993 resultados para network simulator


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Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

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Paper presented at the ECKM 2010 – 11th European Conference on Knowledge Management, 2-3 September, 2010, Famalicão, Portugal. URL: http://www.academic-conferences.org/eckm/eckm2010/eckm10-home.htm

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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 Informática

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We study exotic patterns appearing in a network of coupled Chen oscillators. Namely, we consider a network of two rings coupled through a “buffer” cell, with Z3×Z5 symmetry group. Numerical simulations of the network reveal steady states, rotating waves in one ring and quasiperiodic behavior in the other, and chaotic states in the two rings, to name a few. The different patterns seem to arise through a sequence of Hopf bifurcations, period-doubling, and halving-period bifurcations. The network architecture seems to explain certain observed features, such as equilibria and the rotating waves, whereas the properties of the chaotic oscillator may explain others, such as the quasiperiodic and chaotic states. We use XPPAUT and MATLAB to compute numerically the relevant states.

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We model the cytoskeleton as a fractal network by identifying each segment with a simple Kelvin-Voigt element with a well defined equilibrium length. The final structure retains the elastic characteristics of a solid or a gel, which may support stress, without relaxing. By considering a very simple regular self-similar structure of segments in series and in parallel, in one, two, or three dimensions, we are able to express the viscoelasticity of the network as an effective generalized Kelvin-Voigt model with a power law spectrum of retardation times L similar to tau(alpha). We relate the parameter alpha with the fractal dimension of the gel. In some regimes ( 0 < alpha < 1), we recover the weak power law behaviors of the elastic and viscous moduli with the angular frequencies G' similar to G" similar to w(alpha) that occur in a variety of soft materials, including living cells. In other regimes, we find different power laws for G' and G".

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The use of a solar photovoltaic (PV) panel simulator can be a valued tool for the design and evaluation of the several components of a photovoltaic system. This simulator is based on power electronic converter controlled in such a way that will behave as a PV panel. Thus, in this paper a PV panel simulator based on a two quadrant DC/DC power converter is proposed. This topology will allow to achieve fast responses, like suddenly changes in the irradiation and temperature. To control the power converter it will be used a fast and robust sliding mode controller. Therefore, with the proposed system I-V curve simulation of a PV panel is obtained. Experimental results from a laboratory prototype are presented in order to confirm the theoretical operation.

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Comunicação apresentada na 18th Conference International of Health Promotion Hospitals & Health Services "Tackling causes and consequences of inequalities in health: contributions of health services and the HPH network", em Manchester de 14-16 de april de 2010

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Comunicação apresentada na 30th Sunbelt Social Networks Conference, em Riva del Garda, Itália, a 3 de Julho de 2010.

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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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Os consumidores finais são vistos, no novo paradigma da operação das redes elétricas, como intervenientes ativos com capacidade para gerir os seus recursos energéticos, nomeadamente as cargas, as unidades de produção, os veículos elétricos e a participação em eventos de Demand Response. Tem sido evidente um aumento do consumo de energia, sendo que o setor residencial representa uma importante parte do consumo global dos países desenvolvidos. Para que a participação ativa dos consumidores seja possível, várias abordagens têm vindo a ser propostas, com ênfase nas Smart Grids e nas Microgrids. Diversos sistemas têm sido propostos e desenvolvidos com o intuito de tornar a operação dos sistemas elétricos mais flexível. Neste contexto, os sistemas de gestão de instalações domésticas apresentam-se como um elemento fulcral para a participação ativa dos consumidores na gestão energética, permitindo aos operadores de sistema coordenarem a produção mas também a procura. No entanto, é importante identificar as vantagens da implementação e uso de sistemas de gestão de energia elétrica para os consumidores finais. Nesta dissertação são propostas metodologias de apoio ao consumidor doméstico na gestão dos recursos energéticos existentes e a implementação das mesmas na plataforma de simulação de um sistema de gestão de energia desenvolvido para consumidores domésticos, o SCADA House Intelligent Management (SHIM). Para tal, foi desenvolvida uma interface que permite a simulação em laboratório do sistema de gestão desenvolvido. Adicionalmente, o SHIM foi incluído no simulador Multi-Agent Smart Grid Simulation Plataform (MASGriP) permitindo a simulação de cenários considerando diferentes agentes. Ao nível das metodologias desenvolvidas são propostos diferentes algoritmos de gestão dos recursos energéticos existentes numa habitação, considerando utilizadores com diferentes tipos de recursos (cargas; cargas e veículos elétricos; cargas, veículos elétricos e microgeração). Adicionalmente é proposto um método de gestão dinâmica das cargas para eventos de Demand Response de longa duração, considerando as características técnicas dos equipamentos. Nesta dissertação são apresentados cinco casos de estudos em que cada um deles tem diferentes cenários de simulação. Estes casos de estudos são importantes para verificar a viabilidade da implementação das metodologias propostas para o SHIM. Adicionalmente são apresentados na dissertação perfis reais dos vários recursos energéticos e de consumidores domésticos que são, posteriormente, utilizados para o desenvolvimento dos casos de estudo e aplicação das metodologias.

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The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM – a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.

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Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, performed so that the competitiveness could be increased, but with exponential implications in the increase of the complexity and unpredictability in those markets’ scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behavior. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) – a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities.

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This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

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The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.