Journals
2025 EN
Seidu Ibrahim · Salisu Sani · Mas'ud Abdullahi Abubakar
+4 more
ABSTRACT This study reviews recent developments in optimization techniques for hybrid solar photovoltaic and wind energy systems, particularly those using artificial intelligence (AI) and hybrid algorithms. Due to the global need for sustainable energy, the study compares both traditional and modern optimization techniques. It shows that hybrid algorithms, like, Gray Wolf–Cuckoo Search Optimization (GWCSO), can speed up convergence and reduce costs by up to 25% compared with other conventional methods, such as linear programming. The study groups optimization techniques into traditional, software‐based, AI‐driven, and hybrid approaches; assessing how well they improve system efficiency, reliability, and cost. It also outlines sizing methods and their economic, technical, and environmental effects, with results showing that AI‐driven methods can lower the levelized cost of energy by 10%–15% in complex microgrids (MGs). The study further provides a structured way to size MGs, addressing a gap in optimization methods for independent hybrid systems in remote locations. Greater flexibility of hybrid algorithms in handling complex optimization problems was emphasized. Ultimately, this study offers new insights into combining AI with traditional methods, suggesting future research directions for both smart grid and MG design.
Journals
2025 EN
BaQais Amal · ElSalamony Radwa A. · Ibrahim Ahmed A.
+7 more
ABSTRACT This study investigates the catalytic efficiency of Ni catalysts for the dry reforming of methane, utilizing different metal oxides (CeO₂, SiO₂, SmO₃, and YO₃) support. The impact of the support material on the conversion of CH₄ and CO₂, as well as the resulting H₂/CO ratio, is investigated at 700°C and 800°C. The Ni/CeO₂ showed the most promising performance at 700°C, converting around 99% of the CH₄ and CO₂. Nevertheless, out of all the catalysts evaluated, its syngas selectivity was the lowest. On the other hand, at 700°C, Ni/Sm₂O₃ and Ni/Y₂O₃ showed comparable CH₄ conversion rates of 40% and a H₂/CO ratio of about 1. The CH₄ conversion over Ni/Y₂O₃ doubled with an increase in reaction temperature, but its syngas selectivity stayed as low as that of Ni/CeO₂. Based on a temperature‐programmed reduction (TPR) study, it can be said that the metal‐support interaction over a catalyst is modified by the extent of reduction of NiO over a specified support. The existence of NiO and the crystalline phases of the supports were verified by X‐ray diffraction (XRD). The basic and acidic characteristics of CO₂ (TPD‐CO₂) and NH₃ (TPD‐NH₃) were clarified by temperature‐programmed desorption, respectively, demonstrating that the support material has a major influence on the distribution and strength of these sites. According to nitrogen physisorption studies, all catalysts had mesoporous structures, with differences in pore size and distribution of carbonaceous deposits found on used catalysts using Raman spectroscopy; the greatest graphitic carbon was found in Ni/CeO₂. The morphology and dispersion of Ni particles changed during the reaction, including sintering and the production of carbon nanotubes, as shown by transmission electron microscope images. The study emphasizes the crucial role that support material plays in adjusting the catalytic characteristics of Ni‐based catalysts for DRM.
Journals
2025 EN
Tian ManWen · Mao JunBo · Tavoosi Jafar
+3 more
ABSTRACT Microgrids with integrated renewable energy sources are becoming more and more important in the fast‐changing electrical energy production scenario. An 8 kW wind generator and a 4.5 kW solar photovoltaic system are the two renewable energy sources utilized in the hybrid alternating current (AC) and/or direct current (DC) microgrid architecture in this study. The energy storage component is a 33 Ah battery. An adaptive control technique based on type‐3 fuzzy sliding mode control (T3FSMC) is applied to improve voltage control reliability under changing operating circumstances and external disturbances. Specifically intended for islanded operating circumstances, where stabilizing the DC link voltage is especially important, this intelligent controller provides adaptive resilience without requiring specified limitations for system disturbances. To assist the control design, a comprehensive dynamic model of the microgrid is created, and MATLAB/SIMULINK simulations are used to test the suggested approach. In the context of standalone microgrid operation, the findings demonstrate the T3FSMC approach's better dynamic response and disturbance rejection capacity when compared to benchmark controllers, such as conventional sliding mode control, barrier function‐based adaptive sliding mode control, and proportional integral derivative (PID). Furthermore, the proposed method has been able to improve tracking error by 20%, 8%, and 3% compared to PID, sliding mode control (SMC), and barrier function‐based adaptive SMC (BFSMC), respectively.
Journals
2025 EN
Chaudhry Vivek · Singh Joginder · Ibrahim Ahmed A.
