Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Load compensation in four-wire electrical power systems

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and another in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the methodology was adapted to accept different power factors for the system to be compensated. on the other hand, the determination of the compensation susceptances is based on the instantaneous values of the load currents. The results are obtained using the MatLab - Simulink environment.

Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fault section estimation in electric power systems using an optimization immune algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sistemas distribuídos aplicados à compressão e recuperação de imagens

Digital image processing is a field that demands great processing capacity. As such it becomes relevant to implement software that is based on the distribution of the processing into several nodes divided by computers belonging to the same network. Specifically discussed in this work are distributed algorithms of compression and expansion of images using the discrete cosine transform. The results show that the savings in processing time obtained due to the parallel algorithms in comparison to its sequential equivalents is a function that depends on the resolution of the image and the complexity of the involved calculation; that is efficiency is greater the longer the processing period is in terms of the time involved for the communication between the network points.

Critical temperature for first-order phase transitions in confined systems

We consider the Euclidean D-dimensional -lambda vertical bar phi vertical bar(4)+eta vertical bar rho vertical bar(6) (lambda,eta > 0) model with d (d <= D) compactified dimensions. Introducing temperature by means of the Ginzburg-Landau prescription in the mass term of the Hamiltonian, this model can be interpreted as describing a first-order phase transition for a system in a region of the D-dimensional space, limited by d pairs of parallel planes, orthogonal to the coordinates axis x(1), x(2),..., x(d). The planes in each pair are separated by distances L-1, L-2, ... , L-d. We obtain an expression for the transition temperature as a function of the size of the system, T-c({L-i}), i = 1, 2, ..., d. For D = 3 we particularize this formula, taking L-1 = L-2 = ... = L-d = L for the physically interesting cases d = 1 (a film), d = 2 (an infinitely long wire having a square cross-section), and for d = 3 (a cube). For completeness, the corresponding formulas for second-order transitions are also presented. Comparison with experimental data for superconducting films and wires shows qualitative agreement with our theoretical expressions.

Artificial immune systems for classification of petroleum well drilling operations

This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning.

Processing of high performance composites based on peek by aqueous suspension prepregging

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electronic ballast for multiple fluorescent lamp systems

An electronic ballast for multiple tubular fluorescent lamp systems is presented. The proposed structure has a high value for the power factor, a dimming capability, and soft switching of the semiconductor devices operated at high frequencies. A zero-current switching pulse width modulated SEPIC converter is used as the rectifying stage and it is controlled using the instantaneous average input current technique. The inverting stage consists of classical resonant half-bridge converter with series-resonant parallel-loaded filters. The dimming control technique is based on varying the switching frequency and monitoring the phase shift of the current drained by the filters and lamps in order to establish a closed loop control. Experimental results are presented that validate the theoretical analysis.

High current-density anodic electro-dissolution in flow-injection systems for the determination of aluminium, copper and zinc in non-ferroalloys by flame atomic absorption spectrometry

An automatic Procedure with a high current-density anodic electrodissolution unit (HDAE) is proposed for the determination of aluminium, copper and zinc in non-ferroalloys by flame atonic absorption spectrometry, based on the direct solid analysis. It consists of solenoid valve-based commutation in a flow-injection system for on-line sample electro-dissolution and calibration with one multi-element standard, an electrolytic cell equipped with two electrodes (a silver needle acts as cathode, and sample as anode), and an intelligent unit. The latter is assembled in a PC-compatible microcomputer for instrument control, and far data acquisition and processing. General management of the process is achieved by use of software written in Pascal. Electrolyte compositions, flow rates, commutation times, applied current and electrolysis time mere investigated. A 0.5 mol l(-1) HNO3 solution was elected as electrolyte and 300 A/cm(2) as the continuous current pulse. The performance of the proposed system was evaluated by analysing aluminium in Al-allay samples, and copper/zinc in brass and bronze samples, respectively. The system handles about 50 samples per hour. Results are precise (R.S.D < 2%) and in agreement with those obtained by ICP-AES and spectrophotometry at a 95% confidence level.

Speedup and scalability analysis of Master-Slave applications on large heterogeneous clusters

Although cluster environments have an enormous potential processing power, real applications that take advantage of this power remain an elusive goal. This is due, in part, to the lack of understanding about the characteristics of the applications best suited for these environments. This paper focuses on Master/Slave applications for large heterogeneous clusters. It defines application, cluster and execution models to derive an analytic expression for the execution time. It defines speedup and derives speedup bounds based on the inherent parallelism of the application and the aggregated computing power of the cluster. The paper derives an analytical expression for efficiency and uses it to define scalability of the algorithm-cluster combination based on the isoefficiency metric. Furthermore, the paper establishes necessary and sufficient conditions for an algorithm-cluster combination to be scalable which are easy to verify and use in practice. Finally, it covers the impact of network contention as the number of processors grow. (C) 2007 Elsevier B.V. All rights reserved.

Oxytocinergic and serotonergic systems involvement in sodium intake regulation: satiety or hypertonicity markers?

Previous studies demonstrated the inhibitory participation of serotonergic ( 5-HT) and oxytocinergic (OT) neurons on sodium appetite induced by peritoneal dialysis (PD) in rats. The activity of 5-HT neurons increases after PD- induced 2% NaCl intake and decreases after sodium depletion; however, the activity of the OT neurons appears only after PD-induced 2% NaCl intake. To discriminate whether the differential activations of the 5-HT and OT neurons in this model are a consequence of the sodium satiation process or are the result of stimulation caused by the entry to the body of a hypertonic sodium solution during sodium access, we analyzed the number of Fos-5-HT- and Fos-OT-immunoreactive neurons in the dorsal raphe nucleus and the paraventricular nucleus of the hypothalamus-supraoptic nucleus, respectively, after isotonic vs. hypertonic NaCl intake induced by PD. We also studied the OT plasma levels after PD- induced isotonic or hypertonic NaCl intake. Sodium intake induced by PD significantly increased the number of Fos-5- HT cells, independently of the concentration of NaCl consumed. In contrast, the number of Fos-OT neurons increased after hypertonic NaCl intake, in both depleted and nondepleted animals. The OT plasma levels significantly increased only in the PD- induced 2% NaCl intake group in relation to others, showing a synergic effect of both factors. In summary, 5-HT neurons were activated after body sodium status was reestablished, suggesting that this system is activated under conditions of satiety. In terms of the OT system, both OT neural activity and OT plasma levels were increased by the entry of hypertonic NaCl solution during sodium consumption, suggesting that this system is involved in the processing of hyperosmotic signals.

Mechanical and electrical driving field induced high-frequency dielectric anomalies in ferroelectric systems

Polycrystalline or single-crystal ferroelectric materials present dielectric dispersion in the frequency range 100 MHz-1 GHz that has been attributed to a dispersive ( relaxation-like) mechanism as well as a resonant mechanism. Particularly in 'normal' ferroelectric materials, a dielectric response that is indistinguishable from dispersion or a resonance has been reported. Nevertheless, the reported results are not conclusive enough to distinguish each mechanism clearly. A detailed study of the dielectric dispersion phenomenon has been carried out in PbTiO3-based ferroelectric ceramics, with the composition Pb1-xLaxTiO3 (x = 0.15), over a wide range of temperatures and frequencies, including microwave frequencies. The dielectric response of La-modified lead titanate ferroelectric ceramics, in 'virgin' and poled states, has been investigated in the temperature and frequency ranges 300-450 K and 1 kHz-2 GHz, respectively. The results revealed that the frequency dependence of the dielectric anomalies, depending on the measuring direction with respect to the orientation of the macroscopic polarization, may be described as a general mechanism related to an 'over-damped' resonant process. Applying either a uniaxial stress along the measurement field direction or a poling electric field parallel and/or perpendicular to the measuring direction, a resonant response of the real and imaginary components of the dielectric constant is observed, in contrast to the dispersion behavior obtained in the absence of the stress, for the 'virgin' samples. Both results, resonance and/or dispersion, can be explained by considering a common mechanism involving a resonant response (damped and/or over-damped) which is strongly affected by a ferroelastic-ferroelectric coupling, contributing to the low-field dielectric constant.