scholarly journals Quantify Photovoltaic Module Degradation using the Loss Factor Model Parameters

2017 ◽  
Author(s):  
C. Birk Jones ◽  
Bruce H. King ◽  
Joshua S. Stein ◽  
Justin S. Fada ◽  
Alan J. Curran ◽  
...  
Keyword(s):  
Loss Factor ◽  
Factor Model ◽  
Photovoltaic Module ◽  
Model Parameters

Lifetime Estimation of a Photovoltaic Module Subjected to Corrosion Due to Damp Heat Testing

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
R. Laronde ◽  
A. Charki ◽  
D. Bigaud
Keyword(s):  
Crystalline Silicon ◽  
Meteorological Data ◽  
Photovoltaic Module ◽  
Model Parameters ◽  
Solar Panels ◽  
Power Requirement ◽  
Pv Module ◽  
Accelerated Life ◽  
Mean Lifetime ◽  
Initial Power

In this paper, a methodology is presented for estimating the lifetime of a photovoltaic (PV) module. Designers guarantee an acceptable level of power (80% of the initial power) up to 25 yr for solar panels without having sufficient feedback to validate this lifetime. Accelerated life testing (ALT) can be carried out in order to determine the lifetime of the equipment. Severe conditions are used to accelerate the ageing of components and the reliability is then deduced in normal conditions, which are considered to be stochastic rather than constant. Environmental conditions at normal operations are simulated using IEC 61725 standard and meteorological data. The mean lifetime of a crystalline-silicon photovoltaic module that meets the minimum power requirement is estimated. The main results show the influence of lifetime distribution and Peck model parameters on the estimation of the lifetime of a photovoltaic module.

Wear-Factor Prediction Based on Data-Driven Inversion Technique for Casing Wear Estimation

2020 ◽  
Author(s):  
Manish K. Mittal ◽  
Robello Samuel ◽  
Aldofo Gonzales
Keyword(s):  
Physical Model ◽  
Factor Model ◽  
Data Driven ◽  
Wear Volume ◽  
Model Parameters ◽  
Wear Factor ◽  
Side Force ◽  
Inversion Technique ◽  
Casing Wear ◽  
Volume Output

Abstract Wear factor is an important parameter for estimating casing wear, yet the industry lacks a sufficient data-driven wear-factor prediction model based on previous data. Inversion technique is a data-driven method for evaluating model parameters for a setting wherein the input and output values for the physical model/equation are known. For this case, the physical equation to calculate wear volume has wear factor, side force, RPM, tool-joint diameter, and time for a particular operation (i.e., rotating on bottom, rotating off bottom, sliding, back reaming, etc.) as inputs. Except for wear factor, these values are either available or can be calculated using another physical model (wear-volume output is available from the drilling log). Wear factor is considered the model parameter and is estimated using the inversion technique method. The preceding analysis was performed using soft-string and stiff-string models for side-force calculations and by considering linear and nonlinear wear-factor models. An iterative approach was necessary for the nonlinear wear-factor model because of its complexity. Log data provide the remaining thickness of the casing, which was converted into wear volume using standard geometric calculations. A paper [1] was presented in OMC 2019 discussing a method for bridging the gap. A study was conducted in this paper for a real well based on the new method, and successful results were discussed. The current paper extends that study to another real well casing wear prediction with this novel approach. Some methods discussed are already included in the mentioned paper.

Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models

2016 ◽  
Vol 51 (2-3) ◽  
pp. 257-258 ◽  
Author(s):  
Andrea Hildebrandt ◽  
Oliver Lüdtke ◽  
Alexander Robitzsch ◽  
Christopher Sommer ◽  
Oliver Wilhelm
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Factor Model ◽  
Model Parameters ◽  
Continuous Variables

scholarly journals Measurement and validation of polysilicon photovoltaic module degradation rates over five years of field exposure in Oman

AIMS Energy ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1192-1212
Author(s):  
Honnurvali Mohamed Shaik ◽  
◽  
Adnan Kabbani ◽  
Abdul Manan Sheikh ◽  
Keng Goh ◽  
...  
Keyword(s):  
Loss Factor ◽  
Visual Loss ◽  
Short Circuit ◽  
Production Capacity ◽  
Short Circuit Current ◽  
Photovoltaic Module ◽  
Pv System ◽  
Field Exposure ◽  
Degradation Rates ◽  
Pv Modules

