A Hybrid Renewable Energy System Management Using an Artificial Intelligence MIMO-Fuzzy Controller

Authors

  • Ilham Aouaci Smart Grids and Renewable Energies Laboratory, Tahri Mohammed University of Bechar, BP 417, 08000 Bechar, Algeria
  • Boumediene Allaoua Smart Grids and Renewable Energies Laboratory, Tahri Mohammed University of Bechar, BP 417, 08000 Bechar, Algeria
  • Bousmaha Bouchiba Smart Grids and Renewable Energies Laboratory, Tahri Mohammed University of Bechar, BP 417, 08000 Bechar, Algeria
Volume: 15 | Issue: 4 | Pages: 25688-25698 | August 2025 | https://doi.org/10.48084/etasr.10952

Abstract

The integration of clean energy sources into standalone power systems requires the selection of appropriate renewable resources based on the local weather conditions, geographic location, and installation costs. Photovoltaic (PV) panels and hydrogen-based systems, particularly those using Solid Oxide Fuel Cells (SOFCs), are often used in a complementary manner. The efficient operation of such hybrid systems necessitates an intelligent energy management capable of optimizing the power flow to the electrical loads and of storing the surplus energy. To achieve a high power quality and reduce the overall system costs, a suitable system architecture and advanced control strategies are essential. In this context, an intelligent supervisory control based on Multi-Input Multi-Output Fuzzy Logic Control (MIMO-FLC) is proposed. This controller addresses key challenges, such as enhancing the energy efficiency, ensuring a smooth production-consumption balance, and maintaining the service continuity and reliability. The proposed MIMO-FLC effectively manages the hybrid energy system by adapting to the changing weather conditions and load demands. The system was modeled and simulated using MATLAB/Simulink. The simulation results demonstrate that the fuzzy logic-based control significantly improves the system performance, ensuring high power quality and efficient energy usage. The controller successfully directs energy either to the load or to the battery storage without power loss or interruptions. This study emphasizes the simulation process and analyzes the evolution of key parameters—such as power, voltage, pressure, and current density—over time to estimate the electrical energy required for a 1 MW output load.

Keywords:

hybrid energy system management, Solid Oxide Fuel Cell (SOFC), PV, energy storage, grid on/off, MIMO-FLC

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How to Cite

[1]
I. Aouaci, B. Allaoua, and B. Bouchiba, “A Hybrid Renewable Energy System Management Using an Artificial Intelligence MIMO-Fuzzy Controller”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 4, pp. 25688–25698, Aug. 2025.

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