Multilevel high-voltage pulse generation based on a new modular solid-state switch

This paper describes a modular solid-state switching cell derived from the Marx generator concept to be used in topologies for generating multilevel unipolar and bipolar high-voltage (HV) pulses into resistive loads. The switching modular cell comprises two ON/OFF semiconductors, a diode, and a capacitor. This cell can be stacked, being the capacitors charged in series and their voltages balanced in parallel. To balance each capacitor voltage without needing any parameter measurement, a vector decision diode algorithm is used in each cell to drive the two switches. Simulation and experimental results, for generating multilevel unipolar and bipolar HV pulses into resistive loads are presented.

Offshore wind turbine simulation: multibody drive train. Bacl-to-back NPC (Neutral Point Clamped) converters: Fractional-order control

This paper is on offshore wind energy conversion systems installed on the deep water and equipped with back-to-back neutral point clamped full-power converter, permanent magnet synchronous generator with an AC link. The model for the drive train is a five-mass model which incorporates the dynamic of the structure and the tower in order to emulate the effect of the moving surface. A three-level converter and a four-level converter are the two options with a fractional-order control strategy considered to equip the conversion system. Simulation studies are carried out to assess the quality of the energy injected into the electric grid. Finally, conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Simulation of offshore wind system with two levels converters: HVDC power transmission

A new integrated mathematical model for the simulation of offshore wind energy conversion system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using full-power two-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a high voltage DC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the structure and tower due to the need to emulate the effects of the moving surface. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistor of the converter. Finally, a case study is presented to access the system performance. © 2014 IEEE.

Spinning reserve and emission unit commitment through stochastic optimization

This paper proposes a stochastic mixed-integer linear approach to deal with a short-term unit commitment problem with uncertainty on a deregulated electricity market that includes day-ahead bidding and bilateral contracts. The proposed approach considers the typically operation constraints on the thermal units and a spinning reserve. The uncertainty is due to the electricity prices, which are modeled by a scenario set, allowing an acceptable computation. Moreover, emission allowances are considered in a manner to allow for the consideration of environmental constraints. A case study to illustrate the usefulness of the proposed approach is presented and an assessment of the cost for the spinning reserve is obtained by a comparison between the situation with and without spinning reserve.

Micro – and nanofibers and liquid crystals for ligth-scattering shutters: Simulation of electrp-optical properties

This work demonstrates the feasibility of using polymeric micro- and nanofiber-composed films and liquid crystals as electrically switchable scattering light shutters. We present a concept of electro-optic device based on an innovative combination of two mature technologies: optics of nematic liquid crystals and electrospinning of nanofibers. These devices have electric and optical characteristics far superior to other comparable methods. The simulation presented shows results that are highly consistent with those of experiments and that explain the working mechanism of the devices.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Demux devices based on A-SiC:H

In this paper we present results about the functioning of a multilayered a-SiC:H heterostructure as a device for wavelength-division demultiplexing of optical signals. The device is composed of two stacked p-i-n photodiodes, both optimized for the selective collection of photogenerated carriers. Band gap engineering was used to adjust the photogeneration and recombination rates profiles of the intrinsic absorber regions of each photodiode to short and long wavelength absorption and carrier collection in the visible spectrum. The photocurrent signal using different input optical channels was analyzed at reverse and forward bias and under steady state illumination. This photocurrent is used as an input for a demux algorithm based on the voltage controlled sensitivity of the device. The device functioning is explained with results obtained by numerical simulation of the device, which permit an insight to the internal electric configuration of the double heterojunction.These results address the explanation of the device functioning in the frequency domain to a wavelength tunable photocapacitance due to the accumulation of space charge localized at the internal junction. The existence of a direct relation between the experimentally observed capacitive effects of the double diode and the quality of the semiconductor materials used to form the internal junction is highlighted.

Light-activated amplification in SiC Tandem devices: A capacitive active filter model

Characteristics of tunable wavelength pi'n/pin filters based on a-SiC:H multilayered stacked cells are studied both experimentally and theoretically. Results show that the device combines the demultiplexing operation with the simultaneous photodetection and self amplification of the signal. An algorithm to decode the multiplex signal is established. A capacitive active band-pass filter model is presented and supported by an electrical simulation of the state variable filter circuit. Experimental and simulated results show that the device acts as a state variable filter. It combines the properties of active high-pass and low-pass filter sections into a capacitive active band-pass filter using a changing capacitance to control the power delivered to the load.

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Projeto de um conversor eletrónico para utilização num sistema eólico de produção de energia

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica no Ramo de Automação e Electrónica Industrial

Sobrevivência das redes de transporte da nova geração

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Desenvolvimento de modelo de primeiros princípios para simulação dinâmica de uma coluna de destilação contínua

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Simulation of rectifier voltage malfunction on OWECS, four-level converter, HVDC light link: Smart grid context tool

This paper presents a model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase. The offshore wind system model comprises a variable-speed wind turbine supported on a floating platform, equipped with a permanent magnet synchronous generator using full-power four-level neutral point clamped converter. The link from the offshore floating platform to the onshore electrical grid is done through a light high voltage direct current submarine cable. The drive train is modeled by a three-mass model. Considerations about the smart grid context are offered for the use of the model in such a context. The rectifier voltage malfunction domino effect is presented as a case study to show capabilities of the model. (C) 2015 Elsevier Ltd. All rights reserved.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

Brownian bridge and other path-dependent Gaussian processes vectorial simulation

The iterative simulation of the Brownian bridge is well known. In this article, we present a vectorial simulation alternative based on Gaussian processes for machine learning regression that is suitable for interpreted programming languages implementations. We extend the vectorial simulation of path-dependent trajectories to other Gaussian processes, namely, sequences of Brownian bridges, geometric Brownian motion, fractional Brownian motion, and Ornstein-Ulenbeck mean reversion process.