehrotra, S., et al: ‘Robust distribution network reconfiguration’, IEEE Trans. Smart Grid, 2015, 6, (2), pp. 836–842.
    16. 16)
      • 17. Hu, G., Bie, Z.: ‘Dynamic adjustment strategy for distribution network reconfiguration’, J. Xi'an Jiaotong Univ., 2012, 46, (12), pp. 78–84.
    17. 17)
      • 11. Schmidt, H.P., Ida, N., Kagan, N., et al: ‘Fast reconfiguration of distribution systems considering loss minimization’, IEEE Trans. Power Syst., 2005, 20, (3), pp. 1311–1319.
    18. 18)
      • 37. Hu, X., Johannesson, L., Murgovski, N., et al: ‘Longevity-conscious dimensioning and power management of the hybrid energy storage system in a fuel cell hybrid electric bus’, Appl. Energy, 2015, 137, (1), pp. 913–924.
    19. 19)
      • 4. Xiao, J., Li, X., Gu, W., et al: ‘Model of distribution system total supply capability considering feeder and substation transformer contingencies’, Int. J. Electr. Power Energy Syst., 2015, 65, (1), pp. 419–424.
    20. 20)
      • 30. Shirmohammadi, D., Hong, H.W.: ‘Reconfiguration of electric distribution networks for resistive line losses reduction’, IEEE Trans. Power Deliv., 1989, 4, (2), pp. 1492–1498.
    21. 21)
      • 5. Luo, F., Wang, C., Xiao, J., et al: ‘Rapid evaluation method for power supply capability of urban distribution system based on N−1 contingency analysis of main-transformers’, Int. J. Electr. Power Energy Syst., 2010, 32, (10), pp. 1063–1068.
    22. 22)
      • 2. Liu, C.C.: ‘Distribution systems: reliable but not resilient? [In My View]’, IEEE Power Energy Mag., 2015, 13, (3), pp. 93–96.
    23. 23)
      • 26. Wang, Y., Chen, C., Wang, J., et al: ‘Research on resilience of power systems under natural disasters; a review’, IEEE Trans. Power Syst., 2015, 31, (2), pp. 1–10.
    24. 24)
      • 29. Farivar, M., Low, S.H.: ‘Branch flow model: relaxations and convexification’. Decision and Control (CDC), 2012 IEEE 51st Annual Conf. on, 2012, pp. 3672–3679.
    25. 25)
      • 1. Zeng, B., Zhang, J., Yang, X., et al: ‘Integrated planning for transition to low-carbon distribution system with renewable energy generation and demand response’, IEEE Trans. Power Syst., 2014, 29, (3), pp. 1153–1165.
    26. 26)
      • 9. Xiao, J., Liu, S., Li, Z., et al: ‘Model of total supply capability for distribution network based on power flow calculation’, Proc. CSEE, 2014, 34, (31), pp. 5516–5524.
    27. 27)
      • 31. Li, J., Ma, X., Liu, C., et al: ‘Distribution system restoration with microgrids using spanning tree search’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 3021–3029.
    28. 28)
      • 10. Gomes, F.V.: ‘A new distribution system reconfiguration approach using optimum power flow and sensitivity analysis for loss reduction’, IEEE Trans. Power Syst., 2006, 4, (21), pp. 1616–1623.
    29. 29)
      • 21. Franco, J.F., Rider, M.J., Lavorato, M., et al: ‘A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation’, Electr. Power Syst. Res., 2013, 97, (1), pp. 51–60.
    30. 30)
      • 19. Jabr, R., Singh, R., Pal, B.C.: ‘Minimum loss network reconfiguration using mixed-integer convex programming’, IEEE Trans. Power Syst., 2012, 2, (27), pp. 1106–1115.
    31. 31)
      • 27. Bie, Z., Lin, Y., Qiu, A.: ‘Concept and research prospects of power system resilience’, Autom. Electr. Power Syst., 2015, 22, pp. 1–9.
    32. 32)
      • 38. Zeng, B., An, Y.: ‘Solving bilevel mixed integer program by reformulations and decomposition’, http://www.optimization-online.org/DB_FILE/2014/07/4455.pdf, accessed 27 January 2014.
    33. 33)
      • 8. Wang, Z., Wu, S., Liu, W., et al: ‘Total supply capability for city distribution systems based on the probability load growth’. IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 2014, pp. 354–359.
    34. 34)
      • 23. Jin, X., Mu, Y., Jia, H., et al: ‘An active reconfiguration strategy for distribution network based on maximum power supply capability’, Trans. China Electrotechnical Soci., 2014, 29, (12), pp. 137–146.
    35. 35)
      • 15. Zhu, J.Z.: ‘Optimal reconfiguration of electrical distribution network using the refined genetic algorithm’, Electr. Power Syst. Res., 2002, 62, (1), pp. 37–42.
    36. 36)
      • 3. Xiao, J., Li, F., Gu, W.Z., et al: ‘Total supply capability and its extended indices for distribution systems: definition, model calculation and applications’, IET. Gener. Transm. Distrib., 2011, 5, (8), pp. 869–876.
    37. 37)
      • 39. Ding, T., Liu, S., Yuan, W., et al: ‘A two-stage robust reactive power optimization considering uncertain wind power integration in active distribution networks’, IEEE Trans. Sustain. Energy, 2016, 7, (1), pp. 301–311.
    38. 38)
      • 16. Parada, V., Ferland, J.A., Arias, M., et al: ‘Optimization of electrical distribution feeders using simulated annealing’, IEEE Trans. Power Deliv., 2004, 3, (19), pp. 1135–1141.
    39. 39)
      • 22. Khodr, H.M., Martinez-Crespo, J., Matos, M.A., et al: ‘Distribution systems reconfiguration based on OPF using Benders decomposition’, IEEE Trans. Power Deliv., 2009, 24, (4), pp. 2166–2176.
    40. 40)
      • 35. Ibaraki, T.: ‘Theoretical comparisons of search strategies in branch-and-bound algorithms’, Int. J. Comput. Inf. Sci., 1976, 5, (4), pp. 315–344.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2016.1071
Loading

Related content

content/journals/10.1049/iet-gtd.2016.1071
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading