67 resultados para Modelos de Location-Allocation

em Instituto Politécnico do Porto, Portugal


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The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

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A major determinant of the level of effective natural gas supply is the ease to feed customers, minimizing system total costs. The aim of this work is the study of the right number of Gas Supply Units – GSUs - and their optimal location in a gas network. This paper suggests a GSU location heuristic, based on Lagrangean relaxation techniques. The heuristic is tested on the Iberian natural gas network, a system modelized with 65 demand nodes, linked by physical and virtual pipelines. Lagrangean heuristic results along with the allocation of loads to gas sources are presented, using a 2015 forecast gas demand scenario.

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Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

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Orientador: Doutor, José Manuel Veiga Pereira

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O tecido adiposo é um órgão endócrino dinâmico, secretando factores importantes na regulação do metabolismo, fluxo vascular sanguíneo e linfático, e função imunológica, entre outros. Em caso de acumulação de tecido adiposo por ingestão de uma dieta gorda, ou por disfunção metabólica, os adipócitos podem desencadear uma reacção inflamatória por falha na drenagem linfática, acumulando-se mediadores inflamatórios, os quais potenciam a propagação da reacção. Assim, questiona-se uma potencial associação entre o aumento de tecido adiposo na obesidade, hipóxia adipocitária e estimulação da linfangiogénese. Além disso, a expressão de adipocinas varia de acordo com a distribuição do tecido adiposo (subcutâneo, TAS e visceral, TAV). Deste modo, pretende-se com este estudo contribuir para o aumento do conhecimento sobre os complexos mecanismos moleculares subjacentes à linfangiogénese. Ensaios com ratinhos da estirpe C57Bl/6J (modelo de obesidade) e BALB/c (modelo de asma e obesidade), divididos em grupos submetidos a dieta normal e dieta rica em gordura. Avaliação semi-quantitativa da expressão tecidular de LYVE-1 (marcador da linfangiogénese) por imunohistoquímica em material embebido em parafina, no TAS e TAV, e cromatografia líquida de ultra-performance acoplada de espectrometria de massa (UPLC-MS) para análise da expressão plasmática de ceramida e esfingosina-1-fosfato (S1P). No modelo de obesidade observou- -se diminuição do número de vasos linfáticos e expressão de LYVE-1 ao longo do tempo no TAV, e aumento de ambos os parâmetros e hipertrofia adipocitária no TAS. As concentrações de ceramida e S1P corroboram a existência de um processo inflamatório nos ratinhos em estudo, ainda que numa fase muito inicial. No modelo de asma e obesidade, após 17 semanas de tratamento, observou-se incremento da linfangiogénese no TAV, mas não no TAS. A resposta inflamatória avaliada através dos diferentes parâmetros permite afirmar que num estadio inicial de obesidade a proliferação linfática poderá estar a ser retardada pela hipertrofia adipocitária. A libertação de adipocinas será observada apenas numa fase posterior, desencadeando todo o processo inflamatório que incrementará a proliferação linfática. Adicionalmente, é possível sugerir que a maior pressão à qual o TAV se encontra sujeito não favorece a proliferação linfática, pelo menos num estadio incial.

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Introdução PARTE 1 - Noções gerais e metodologias de medição baseadas nos diferenciais 1.1. Noção de risco 1.2. Principais riscos na actividade bancária 1.3. Modelos de quantificação do risco da taxa de juro 1.4. Modelos para quantificar o risco de reinvestimento 1.5. O modelo de diferencial de duração (DD) 1.6. Modelos para quantificar o risco de preço 1.7. Diferencial de duração da situação líquida 1.8. Vantagens/desvantagens dos modelos de duração (resultado e situação líquida) 1.9. Perspectivas e conclusão sobre os Modelos de Diferencial de Fundos e Duração PARTE II - Conceito de VAR 2.1 A noção de VAR (Valor em Risco) 2.2 Conceitos-chave dos modelos VAR 2.3 Fórmula de cálculo da duração modificada 2.4 A importância da duração para determinar a sensibilidade da taxa de juro 2.5 A problemática da convexidade 2.6 O conceitos de volatilidade 2.7 A agregação dos riscos 2.8 O tratamento do VAR com a matriz de correlação do andamento das taxas de juro 2.9 Esquemas sequenciais de cálculo da volatilidade preço - taxa de juro e VAR PARTE III - Casos práticos de VAR 3.1 As relações entre as taxas a prazo (forward) e as taxas à vista (spot) 3.2 Desenvolvimento de um caso prático 3.3 Cálculo do diferencial de duração e do VAR aplicado à situação líquida 3.4 Admissão de pressupostos 3.5 Os diferentes VAR´s 3.6 A importância do VAR no contexto de gestão de risco numa instituição 3.7 Os modelos de simulação estática e dinâmica PARTE IV - Situações especiais 4.1 O tratamento dos FRA´s e futuros 4.2 O tratamento das opções 4.3 O tratamento dos swap´s taxa de juro 4.4 A aplicação do modelo VAR aos riscos taxa de juro e cambial 4.5 A utilização dos modelos VAR na afectação do capital (RAROC) 4.6 A análise da instruçaõ nº 19/2005 ANEXOS Anexo 1 - Instrução nº 19/2005: risco de taxa de juro da carteira bancária Anexo 2 - Instrução nº 72/96: Princípios orientadores para ocontrolo do risco da taxa de juro Anexo 3 - Anexo V do Aviso nº 7/96 Conclusão Índice dos Quadros Bibliografia

