scholarly journals Experimental and Theoretical Validation of One Diode and Three Parameters–Based PV Models

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2140
Author(s):  
Rui Castro ◽  
Miguel Silva
Keyword(s):  
Crystalline Silicon ◽  
Theoretical Data ◽  
High Irradiance ◽  
Operating Conditions ◽  
Computational Time ◽  
Electrical Behavior ◽  
Pv Modules ◽  
Iterative Equations ◽  
3P Model ◽  
Theoretical Results

The present paper defines and assesses a new simplified method to represent the photovoltaic (PV) modules’ electrical behavior, based on the commonly used one diode and three parameters (1D + 3P) model, addressing two main objectives. The first one is to quantify and assess, at different operating conditions, the PV modules electrical behavior estimations’ accuracy provided by the well-known 1D + 3P, through a comparison based on experimental and theoretical results. The second one concerns the performance assessment of the 1D + 3P model’s suggested approximation, aiming at simplifying the mathematics instead of solving complex iterative equations, which hinges on higher computational time to obtain accurate results. Hence, experimental and theoretical data were considered, aiming at performing a thorough comparison with more than 17,000 PV modules being assessed, which was achieved by using both the California Energy Commission (CEC) database and PVsyst software. The findings show that the already known 1D + 3P model delivers satisfactory power output estimations for crystalline silicon modules and high irradiance conditions. However, its performance worsens when considering Low Irradiance and thin-film technology. In comparison with the original model, accurate results were obtained with the new simplified suggested 1D + 3P for all irradiance conditions and technologies assessed, thus proving its validity and capability of circumventing the aforementioned challenges.

Effects of Dynamic Operational Conditions on Thermal Infrared Imaging of Monocrystalline Silicon Photovoltaic Modules

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
M. Vumbugwa ◽  
J. L. Crozier McCleland ◽  
E. E. van Dyk ◽  
F. J. Vorster
Keyword(s):  
Infrared Imaging ◽  
Short Circuit ◽  
Thermal Infrared ◽  
Climatic Conditions ◽  
High Irradiance ◽  
Operating Conditions ◽  
Ambient Conditions ◽  
Operational Conditions ◽  
Pv Modules ◽  
Electrical Loads

Abstract Photovoltaic (PV) modules installed in the field generate electrical power under different meteorological and operational conditions; therefore, maintenance of the modules is crucial for the longevity of the PV modules. Thermal infrared (TIR) imaging is a widely used monitoring technique for quality checks of PV modules in plants. It is ideally conducted on operational PV modules under steady ambient conditions; however, PV modules operate under dynamic climatic conditions which influence the overall operation of all solar cells and modules. The dynamic nature of thermal signatures was observed on TIR images when monocrystalline PV modules operated under varying electrical loads and irradiance. A change in operating conditions affected the level of current mismatch between cells since at high irradiance of about 1000 watts per square meter (W m−2) and while operating close to short circuit current at reduced load, the PV cells generated a higher current which led to significant current mismatch. This resulted in several abnormally hot cells being identified on TIR images. Under lower irradiance and larger electrical loads, fewer hot cells were observed and cracked cells (identified through Electroluminescence (EL)) appeared as good cells due to minimal current mismatch. The effectiveness of TIR imaging to reveal underperforming defective cells as hot cells depends on the operating conditions and can mislead decision-making when PV module maintenance is carried out. This work gives valuable information which can be of importance in improving the maintenance systems of PV modules when TIR imaging is conducted.

Water Cooling Method to Improve the Performance of Field-Mounted, Insulated, and Concentrating Photovoltaic Modules

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Matthew K. Smith ◽  
Hanny Selbak ◽  
Carl C. Wamser ◽  
Nicholas U. Day ◽  
Mathew Krieske ◽  
...  
Keyword(s):  
Particle Deposition ◽  
Crystalline Silicon ◽  
Cooling System ◽  
Effective Means ◽  
Operating Conditions ◽  
Energy Output ◽  
Mechanical Degradation ◽  
Water Cooling ◽  
Local Climate ◽  
Pv Modules