<abstract> <p>Degradation of PV modules have a severe impact on its power-producing capabilities thus affecting the reliability, performance over the long run. To understand the PV degradation happening under the influence of local environmental conditions a survey was conducted on six polycrystalline silicon-based PV modules over five years. It has been observed that the average degradation rates stood at 1.02%/year at irradiances 800 W/m<sup>2</sup> and 0.99%/year at irradiances 600 W/m<sup>2</sup>, which are almost double the manufacturer proposed values. Upon further investigations, it has been found that discoloration of encapsulant in modules 3, 5, and 6 have been the main factor causing the reduction of the short circuit current (I<sub>sc</sub>) thus affecting the overall power production capacity of the installed PV system. Considering the amount of time, resources and manpower invested to perform this survey an alternate way of estimating the PV degradation rates is also investigated. The exponential decay factor-based model is adopted to correlate the encapsulant discoloration seen on-site in the form of a mathematical equation to predict the current loss. This loss is defined as the visual loss factor in this paper. Further, the output I-V curves are simulated using MATLAB Simulink-based mathematical model which also integrates visual loss factor (VLF) losses into it. Such simulated I-V curves have shown a good match with the measured I-V curves at the same irradiance with an error less than 3%. Authors anticipate that this modelling approach can open the door for further research in developing algorithms that can simulate the PV degradation rates.</p> </abstract>

Estimation of Subject-Specific Heritabilities From Intra-Individual Variation: iFACE

2012 ◽  
Vol 15 (3) ◽  
pp. 393-400 ◽  
Author(s):  
Peter C. M. Molenaar ◽  
Dirk J. A. Smit ◽  
Dorret I. Boomsma ◽  
John R. Nesselroade
Keyword(s):  
Genetic Factor ◽  
Factor Model ◽  
Parametric Model ◽  
Specific Model ◽  
Model Parameters ◽  
Dizygotic Twin ◽  
Subject Specificity ◽  
Subject Specific ◽  
Genetic And Environmental Factors ◽  
Psychophysiological Data

A new genetic factor model for multivariate phenotypic time series, iFACE, is presented which allows for the estimation of subject-specific model parameters of genetic and environmental factors. The iFACE was applied to multivariate EEG registrations obtained with single dizygotic twin pairs. The results showed evidence for considerable subject-specificity in heritabilities and environmental effects. The assumption that the population is homogeneous (i.e., that each case in the population obeys the same parametric model), does not hold for these psychophysiological data, and its use should be critically reconsidered. We conclude that the iFACE provides a powerful new methodology to assess heterogeneity (subject-specificity) based on phenotypic observations.

The Aphasia Communication Outcome Measure (ACOM): Dimensionality, Item Bank Calibration, and Initial Validation

2015 ◽  
Vol 58 (3) ◽  
pp. 906-919 ◽  
Author(s):  
William D. Hula ◽  
Patrick J. Doyle ◽  
Clement A. Stone ◽  
Shannon N. Austermann Hula ◽  
Stacey Kellough ◽  
...  
Keyword(s):  
Outcome Measure ◽  
Factor Model ◽  
Measurement Model ◽  
Item Bank ◽  
Measurement Properties ◽  
Model Parameters ◽  
Good Precision ◽  
Good Convergence ◽  
Patient Reported ◽  
Communication Outcome

Purpose The purpose of this study is to investigate the structure and measurement properties of the Aphasia Communication Outcome Measure (ACOM), a patient-reported outcome measure of communicative functioning for persons with aphasia. Method Three hundred twenty-nine participants with aphasia responded to 177 items asking about communicative functioning. The data were analyzed using a categorical item factor analysis approach. Validity of ACOM scores on the basis of their convergence with performance-based, clinician-reported, and surrogate-reported assessments of communication was also assessed. Results Fifty-nine items that obtained adequate fit to a modified bifactor measurement model and functioned similarly across several demographic and clinical subgroupings were identified. The factor model estimates were transformed to item response theory graded response model parameters, and the resulting score estimates showed good precision and moderately strong convergence with other measures of communicative ability and functioning. A free software application for administration and scoring of the ACOM item bank is available from the first author. Conclusions The ACOM provides reliable measurement of patient-reported communicative functioning in aphasia. The results supported the validity of ACOM scores insofar as (a) factor analyses provided support for a coherent measurement model, (b) items functioned similarly across demographic and clinical subgroups, and (c) scores showed good convergence with measures of related constructs.

