924 resultados para RENEWABLE ENERGY SOURCES
Impact of design options in zero energy building conception: the case of large buildings in Portugal
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The new recast of Directive 2010/31/EU in order to implement the new concept NZEB in new buildings, is to be fully respected by all Member States, and is revealed as important measure to promote the reduction of energy consumption of buildings and encouraging the use of renewable energy. In this study, it was tested the applicability of the nearly zero energy building concept to a big size office building and its impact after a 50-years life cycle span.
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Master Thesis to obtain the Master degree in Chemical Engineering - Branch Chemical Processes
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Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química
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Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.
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Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.
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Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.
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Actualmente a humanidade depara-se com um dos grandes desafios que é o de efectivar a transição para um futuro sustentável. Logo, o sector da energia tem um papel chave neste processo de transição, com principal destaque para a energia solar, tendo em conta que é uma das fontes de energias renováveis mais promissoras, podendo no médiolongo prazo, tornar-se uma das principais fontes de energia no panorama energético dos países. A energia solar térmica de concentração (CSP), apesar não ser ainda conhecida em Portugal, possui um potencial relevante em regiões específicas do nosso território. Logo, o objectivo deste trabalho é efectuar uma análise detalhada dos sistemas solares de concentração para produção de energia eléctrica, abordando temas, tais como, o potencial da energia solar, a definição do processo de concentração solar, a descrição das tecnologias existentes, o estado da arte do CSP, mercado CSP no mundo, e por último, a análise da viabilidade técnico-económica da instalação de uma central tipo torre solar de 20 MW, em Portugal. Para que este objectivo fosse exequível, recorreu-se à utilização de um software de simulação termodinâmica de centrais CSP, denominado por Solar Advisor Model (SAM). O caso prático foi desenvolvido para a cidade de Faro, onde foram simuladas quatro configurações distintas para uma central do tipo torre solar de 20 MW. Foram apresentados resultados, focando a desempenho diário e anual da central. Foi efectuada uma análise para avaliação da influência da variabilidade dos parâmetros, localização geográfica, múltiplo solar, capacidade de armazenamento de calor e fracção de hibridização sobre o custo nivelado da energia (LCOE), o factor de capacidade e a produção anual de energia. Conjuntamente, é apresentada uma análise de sensibilidade, com a finalidade de averiguar quais os parâmetros que influenciam de forma mais predominante o valor do LCOE. Por último, é apresentada uma análise de viabilidade económica de um investimento deste tipo.
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Nos últimos anos o consumo de energia elétrica produzida a partir de fontes renováveis tem aumentado significativamente. Este aumento deve-se ao impacto ambiental que recursos como o petróleo, gás, urânio, carvão, entre outros, têm no meio ambiente e que são notáveis no diaa- dia com as alterações climáticas e o aquecimento global. Por sua vez, estes recursos têm um ciclo de vida limitado e a dada altura tornar-se-ão escassos. A preocupação de uma melhoria contínua na redução dos impactos ambientais levou à criação de Normas para uma gestão mais eficiente e sustentável do consumo de energia nos edifícios. Parte da eletricidade vendida pelas empresas de comercialização é produzida através de fontes renováveis, e com a recente publicação do Decreto de Lei nº 153/2014 de 20 outubro de 2014 que regulamenta o autoconsumo, permitindo que também os consumidores possam produzir a sua própria energia nas suas residências para reduzir os custos com a compra de eletricidade. Neste contexto surgiram os edifícios inteligentes. Por edifícios inteligentes entende-se que são edifícios construídos com materiais que os tornam mais eficientes, possuem iluminação e equipamentos elétricos mais eficientes, e têm sistemas de produção de energia que permitem alimentar o próprio edifício, para um consumo mais sustentado. Os sistemas implementados nos edifícios inteligentes visam a monitorização e gestão da energia consumida e produzida para evitar desperdícios de consumo. O trabalho desenvolvido visa o estudo e a implementação de Redes Neuronais Artificiais (RNA) para prever os consumos de energia elétrica dos edifícios N e I do ISEP/GECAD, bem como a previsão da produção dos seus painéis fotovoltáicos. O estudo feito aos dados de consumo permitiu identificar perfis típicos de consumo ao longo de uma semana e de que forma são influenciados pelo contexto, nomeadamente, com os dias da semana versus fim-de-semana, e com as estações do ano, sendo analisados perfis de consumo de inverno e verão. A produção de energia através de painéis fotovoltaicos foi também analisada para perceber se a produção atual é suficiente para satisfazer as necessidades de consumo dos edifícios. Também foi analisada a possibilidade da produção satisfazer parcialmente as necessidades de consumos específicos, por exemplo, da iluminação dos edifícios, dos seus sistemas de ar condicionado ou dos equipamentos usados.
