Skip to main content
SpringerLink
Log in
Book cover

Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems pp 247–281Cite as

Adaptive Fuzzy Logic Controller as MPPT Optimization Technique Applied to Grid-Connected PV Systems

  • Chapter
  • First Online:

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

Abstract

This chapter presents a complete design of maximum power point tracking control scheme applied to single-phase single-stage and two-stage grid-connected PV systems based on an adaptive fuzzy controller (AFLC). This technique is proposed to enhance the efficiency of a photovoltaic (PV) array and diminish the output power oscillations. The adaptive nature of the proposed controller provides online tuning of fuzzy rules parameters to deal with varying sun radiation and ambient temperature. Ranges of input variables of fuzzy system are defined using genetic algorithm. The adaptive MPPT controller is compared with existing setups, namely the “incremental conductance” (IC) technique and fuzzy logic controller (FLC). The inverter controller is designed in the synchronous frame so that a simplified controller such as PI-controller is implemented. Simulation and experimental results demonstrate the supremacy of the adaptive technique in terms of the speed of tracking and oscillations reduction around the maximum point of power–voltage (P–V) curve.

This is a preview of subscription content, 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   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   109.99
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

Learn about institutional subscriptions

References

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Hussein KH, Mota I, Hoshino T, Osakada M (1995) Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions. IET 142(11):59–64

    Google Scholar 

  4. Elobaid LM, Abdelsalam AK, Zakzouk EE (2015) Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey. IET Renew Power Gener 9(8):1043–1063

    Article  Google Scholar 

  5. Mathew A, Selvakumar AI (2006) New MPPT for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive network. IEEE Trans Energy Convers 21(3):793–803

    Google Scholar 

  6. Chiu C-S (2010) T-S fuzzy maximum power point tracking control of solar power generation systems. IEEE Trans Energy Convers 25(4):1123–1132

    Article  Google Scholar 

  7. Senjyu T, Uezato K (1994) Maximum power point tracker using fuzzy control for photovoltaic arrays. In: Proceedings of IEEE international conference on industrial technology, pp 143–147

    Google Scholar 

  8. Kosko B (1997) Fuzzy engineering. Prentice Hall International, New Jersey, CA

    Google Scholar 

  9. Elshafei L, El-Metwally KA, Shaltout AA (2005) A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems. Control Eng Pract 13:413–423

    Article  Google Scholar 

  10. Won C-Y, Kim D-H, Kim S-C, Kim W-S, Kim H-S (1994) A new maximum power point tracker of photovoltaic arrays using fuzzy controller. In: Proceedings of 25th annual IEEE power electronics specialists conference, pp 396–403

    Google Scholar 

  11. Simoes MG, Franceschetti NN, Friedhofer M (1998) A fuzzy logic based photovoltaic peak power tracking control. In: Proceedings of IEEE international symposium on industrial electronics, pp 300–305

    Google Scholar 

  12. Patcharaprakiti N, Premrudeepreechacharn S (2002) Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system. In: IEEE power engineering society winter meeting, pp 372–377

    Google Scholar 

  13. Refaat MM, Atia Y, Sayed MM, Abdel Fattah HA (2017) Maximum power point tracking of photovoltaic system using adaptive fuzzy controller. In: Proceedings of the 5th international conference on advanced control circuits and systems (ACCS’017), Alexandria, Egypt

    Google Scholar 

  14. Ahmed A (2010) Power conditioning for small scale hybrid PV-wind generation system. Doctor of Philosophy’s thesis. School of Engineering and Computing Sciences, 2010, Durham University, UK

    Google Scholar 

  15. Femia N, Petrone G, Spagnuolo G, Vitelli M (2013) Power electronics and control techniques for maximum energy harvesting in Photovoltaic systems. CRC Press, Boca Raton

    Google Scholar 

  16. Villalva MG, Ruppert EF, Filho ER (2009) Analysis and simulation of the P&O MPPT algorithm using a linearized PV array model. In: Proceedings of the 10th Brazilian, 2009, Bonito-Mato Grosso do Sul, Brazil

    Google Scholar 

  17. Refaat MM (2018) Maximum power point tracking for grid connected PV systems. Master of Science’s thesis, 2018, Faculty of Engineering, Cairo university, Egypt

    Google Scholar 

  18. Deb SG (2012) Optimal sizing of a stand-alone solar-wind-battery-DG/biomass hybrid power system to meet the load demand of a typical village at Sagar Island using genetic algorithm. MSc thesis, 2012, Faculty of engineering and Technology, Jadavpur University, Kolkata, Indian

    Google Scholar 

  19. Hsu L, Costa R (1994) Analysis and design of I/O based variable structure adaptive control. IEEE Trans Autom Control 39(1)

    Google Scholar 

  20. Elshafei AL (2000) Adaptive fuzzy control of nonlinear systems via a variable-structure algorithm. In: IEEE international symposium on intelligent control, Vancouver, Canada

    Google Scholar 

  21. IEEE Application Guide for IEEE Std 1547™ (2003) IEEE standard for interconnecting distributed resources with electric power systems. The published standard is available from the IEEE Std 1547-2003 web page. (IEEE standard for interconnecting distributed resources with electric power systems, IEEE Std 1547-2003, pp 0_1–16)

    Google Scholar 

  22. Yazdani A, Iravani R (2010) Voltage sourced converters in power system. Wiley, London

    Google Scholar 

  23. Silva SM, Lopes BM, Filho BJ, Campana RP (2004) Performance evaluation of PLL algorithms for single phase grid-connected systems. In: Proceedings of the IEEE industry applications conference, Seattle, WA, USA

    Google Scholar 

  24. Yongheng Y, Blaabjerg F (2012) Synchronization in single-phase grid-connected photovoltaic systems under grid faults. In: Proceedings of the 3rd international symposium on power electronics for distributed generation systems (PEDG), Aalborg, Denmark

    Google Scholar 

  25. Crowhurst B, El-Saadany EF, El-Chaar L, Lamont LA (2010) Single-phase grid-tie inverter control using DQ transform for active and reactive load power compensation. In: Proceedings of the international conference on power and energy (PECon), 29 November–1 December 2010, Kuala Lumpur, Malaysia

    Google Scholar 

  26. Guo XQ, Wu WY, Gu HR (2001) Phase locked loop and synchronization methods for grid interfaced converters: a review. Przeglad Elektrotechniczny (Electr Rev) 87(4):182–187

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Photovoltaic Cells Department, Electronics Research Institute, Cairo, Egypt

    Mohamed M. Refaat & Yousry Atia

  2. Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Giza, Egypt

    M. M. Sayed & Hossam Abdel Fattah

Authors
  1. Mohamed M. Refaat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yousry Atia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. M. Sayed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hossam Abdel Fattah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yousry Atia .

Editor information

Editors and Affiliations

  1. Sustainable Energy Technologies Center, King Saud University, Riyadh, Saudi Arabia

    Ali M. Eltamaly

  2. Electrical Power and Machines Department, Ain Shams University, Abbassia, Egypt

    Almoataz Y. Abdelaziz

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Refaat, M.M., Atia, Y., Sayed, M.M., Fattah, H.A. (2020). Adaptive Fuzzy Logic Controller as MPPT Optimization Technique Applied to Grid-Connected PV Systems. In: Eltamaly, A., Abdelaziz, A. (eds) Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-05578-3_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-05578-3_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05577-6

  • Online ISBN: 978-3-030-05578-3

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation