983 resultados para network solution
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Comunicação apresentada na 30th Sunbelt Social Networks Conference, em Riva del Garda, Itália, a 3 de Julho de 2010.
Utilização de coberturas ajardinadas de vegetação intensiva, extensiva e horta urbana em edificações
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil
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Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores
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The main result of this work is a new criterion for the formation of good clusters in a graph. This criterion uses a new dynamical invariant, the performance of a clustering, that characterizes the quality of the formation of clusters. We prove that the growth of the dynamical invariant, the network topological entropy, has the effect of worsening the quality of a clustering, in a process of cluster formation by the successive removal of edges. Several examples of clustering on the same network are presented to compare the behavior of other parameters such as network topological entropy, conductance, coefficient of clustering and performance of a clustering with the number of edges in a process of clustering by successive removal.
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A Internet, conforme a conhecemos, foi projetada com base na pilha de protocolos TCP/IP, que foi desenvolvida nos anos 60 e 70 utilizando um paradigma centrado nos endereços individuais de cada máquina (denominado host-centric). Este paradigma foi extremamente bem-sucedido em interligar máquinas através de encaminhamento baseado no endereço IP. Estudos recentes demonstram que, parte significativa do tráfego atual da Internet centra-se na transferência de conteúdos, em vez das tradicionais aplicações de rede, conforme foi originalmente concebido. Surgiram então novos modelos de comunicação, entre eles, protocolos de rede ponto-a-ponto, onde cada máquina da rede pode efetuar distribuição de conteúdo (denominadas de redes peer-to-peer), para melhorar a distribuição e a troca de conteúdos na Internet. Por conseguinte, nos últimos anos o paradigma host-centric começou a ser posto em causa e apareceu uma nova abordagem de Redes Centradas na Informação (ICN - information-centric networking). Tendo em conta que a Internet, hoje em dia, basicamente é uma rede de transferência de conteúdos e informações, porque não centrar a sua evolução neste sentido, ao invés de comunicações host-to-host? O paradigma de Rede Centrada no Conteúdo (CCN - Content Centric Networking) simplifica a solução de determinados problemas de segurança relacionados com a arquitetura TCP/IP e é uma das principais propostas da nova abordagem de Redes Centradas na Informação. Um dos principais problemas do modelo TCP/IP é a proteção do conteúdo. Atualmente, para garantirmos a autenticidade e a integridade dos dados partilhados na rede, é necessário garantir a segurança do repositório e do caminho que os dados devem percorrer até ao seu destino final. No entanto, a contínua ineficácia perante os ataques de negação de serviço praticados na Internet, sugere a necessidade de que seja a própria infraestrutura da rede a fornecer mecanismos para os mitigar. Um dos principais pilares do paradigma de comunicação da CCN é focalizar-se no próprio conteúdo e não na sua localização física. Desde o seu aparecimento em 2009 e como consequência da evolução e adaptação a sua designação mudou atualmente para Redes de Conteúdos com Nome (NNC – Named Network Content). Nesta dissertação, efetuaremos um estudo de uma visão geral da arquitetura CCN, apresentando as suas principais características, quais os componentes que a compõem e como os seus mecanismos mitigam os tradicionais problemas de comunicação e de segurança. Serão efetuadas experiências com o CCNx, que é um protótipo composto por um conjunto de funcionalidades e ferramentas, que possibilitam a implementação deste paradigma. O objetivo é analisar criticamente algumas das propostas existentes, determinar oportunidades, desafios e perspectivas para investigação futura.
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The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.
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The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.
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The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.
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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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The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.
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The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.
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Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific programs in the LMP values supports the manager decision concerning the DR use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 33-bus network with intensive use of DG.
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The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.
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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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A presente tese descreve diferentes soluções que permitem a reutilização da energia recuperada em ascensores eléctricos de roda de aderência dotados de conversores electrónicos de frequência e dessa forma contribuir para a melhoria da eficiência energética nos ascensores. Nos ascensores, a energia potencial é constantemente transferida enquanto a cabina está em movimento. Se a cabina se estiver a movimentar em sentido descendente com plena carga, ou em sentido ascendente, mas vazia, o motor estará em modo gerador. Quando a cabina se movimenta em sentido descendente, e o peso na cabina é superior ao peso do contrapeso, então o binário do motor encontra-se em sentido contrário à velocidade, isto é, o motor está a travar, havendo lugar à recuperação de energia. Igualmente, se a cabina subir vazia, também se poderá recuperar energia eléctrica. A energia acumulada em forma de energia potencial nas pessoas e no contrapeso pode ser recuperada, dado que o motor estará a funcionar como um gerador. De modo a estudar a viabilidade técnica e económica das diferentes soluções foram realizadas medições a uma amostra representativa de ascensores eléctricos de roda de aderência. Esta amostra é constituída por 39 ascensores que estão instalados em diferentes tipos de edifícios e que pertencem a diferentes categorias de utilização, de acordo com a norma VDI 4707:2009. Para cada ascensor foi medida a energia consumida e a energia gerada para uma manobra completa – a descida e a subida da cabina sem carga. A partir das medições, e com base na norma VDI 4707:2009 foram calculados os valores anualizados de energia eléctrica consumidos e produzidos por cada ascensor. A partir das 5 hipóteses identificadas para a utilização da energia recuperada (carregamento de bateria para alimentação dos circuitos em stand-by; carregamento de supercondensador para alimentação dos circuitos em stand-by; carregamento de supercondensador para alimentar o barramento DC; reinjecção da energia no barramento DC de um conjunto de ascensores em grupo; reinjecção da energia na rede eléctrica do edifício onde o ascensor está instalado) foi realizada a avaliação técnica e a avaliação económico-financeira para cada um dos ascensores. Por último, foi desenvolvido um simulador que permite definir a solução de recuperação de energia que seja técnica e economicamente mais viável, para um dado ascensor eléctrico de roda de aderência instalado, mediante a introdução dos parâmetros técnicos do ascensor em avaliação.