PID-like Neural Network for Maximum Power Point Tracking of a Photovoltaic System

Document Type : Original Article

Authors

Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

Abstract

In this study, the PID–like neural network (PIDNN) controller is proposed for maximum power point tracking (MPPT) of the photovoltaic (PV) systems. The proposed neural network (NN) structure works as a nonlinear PID controller. The proposed controller combines the advantages of the PID controller such as easy to implement and the advantages of the NN. The parameters of the proposed PIDNN are learned and tuned on-line based on the gradient descent method. This scheme creates a nonlinear PID controller, which improves the system performance. The results show the robustness of the PIDNN under different levels of the environmental changes such as PV cell temperature and solar irradiance. The simulation results for the proposed PIDNN are compared with other schemes in order to show the robustness of the proposed structure.

Keywords

References

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Menoufia Journal of Electronic Engineering Research
Volume 28, ICEEM2019-Special Issue
ICEEM2019-Special Issue: 1st International Conference on Electronic Eng., Faculty of Electronic Eng., Menouf, Egypt, 7-8 Dec.
2019
Pages 242-247

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