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As espécies reativas de oxigénio (ROS) estão envolvidas no desenvolvimento de dor neuropática. No entanto, a aplicação clínica de moléculas antioxidantes no tratamento desta patologia tem demonstrado pouca eficácia. A inibição da NADPH oxidase (NOX), uma das principais fontes de ROS, poderá ser uma boa estratégia terapêutica. O nosso grupo verificou que a apocinina (inibidor da NOX) melhora parcialmente os sintomas de dor neuropática e a disfunção redox espinhal no modelo SNI (spared nerve injury). De forma a melhorar este efeito terapêutico, o presente estudo insere-se num projeto maior, que visa identificar as isoformas da NOX envolvidas na fisiopatologia da doença e avaliar o efeito da administração de inibidores específicos para essas isoformas. Assim, propusemo-nos a avaliar a disfunção redox espinhal em fases precoces dador neuropática periférica induzida pelo modelo SNI no Rato, relacionando-a com os comportamentos de dor demonstrados pelos animais. Foram constituídos três grupos experimentais: SNI, sham e naïve, com subgrupos testados e sacrificados aos dias 1, 3, 7 e 14 após a cirurgia. Avaliou-se a sensibilidade mecânica (vonFrey e pinprick) e ao frio (acetona) dos animais, sacrificaram-se e recolheram-se as medulas espinhais para análise imunohistoquímica, com marcadores de dano oxidativo no DNA e de dano nitrosativo. Ao contrário dos animais sham, que demonstraram um comportamento muito próximo dos naïve, os animais SNI desenvolveram alodínia mecânica e ao frio e hiperalgesia mecânica na pata ipsilateral. No entanto, o dano oxidativo no corno dorsal ipsilateral da medula espinhal apresentou-se idêntico nos grupos SNI e sham ao longo dos 14 dias de estudo, não havendo também diferenças entre os cornos ipsi e contralateral à lesão nervosa. É possível que o desenvolvimento de dor neuropática nos animais SNI não se faça acompanhar de disfunção redox espinhal, pelo menos até aos 14 dias pós indução. O facto de a lesão nervosa no modelo SNI se localizar numa porção distal do ciático, ao contrário de outros modelos em que o stresse oxidativo espinhal foi já descrito, poderia explicar essas diferenças. Em todo o caso, considerando que os resultados comportamentais obtidos indicam que as cirurgias SNI e sham causam diferentes níveis de sensibilização nos animais, parece-nos fulcral prolongar os tempos de neuropatia, e executar uma avaliação do estado redox com outros marcadores, de forma a elucidar se, de facto, existem ROS envolvidas nesta sensibilização e, em caso positivo, poder identificar essas espécies, bem como as suas fontes.

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In this paper we study the optimal natural gas commitment for a known demand scenario. This study implies the best location of GSUs to supply all demands and the optimal allocation from sources to gas loads, through an appropriate transportation mode, in order to minimize total system costs. Our emphasis is on the formulation and use of a suitable optimization model, reflecting real-world operations and the constraints of natural gas systems. The mathematical model is based on a Lagrangean heuristic, using the Lagrangean relaxation, an efficient approach to solve the problem. Computational results are presented for Iberian and American natural gas systems, geographically organized in 65 and 88 load nodes, respectively. The location model results, supported by the computational application GasView, show the optimal location and allocation solution, system total costs and suggest a suitable gas transportation mode, presented in both numerical and graphic supports.

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This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

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To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

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Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

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In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

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Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

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The ability to locate an individual is an essential part of many applications, specially the mobile ones. Obtaining this location in an open environment is relatively simple through GPS (Global Positioning System), but indoors or even in dense environments this type of location system doesn't provide a good accuracy. There are already systems that try to suppress these limitations, but most of them need the existence of a structured environment to work. Since Inertial Navigation Systems (INS) try to suppress the need of a structured environment we propose an INS based on Micro Electrical Mechanical Systems (MEMS) that is capable of, in real time, compute the position of an individual everywhere.

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Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.