A Model-Based Approach for Small-Signal Stability Assessment of Unbalanced Power Systems

In this paper, a modeling technique for small-signal stability assessment of unbalanced power systems is presented. Since power distribution systems are inherently unbalanced, due to its lines and loads characteristics, and the penetration of distributed generation into these systems is increasing nowadays, such a tool is needed in order to ensure a secure and reliable operation of these systems. The main contribution of this paper is the development of a phasor-based model for the study of dynamic phenomena in unbalanced power systems. Using an assumption on the net torque of the generator, it is possible to precisely define an equilibrium point for the phasor model of the system, thus enabling its linearization around this point, and, consequently, its eigenvalue/eigenvector analysis for small-signal stability assessment. The modeling technique presented here was compared to the dynamic behavior observed in ATP simulations and the results show that, for the generator and controller models used, the proposed modeling approach is adequate and yields reliable and precise results.

Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.

Changes in a nanoparticle's spectroscopic signal mediated by the local environment

Using a first-principles theoretical model the adsorption of a methyl radical on different sized silver nanoparticles is compared to the adsorption of the same radical on model surfaces. Calculations of our structural, dynamical and electronic properties indicated that small changes in the local environment will lead to small changes in infrared (IR) wavenumbers, but in dramatic changes in the IR signal. Our calculations indicate the lower the adsorption site coordination, the higher is the signal strength, suggesting that small changes in the electronic charge distribution will result in bigger changes in the polarizability and hence in the spectroscopic signal intensity. This effect explains, among others, the signal magnification observed for nanoparticles in surface enhanced Raman spectroscopic (SERS) experiments.

Hybrid density functional study of small Rh-n (n=2-15) clusters

The physical properties of small rhodium clusters, Rh-n, have been in debate due to the shortcomings of density functional theory (DFT). To help in the solution of those problems, we obtained a set of putative lowest energy structures for small Rh-n (n = 2-15) clusters employing hybrid-DFT and the generalized gradient approximation (GGA). For n = 2-6, both hybrid and GGA functionals yield similar ground-state structures (compact), however, hybrid favors compact structures for n = 7-15, while GGA favors open structures based on simple cubic motifs. Thus, experimental results are crucial to indicate the correct ground-state structures, however, we found that a unique set of structures (compact or open) is unable to explain all available experimental data. For example, the GGA structures (open) yield total magnetic moments in excellent agreement with experimental data, while hybrid structures (compact) have larger magnetic moments compared with experiments due to the increased localization of the 4d states. Thus, we would conclude that GGA provides a better description of the Rh-n clusters, however, a recent experimental-theoretical study [ Harding et al., J. Chem. Phys. 133, 214304 (2010)] found that only compact structures are able to explain experimental vibrational data, while open structures cannot. Therefore, it indicates that the study of Rh-n clusters is a challenging problem and further experimental studies are required to help in the solution of this conundrum, as well as a better description of the exchange and correlation effects on the Rh n clusters using theoretical methods such as the quantum Monte Carlo method.

Quantum Monte Carlo study of small aluminum clusters Al-n (n=2-13)

Using fixed node diffusion quantum Monte Carlo (FN-DMC) simulations and density functional theory (DFT) within the generalized gradient approximations, we calculate the total energies of the relaxed and unrelaxed neutral, cationic, and anionic aluminum clusters, Al-n (n = 1-13). From the obtained total energies, we extract the ionization potential and electron detachment energy and compare with previous theoretical and experimental results. Our results for the electronic properties from both the FN-DMC and DFT calculations are in reasonably good agreement with the available experimental data. A comparison between the FN-DMC and DFT results reveals that their differences are a few tenths of electron volt for both the ionization potential and the electron detachment energy. We also observe two distinct behaviors in the electron correlation contribution to the total energies from smaller to larger clusters, which could be assigned to the structural transition of the clusters from planar to three-dimensional occurring at n = 4 to 5.

