International Journal of Energetica
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Electrical Characteristics Analysis of High-Efficiency SnS Solar Cells
Get PDFThe simulation of SnS homojunction solar cells involved systematically adjusting key parameters, such as doping concentration and layer thickness, to optimize their photovoltaic performance. The study identified that optimal efficiency is achieved with a carrier concentration of 5.5 × 1015 cm⁻³ in the front n-type region, a 500 nm thick n-layer, and a 500 nm thick p+ layer with a carrier concentration of 3 × 10¹⁶ cm⁻³. Under these conditions, the solar cell demonstrated excellent electrical characteristics, including an open-circuit voltage (Voc) of 0.90 V, a short-circuit current density (Jsc) of 34.20 mA/cm², a fill factor (FF) of 0.829, and an efficiency (η) of 25.71%. These results underscore the importance of precise control over material properties and structural dimensions in achieving high-efficiency SnS-based solar cells, positioning SnS as a promising material for future photovoltaic applications
Prediction of the Insulating Paper State of Power Transformers Using Artificial Neural Network
Get PDFPower transformers are considered the heart of power systems. The malfunction or undesirable outage of the power transformer will cause a tremendous revenue loss for the utilities. Therefore, a regular or preventive test must be accomplished on the transformer to check its state. Some standards, such as the American Transformer Diagnosis Guide and the American Society for Testing and Materials, have instructions for testing the transformers. The current works addressed which tests can be accomplished to predict the insulating paper state, which is the indicator of transformer aging. Furthermore, ANN model will be constructed to use it as a prediction tool of the paper state when the water content (WC), acidity (ACI), interfacial tension (IFT), oil color (OC), and 2-furfuraldehyde (2-FAL) were known. The ANN results indicated that the ANN's prediction accuracy was 93.87%
Application of Grey Wolf Optimization Algorithm for Maximum Power Point Tracking of Solar Panels
Get PDFOne of the applications of evolutionary algorithms is increasing the efficiency of photovoltaic (PV) systems. The main problem with using standard algorithms like the Incremental Conductance (IC) controller for maximum power point tracking (MPPT) under partial shading conditions (PSC) is that they do not provide reliable tracking of the global peak of the volt-watt characteristic, leading to increased losses and reduced power plant performance. Furthermore, there is currently no methodology for selecting the optimal sampling time of soft computing algorithm-based maximum power trackers for PV systems. The aim of this paper is to apply the Grey Wolf technique with optimally selected sampling time, which will result in fast and reliable tracking of the global maximum point of the PV panels. The results show that the selected optimal sampling time for the digital MPP controllers can increase the performance and efficiency of MPPT controllers. A DC-DC boost converter is used to match the PV panels with the resistive load. Several simulations were performed using MATLAB/Simulink to examine the performance of the proposed system. The results demonstrate that the proposed Grey Wolf algorithm can quickly capture the GMPP within 0.2 seconds under different shading conditions of the PV panels
Design and Economic Evaluation of a Photovoltaic Water Pumping System for Tomato Irrigation in El Oued, Algeria
Get PDFThis paper explores the design, economic assessment, and operation of a photovoltaic water pumping system for irrigating tomatoes in Terifaoui, El Oued, Algeria. Terifaoui's desert climate and lack of grid access make it a suitable candidate for a solar-powered irrigation system. The system design, simulated using PVsyst software, considers El Oued's climate to ensure reliable operation. This study examines the technology, economics, and operational aspects of the system, highlighting its potential to boost agricultural output and regional economic resilience
Power losses reduction by optimal allocation of renewable distributed generation in distribution networks
Get PDFThe electrical energy demand is increasing dramatically in many countries around the world due to population growth. As a result of this significant increase in demand, electricity distribution companies are seeking to promote distributed generation (DG). With the growing integration of decentralized renewable power generation into the distribution network, it becomes an active circuit where power flows and voltages are influenced not only by loads but also by sources. In distribution networks (DN), the optimal allocation of Renewable Distributed Generation (DG) units can significantly improve system performance by reducing power losses and enhancing the voltage profile and stability of the radial distribution network. The main objective of this paper is to apply the marine predator algorithm (MPA) to optimize the siting and sizing of DG units in the DN. The objective function considered is the minimization of active power losses. The proposed algorithm is tested on the IEEE 33-bus and 69-bus DN. The simulation results demonstrate that the MPA algorithm outperforms other optimization algorithms in terms of perform
CPU-Based Data Acquisition in Assessing the Impact of Inclination on Solar Panels
