Dedução de Funções de Alívio para Priorização de Variantes de Chaveamento Adequadas à Eliminação de Sobrecargas

Eventually, violations of voltage limits at buses or admissible loadings of transmission lines and/or power transformers may occur by the power system operation. If violations are detected in the supervision process, corrective measures may be carried out in order to eliminate them or to reduce their intensity. Loading restriction is an extreme solution and should only be adopted as the last control action. Previous researches have shown that it is possible to control constraints in electrical systems by changing the network topology, using the technique named Corrective Switching, which requires no additional costs. In previous works, the proposed calculations for verifying the ability of a switching variant in eliminating an overload in a specific branch were based on network reduction or heuristic analysis. The purpose of this work is to develop analytical derivation of linear equations to estimate current changes in a specific branch (due to switching measures) by means of few calculations. For bus-bar coupling, derivations will be based on short-circuit theory and Relief Function methodology. For bus-bar splitting, a Relief Function will be derived based on a technique of equivalent circuit. Although systems of linear equations are used to substantiate deductions, its formal solution for each variant, in real time does not become necessary. A priority list of promising variants is then assigned for final check by an exact load flow calculation and a transient analysis using ATP Alternative Transient Program. At last, results obtained by simulation in networks with different features will be presented

Otimização de uma metodologia para análise mineralógica racional de argilominerais

VARELA, M.L. et al. Otimização de uma metodologia para análise mineralógica racional de argilominerais. Cerâmica, São Paulo, n. 51, p. 387-391, 2005.

Usando a história da resolução de alguns problemas para introduzir conceitos: sistemas lineares, determinantes e matrizes.

In this work we studied the method to solving linear equations system, presented in the book titled "The nine chapters on the mathematical art", which was written in the first century of this era. This work has the intent of showing how the mathematics history can be used to motivate the introduction of some topics in high school. Through observations of patterns which repeats itself in the presented method, we were able to introduce, in a very natural way, the concept of linear equations, linear equations system, solution of linear equations, determinants and matrices, besides the Laplacian development for determinants calculations of square matrices of order bigger than 3, then considering some of their general applications

Otimização de uma metodologia para análise mineralógica racional de argilominerais

VARELA, M.L. et al. Otimização de uma metodologia para análise mineralógica racional de argilominerais. Cerâmica, São Paulo, n. 51, p. 387-391, 2005.

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.