scholarly journals Parameters Identification of PV Triple-Diode Model Using Improved Generalized Normal Distribution Algorithm

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 995
Author(s):  
Mohamed Abdel-Basset ◽  
Reda Mohamed ◽  
Attia El-Fergany ◽  
Mohamed Abouhawwash ◽  
S. S. Askar
Keyword(s):  
Normal Distribution ◽  
Statistical Tests ◽  
Convergence Speed ◽  
Operating Conditions ◽  
Pv Systems ◽  
Optimization Framework ◽  
Principal Performance ◽  
Convergence Method ◽  
Generalized Normal Distribution ◽  
Statistical Metrics

To simulate the behaviors of photovoltaic (PV) systems properly, the best values of the uncertain parameters of the PV models must be identified. Therefore, this paper proposes a novel optimization framework for estimating the parameters of the triple-diode model (TDM) of PV units with different technologies. The proposed methodology is based on the generalized normal distribution optimization (GNDO) with two novel strategies: (i) a premature convergence method (PCM), and (ii) a ranking-based updating method (RUM) to accelerate the convergence by utilizing each individual in the population as much as possible. This improved version of GNDO is called ranking-based generalized normal distribution optimization (RGNDO). RGNDO is experimentally investigated on three commercial PV modules (Kyocera KC200GT, Ultra 85-P and STP 6-120/36) and a solar unit (RTC Si solar cell France), and its extracted parameters are validated based on the measured dataset points extracted at generalized operating conditions. It can be reported here that the best scores of the objective function are equal to 0.750839 mA, 28.212810 mA, 2.417084 mA, and 13.798273 mA for RTC cell, KC200GT, Ultra 85-P, and STP 6-120/36; respectively. Additionally, the principal performance of this methodology is evaluated under various statistical tests and for convergence speed, and is compared with a number of the well-known recent state-of-the-art algorithms. RGNDO is shown to outperform the other algorithms in terms of all the statistical metrics as well as convergence speed. Finally, the performance of the RGNDO is validated in various operating conditions under varied temperatures and sun irradiance levels.

scholarly journals Consistency of the Empirical Distributions of Navigation Positioning System Errors with Theoretical Distributions—Comparative Analysis of the DGPS and EGNOS Systems in the Years 2006 and 2014

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 31
Author(s):  
Mariusz Specht
Keyword(s):  
Normal Distribution ◽  
Root Mean Square ◽  
Statistical Tests ◽  
Position Error ◽  
Positioning System ◽  
Navigation Systems ◽  
Mean Square ◽  
Positioning Systems ◽  
Position Errors ◽  
System Errors

Positioning systems are used to determine position coordinates in navigation (air, land and marine). The accuracy of an object’s position is described by the position error and a statistical analysis can determine its measures, which usually include: Root Mean Square (RMS), twice the Distance Root Mean Square (2DRMS), Circular Error Probable (CEP) and Spherical Probable Error (SEP). It is commonly assumed in navigation that position errors are random and that their distribution are consistent with the normal distribution. This assumption is based on the popularity of the Gauss distribution in science, the simplicity of calculating RMS values for 68% and 95% probabilities, as well as the intuitive perception of randomness in the statistics which this distribution reflects. It should be noted, however, that the necessary conditions for a random variable to be normally distributed include the independence of measurements and identical conditions of their realisation, which is not the case in the iterative method of determining successive positions, the filtration of coordinates or the dependence of the position error on meteorological conditions. In the preface to this publication, examples are provided which indicate that position errors in some navigation systems may not be consistent with the normal distribution. The subsequent section describes basic statistical tests for assessing the fit between the empirical and theoretical distributions (Anderson-Darling, chi-square and Kolmogorov-Smirnov). Next, statistical tests of the position error distributions of very long Differential Global Positioning System (DGPS) and European Geostationary Navigation Overlay Service (EGNOS) campaigns from different years (2006 and 2014) were performed with the number of measurements per session being 900’000 fixes. In addition, the paper discusses selected statistical distributions that fit the empirical measurement results better than the normal distribution. Research has shown that normal distribution is not the optimal statistical distribution to describe position errors of navigation systems. The distributions that describe navigation positioning system errors more accurately include: beta, gamma, logistic and lognormal distributions.

scholarly journals Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller

2021 ◽  
Author(s):  
Mostafa Ahmed ◽  
Ibrahim Harbi ◽  
Ralph Kennel ◽  
Mohamed Abdelrahem
Keyword(s):  
Power Generation ◽  
Voltage Regulation ◽  
Operating Conditions ◽  
Switching Frequency ◽  
Atmospheric Conditions ◽  
Voltage Profile ◽  
Dual Mode ◽  
Power Extraction ◽  
Pv Systems ◽  
Power Operation