Get PDFA data logging system has been deployed to monitor two solar panels positioned at distinct inclination angles. This system records crucial parameters such as current, voltage, solar radiation incident on the panels, and panel temperatures. Comprising an Arduino microcontroller, a current sensor, a current and voltage sensor, and a Memory Card, the data logger captures and stores data in .txt files at 20-minute intervals. Employing a real-time acquisition system, the obtained results indicate that the data logger effectively archives and presents a wealth of information about solar panel characteristics. Notably, the data reveals superior performance of the solar panels at a 35-degree tilt angle compared to 32 degrees during April in the Ouargla region of Algeria
Effect of Rubber Thickness on the Performance of Conventional Solar Stills under El Oued city climate (Algeria)
Get PDFOur study focuses on examining the performance of conventional solar stills in an arid region, specifically investigating the impact of rubber material and its thickness on the distillation process. Four solar stills were tested, including a reference solar still (SSR) and three modified solar stills (MSS1, MSS2, and MSS3) with rubber thicknesses of 1 cm, 2 cm, and 3 cm, respectively. The experimental findings clearly demonstrate a notable difference in distilled water productivity between varying rubber thicknesses. The outputs of MSS1, MSS2, and MSS3 were measured at 1105 ml/day, 1010 ml/day, and 955 ml/day, respectively, all surpassing the output of SSR, which was recorded at 830 ml/day. These results indicate that the utilization of rubber with varying thicknesses positively impacts the productivity of the solar still, leading to higher distilled water yields compared to the reference configuratio
Optimizing Parabolic Through Collectors for Solar Stills: A 2D CFD Parametric Analysis
Get PDFThe thermal efficiency of parabolic trough collectors (PTCs) is influenced by various parameters, including length, diameter, and mass flow rate. This study employs 2D steady-state Computational Fluid Dynamics (CFD) simulations to investigate heat transfer within PTCs and enhance their performance. Exploring diverse PTC designs, involving variations in length (L = 0.5 to 3 m) and diameter (D = 10 to 60 mm), sourced from existing research to optimize desalination system applications. The investigation covers both laminar and turbulent regimes with fully developed flows, examining the effects of Reynolds number and mass flow rate. The results highlight that collector diameter has the most pronounced impact on thermal efficiency, followed by mass flow rate, while the effect of length can be neglected in comparison. A 50% diameter increase leads to over a 60% rise in efficiency for both laminar and turbulent cases, whereas a 60% decrease in mass flow rate corresponds to a 50% enhancement and a 60% improvement in efficiency for both regimes. These findings suggest that an optimal PTC design should prioritize a smaller diameter and lower mass flow rate, with length being of secondary importance and application-specific considerations also playing a pivotal role
Developed nonlinear model based on bootstrap aggregated neural networks for predicting global hourly scale horizontal irradiance
Get PDFThis research study examines the use of two models of artificial intelligence based on a single neural network (SNN) and bootstrap aggregated neural networks (BANN) for the prediction value of hourly global horizontal irradiance (GHI) received over one year in Tamanrasset City (Southern Algeria). The SNN and BANN were created using overall data points. To improve the accuracy and durability of neural network models generated with a limited amount of training data, stacked neural networks are developed. To create many subsets of training data, the training dataset is re-sampled using bootstrap re-sampling with replacement. A neural network model is created for each set of training datasets. A stacked neural network is created by combining multiple individual neural networks (INN). For the testing phase, higher correlation coefficients (R = 0.9580) were discovered when experimental global horizontal irradiance (GHI) was compared to predicted global horizontal irradiance (GHI). The performance of the models (INN, BANN, and SNN) demonstrates that models generated with BANN are more accurate and robust than models built with individual neural networks (INN) and (SNN)
Optimal Controller Design and Dynamic Performance Enhancement of High Step-up Non-Isolated DC-DC Converter for Electric Vehicle Charging Applications
Get PDFIdeally, traditional boost converters can achieve a high conversion ratio with a high-duty cycle. But, in regular practice, due to low conversion efficiency, RR reverse-recovery, and EMI (electromagnetic interference) problems, the high voltage gain cannot be performed, whereas CIBC (coupled inductor-based converters) can achieve high voltage gain by re-adjusting the turn ratios. Even though the leakage inductor of the CI (coupled inductor) makes some problems like voltage spikes on the main connectivity switch, high power dissipation, and voltage pressure can be minimized by voltage clamp. In this paper, a non-isolated DC-DC converter with high voltage gain is demonstrated with 3 diodes, 3 capacitors, 1-inductor, and a coupled inductor. The main inductor is connected to the input to decrease the current ripple. The voltage stress at main switch S is shared by diode D1 and capacitor C1 and the main switch is turned ON under zero current, hence it turns to low switching losses. This paper proposes two controllers like proportional-integral (PI) controller and fuzzy logic (FLC) for dc-dc converter. Furthermore, it demonstrates the operation, design, mathematical analysis, and performance of DC-DC converter using controllers for efficient operation of the system is performed using simulations in MATLAB 2012b