Skip to main content
SpringerLink
Log in

Application of Modified MPPT Algorithms: A Comparative Study between Different Types of Solar Cells

  • DIRECT CONVERSION OF SOLAR ENERGY INTO ELECTRICAL ENERGY
  • Published:
Applied Solar Energy Aims and scope Submit manuscript

Abstract

Due to the broad needs for energy as market demands, searching on how to improve the efficiency of the PV systems is an essential concern for researchers to worry about. So, it is crucial to force the PV system to work at its peak power point in order to get the maximum available power from the photovoltaic panel. This paper presents a comprehensive comparison between four Maximum Power Point Tracking (MPPT) Algorithms; Perturb and Observe (P&O), Incremental Conductance (INC), Modified Variable Step Size Perturb and Observe (M-VSS-P&O) and Modified Variable Step Size Incremental Conductance (M-VSS-INC) by using of the DC-DC boost converter for three different kinds of solar cells. These cells are polycrystalline KC200GT cell, monocrystalline shell SQ85 cell and thin film shell ST40 cell. Simulations have been performed using MATLAB-SIMULINK for the three types of solar cells to investigate their performance under both standard test conditions (STC) and slowly varying and sudden changes in solar irradiance. The study has considered the response time, output power efficiency and steady-state-oscillations. The simulation results of the modified algorithms show an improvement in the cell performance in steady state conditions, tracking time and boost converter efficiency as well as an enhancement in the dynamic response in tracking the maximum power point (MPP) in varying climatic conditions over conventional algorithms.

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.
Fig. 14.
Fig. 15.

Similar content being viewed by others

REFERENCES

  1. Bayrak, F., Ertürk, G., and Oztop, H.F., Effects of partial shading on energy and exergy efficiencies for photovoltaic panels, J. Cleaner Prod., 2017, vol. 164, pp. 58–69.

    Article  Google Scholar 

  2. Awad, A., Bazan, P., and German, R., Optimized operation of PV/T and micro-CHP hybrid power systems, Technol. Econ. Smart Grids Sustainable Energy, 2016, vol. 1, no. 2.

  3. Singh, G.K., Solar power generation by PV (photovoltaic) technology: A review, Energy, 2013, vol. 53, pp. 1–13.

    Article  Google Scholar 

  4. Hoseinzadeh, S. and Azadi, R., Simulation and optimization of a solar-assisted heating and cooling system for a house in Northern of Iran, J. Renewable Sustainable Energy, 2017, vol. 9, id. 045101.

  5. Marinic-Kragic, I., Nižetic, S., et al., Analysis of flow separation effect in the case of the free-standing photovoltaic panel exposed to various operating conditions, J. Cleaner Prod., 2018, vol. 174, pp. 53–64.

    Article  Google Scholar 

  6. Nezhad, M.E.Y. and Hoseinzadeh, S., Mathematical simulation and optimization of a solar water heater for an aviculture unit using MATLAB/SIMULINK, J. Renewable Sustainable Energy, 2017, vol. 9, id. 063702.

  7. Hoseinzadeh, S., Yargholi, R., Kariman, H. and Heyns, P.S., Exergoeconomic analysis and optimization of reverse osmosis desalination integrated with geothermal energy, Environ. Prog. Sustainable Energy, 2020, vol. 39, no. 5, id. e13405.

  8. Hoseinzadeh, S., Zakeri, M.H., Shirkhani, A., and Chamkha, A.J., Analysis of energy consumption improvements of a zero-energy building in a humid mountainous area, J. Renewable Sustainable Energy, 2019, vol. 11, id. 015103.

  9. Motahhir, S., El Ghzizal, A., Sebti, S., and Derouich, A., MIL and SIL and PIL tests for MPPT algorithm, Cogent Eng., 2017, vol. 4, id. 1378475.

  10. Zekry, A., Shaker, A., and Salem, M., Solar cells and arrays, in Advances in Renewable Energies and Power Technologies, Amsterdam: Elsevier, 2018, pp. 3–56.

    Google Scholar 

  11. El Hammoumi, A., Motahhir, S., Chalh, A., et al., Low-cost virtual instrumentation of PV panel characteristics using Excel and Arduino in comparison with traditional instrumentation, Renewables: Wind, Water, Sol., 2018, vol. 5, art. no. 3.

  12. Patel, H. and Agarwal, V., MATLAB-based modeling to study the effects of partial shading on PV array characteristics, IEEE Trans. Energy Convers., 2008, vol. 23, no. 1, pp. 302–310.

    Article  Google Scholar 

  13. Motahhir, S., El Ghzizal, A., Sebti, S., and Derouich, A., Proposal and implementation of a novel perturb and observe algorithm using embedded software, in 3rd International Renewable and Sustainable Energy Conference (IRSEC), 2015, pp. 1–5.

  14. Ansari, B. and Simoes, M.G., Distributed energy management of PV-storage systems for voltage rise mitigation, Technol. Econ. Smart Grids Sustainable Energy, 2017, vol. 2, no. 1, p. 15.

    Article  Google Scholar 

  15. Verma, D., Nema, S., Shandilya, A.M., and Dash, S.K., Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems, Renewable Sustainable Energy Rev., 2016, vol. 54, pp. 1018–1034.

    Article  Google Scholar 

  16. El-Khozondar, H.J., El-Khozondar, R.J., Matter, K., and Suntio, T., A review study of photovoltaic array maximum power tracking algorithms, Renewables: Wind, Water, Sol., 2016, vol. 3, art. no. 3.

  17. Gupta, A., Chauhan, Y.K., Pachauri, R.K., Yin, X., and Pickert, V., A comparative investigation of maximum power point tracking methods for solar PV system, Sol. Energy, 2016, vol. 136, pp. 236–253.

    Article  Google Scholar 

  18. Ahmed, J., A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays, in 2nd International Conference on Software Technology and Engineering (ICSTE), 2010, vol. 1, pp. V1–247.

  19. Kottas, T.L., Boutalis, Y.S., and Karlis, A.D., New maximum power point tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive networks, IEEE Trans. Energy Convers., 2006, vol. 21, no. 3, pp. 793–803.

    Article  Google Scholar 

  20. Miloudi, L., Acheli, D., and Kesraoui, M., Application of artificial neural networks for forecasting photovoltaic system parameters, Appl. Sol. Energy, 2017, vol. 53, no. 2, pp. 85–91.

    Article  Google Scholar 

  21. Sellami, A., Kandoussi, K., et al., A novel auto-scaling MPPT algorithm based on perturb and observe method for photovoltaic modules under partial shading conditions, Appl. Sol. Energy, 2018, vol. 54, no. 3, pp. 149–158.

    Article  Google Scholar 

  22. Elgendy, M.A., Zahawi, B., and Atkinson, D.J., Assessment of perturb and observe MPPT algorithm implementation techniques for PV pumping applications, IEEE Trans. Power Electron., 2012, vol. 3, no. 1, pp. 21–33.

    Google Scholar 

  23. Elgendy, M.A., Zahawi, B., and Atkinson, D.J., Assessment of the incremental conductance maximum power point tracking algorithm, IEEE Trans. Sustainable Energy, 2013, vol. 4, no. 1, pp. 108–117.

    Article  Google Scholar 

  24. Motahhir, S., El Ghzizal, A., Sebti, S., and Derouich, A., Modeling of photovoltaic system with modified incremental conductance algorithm for fast changes of irradiance, Int. J. Photoenergy, 2018, vol. 2018, pp. 1–13. https://doi.org/10.1155/2018/3286479

    Article  Google Scholar 

  25. Femia, N., Granozio, D., et al., Predictive & adaptive MPPT perturb and observe method, IEEE Trans. Aerosp. Electron. Syst., 2007, vol. 43, no. 3, pp. 934–950.

    Article  Google Scholar 

  26. Piegari, L. and Rizzo, R., Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking, IET Renewable Power Gener., 2010, vol. 4, no. 4, pp. 317–328.

    Article  Google Scholar 

  27. Elbaset, A.A., Ali, H., Sattar, M., and Khaled, M., Implementation of a modified perturb and observe maximum power point tracking algorithm for photovoltaic system using an embedded microcontroller, IET Renewable Power Gener., 2016, vol. 10, no. 4, pp. 1–10.

    Article  Google Scholar 

  28. Motahhir, S., El Ghzizal, A., Sebti, S., and Derouich, A., Shading effect to energy withdrawn from the photovoltaic panel and implementation of DMPPT using C language, Int. Rev. Autom. Control (IREACO), 2016, vol. 9, no. 2, pp. 88–94.

    Google Scholar 

  29. Ishaque, K., Salam, Z., and Lauss, G., The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions, Appl. Energy, 2014, vol. 119, pp. 228–236.

    Article  Google Scholar 

  30. Motahhir, S., Chalh, A., Ghzizal, A., Sebti, S., Derouich, A., Modeling of photovoltaic panel by using proteus, J. Eng. Sci. Technol. Rev., 2017, vol. 10, no. 2, pp. 8–13. https://doi.org/10.1155/2018/3286479

    Article  Google Scholar 

  31. Farayola, A.M., Hasan, A.N., and Ali, A., Implementation of modified incremental conductance and fuzzy logic MPPT techniques using MCUK converter under various environmental conditions, Appl. Sol. Energy, 2017, vol. 53, no. 2, pp. 173–184.

    Article  Google Scholar 

  32. Elbreki, A.M., Alghoul, M.A., et al., The role of climatic-design-operational parameters on combined PV/T collector performance: A critical review, Renewable Sustainable Energy Rev., 2016, vol. 57, pp. 602–647.

    Article  Google Scholar 

  33. Jahan Mukti, R. and Islam, A., Modeling and performance analysis of PV module with maximum power point tracking in Matlab/Simulink, Appl. Sol. Energy, 2015, vol. 51, no. 4, pp. 245–252.

    Article  Google Scholar 

  34. Aoune, A., Motahhir, S., El Ghzizal, A., Sebti, S., and Derouich, A., Determination of the Maximum Power Point in a photovoltaic panel using Kalman filter on the environment PSIM, IEEE Int. Conf. on Information Technology for Organizations Development (IT4OD), 2016, pp. 1–4.

  35. Gow, J.A. and Manning, C.D., Development of a photovoltaic array model for use in power-electronics simulation studies, lEE Proc. – Electr. Power Appl., 1999, vol. 146, no. 2, pp. 193–200.

    Article  Google Scholar 

  36. Nishioka, K., Sakitani, N., Uraoka, Y., Fuyuki, T., et al., Analysis of multicrystalline silicon solar cells by modified 3-diode equivalent circuit model taking leakage current through periphery into consideration, Sol. Energy Mater. Sol. Cells, 2007, vol. 91, no. 13, pp. 1222–1227.

    Article  Google Scholar 

  37. Ba, A., Ehsseinb, C.O., et al., Comparative study of different DC/DC power converter for optimal PV system using MPPT (P&O) method, Appl. Sol. Energy, 2018, vol. 54, no. 4, pp. 235–245.

    Article  Google Scholar 

  38. Biswas, P.P., Suganthan, P.N., Wu, G., and Amaratunga, G.A.J., Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm, Renewable Energy, 2018, vol. 132, pp. 425–438.

    Article  Google Scholar 

  39. Louzazni, M. and Aroudam, El H., An analytical mathematical modeling to extract the parameters of solar cell from implicit equation to explicit form, Appl. Sol. Energy, 2015, vol. 51, no. 3, pp. 165–171.

    Article  Google Scholar 

  40. Ayop, R. and Tan, C.W., Design of boost converter based on maximum power point resistance for photovoltaic applications, Sol. Energy, 2018, vol. 160, pp. 322–335.

    Article  Google Scholar 

  41. Sanjaya, S., Switching Power Supplies A to Z, Boston: Newnes, 2006.

  42. Al-Diab, A. and Sourkounis, S., Variable step size P&O MPPT algorithm for PV systems, Int. Conf. on Optimization of Electrical and Electronic Equipment, 2010.

  43. Zakzouk, N.E., Elsaharty, M.A., Abdelsalam, A.K., Helal, A.A., and Williams, B.W., Improved performance low-cost incremental conductance PV MPPT technique, IET Renewable Power Gener., 2016, vol. 10, no. 4, pp. 561–574.

    Article  Google Scholar 

  44. Zhang, L., Yu, S.S., Fernando, T., Iu, H.C.H., and Wong, K.P., An online maximum power point capturing technique for high efficiency power generation of solar photovoltaic systems, J. Mod. Power Syst. Clean Energy, 2019, vol. 7, no. 2, pp. 357–368.

    Article  Google Scholar 

Download references

ACKNOWLEDGMENTS

The authors thank Prof. Abdelhalim Zekry at Microelectronics Laboratory, Faculty of Engineering, Ain Shams University for his support.

Funding

This research has been funded by Research Deanship of University of Ha’il – Saudi Arabia through project number RG-191279.

Author information

Authors and Affiliations

  1. Department of Electronics and Electrical Communications, Faculty of Engineering, Ain Shams University, 11517, Cairo, Egypt

    D. Khodair & M. Abouelatta

  2. Department of Engineering Physics, Faculty of Engineering and Technology, Future University, Cairo, Egypt

    D. Khodair

  3. Department of Computer Engineering, Computer Science and Engineering College, University of Ha’il, Ha’il, Saudi Arabia

    M. S. Salem

  4. Department of Electrical Communication and Electronics Systems Engineering, Faculty of Engineering, Modern Science and Arts University, Cairo, Egypt

    M. S. Salem

  5. Department of Engineering Physics and Mathematics, Faculty of Engineering, Ain Shams University, 11517, Cairo, Egypt

    A. Shaker

  6. Department of Computer and Systems Engineering, Faculty of Engineering, Ain Shams University, 11517, Cairo, Egypt

    H. E. Abd El Munim

Authors
  1. D. Khodair
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. S. Salem
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Shaker
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. H. E. Abd El Munim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Abouelatta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Abouelatta.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khodair, D., Salem, M.S., Shaker, A. et al. Application of Modified MPPT Algorithms: A Comparative Study between Different Types of Solar Cells. Appl. Sol. Energy 56, 309–323 (2020). https://doi.org/10.3103/S0003701X20050084

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0003701X20050084

Keywords:

Search

Navigation