Enhancement of voltage stability margin in radial distribution system with squirrel cage induction generator based distributed generators

Enhancement of voltage stability margin in radial distribution system with squirrel cage induction generator based distributed generators

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This study investigates the effect of voltage profile and steady-state voltage stability margin when a wind-driven squirrel cage induction generator (SCIG)-based distributed generator (DG) is integrated with radial distribution system (RDS). The study has been carried out considering different configurations of SCIG. The node at which a DG has to be installed is identified based on voltage collapse index (VCI), which is a measure of steady-state voltage stability margin. The computational procedure for studying the voltage profile of RDS without and with DG has been developed. The developed algorithm has been tested on the 33-bus RDS with 1 MW SCIG integrated at the identified node and results are furnished. Finally, a configuration of SCIG having star and delta switching arrangements with permanently connected capacitor across each phase winding of the stator is found to be superior in providing improved system performance over a wide range of wind velocity. A switching criterion for this type of DG is proposed based on VCI for the improved performance of RDS.


    1. 1)
      • 1. Pipattanasomporn, M., Willingham, M., Rahman, S.: ‘Implications of on-site distributed generation for commercial/industrial facilities’, IEEE Trans. Power Syst., 2005, 20, (1), pp. 206212 (doi: 10.1109/TPWRS.2004.841233).
    2. 2)
      • 2. Fahrioglu, M., Yong, T., Lasseter, R.H., Alvarado, F.L.: ‘Integrating distributed generation technology into demand management schemes’,, 2001.
    3. 3)
      • 3. Pipattanasomporn, M., Rahman, S.: ‘Intelligent distributed autonomous power systems (IDAPS) and their impact on critical electrical loads’. IEEE Int. Workshop on Critical Infrastructure Protection, Darmstadt, Germany, November 2005, pp. 34.
    4. 4)
      • 4. Ochoa, L.F., Padilha-Feltrin, A., Harrison, G.P.: ‘Time series based maximization of distributed wind power generation integration’, IEEE Trans. Energy Convers., 2008, 23, (3), pp. 968974 (doi: 10.1109/TEC.2007.914180).
    5. 5)
      • 5. Rau, N.S., Wan, Y.H.: ‘Optimum location of resources in distributed planning’, IEEE Trans. Power Syst., 1994, 9, (4), pp. 20142020 (doi: 10.1109/59.331463).
    6. 6)
      • 6. Nara, K., Hayashi, Y., Ikeda, K., Ashizawa, T.: ‘Application of Tabu search to optimal placement of distributed generators’. IEEE PES Winter Meeting, 2001, pp. 918923.
    7. 7)
      • 7. Hemadani Golshan, M.E., Arefifar, S.A.: ‘Distributed generation, reactive sources and network-configuration planning for power and energy-loss reduction’, IEE Proc., Gener. Transm. Distrib., 2006, 153, (2), pp. 127136 (doi: 10.1049/ip-gtd:20050170).
    8. 8)
      • 8. Singh, D., Singh, D., Verma, K.S.: ‘Multiobjective optimization for DG planning with load models’, IEEE Trans. Power Syst., 2009, 24, (1), pp. 427436 (doi: 10.1109/TPWRS.2008.2009483).
    9. 9)
      • 9. Harrison, G.P., Piccolo, A., Siano, P., Robin Wallace, A.: ‘Distributed generation capacity evaluation using combined genetic algorithm and OPF’, Int. J. Emerging Electr. Power Syst., 2007, 8, (2), pp. 113.
    10. 10)
      • 10. Borges, C.L.T., Falcao, D.M.: ‘Optimal distributed generation allocation for reliability, losses, and voltage improvement’, Electr. Power Energy Syst., 2006, 28, pp. 413420. (doi: 10.1016/j.ijepes.2006.02.003).
    11. 11)
      • 11. Grady, S.A., Hussaini, M.Y., Abdullah, M.M.: ‘Placement of wind turbines using genetic algorithms’, Renew. Energy, 2005, 30, pp. 259270 (doi: 10.1016/j.renene.2004.05.007).
    12. 12)
      • 12. Celli, G., Ghiani, E., Mocci, S., Pilo, F.: ‘A multiobjective evolutionary algorithm for the sizing and siting of distributed generation’, IEEE Trans. Power Syst., 2005, 20, (2), pp. 750757. (doi: 10.1109/TPWRS.2005.846219).
    13. 13)
      • 13. Carpinelli, G., Celli, G., Mocci, S., Pilo, F., Russo, A.: ‘Optimisation of embedded generation sizing and siting by using a double trade-off method’, IEE Proc. Gener. Transm. Distrib., 2005, 152, (4), pp. 503513 (doi: 10.1049/ip-gtd:20045129).
