Skip to main content
SpringerLink
Log in

Seven-parameter PV model estimation using Differential Evolution

  • Original Paper
  • Published:
Electrical Engineering Aims and scope Submit manuscript

Abstract

The electrical characteristics of PV panel can be represented by an equivalent electric circuit model. Major challenge lies in the accurate estimation of PV model parameters. In this study, a new and efficient approach is proposed to estimate the seven-parameter PV electric circuit model. Estimation process is converted to an optimization problem where differential evolution is employed to identify the model parameters using only the data provided by the manufacturer. The effectiveness of the proposed method is assessed by estimating the parameters of six PV panels of different technologies. These are mono-crystalline, poly-crystalline and thin film. The identified parameters are confirmed by comparing the modeled I–V curves with the experimental curves. In addition, comparison of well-known five-parameter and the estimated seven-parameter models is also carried out. The results show that the estimated seven-parameter model can simulate the output characteristics of PV panel more accurately.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Hossain MJ, Saha TK, Mithulananthan N, Pota HR (2012) Robust control strategy for PV system integration in distribution systems. Appl Energy 99:355–362

    Article  Google Scholar 

  2. Orioli Aldo, Di Gangi Alessandra (2014) Review of the energy and economic parameters involved in the effectiveness of grid-connected PV systems installed in multi-storey buildings. Appl Energy 113:955–969

    Article  Google Scholar 

  3. Xueqian Fu, Chen Haoyong, Cai Runqing, Yang Ping (2015) Optimal allocation and adaptive VAR control of PV-DG in distribution networks. Appl Energy 136:173–182

    Google Scholar 

  4. Sheraz M, Abido MA (2013) An efficient fuzzy logic based maximum power point tracking controller for photovoltaic systems key words. In: International conference on renewable energies and power quality (ICREPQ’13), no. 11, p 6

  5. Benavides ND, Chapman PL (2008) Modeling the effect of voltage ripple on the power output of photovoltaic modules. IEEE Trans Ind Electron 55(7):2638–2643

    Article  Google Scholar 

  6. Tan YT, Kirschen DS, Jenkins N (2004) A model of PV generation suitable for stability analysis. IEEE Trans Energy Convers 19(4):748–755

    Article  Google Scholar 

  7. Dunford WG, Capel A (2004) A novel modeling method for photovoltaic cells. In: 2004 IEEE 35th annual power electronics specialists conference, pp 1950–1956

  8. Dougal RA (2002) Dynamic multiphysics model for solar array. IEEE Trans Energy Convers 17(2):285–294

    Article  Google Scholar 

  9. Illanes Rafael, De Francisco Adolfo, Nunez Francisco, De Blas Marian, Garcia Almudena, Torres Jose Luis (2014) Dynamic simulation and modelling of stand-alone PV systems by using state equations and numerical integration methods. Appl Energy 135:440–449

    Article  Google Scholar 

  10. Attivissimo F, Di Nisio A, Savino M, Spadavecchia M (2012) Uncertainty analysis in photovoltaic cell parameter estimation. IEEE Trans Inst Meas 61(5):1334–1342

    Article  Google Scholar 

  11. Pongratananukul N, Kaspafis T (2004) Tool for automated simulation of solar arrays using general-purpose simulators. In: IEEE workshop on computers in power electronics, pp 10–14

  12. Celik A, Acikgoz N (2007) Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models. Appl Energy 84:1–15

    Article  Google Scholar 

  13. Chan DSH, Phang JCH (1987) Analytical methods for the extraction of solar-cell single- and double-diode model parameters from I–V characteristics. IEEE Trans Electron Devices 34(2):286–293

    Article  Google Scholar 

  14. Chatterjee A, Keyhani A, Kapoor D (2011) Identification of photovoltaic source models. IEEE Trans Energy Convers 26(3):883–889

    Article  Google Scholar 

  15. Ishaque K, Salam Z, Taheri H (2011) Simple, fast and accurate two-diode model for photovoltaic modules. Sol Energy Mater Sol Cells 95(2):586–594

    Article  Google Scholar 

  16. Siddiqui MU, Abido MA (2013) Parameter estimation for five- and seven-parameter photovoltaic electrical models using evolutionary algorithms. Appl Soft Comput 13(12):4608–4621

    Article  Google Scholar 

  17. Mahmoud YA, Xiao W, Zeineldin HH (2013) A parameterization approach for enhancing PV model accuracy. IEEE Trans Ind Electron 60(12):5708–5716

    Article  Google Scholar 

  18. Hejri M, Mokhtari H, Azizian MR, Ghandhari M, Soder L (2014) On the parameter extraction of a five-parameter double-diode model of photovoltaic cells and modules. IEEE J Photovolt 4(3):915–923

