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access icon free Imposing voltage security and network radiality for reconfiguration of distribution systems using efficient heuristic and meta-heuristic approach

  • Author(s): Pawan Kumar 1 1 ; Ikbal Ali 2 2 ; Mini S. Thomas 3 3 ; Surjit Singh 4 4
    • View affiliations
    • Affiliations: 1: School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab 144402, India ;
      2: Electrical Engineering, Faculty of Engineering and Technology, Jamia Millia Islamia, New Delhi 110025, India ;
      3: National Institute of Technology, Tiruchirappalli, Tamil Nadu 620015, India ;
      4: Department of Computer Engineering, National Institute of Technology, Kurukshetra, Haryana 136119, India
  • Source: Volume 11, Issue 10, 13 July 2017, p. 2457 – 2467
    DOI:  10.1049/iet-gtd.2016.0935 , Print ISSN 1751-8687, Online ISSN 1751-8695
© The Institution of Engineering and Technology
Received 18/09/2016, Accepted 27/02/2017, Revised 10/02/2017, Published 24/03/2017

In a deregulated energy market, voltage security (VS) is one of the major concerns, as it improves the loadability limits, loading profiles while concurrently reducing power loss. Further, voltage dependent loads can operate at high efficiency at rated voltage. Therefore, power utilities have to explore options of reconfiguration to secure the voltage level under frequently changing operating conditions. In this study, an efficient heuristic and meta-heuristic (harmony search) approach for reconfiguration is proposed by imposing VS. Two indices namely node voltage security index (NVSI) and node voltage quality index are developed for aggregated improvement in node voltages. Moreover, efficient methodologies for identification of new tie-lines, network radiality and the load flow solution are also presented. The effectiveness of the proposed index and the methodology is tested for reconfiguration of various distribution systems and the results are obtained with reduced computational efforts.

Inspec keywords: power system security; power distribution protection; power markets; power supply quality

Other keywords: power loss reduction; node voltage security index; deregulated energy market; voltage security; metaheuristic approach; node voltage quality index; harmony search approach; heuristic approach; power utilities; network radiality; loadability limit improvement; distribution system reconfiguration

Subjects: Distribution networks; Power system management, operation and economics; Power system protection

