Simulation of Metaheuristic Intelligence MPPT Techniques for Solar PV Under Partial Shading Condition

  • CH Hussaian Basha
  • C. RaniEmail author
  • R. M. Brisilla
  • S. Odofin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1048)


The nonlinear characteristics of solar PV consist of different MPPs under the partial shading condition. Hence, it is difficult to find out true MPP. The conventional MPPT methods are not giving an accurate position of MPP. In this work, two global metaheuristic optimization techniques are simulated and the comparative analysis is carried out in terms of tracking speed, steady-state oscillations, algorithm complexity, periodic tuning, and dynamic response. Those are the Cuckoo Search Optimization (CSO) and Particle Swarm Optimization (PSO) MPPT methods used to extract the maximum power of solar PV under partial shading condition. The Matlab/Simulink is used to evaluate performance results of CSA and PSO MPPT techniques.


Boost converter CSO Duty cycle I-V and P-V curves Partially shaded solar PV PSO 



I would like to thank the University Grants Commission (Govt. of India) for funding my research program and I especially thank VIT University management for providing all the facilities to carry out my research work.


  1. 1.
    Ram, P.J., Sudhakar Sudhakar, T., Rajasekar, N.: A comprehensive review on solar PV maximum power point tracking techniques. Renew. Sustain. Energy Rev. 67, 826–847 (2017)CrossRefGoogle Scholar
  2. 2.
    Rezk, H., Fathy, A., Abdelaziz, A.Y.: A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions. Renew. Sustain. Energy Rev. 74, 377–386 (2017)CrossRefGoogle Scholar
  3. 3.
    Nasir, M., et al.: Solar PV-based scalable DC microgrid for rural electrification in developing regions. IEEE Trans. Sustain. Energy 9(1), 390–399 (2018)CrossRefGoogle Scholar
  4. 4.
    Capizzi, G., et al.: Optimizing the organic solar cell manufacturing process by means of AFM measurements and neural networks. Energies 11(5), 1221 (2018)CrossRefGoogle Scholar
  5. 5.
    Lee, H.K.H., et al.: Organic photovoltaic cells–promising indoor light harvesters for self-sustainable electronics. J. Mater. Chem. A 6(14), 5618–5626 (2018)CrossRefGoogle Scholar
  6. 6.
    Mathew, M., Kumar, N.M., Ponmiler i Koroth, R.: Outdoor measurement of mono and poly c-Si PV modules and array characteristics under varying load in hot-humid tropical climate. Mater. Today Proc. 5(2), 3456–3464 (2018)CrossRefGoogle Scholar
  7. 7.
    Rani, C., Hussaian Basha, C.H., Odofin, S.: Design and switching loss calculation of single leg 3-level 3-phase VSI. In: 2018 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC). IEEE (2018)Google Scholar
  8. 8.
    Segev, G., et al.: The spatial collection efficiency of charge carriers in photovoltaic and photoelectrochemical cells. Joule (2018)Google Scholar
  9. 9.
    Lloyd, J., et al.: Performance of a prototype stationary catadioptric concentrating photovoltaic module. Opt. Express 26(10), A413–A419 (2018)CrossRefGoogle Scholar
  10. 10.
    Rani, C., Hussain Basha, C.H.: A review on non-isolated inductor coupled DC–DC converter for photovoltaic grid-connected applications. Int. J. Renew. Energy Res. (IJRER) 7(4), 1570–1585 (2017)Google Scholar
  11. 11.
    Laudani, A., et al.: Irradiance intensity dependence of the lumped parameters of the three-diodes model for organic solar cells. Sol. Energy 163, 526–536 (2018)CrossRefGoogle Scholar
  12. 12.
    Rani, C., Hussaian Basha, C.H., Odofin, S.: Analysis and comparison of SEPIC, Landsman and Zeta converters for PV fed induction motor drive applications. In: 2018 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC). IEEE (2018)Google Scholar
  13. 13.
    Guichi, A., et al.: A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system. Sol. Energy 170, 974–987 (2018)CrossRefGoogle Scholar
  14. 14.
    Gallardo-Saavedra, S., Karlsson, B.: Simulation, validation and analysis of shading effects on a PV system. Sol. Energy 170, 828–839 (2018)CrossRefGoogle Scholar
  15. 15.
    Dolara, A., et al.: An evolutionary-based MPPT algorithm for photovoltaic systems under dynamic partial shading. Appl. Sci. 8(4), 558 (2018)CrossRefGoogle Scholar
  16. 16.
    Samal, S., Barik, P.K., Sahu, S.K.: Extraction of maximum power from a solar PV system using fuzzy controller based MPPT technique. In: Technologies for Smart-City Energy Security and Power (ICSESP). IEEE (2018)Google Scholar
  17. 17.
    Tey, K.S., et al.: Improved differential evolution-based MPPT algorithm using SEPIC for PV systems under partial shading conditions and load variation. IEEE Trans. Ind. Inf. (2018)Google Scholar
  18. 18.
    Dawson, F.H., Kern-Hansen, U.: Aquatic weed management in natural streams: the effect of shade by the marginal vegetation: with 4 figures and 2 tables in the text. Int. Ver. Theor. Angew. Limnol. Verh. 20(2), 1451–1456 (1978)Google Scholar
  19. 19.
    Li, G., et al.: Application of bio-inspired algorithms in maximum power point tracking for PV systems under partial shading conditions—a review. Renew. Sustain. Energy Rev. 81, 840–873 (2018)CrossRefGoogle Scholar
  20. 20.
    Soufyane Benyoucef, A., et al.: Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions. Appl. Soft Comput. 32, 38–48 (2015)CrossRefGoogle Scholar
  21. 21.
    Babu, T.S., et al.: Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions. IEEE Trans. Sustain. Energy 9(1), 74–85 (2018)CrossRefGoogle Scholar
  22. 22.
    García, J., et al.: A binary cuckoo search big data algorithm applied to large-scale crew scheduling problems. Complexity 2018 (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • CH Hussaian Basha
    • 1
  • C. Rani
    • 1
    Email author
  • R. M. Brisilla
    • 1
  • S. Odofin
    • 2
  1. 1.School of Electrical EngineeringVIT UniversityVelloreIndia
  2. 2.School of Energy and EnvironmentUniversity of DerbyDerbyUK

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