Comparative Study of MPPT Control of Grid-Tied PV Generation by Intelligent Techniques

  • S. BeheraEmail author
  • D. Meher
  • S. Poddar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 711)


A grid-tied photovoltaic (PV) system with boost converter is considered for study here. The maximum power point tracking (MPPT) control on the duty cycle of the boost converter is achieved by intelligent techniques such as grey wolf optimization (GWO), Moth-Flame optimization (MFO) and compared with perturb and observe (P&O) method. The proposed approach of MFO reduces the ripples in power, voltage and current and imparts better efficiency under different configurations as compared to latest literature for a similar approach.


P&O MFO GWO PV Boost Grid-tied 


  1. 1.
    Salam, Z., Ahmed, J., Merugu, B.S.: The application of soft computing methods for MPPT of PV system: A technological and status review. Applied Energy, Vol. 107 (2013) 135–148.CrossRefGoogle Scholar
  2. 2.
    Elgendy, M. A., Zahawi, B., Atkinson, D. J.: Assessment of perturb and observe MPPT algorithm implementation techniques for PV pumping applications. IEEE Trans. Sustain. Energy, Vol. 3(1) (Jan. 2012) 21–31.Google Scholar
  3. 3.
    Elgendy, M. A., Zahawi, B., Atkinson, D. J.: Operating characteristics of the P&O algorithm at high perturbation frequencies for standalone PV systems. IEEE Trans. Energy Convers., Vol. 30(1) (Jun. 2015) 189–198.Google Scholar
  4. 4.
    Hsieh, G.C., Hsieh, H.I., Tsai, C.Y., Wang, C.H.: Photovoltaic power-increment-aided incremental-conductance MPPT with two-phased tracking. IEEE Transactions on Power Electronics, 28(6) (2013) 2895–2911.CrossRefGoogle Scholar
  5. 5.
    Gheibi, A., Mohammadi, S.M.A, Farsangi, M.M.: A proposed maximum power point tracking by using adaptive fuzzy logic controller for photovoltaic systems. Scientia Iranica. Transaction D, Computer Science & Engineering, Electrical, 23(3) (2016) 1272–1281.Google Scholar
  6. 6.
    Dallago, E., Liberale, A., Miotti, D., Venchi, G.: Direct MPPT algorithm for PV sources with only voltage measurements. IEEE Transactions on Power Electronics, Vol. 30(12) (2015) 6742–6750.CrossRefGoogle Scholar
  7. 7.
    Hohm, D.P., Ropp, M.E.: Comparative study of maximum power point tracking algorithms. Progress in photovoltaics: Research and Applications, Vol. 11(1) (2003) pp. 47–62.CrossRefGoogle Scholar
  8. 8.
    Ishaque, K., Salam, Z., Amjad, M., Mekhilef, S.: An improved particle swarm optimization (PSO)–based MPPT for PV with reduced steady-state oscillation. IEEE transactions on Power Electronics, Vol. 27(8) (2012) 3627–3638.CrossRefGoogle Scholar
  9. 9.
    Sundareswaran, K., Peddapati, S., Palani, S.: MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE transactions on energy conversion, 29(2) (2014) 463–472.Google Scholar
  10. 10.
    Ahmed, J., Salam, Z.: A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability. Applied Energy, Vol. 119(2014) 118–130.CrossRefGoogle Scholar
  11. 11.
    Mirjalili, S., Mirjalili, S. M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Software, Vol. 69 (2014) 46–61.CrossRefGoogle Scholar
  12. 12.
    Mohanty, S., Subudhi, B., Ray, P.K.: A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions. IEEE Transactions on Sustainable Energy, Vol. 7(1) (2016) 181–188.CrossRefGoogle Scholar
  13. 13.
    Mirjalili, S.: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, Vol. 89 (2015) 228–249.CrossRefGoogle Scholar
  14. 14.
    Villalva, M.G., Gazoli, J.R., Ruppert Filho, E.: Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Transactions on Power Electronics, Vol. 24(5) (2009) 1198–1208.CrossRefGoogle Scholar
  15. 15.
    Jantsch, M., Real, M., Häberlin, H., Whitaker, C., Kurokawa, K., Blässer. G., Kremer, P., Verhoeve, C.W.: Measurement of PV maximum power point tracking performance. Netherlands Energy Research Foundation ECN, 30 Jun 1997.Google Scholar

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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Veer Surendra Sai University of TechnologyBurlaIndia

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