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Dissertation presented to obtain the Ph.D degree in Chemistry
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Dissertação para obtenção do Grau de Doutor em Ambiente
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Theawareness that fossil fuels exist in limited quantities has stimulated research into energy production from renewable sources. Future energy sources! should! be! plentiful! with! negligible! impact! on! the! environment.! Hydrogen!has!the!potential!to!satisfy!these!requirements.!Nevertheless,!current! methods! of! H2! production! rely! on! nonOrenewable! resources.! Biological! H2! production! from! sunlight! or! biomass! is! an! appealing! alternative! to! current! production!methods.!!(...)
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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.
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The thrust towards energy conservation and reduced environmental footprint has fueled intensive research for alternative low cost sources of renewable energy. Organic photovoltaic cells (OPVs), with their low fabrication costs, easy processing and flexibility, represent a possible viable alternative. Perylene diimides (PDIs) are promising electron-acceptor candidates for bulk heterojunction (BHJ) OPVs, as they combine higher absorption and stability with tunable material properties, such as solubility and position of the lowest unoccupied molecular orbital (LUMO) level. A prerequisite for trap free electron transport is for the LUMO to be located at a level deeper than 3.7 eV since electron trapping in organic semiconductors is universal and dominated by a trap level located at 3.6 eV. Although the mostly used fullerene acceptors in polymer:fullerene solar cells feature trap-free electron transport, low optical absorption of fullerene derivatives limits maximum attainable efficiency. In this thesis, we try to get a better understanding of the electronic properties of PDIs, with a focus on charge carrier transport characteristics and the effect of different processing conditions such as annealing temperature and top contact (cathode) material. We report on a commercially available PDI and three PDI derivatives as acceptor materials, and its blends with MEH-PPV (Poly[2-methoxy 5-(2-ethylhexyloxy)-1,4-phenylenevinylene]) and P3HT (Poly(3-hexylthiophene-2,5-diyl)) donor materials in single carrier devices (electron-only and hole-only) and in solar cells. Space-charge limited current measurements and modelling of temperature dependent J-V characteristics confirmed that the electron transport is essentially trap-free in such materials. Different blend ratios of P3HT:PDI-1 (1:1) and (1:3) show increase in the device performance with increasing PDI-1 ratio. Furthermore, thermal annealing of the devices have a significant effect in the solar cells that decreases open-circuit voltage (Voc) and fill factor FF, but increases short-circuit current (Jsc) and overall device performance. Morphological studies show that over-aggregation in traditional donor:PDI blend systems is still a big problem, which hinders charge carrier transport and performance in solar cells.
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Building sector has become an important target for carbon emissions reduction, energy consumption and resources depletion. Due to low rates of replacement of the existing buildings, their low energy performances are a major concern. Most of the current regulations are focused on new buildings and do not account with the several technical, functional and economic constraints that have to be faced in the renovation of existing buildings. Thus, a new methodology is proposed to be used in the decision making process for energy related building renovation, allowing finding a cost-effective balance between energy consumption, carbon emissions and overall added value.
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Dissertação de mestrado integrado em Engenharia Civil