DOI QR코드

DOI QR Code

Harmonic Elimination in Three-Phase Voltage Source Inverters by Particle Swarm Optimization

  • Azab, Mohamed (Dept. of Electrical Engineering Technology, High Institute of Technology, Benha University, Egypt. On leave to Yanbu Industrial College, EEET Department)
  • Received : 2010.01.05
  • Accepted : 2010.12.29
  • Published : 2011.05.02

Abstract

This paper presents accurate solutions for nonlinear transcendental equations of the selective harmonic elimination technique used in three-phase PWM inverters feeding the induction motor by particle swarm optimization (PSO). With the proposed approach, the required switching angles are computed efficiently to eliminate low order harmonics up to the $23^{rd}$ from the inverter voltage waveform, whereas the magnitude of the fundamental component is controlled to the desired value. A set of solutions and the evaluation of the proposed method are presented. The obtained results prove that the algorithm converges to a precise solution after several iterations. The salient contribution of the paper is the application of the particle swarm algorithm to attenuate successfully any undesired loworder harmonics from the inverter output voltage. The current paper demonstrates that the PSO is a promising approach to control the operation of a three-phase voltage source inverter with a selective harmonic elimination strategy to be applied in induction motor drives.

Keywords

References

  1. F. G. Turnbull, “Selected harmonic reduction in static dc-ac inverters,” IEEE Trans. Commun. Electron., vol. 83, pp. 374-378, 1964. https://doi.org/10.1109/TCOME.1964.6541241
  2. H. S. Patel and R. G. Hoft, “Generalized harmonic elimination and voltage control in thyristor inverters: Part I-harmonic elimination,” IEEE Trans. Ind. Appl., vol. IA-9, no. 3, pp. 310-317, May/Jun. 1973. https://doi.org/10.1109/TIA.1973.349908
  3. H. S. Patel and R. G. Hoft, “Generalized techniques of harmonic elimination and voltage control in thyristor inverters: part II-voltage control techniques,” IEEE Trans. Ind. Appl., vol. IA-10, pp. 666-673, Sep/Oct 1974. https://doi.org/10.1109/TIA.1974.349239
  4. J. R. Wells, et. al., “Modulation-Based Harmonic Elimination,” IEEE Trans. Power Electron., vol. 22, no. 1, pp. 336-340, Jan 2007. https://doi.org/10.1109/TPEL.2006.888910
  5. V. G. Agelidis, et. al., “Multiple Sets of Solutions for Harmonic Elimination PWM Bipolar Waveforms: Analysis and Experimental Verification,” IEEE Trans. Power Electron., vol. 21, no. 2, pp.415-421, March 2006. https://doi.org/10.1109/TPEL.2005.869752
  6. R. A. Jabr, “Solution trajectories of the harmonicelimination problem,” Proc. Inst. Electr. Eng.-Electric Power Applications, vol. 153, no. 1, pp. 97-104, Jan. 1, 2006. https://doi.org/10.1049/ip-epa:20050112
  7. J. N. Chiasson, et. al., “A complete solution to the harmonic elimination problem,” IEEE Trans. Power Electron., vol. 19, no. 2, pp. 491-499, Mar. 2004. https://doi.org/10.1109/TPEL.2003.823207
  8. F. Swift and A. Kamberis, “A new Walsh domain technique of harmonic elimination and voltage control in pulse-width modulated inverters,” IEEE Trans. Power Electron., vol. 8, no. 2, pp. 170-185, Apr. 1993. https://doi.org/10.1109/63.223969
  9. T.-J. Lang, et. al., “Inverter harmonic reduction using Walsh function harmonic elimination method,” IEEE Trans. Power Electron., vol. 12, no. 6, pp. 971-982, Nov. 1997. https://doi.org/10.1109/63.641495
  10. A. I. Maswood, et. al., “A Flexible Way to Generate PWM-SHE Switching Pattern using Genetic Algorithm,” IEEE Applied Power Electronics (APEC) Conf. Proc., Anaheim, California, USA, Vol. 2, 2001, pp. 1130-1134.
  11. A. Sayyah, et. al., “Optimization of THD and Suppressing Certain Order Harmonics in PWM Inverters using Genetic Algorithms,” Proc. of IEEE International Symposium on Intelligent Control, Germany, Oct. 2006, pp. 874-879.
  12. K. Sundareswaran, et. al., “Inverter Harmonic Elimination Through a Colony of Continuously Exploring Ants,” IEEE Trans. Ind. Elect., vol. 54, no. 5, pp. 2558-2565, October 2007. https://doi.org/10.1109/TIE.2007.899846
  13. Mohamed azab, “Particle Swarm Optimization-Based Solutions For Selective Harmonic Elimination In Single-Phase PWM Inverters”, International Journal of Power electronics, Vol. 2, No. 2, 2010, Inderscience Enterprises Ltd- UK.
  14. M. Dorigo, et. al., “Ant system: Optimization by a colony of cooperation agents,” IEEE Trans. Syst., Man, Cybern. B, Cybern., Vol. 26, no. 1, pp. 29-41, Feb. 1996. https://doi.org/10.1109/3477.484436
  15. M. Dorigo, et. al., “Special section on ant colony optimization,” IEEE Transactions on Evolutionary Computation, August 2002.
  16. J. Kennedy , R. Eberhart , “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks (ICNN'95), Vol. IV, pp.1942-1948, 1995.
  17. Mohamed Azab, "Global maximum power point tracking for partially shaded PV arrays using particle swarm optimization", International Journal of Renewable Energy Technology, vol. 1, no. 2, pp. 211-235, Inderscience Enterprises Ltd- UK , 2009. https://doi.org/10.1504/IJRET.2009.027991
  18. J. Hereford, M. Siebold, "Multi-robot search using a physically-embedded particle swarm optimization", International Journal of Computational Intelligence Research, Vol. 4, No. 2, pp.197–209, 2008.

Cited by

  1. Implementation of ANN-based Selective Harmonic Elimination PWM using Hybrid Genetic Algorithm-based optimization vol.85, 2016, https://doi.org/10.1016/j.measurement.2016.02.012
  2. Training HMM Structure and Parameters with Genetic Algorithm and Harmony Search Algorithm vol.7, pp.1, 2012, https://doi.org/10.5370/JEET.2012.7.1.109
  3. Transformer Parameters Estimation From Nameplate Data Using Evolutionary Programming Techniques vol.29, pp.5, 2014, https://doi.org/10.1109/TPWRD.2014.2311153
  4. Artificial bee colony algorithm for inverter complex wave reduction under line-load variations 2017, https://doi.org/10.1177/0142331216687019
  5. A Ripple Rejection Inherited RPWM for VSI Working with Fluctuating DC Link Voltage vol.10, pp.5, 2015, https://doi.org/10.5370/JEET.2015.10.5.2018
  6. Robust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods vol.35, pp.1, 2015, https://doi.org/10.1108/AA-05-2014-038
  7. A Particle Swarm Optimization Algorithm With Novel Expected Fitness Evaluation for Robust Optimization Problems vol.48, pp.2, 2012, https://doi.org/10.1109/TMAG.2011.2173753
  8. Selective elimination of harmonic contents in an uninterruptible power supply: an enhanced adaptive hybrid technique vol.5, pp.8, 2012, https://doi.org/10.1049/iet-pel.2011.0472