Impacto da Introdução de Baterias de armazenamento de Energia em Smart Grids

De forma a não comprometer o conforto ou a qualidade de vida, nos dias de hoje, é obrigatório que a energia elétrica esteja presente. Sendo indispensável, torna-se necessário assegurar que a sua distribuição seja feita da forma mais qualitativa possível. Uma resposta rápida e eficaz a possíveis falhas que ocorram na rede, irá garantir a tal qualidade de serviço desejada. Para isso, a automatização dos processos é uma grande evolução e objetivo de concretização do setor elétrico. Neste contexto surge o conceito de Smart Grid, que tem como principal objetivo a combinação entre o setor elétrico e a evolução da tecnologia. A par desta característica, estes tipos de redes vêm também trazer evoluções no âmbito ambiental, pois a produção de energia elétrica é feita, maioritariamente, por fontes de energia renovável. Este projeto incide na análise das vantagens técnicas e económicas da inclusão de equipamentos que detêm capacidades de armazenamento de energia, as Baterias de Armazenamento de Energia (BAE), neste tipo de redes. Para tal, procedeu-se à utilização do método do Despacho Económico, que tem como principal objetivo a determinação dos níveis de produção de todas as unidades geradoras do sistema, satisfazendo a carga, ao mais baixo custo de produção. Com este método, foram criados vários cenários de estudo com vista a validar todo o propósito deste projeto. Nesta dissertação, é também realizado um estudo de viabilidade económica destes equipamentos de armazenamento de energia.

Controlo de conversores de eletrónica de potência para integração com SMES na melhoria da qualidade de energia elétrica

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Sistema para o estudo da condutividade térmica a baixa temperatura aplicado à espuma de cobre

O desenvolvimento de novos materiais e a sua caracterização é de extrema importância no dimensionamento e construção de equipamentos criogénicos. A empresa Versarien desenvolveu uma técnica capaz de produzir cobre poroso, conseguindo controlar a porosidade e o tamanho de poros. Os materiais porosos são de especial interesse para dispositivos criogénicos em aplicações espaciais. Um exemplo desta aplicação são as unidades de armazenamento de energia (Energy Storage Units-ESU), onde um material poroso é usado em ausência de gravidade para reter um líquido criogénico por capilaridade, de modo a manter dispositivos a uma temperatura baixa e constante. Neste caso, um material poroso de elevada condutividade térmica, como o cobre, seria de grande interesse uma vez que permite obter uma boa homogeneidade de temperatura na célula. Neste trabalho foi desenvolvido um sistema para medir a condutividade térmica deste material, entre 15 e 260 K, para porosidades entre 50% e 80%, utilizando um criorrefrigerador 2 W @ 20 K. Estas medições permitiram determinar que a pureza do cobre poroso se encontra entre RRR20 (RRR: Residual-resistivity ratio) e RRR10, apresentando uma tortuosidade que se encontra de acordo com um modelo simples descrito nesta dissertação. Foi ainda desenhado, construído e testado um criostato portátil, que apenas necessita de azoto líquido e de bombeamento primário para que se possam realizar medições de condutividade térmica entre 77 e 300 K.

Technology transition towards electric mobility - technology assessment as a tool for policy design

Paper presented at the Colloquium Gerpisa 2013, Paris (http://gerpisa.org/node/2085), Session n°: 19 New kinds of mobility: old and new business models

Prospective system analysis of stationary battery systems under the frame of Constructive Technology Assessment

Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.

Analysis and implementation of a multi-ratio switched capacitor DC-DC converter for a supercapacitor power supply

An energy harvesting system requires an energy storing device to store the energy retrieved from the surrounding environment. This can either be a rechargeable battery or a supercapcitor. Due to the limited lifetime of rechargeable batteries, they need to be periodically replaced. Therefore, a supercapacitor, which has ideally a limitless number of charge/discharge cycles can be used to store the energy; however, a voltage regulator is required to obtain a constant output voltage as the supercapacitor discharges. This can be implemented by a Switched-Capacitor DC-DC converter which allows a complete integration in CMOS technology, although it requires several topologies in order to obtain a high efficiency. This thesis presents the complete analysis of four different topologies in order to determine expressions that allow to design and determine the optimum input voltage ranges for each topology. To better understand the parasitic effects, the implementation of the capacitors and the non-ideal effect of the switches, in 130 nm technology, were carefully studied. With these two analysis a multi-ratio SC DC-DC converter was designed with an output power of 2 mW, maximum efficiency of 77%, and a maximum output ripple, in the steady state, of 23 mV; for an input voltage swing of 2.3 V to 0.85 V. This proposed converter has four operation states that perform the conversion ratios of 1/2, 2/3, 1/1 and 3/2 and its clock frequency is automatically adjusted to produce a stable output voltage of 1 V. These features are implemented through two distinct controller circuits that use asynchronous time machines (ASM) to dynamically adjust the clock frequency and to select the active state of the converter. All the theoretical expressions as well as the behaviour of the whole system was verified using electrical simulations.

Semantic relations extraction from unstructured information for domain ontologies enrichment

Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Desenvolvimento de um Posto de Carregamento Lento com BMS e Interface com o Cockpit para o CEPIUM

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Controlador com FPGA para um motor-in-wheel CA de fluxo axial

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Desenvolvimento de um Range Extender para Veículo Elétrico

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Optimal behavior of responsive residential demand considering hybrid phase change materials

Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customerâ s cost in different DRPs but also to guaranty the habitantsâ  satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customerâ s electricity cost can be reduced up to 48% by utilizing the proposed model.