917 resultados para Power Sensitivity Model
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The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.
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Dissertation to obtain a Master Degree in Biotechnology
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Actualmente a humanidade depara-se com um dos grandes desafios que é o de efectivar a transição para um futuro sustentável. Logo, o sector da energia tem um papel chave neste processo de transição, com principal destaque para a energia solar, tendo em conta que é uma das fontes de energias renováveis mais promissoras, podendo no médiolongo prazo, tornar-se uma das principais fontes de energia no panorama energético dos países. A energia solar térmica de concentração (CSP), apesar não ser ainda conhecida em Portugal, possui um potencial relevante em regiões específicas do nosso território. Logo, o objectivo deste trabalho é efectuar uma análise detalhada dos sistemas solares de concentração para produção de energia eléctrica, abordando temas, tais como, o potencial da energia solar, a definição do processo de concentração solar, a descrição das tecnologias existentes, o estado da arte do CSP, mercado CSP no mundo, e por último, a análise da viabilidade técnico-económica da instalação de uma central tipo torre solar de 20 MW, em Portugal. Para que este objectivo fosse exequível, recorreu-se à utilização de um software de simulação termodinâmica de centrais CSP, denominado por Solar Advisor Model (SAM). O caso prático foi desenvolvido para a cidade de Faro, onde foram simuladas quatro configurações distintas para uma central do tipo torre solar de 20 MW. Foram apresentados resultados, focando a desempenho diário e anual da central. Foi efectuada uma análise para avaliação da influência da variabilidade dos parâmetros, localização geográfica, múltiplo solar, capacidade de armazenamento de calor e fracção de hibridização sobre o custo nivelado da energia (LCOE), o factor de capacidade e a produção anual de energia. Conjuntamente, é apresentada uma análise de sensibilidade, com a finalidade de averiguar quais os parâmetros que influenciam de forma mais predominante o valor do LCOE. Por último, é apresentada uma análise de viabilidade económica de um investimento deste tipo.
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Many-core platforms are an emerging technology in the real-time embedded domain. These devices offer various options for power savings, cost reductions and contribute to the overall system flexibility, however, issues such as unpredictability, scalability and analysis pessimism are serious challenges to their integration into the aforementioned area. The focus of this work is on many-core platforms using a limited migrative model (LMM). LMM is an approach based on the fundamental concepts of the multi-kernel paradigm, which is a promising step towards scalable and predictable many-cores. In this work, we formulate the problem of real-time application mapping on a many-core platform using LMM, and propose a three-stage method to solve it. An extended version of the existing analysis is used to assure that derived mappings (i) guarantee the fulfilment of timing constraints posed on worst-case communication delays of individual applications, and (ii) provide an environment to perform load balancing for e.g. energy/thermal management, fault tolerance and/or performance reasons.
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20th International Conference on Reliable Software Technologies - Ada-Europe 2015 (Ada-Europe 2015), 22 to 26, Jun, 2015, Madrid, Spain.
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Herpes simplex virus type 1 (HSV-1) ophthalmic disease is the most common cause of corneal blindness in humans world-wide. Current culture techniques for HSV take several days and commercially available HSV laboratory based diagnostic techniques vary in sensitivity. Our study was conducted to evaluate the use of a quicker and simpler method to herpes ophthalmic diagnosis. Corneal smears were made by firm imprints of infected mouse eyes to glass slides, after smears were fixated with cold acetone, and an indirect immunofluorescence (IIF) method was performed using monoclonal antibodies in a murine model of ophthalmic herpes. Eye swabs from infected mice were inoculated in Vero cells for virus isolation. Cytology and histology of the eye were also performed, using hematoxylin-eosin routine. Mouse eyes were examined by slit-lamp biomicroscopy for evidence of herpetic disease at various times postinoculation. We made a comparative evaluation of sensitivity, specificity and speed of methods for laboratory detection of HSV. Our results indicate that this IIF method is quick, sensitive, specific and can be useful in the diagnosis of ophthalmic herpes as demonstrated in an animal model.
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Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.
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The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.
Multi-criteria optimisation approach to increase the delivered power in radial distribution networks
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This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.
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The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial
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Dissertação para obtenção do Grau de Mestre em Biotecnologia