928 resultados para Hybrid simulation-optimization
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Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.
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This study uses the process simulator ASPEN Plus and Life Cycle Assessment (LCA) to compare three process design alternatives for biodiesel production from waste vegetable oils that are: the conventional alkali-catalyzed process including a free fatty acids (FFAs) pre-treatment, the acid-catalyzed process, and the supercritical methanol process using propane as co-solvent. Results show that the supercritical methanol process using propane as co-solvent is the most environmentally favorable alternative. Its smaller steam consumption in comparison with the other process design alternatives leads to a lower contribution to the potential environmental impacts (PEI’s). The acid-catalyzed process generally shows the highest PEI’s, in particular due to the high energy requirements associated with methanol recovery operations.
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Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.
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In this paper we consider a differentiated Stackelberg model, when the leader firm engages in an R&D process that gives an endogenous cost-reducing innovation. The aim is to study the licensing of the cost-reduction by a two-part tariff. By using comparative static analysis, we conclude that the degree of the differentiation of the goods plays an important role in the results. We also do a direct comparison between our model and Cournot duopoly model.
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Com o presente trabalho é pretendido demonstrar a possibilidade de alimentação de um sistema de iluminação decorativa com recurso a soluções alternativas renováveis. O estudo é focado essencialmente na produção local de energia solar fotovoltaica e eólica. Inicialmente é efetuado o estudo técnico-económico da implementação de um sistema fotovoltaico. Posteriormente é efetuado o estudo da viabilidade técnico-económica da implementação do sistema hibrido, composto por um sistema fotovoltaico e um sistema eólico, optando pelo que mais se adequa à alimentação do sistema de iluminação decorativa exterior. Esta dissertação descreve a metodologia que procura melhorar a eficiência do sistema de led com o auxílio de ensaios em laboratório e simulação em software, com o objetivo de adaptar os sistemas de led instalados pela empresa ao sistema hibrido dimensionado. Finalmente, é efetuada a análise comparativa entre o atual sistema de iluminação decorativa e o sistema renovável dimensionado mais favorável para alimentar sistemas de iluminação decorativa. Procura-se assim com este projeto para além de apresentar um estudo teórico, proporcionar uma orientação à implementação de sistemas de microprodução destinados a alimentar sistemas de iluminação decorativa exterior.
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In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Perfil Energia, Refrigeração e Climatização
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An optimised version of the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method for simultaneous determination of 14 organochlorine pesticides in carrots was developed using gas chromatography coupled with electron-capture detector (GC-ECD) and confirmation by gas chromatography tandem mass spectrometry (GC-MS/MS). A citrate-buffered version of QuEChERS was applied for the extraction of the organochlorine pesticides, and for the extract clean-up, primary secondary amine, octadecyl-bonded silica (C18), magnesium sulphate (MgSO4) and graphitized carbon black were used as sorbents. The GC-ECD determination of the target compounds was achieved in less than 20 min. The limits of detection were below the EUmaximum residue limits (MRLs) for carrots, 10–50 μg kg−1, while the limit of quantification did exceed 10 μg kg−1 for hexachlorobenzene (HCB). The introduction of a sonication step was shown to improve the recoveries. The overall average recoveries in carrots, at the four tested levels (60, 80, 100 and 140 μg kg−1), ranged from 66 to 111% with relative standard deviations in the range of 2– 15 % (n03) for all analytes, with the exception of HCB. The method has been applied to the analysis of 21 carrot samples from different Portuguese regions, and β-HCH was the pesticide most frequently found, with concentrations oscillating between less than the limit of quantification to 14.6 μg kg−1. Only one sample had a pesticide residue (β-HCH) above the MRL, 14.6 μg kg−1. This methodology combines the advantages of both QuEChERS and GC-ECD, producing a very rapid, sensitive and reliable procedure which can be applied in routine analytical laboratories.
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The present work describes the optimization of a short-term assay, based on the inhibition of the esterase activity of the alga Pseudokirchneriella subcapitata, in a microplate format. The optimization of the staining procedure showed that the incubation of the algal cells with 20 μmolL−1 fluorescein diacetate (FDA) for 40 min allowed discrimination between metabolic active and inactive cells. The shortterm assay was tested using Cu as toxicant. For this purpose, algal cells, in the exponential or stationary phase of growth, were exposed to the heavy metal in growing conditions. After 3 or 6 h, cells were subsequently stained with FDA, using the optimized procedure. For Cu, the 3- and 6-h EC50 values, based on the inhibition of the esterase activity of algal cells in the exponential phase of growth, were 209 and 130 μg L−1, respectively. P. subcapitata cells, in the stationary phase of growth, displayed higher effective concentration values than those observed in the exponential phase. The 3- and 6-h EC50 values for Cu, for cells in the stationary phase, were 443 and 268 μgL−1, respectively. This short-term microplate assay showed to be a rapid endpoint for testing toxicity using the alga P. subcapitata. The small volume required, the simplicity of the assay (no washing steps), and the automatic reading of the fluorescence make the assay particularly well suited for the evaluation of the toxicity of a high number of environmental samples.
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This paper is a contribution for the assessment and comparison of magnet properties based on magnetic field characteristics particularly concerning the magnetic induction uniformity in the air gaps. For this aim, a solver was developed and implemented to determine the magnetic field of a magnetic core to be used in Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry. The electromagnetic field computation is based on a 2D finite-element method (FEM) using both the scalar and the vector potential formulation. Results for the magnetic field lines and the magnetic induction vector in the air gap are presented. The target magnetic induction is 0.2 T, which is a typical requirement of the FFC NMR technique, which can be achieved with a magnetic core based on permanent magnets or coils. In addition, this application requires high magnetic induction uniformity. To achieve this goal, a solution including superconducting pieces is analyzed. Results are compared with a different FEM program.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações
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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia
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Although power-line communication (PLC) is not a new technology, its use to support communication with timing requirements is still the focus of ongoing research. Recently, a new infrastructure was presented, intended for communication using power lines from a central location to geographically dispersed nodes using inexpensive devices. This new infrastructure uses a two-level hierarchical power-line system, together with an IP-based network. Within this infrastructure, in order to provide end-toend communication through the two levels of the powerline system, it is necessary to fully understand the behaviour of the underlying network layers. The masterslave behaviour of the PLC MAC, together with the inherent dynamic topology of power-line networks are important issues that must be fully characterised. Therefore, in this paper we present a simulation model which is being used to study and characterise the behaviour of power-line communication.