Switching Control based on Achievement of Maximum Power in Solar Cell with Adaptive Controller

  • Sayed Abdolhossein Emadi Author
  • Mohammad Reza Zare
Keywords: : Solar Cell-Tracking Maximum Power-Adaptive Smart Controller Chart.

Abstract

 In this paper by using the nonlinear structure for model the solar cell, the voltage and the desired power as the solar cell output are provided. The optimal operating point for power of solar cell system is called the maximum power point and varies in different conditions. In order to achieve this goal, the DC / DC converter is boost converter, which controls by its switching. Fuzzy theory has been used to achieve optimal power for load and maximum solar cell power. In this paper, the fuzzy algorithm is also used to optimize the control method. Changes in output load and amount of sunlight are among the issues in which the stability of the control system is analyzed. The results are presented according to the simulation in MATLAB software and the good performance of the controller is shown in different conditions of the system's performance.

References

[1] O. Guenounou, B. Dahhou, and F. Chabour, “Adaptive fuzzy controller based MPPT for photovoltaic systems,” Energy Convers. Manag., vol. 78, pp. 843–850, Feb. 2014.
[2] N. A. Rahim, A. Che Soh, M. A. M. Radzi, and M. A. A. M. Zainuri, “Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter,” IET Renew. Power Gener., vol. 8, no. 2, pp. 183–194, Mar. 2014.
[3] R. K. Kharb, S. L. Shimi, S. Chatterji, and M. F. Ansari, “Modeling of solar PV module and maximum power point tracking using ANFIS,” Renew. Sustain. Energy Rev., vol. 33, pp. 602–612, May 2014.
[4] M. Muthuramalingam and P. S. Manoharan, “Comparative analysis of distributed MPPT controllers for partially shaded stand alone photovoltaic systems,” Energy Convers. Manag., vol. 86, pp. 286–299, Oct. 2014.
[5] K. Ishaque and Z. Salam, “A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition,” Renew. Sustain. Energy Rev., vol. 19, pp. 475–488, Mar. 2013.
[6] B. N. Alajmi, K. H. Ahmed, S. J. Finney, and B. W. Williams, “A maximum power point tracking technique for partially shaded photovoltaic systems in microgrids,” IEEE Trans. Ind. Electron., vol. 60, no. 4, pp. 1596–1606, Apr. 2013.
[7] M. Muthuramalingam and P. S. Manoharan, “Comparative analysis of distributed MPPT controllers for partially shaded stand alone photovoltaic systems,” Energy Convers. Manag., vol. 86, pp. 286–299, Oct. 2014.
[8] M. Veerachary, T. Senjyu, and K. Uezato, “Neural-netwrk-based maximum-power-point tracking of coupled-inductor,” IEEE Trans. Ind. Electron., vol. 50, no. 4, pp. 749–758, Aug. 2003.
[9] A. K. Mahammad, S. Saon, and W. S. Chee, “Development of optimum controller based on mppt for photovoltaic system during shading condition,” Malaysian Technical Universities Conf, Vol. 53, pp. 337–346, Jan. 2013.
[10] C. Chu and C. Chen, “Robust maximum power point tracking method for photovoltaic cells : A sliding mode control approach,” Sol. Energy, vol. 83, no. 8, pp. 1370–1378, Mar.2009.
[11] C. Chiu, Y. Ouyang, and C. Ku, “Terminal sliding mode control for maximum power point tracking of photovoltaic power generation systems,” Sol. Energy, vol. 86, no. 10, pp. 2986–2995, Aug. 2012.
Published
2019-05-23
Section
Articles