International Journal of Energetica
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Numerical and experimental characterization of internal heat and mass transfer during convective drying of papaya (Carica papaya L.) in a drying air stream
Get PDFThis work consisted of simulating convective heat and mass transfers during the drying of papaya in a parallel air stream. The aim of this work was to simultaneously couple the two-dimensional heat and mass transfer equations in the product in order to predict the drying kinetics of the papaya. These papaya slices were arranged on a rack with a length (L) of 30 cm and thickness (E) of 5 mm. The Luikov equations thus established for this model were discretized using the implicit finite difference method and then solved simultaneously using the Matlab 2014 tool. Simulations of papaya drying were performed under the influence of drying air temperature (40, 50, and 60 °C), drying air velocity (0.5, 1 and 1.76 m/s), relative air humidity (20, 40, and 60%), and product thickness (4, 5, and 6 mm). The numerical simulation results allowed the prediction of the temperature and humidity distributions inside the product during the drying process. The predicted data from this model were compared to the experimental data. The results showed agreement between the predicted and experimental data with average relative errors of 5.21% and 4.35% for moisture ratio and product temperature, respectively
ANFIS Models for Fault Detection and Isolation in the Drive Train of a Wind Turbine
Get PDFThe paper aims to improve the fault detection and isolation process in wind turbine systems by developing intelligent systems that can effectively identify and isolate faults. Specifically, the paper focuses on the drive train part of a horizontal axis wind turbine machine. The proposed fault diagnostic strategy is designed using an adaptive neural fuzzy inference system (ANFIS), which is a type of artificial neural network that combines the advantages of both fuzzy logic and neural networks. The ANFIS is used to generate residuals that occur after faults have been detected, and to determine the appropriate thresholds needed to correctly detect faults. The simulation results show that the proposed fault diagnostic strategy is effective in detecting faults in the drive train part of the wind turbine system. By using intelligent systems such as ANFIS, the fault detection process can be automated and streamlined, potentially reducing maintenance costs and improving the overall performance and efficiency of wind turbine systems
Predictive Study on the Application of the Soweto Wind Turbine Results in the Coastal Region of South Africa
Get PDFThis study evaluates the performance of three wind turbine prototypes (Prototypes 1, 2, and 3) in Soweto, South Africa, by analyzing their monthly energy generation under different time of day/month conditions. Prototype 3 emerges as the most efficient, generating 39.5 W at a wind speed of 1.17 m/s and projecting a maximum of 40 kWh per month. Building upon these results, a predictive study examines the feasibility of implementing the same technology in coastal regions, specifically Gqeberha, where stronger winds prevail. Utilizing empirical data from Soweto, the study forecasts an improved energy output of up to 54.3 W at a wind speed of 5.16 m/s (18.6 km/h) and up to 100 kWh per month. The findings highlight the potential benefits of utilizing wind turbine technology in coastal areas, contributing valuable insights to renewable energy system development in similar geographical contexts
Optimizing Small Wind Turbine Blades: A BEMT Approach
Get PDFThis paper explores the optimization of small wind turbine blades, focusing on the design and utilization of theoretical algorithms such as computational fluid dynamics (CFD), blade elementary method (BEM) theory, and the vortex wake system (VWS). Among these methods, BEM theory has proven to be the most effective in optimizing horizontal-axis wind turbine (HAWT) blades and is commonly employed in modeling and constructing small wind turbine blades. The study centers on designing and optimizing aerofoils to enhance rotor blade pitch angles and determining the optimal number of blades for maximizing power output at various wind speeds using BEMT. Using a NACA-4412 type aerofoil as the starting point, the paper investigates different pitch angles, blade radii, and chord lengths for Designs 1, 2, and 3. Results indicate that at an average wind speed of 0 - 2.3 m/s (8.28 km/h), 3-blade, 5-blade, and 7-blade sets were designed and optimized for performance. The predictions suggest rated outputs of 7.5 W, 20 W, and 40 W for Designs 1, 2, and 3, respectively. The study reveals that Design 3, with a blade radius of 1m, a chord length of 0.1m, and a pitch angle ranging from 12° near the rotor hub to 2° at the blade radius tip, achieved a significant power output of 39.5 W at a wind speed of 4.2 km/h. The findings contribute valuable insights into optimizing wind turbine blade design for enhanced energy efficiency
Fuel Consumption Estimation via Bookkeeping Method for Geostationary Satellites: Simple Application
No full textThis work focuses on the Satellite Propulsion Subsystem (UPS), a critical aspect of satellite technology that can be supported by various propulsion types: electrical, chemical, cold gas, and nuclear propulsion. For communication satellites, chemical propulsion emerges as the most suitable option due to its simplicity and lower energy requirements. The chemical propulsion subsystem comprises oxidizer and fuel tanks, gas pressuring tanks utilizing helium. Wherein, Thrusters are employed for diverse tasks, encompassing tank sinking, orbital maneuvers (correction), attitude control, and deorbiting. These processes induce propellant consumption from orbit transfer to the deorbiting operation. The satellite's mission life hinges on propellant quantity, emphasizing the need to maintain sufficient reserves for deorbiting at satellite’s end of life. Thus, accurately estimating propellant mass becomes a crucial task. This work delves into propellant mass estimation methods, specifically Bookkeeping (BKP). Moreover, we introduce and test a developed tool based on the Bookkeeping method. This tool proves instrumental in estimating the remaining propellant, offering a valuable resource for satellite mission planning and longevity
