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.

A Low Power CMOS Voltage Regulator for a Wireless Blood Pressure Biosensor

This paper describes a CMOS implementation of a linear voltage regulator (LVR) used to power up implanted physiological signal systems, as it is the case of a wireless blood pressure biosensor. The topology is based on a classical structure of a linear low-dropout regulator. The circuit is powered up from an RF link, thus characterizing a passive radio frequency identification (RFID) tag. The LVR was designed to meet important features such as low power consumption and small silicon area, without the need for any external discrete components. The low power operation represents an essential condition to avoid a high-energy RF link, thus minimizing the transmitted power and therefore minimizing the thermal effects on the patient's tissues. The project was implemented in a 0.35-mu m CMOS process, and the prototypes were tested to validate the overall performance. The LVR output is regulated at 1 V and supplies a maximum load current of 0.5 mA at 37 degrees C. The load regulation is 13 mV/mA, and the line regulation is 39 mV/V. The LVR total power consumption is 1.2 mW.

A novel method for power quality multiple disturbance decomposition based on Independent Component Analysis

In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.

Alpha-band power in the left frontal cortex discriminates the execution of fixed stimulus during saccadic eye movement

Introduction: The saccadic paradigm has been used to investigate specific cortical networks involving attention. The behavioral and electrophysiological investigations of the SEM contribute significantly to the understanding of attentive patterns presented of neurological and psychiatric disorders and sports performance. Objective: The current study aimed to investigate absolute alpha power changes in sensorimotor brain regions and the frontal eye fields during the execution of a saccadic task. Methods: Twelve healthy volunteers (mean age: 26.25; SD: +/- 4.13) performed a saccadic task while the electroencephalographic signal was simultaneously recorded for the cerebral cortex electrodes. The participants were instructed to follow the LEDs with their eyes, being submitted to two different task conditions: a fixed pattern versus a random pattern. Results: We found a moment main effect for the C3, C4, F3 and F4 electrodes and a condition main effect for the F3 electrode. We also found interaction between factor conditions and frontal electrodes. Conclusions: We conclude that absolute alpha power in the left frontal cortex discriminates the execution of the two stimulus presentation patterns during SEM. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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.

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.