Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System

Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative data. However, another type of uncertainty (epistemic uncertainty) must be accounted for in the modeling, due to incomplete knowledge of the phenomena and imprecise evaluation of the related characteristic parameters. In circumstances of few informative data, this type of uncertainty calls for alternative methods of representation, propagation, analysis and interpretation. In this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of DG systems modeling for adequacy assessment. Probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. Evidence theory is used to incorporate the two uncertainties under a single framework. Based on the plausibility and belief functions of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system adapted from the IEEE 34 nodes distribution test feeder. Compared to the pure probabilistic approach, it is shown that the hybrid propagation is capable of explicitly expressing the imprecision in the knowledge on the DG parameters into the final adequacy values assessed. It also effectively captures the growth of uncertainties with higher DG penetration levels

Имитационное моделирование случайных процессов в СМ-ДЭС

Предлагаются технология и программное обеспечение имитационного моделирования широкого класса случайных процессов. Представлены примеры решения двух известных задач теории вероятностей и теории надежности, связанных с анализом случайных процессов, методом имитационного моделирования в пакете СМ-ДЭС. Показана возможность решения широкого спектра других прикладных задач.Пропонуються технологія і програмне забезпечення імітаційного моделювання широкого класу випадкових процесів. Наведені приклади вирішення двох відомих задач теорії ймовірностей і теорії надійності, пов'язаних з аналізом випадкових процесів, методом імітаційного моделювання в пакеті СМ-ДЕС. Показано можливість вирішення широкого спектру інших прикладних задач.Technology and software are offered for simulation modeling of the broad class of the random processes. There are two well-known problems of probability theory and reliability theory associated with analysis of random processes. The article contains examples of solving these problems by simulation in the package SM-DES. Possibility of solving a wide range of other applications is also presented

Direct 2D measurement of time-averaged forces and pressure amplitudes in acoustophoretic devices using optical trapping

Ultrasonic standing waves are increasingly applied in the manipulation and sorting of micrometer-sized particles in microfluidic cells. To optimize the performance of such devices, it is essential to know the exact forces that the particles experience in the acoustic wave. Although much progress has been made via analytical and numerical modeling, the reliability of these methods relies strongly on the assumptions used, e.g. the boundary conditions. Here, we have combined an acoustic flow cell with an optical laser trap to directly measure the force on a single spherical particle in two dimensions. While performing ultrasonic frequency scans, we measured the time-averaged forces on single particles that were moved with the laser trap through the microfluidic cell. The cell including piezoelectric transducers was modeled with finite element methods. We found that the experimentally obtained forces and the derived pressure fields confirm the predictions from theory and modeling. This novel approach can now be readily expanded to other particle, chamber, and fluid regimes and opens up the possibility of studying the effects of the presence of boundaries, acoustic streaming, and non-linear fluids.ISSN:1473-0197ISSN:1473-018

The CIO role expectations instrument: validation and model testing

The validation of IS instruments has not been given the attention that it deserves. This study uses component-based structural equation modelling (PLS/SEM) to investigate the psychometric properties and possible modelling of the CIO role expectations instrument based on data obtained from 174 Australian CIOs. Results show that the CIO role expectation instrument has exhibited solid validity and reliability indices despite some minor weaknesses. The results also demonstrate the possibility to model the constructs of this instrument in different null and hierarchical models, and the validity of this instrument to measure the CIO role in different types of industries not just the healthcare sector in which it was developed. The results provide support for CIO role theory on two central issues: (1) CIOs are fulfilling a configuration of roles not just one specific role (2) the CIO roles can be grouped into two major categories: supply side roles and demand side roles

On the Statistical Modeling and Analysis of Repairable Systems

We review basic modeling approaches for failure and maintenance data from repairable systems. In particular we consider imperfect repair models, defined in terms of virtual age processes, and the trend-renewal process which extends the nonhomogeneous Poisson process and the renewal process. In the case where several systems of the same kind are observed, we show how observed covariates and unobserved heterogeneity can be included in the models. We also consider various approaches to trend testing. Modern reliability data bases usually contain information on the type of failure, the type of maintenance and so forth in addition to the failure times themselves. Basing our work on recent literature we present a framework where the observed events are modeled as marked point processes, with marks labeling the types of events. Throughout the paper the emphasis is more on modeling than on statistical inference.Comment: Published at http://dx.doi.org/10.1214/088342306000000448 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A nonparametric urn-based approach to interacting failing systems with an application to credit risk modeling

In this paper we propose a new nonparametric approach to interacting failing systems (FS), that is systems whose probability of failure is not negligible in a fixed time horizon, a typical example being firms and financial bonds. The main purpose when studying a FS is to calculate the probability of default and the distribution of the number of failures that may occur during the observation period. A model used to study a failing system is defined default model. In particular, we present a general recursive model constructed by the means of inter- acting urns. After introducing the theoretical model and its properties we show a first application to credit risk modeling, showing how to assess the idiosyncratic probability of default of an obligor and the joint probability of failure of a set of obligors in a portfolio of risks, that are divided into reliability classes