Multi-objective Fuzzy-optimization of Crowbar Resistances for the Low-Voltage Ride-through of Doubly Fed Induction Wind Turbine Generation Systems

DOI QR코드

DOI QR Code

Zhang, Wenjuan;Ma, Haomiao;Zhang, Junli;Chen, Lingling;Qu, Yang

  • 투고 : 2014.11.06
  • 심사 : 2015.03.04
  • 발행 : 2015.07.31

초록

This study investigates the multi-objective fuzzy optimization of crowbar resistance for the doubly fed induction generator (DFIG) low-voltage ride-through (LVRT). By integrating the crowbar resistance of the crowbar circuit as a decision variable, a multi-objective model for crowbar resistance value optimization has been established to minimize rotor overcurrent and to simultaneously reduce the DFIG reactive power absorbed from the grid during the process of LVRT. A multi-objective genetic algorithm (MOGA) is applied to solve this optimization problem. In the proposed GA, the value of the crowbar resistance is represented by floating-point numbers in the GA population. The MOGA emphasizes the non-dominated solutions and simultaneously maintains diversity in the non-dominated solutions. A fuzzy-set-theory-based is employed to obtain the best solution. The proposed approach has been evaluated on a 3 MW DFIG LVRT. Simulation results show the effectiveness of the proposed approach for solving the crowbar resistance multi-objective optimization problem in the DFIG LVRT.

키워드

Crowbar resistance;Doubly-fed induction generator (DFIG);Genetic algorithm (GA);Low voltage ride through (LVRT);Multi-objective fuzzy optimization;Objective functions

