access icon free Global maximum power point tracking of PV arrays under partial shading conditions using a modified particle velocity-based PSO technique

Modern PV arrays are generally designed with bypass diodes to avoid damage. However, such arrays exhibit multiple peaks in their PV characteristics under partial shading conditions. Owing to the limitation in the abilities of conventional maximum power point tracking algorithms in such cases, the application of other optimisation algorithms has been explored. This study proposes a modified particle velocity-based particle swarm optimisation (MPV-PSO) algorithm for tracking the global power peak of the multiple peak PV characteristics. The MPV-PSO algorithm is both adaptive and deterministic in nature. It eliminates the inherent randomness in the conventional PSO algorithm by excluding the use of random numbers in the velocity equation. The proposed algorithm also eliminates the need for tuning the weight factor, the cognitive and social acceleration coefficients by introducing adaptive values for them which adjust themselves based on the particle position. These adaptive values also solve problems like oscillations about the global best position during steady-state operation and particles getting trapped in local minima. The effectiveness of the proposed MPV-PSO algorithm is validated through MATLAB/Simulink simulations and hardware experiments.

Inspec keywords: particle swarm optimisation; maximum power point trackers; photovoltaic power systems

Other keywords: multiple peak P-V characteristics; global maximum power point tracking algorithm; partial shading condition; PV array; bypass diode; cognitive acceleration coefficient; optimisation algorithms; social acceleration coefficient; modified particle velocity-based particle swarm optimisation technique; MATLAB-Simulink simulation; MPV-PSO algorithm

Subjects: DC-DC power convertors; Optimisation techniques; Solar power stations and photovoltaic power systems

References

    1. 1)
      • 9. Syafaruddin Karatepe, E., Hiyama, T.: ‘Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions’, IET Renew. Power Gener., 2009, 3, (2), pp. 239253.
    2. 2)
      • 8. Patel, H., Agarwal, V.: ‘Maximum power point tracking scheme for PV systems operating under partially shaded conditions’, IEEE Trans. Ind. Electron., 2008, 55, (4), pp. 16891698.
    3. 3)
      • 6. Jain, S., Agarwal, V.: ‘Comparison of the performance of maximum power point tracking schemes applied to single-stage grid-connected photovoltaic systems’, IET Electr. Power Appl., 2007, 1, (5), pp. 753762.
    4. 4)
      • 1. Esram, T., Chapman, P.L.: ‘Comparison of photovoltaic array maximum power point tracking techniques’, IEEE Trans. Energy Convers., 2007, 22, (2), pp. 439449.
    5. 5)
      • 20. Villalva, M.G., de Siqueira, T.G., Ruppert, E.: ‘Voltage regulation of photovoltaic arrays: small-signal analysis and control design’, IET Power Electron., 2010, 3, (6), pp. 869880.
    6. 6)
      • 12. Kobayashi, K., Takano, I., Sawada, Y.: ‘A study on a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions’. Proc. IEEE Power Eng. Soc. General Meeting, July 2003, pp. 26122617.
    7. 7)
      • 2. Houssamo, I., Locment, F., Sechilariu, M.: ‘Maximum power tracking for photovoltaic power system: development and experimental comparison of two algorithms’, IET Renew. Energy, 2010, 35, pp. 23812387.
    8. 8)
      • 15. Jhang, J.H., Tian, I.S.: ‘A maximum power point tracking method based on perturb-and-observe combined with particle swarm optimization’, IEEE J. Photovolt., 2014, 4, (2), pp. 626633.
    9. 9)
      • 11. Nguyen, T.L., Low, K.S.: ‘A global maximum power point tracking scheme employing DIRECT search algorithm for photovoltaic systems’, IEEE Trans. Ind. Electron., 2010, 57, (10), pp. 34563467.
    10. 10)
      • 4. Mohd Zainuri, M.A.A., Mohd Radzi, M.A., Soh, A.C., et al: ‘Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc-dc converter’, IET Renew. Power Gener., 2014, 8, (2), pp. 183194.
    11. 11)
      • 3. Faraji, R., Rouholamini, A., Naji, H.R., et al: ‘FPGA-based real time incremental conductance maximum power point tracking controller for photovoltaic systems’, IET Power Electron., 2014, 7, (5), pp. 12941304.
    12. 12)
      • 16. Ishaque, K., Salam, Z.: ‘A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition’, IEEE Trans. Ind. Electron., 2012, 60, (8), pp. 31953206.
    13. 13)
      • 13. Boztepe, M., Guinjoan, F., Velasco-Quesada, G., et al: ‘Global MPPT scheme for photovoltaic string inverters based on restricted voltage window search algorithm’, IEEE Trans. Ind. Electron., 2014, 61, (7), pp. 33023312.
    14. 14)
      • 14. Ishaque, K., Salam, Z., Amjad, M., et al: ‘An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation’, IEEE Trans. Power Electron., 2012, 27, (8), pp. 36273638.
    15. 15)
      • 18. Clerc, M., Kennedy, J.: ‘The particle swarm – explosion, stability, and convergence in a multidimensional complex space’, IEEE Trans. Evol. Comput., 2002, 6, (1), pp. 5873.
    16. 16)
      • 10. Koutroulis, E., Blaabjerg, F.: ‘A new technique for tracking the global maximum power point of PV arrays operating under partial-shading conditions’, IEEE J. Photovolt., 2012, 2, (2), pp. 184190.
    17. 17)
      • 5. Andrejasic, T., Jankovec, M., Topic, M.: ‘Comparison of direct maximum power point tracking algorithms using EN 50530 dynamic test procedure’, IET Renew. Power Gener., 2011, 5, (4), pp. 281286.
    18. 18)
      • 19. Kollimalla, S.K., Mishra, M.K.: ‘Variable perturbation size adaptive P&O MPPT algorithm for sudden changes in irradiance’, IEEE Trans. Sustain. Energy, 2014, 5, (3), pp. 718728.
    19. 19)
      • 7. Tafticht, T., Agbossou, K., Doumbia, E.L., et al: ‘An improved maximum power point tracking method for photovoltaic systems’, IET Renew. Energy, 2008, 33, pp. 15081516.
    20. 20)
      • 17. Liu, Y.H., Huang, S.C., Huang, J.W., et al: ‘A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions’, IEEE Trans. Energy Convers., 2012, 27, (4), pp. 10271035.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2016.0838
Loading

Related content

content/journals/10.1049/iet-rpg.2016.0838
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading