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Maximum Power Point Tracking of Photovoltaic Panels by Using Improved Pattern Search Methods

Author

Listed:
  • Andrés Tobón

    (Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia)

  • Julián Peláez-Restrepo

    (Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia)

  • Juan P. Villegas-Ceballos

    (Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia)

  • Sergio Ignacio Serna-Garcés

    (Departamento de Electrónica y Telecomunicaciones, Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín, Antioquia, Colombia)

  • Jorge Herrera

    (Departamento de Ingeniería, Facultad de Ciencias Naturales e Ingeniería, Universidad de Bogotá Jorge Tadeo Lozano, Bogotá, Distrito Capital, Colombia)

  • Asier Ibeas

    (Departamento de Ingeniería, Facultad de Ciencias Naturales e Ingeniería, Universidad de Bogotá Jorge Tadeo Lozano, Bogotá, Distrito Capital, Colombia
    Departament de Telecomunicació i d’Enginyeria de Sistemes, Escola d’Enginyeria Universitat Autònoma de Barcelona (UAB), Bellaterra, Cerdanyola del Vallés, 08193 Barcelona, Spain)

Abstract

This paper deals with the optimization of maximum power point tracking when a photovoltaic panel is modelled as two diodes. The adopted control is implemented using a sliding mode control (SMC) and the optimization is implemented using an improved Pattern Search Method. Thus, the problem of maximum power point tracking is reduced to an optimization problem whose solution is implemented by Pattern Search Techniques, inheriting their convergence properties. Simulation examples show the effectiveness of the proposed technique in practice, being able to deal with different radiations. In addition, improved pattern search method (IPSM) is compared with other techniques such as perturb & observe and Particle Swarm optimization, after which IPSM presents lower energy losses in comparison with the other two algorithms, with the advantage of ensuring the location of the optimal power point in all cases.

Suggested Citation

  • Andrés Tobón & Julián Peláez-Restrepo & Juan P. Villegas-Ceballos & Sergio Ignacio Serna-Garcés & Jorge Herrera & Asier Ibeas, 2017. "Maximum Power Point Tracking of Photovoltaic Panels by Using Improved Pattern Search Methods," Energies, MDPI, vol. 10(9), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1316-:d:110646
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    References listed on IDEAS

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    4. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
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    5. Kommoju Naga Durga Veera Sai Eswar & Mohan Arun Noyal Doss & Pradeep Vishnuram & Ali Selim & Mohit Bajaj & Hossam Kotb & Salah Kamel, 2022. "Comprehensive Study on Reduced DC Source Count: Multilevel Inverters and Its Design Topologies," Energies, MDPI, vol. 16(1), pages 1-25, December.
    6. Fatemeh Nasr Esfahani & Ahmed Darwish & Ahmed Massoud, 2022. "PV/Battery Grid Integration Using a Modular Multilevel Isolated SEPIC-Based Converter," Energies, MDPI, vol. 15(15), pages 1-25, July.
    7. Carlos Robles Algarín & John Taborda Giraldo & Omar Rodríguez Álvarez, 2017. "Fuzzy Logic Based MPPT Controller for a PV System," Energies, MDPI, vol. 10(12), pages 1-18, December.
    8. Eduardo Manuel Godinho Rodrigues & Radu Godina & Mousa Marzband & Edris Pouresmaeil, 2018. "Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity," Energies, MDPI, vol. 11(11), pages 1-21, October.
    9. Xiaoguang Liu & Yuefeng Wang, 2019. "Reconfiguration Method to Extract More Power from Partially Shaded Photovoltaic Arrays with Series-Parallel Topology," Energies, MDPI, vol. 12(8), pages 1-16, April.
    10. João Faria & José Pombo & Maria do Rosário Calado & Sílvio Mariano, 2019. "Power Management Control Strategy Based on Artificial Neural Networks for Standalone PV Applications with a Hybrid Energy Storage System," Energies, MDPI, vol. 12(5), pages 1-24, March.
    11. Andrés Tobón & Julián Peláez-Restrepo & Jhon Montano & Mariana Durango & Jorge Herrera & Asier Ibeas, 2020. "MPPT of a Photovoltaic Panels Array with Partial Shading Using the IPSM with Implementation Both in Simulation as in Hardware," Energies, MDPI, vol. 13(4), pages 1-17, February.

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