Conversor multinível NPC de cinco níveis como ondulador de tensão ligado à rede

O crescimento da utilização de accionamentos electromecânicos de velocidade variável entre outros dispositivos que necessitam de tensões elevadas, na ordem dos kV e com elevados níveis de qualidade, despertou o interesse pelos conversores multinível. Este tipo de conversor consegue alcançar elevadas tensões de funcionamento e simultaneamente melhorar a qualidade das formas de onda de tensão e corrente nas respectivas fases. Esta dissertação de mestrado tem por objectivo apresentar um estudo sobre o conversor multinível com díodos de ligação ao neutro (NPC – neutral point clamped), de cinco níveis utilizado como ondulador de tensão ligado à rede. O trabalho começa por desenvolver o modelo matemático do conversor multinível com díodos de ligação ao neutro de cinco níveis e a respectiva interligação com a rede eléctrica. Com base no modelo do conversor são realizadas simulações numéricas desenvolvidas em Matlab-Simulink. Para controlo do trânsito de energia no conversor é utilizando controlo por modo de deslizamento aplicado às correntes nas fases. As simulações efectuadas são comparadas com resultados de simulação obtidos para um ondulador clássico de dois níveis. Resultados de simulação do conversor multinível são posteriormente comparados com resultados experimentais para diferentes valores de potências activa e reactiva. Foi desenvolvido um protótipo experimental de um conversor multinível com díodos de ligação ao neutro de cinco níveis e a respectiva electrónica associada para comando e disparo dos semicondutores de potência.

Design of a sea-level tsunami detection network for the Gulf of Cadiz

The devastating impact of the Sumatra tsunami of 26 December 2004, raised the question for scientists of how to forecast a tsunami threat. In 2005, the IOC-UNESCO XXIII assembly decided to implement a global tsunami warning system to cover the regions that were not yet protected, namely the Indian Ocean, the Caribbean and the North East Atlantic, the Mediterranean and connected seas (the NEAM region). Within NEAM, the Gulf of Cadiz is the more sensitive area, with an important record of devastating historical events. The objective of this paper is to present a preliminary design for a reliable tsunami detection network for the Gulf of Cadiz, based on a network of sea-level observatories. The tsunamigenic potential of this region has been revised in order to define the active tectonic structures. Tsunami hydrodynamic modeling and GIS technology have been used to identify the appropriate locations for the minimum number of sea-level stations. Results show that 3 tsunameters are required as the minimum number of stations necessary to assure an acceptable protection to the large coastal population in the Gulf of Cadiz. In addition, 29 tide gauge stations could be necessary to fully assess the effects of a tsunami along the affected coasts of Portugal, Spain and Morocco.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Optical demultiplexer device operating in the visible spectrum

In this paper, we present results on the use of multilayered a-SiC:H heterostructures as a device for wavelength-division demultiplexing of optical signals. These devices are useful in optical communications applications that use the wavelength division multiplexing technique to encode multiple signals into the same transmission medium. The device is composed of two stacked p-i-n photodiodes, both optimized for the selective collection of photo generated carriers. Band gap engineering was used to adjust the photogeneration and recombination rate profiles of the intrinsic absorber regions of each photodiode to short and long wavelength absorption in the visible spectrum. The photocurrent signal using different input optical channels was analyzed at reverse and forward bias and under steady state illumination. A demux algorithm based on the voltage controlled sensitivity of the device was proposed and tested. An electrical model of the WDM device is presented and supported by the solution of the respective circuit equations.

Avaliação de dados funcionais em repouso do cérebro normal: causalidade de Granger

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Ressonância Magnética

Grid Integration of Offshore Wind Farms Using Modular Marx Multilevel Converters

This paper proposes the use of a Modular Marx Multilevel Converter, as a solution for energy integration between an offshore Wind Farm and the power grid network. The Marx modular multilevel converter is based on the Marx generator, and solves two typical problems in this type of multilevel topologies: modularity and dc capacitor voltage balancing. This paper details the strategy for dc capacitor voltage equalization. The dynamic models of the converter and power grid are presented in order to design the converter ac output voltages and the dc capacitor voltage controller. The average current control is presented and used for power flow control, harmonics and reactive power compensation. Simulation results are presented in order to show the effectiveness of the proposed (MC)-C-3 topology.

Solid-State Bipolar Marx Generator with Voltage Droop Compensation

This paper addresses the voltage droop compensation associated with long pulses generated by solid-stated based high-voltage Marx topologies. In particular a novel design scheme for voltage droop compensation in solid-state based bipolar Marx generators, using low-cost circuitry design and control, is described. The compensation consists of adding one auxiliary PWM stage to the existing Marx stages, without changing the modularity and topology of the circuit, which controls the output voltage and a LC filter that smoothes the voltage droop in both the positive and negative output pulses. Simulation results are presented for 5 stages Marx circuit using 1 kV per stage, with 1 kHz repetition rate and 10% duty cycle.

A DC-DC Step-Up mu-Power Converter for Energy Harvesting Applications, Using Maximum Power PointTracking, Based on Fractional Open Circuit Voltage

A DC-DC step-up micro power converter for solar energy harvesting applications is presented. The circuit is based on a switched-capacitorvoltage tripler architecture with MOSFET capacitors, which results in an, area approximately eight times smaller than using MiM capacitors for the 0.131mu m CMOS technology. In order to compensate for the loss of efficiency, due to the larger parasitic capacitances, a charge reutilization scheme is employed. The circuit is self-clocked, using a phase controller designed specifically to work with an amorphous silicon solar cell, in order to obtain themaximum available power from the cell. This will be done by tracking its maximum power point (MPPT) using the fractional open circuit voltage method. Electrical simulations of the circuit, together with an equivalent electrical model of an amorphous silicon solar cell, show that the circuit can deliver apower of 1132 mu W to the load, corresponding to a maximum efficiency of 66.81%.

Fast optimum-predictive control and capacitor voltage balancing strategy for bipolar back-to-back NPC converters in high-voltage direct current transmission systems

Multilevel power converters have been introduced as the solution for high-power high-voltage switching applications where they have well-known advantages. Recently, full back-to-back connected multilevel neutral point diode clamped converters (NPC converter) have been used inhigh-voltage direct current (HVDC) transmission systems. Bipolar-connected back-to-back NPC converters have advantages in long-distance HVDCtransmission systems over the full back-to-back connection, but greater difficulty to balance the dc capacitor voltage divider on both sending and receiving end NPC converters. This study shows that power flow control and dc capacitor voltage balancing are feasible using fast optimum-predictive-based controllers in HVDC systems using bipolar back-to-back-connected five-level NPC multilevel converters. For both converter sides, the control strategytakes in account active and reactive power, which establishes ac grid currents in both ends, and guarantees the balancing of dc bus capacitor voltages inboth NPC converters. Additionally, the semiconductor switching frequency is minimised to reduce switching losses. The performance and robustness of the new fast predictive control strategy, and its capability to solve the DC capacitor voltage balancing problem of bipolar-connected back-to-back NPCconverters are evaluated.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

New Technique for Uniform Voltage Sharing in Series Stacked Semiconductors

This paper describes the operation of a solid-state series stacked topology used as a serial and parallel switch in pulsed power applications. The proposed circuit, developed from the Marx generator concept, balances the voltage stress on each series stacked semiconductor, distributing the total voltage evenly. Experimental results from a 10 kV laboratory series stacked switch, using 1200 V semiconductors in a ten stages solid-state series stacked circuit, are reported and discussed, considering resistive, capacitive and inductive type loads for high and low duty factor voltage pulse operation.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]