The installation rate of crystalline silicon photovoltaic (PV) modules worldwide is at an all-time high and is projected to continue to grow as the cost of PV technology is reduced. It is important to note that PV power generation is heavily influenced by the local climate. In particular, for crystalline silicon-based PV devices, as the operating temperature of the panel increases, the efficiency decreases. Higher operating temperatures also lead to accelerated material and mechanical degradation, potentially compromising system effectiveness over the lifetime of the panels. In addition, atmospheric pollution can cause particle deposition on the surface of PV modules (soiling), reducing the amount of solar irradiance that reaches the PV material and reducing panel efficiency. Various cooling and cleaning methods have been proposed in the literature to mitigate these problems. In this study, a uniform film of water was continuously recirculated by pumping over the surface of a solar panel using an emitter head attached to the top of the panel. The water cooling technique was able to maintain panel temperature below 40 °C while adjacent untreated panels were operating near 55 °C. Besides the efficiency improvements due to cooling, the film of water also kept the panels clean, avoiding any reduced power output caused by panel soiling. Additional studies were carried out with artificially chilled cooling fluid, insulating materials, and side mirrors to examine the cooling system performance under different installation scenarios. Water cooling is concluded to be an effective means of increasing the efficiency of monocrystalline silicon photovoltaic panels. Under normal operating conditions, the increased energy output from the panels is more than sufficient to compensate for the energy required to pump the water.

scholarly journals Efficient Cell Segmentation from Electroluminescent Images of Single-Crystalline Silicon Photovoltaic Modules and Cell-Based Defect Identification Using Deep Learning with Pseudo-Colorization

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4292
Author(s):  
Horng-Horng Lin ◽  
Harshad Kumar Dandage ◽  
Keh-Moh Lin ◽  
You-Teh Lin ◽  
Yeou-Jiunn Chen
Keyword(s):  
Deep Learning ◽  
Defect Detection ◽  
Crystalline Silicon ◽  
Cell Segmentation ◽  
Solar Pv ◽  
Single Crystalline Silicon ◽  
Defect Inspection ◽  
Defect Identification ◽  
Pv Modules ◽  
A Cell

Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate the effectiveness of solar PV modules, manufacturing defects are required to be identified. Conventional defect inspection in industries mainly depends on manual defect inspection by highly skilled inspectors, which may still give inconsistent, subjective identification results. In order to automatize the visual defect inspection process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based defect detection system with pseudo-colorization of defects is designed in this paper. High-resolution Electroluminescence (EL) images of single-crystalline silicon (sc-Si) solar PV modules are used in our study for the detection of defects and their quality inspection. Firstly, an automatic cell segmentation methodology is developed to extract cells from an EL image. Secondly, defect detection can be actualized by CNN-based defect detector and can be visualized with pseudo-colors. We used contour tracing to accurately localize the panel region and a probabilistic Hough transform to identify gridlines and busbars on the extracted panel region for cell segmentation. A cell-based defect identification system was developed using state-of-the-art deep learning in CNNs. The detected defects are imposed with pseudo-colors for enhancing defect visualization using K-means clustering. Our automatic cell segmentation methodology can segment cells from an EL image in about 2.71 s. The average segmentation errors along the x-direction and y-direction are only 1.6 pixels and 1.4 pixels, respectively. The defect detection approach on segmented cells achieves 99.8% accuracy. Along with defect detection, the defect regions on a cell are furnished with pseudo-colors to enhance the visualization.

Failure analysis of laser-textured surfaces

2000 ◽  
Vol 214 (5) ◽  
pp. 471-483 ◽  
Author(s):  
S Chilamakuri ◽  
X Zhao ◽  
B Bhushan
Keyword(s):  
Plastic Deformation ◽  
Operating Conditions ◽  
Disk Drives ◽  
Critical Number ◽  
Textured Surfaces ◽  
Tribological Behaviour ◽  
Magnetic Disk ◽  
Size And Shape ◽  
Ultrahigh Density ◽  
Theoretical Results

Friction/stiction behaviour of ultrahigh-density magnetic disk drives can be controlled by controlling the size and shape of the laser bumps. Tribological behaviour of laser-textured disk surfaces depends on the size and shape of the laser bumps, bump density and operating conditions. In this study, theoretical and experimental analyses have been carried out on nine different laser-textured disk surfaces. Stiction and friction experiments have been carried out on sombrero, V-type and W-type laser-textured disks and these results are compared with theoretical results. A good correlation is obtained between experimental and theoretical results. The effect of laser bump uniformity on critical number of bumps required to prevent plastic deformation and stiction has also been studied.

Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study

2018 ◽  
Vol 06 (02) ◽  
pp. 95-118 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar ◽  
Paul H. Guentert ◽  
Mohammad Sarim
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Operating Conditions ◽  
Computational Time ◽  
Safe Operation ◽  
Sense And Avoid ◽  
Planning Algorithms ◽  
And Control ◽  
Global And Local ◽  
Further Development

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information.

Laminar flame speed correlations for methane, ethane, propane and their mixtures, and natural gas and gasoline for spark-ignition engine simulations

2017 ◽  
Vol 18 (9) ◽  
pp. 951-970 ◽  
Author(s):  
Riccardo Amirante ◽  
Elia Distaso ◽  
Paolo Tamburrano ◽  
Rolf D Reitz
Keyword(s):  
Natural Gas ◽  
Laminar Flame ◽  
Spark Ignition ◽  
Flame Speed ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Computational Time ◽  
Laminar Flame Speed ◽  
Spark Ignition Engines ◽  
Empirical Correlations

The laminar flame speed plays an important role in spark-ignition engines, as well as in many other combustion applications, such as in designing burners and predicting explosions. For this reason, it has been object of extensive research. Analytical correlations that allow it to be calculated have been developed and are used in engine simulations. They are usually preferred to detailed chemical kinetic models for saving computational time. Therefore, an accurate as possible formulation for such expressions is needed for successful simulations. However, many previous empirical correlations have been based on a limited set of experimental measurements, which have been often carried out over a limited range of operating conditions. Thus, it can result in low accuracy and usability. In this study, measurements of laminar flame speeds obtained by several workers are collected, compared and critically analyzed with the aim to develop more accurate empirical correlations for laminar flame speeds as a function of equivalence ratio and unburned mixture temperature and pressure over a wide range of operating conditions, namely [Formula: see text], [Formula: see text] and [Formula: see text]. The purpose is to provide simple and workable expressions for modeling the laminar flame speed of practical fuels used in spark-ignition engines. Pure compounds, such as methane and propane and binary mixtures of methane/ethane and methane/propane, as well as more complex fuels including natural gas and gasoline, are considered. A comparison with available empirical correlations in the literature is also provided.

Artificial intelligence technique for estimating PV modules performance ratio under outdoor operating conditions

2018 ◽  
Vol 10 (5) ◽  
pp. 053505 ◽  
Author(s):  
Alain K. Tossa ◽  
Y. M. Soro ◽  
Y. Coulibaly ◽  
Y. Azoumah ◽  
Anne Migan-Dubois ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Operating Conditions ◽  
Performance Ratio ◽  
Artificial Intelligence Technique ◽  
Pv Modules ◽  
Intelligence Technique

scholarly journals Energy-Dissipation Limits in Variance-Based Computing

2018 ◽  
Vol 17 (02) ◽  
pp. 1850013
Author(s):  
Sri Harsha Kondapalli ◽  
Xuan Zhang ◽  
Shantanu chakrabartty
Keyword(s):  
Energy Dissipation ◽  
Thermal Noise ◽  
Operating Conditions ◽  
Superior Performance ◽  
Energy Scavenging ◽  
Logic Device ◽  
Additional Energy ◽  
Fundamental Limits ◽  
Bit Flip ◽  
Theoretical Results

Variance-based logic (VBL) uses the fluctuations or the variance in the state of a particle or a physical quantity to represent different logic levels. In this paper, we show that compared to the traditional bi-stable logic representation, the variance-based representation can theoretically achieve a superior performance trade-off (in terms of energy dissipation and information capacity) when operating at fundamental limits imposed by thermal noise. We show that, in addition to the universal KT ln(1/[Formula: see text]) energy dissipation required for a single bit flip, a bi-stable logic device needs to dissipate at least 4.35[Formula: see text]KT/bit of energy, whereas under similar operating conditions, a VBL device reduces the additional energy dissipation requirements down to sub-KT/bit. These theoretical results are generally enough to be applicable to different instantiations and variants of VBL ranging from digital processors based on energy-scavenging or to processors based on the emerging valleytronic devices.

scholarly journals Smoothed Particle Hydrodynamics Simulation of a Mariculture Platform under Waves

Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2847
Author(s):  
Feng Zhang ◽  
Li Zhang ◽  
Yanshuang Xie ◽  
Zhiyuan Wang ◽  
Shaoping Shang
Keyword(s):  
Smoothed Particle Hydrodynamics ◽  
Graphics Processing Units ◽  
Degrees Of Freedom ◽  
High Tide ◽  
Theoretical Data ◽  
Emergency Evacuation ◽  
Water Levels ◽  
Computational Time ◽  
Particle Hydrodynamics ◽  
Smoothed Particle

This work investigates the dynamic behaviors of floating structures with moorings using open−source software for smoothed particle hydrodynamics. DualSPHysics permits us to use graphics processing units to recreate designs that include complex calculations at high resolution with reasonable computational time. A free damped oscillation was simulated, and its results were compared with theoretical data to validate the numerical model developed. The simulated three degrees of freedom (3−DoF) (surge, heave, and pitch) of a rectangular floating box have excellent consistency with experimental data. MoorDyn was coupled with DualSPHysics to include a mooring simulation. Finally, we modelled and simulated a real mariculture platform on the coast of China. We simulated the 3−DoF of this mariculture platform under a typical annual wave and a Typhoon Dujuan wave. The motion was light and gentle under the typical annual wave but vigorous under the Typhoon Dujuan wave. Experiments at different tidal water levels revealed an earlier motion response and smaller motion range during the high tide. The results reveal that DualSPHysics combined with MoorDyn is an adaptive scheme to simulate a coupled fluid–solid–mooring system. This work provides support to disaster warning, emergency evacuation, and proper engineering design.

scholarly journals Feasibility Study of the Technical and Economic Performance of Grid-Connected PV System for Selected Rooftops in UTHM

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Mohamad Fakrie Mohamad Ali ◽  
◽  
Mohd Noor Abdullah ◽  
Keyword(s):  
Feasibility Study ◽  
Crystalline Silicon ◽  
Electricity Consumption ◽  
Payback Period ◽  
Net Energy ◽  
Pv System ◽  
Pv Module ◽  
Electricity Bill ◽  
Pv Modules ◽  
Energy Metering

This paper presents the feasibility study of the technical and economic performances of grid-connected photovoltaic (PV) system for selected rooftops in Universiti Tun Hussein Onn Malaysia (UTHM). The analysis of the electricity consumption and electricity bill data of UTHM campus show that the monthly electricity usage in UTHM campus is very high and expensive. The main purpose of this project is to reduce the annual electricity consumption and electricity bill of UTHM with Net Energy Metering (NEM) scheme. Therefore, the grid-connected PV system has been proposed at Dewan Sultan Ibrahim (DSI), Tunku Tun Aminah Library (TTAL), Fakulti Kejuruteraan Awam dan Alam Bina (FKAAS) and F2 buildings UTHM by using three types of PV modules which are mono-crystalline silicon (Mono-Si), poly-crystalline silicon (Poly-Si) and Thin-film. These three PV modules were modeled, simulated and calculated using Helioscope software with the capacity of 2,166.40kWp, 2,046.20kWp and 1,845kWp respectively for the total rooftop area of 190,302.9 ft². The economic analysis was conducted on the chosen three installed PV modules using RETScreen software. As a result, the Mono-Si showed the best PV module that can produce 2,332,327.40 kWh of PV energy, 4.4% of CO₂ reduction, 9.3 years of payback period considering 21 years of the contractual period and profit of RM4,932,274.58 for 11.7 years after payback period. Moreover, the proposed installation of 2,166.40kWp (Mono-SI PV module) can reduce the annual electricity bill and CO2 emission of 3.6% (RM421,561.93) and 4.4% (1,851.40 tCO₂) compared to the system without PV system.

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