Construct Validity of the Maslach Burnout Inventory: Two Swedish Health Care Samples

2004 ◽  
Vol 20 (4) ◽  
pp. 320-338 ◽  
Author(s):  
Ulrika E. Hallberg ◽  
Magnus Sverke
Keyword(s):  
Health Care ◽  
Construct Validity ◽  
Factor Model ◽  
Strong Support ◽  
Maslach Burnout Inventory ◽  
Measurement Model ◽  
Personal Accomplishment ◽  
Model Parameters ◽  
Model Stability ◽  
Two Samples

Summary: Burnout has become a serious matter in workplace health, and the Maslach Burnout Inventory (MBI) is today the most widely used instrument for assessing the construct empirically. The present study examined the construct validity of a Swedish translation of the instrument for human service employees (MBI-HSS). Data from two samples of health care workers (N = 448 and N = 462) were used to test six propositions concerning dimensionality, internal consistency, measurement model stability, and relationships with predictors and outcomes. Support for the postulated three-factor model of emotional exhaustion, depersonalization, and (reduced) personal accomplishment as well as for adequate reliabilities of the dimensions was found. A post hoc modification of the MBI was suggested in order to improve model fit. Multi-group confirmatory factor analysis indicated stability of measurement model parameters across organizational settings. Moreover, the propositions about the association between the burnout dimensions, and predictors and outcomes were partly supported. Taken together, these tests provide strong support for the construct validity of the Swedish translation of the MBI-HSS.

scholarly journals Parametric Identification of the Models with Specified Quality Characteristics

2019 ◽  
Vol 29 (4) ◽  
pp. 480-495
Author(s):  
Olga G. Kantor ◽  
Semen I. Spivak ◽  
Nikolay D. Morozkin
Keyword(s):  
Experimental Data ◽  
Factor Model ◽  
Parametric Identification ◽  
Reaction Rate Constant ◽  
Quality Characteristics ◽  
Data Uncertainty ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Chemical Reaction Rate Constant ◽  
The Impact

Introduction. The model of a given structure should be identified based on the results of solving the problem of parametric identification. This model should provide the best possible the database development reproduction of the experimental data. The concept of “best” is not strictly structured. Therefore, the procedure for identifying such a model is subject to natural logic and includes the stages of data a determination of a set of acceptable models and subsequent selection of the best of them. If the set of acceptable models is large, the procedure for determining the best one can be time-consuming. In this regard, the development of methods for parametric identification, which at the stage of creating a set of acceptable models allows taking into account the qualitative aspects of the identified dependence, which are of interest to the researcher, is of particular importance. Materials and Methods. The set of acceptable methods in the problems of parametric identification largely depends on the type of the experimental data. Uncertainty for example, probabilistic and statistical methods are useful if the observed factors are random and subject to any law of probability distribution. If the conditions for the use of such methods are not met, it may be useful to present an approach based on identifying the boundaries of location of the model parameters that ensure the achievement of specified levels of quality characteristics. Results. The procedure of parametric identification of models is formalized. It is based on the use of maximum permissible parameter estimates and allows one to determining the set of parameter values that guarantee the achievement of the required qualitative level of experimental data description, including from the standpoint of analyzing the impact of changes in accord with requirements to the accuracy of their reproduction. The approbation of the developed method on the example of the construction of a one-factor model of chemical kinetics is presented. Discussion and Conclusion. It is shown that the obtained value of the chemical reaction rate constant, in accordance with the introduced criteria, provides acceptable accuracy, adequacy, and stability of the identified kinetic model. At the same time, the results of calculations revealed the information that can form the basis for planning experiments carried out in order to improve the accuracy of the experimental data.

Sign in / Sign up

Export Citation Format

Share Document