+3 more
ABSTRACT Supercapacitors, known for their high‐power energy storage capabilities, have garnered significant attention due to their rapid charge–discharge cycles and extended life span. To expand their application in fields such as electric vehicles, renewable energy systems, and portable electronic devices, the development of advanced electrolytes that can boost energy density, power density, and overall performance is crucial. This study introduces a novel electrolyte formulation comprising lithium chloride in ethylene glycol and Magnesium Acetate in methanol. These formulations are designed to address existing challenges and enhance supercapacitor efficiency. The study reports impressive specific capacitance values (Csp = 582, 360, and 224 F/g), specific energy (SE = 323, 200, and 124 Wh/kg), and specific power (SP = 11 628, 7200, and 1322 W/kg) for lithium chloride, magnesium acetate, and zinc chloride electrolytes, respectively. These findings open new avenues for developing optimal and sustainable energy storage solutions in an increasingly electrified world. Continued research in this domain is expected to unlock the full potential of supercapacitors, contributing to a cleaner and more energy‐efficient future.
Journals
2025 EN
Ashok Aromal · Reesh Ibrahim Abu · Kumar Anand
ABSTRACT Electrochemical degradation of 4‐chlorophenol (4‐CP) was investigated using a rotating disk electrode (RDE) over magnesium ferrite (MgFe 2 O 4 ), iron‐oxide and magnesium‐oxide in presence of 4‐CP in varying concentrations of 25, 50, and 75 mg/L. The objective of this study is to evaluate the effectiveness of these catalysts in achieving high current densities during the degradation process, and to understand their relation with the structural properties of the catalysts obtained from standard characterization techniques. Our results indicate that the MgO catalyst shows a poor current density for electrocatalytic degradation of 4‐CP. However, when MgO is used in presence of iron oxide, as in MgFe 2 O 4 , a high current density for 4‐CP degradation is observed, indicating the synergistic role of MgFe system in improving catalytic activity. On the other hand, iron oxide alone showed the highest current density, however, most of which is expected to be associated with water splitting as opposed to 4‐CP degradation. Our findings highlight the potential of magnesium ferrite based mixed oxide catalysts in environmental applications, and also provide insights into the role of Mg in modulating catalytic performance. Additionally, this work also emphasizes the role of implementing RDE technique in identifying suitable catalysts for studying 4‐CP degradation in wastewater.
Journals
2025 EN
Zakariya'u Ibrahim · Nasir Sehrish · Rawat Neelam
+4 more
ABSTRACT In the present work, highly conducting polymer electrolyte films are prepared by integrating Polyvinyl‐pyrrolidone (PVP) with sodium iodide (NaI) salt. To further improve performance, different concentrations of an ionic liquid, 1‐ethyl‐3‐methylimidazolium thiocyanate, were added to the optimized polymer matrix containing salt through the solution casting method. Experiments with complex impedance spectroscopy identified conductivity, and the electrochemical stability window was measured using linear sweep voltammetry. The number of charge carriers ( T ion ) is studied using Wagner's DC polarization method. A notable increase in conductivity was recorded after the addition of the ionic liquid to the maximum conductive polymer‐salt system. Fourier transform infrared (FTIR) spectroscopy validated the composite structure and the complexation within the matrix. Additionally, polarized optical microscopy indicated a decrease in crystallinity and an increase in amorphous content because of interaction with both the salt and the ionic liquid. The resulting highly conductive polymer electrolyte, achieved by combining the salt and ionic liquid, and previously reported activated carbon‐based electrodes are utilized to fabricate an electrical double‐layer capacitor (EDLC). The EDLC cell is further studied using various electrochemical tools such as EIS, CV, and GCD.
Journals
2025 EN
Bannour Youness · El Alami Yassine · Nasrin Rehena
+3 more
ABSTRACT The current work investigates approaches to augment photovoltaic (PV) panels through phase change material (PCM) systems' efficiency, with the addition of aluminum fins and varying angles of inclination. A two‐dimensional numerical simulation using the enthalpy–porosity method was conducted in ANSYS Fluent for modeling PCM melting behavior. This research studied five cases of PCMs (for the same fin area and size) at five angles of inclination (30°, 60°, 90°, 120°, and 150°). The results show good agreement with literature values. PV tilt angle's influence on heat dissipation for conduction and natural convection ratio in PCM is significant. Case 3 configuration (90° inclination) exhibits the best performance of all configurations: lowest PV temperature (318.2 K), highest electrical efficiency (11.83%), maximum thermal efficiency (46.7%), maximum melting fraction transport (0.47), and maximum overall efficiency (58.61%). Case 3 exhibits a temperature improvement of 3.36 K in comparison to the worst‐performing setup at 150° (Case 5) values with increases of 1.72% in electrical efficiency, 23.2% in thermal efficiency, 34.3% in melting fraction, and an 18.8% improvement in overall efficiency. Past studies have looked at the geometry of the fins, while this current study looks at the orientation of the fins. The study confirms that the 90° fin angle (which is least obstructive to vertical thermal transfer) is ideal to optimize the PV‐PCM systems' efficiency under the current boundary conditions.
