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Published in: Arabian Journal for Science and Engineering 11/2023

21-08-2023 | Research Article-Electrical Engineering

Hybrid Neural Network and Adaptive Terminal Sliding Mode MPPT Controller for Partially Shaded Standalone PV Systems

Authors: Abdullah Baraean, Mahmoud Kassas, Md Shafiul Alam, Mohamed A. Abido

Published in: Arabian Journal for Science and Engineering | Issue 11/2023

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Abstract

This research presents a new method for controlling the maximum power point tracking (MPPT) of solar photovoltaic (PV) systems that are partially shaded. The proposed approach uses a neural network and an adaptive terminal sliding mode controller (NN-ATSMC) to ensure that the PV system operates at optimal performance under uncertain conditions. The NN-ATSMC controller is applied to a DC/DC boost converter to drive the system to the maximum power point (MPP). This method ensures that the error will converge in finite time and the chattering effect will be minimized without losing robustness under various disturbances and load conditions. Simulation results show that the proposed NN-ATSMC controller performs better than other types of controllers existing in the literature, such as a sliding mode controller (SMC) and a conventional proportional-integral controller (CPI). For the validation of the proposed controller, control hardware-in-the-loop (C-HIL) experimental implementation has been carried out through Texas Instruments digital signal processor C2000. The experimental results show the viability of real-time implementation and verify the effectiveness of the proposed method, which ensures the low cost and stability of the standalone PV systems.

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Metadata
Title
Hybrid Neural Network and Adaptive Terminal Sliding Mode MPPT Controller for Partially Shaded Standalone PV Systems
Authors
Abdullah Baraean
Mahmoud Kassas
Md Shafiul Alam
Mohamed A. Abido
Publication date
21-08-2023
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 11/2023
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-023-08179-9

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