Cover
Vol. 21 No. 1 (2025)

Published: September 19, 2025

Pages: 1-15

Original Article

Integration of Fuzzy Logic and Neural Networks for Enhanced MPPT in PV Systems Under Partial Shading Conditions

Hayder Dakhil Atiya 1 Mohamed Boukattaya 2 Fatma Ben Salem 3
1Department electrical power at National School of Engineering of Sfax, Tunisia
2Laboratory of sciences and Techniques of Automatic Control & Computer Engineering (Lab-STA), National School of Engineering of
3Department of Electrical Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj 16273, Saudi Arabiay
History
  • Received: October 9, 2023
  • Revised: December 4, 2023
  • Accepted: December 21, 2023
  • Available Online: September 19, 2024
DOI

https://doi.org/10.37917/ijeee.21.1.1

Abstract

Efficient energy collection from photovoltaic (PV) systems in environments that change is still a challenge, especially when partial shading conditions (PSC) come into play. This research shows a new method called Maximum Power Point Tracking (MPPT) that uses fuzzy logic and neural networks to make PV systems more flexible and accurate when they are exposed to PSC. Our method uses a fuzzy logic controller (FLC) that is specifically made to deal with uncertainty and imprecision. This is different from other MPPT methods that have trouble with the nonlinearity and transient dynamics of PSC. At the same time, an artificial neural network (ANN) is taught to guess where the Global Maximum Power Point (GMPP) is most likely to be by looking at patterns of changes in irradiance and temperature from the past. The fuzzy controller fine-tunes the ANN’s prediction, ensuring robust and precise MPPT operation. We used MATLAB/Simulink to run a lot of simulations to make sure our proposed method would work. The results showed that combining fuzzy logic with neural networks is much better than using traditional MPPT algorithms in terms of speed, stability, and response to changing shading patterns. This innovative technique proposes a dual-layered control mechanism where the robustness of fuzzy logic and the predictive power of neural networks converge to form a resilient and efficient MPPT system, marking a significant advancement in PV technology.

Keywords

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