References

    1. 1)
      • 11. Subrahmanyam, J.B.V., Radhakrishna, C.A.: ‘Simple method for feeder reconfiguration of balanced and unbalanced distribution systems for loss minimization’, Electr. Power Compon. Syst., 2010, 38, pp. 72–84.
    2. 2)
      • 14. Nara, K., Shiose, A., Kitagawoa, M., et al: ‘Implementation of genetic algorithm for distribution system loss minimum reconfiguration’, IEEE Trans. Power Syst., 1992, 7, (3), pp. 1044–1051.
    3. 3)
      • 9. Saffar, A., Hooshmand, R., Khodabakhshian, A.: ‘A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm’, Appl. Soft Comput., 2011, 11, (5), pp. 4021–4028.
    4. 4)
      • 28. Narimani, M.R., Vahed, A.A., Abarghooee, R.A., et al: ‘Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost’, IET Gener. Transm. Distrib., 2014, 8, (1), pp. 55–69.
    5. 5)
      • 1. Ali, I., Thomas, M.S., Kumar, P.: ‘Energy efficient reconfiguration for practical load combinations in distribution systems’, IET Gener. Transm. Distrib, 2015, 9, (11), pp. 1051–1060, doi: 10.1049/iet-gtd.2014.0915.
    6. 6)
      • 31. López1, J.C., Lavorato, M., Franco, J.F., et al: ‘Robust optimisation applied to the reconfiguration of distribution systems with reliability constraints’, IET Gener. Transm. Distrib., 2016, 10, (4), pp. 917–927.
    7. 7)
      • 5. Su, S.-Y., Lu, C.-N., Chang, R.-F., et al: ‘Distributed generation interconnection planning: a wind power case study’, IEEE Trans. Smart Grid, 2011, 2, (1), pp. 181–189.
    8. 8)
      • 8. Ali, I., Thomas, M.S., Kumar, P.: ‘Optimal capacitor placement in smart distribution systems to improve its maximum loadability and energy efficiency’, Int. J. Engg. Sci. Tech., 2011, 3, (8), pp. 271–284, doi: http://dx.doi.org/10.4314/ijest.v3i8.21.
    9. 9)
      • 21. Lavorato, M., Franco, J.F., Rider, M.J., et al: ‘Imposing radiality constraints in distribution system optimization problems’, IEEE Trans. Power Syst., 2012, 27, (1), pp. 172–180.
    10. 10)
      • 16. Raju, G.K.V., Bijwe, P.R.: ‘Efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization’, IET Gener. Transm. Distrib., 2008, 2, (1), pp. 7–12.
    11. 11)
      • 3. Sivanagaraju, S., Visali, N., Sankar, V., et al: ‘Enhancing voltage stability of radial distribution systems by network reconfiguration’, Electr. Power Compon. Syst. 2005, 33, (5), pp. 539–550.
    12. 12)
      • 4. Kumar, P., Singh, S.: ‘Comprehensive stability analysis of radial distribution system with load growth’. Proc. of IEEE Int. Conf. IICPE, 2014.
    13. 13)
      • 7. Aman, M.M., Jasmon, G.B., Bakar, A.H.A., et al: ‘A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses’, Energy Convers. Manage., 2013, 70, pp. 202–210.
    14. 14)
      • 10. Baran, M.E., Wu, F.F.: ‘Network reconfiguration in distribution system for loss reduction and load balancing’, IEEE Trans. Power Deliv., 1989, 4, (2), pp. 1401–1407.
    15. 15)
      • 13. Ababei, C., Kavasseri, R.: ‘Efficient network reconfiguration using minimum cost maximum flow-based branch exchanges and random walks-based loss estimations’, IEEE Trans. Power Syst., 2011, 26, (1), pp. 30–37.
    16. 16)
      • 29. Gupta, N., Swarnkar, A., Niazi, K.R.: ‘Distribution network reconfiguration for power quality and reliability improvement using genetic algorithm’, Electr. Power Energy Syst., 2014, 54, pp. 664–671.
    17. 17)
      • 15. Zhang, D., Fu, Z., Zhang, L.: ‘An improved TS algorithm for loss minimum reconfiguration in large scale distribution system’, Electr. Power Syst. Res., 2007, 77, pp. 685–694.
    18. 18)
      • 25. Andervazh, M.R., Olamaei, J., Haghifam, M.R.: ‘Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimization algorithm and graph theory’, IET Gener. Transm. Distrib., 2013, 7, (12), pp. 1367–1382.
    19. 19)
      • 27. Mendoza, J.E., López1, M.E., Coello Coello, C.A., et al: ‘Microgenetic multi-objective reconfiguration algorithm considering power losses and reliability indices for medium voltage distribution network’, IET Gener. Transm. Distrib., 2009, 3, (9), pp. 825–840.
    20. 20)
      • 34. Kumar, P., Singh, S.: ‘Reconfiguration of distribution system with static load models for loss minimization’. Proc. of IEEE Int. Conf. PEDES, 2014.
    21. 21)
      • 24. Aman, M.M., Jasmon, G.B., Bakar, A.H.A., et al: ‘Graph theory-based radial load flow analysis to solve the dynamic network reconfiguration problem’, Int. Trans. Electr. Energy Syst., 2015, doi: 10.1002/etep.2108.
    22. 22)
      • 26. Kundur, P.: ‘Power system stability and control’ (The McGraw Hill, 2009, 8th edn.), (reprint).
    23. 23)
      • 6. Singh, D., Singh, D., Verma, K.S.: ‘Multi-objective optimization for DG planning with load models’, IEEE Trans. Power Syst., 2009, 24, (1), pp. 227–236.
    24. 24)
      • 19. Farahani, V., Vahidi, B., Abyaneh, H.A.: ‘Reconfiguration and capacitor placement simultaneously for energy loss reduction based on an improved reconfiguration method’, IEEE Trans. Power Syst., 2012, 27, (2), pp. 587–595.
    25. 25)
      • 23. Das, D., Kothari, D.P., Kalam, A.: ‘Simple and efficient method for load flow solution of radial distribution system’, Electri. Power Energy Syst., 1995, 17, (5), pp. 335–346.
    26. 26)
      • 32. Khorshid-Ghazani, B., Seyedi, H., Mohammadi-ivatloo, B., et al: ‘Reconfiguration of distribution networks considering coordination of the protective devices’, IET Gener. Transm. Distrib., doi: 10.1049/iet-gtd.2016.0539, ISSN 1751–8695.
    27. 27)
      • 17. Su, C.-T., Chang, C.-F., Chiou, J.-P.: ‘Distribution network reconfiguration for loss reduction by ant colony search algorithm’, Electr. Power Syst. Res., 2005, 75, pp. 190–199.
    28. 28)
      • 30. Abbasi, F., Hosseini, S.M.: ‘Optimal DG allocation and sizing in presence of storage systems considering network configuration effects in distribution systems’, IET Gener. Transm. Distrib., 2016, 10, (3), pp. 617–624.
    29. 29)
      • 22. Oliveira, E.J.D., Rosseti, G.J., Oliveira, L.W.D., et al: ‘New algorithm for reconfiguration and operating procedures in electric distribution systems’, Electr. Power Energy Syst., 2014, 57, pp. 129–134.
    30. 30)
      • 18. Hooshmand, R., Mashhoor, E.: ‘Application of fuzzy algorithm in optimal reconfiguration of distributed networks for loss reduction and load balancing’, Eng. Int. Syst., 2006, 14, (1), pp. 15–23.
    31. 31)
      • 20. Rabih, A.J., Singh, R., Pal, B.C.: ‘Minimum loss network reconfiguration using mixed-integer convex programming’, IEEE Trans. Power Syst., 2012, 27, (2), pp. 1106–1115.
    32. 32)
      • 33. Ali, I., Thomas, M.S., Kumar, P.: ‘Effect of loading pattern on the performance of reconfigured medium size distribution system’. Proc. of fifth IEEE Power India Conf., 2012, doi: 10.1109/PowerI.2012.6479503.
    33. 33)
      • 12. Rao, R.S., Narasimham, S.V.L., Raju, M.R., et al: ‘Optimal network reconfiguration of large-scale distribution system using harmony search algorithm’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 1080–1088.
    34. 34)
      • 2. Venkatesh, B., Ranjan, R., Gooi, H.B.: ‘Optimal reconfiguration of radial distribution systems to maximize loadability’, IEEE Trans. Power Syst., 2004, 19, (1), pp. 260–266.
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