Simulation and Implementation of a Modified ANFIS MPPT Technique
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.
P. Srinivas, K. V. Lakshmi, and C. Ramesh, “Simulation of Incremental Conductance MPPT Algorithm for PV systems using Labview,” International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 4, no. 1, pp. 34-38, January 2016.
A. Bouchakour, M. Brahimi, and A. Borni, “Comparative study on photovoltaic pumping systems driven by different motors optimized with sliding mode control,” International Journal of Engineering and Technology Innovation, vol. 7, no. 3, pp. 201-216, January 2017.
A. Nouaiti, A. Saad, A. Mesbahi, and M. Khafallah, “A new efficient topology of single-phase five-level inverter for PV system,” International Journal of Engineering and Technology Innovation, vol. 8, no. 4, pp. 241-260, January 2018.
S. Diwania, S. Agrawal, A. S. Siddiqui, and S. Singh, “Photovoltaic-thermal (PV/T) technology: a comprehensive review on applications and its advancement,” International Journal of Energy and Environmental Engineering, November 2019.
H. Bounechba, A. Bouzid, H. Snani, and A. Lashab, “Real time simulation of MPPT algorithms for PV energy system,” Electrical Power and Energy System, vol. 83, pp. 67-78, December 2016.
H. Shahid, M. Kamran, Z. Mehmood, M. Y. Saleem, M. Mudassar, and K. Haider, “Implementation of the novel temperature controller and incremental conductance MPPT algorithm for indoor photovoltaic system,” Solar Energy, vol. 163, pp. 235-242, March 2018.
M. Kamran, M. Bilal and Z. Zeeshanjahan, “LabVIEW based simulator for solar cell characteristics and MPPT under varying atmospheric conditions,” Mehran University Research Journal of Engineering and Technology, vol. 37, no. 3, pp. 529-538, July 2018.
A. Dolara, R. Faranda, and S. Leva, “Energy comparison of seven MPPT techniques for PV systems,” Journal of Electromagnetic Analysis and Applications, vol. 1, no. 3, pp. 152-162, January 2009.
A. Attou, A. Massoum, and M. Saidi, “Photovoltaic power control using MPPT and boost converter,” Balkan Journal of Electrical & Computer Engineering, vol. 2, no. 1, pp. 23-27, September 2014.
D. Choudhary and A. R. Saxena, “DC-DC buck-converter for MPPT of PV system,” International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 7, pp. 813-821, July. 2014.
N. Karami, N. Moubayed, and R. Outbib, “General review and classification of different MPPT techniques,” Renewable and Sustainable Energy Reviews , vol. 68, pp. 1-18, February 2017.
M. Bachar, A. Naddami, S. Hayani, and A. Fahli, “Optimization of pv panel using P&O and incremental conductance algorithms for desalination mobile unit,” Advanced Intelligent Systems Applied to Energy, vol. 2, pp. 164-184, January 2019.
M. S. Reddy and P. V. R. Rao, “Fast tracking MPPT for photo voltaic system using ANFIS control logic ALgorithm,” International Journal of Innovation Research in Science, Engineering and Technology, vol. 6, no. 3, pp. 3717-3726, March 2007.
K. Ishaque, Z. Salam, and G. Lauss, “The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions,” Journal of Applied Energy, vol. 119, pp. 228-236, April 2014.
M. S. Reddy and P. V. R. Rao, “Fast tracking MPPT for photo voltaic system using ANFIS control logic algorithm,” International Journal of Innovation Research in Science, Engineering and Technology, vol. 6, no. 3, pp. 3717-3726, March 2007.
M. Bachar, A. Naddami, S. Hayani, and A. Fahli, “Design and dimensioning of desalination mobile unit and optimization of electrical energy with MPPT algorithms,” Proc. Americain Institut of Physics, 2018.
M. R. Kumar, S. S. Narayana, and G. Vulasala, “Advanced sliding mode control for solar PV array with fast voltage tracking for MPP algorithm,” International Journal of Ambient Energy, pp. 1-9, July 2018.
S. E. Babaa, M. Armstrong, and V. Pickert, “Overview of maximum power point tracking control methods for PV systems,” Journal of Power and Energy Engineering, vol. 2, pp. 59-72, January 2014.
M. Bachar, A. Naddami, and A. Fahli, “Photovoltaic power control using fuzzy logic and fuzzy logic type 2 MPPT algorithms and buck converter,” Advances in Technology Innovation, vol. 4, no. 3, pp. 59-72, May 2019.
M. Kermadi and E. M. Berkouk, “Artificial intelligence-based maximum power point tracking controllers for photovoltaic systems: comparative study,” Renewable and Sustainable Energy Reviews, vol. 69, pp. 369-386, March 2017.
M. A. M. Ramli, S. Twaha, K. Ishaque, and Y. A. Al-Turki, “A review on maximum power point tracking for photovoltaic systems with and without shading conditions,” Renewable and Sustainable Energy Reviews, vol. 67, pp. 144-159, January 2017.
A. P. K. Yadav, S. Thirumaliah, and G. Haritha, “Comparison of MPPT Algorithms for DC-DC converters-based PV systems,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 1, no. 1, pp. 18-23, January 2012.
R. K. Kharb, S. L. Shimi, S. Chatterji, and M. F. Ansari, “Modeling of solar PV module and maximum power point tracking using ANFIS,” Renewable and Sustainable Energy Reviews, vol. 33, pp. 602-612, May 2014.
E. H. Mamdani and S. Assilian, “An experiment in linguistic synthesis with a fuzzy logic controller”, International Journal of Man-Machine Studies, vol. 7, pp.1-13, January 1995.
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