    Article  Google Scholar 

  19. Kim W, Choi W (2010) A novel parameter extraction method for the one-diode solar cell model. Sol Energy 84(6):1008–1019

    Article  Google Scholar 

  20. Zagrouba M, Sellami A, Bouaïcha M, Ksouri M (2010) Identification of PV solar cells and modules parameters using the genetic algorithms: application to maximum power extraction. Sol Energy 84(5):860–866

    Article  Google Scholar 

  21. Villalva MG, Gazoli JR, Filho ER (2009) Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Trans Power Electron 24(5):1198–1208

    Article  Google Scholar 

  22. Chenni R, Makhlouf M, Kerbache T, Bouzid a (2007) A detailed modeling method for photovoltaic cells. Energy 32(9):1724–1730

    Article  Google Scholar 

  23. Kuo Y, Liang T, Chen J (2001) Novel maximum-power-point-tracking controller for photovoltaic energy conversion system. IEEE Trans Ind Electron 48(3):594–601

    Article  Google Scholar 

  24. Boyd MT, Klein Sa, Reindl DT, Dougherty BP (2011) Evaluation and validation of equivalent circuit photovoltaic solar cell performance models. J SolEnergy Eng 133(2):021005

    Google Scholar 

  25. Elhagry MT, Elkousy AAT, Saleh MB, Elshatter TF, Abou-Elzahab EM (2000) Fuzzy modeling of photovoltaic panel equivalent circuit. In: Proceedings of 40th midwest symposium on circuits and systems. Dedicated to the memory of Professor Mac Van Valkenburg, vol 1, pp 60–63

  26. Almonacid F, Rus C, Hontoria L, Fuentes M, Nofuentes G (2009) Characterisation of Si-crystalline PV modules by artificial neural networks. Renew Energy 34(4):941–949

    Article  Google Scholar 

  27. Ikegami T, Maezono T, Nakanishi F, Yamagata Y, Ebihara K (2001) Estimation of equivalent circuit parameters of PV module and its application to optimal operation of PV system. Sol Energy Mater Sol Cells 67(1–4):389–395

    Article  Google Scholar 

  28. Moldovan N, Picos R, Garcia-Moreno E (2009) Parameter extraction of a solar cell compact model usign genetic algorithms. Span Conf Electron Devices 2009:379–382

    Google Scholar 

  29. Soon JJ, Low K-S (2012) Photovoltaic model identification using particle swarm optimization with inverse barrier constraint. IEEE Trans Power Electron 27(9):3975–3983

    Article  Google Scholar 

  30. Ye M, Wang X, Xu Y (2009) Parameter extraction of solar cells using particle swarm optimization. J Appl Phys 105(9):094502

    Article  Google Scholar 

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

    Article  Google Scholar 

  32. Ishaque K, Salam Z, Mekhilef S, Shamsudin A (2012) Parameter extraction of solar photovoltaic modules using penalty-based differential evolution. Appl Energy 99:297–308

    Article  Google Scholar 

  33. González-Longatt F (2005) Model of photovoltaic module in matlab. In: II CIBELEC, pp 1–5

  34. California Energy Commission Guidelines (2013) Guidelines for California’s solar electric incentive programs (Senate Bill 1), 5th edn. California Energy Commission, CEC-300-2012-008-ED5-CMF

  35. Stutenbaeumer U, Mesfin B (1999) Equivalent model of monocrystalline, polycrystalline and amorphous silicon solar cells. Renew Energy 18(4):501–512

    Article  Google Scholar 

  36. Guimard D, Grand PP, Bodereau N, Cowache P, Guillemoles J-F, Lincot D, Taunier S, Ben Farah M, Mogensen P (2002) Copper indium diselenide solar cells prepared by electrodeposition. In: The twenty-ninth IEEE photovoltaic specialists conference, 19–24 May 2002, New Orleans, Louisiana, USA, pp 692–695

  37. King D, Kratochvil J, Boyson W (2004) Photovoltaic array performance model. Sandia report, SAND2004-3535. Sandia National Laboratories Albuquerque, New Mexico, USA

Download references

Acknowledgements

The authors would like to acknowledge the support of King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) for funding this work through project No. 14-ENE265-04 as a part of the National Science, Technology and Innovation Plan (NSTIP).

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    M. A. Abido & M. Sheraz Khalid

Authors
  1. M. A. Abido
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Sheraz Khalid
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. A. Abido.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abido, M.A., Khalid, M.S. Seven-parameter PV model estimation using Differential Evolution. Electr Eng 100, 971–981 (2018). https://doi.org/10.1007/s00202-017-0542-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00202-017-0542-2

Keywords

Search

Navigation