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[en] When conducting sensitivity and uncertainty analysis, most of the global sensitivity techniques assume parameter independence. However, it is common that the parameters are correlated with each other. For models with correlated inputs, we propose that the contribution of uncertainty to model output by an individual parameter be divided into two parts: the correlated contribution (by the correlated variations, i.e. variations of a parameter which are correlated with other parameters) and the uncorrelated contribution (by the uncorrelated variations, i.e. the unique variations of a parameter which cannot be explained by any other parameters). So far, only a few studies have been conducted to obtain the sensitivity index for a model with correlated input. But these studies do not distinguish between the correlated and uncorrelated contribution of a parameter. In this study, we propose a regression-based method to quantitatively decompose the total uncertainty in model output into partial variances contributed by the correlated variations and partial variances contributed by the uncorrelated variations. The proposed regression-based method is then applied in three test cases. Results show that the regression-based method can successfully measure the uncertainty contribution in the case where the relationship between response and parameters is approximately linear
[en] The increasing attention given to global energy issues and the international policies needed to reduce greenhouse gas emissions have given a renewed stimulus to research interest in the linkages between the energy sector and economic performance at country level. In this paper, we analyse the causal relationship between economy and energy by adopting a Vector Error Correction Model for non-stationary and cointegrated panel data with a large sample of developed and developing countries and four distinct energy sectors. The results show that alternative country samples hardly affect the causality relations, particularly in a multivariate multi-sector framework.
[en] In this work, we consider an evolutionary prisoner's dilemma game on a homogeneous random network with the richest-following strategy adoption rule. By constructing homogeneous random networks from a regular ring graph, we investigate the effects of topological randomness on cooperation. In contrast to the ordinary view that the presence of small amount of shortcuts in ring graphs favors cooperation, we find the cooperation inhibition by weak topological randomness. The explanations on the observations are presented. (general)
[en] Highlights: ► We model the behavior of Gencos in the active and reactive power markets. ► Genco’s strategy is modeled as a bi-level optimization problem. ► The ISO’s market clearing model is modified with applying generator APFs. ► Good forecast of Genco’s information will increase the accuracy of proposed method. ► Obtained profit of Gencos depend on their bidding strategy. - Abstract: As Gencos are responsible for providing active and reactive power generation, they should devise good bidding strategies for energy and reactive power market. The paper describes a method for analyzing the competition among transmission-constrained Gencos with incomplete information. The proposed methodology employs the Supply Function Equilibrium (SFE) for modeling a Genco’s bidding strategy in energy market and uses Expected Payment Function (EPF) to construct a bidding framework in the reactive power market. The problem of finding the optimum strategy of Gencos is modeled as a bi-level optimization problem, where the upper sub-problem represents individual Genco’s payoff and the lower sub-problem solves the ISO’s market clearing problem. The ISO’s market clearing model is modified with applying generator Active Participation Factors to improve the voltage stability margin. The IEEE 39 bus test system is used to verify the effectiveness of the proposed method.
[en] Highlight: • We established a new evolutionary model of spatial prisoner's dilemma game dovetailed with indirect reciprocity. • Adding indirect reciprocity does not always increase the level of cooperation beyond the level of model without indirect reciprocity. • Two different reciprocity mechanisms can lead negative interference effect on cooperation. - Abstract: Network reciprocity is one of the key mechanisms to solve social dilemmas, and has attracted many researchers for the last decade. Here, we explore what happens if network reciprocity is dovetailed with indirect reciprocity. This is motivated by the idea that a player may utilize observed information to evaluate his neighbors. Simulations based on our minimal model reveal that adding indirect reciprocity does not always increase the level of cooperation beyond the level of model without indirect reciprocity. This implies that the combination of two different reciprocity mechanisms, each enhancing cooperation if applied independently, can lead negative interference effect on cooperation. The details of this depend on type of action assessment system determining what is good and bad. Interestingly, we found that a high level of information is not always superior to low levels of information.
[en] Some discrete distributions such as Bernoulli, binomial, geometric, negative binomial, Poisson, Polya–Aeppli, and others play an important role in applied problems of probability theory and mathematical statistics. We propose a variant of a multivariate distribution whose components have a given univariate discrete distribution. In fact we consider some very general variant of the so-called reduction method. We find the explicit form of the mass function and generating function of such distribution and study their properties. We prove that our construction is unique in natural exponential families of distributions. Our results are the generalization and unification of many results of other authors.