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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Ennaoui, Ilias
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Control & Systems Engineering Electrical & Electronics Engineering

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The implementation of an optimized neural network in a hybrid system for energy management Jarmouni, Ezzitouni; Mouhsen, Ahmed; Lamhamdi, Mohamed; Ennajih, Elmehdi; Ennaoui, Ilias; Krari, Ayoub
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp815-823

Abstract

In the face of increasing global energy demand and volatile energy prices, many countries are searching for solutions to ensure their energy independence. One of the most popular solutions is to incorporate renewable energy sources in their energy systems. While there are many advantages to integrating renewable energy sources, it is important to note that their intermittent operation can present challenges. Energy storage and smart grid management systems are key solutions to overcome these challenges and ensure sustainable, reliable use of renewable energy sources. In this article, we present an intelligent electrical energy management system for hybrid energy systems. This management system is based on a multi-layer neural network that has undergone an architecture optimization phase to improve the accuracy of real-time energy management and simplify its implementation. The management model that was built demonstrated highly good performance across a range of test circumstances.
Comparing fuzzy logic and backstepping control for a buck boost converter in electric vehicles Ennajih, Elmehdi; Allali, Hakim; Jarmouni, Ezzitouni; Ennaoui, Ilias
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp883-891

Abstract

Significant advances have been made in the control of DC/DC converters, owing to the effective combination of linear and nonlinear approaches. The above-mentioned approaches have greatly improved the efficiency as well as stability of the converter, even when faced with changing conditions. Nevertheless, the emergence of artificial intelligence has introduced new perspectives in the domain. The objective of the article is to examine two separate methodologies for controlling a boost-buck converter: using a nonlinear approach, especially backstepping, and utilizing artificial intelligence through fuzzy logic. The main aim of this work is to illustrate the inherent stability and robustness of fuzzy logic controllers compared to backstepping control in managing effectively various variations and challenges encountered in converter control.
Co-Authors Allali, Hakim Ennajih, Elmehdi Jarmouni, Ezzitouni Krari, Ayoub Lamhamdi, Mohamed Mouhsen, Ahmed