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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Bulletin of Electrical Engineering and Informatics
ALtalqi, Fatehi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Evaluating the feasibility of a photovoltaic-wind-diesel-battery hybrid microgrid for sustainable off-grid electrification in Dakhla, Morocco Fennane, Sara; Kacimi, Houda; Mabchour, Hamza; ALtalqi, Fatehi; Echchelh, Adil
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2655-2668

Abstract

Hybrid renewable energy systems (HRES) present a promising solution for improving energy reliability and reducing costs in remote, off-grid areas. This study explores the feasibility of implementing an HRES in Dakhla, Morocco, where conventional electrical infrastructure is lacking. By integrating photovoltaic (PV) panels, wind turbines, diesel generators, and battery storage, this study aims to optimize energy resource management while balancing technical performance and economic viability. Using real- world data on energy consumption, climatic conditions, and installation constraints, advanced simulation tools such as HOMER were employed to evaluate both technical and economic parameters. The objective was to minimize the cost of energy (COE) while ensuring reliability, availability, and a high renewable fraction. The results, compared with optimization algorithms like genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA), revealed the PV-wind-diesel-battery configuration as the most cost-effective solution. This configuration resulted in a net present cost (NPC) of $829,380, a COE of $0.160/kWh, and minimal CO2 emissions of 54.9 kg/year. The findings highlight the viability of this hybrid microgrid as a sustainable off-grid electrification solution and emphasize the role of renewable energy in addressing global energy challenges.
Design and performance evaluation of a high-efficiency circular microstrip patch antenna for RFID applications at 900 MHz Sahel, Zahra; Habibi, Sanae; Bendali, Abdelhak; ALtalqi, Fatehi; Mouhib, Omar; Habibi, Mohamed
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.9110

Abstract

This study presents a high-efficiency circular microstrip patch antenna designed for radio frequency identification (RFID) applications simulation results illustrate the performance of a circular microstrip patch antenna operating at 900 MHz. Microstrip antennas are renowned for their ability to meet the requirements of compact, lightweight designs, ensuring compatibility, and ease of integration. This research focuses on the development of a circular microstrip antenna, formed as a circular patch on a 0.035 mm thick FR-4 substrate. The design was realized using a substrate with a relative permittivity (εr) of 4.3, a loss tangent (tan δ) of 0.021 and a substrate height (h) of 1.6 mm. The antenna dimensions are small, measuring 58×45 mm, with a circular patch radius of 17 mm. The antenna operates over a frequency range from 0.5 GHz to 2 GHz. Key performance parameters include a return loss of -49.8 dB, a wide bandwidth of 150 MHz, a voltage standing wave ratio (VSWR) of 1.009, a gain of 2.161 dB, and a directivity of 2.200 dBi. Antenna design and simulation were carried out using computer simulation technology (CST) Studio Suite Software, specifically adapted to RFID applications.
Comparison of multilayer perceptron and nonlinear autoregressive models for wind speed prediction Kacimi, Houda; Fennane, Sara; Mabchour, Hamza; ALtalqi, Fatehi; El Moury, Ibtissam; Echchelh, Adil
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8541

Abstract

Wind energy is a critical component of the global shift to renewable energy sources, with significant growth driven by the need to reduce carbon emissions. Accurate wind speed prediction is crucial for increasing wind energy output since it directly influences wind farm design and performance. The purpose of this study is to compare two artificial neural network (ANN) models for predicting wind speed in Dakhla City, a place with a high wind energy potential. The first model is a multilayer perceptron (MLP) trained with the backpropagation algorithm, while the second is a nonlinear autoregressive with exogenous inputs (NARX) model, a form of recurrent neural network (RNN) noted for its ability to handle time-series data more well. The comparative analysis results show that the NARX model outperforms the MLP model in terms of wind speed forecast accuracy. The NARX model achieved a near-perfect regression coefficient (R) of 0.9998 and a root mean square error (RMSE) of 1.02899, indicating that it can represent complex, nonlinear wind speed patterns. These findings indicate that the NARX model could be a beneficial tool for increasing the efficiency of Dakhla City’s wind energy infrastructure, assisting the region in meeting its renewable energy ambitions.
Performance enhancement of photovoltaic systems using hybrid LSTM-CNN solar forecasting integrated with P&O MPPT Fennane, Sara; Kacimi, Houda; Mabchour, Hamza; ALtalqi, Fatehi; Echchelh, Adil
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i1.pp696-708

Abstract

The increasing penetration of photovoltaic (PV) systems in smart grids highlights the need for reliable solutions to mitigate the inherent intermittency of solar energy. Short-term variability in solar irradiance remains a critical challenge for stable grid operation and efficient PV energy management. This paper proposes an integrated forecasting-control framework that combines short-term global horizontal irradiance (GHI) prediction with a conventional P&O MPPT strategy to enhance PV system performance. A hybrid LSTM-CNN architecture is developed to forecast one-step-ahead GHI under the semi-arid climatic conditions of Dakhla, Morocco, a region characterized by high solar potential and pronounced irradiance fluctuations. The forecasting model is validated using measured irradiance data from the National Renewable Energy Laboratory (NREL) via the National Solar Radiation Database (NSRDB). Predicted irradiance is then used to improve PV power estimation and support predictive maximum power point tracking (MPPT) operation. Simulation results obtained in MATLAB/Simulink demonstrate that the proposed framework achieves accurate GHI forecasting, faster MPPT convergence, reduced steady-state oscillations, and improved PV power stability under rapidly changing irradiance. The proposed approach provides a practical and computationally efficient solution for enhancing the dynamic response and energy extraction efficiency of PV systems in smart grid applications.
Co-Authors Bendali, Abdelhak Echchelh, Adil El Moury, Ibtissam Fennane, Sara Habibi, Sanae Kacimi, Houda Mabchour, Hamza Mohamed Habibi Mouhib, Omar Sahel, Zahra