scholarly journals Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Xiangqing Jiao ◽  
Yuan Liao ◽  
Thai Nguyen
Keyword(s):  
Statistical Analysis ◽  
System Analysis ◽  
Research Work ◽  
Field Measurements ◽  
Model Verification ◽  
Verification And Validation ◽  
Load Model ◽  
Load Models ◽  
Utility System ◽  
Model Verification And Validation

AbstractAccurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model’s effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model’s accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.

Exposing System and Model Disparity and Agreement Using Wavelets

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Andrew D. Atkinson ◽  
Raymond R. Hill ◽  
Joseph J. Pignatiello ◽  
G. Geoffrey Vining ◽  
Edward D. White ◽  
...  
Keyword(s):  
Development Process ◽  
Model Development ◽  
Model Verification ◽  
Verification And Validation ◽  
High Dimensional ◽  
Model Data ◽  
Accurate Representation ◽  
Model Verification And Validation ◽  
Model Development Process ◽  
Functional Output

Model verification and validation (V&V) remain a critical step in the simulation model development process. A model requires verification to ensure that it has been correctly transitioned from a conceptual form to a computerized form. A model also requires validation to substantiate the accurate representation of the system it is meant to simulate. Validation assessments are complex when the system and model both generate high-dimensional functional output. To handle this complexity, this paper reviews several wavelet-based approaches for assessing models of this type and introduces a new concept for highlighting the areas of contrast and congruity between system and model data. This concept identifies individual wavelet coefficients that correspond to the areas of discrepancy between the system and model.

The role of nondeterminism in model verification and validation

2006 ◽  
Vol 25 (1/2/3) ◽  
pp. 144 ◽  
Author(s):  
Ben H. Thacker ◽  
Mark C. Anderson ◽  
Paul E. Senseny ◽  
Edward A. Rodriguez
Keyword(s):  
Model Verification ◽  
Verification And Validation ◽  
Model Verification And Validation

scholarly journals Wind Energy High-Fidelity Model Verification and Validation Roadmap

2020 ◽  
Author(s):  
David Charles Maniaci ◽  
Patrick J. Moriarty ◽  
Matthew F. Barone ◽  
Matthew J. Churchfield ◽  
Michael A. Sprague ◽  
...  
Keyword(s):  
Wind Energy ◽  
Model Verification ◽  
Verification And Validation ◽  
High Fidelity ◽  
Model Verification And Validation ◽  
Fidelity Model

Debris flow interaction with structures: challenges to traditional load models

2020 ◽  
Author(s):  
Alessandro Leonardi ◽  
Andrea Pasqua ◽  
Marina Pirulli
Keyword(s):  
Debris Flow ◽  
Relative Size ◽  
Nonlinear Function ◽  
Field Measurements ◽  
Italian Alps ◽  
Load Model ◽  
Flow Energy ◽  
Load Models ◽  
Maintenance Work ◽  
Flow Through

<p>Debris flow barriers often feature one or more filter elements, i.e. narrow outlets that induce deposition of the coarsest sediments, while allowing water and fines to filter through. Slit dams and steel nets are examples of this type of barriers. The design of the filter elements must balance the need to trap boulders and to dissipate the flow energy, while keeping maintenance work as low as possible.</p><p>Filter barriers elude the traditional load model prescribed by guidelines. Under some conditions, the outlets can clog with large boulders. The time necessary for this to happen mainly depends on the relative size between boulder and outlet, and is a nonlinear function of the flow composition. In any case, the main clogging mechanism is the formation of granular arches. These can induce significant load also in directions different from the main direction of the incoming flow.</p><p>Unless the barrier is specifically designed to withstand this type of load, granular arches, but also prolonged flow through the outlet, can induce deterioration and loss of functionality of the structure. In this work, we estimate these effects employing a combination of discrete- and continuum-based numerical methods. We evaluate the performance of two types of debris-resisting barriers, comparing the results with laboratory measurements and with the outcome of a monitoring campaign on a real barrier located in the Italian alps.</p><p> </p><p> </p><p>References:</p><p>Leonardi, A., Goodwin, G. R., & Pirulli, M. (2019). The force exerted by granular flows on slit dams. Acta Geotechnica, 14(6), 1949–1963.</p><p>Leonardi, A., & Pirulli, M. (2020). Analysis of the load exerted by debris flows on filter barriers : Comparison between numerical results and field measurements. Computer & Geotechnics, 118, 103311.</p>

scholarly journals Is Precipitation a Good Metric for Model Performance?

2019 ◽  
Vol 100 (2) ◽  
pp. 223-233 ◽  
Author(s):  
Francisco J. Tapiador ◽  
Rémy Roca ◽  
Anthony Del Genio ◽  
Boris Dewitte ◽  
Walt Petersen ◽  
...  
Keyword(s):  
Quantitative Measurement ◽  
Climate Models ◽  
Model Performance ◽  
Model Verification ◽  
Verification And Validation ◽  
Weather And Climate ◽  
Model Verification And Validation ◽  
Global Precipitation Mission ◽  
Global Precipitation

AbstractPrecipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients among all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties, and there are even notable differences among different reference datasets. Several additional issues sometimes lead to questions about its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation and the crucial role of highly precise and reliable satellite estimates, such as those from NASA’s Global Precipitation Mission Core Observatory.

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