AbstractPhotovoltaic (PV) power systems are integrated with high penetration levels into the grid. This in turn encourages several modifications for grid codes to sustain grid stability and resilience. Recently, constant power management and regulation is a very common approach, which is used to limit the PV power production. Thus, this article proposes dual-mode power generation algorithm for grid-connected PV systems. The developed system considers the two-stage PV configuration for implementation, where the dual-mode power generation technique is executed within the DC–DC conversion (boost) stage. Most of the techniques adopted for dual-mode power operation employ the conventional perturb and observe method, which is known with unsatisfactory performance at fast-changing atmospheric conditions. Considering this issue, this study suggests a modified maximum power point tracker for power extraction. Furthermore, a new adaptive DC-link controller is developed to improve the DC-link voltage profile at different operating conditions. The adaptive DC-link controller is compared with the traditional PI controller for voltage regulation. The inverter control is accomplished using finite-set model predictive control with two control objectives, namely reference current tracking and switching frequency minimization. The overall control methodology is evaluated at different atmospheric and operating conditions using MATLAB/Simulink software.

scholarly journals A Tamper-Resistant Algorithm Using Blockchain for the Digital Tachograph

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 581
Author(s):  
Yongbae Kim ◽  
Juyong Back ◽  
Jongweon Kim
Keyword(s):  
Wireless Communication ◽  
Statistical Tests ◽  
Operating Conditions ◽  
External Memory ◽  
Data Recording ◽  
Storage Devices ◽  
Suggested Algorithm ◽  
Operation Conditions ◽  
Before And After ◽  
Verification Test

A tachograph in a vehicle records the vehicle operating conditions, such as speed, distance, brake operation conditions, acceleration, GPS information, etc., in intervals of one second. For accidents, the tachograph records information, such as the acceleration and direction of a vehicle traveling in intervals of 1/100 s for 10 s before and after the accident occurs as collision data. A vehicle equipped with a tachograph is obliged to upload operation data to administrative organizations periodically via other auxiliary storage devices like a USB attached external memory or online wireless communication. If there is a problem with the recorded contents, data may be at risk of being tampered with during the uploading process. This research proposed tamper-resistant technology based on blockchain for data in online and offline environments. The suggested algorithm proposed a new data recording mechanism that operates in low-level hardware of digital tachographs for tamper-resistance in light blockchains and on/offline situations. The average encoding time of the proposed light blockchain was 1.85 ms/Mb, while the average decoding time was 1.65 ms/Mb. With the outliers in statistical tests removed, the estimated average encoding and decoding time was 1.32 ms/Mb and 1.29 ms/Mb, respectively, and the tamper verification test detected all the tampered data.

scholarly journals Different Techniques to Mitigate Partial Shading in Photovoltaic Panels

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3863
Author(s):  
Tiago Alves ◽  
João Paulo N. Torres ◽  
Ricardo A. Marques Lameirinhas ◽  
Carlos A. F. Fernandes
Keyword(s):  
Cell Model ◽  
Research Work ◽  
Experimental Tests ◽  
Operating Conditions ◽  
Pv System ◽  
Partial Shading ◽  
System Architectures ◽  
Pv Systems ◽  
Advantages And Disadvantages ◽  
Pv Panel

The effect of partial shading in photovoltaic (PV) panels is one of the biggest problems regarding power losses in PV systems. When the irradiance pattern throughout a PV panel is inequal, some cells with the possibility of higher power production will produce less and start to deteriorate. The objective of this research work is to present, test and discuss different techniques to help mitigate partial shading in PV panels, observing and commenting the advantages and disadvantages for different PV technologies under different operating conditions. The motivation is to contribute with research, simulation, and experimental work. Several state-of-the-artsolutions to the problem will be presented: different topologies in the interconnection of the panels; different PV system architectures, and also introducing new solution hypotheses, such as different cell interconnections topologies. Alongside, benefits and limitations will be discussed. To obtain actual results, the simulation work was conducted by creating MATLAB/Simulink models for each different technique tested, all centered around the 1M5P PV cell model. The several techniques tested will also take into account different patterns and sizes of partial shading, different PV panel technologies, different values of source irradiation, and different PV array sizes. The results will be discussed and validated by experimental tests.

scholarly journals Particle Size Distribution of Various Soil Materials Measured by Laser Diffraction—The Problem of Reproducibility

Minerals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 465
Author(s):  
Cezary Polakowski ◽  
Magdalena Ryżak ◽  
Agata Sochan ◽  
Michał Beczek ◽  
Rafał Mazur ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Normal Distribution ◽  
Size Distribution ◽  
Precise Measurement ◽  
Soil Analysis ◽  
Statistical Tests ◽  
Diffraction Method ◽  
Laser Diffraction ◽  
Method Analysis

Particle size distribution is an important soil parameter—therefore precise measurement of this characteristic is essential. The application of the widely used laser diffraction method for soil analysis continues to be a subject of debate. The precision of this method, proven on homogeneous samples, has been implicitly extended to soil analyses, but this has not been sufficiently well confirmed in the literature thus far. The aim of this study is to supplement the information available on the precision of the method in terms of reproducibility of soil measurement and whether the reproducibility of soil measurement is characterized by a normal distribution. To estimate the reproducibility of the laser diffraction method, thirteen various soil samples were characterized, and results were analysed statistically. The coefficient of variation acquired was lowest (3.44%) for silt and highest for sand (23.28%). Five of the thirteen tested samples were characterized by a normal distribution. The fraction content of eight samples was not characterized by normal distribution, but the extent of this phenomenon varied between soils. Although the laser diffraction method is repeatable, the measurement of soil particle size distribution can have limited reproducibility. The main cause seems to be small amounts of sand particles. The error can be amplified by the construction of the dispersion unit. Non-parametric statistical tests should be used by default for soil laser diffraction method analysis.

