980 resultados para Particle Level Set


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Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

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We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

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The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs’ management. The proposed methodology is implemented and tested in MASCEM – a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.

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To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

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Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

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Mestrado em Controlo e Gestão dos Negócios

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Cancer is a national and international health care concern. It’s important to find strategies for early diagnosis as well as for the optimization of the various therapeutic options currently existing in Portugal. Cancer is the second leading cause of death in Portugal, the choice of this study, is due to the importance of radiotherapy approach in cancer treatment and because is the therapy used in 40% of oncology patients. Radiation therapy has evolve data technological level, that allows new treatment techniques that are more efficient and that also promotes greater professional satisfaction. The hadrons are charged particles, used in cancer therapy. These particles can bring a paradigm shift regarding the therapeutic approach in radiotherapy. The technique used is proton therapy, that reveal to be more accurate, efficacious and less toxic to surrounding tissue. Proton therapy may be a promising development in the field of oncology and how the treatment is given in radiotherapy. Although there is awareness of the benefits of proton therapy in oncology it’s also important to take in consideration the costs of these therapy, because they are considerably higher than conventional treatments of radiotherapy. Given the lack of a proton therapy service in Portugal, this study aims to be a documentary analysis of clinical records that will achieve the following objectives: to identify the number of cancer patients diagnosed in 2010 in Portugal and to calculate the estimated number of patients that could have been treated with proton therapy according to the Health Council of the Netherlands registration document.

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Dissertação de Mestrado, Educação (Administração e Organização Escolar), 7 de Fevereiro de 2014, Universidade dos Açores.

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Dissertação de Mestrado, Ciências Económicas e Empresariais, 6 de Dezembro de 2012, Universidade dos Açores.

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Mestrado em Engenharia Electrotécnica e de Computadores

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Sendo o manual escolar o recurso pedagógico mais utilizado por alunos e professores foi realizada uma investigação tendo por objectivo avaliar qualitativamente a forma comunicacional de um conjunto de manuais escolares do 2º ciclo do ensino básico1. A importância atribuída atualmente à imagem é patente nos manuais escolares, sob pretexto de se tornarem mais apelativos e mais eficazes. Tal como em outras áreas em que a quantidade de imagens acaba por se transformar em poluição visual porque o ser humano não tem capacidade para reagir, simultaneamente, a um demasiado número de estímulos, nas estratégias comunicacionais dos manuais escolares este problema deve ser acautelado porque delas depende a sua qualidade pedagógica. As investigações não comprovam que exista uma relação direta entre a presença de ilustrações num texto e o aumento da sua compreensão. Pelo contrário, há estudos que sugerem que muitas ilustrações falham como potenciadoras da aprendizagem. Neste sentido, da investigação referida, consta uma análise ao rácio imagem/texto e uma auscultação a dois grupos de amostra - professores e alunos – sobre alguns aspectos gerais relativos à presença e eficácia pedagógica das ilustrações dos manuais escolares. Destacamos que, no caso dos alunos, apesar do seu nível de literacia ter constituído um obstáculo ao tratamento das questões, optámos por apresentar as suas respostas.

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Dissertação de Mestrado, Sociologia, 24 de Março de 2014, Universidade dos Açores.