Skip to main content
SpringerLink
Log in

Formulation and Evaluation of Firefly and Artificial Bee Colony Algorithms for Maximum Power Extraction of Photovoltaic Systems Under Partial Shade

  • Chapter
  • First Online:
Advancement of Science and Technology in Sustainable Manufacturing and Process Engineering

Part of the book series: Green Energy and Technology ((GREEN))

  • 68 Accesses

Abstract

The main aim of this research is to formulate and evaluate firefly and artificial bee colony metaheuristic algorithms to track the global maximum power point for photovoltaic (PV) system in partial shading condition. The review of related researchs group available approaches as classical and evolutionary algorithms-based techniques for the proposed application. However, the classical optimization technique-based approaches have common shortcomings of being unable to track the global maximum power point whenever partial shading and mismatching in PV panels happen, missing the correct tracking direction during fast radiation change and output oscillation during steady-state condition since they are perturbation based approaches even though they are simple and have less complexity. A number of research activities using artificial intelligence-based approaches inspired by human intelligence, swarm intelligence, and different animals’ natural intelligence have been proposed and implemented using a direct duty ratio control approach for the power electronic converter. In this research firefly and artificial bee colony-based algorithms are formulated for direct voltage control approach, implemented, and their performance is evaluated. The results revealed that the proposed approach can track the global peak accurately and reduce steady-state oscillations compared to the incremental conductance (InCod) classical approach implemented for comparison purpose.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Rekioua, D., Matagne, E.: Optimization of Photovoltaic Power Systems: Modeling, Simulation and Control. © Springer-Verlag London Limited, New York (2012)

    Google Scholar 

  2. Singh, G.K.: Solar power generation by PV technology: a review. Energy. 53, 1–13 (2013)

    Article  Google Scholar 

  3. Femian, N., Petrone, G., Spagnuolo, G., Vitelli, M.: Power Electronics and Control Techniques for Maximum Energy Harvesting in Photovoltaic Systems. Taylor & Francis Group, London (2013)

    Google Scholar 

  4. Ismail, M.S., Moghavvemi, M., Mahlia, T.M.I.: Characterization of PV panel cells and global optimization of its model parameters using genetic algorithm. Energy Convers. Manag. 73, 10–25 (2010)

    Article  Google Scholar 

  5. Ishaque, K., Salam, Z.: An improved modeling method to determine the model parameters of photovoltaic (PV) modules using differential evolution (DE). Sol. Energy. 85(9), 2349–2359 (2011)

    Article  Google Scholar 

  6. Shmilovitz, D., Levron, Y.: Distributed maximum power point tracking in photovoltaic systems – emerging architectures and control methods. ATKAFF. 53(2), 142–155 (2012). https://doi.org/10.7305/automatika.53-2.185

    Article  Google Scholar 

  7. Ahmed, J., Salam, Z.: An improved method to predict the position of maximum power point during partial shading for PV arrays. IEEE Trans. Ind. Inform. 11(6), 1378–1387 (2015)

    Article  Google Scholar 

  8. Ahmed, N.A., Miyatake, M.: A novel maximum power point tracking for photovoltaic applications under partially shaded insolation conditions. Electr. Power Syst. Res. 78(5), 777–784 (2008)

    Article  Google Scholar 

  9. Patel, H., Agarwal, V.: Maximum power point tracking scheme for PV systems operating under partially shaded conditions. IEEE Trans. Ind. Electron. 55(4), 1689–1698 (2008)

    Article  Google Scholar 

  10. Sundareswaran, K., Vigneshkumar, V., Sankar, P., Simon, S.P., Nayak, P.S.R., Palani, S.: Development of an improved P&O algorithm assisted through a colony of foraging ants for MPPT in PV system. IEEE Trans. Ind. Inform. 12(1), 187–200 (2016)

    Article  Google Scholar 

  11. Ishaque, K., Salam, Z., Amjad, M., Mekhilef, S.: An improved Particle Swarm Optimization (PSO)–based MPPT for PV with reduced steady-state oscillation. IEEE Trans. Power Electron. 27(8), 3627–3638 (2012)

    Article  Google Scholar 

  12. Lian, K.L., 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. 4, 626–633 (2014)

    Article  Google Scholar 

  13. Taheri, H., Salam, Z., Ishaque, K., Syafaruddin: A novel maximum power point tracking control of photovoltaic system under partial and rapidly fluctuating shadow conditions using differential evolution. In: Proceedings of 2010 IEEE Symposium on Industrial Electronics & Applications (ISIEA), pp. 82–87 (2010)

    Google Scholar 

  14. Esram, T., Chapman, P.L.: Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans. Energy Convers. 22(2), 439–449 (2007)

    Article  Google Scholar 

  15. Subudhi, B., Pradhan, R.: A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Trans. Sustain. Energy. 4(1), 89–98 (2013)

    Article  Google Scholar 

  16. Brito, M.A.G., Galotto, L., Sampaio, L.P., Melo, G., Canesin, C.A.: Evaluation of the main MPPT techniques for photovoltaic applications. IEEE Trans. Ind. Elect. 60(3), 1156–1167 (2013)