scholarly journals Testing the Validity of a Link Function Assumption in Repeated Type-II Censored General Step-Stress Experiments

Sankhya B ◽  
2021 ◽  
Author(s):  
Stefan Bedbur ◽  
Thomas Seiche
Keyword(s):  
Null Hypothesis ◽  
Statistical Tests ◽  
Operating Conditions ◽  
Link Function ◽  
Asymptotic Results ◽  
Failure Data ◽  
Stress Levels ◽  
Log Linear ◽  
Multiple Samples ◽  
General Step

AbstractIn step-stress experiments, test units are successively exposed to higher usually increasing levels of stress to cause earlier failures and to shorten the duration of the experiment. When parameters are associated with the stress levels, one problem is to estimate the parameter corresponding to normal operating conditions based on failure data obtained under higher stress levels. For this purpose, a link function connecting parameters and stress levels is usually assumed, the validity of which is often at the discretion of the experimenter. In a general step-stress model based on multiple samples of sequential order statistics, we provide exact statistical tests to decide whether the assumption of some link function is adequate. The null hypothesis of a proportional, linear, power or log-linear link function is considered in detail, and associated inferential results are stated. In any case, except for the linear link function, the test statistics derived are shown to have only one distribution under the null hypothesis, which simplifies the computation of (exact) critical values. Asymptotic results are addressed, and a power study is performed for testing on a log-linear link function. Some improvements of the tests in terms of power are discussed.

scholarly journals Occlusal contacts evaluation along orthodontic treatment with clear aligners and fixed appliance

2021 ◽  
Vol 10 (8) ◽  
pp. e51310817726
Author(s):  
Isabelle Vital Ortiz ◽  
Paula Vanessa Pedron Oltramari ◽  
Graziela Hernandes Volpato ◽  
Thais Maria Freire Fernandes Poleti ◽  
Victor de Miranda Ladewig ◽  
...  
Keyword(s):  
Data Analysis ◽  
Normal Distribution ◽  
Significant Influence ◽  
Orthodontic Treatment ◽  
Statistical Tests ◽  
Orthodontic Appliance ◽  
Fixed Appliance ◽  
Significance Level ◽  
Parametric Test ◽  
Anova Test

The present research aim was to assess how occlusal contacts change along the initial 6 months of orthodontic treatment with fixed appliance and clear aligners. A sample with 40 patients was divided into 2 groups: Clear Aligners (CA) and Fixed Appliance (FA). In order to register occlusal contacts, patients were posit and instructed about how bite in habitual maximum intercuspidation. Registrations were perfomed monthly along 6 starting treatment months and noted in an occlusogram. A parametric test was applied to evaluate data since it presented a normal distribution according to Shapiro-Wilk test. For inter- and intergroup data analysis the Anova test was performed with a 5% significance level. Statistical tests were executed on Jamovi software (Jamovi Stats, Version1.2, Sydeney, Australia). There was a reduction in the amount of occlusal contacts for indivduals from both groups, CA and FA. Such reduction was more significative in the 3 starting months for FA group and between 3rd and 4th months for CA group. Therefore, the sort orthodontic appliance had no significant influence over occlusal contacts.

scholarly journals A Density Peak-Based Clustering Approach for Fault Diagnosis of Photovoltaic Arrays

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Peijie Lin ◽  
Yaohai Lin ◽  
Zhicong Chen ◽  
Lijun Wu ◽  
Lingchen Chen ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Local Density ◽  
Operating Conditions ◽  
Cluster Center ◽  
Pv System ◽  
Density Peak ◽  
Pv Systems ◽  
Distribution Features ◽  
Clustering Approach ◽  
Distance Vector

Fault diagnosis of photovoltaic (PV) arrays plays a significant role in safe and reliable operation of PV systems. In this paper, the distribution of the PV systems’ daily operating data under different operating conditions is analyzed. The results show that the data distribution features significant nonspherical clustering, the cluster center has a relatively large distance from any points with a higher local density, and the cluster number cannot be predetermined. Based on these features, a density peak-based clustering approach is then proposed to automatically cluster the PV data. And then, a set of labeled data with various conditions are employed to compute the minimum distance vector between each cluster and the reference data. According to the distance vector, the clusters can be identified and categorized into various conditions and/or faults. Simulation results demonstrate the feasibility of the proposed method in the diagnosis of certain faults occurring in a PV array. Moreover, a 1.8 kW grid-connected PV system with6×3 PVarray is established and experimentally tested to investigate the performance of the developed method.

MLE for the γ-order generalized Normal distribution

2014 ◽  
Vol 34 (1-2) ◽  
pp. 143 ◽  
Author(s):  
Christos P. Kitsos ◽  
Thomas L. Toulias ◽  
Vassilios G. Vassiliadis
Keyword(s):  
Normal Distribution ◽  
Generalized Normal Distribution
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