989 resultados para Network tariffs allocation
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The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.
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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.
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Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.
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In the context of electricity markets, transmission pricing is an important tool to achieve an efficient operation of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for this reason transmission tariffs must follow strict criteria. This paper presents the following methods to tariff the use of transmission networks by electricity market players: Post-Stamp Method; MW-Mile Method Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price. A nine bus transmission network is used to illustrate the application of the tariff methods.
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Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.
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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.
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Mestrado em Engenharia Informática
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Mestrado em Engenharia Electrotécnica e de Computadores
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The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.
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This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.
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This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327
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Actualmente, os sistemas embebidos estão presentes em toda a parte. Embora grande parte da população que os utiliza não tenha a noção da sua presença, na realidade, se repentinamente estes sistemas deixassem de existir, a sociedade iria sentir a sua falta. A sua utilização massiva deve-se ao facto de estarem practicamente incorporados em quase os todos dispositivos electrónicos de consumo, telecomunicações, automação industrial e automóvel. Influenciada por este crescimento, a comunidade científica foi confrontada com novos problemas distribuídos por vários domínios científicos, dos quais são destacados a gestão da qualidade de serviço e gestão de recursos - domínio encarregue de resolver problemas relacionados com a alocação óptima de recursos físicos, tais como rede, memória e CPU. Existe na literatura um vasto conjunto de modelos que propõem soluções para vários problemas apresentados no contexto destes domínios científicos. No entanto, não é possível encontrar modelos que lidem com a gestão de recursos em ambientes de execução cooperativos e abertos com restrições temporais utilizando coligações entre diferentes nós, de forma a satisfazer os requisitos não funcionais das aplicações. Devido ao facto de estes sistemas serem dinâmicos por natureza, apresentam a característica de não ser possível conhecer, a priori, a quantidade de recursos necessários que uma aplicação irá requerer do sistema no qual irá ser executada. Este conhecimento só é adquirido aquando da execução da aplicação. De modo a garantir uma gestão eficiente dos recursos disponíveis, em sistemas que apresentam um grande dinamismo na execução de tarefas com e sem restrições temporais, é necessário garantir dois aspectos fundamentais. O primeiro está relacionado com a obtenção de garantias na execução de tarefas de tempo-real. Estas devem sempre ser executadas dentro da janela temporal requirida. O segundo aspecto refere a necessidade de garantir que todos os recursos necessários à execução das tarefas são fornecidos, com o objectivo de manter os níveis de performance quer das aplicações, quer do próprio sistema. Tendo em conta os dois aspectos acima mencionados, o projecto CooperatES foi especificado com o objectivo de permitir a dispositivos com poucos recursos uma execução colectiva de serviços com os seus vizinhos, de modo a cumprir com as complexas restrições de qualidade de serviço impostas pelos utilizadores ou pelas aplicações. Decorrendo no contexto do projecto CooperatES, o trabalho resultante desta tese tem como principal objectivo avaliar a practicabilidade dos conceitos principais propostos no âmbito do projecto. O trabalho em causa implicou a escolha e análise de uma plataforma, a análise de requisitos, a implementação e avaliação de uma framework que permite a execução cooperativa de aplicações e serviços que apresentem requisitos de qualidade de serviço. Do trabalho desenvolvido resultaram as seguintes contribuições: Análise das plataformas de código aberto que possam ser utilizadas na implementação dos conceitos relacionados com o projecto CooperatES; Critérios que influenciaram a escolha da plataforma Android e um estudo focado na análise da plataforma sob uma perspectiva de sistemas de tempo-real; Experiências na implementação dos conceitos do projecto na plataforma Android; Avaliação da practicabilidade dos conceitos propostos no projecto CooperatES; Proposta de extensões que permitam incorporar características de sistemas de tempo real abertos na plataforma Android.
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Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.
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This work shows the influence of using different allocation approaches when modelling the inventory analysis in a soybean biodiesel life cycle assessment (LCA). Results obtained using mass, energy and economic based allocations are compared, focusing on the following aspects: normalised potential environmental impact (PEI) categories, total PEI and relative contributions to the total PEI from each life cycle stage and environmental impact category. Similar results are obtained either using economic and energy based allocations. However, different results are obtained when mass based allocation is used when compared with the other two. This study also illustrates that using different allocation approaches in biodiesel LCA may influence the final conclusions, especially in comparative assertions, emphasising the need to perform a sensitivity analysis in the LCA interpretation step.
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Doutoramento em Gestão