    Article  Google Scholar 

  17. Tofoli, F.L., de Castro Pereira, D., de Paula, W.J.: Comparative study of maximum power point tracking techniques for photovoltaic systems. Int. J. Photo Energy 10 (2015). https://doi.org/10.1155/2015/812582

  18. Tajuddin, M.F.N., Arif, M.S., Ayob, S.M., Salam, Z.: Perturbative methods for maximum power point tracking (MPPT) of photovoltaic (PV) systems: a review. Int. J. Energy Res. 39, 1153–1178 (2015). https://doi.org/10.1002/er.3289

    Article  Google Scholar 

  19. Xiao, W., Dunford, W.G.: A modified adaptive hill climbing MPPT method for photovoltaic power systems. In Proceedings of 35th Annual IEEE Power Electronics Specialists Conference, pp. 1957–1963 (2004)

    Google Scholar 

  20. Femia, N., Petrone, G., Spagnuolo, G., Vitelli, M.: Optimization of perturb and observe maximum power point tracking method. IEEE Trans. Power Electron. 20(4), 963–973 (2005)

    Article  Google Scholar 

  21. Masoum, M.A.S., Dehbonei, H., Fuchs, E.F.: Theoretical and experimental analyses of photovoltaic systems with voltage and current-based maximum power-point tracking. IEEE Trans. Energy Convers. 17(4), 514–522 (2002)

    Article  Google Scholar 

  22. Garrigos, A., Blanes, J.M., Carrascoa, J.A., Ejea, J.B.: Real time estimation of photovoltaic modules characteristics and its application to maximum power point operation. Renew. Energy. 32(6), 1059–1076 (2007)

    Article  Google Scholar 

  23. Liu, F., Duan, S., Liu, F., Liu, B., Kang, Y.: A variable step size INC MPPT method for PV systems. IEEE Trans. Ind. Electron. 55(7), 2622–2628 (2008)

    Article  Google Scholar 

  24. Kobayashi, K., Takano, I., Sawada, Y.: A study of a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions. Sol. Energy Mater. Sol. Cell. 90, 2975–2988 (2006)

    Article  Google Scholar 

  25. Miyatake, M., Inada, T., Hiratsuka, I., Hongyan, Z., Otsuka, H., Nakano, M.: Control characteristics of a fibonacci-search-based maximum power point tracker when a photovoltaic array is partially shaded. In: Proceedings of 4th International on Power Electronics and Motion Control Conference, vol. 2, pp. 816–821 (2004)

    Google Scholar 

  26. Jiang, L.L., Maskell, D.L., Patra, J.C.: A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energ. Buildings. 58, 227–236 (2013)

    Article  Google Scholar 

  27. Liu, Y., Huang, S., Huang, J., Liang, W.: A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions. IEEE Trans. Energy Convers. 27(4), 1027–1035 (2012)

    Article  Google Scholar 

  28. Ishaque, K., Salam, Z., Shamsudin, A., Amjad, M.: A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm. Appl. Energy. 99, 414–422 (2012)

    Article  Google Scholar 

  29. Sundareswaran, K., Peddapati, S., Palani, S.: MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE Trans. Energy Convers. 29(2), 463–472 (2014)

    Article  Google Scholar 

  30. Ishaque, K., Salam, Z.: A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition. IEEE Trans. Ind. Electron. 60(8), 3195–3206 (2013)

    Google Scholar 

  31. Mohanty, S., Subudhi, B., Ray, P.K.: A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions. IEEE Trans. Sustain. Energy. 7(1), 181–188 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Adama Science and Technology University, School of Electrical Engineering and Computing, Adama, Ethiopia

    Tefera T. Yetayew

  2. Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, Ethiopia

    Tigist D. Wudmatas

Authors
  1. Tefera T. Yetayew
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tigist D. Wudmatas
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Chemical and Biochemical Engineering, Western University, London, ON, Canada

    Kibret Mequanint

  2. Mechanical Engineering, Bahir Dar University, Bahir Dar, Ethiopia

    Assefa Asmare Tsegaw

  3. Chemical Engineering, Bahir Dar University, Bahir Dar, Ethiopia

    Zenamarkos Bantie Sendekie

  4. Civil and Water Resources Engineering, Bahir Dar University, Bahir Dar, Ethiopia

    Birhanu Kebede

  5. Civil and Water Resources Engineering, Bahir Dar University, Bahir Dar, Ethiopia

    Ephrem Yetbarek Gedilu

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Yetayew, T.T., Wudmatas, T.D. (2024). Formulation and Evaluation of Firefly and Artificial Bee Colony Algorithms for Maximum Power Extraction of Photovoltaic Systems Under Partial Shade. In: Mequanint, K., Tsegaw, A.A., Sendekie, Z.B., Kebede, B., Yetbarek Gedilu, E. (eds) Advancement of Science and Technology in Sustainable Manufacturing and Process Engineering. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-41173-1_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-41173-1_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41172-4

  • Online ISBN: 978-3-031-41173-1

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation