An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

  • Authors

    • M. I. Iman
    • M. F. Roslan
    • Pin Jern Ker
    • M. A. Hannan
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.35.22861
  • DC-DC Boost Converter, Maximum Power Point Tracking, Photovoltaic.
  • This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.

  • References

    1. [1] S. Ahmed et al., “RenewableS 2011,†Renew. Energy, vol. 5, no. 4, p. 116, 2011.

      [2] N. Karami, N. Moubayed, and R. Outbib, “General review and classification of different MPPT Techniques,†Renew. Sustain. Energy Rev., vol. 68, no. July 2015, pp. 1–18, 2017.

      [3] W. Bai and K. Lee, Distributed Generation System Control Strategies in Microgrid Operation, vol. 47, no. 3. IFAC, 2014.

      [4] A. Saeed Ahmed Student, B. A. Abdullah, and W. Gharieb Ali Abdelaal, “MPPT Algorithms: Performance and Evaluation,†2016 11th Int. Conf. Comput. Eng. Syst., pp. 1–7, 2016.

      [5] L. Zhang, S. Member, W. G. Hurley, and W. H. W, “A New Approach to Achieve Maximum Power Point Tracking for PV System With a Variable Inductor,†vol. 26, no. 4, pp. 1031–1037, 2011.

      [6] C. P. Roy, D. Vijaybhaskar, and T. Maity, “Modelling of Fuzzy Logic Controller for Variable- Step Mppt in Photovoltaic System,†no. 2, pp. 426–432, 2013.

      [7] T. Esram and P. L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,†IEEE Trans. Energy Convers., vol. 22, no. 2, pp. 439–449, 2007.

      [8] J. Ahmad, “A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays,†Softw. Technol. Eng. (ICSTE), 2010 2nd Int. Conf., vol. 1, pp. 247–250, 2010.

      [9] N. Díaz, A. Luna, and O. Duarte, “Improved MPPT short-circuit current method by a fuzzy short-circuit current estimator,†IEEE Energy Convers. Congr. Expo. Energy Convers. Innov. a Clean Energy Futur. ECCE 2011, Proc., pp. 211–218, 2011.

      [10] Subiyanto, A. Mohamed, and M. A. Hannan, “Maximum power point tracking in grid connected PV system using a novel fuzzy logic controller,†2009 IEEE Student Conf. Res. Dev., no. SCOReD, pp. 349–352, 2009.

      [11] D. Sera, T. Kerekes, R. Teodorescu, and F. Blaabjerg, “Improved MPPT Algorithm for Rapidly Changing Environmental Conditions,†pp. 1614–1619, 2006.

      [12] M. A. Hannan, Z. Abd Ghani, and A. Mohamed, “An enhanced inverter controller for PV applications using the dSPACE platform,†Int. J. Photoenergy, vol. 2010, 2010.

      [13] N. Khaehintung and K. Pramotung, “RlSC-Microcontroller Built-in Fuzzy Logic Controller of Maximum Power Point Tracking for Solar-Powered Light-Flasher Applications,†Ieee, pp. 2673–2678, 2004.

      [14] Jiyong Li and Honghua Wang, “Maximum power point tracking of photovoltaic generation based on the fuzzy control method,†2009 Int. Conf. Sustain. Power Gener. Supply, pp. 1–6, 2009.

      [15] J. Kennedy and R. Eberhart, “Particle swarm optimization,†Neural Networks, 1995. Proceedings., IEEE Int. Conf., vol. 4, pp. 1942–1948 vol.4, 1995.

      [16] I.-Y. Chung, W. Liu, D. A. Cartes, and K. Schoder, “Control parameter optimization for a microgrid system using particle swarm optimization,†2008 IEEE Int. Conf. Sustain. Energy Technol., pp. 837–842, 2008.

      [17] A. K. Paul and P. C. Shill, “Optimizing fuzzy membership function using dynamic multi swarm - PSO,†2016 5th Int. Conf. Informatics, Electron. Vision, ICIEV 2016, pp. 139–144, 2016.

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  • How to Cite

    Iman, M. I., Roslan, M. F., Ker, P. J., & Hannan, M. A. (2018). An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System. International Journal of Engineering & Technology, 7(4.35), 457-462. https://doi.org/10.14419/ijet.v7i4.35.22861