An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Artificial immune systems applied to optimal capacitor placement in radial distribution networks

The capacitor placement problem for radial distribution networks aims to determine capacitor types, sizes, locations and control scheme. This is a combinatorial problem that can be formulated as a mixed integer nonlinear program. The paper presents an algorithm inspired in artificial immune systems and developed for this specific problem. A good performance was obtained through experimental tests applied to known systems. © 2006 IEEE.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems

Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. So, mathematical model is a very important tool to guarantee the development of the neural network area. In this article we will introduce one series of mathematical demonstrations that guarantee the wavelets properties for the PPS functions. As application, we will show the use of PPS-wavelets in pattern recognition problems of handwritten digit through function approximation techniques.

Multidimensional polynomial powers of sigmoid (PPS) Wavelet neural networks

Wavelet functions have been used as the activation function in feedforward neural networks. An abundance of R&D has been produced on wavelet neural network area. Some successful algorithms and applications in wavelet neural network have been developed and reported in the literature. However, most of the aforementioned reports impose many restrictions in the classical backpropagation algorithm, such as low dimensionality, tensor product of wavelets, parameters initialization, and, in general, the output is one dimensional, etc. In order to remove some of these restrictions, a family of polynomial wavelets generated from powers of sigmoid functions is presented. We described how a multidimensional wavelet neural networks based on these functions can be constructed, trained and applied in pattern recognition tasks. As an example of application for the method proposed, it is studied the exclusive-or (XOR) problem.

Optimal reactive power flow via the modified barrier Lagrangian function approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks

The accurate identification of the nitrogen content in crop plants is extremely important since it involves economic aspects and environmental impacts. Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification involves a lot of nonlinear parametes and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Structural Basis of Importin-alpha-Mediated Nuclear Transport for Ku70 and Ku80

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

SMase II, a new sphingomyelinase D from Loxosceles laeta venom gland: Molecular cloning, expression, function and structural analysis

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

Structural basis for branching-enzyme activity of glycoside hydrolase family 57: Structure and stability studies of a novel branching enzyme from the hyperthermophilic archaeon Thermococcus Kodakaraensis KOD1

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

On the Baker-Akhiezer function in the AKNS scheme

Expressions for the Baker-Akhiezer function and their logarithmic space and time derivatives are derived in terms of the matrix elements of U - V matrices and 'squared basis functions'. These expressions generalize the well known formulas for the KdV equation case and establish links between different forms of the Whitham averaging procedure.

Myocyte necrosis is the basis for fibrosis inrenovascular hypertensive rats

The pathogenesis of fibrosis and the functional features of pressure overload myocardial hypertrophy are still controversial. The objectives of the present study were to evaluate the function and morphology of the hypertrophied myocardium in renovascular hypertensive (RHT) rats. Male Wistar rats were sacrificed at week 4 (RHT4) and 8 (RHT8) after unilateral renal ischemia (Goldblatt II hypertension model). Normotensive rats were used as controls. Myocardial function was analyzed in isolated papillary muscle preparations, morphological features were defined by light microscopy, and myocardial hydroxyproline concentration (HOP) was determined by spectrophotometry. Renal artery clipping resulted in elevated systolic arterial pressure (RHT4: 178 ± 19 mmHg and RHT8: 194 ± 24 mmHg, P<0.05 vs control: 123 ± 7 mmHg). Myocardial hypertrophy was observed in both renovascular hypertensive groups. The myocardial HOP concentration was increased in the RHT8 group (control: 2.93 ± 0.38 µg/mg; RHT4: 3.02 ± 0.40 µg/mg; RHT8: 3.44 ± 0.45 µg/mg of dry tissue, P<0.05 vs control and RHT4 groups). The morphological study demonstrated myocyte necrosis, vascular damage and cellular inflammatory response throughout the experimental period. The increased cellularity was more intense in the adventitia of the arterioles. As a consequence of myocyte necrosis, there was an early, local, conjunctive stroma collapse with disarray and thickening of the argyrophilic interstitial fibers, followed by scarring. The functional data showed an increased passive myocardial stiffness in the RHT4 group. We conclude that renovascular hypertension induces myocyte and arteriole necrosis. Reparative fibrosis occurred as a consequence of the inflammatory response to necrosis. The mechanical behavior of the isolated papillary muscle was normal, except for an early increased myocardial passive stiffness

GCHF basis sets and their application in the electronic structure study of PrMnO3

The approach called generator coordinate Hartree-Fock (GCHF) method is used in the selection of Gaussian basis set [25s18p for O ((3)p), 31s21p14d for Mn (S-6), and 33s22p16d9f for Pr ((4)J)] for atoms. The role of the weight functions in the assessment of the numerical integration range of the GCHF equations is shown. These basis sets are contracted to (25s18p/9s5p), (31s21p14d/9s6p4d), and (33s22pl6d9f118sl2p5d3f) by segmented contraction scheme of Dunning and they are utilized in calculations of Restricted-Open-HF (ROHF) Total and Orbital energies of the (MnO+1)-Mn-3 and (PrO+1)-Pr-1 fragments, to evaluate their quality in molecular studies. The addition of one d polarization function in the contracted (9s5p) basis set for O(P-3) atom and their application with the contracted (9s6p4d), (18s21p5d3f) basis sets for Mn (S-6) and Pr-Pr ((4)j) atoms lead to the electronic structure study of PrMnO3. The dipole moment, the total energy, and total atomic charges properties were calculated and were carried out at ROHF level with the [PrMnO3](2) fragment. The calculated values show that PrMnO3 does not present piezoelectric properties. (C) 2004 Elsevier B.V. All rights reserved.