참고문헌

  1. A. T. D. Perera, R. A. Attalage, K. K. C. .K. Perera, etal, “A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems,” Applied Energy, Vol. 107, pp. 412-425, Jul. 2013. https://doi.org/10.1016/j.apenergy.2013.02.049
  2. K. Y. Lee, A. S. Yome, and J. H. Park, “Adaptive Hopfield neural networks for economic load dispatch,” IEEE Trans. Power Syst, Vol. 13, No. 2, pp. 519-526, Feb. 1998. https://doi.org/10.1109/59.667377
  3. S. Cheng and M.-Y. Chen, “Multi-objective reactive power optimization strategy for distribution system with penetration of distributed generation,” International Journal of Electrical Power & Energy Systems, Vol. 62, pp. 221-228, Nov. 2014. https://doi.org/10.1016/j.ijepes.2014.04.040
  4. E. Khorram and H. Zarei, “Multi-objective optimization problems with Fuzzy relation equation constraints regarding max-average composition,” Mathematical and Computer Modelling, Vol. 49, No. 5-6, pp. 856-867, Mar. 2009. https://doi.org/10.1016/j.mcm.2008.10.018
  5. A. Thapara, D. Pandey, and S. K. Gaur, “Satisficing solutions of multi-objective fuzzy optimization problems using genetic algorithm,” Applied Soft Computing, Vol. 12, No. 8, pp. 2178-2187, Aug. 2012. https://doi.org/10.1016/j.asoc.2012.03.002
  6. L. Wang and C. Singh, “Balancing risk and cost in fuzzy economic dispatch including wind power penetration based on particle swarm optimization,” Electric Power Systems Research, Vol. 78, No. 8, pp. 1361-1368, Aug. 2008. https://doi.org/10.1016/j.epsr.2007.12.005
  7. Z. Honglin and Y. Geng, "Short circuit current characteristics of doubly fed induction generator with crowbar protection under different voltage dips," in Proc. the CSEE, Vol. 47, No. 2, pp. 184-191, Jan. 2009. (in Chinese)
  8. M. Mohseni, M. A. S. Masoum, and S. M. Islam, “Low and high voltage ride-through of DFIG wind turbines using hybrid current controlled converters,” Electric Power Systems Research, Vol. 81, No. 7, pp. 1456-1465, Jul. 2011. https://doi.org/10.1016/j.epsr.2011.02.010
  9. K. Vinothkumar and M. P. Selvan, “Novel scheme for enhancement of fault ride-through capability of doubly fed induction generator based wind farms,” Energy Conversion and Management, Vol. 52, No. 7, pp. 2651-2658, Jul. 2011. https://doi.org/10.1016/j.enconman.2011.01.003
  10. J. Lopez, E. Gubia, and P. Sanchis, “Wind turbines based on doubly fed induction generator under asymmetrical voltage dips,” IEEE Trans. Energy Convers., Vol. 23, No. 1, pp. 321-329, Jan. 2008. https://doi.org/10.1109/TEC.2007.914317
  11. J. Lopez, P. Sanchis, X. Roboam, and L. Marroyo, “Dynamic behavior of the doubly fed induction generator during three-phase voltage dips,” IEEE Trans. Energy Convers., Vol. 22, No. 3, pp. 9-17, Mar. 2007. https://doi.org/10.1109/TEC.2006.878241
  12. J. Morren and S. W. H. de Haan, “Short-circuit current of wind turbines with doubly fed induction generator,” IEEE Trans. Energy Convers., Vol.22, No. 1, pp. 174-180, Jan. 2007. https://doi.org/10.1109/TEC.2006.889615
  13. R. N. Banu and D. Devaraj, “Multi-objective GA with fuzzy decision making for security enhancement in power system,” Applied Soft Computing, Vol.12, No. 9, pp. 2756-2764, Sep. 2012. https://doi.org/10.1016/j.asoc.2012.03.057
  14. W. Zhang and Y. Liu, “Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm,” Electr Power Energy System, Vol. 30, No. 9, pp. 525-532, Nov. 2008. https://doi.org/10.1016/j.ijepes.2008.04.005
  15. M. Rahimi and M. Parniani, “Grid-fault ride-through analysis and control of wind turbines with doubly fed induction generators,” Electric Power Systems Research, Vol. 80, No. 2, pp. 184-195, Feb. 2010. https://doi.org/10.1016/j.epsr.2009.08.019
  16. M. Alberdi, M. Amundarain, A. Garrido, and I. Garrido, “Neural control for voltage dips ride-through of oscillating water column-based wave energy converter equipped with doubly-fed induction generator,” Renewable Energy, Vol. 48, pp. 16-26, Dec. 2012. https://doi.org/10.1016/j.renene.2012.04.014
  17. K. Vinothkumar and M. P. Selvan, “Novel scheme for enhancement of fault ride-through capability of doubly fed induction generator based wind farms,” Energy Conversion and Management, Vol. 52, No. 7, pp. 2651-2658, Jul. 2011. https://doi.org/10.1016/j.enconman.2011.01.003
  18. J. Ouyang and X. Xiong, “Research on short-circuit current of doubly fed induction generator under non-deep voltage drop,” Electric Power Systems Research, Vol. 107, pp. 158-166, Feb. 2014. https://doi.org/10.1016/j.epsr.2013.10.008
  19. J. Mohammadi, S. Afsharnia, and S. Vaez-Zadeh, “Efficient fault-ride-through control strategy of DFIG-based wind turbines during the grid faults,” Energy Conversion and Management, Vol. 78, pp. 88-95, Feb. 2014. https://doi.org/10.1016/j.enconman.2013.10.029
  20. J. Niiranen, "Voltage dip ride through of doubly-fed generator equipped with active crowbar," in the Nordic Wind Power Conference," pp. 1501-1507, 2004.
  21. J. Morren and S. W. H. Haan, “Ride-through of wind turbines with doubly-fed induction generator during a voltage dip,” IEEE Trans. Energy Convers., Vol. 47, No. 2, pp. 435-441, Feb. 2012.
  22. F. Sulla, J. Svensson, and O. Samuelsson, “Symmetrical and unsymmetrical short-circuit current of squirrel-cage and doubly-fed induction generators,” Electric Power Systems Research, Vol. 81, No.7, pp. 1610-1618, Jul. 2011. https://doi.org/10.1016/j.epsr.2011.03.016
  23. H. Li, C. Yang, Y. G. Hu, B. Zhao, M. Zhao, and Z. Chen, “Fault-tolerant control for current sensors of doubly fed induction generators based on an improved fault detection method,” Measurement, Vol. 47, No. 2, pp. 929-937, Jan. 2014. https://doi.org/10.1016/j.measurement.2013.10.021