Structural analysis of wind blades with and without power control
Get PDFThe blade is the principal element in the wind rotor mechanism. the efficiency of the wind turbine depends on the optimal geometry of this element, as well as its structural configuration. This work presents a contribution to wind blade structural design. the blade structure was evaluated without the control power operating case and with the power control case. In this case, an 80KW horizontal axis wind turbine design was proposed. the process begins with design and aerodynamic analysis based on blade element momentum theory by using Qblade software to determine the blade geometry. The blade structure was defined by the NuMad package, it is composed of two parts. the shell part is four layers of composite materials and the rib part has a sandwich panel shape. The evolution of structure was done by the Co-Blade package. The results show a decreasing in displacement decreased to 64% at the tip of the blades which leads to the stress at the leading and trailing edge being negligible. That proves the importance of a control power system in the protection of the blade structure and turbine generator in the operating case under high wind velocity and ensures the stability of the power output value
Optimal tilt angle for photovoltaic panels in the Algerian region of El-Oued in the spring season: An experimental study
Get PDFThe tendency to exploit solar energy in the electricity production in Algeria is a priority and a major goal of the Algerian government, and for this reason it seeks to provide all the necessary capabilities to achieve this lofty goal. Photovoltaic electricity is one of the effective technologies for the solar electricity production, but before installing any photovoltaic panel, it is important to determine its optimal tilt angle, and based on this, this study allowed to show the optimal tilt angle of the photovoltaic panels in the Algerian region of El Oued in the spring season, and accordingly, two days (March 21st, 2023, and April 21st, 2023) were chosen to conduct this experimental study. Based on the obtained results, the optimal PV tilt angle for the month of March is 33° and 28° for the month of April. In addition, the greater the amount of solar radiation, the higher the efficiency and productivity of the PV panels, as the highest values for them (6.31 % and 62.17 W, respectively) were recorded on April 21st, 2023. The results of this study will contribute to the correct installation of photovoltaic panels in the Algerian region of El-Oued, especially if the photovoltaic panels are equipped with dual-axis solar tracking systems
Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves
Get PDFPhotovoltaic (PV) system health monitoring and fault diagnosis are essential for optimizing power generation, enhancing reliability, and prolonging the lifespan of PV power plants. Shading, especially in PV systems, leads to unique voltage-current (I-V) characteristics, serving as indicators of system health. This paper presents a cost-effective and highly accurate method for detecting, diagnosing, and classifying shading faults based on real I-V data obtained through electrical measurements under both healthy and shaded conditions. The method leverages Principal Component Analysis (PCA) to separate classes, and a confusion matrix assesses classification accuracy. The results demonstrate a success rate exceeding 98% in various configurations, using experimental data from a 250 W PV module. Importantly, this method relies solely on existing electrical measurements, eliminating the need for additional sensors, making it both efficient and cost-effective
Effective Modeling of Photovoltaic Modules Using Sailfish Optimizer
Get PDFThe current study proposes a novel meta-heuristic technique called sailfish optimizer (SFO) to design reliable photovoltaic (PV) modeling models. Unlike others, the proposed technique employs two populations (prey and predator) instead of one to effectively reach the desired solution. This unique propriety can substantially augment the probability of locating the global optimum as well as accelerating the search process. Moreover, to show the efficacy of the algorithm, the results are compared with some literature techniques such as Salp-Swarm-Optimizer (SSA), Whale Optimization (WOA), Artificial-Bee-Colony (ABC), and Particle-Swarm Optimization (PSO) methods. Eventually, the proposed SFO algorithm demonstrated a remarkable amelioration in terms of accuracy with Root-Mean-Square-Error of 13E-3 A
Generating temperature cycle profiles of different solar photovoltaic module technologies from in-situ conditions for accurate prediction of thermomechanical degradation
Get PDFThe IEC61215 TC200 is a rigorous approval thermal cycling test process that assesses the reliability of solar photovoltaic modules and offers a 25-year lifetime guarantee. However, previous research has shown that installed solar photovoltaic modules experience different rates of degradation depending on the location and climate with most research focused on crystalline silicon. In this study, outdoor weathering data obtained from a rig set up in Kumasi, Ghana for the year 2014, is used to generate thermal cycles for 5 different technologies including monocrystalline, polycrystalline, and amorphous silicon, Copper Indium Gallium Selenide (CIGS) and Heterojunction-With-Intrinsic-Thin-Layer (HIT). From the results, the highest yearly average of the maximum and minimum temperatures, and ramp rates of 54.8oC, 26.1oC, and 6.05oC/h respectively are recorded in CIGS. Polycrystalline recorded the least temperatures of 45.2°C and 23.9°C while HIT recorded the least ramp rate of 4.45°C /h. A comparison between the 2014 and the IEC61215 thermal cycles show extremely wide differences which could explain the higher degradation rates and shorter life of installed solar photovoltaic modules. The procedure adopted in this research can be repeated at different locations to obtain technology-specific thermal cycling profiles to evaluate the thermomechanical damage and predict the life of different solar photovoltaic modules