Simulation and Implementation of a Modified ANFIS MPPT Technique

  • Bachar Meryem Department of Electrical Engineering, Hassan First University, Settat, Morocco
  • Naddami Ahmed Department of Electrical Engineering, Hassan First University, Settat, Morocco
  • Fahli Ahmed Department of Electrical Engineering, Hassan First University, Settat, Morocco
Keywords: PV panel, MPPT algorithm, Buck converter, ANFIS

Abstract

The maximum power point tracking (MPPT) algorithms ensure optimal operation of a photovoltaic (PV) system to extract the maximum PV power, regardless of the climatic conditions. This paper exposes the study, design, simulation and implementation of a modified advanced neural fuzzy inference system (ANFIS) MPPT algorithm based on fuzzy data for a PV system. The studied system includes a PV array, a DC/DC buck converter, the ANFIS controller, a proportional-integral (PI) controller, and a load. The simulation and experimental tests are carried out with the MATLAB/Simulink software and LabVIEW, respectively. Moreover, the obtained results are compared with previously published results by incremental conductance (IC) and fuzzy logic (FL) algorithms under different climatic conditions of irradiation and temperature. The results show that the proposed ANFIS algorithm is able to track the maximum power point for varying climatic conditions. Furthermore, the comparison analysis reveals that the PV system using ANFIS algorithm has more efficient and better dynamic response than FL and IC.

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Published
2020-09-01
How to Cite
[1]
Bachar Meryem, Naddami Ahmed, and Fahli Ahmed, “Simulation and Implementation of a Modified ANFIS MPPT Technique”, Adv. technol. innov., vol. 5, no. 4, pp. 230-247, Sep. 2020.
Section
Articles