Design and real-time implementation of an ANN-driven MPPT controller for hybrid renewable energy systems

Mohamed El-Sayed M. Essa, Hemdan S. El-Sayed, Elwy E. El-Kholy, Hilmy El-Sayed Awad, Mohamed Saleh Elsayed

Abstract


Enhancing the reliability and efficiency for hybrid renewable systems under dynamic conditions of environmental needs efficient and effective control of power extraction. Conventional methods for maximum power point tracking (MPPT) often undergo from limited accuracy and slow response when dealing with rapid fluctuations in temperature and irradiance and nonlinear characteristics. For this purpose, this paper proposes a distinct MPPT approach based on Artificial Neural Network (ANN) technique. The proposed approaches are implemented on a grid-connected 150-kW hybrid PV/wind energy system. The objective of the control is to ensure optimal power extraction despite temperature, solar irradiation, and wind speed variations. In addition, FOPID controllers are designed for inverter control to enhance voltage regulation and, hence, power quality. Additionally, the performance of IC and ANN techniques are compared using detailed MATLAB/Simulink simulations. The experimental real-time validation is performed through investigation based on OPAL-RT 4512 hardware-in-the-loop platform. The results show that the ANN – based collected data from conventional MPPT techniques significantly outperforms the IC technique in terms of tracking speed, dynamic stability, and steady-state accuracy. ANN provided the best comprehensive performance in both simulation and experiment studies. Hence, the originality of this work is to integrate the ANN technique in a hybrid PV/wind MPPT framework and validate its efficacy with FOPID control for inverter control strategies through real-time HIL experiments that offer a robust and high-efficiency solution for rapidly time-varying environmental conditions.

 

Received: 06 January 2026

Accepted: 08 May 2026

Published: 07 June 2026


Keywords


PV system; wind system; MPPT; ANN; Hardware-in-the-loop; OPAL-RT 4512; FOPID

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References


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DOI: https://dx.doi.org/10.21622/resd.2026.12.1.1889

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Copyright (c) 2026 Mohamed El-Sayed M. Essa, Hemdan S. El-Sayed, Elwy E. El-Kholy, Hilmy El-Sayed Awad, Mohamed Saleh El-Sayed

Renewable Energy and Sustainable Development

E-ISSN: 2356-8569

P-ISSN: 2356-8518

 

Published by:

Academy Publishing Center (APC)

Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

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