Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

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. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Detecção e seguimento de objectos em imagens termográficas: análise experimental de modelos de descrição

A instalação de sistemas de videovigilância, no interior ou exterior, em locais como aeroportos, centros comerciais, escritórios, edifícios estatais, bases militares ou casas privadas tem o intuito de auxiliar na tarefa de monitorização do local contra eventuais intrusos. Com estes sistemas é possível realizar a detecção e o seguimento das pessoas que se encontram no ambiente local, tornando a monitorização mais eficiente. Neste contexto, as imagens típicas (imagem natural e imagem infravermelha) são utilizadas para extrair informação dos objectos detectados e que irão ser seguidos. Contudo, as imagens convencionais são afectadas por condições ambientais adversas como o nível de luminosidade existente no local (luzes muito fortes ou escuridão total), a presença de chuva, de nevoeiro ou de fumo que dificultam a tarefa de monitorização das pessoas. Deste modo, tornou‐se necessário realizar estudos e apresentar soluções que aumentem a eficácia dos sistemas de videovigilância quando sujeitos a condições ambientais adversas, ou seja, em ambientes não controlados, sendo uma das soluções a utilização de imagens termográficas nos sistemas de videovigilância. Neste documento são apresentadas algumas das características das câmaras e imagens termográficas, assim como uma caracterização de cenários de vigilância. Em seguida, são apresentados resultados provenientes de um algoritmo que permite realizar a segmentação de pessoas utilizando imagens termográficas. O maior foco desta dissertação foi na análise dos modelos de descrição (Histograma de Cor, HOG, SIFT, SURF) para determinar o desempenho dos modelos em três casos: distinguir entre uma pessoa e um carro; distinguir entre duas pessoas distintas e determinar que é a mesma pessoa ao longo de uma sequência. De uma forma sucinta pretendeu‐se, com este estudo, contribuir para uma melhoria dos algoritmos de detecção e seguimento de objectos em sequências de vídeo de imagens termográficas. No final, através de uma análise dos resultados provenientes dos modelos de descrição, serão retiradas conclusões que servirão de indicação sobre qual o modelo que melhor permite discriminar entre objectos nas imagens termográficas.

Ferramenta de apoio ao projeto, configuração e gestão de instalações domóticas

Esta dissertação apresenta o trabalho realizado no âmbito da unidade curricular de Tese / Dissertação (TEDI) do Mestrado em Engenharia Eletrotécnica e de Computadores – Especialização em Automação e Sistemas em parceria com a empresa Live Simply, uma empresa de domótica que decidiu apostar na inovação e no desenvolvimento de serviços e produtos de valor acrescentado para consolidar a sua posição no mercado. Neste contexto, foram identificadas como mais-valias para a Live Simply a conceção, por um lado, de uma ferramenta de apoio técnico de integração e simplificação das fases de projeto, configuração e gestão de instalações domóticas e, por outro lado, de uma interface com a instalação para o cliente consultar e alterar, em tempo real, o estado dos atuadores. Depois de analisadas as tecnologias disponíveis, selecionaram-se as soluções a adotar (linguagens de programação, servidores de base de dados e ambientes de desenvolvimento), definiu-se a arquitetura do sistema, detalhando-se os módulos de projeto, configuração e gestão de instalações, a estrutura da base de dados assim como o hardware de controlo da instalação. De seguida, procedeu-se ao desenvolvimento dos módulos de software e à configuração e programação do módulo de hardware. Por último, procedeu-se a um conjunto exaustivo de testes aos diferentes módulos que demonstraram o correto funcionamento da ferramenta e a adequação das tecnologias empregues. A ferramenta de apoio técnico realizada integra as fases do projeto, configuração e gestão de instalações domóticas, permitindo melhorar o desempenho dos técnicos e a resposta aos clientes. A interface oferecida ao dono da instalação é uma interface Web de aspeto amigável e fácil utilização que permite consultar e modificar em tempo real o estado da instalação.

Control of a power supply with cycling current using different controllers

Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometers require controlled current sources in order to get accurate flux density with respect to its magnet. The main elements of the proposed solution are a power semiconductor, a DC voltage source and the magnet. The power semiconductor is commanded in order to get a linear control of the flux density. To implement the flux density control, a Hall Effect sensor is used. Furthermore, the dynamic behavior of the current source is analyzed and compared when using a PI controller and a PD2I controller.

Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

Modeling for control design of a multi-reach water canal

This article addresses the problem of obtaining reduced complexity models of multi-reach water delivery canals that are suitable for robust and linear parameter varying (LPV) control design. In the first stage, by applying a method known from the literature, a finite dimensional rational transfer function of a priori defined order is obtained for each canal reach by linearizing the Saint-Venant equations. Then, by using block diagrams algebra, these different models are combined with linearized gate models in order to obtain the overall canal model. In what concerns the control design objectives, this approach has the advantages of providing a model with prescribed order and to quantify the high frequency uncertainty due to model approximation. A case study with a 3-reach canal is presented, and the resulting model is compared with experimental data. © 2014 IEEE.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff. © 2014 IEEE.

Fractional order control on a wind turbine benchmark

This paper is about a hierarchical structure with an event-based supervisor in a higher level and a fractional-order proportional integral (FOPI) in a lower level applied to a wind turbine. The event-based supervisor analyzes the operation conditions to determine the state of the wind turbine. This controller operate in the full load region and the main objective is to capture maximum power generation while ensuring the performance and reliability required for a wind turbine to be integrated into an electric grid. The main contribution focus on the use of fractional-order proportional integral controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. Comparisons between fractional-order pitch control and a default proportional integral pitch controller applied to a wind turbine benchmark are given and simulation results by Matlab/Simulink are shown in order to prove the effectiveness of the proposed approach.

Road lane detection for autonomous robot guidance

Computational Vision stands as the most comprehensive way of knowing the surrounding environment. Accordingly to that, this study aims to present a method to obtain from a common webcam, environment information to guide a mobile differential robot through a path similar to a roadway.

Simulation of offshore wind system with two-level 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.

Micro-generation Evaluation of the Zero Emissions Technologies in the Portuguese Market

Micro-generation is the small scale production of heat and/or electricity from a low carbon source and can be a powerful driver for carbon reduction, behavior change, security of supply and economic value. The energy conversion technologies can include photovoltaic panels, micro combined heat and power, micro wind, heat pumps, solar thermal systems, fuel cells and micro hydro schemes. In this paper, a small research of the availability of the conversion apparatus and the prices for the micro wind turbines and photovoltaic systems is made and a comparison between these two technologies is performed in terms of the availability of the resource and costs. An analysis of the new legal framework published in Portugal is done to realize if the incentives to individualspsila investment in sustainable and local energy production is worth for their point of view. An economic evaluation for these alternatives, accounting with the governmentpsilas incentives should lead, in most cases, into attractive return rates for the investment. Apart from the attractiveness of the investment there are though other aspects that should be taken into account and those are the benefits that these choices have to us all. The idea is that micro-generation will not only make a significant direct contribution to carbon reduction targets, it will also trigger a multiplier effect in behavior change by engaging hearts and minds, and providing more efficient use of energy by householders. The diversified profile of power generation by micro-generators, both in terms of location and timing, should reduce the impact of intermittency or plant failures with significant gains for security of supply.

Short-term Value for the Water Stored in Headsensitivity Power System Reservoirs

As it is well known, competitive electricity markets require new computing tools for generation companies to enhance the management of its resources. The economic value of the water stored in a power system reservoir is crucial information for enhancing the management of the reservoirs. This paper proposes a practical deterministic approach for computing the short-term economic value of the water stored in a power system reservoir, emphasizing the need to considerer water stored as a scarce resource with a short-term economic value. The paper addresses a problem concerning reservoirs with small storage capacities, i.e., the reservoirs considered as head-sensitivity. More precisely, the respective hydro plant is head-dependent and a pure linear approach is unable to capture such consideration. The paper presents a case study supported by the proposed practical deterministic approach and applied on a real multi-reservoir power system with three cascaded reservoirs, considering as input data forecasts for the electric energy price and for the natural inflow into the reservoirs over the schedule time horizon. The paper presents various water schedules due to different final stored water volume conditions on the reservoirs. Also, it presents the respective economic value of the water for the reservoirs at different stored water volume conditions.

Correlation modeling for a distributed scalable video codec based on the HEVC standard

The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.

Corrugated horn antenna for a CosmoGal satellite with reduced dimensions

This paper presents the design methodology for the creation of corrugated horn antennas for the CosmoGal satellite. The mission will collect the radiation of the cosmic microwave background, by a radiometer in three different radio astronomy frequency bands (10.6-10.7GHz; 15.35-15.4GHz; 23.6-24GHz). It is discussed the design of several types of horns, simulated with the CST software. The best result points to a choked Gaussian corrugated horn antenna, with directivity of 23 dBi, side lobes 35 dB below and cross polarization better than -45 dB. Plus, with the advantage of having a small dimension, with a total length of only 7.43λ © 2014 IEEE.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.