Encapsulation of small magnetic clusters in fullerene cages: A density functional theory investigation within van der Waals corrections

The encapsulation of magnetic transition-metal (TM) clusters inside carbon cages (fullerenes, nanotubes) has been of great interest due to the wide range of applications, which spread from medical sensors in magnetic resonance imaging to photonic crystals. Several theoretical studies have been reported; however, our atomistic understanding of the physical properties of encapsulated magnetic TM 3d clusters is far from satisfactory. In this work, we will report general trends, derived from density functional theory within the generalized gradient approximation proposed by Perdew, Burke, and Ernzerhof (PBE), for the encapsulation properties of the TMm@C-n (TM = Fe, Co, Ni; m = 2-6, n = 60,70,80,90) systems. Furthermore, to understand the role of the van der Waals corrections to the physical properties, we employed the empirical Grimme's correction (PBE + D2). We found that both PBE and PBE + D2 functionals yield almost the same geometric parameters, magnetic and electronic properties, however, PBE + D2 strongly enhances the encapsulation energy. We found that the center of mass of the TMm clusters is displaced towards the inside C-n surfaces, except for large TMm clusters (m = 5 and 6). For few cases, e. g., Co-4 and Fe-4, the encapsulation changes the putative lowest-energy structure compared to the isolated TMm clusters. We identified few physical parameters that play an important role in the sign and magnitude of the encapsulation energy, namely, cluster size, fullerene equatorial diameter, shape, curvature of the inside C-n surface, number of TM atoms that bind directly to the inside C-n surface, and the van der Waals correction. The total magnetic moment of encapsulated TMm clusters decreases compared with the isolated TMm clusters, which is expected due to the hybridization of the d-p states, and strongly depends on the size and shape of the fullerene cages.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

MicroRNA miR-146b-5p regulates signal transduction of TGF-beta by repressing SMAD4 in thyroid cancer

MicroRNAs (miRNA) are small non-coding RNAs involved in post-transcriptional gene regulation that have crucial roles in several types of tumors, including papillary thyroid carcinoma (PTC). miR-146b-5p is overexpressed in PTCs and is regarded as a relevant diagnostic marker for this type of cancer. A computational search revealed that miR-146b-5p putatively binds to the 3' untranslated region (UTR) of SMAD4, an important member of the transforming growth factor beta (TGF-beta) signaling pathway. The TGF-beta pathway is a negative regulator of thyroid follicular cell growth, and the mechanism by which thyroid cancer cells evade its inhibitory signal remains unclear. We questioned whether the modulation of the TGF-beta pathway by miR-146b-5p can contribute to thyroid tumorigenesis. Luciferase reporter assay confirmed the direct binding of miR-146b-5p on the SMAD4 3'UTR. Specific inhibition of miR-146b-5p with a locked nucleic acid-modified anti-miR-146b oligonucleotide significantly increased SMAD4 levels in the human papillary carcinoma cell lines, TPC-1 and BCPAP. Moreover, suppression of miR-146b-5p increased the cellular response to the TGF-beta anti-proliferative signal, significantly decreasing the proliferation rate. The overexpression of miR-146b-5p in normal rat follicular PCCL3 cells decreased SMAD4 levels and disrupted TGF-beta signal transduction. MiR-146b-5p overexpression in PCCL3 cells also significantly increased cell proliferation in the absence of thyroid-stimulating hormone and conferred resistance to TGF-beta-mediated cell-cycle arrest. Additionally, the activation of thyroid most common oncogenes RET/PTC3 and BRAF in PCCL3 cells upregulated miR-146b-5p expression. Our results confirm the oncogenic role of miR-146b-5p in thyroid follicular cells and contribute to knowledge regarding the modulation of TGF-beta signal transduction by miRNAs in PTCs. Oncogene (2012) 31, 1910-1922; doi:10.1038/onc.2011.381; published online 29 August 2011