Journals
2025 EN
Ezugwu Absalom E. · Taiwo Olutosin · Egwuche Ojonukpe S.
+8 more
ABSTRACT The advent of the Internet of Things (IoT) has transformed the concept of smart home automation, thereby allowing users to remotely interact with their houses and control home appliances for resource efficiency. This technological development has significantly improved convenience, safety, and overall lifestyles for homeowners. The impact of smart home automation systems (SHAS) extends beyond individual households, positively influencing the global economy in various aspects. While research in smart home automation has proposed solutions to wireless control and monitoring issues, there are still challenges hindering the widespread deployment of these systems. This paper conducts a detailed systematic analysis of state‐of‐the‐art SHAS, covering topics such as the concept of smart home automation, its application domains, architectural framework, enabling technologies, as well as the challenges involved. Furthermore, this paper provides reviews and discussions on the latest essential components, technologies, and protocols employed in designing and developing SHAS. By offering an in‐depth examination of the current scenery, this study aims to provide readers with a comprehensive understanding of smart home automation, its significance, and future research directions. Through addressing the challenges and presenting potential solutions, this research contributes to adopting wider acceptance and successful deployment of SHAS.
Journals
2025 EN
Megahed Amal · Elmesalawy Mahmoud M. · Abd ElHaleem Ahmed. M.
+1 more
ABSTRACT Active Reconfigurable Intelligent Surface (ARIS) shows promise in boosting the desired signal at the receiver user. However, the “fully‐connected” architecture of ARIS needs high power due to additional active components. This paper adopts sub‐connected ARIS to enhance achieved data rates with good energy efficiency at the Cell Edge Users (CEUs) and addresses the “multiplicative fading” effect caused when the signal propagates through a longer path (i.e., the serving Base Station (BS)‐ARIS‐CEU) than the straight route across the serving BS and the CEUs. Additionally, a Nearly Passive RIS (NP‐RIS) is proposed to mitigate interfering signals from other BSs by creating destructive interference at the CEUs. The reflection matrix of the NP‐RIS is extracted using Deep Learning (DL) techniques, with a select few NP‐RIS reflecting elements being active. This model improves achieved data rates by around 58% for M = 16 RIS elements compared with the baseline model with the same number of elements in NP‐RIS without ARIS implementation. Moreover, the proposed model enhances data rates by approximately 31.8% compared with a baseline using negative resistance Reflecting Elements (RE). However, the Spectral Energy Efficiency (SEE) using the second baseline will be improved over the “fully‐connected” ARIS leading to the sub‐connected ARIS solution to improve the SEE by nearly 25%.
Journals
2025 EN
Allafi Randa · Alshahrani Amnah · Arasi Munya A.
+5 more
ABSTRACT Due to the shortage of explainable, resource‐efficient solutions and the lack of unified multi‐attack detection abilities, existing vehicular ad hoc networks (VANET) security frameworks fail to meet the critical requirements of real‐time vehicular environments. Most traditional models rely heavily on centralized processing, making them unsuitable for dynamic, latency‐sensitive distributed VANET architectures. These limitations create a serious threat to the safety and reliability of vehicular communication systems. To address these challenges, this study proposes an explainable machine learning framework for real‐time multi‐attack threat detection (EXMAT) in edge‐enabled VANET environments. The framework is designed specifically for edge‐enabled VANET platforms. EXMAT combines the novel XGBoost classifier with custom‐engineered behavioral features and post hoc explainability to provide accurate decisions directly at the vehicular edge. The novelty of the model lies in its combined feature space, which fuses behavioral dynamics, communication patterns, and lightweight Boolean anomaly flags. The simulation of the model is performed under the VeReMi dataset. To strengthen the dataset for precise analysis of the threat, we synthetically extended it with complex attack patterns. Experimental results show that the proposed model achieves an overall classification accuracy of 95.78% with an almost perfect F1‐score for standard behavior samples of 99.98% and 94.36% for replay attacks. These results highlight EXMAT's ability to be applied in real‐time vehicular networks, enhancing traffic safety and security against unknown cyberattacks.