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Improved Global Maximum Power Point Tracking for Photovoltaic System via Cuckoo Search under Partial Shaded Conditions
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  • Journal title : Journal of Power Electronics
  • Volume 16, Issue 1,  2016, pp.287-296
  • Publisher : The Korean Institute of Power Electronics
  • DOI : 10.6113/JPE.2016.16.1.287
 Title & Authors
Improved Global Maximum Power Point Tracking for Photovoltaic System via Cuckoo Search under Partial Shaded Conditions
Shi, Ji-Ying; Xue, Fei; Qin, Zi-Jian; Zhang, Wen; Ling, Le-Tao; Yang, Ting;
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Conventional maximum power point tracking (MPPT) methods are ineffective under partially shaded conditions because multiple local maximum can be exhibited on power-voltage characteristic curve. This study proposes an improved cuckoo search (ICS) MPPT method after investigating the cuckoo search (CS) algorithm applied in solving multiple MPPT. The algorithm eliminates the random step in the original CS algorithm, and the conception of low-power, high-power, normal and marked zones are introduced. The adaptive step adjustment is also realized according to the different stages of the nest position. This algorithm adopts the large step in low-power and marked zones to reduce search time, and a small step in high-power zone is used to improve search accuracy. Finally, simulation and experiment results indicate that the promoted ICS algorithm can immediately and accurately track the global maximum under partially shaded conditions, and the array output efficiency can be improved.
Improved cuckoo search;Maximum power point tracking;Multiple local maximum;Partially shaded conditions;Photovoltaic array;
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D.-Y. Jung, Y.-H. Ji, S.-H. Park, and Y.-C. Jung, “Interleaved soft-switching boost converter for photovoltaic power-generation system,” IEEE Trans. Power Electron., Vol. 26, No. 4, pp. 1137-1145, Apr. 2011. crossref(new window)

T. Esram and P.L. Chapman, “Comparison of photovoltaic array maximum power point tracking techniques,” IEEE Trans. Energy Convers., Vol. 22, No. 2, pp. 439–449, Jun. 2007. crossref(new window)

J.-H. Lee, J.-S. Lee, and K.-B. Lee, “Current Sensorless MPPT Control Method for Dual-Mode PV Module-Type Interleaved Flyback Inverters,” Journal of Power Electronics, Vol. 15, No. 1 pp. 54-64, Jan. 2015. crossref(new window)

E. M. Ahmed and M. Shoyama, “Variable Step Size Maximum Power Point Tracker Using a Single Variable for Stand-alone Battery Storage PV Systems,” Journal of Power Electronics, Vol. 11, No. 2, pp. 218-227, Mar. 2011 crossref(new window)

J.-Y. Choi, I. Choy, S.-H. Song, J. An, D.-H. Lee, and J.-W. Kim, “A Study of an Implementable Sun Tracking Algorithm for Portable Systems,” Journal of Power Electronics, Vol. 13, No. 6, pp.1051-1057, Nov. 2013. crossref(new window)

N. Fernia, G. Petrone, G. Spagnuolo, and M. Vitelli, “Optimization of perturb and observe maximum power point tracking method,” IEEE Trans. Power Electron., Vol. 20, No. 4, pp. 963-973, Jul. 2005. crossref(new window)

L. Piegari and R. Rizzo, “Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking,” IET Renewable Power Generation, Vol. 4, No. 4, pp. 317-328, Jul. 2010. crossref(new window)

N. Fermia, D. Granozio, G. Petrone, and M. Vitelli, “Predictive & adaptive MPPT perturb and observe method,” IEEE Trans. Aerosp. Electron. Syst., Vol. 43, No. 3, pp. 934-950, Jul. 2007. crossref(new window)

A. K. Abdelsalam, A. M. Massoud, S. Ahmed, and P. Enjeti, “High-performance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids,” IEEE Trans. Power Electron., Vol. 26, No. 4, pp. 1010-1021, Apr. 2011. crossref(new window)

J. Li and H. Wang, "A novel stand-alone PV generation system based on variable step size INC MPPT and SVPWM control," in IEEE 6th International Power Electronics and Motion Control Conference, pp. 2155-2160, May 2009.

A. Safari and S. Mekhilef, “Simulation and hardware implementation of incremental conductance MPPT with direct control method using Cuk converter,” IEEE Trans. Ind. Electron., Vol. 58, No. 4, pp.1154-1161, Apr. 2011. crossref(new window)

B. N. Alajmi, K. H. Ahmed, S. J. Finney, and B. W. Williams, “Fuzzy-logic-control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system,” IEEE Trans. Power Electron., Vol. 26, No. 4, pp. 1022–1030, Apr. 2011. crossref(new window)

W. Xiao and W. G. Dunford, "A modified adaptive hill climbing MPPT method for photovoltaic power systems," in IEEE 35th Annual Power Electronics Specialists Conference(PESC), Vol. 3, pp. 1957-1963, Jun. 2004.

