980 resultados para cultural resource
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Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ensino de Inglês e de Língua Estrangeira (Alemão) no 3º Ciclo do Ensino Básico e no Ensino Secundário.
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Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Património Artístico
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The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
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In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required.
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Presented thesis at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles
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The development in power systems and the introduction of decentralized generation and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which considers not only the generation, but also the management of loads through demand response programs, energy storage units, EVs and other players in a liberalized electricity markets environment. This paper proposes a methodology to be used by Virtual Power Players (VPPs), concerning the energy resource scheduling in smart grids, considering day-ahead, hour-ahead and real-time scheduling. The case study considers a 33-bus distribution network with high penetration of distributed energy resources. The wind generation profile is based on a real Portuguese wind farm. Four scenarios are presented taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour-ahead and realtime scheduling.
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The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.
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An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.
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Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.
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The operation of distribution networks has been facing changes with the implementation of smart grids and microgrids, and the increasing use of distributed generation. The specific case of distribution networks that accommodate residential buildings, small commerce, and distributed generation as the case of storage and PV generation lead to the concept of microgrids, in the cases that the network is able to operate in islanding mode. The microgrid operator in this context is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The present paper proposes a methodology for the energy resource scheduling considering power flow issues and the energy buying and selling from/to the main network in each bus of the microgrid. The case study uses a real distribution network with 25 bus, residential and commercial consumers, PV generation, and storage.
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Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Património, área de Património Urbano
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Os aproveitamentos geotérmicos têm vindo a aumentar significativamente em todo o mundo, sendo os Estados Unidos da América, o maior produtor desta energia proveniente do interior da Terra, com cerca de 3.187 MW de capacidade instalada. Portugal tem capacidade instalada total de 29 MW, no entanto no que se refere ao aproveitamento de “alta entalpia”, isto é, o aproveitamento geotérmico para produção elétrica, apenas se encontra no arquipélago dos Açores, na ilha de S. Miguel, onde estão instaladas e em funcionamento duas centrais geotérmicas com a potência total de 23 MW, com produção de energia de 185 GWh. Em Portugal Continental, não se consegue produzir energia elétrica devido às temperaturas existentes, restringindo esta utilização apenas ao aproveitamento de baixa entalpia (máximo de 76 ºC). Este aproveitamento normalmente é feito em cascata, segundo, predominando o aquecimento de águas sanitárias, climatização, e para termas, usando águas termominerais. Para a exploração deste recurso renovável, é necessário conhecer a hidrogeologia do país, e relacioná-la com a fracturação, e acidentes tectónicos. Portugal Continental, está divido em quatros partes distintas a nível hidrogeológico, o Maciço Antigo, a Orla Ocidental, a Bacia Tejo-Sado e a Orla Meridional. Qualquer aproveitamento geotérmico em Portugal terá de atender a estas características, potenciando também, novas explorações geotérmicas orientadas para as pessoas, respeitando os valores sociais, culturais e ambientais. Neste contexto, existem alguns complexos geotérmicos em funcionamento, outros abandonados, e muitos outros em estudo para uma breve aplicação. Um exemplo de sucesso no aproveitamento do calor geotérmico, é o complexo de Chaves, que foi evoluindo desde 1985, até aos dias de hoje, continuando em exploração e em expansão para um melhor servir da população local. A existência de dois furos, e brevemente dum terceiro, servem para o abastecimento duma piscina, dum hotel, das termas, e da balneoterapia. Devido à riqueza a nível das temperaturas, dos caudais, e ao nível das necessidades energéticas existentes, este complexo apresenta um tempo de retorno de investimento de cerca de 7 anos, o que é geralmente considerado para investimentos para fins públicos, como é o caso. No âmbito das investigações agora realizadas, foi constatado que estes projetos suportam a cobertura de alguma incerteza hidrogeológica, dada a importante procura existente.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia e Gestão Industrial
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Dissertação de Doutoramento em Ciências da Comunicação