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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Adil Echchelh
Ibn Tofail University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Design monopole antenna of ultra-wideband high bandwidth and high efficiency for ground penetrating radar application Fatehi ALtalqi; Sara Fennane; Hamza Mabchour; Houda Kacimi; Adil Echchelh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.25340

Abstract

Over the past years, remote sensing, radar, and imaging applications have all made use of ultra-wideband (UWB) technology. This study undertakes an extensive analysis of tree-shaped monopole antennas tailored for UWB systems. The intended antenna has an incomplete ground plane and a circular radiating patch. To increase bandwidth, two ears have been added to the circular structure. Possessing a dielectric constant of 4.3. The antenna substrate consists of FR-4 material with a dielectric constant of 4.3. To achieve optimal impedance matching for UWB systems, the antenna is fed via a coplanar waveguide (CPW). Design antenna is a simple structure, small size, easy design, and simple integration with the substrate with dimensions of 54 mm ×36 mm ×1.6 mm. All simulation results presented in this article were generated using computer simulation technology (CST) software. He monopole antenna exhibits an impressive impedance bandwidth of 9.6 GHz (146.68%), spanning from 1.99 GHz to 11.56 GHz. Furthermore, the simulated UWB circular monopole antenna exhibits omnidirectional radiation characteristics, boasting a peak gain of 8 dB, and a directivity of 8.2 dBi at the frequency of 5 GHz, and a remarkable radiation efficiency of 97%. With these attributes, the suggested monopole UWB antenna shows significant potential for ground penetrating radar (GPR) applications.
Performance enhancement of photovoltaic systems using hybrid LSTM-CNN solar forecasting integrated with P&O MPPT Sara Fennane; Houda Kacimi; Hamza Mabchour; Fatehi ALtalqi; Adil Echchelh
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.
Enhancing wind speed forecasting accuracy: comparative insights into recurrent neural networks for short-term prediction Sara Fennane; Houda Kacimi; Hamza Mabchour; Fatehi Altalqi; Aziz El Hazmir; Adil Echchelh
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11222

Abstract

Short-term wind speed forecasting is essential for maintaining grid stability and supporting the integration of renewable energy, yet the strong variability of wind makes accurate prediction difficult. Sudden fluctuations and nonlinear atmospheric behavior often reduce the performance of conventional artificial intelligent models. To address this challenge, this study evaluates three forecasting methods which include a gated recurrent unit (GRU) model, a temporal convolutional networks (TCNs) model, and a hybrid GRU–TCN design that enables prolonged term forecasting while enabling quick identification of localized weather changes across various meteorological parameters. The researchers used Laayoune, Morocco data to build their model training process. The hybrid method exceeded all other models because it achieved an R² value of 0.99 and a root mean square error (RMSE) of 0.16 m/s and a mean absolute error (MAE) of 0.03 m/s. The system successfully manages sudden shifts in wind patterns while maintaining accurate site-specific physical behavior. The hybrid GRU–TCN design functions as a dependable and expandable system, which delivers real-time wind forecasting capabilities that enable effective smart grid operations and facilitate the growth of wind energy systems.
Co-Authors Aziz El Hazmir Fatehi ALtalqi Hamza Mabchour Houda Kacimi Sara Fennane