Q. Fu and N. Tong, "A new fuzzy control method based on PSO for Maximum Power Point Tracking of photovoltaic system," in 2011 International Conference on Computer Science and Network Technology(ICCSNT), Vol. 3, pp. 1487-1491, Dec. 2011.

I. S. Kim, “Sliding mode controller for the single-phase grid-connected photovoltaic system,” Applied Energy, Vol. 83, No. 10, pp. 1101-1115, Oct. 2006. crossref(new window)

N. D. Kaushika and N. K. Gautam, "Mismatch losses and time t failure of solar PV arrays," in Proc. International Solar Energy Society Meeting, pp. 1681-1686, 2001.

T. Shimizu, M. Hirakata, T. Kamezawa, and H. Watanabe, “Generation control circuit for photovoltaic modules,” IEEE Trans. Power Electron., Vol. 16, No. 3, pp. 293-300, May 2001. crossref(new window)

T. Mishima and T. Ohnishi, "A power compensation strategy based on electric double layer capacitors for a partially shaded PV array," in the Fifth International Conference on Power Electronics and Drive Systems(PEDS), Vol. 2, pp. 858-863, Nov. 2003.

K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An improved Particle Swarm Optimization (PSO)–based MPPT for PV with reduced steady-state oscillation,” IEEE Trans. Power Electron., Vol. 27, No. 8, pp. 3627-3638, Aug. 2012. crossref(new window)

Y.-H. Liu, S.-C. Huang, J.-W. Huang, and W.-C. Liang, “A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions,” IEEE Trans. Energy Convers., Vol. 27, No. 4, pp. 1027-1035, Dec.2012. crossref(new window)

K. Ishaque and Z. Salam, “A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition,” IEEE Trans. Ind. Electron., Vol. 60, No. 8, pp. 3195-3206, Aug. 2013.

P. Kofinas, A. I. Dounis, G. Papadakis, and M. N. Assimakopoulos, “An Intelligent MPPT Controller based on Direct Neural Control for Partially Shaded PV System,” Energy and Buildings, Vol. 90, No. 1, pp. 51-64, Mar. 2015. crossref(new window)

K. Sundareswaran, P. Sankar, P. S. R. Nayak, and S. P. Simon, “Enhanced Energy Output from a PV System under Partial Shaded Conditions Through Artificial Bee Colony,” IEEE Trans. Sustain. Energy, Vol. 6, No. 1, pp. 198-209, Jan. 2015. crossref(new window)

K. Sundareswaran, S. Peddapati, and S. Palani, “MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies,” IEEE Trans. Energy Convers., Vol. 29, No. 2, pp. 463-472, Jun. 2014. crossref(new window)

Y. M. Safarudin, A. Priyadi, M. H. Purnomo, and M. Pujiantara, "Maximum power point tracking algorithm for photovoltaic system under partial shaded condition by means updating β firefly technique," in 6th International Conference on Information Technology and Electrical Engineering(ICITEE), pp. 1-5, Oct. 2014.

J. Ahmed and Z. Salam, “A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability,” Applied Energy, Vol. 119, No. 15, pp. 118-130, Apr. 2014. crossref(new window)

R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proceedings of the sixth international symposium on micro machine and human science, pp. 39-43. 1995.

X.-S. Yang and S. Deb, “Engineering optimization by cuckoo search”, International Journal of Mathematical Modelling and Numerical Optimization, Vol. 1, No. 4, pp.330-343, Oct.2010. crossref(new window)

X.-S. Yang and S. Deb, "Cuckoo search via Lévy flights," in World Congress on Nature & Biologically Inspired Computing(NaBIC), pp. 210-214, Dec. 2009.

B. Zeng, J. Zhang, Y. Zhang, X. Yang, J. Dong, and W. Liu, “Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm,” Journal of Electrical Engineering & Technology, Vol. 9, No. 2, pp. 433-440, Sep. 2014. crossref(new window)

J. Piechocki, D. Ambroziak, A. Palkowski A, and G. Redlarski, “Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms,” Applied Energy, Vol. 114, No. 2, pp.901-908, Feb. 2014. crossref(new window)

S. Berrazouane and K. Mohammedi, “Parameter optimization via cuckoo optimization algorithm of fuzzy controller for energy management of a hybrid power system,” Energy Conversion & Management, Vol. 78, No. 1, pp.652–660. Feb. 2014. crossref(new window)

C. Mishra, S. P. Singh, and J. Rokadia, “Optimal power flow in the presence of wind power using modified cuckoo search,” IET Generation, Transmission & Distribution, Vol. 9, No. 7, pp.615-626, Apr. 2015. crossref(new window)