994 resultados para Electricity Markets Simulation


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Doutor em Engenharia Química

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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

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The prediction of asymmetric equilibria with Stackelberg outcomes is clearly the most frequent result in the endogenous timing literature. Several experiments have tried to validate this prediction empirically, but failed to find support for it. By contrast, the experiments find that simultaneous-move outcomes are modal and that behavior in endogenous timing games is quite heterogeneous. This paper generalizes Saloner’s (1987) and Hamilton and Slutsky’s (1990) endogenous timing games by assuming that players are averse to inequality in payoffs. We explore the theoretical implications of inequity aversion and compare them to the empirical evidence. We find that this explanation is able to organize most of the experimental evidence on endogenous timing games. However, inequity aversion is not able to explain delay in Hamilton and Slutsky’s endogenous timing games.

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

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This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.

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The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

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The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places.

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This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.