Abstract This paper presents a numerical study and the optimization of very short discrete multi-pump Raman amplifiers using Tellurite-based optical fibers. While most studies about discrete Raman amplifiers usually focus on cases where hundreds of meters of fiber are used, here we consider a multi-pumped Raman amplifier setup with extremely short dimensions, in which the length of the gain media was varied from 2.5 to 30 meters. The optimization process was developed over an broad amplification band from 1520 to 1600 nm, considering a maximum acceptable ripple of 3 dB, and using 2, 3 and 4 pumps with individual powers always below 2.5 W. The results show that it is possible to achieve net gains as high as 10 dB for gain media around 20 meters, and close to 15 dB for 30 meters. These high gains highlight the fact that Tellurite-based optical fibers can be used for the construction of very short and compact broadband amplifiers using just a few pump lasers with modest optical powers. multipump multi Telluritebased Tellurite based multipumped pumped dimensions 25 2 5 2. 152 160 nm W 1 16

Abstract This paper presents measurements at a mock-up medium voltage network to verify the feasibility of Broadband Power Line Communication (BPLC). We use the data extracted within the frequency range 2 − 30 MHz to characterize a MIMO PLC network using different phase combinations, defining the best and worst use case scenarios. The empirical data shows that not only phases directly connected for input-output can be used, but also that we can exploit the coupling between phases to transmit and receive data, therefore creating a dynamic PLC network which will depend on the characteristics of the power grid. By making use of transmission line theory, we also demonstrate how we can mitigate the reflections by measuring the input impedance of the network to allow better use of the bandwidth available for BPLC operation.

Abstract Here we present a numerical analysis and the optimization of a multi-pump discrete Raman amplification system based on the use of a Tellurite optical fiber as the gain media. By using previously reported optimization techniques we were able to exploit the high Raman gain of Tellurite optical fibers and its multipeak spectrum to achieve amplification over an amplification band from 1520 to 1600 nm. Average gains around 10 dB with ripples in the region of 3 dB were achieved using only 3 pumps with less than 800 mW each. Optimized systems were obtained for different lengths of fiber showing that discrete Raman amplifiers based on tellurite fibers with lengths as short as 100 meters can provide high gains and low ripples in a broad wavelength band. Lower cost systems using only 2 pumps were also analyzed in this study providing 5.8 dB of gain with only 2.4 dB of ripple for an 80 nm signal bandwidth.

With the increase in demand to Backbone networks, one became fundamental the application of new telecommunication technologies for efficient use of devices and optical links, such as xPSK modulations with dual polarization, dispersion compensating fibers, coherent detection and digital processing signals. Thus, network planning using analytical models have been proposed in the last years for this purpose. In this paper we propose the use of numerical simulations in wavelength-division multiplexing networks planning via a novel iterative method with high-performance processing, which does an analysis of the quality of transmission in transparent networks.

In this paper, we propose a hybrid methodology based on Graph-Coloring and Genetic Algorithm (GA) to solve the Wavelength Assignment (WA) problem in optical networks, impaired by physical layer effects. Our proposal was developed for a static scenario where the physical topology and traffic matrix are known a priori. First, we used fixed shortest-path routing to attend demand requests over the physical topology and the graph-coloring algorithm to minimize the number of necessary wavelengths. Then, we applied the genetic algorithm to solve WA. The GA finds the wavelength activation order on the wavelengths grid with the aim of reducing the Cross-Phase Modulation (XPM) effect; the variance due to the XPM was used as a function of fitness to evaluate the feasibility of the selected WA solution. Its performance is compared with the First-Fit algorithm in two different scenarios, and has shown a reduction in blocking probability up to 37.14% when considered both XPM and residual dispersion effects and up to 71.42% when only considered XPM effect. Moreover, it was possible to reduce by 57.14% the number of wavelengths.

Este trabalho apresenta uma técnica alternativa para a correção de ondas distorcidas provenientes da saturação dos transformadores de corrente (TCs) através de ferramentas inteligentes baseadas em Redes Neurais Artificiais (RNAs) recorrentes. Os TCs estão presentes em Sistemas Elétricos de Potência com a finalidade de proteção e medição, sendo altamente susceptíveis à saturação. O programa EMTP-ATP (Electromagnetic Transients Program) foi escolhido como ferramenta computacional para a simulação de um sistema elétrico utilizado na geração de dados de treinamento e testes para as RNAs. Muitas arquiteturas de redes neurais artificiais foram treinadas e testadas. Resultados promissores relativos ao novo método são apresentados.

This paper presents an alternative approach to the correction of distorted waveforms caused by the current transformer (CT) saturation. This method uses the Artificial Neural Networks (ANNs) recurrent algorithms. Current transformers are present in the electric power systems for protection and measurements and they are highly susceptible to the saturation phenomenon. The EMTP-ATP software has been chosen as the computational tool to simulate the electrical system in order to generate data to train and test the ANNs. Many ANN architectures were trained and tested. Encouraging results related to the application of the new method are presented.

Este trabalho apresenta uma técnica alternativa para a proteção de transformadores de potência utilizando a lógica diferencial associada ao uso de Redes Neurais Artificiais (RNAs). Este artifício é utilizado na distinção entre faltas internas e correntes de inrush, que surgem durante a energização do transformador. O programa EMTP-ATP (Electromagnetic Transients Program) foi escolhido como ferramenta computacional para a simulação do transformador de potência com o objetivo de gerar dados de treinamento e testes para as RNAs. Um programa em linguagem FORTRAN foi implementado a fim de avaliar o algoritmo completo da proteção diferencial e resultados promissores relativos ao novo método foram obtidos.

This paper presents an alternative approach using the differential logic associated to Artificial Neural Networks for protection of power transformers. Neural networks are used for distinguishing internal faults from inrush currents produced during the transformer energization. The EMTP-ATP software has been chosen as the computational tool to simulate the power transformer in order to generate data to train and test the ANNs. A complete differential protection software was implemented in FORTRAN and encouraging results related to the application of the new method are presented.