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This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) Indonesian Journal of Electrical Engineering and Computer Science
Driss Belkhiri
Ibn Zohr University
Control & Systems Engineering Electrical & Electronics Engineering

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Implementation of a low-cost intelligent street light system using internet of things Fatima Outferdine; Khalid Cherifi; Driss Belkhiri; Brahim Bouachrine; Mohamed Ajaamoum
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1387-1396

Abstract

In the contemporary world, science and technology are advancing swiftly to meet the growing human need for electricity. Within this framework, street lighting, serving as the most vital and ubiquitous element of urban lighting infrastructure, contributes significantly to public electricity consumption. Hence, enhancing the operational efficiency of street lamps becomes imperative to conserve energy. Nonetheless, traditional street lighting systems, being manually controlled, consuming excessive power, and entailing high installation expenses, present notable drawbacks and concerns. Leveraging the internet of things (IoT), advanced innovations automate various areas, including health monitoring, traffic management, agricultural irrigation, street lights, and classrooms. The current manual operation of street lights leads to substantial global energy waste. To address this, an integrated hardware and software solution is proposed. Practical implementation of the hardware devices employs a wireless sensor network, while the software focuses on developing an IoT application for data storage, analysis, and visualization. The proposed system enables effective monitoring of parameters such as ambient temperature, current, voltage, and energy consumption of photovoltaic street lights, which are used as an indicator of the lamp status. Using Xbee modules, a configuration by the X-CTU software is necessary to communicate between all street lights wirelessly. These Xbee modules are used as a leading technology for wireless sensor networks due to its low power and low cost. Experimental results demonstrate that the proposed system is energy-efficient and cost-effective, and further can be implemented in real street light systems.
Robust power optimization strategy for wind-driven induction machines using type-2 and type-1 fuzzy logic controllers Driss Belkhiri; Boujemaa Nassiri; Mohamed Ajaamoum
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i2.pp1313-1325

Abstract

This paper proposes a reliable power optimization strategy that maximizes the harvested power of induction machines driven by wind, taking into account variable wind turbulence and uncertain machine parameters. This work explores the challenging task of designing type-2 fuzzy logic (T2FL) and conventional type-1 fuzzy logic (T1FL) controllers for wind energy conversion systems that exhibit multiple non-linearities. T2FL controllers are proficient in tackling uncertainties and offer quicker and more precise decision-making capabilities. The proposed approach is beneficial as it is independent of accurate wind turbine parameters, wind speed data, or additional sensors. Rather, it utilizes the mechanical rotor speed and the wind turbine power as input, which corresponds to maximum power point tracking (MPPT) through the management of the rotor speed via the machine-side converter. Real data validates the scheme against classical controllers, and via a set of simulations and statistical analyses, performance metrics like steady-state error, overshoot, tracking speed, and efficiency are widely assessed. The results show that the proposed scheme, which is independent of a dedicated wind speed sensor, demonstrates superior tracking performance, lower tracking errors, such as lower RMSE/MAE, and higher energy yield, although the wind speed and the system parameters change rapidly. Overall, this design provides more robust performance to random wind speed variations, increases operational efficiency and wind turbines' service life, and is low in adding mass and cost.
Enhancing electrolyzer performance for hydrogen production in a solar system using a buck converter with sliding mode control Abdellah El Idrissi; Belkasem Imodane; M’hand Oubella; Hatim Ameziane; Mohamed Benydir; Kaoutar Dahmane; Driss Belkhiri; Mohamed Ajaamoum
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp69-79

Abstract

As the world increasingly turns to renewable energy, green hydrogen produced through water electrolysis has emerged as a clean and promising alternative to fossil fuels. In this work, we explore a solar-powered hydrogen production system that uses real data from an operational photovoltaic (PV) installation, ensuring accurate and realistic modeling of environmental conditions. A DC-DC buck converter is used to regulate the fluctuating PV output, supplying the precise voltage needed by a PEM electrolyzer. Sliding mode control (SMC) strategy is applied to maintain voltage stability, and its performance is compared with a traditional proportional-integral (PI) controller. Simulations in MATLAB/Simulink demonstrate that SMC offers better dynamic performance, including minimal overshoot, faster response, and an impressive hydrogen production rate of 0.98 L/min (98% efficiency). By providing more consistent voltage to the electrolyzer, SMC significantly boosts overall system performance. These findings underline the potential of advanced control strategies, supported by real-world data, to make renewable hydrogen production more reliable and efficient.
Co-Authors Abdellah El Idrissi Belkasem Imodane Boujemaa Nassiri Brahim Bouachrine Fatima Outferdine Hatim Ameziane Kaoutar Dahmane Khalid Cherifi Mohamed Ajaamoum Mohamed Benydir M’hand Oubella