    14. 14)
      • 14. Popovic, D.H., Greatbanks, J.A., Begovic, M., Pregelj, A.: ‘Placement of distributed generators and reclosers for distribution network security and reliability’, Electr. Power Energy Syst., 2005, 27, pp. 398408. (doi: 10.1016/j.ijepes.2005.02.002).
    15. 15)
      • 15. Vinoth Kumar, K., Selvan, M.P.: ‘Capacity evaluation and identification of grid integration points of distributed generation in distribution system’, Aust. J. Electr. Electron. Eng., 2011, 8, (2), pp. 137153.
    16. 16)
      • 16. Vinothkumar, K., Selvan, M.P.: ‘Fuzzy embedded genetic algorithm method for distributed generation planning’, Electr. Power Compon. Syst., 2011, 39, (4), pp. 346366. (doi: 10.1080/15325008.2010.528533).
    17. 17)
      • 17. Vinothkumar, K., Selvan, M.P.: ‘Distributed generation planning – a new approach based on goal programming’, Electr. Power Compon. Syst., 2012, 40, (5), pp. 497512. (doi: 10.1080/15325008.2011.647238).
    18. 18)
      • 18. Hedayati, H., Nabaviniaki, S.A., Akbarimajd, A.: ‘A method for placement of DG units in distribution networks’, IEEE Trans. Power Deliv., 2008, 23, (3), pp. 16201627. (doi: 10.1109/TPWRD.2007.916106).
    19. 19)
      • 19. Vinothkumar, K.: ‘Investigations on distributed generation planning and certain grid interaction issues of wind turbine generation system’. PhD thesis, National Institute of Technology, Tiruchirappalli, April 2011.
    20. 20)
      • 20. Selvan, M.P., Shanti Swarup, K.: ‘Distribution system load flow using object oriented methodology’. Int. Conf. Power System Technology, (POWERCON 2004), Singapore, 21st–24th November 2004, pp. 11681173.
    21. 21)
      • 21. Divya, K.C., Nagendra Rao, P.S.: ‘Models for wind turbine generating systems and their application in load flow studies’, Electr. Power Syst. Res., 2006, 76, pp. 844856 (doi: 10.1016/j.epsr.2005.10.012).
    22. 22)
      • 22. Kumaresan, N., Subbiah, M.: ‘Innovative reactive power saving in wind-driven grid-connected induction generators using a delta–star stator winding; part I’, Wind Eng., 2003, 27, (3), pp. 107120 (doi: 10.1260/03095240360698555).
    23. 23)
      • 23. Kumaresan, N., Subbiah, M.: ‘Innovative reactive power saving in wind-driven grid-connected induction generators using a delta–star stator winding; part II. Estimation of annual Wh and VARh of the delta–star generator and comparison with alternative schemes’, Wind Eng., 2003, 27, (3), pp. 195204 (doi: 10.1260/030952403769016672).
    24. 24)
      • 24. Raja, P., Kumaresan, N., Subbiah, M.: ‘Grid-connected induction generators using delta–star switching of the stator winding with a permanently connected capacitor’, Wind Eng., 2012, 36, (2), pp. 219231 (doi: 10.1260/0309-524X.36.2.219).
    25. 25)
      • 25. Kundur, P.: ‘Power system stability and control’, (EPRI, Power Systems Engineering series, McGraw-hill, New York, 1994).
    26. 26)
      • 26. Huang, G.M., Zhao, L.Measurement based voltage stability monitoring of power system’, (
    27. 27)
      • 27. Donnelly, M.K., Dagle, J.E., Trudnowski, D.J., Rogers, G.J.: ‘Impacts of distributed utility on transmission system stability’, IEEE Trans. Power Syst., 1996, 11, (2), pp. 741746 (doi: 10.1109/59.496148).
    28. 28)
      • 28. Guttromson, R.T.: ‘Modeling distributed energy resource dynamics on the transmission system’, IEEE Trans. Power Syst., 2002, 17, (4), pp. 11481153 (doi: 10.1109/TPWRS.2002.804957).
    29. 29)
      • 29. Reza, M., Slootweg, J.G., Schavemaker, P.H., Kling, W.L., Van der Sluis, L.: ‘Investigating impacts of distributed generation on transmission system stability’. IEEE PowerTech Conf., Bologna, Vol. 2, 23–26 June 2003.
    30. 30)
      • 30. CIGRE TF 38.01.10.: ‘Modeling new forms of generation and storage’, November2000.
    31. 31)
      • 31. Thong, V.V., Van Dommelen, D., Driesen, J., Belmans, R.: ‘Impact of large scale distributed and unpredictable generation on voltage and angle stability of transmission system’. 40th CIGRE Conf., article C6–205, Paris, France, August 29–September 3, 2004.
    32. 32)
      • 32. Lubosny, Z.: ‘Wind turbine operation in electric power systems’, (Springer-Verlag, Berlin Heidelberg, New York, 2003, 1st edn.).

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