Les préoccupations environnementales croissantes et la raréfaction des énergies fossiles amènent les constructeurs automobiles à proposer des véhicules efficients hybridant des chaînes de traction conventionnelles. Ces travaux de recherche sont focalisés sur l'hybridation thermique/électrique. Ils présentent une méthodologie de conception optimale pour identifier des voies de progrès et orienter la définition de futures chaînes de traction à haut rendement énergétique. Ils sont basés sur une démarche d'ingénierie systémique qui s'appuie sur trois principaux leviers: l'architecture de la chaîne de traction, la stratégie de gestion énergétique et la définition des organes électriques de puissance. Différentes architectures de chaînes de traction hybrides électriques sont comparées en se basant sur la consommation minimale atteignable par chacune d'entre elles sur cycles automobiles. Pour déterminer ces seuils de consommation, une stratégie de commande optimale basée sur un algorithme de programmation dynamique est développée. Les résultats montrent l'intérêt de l'hybridation parallèle pour concevoir une chaîne de traction efficiente.Les sollicitations des organes électriques de puissance sont déterminées et analysées pour en spécifier le dimensionnement optimal. Deux structures de machines électriques ont été modélisées par réseaux de réluctances pour établir des cartographies de pertes et comparer la performance en émissions de CO2 du véhicule. Cette approche permet d'identifier des axes d'améliorations et on montre qu'une solution de type alterno-démarreur permettrait des gains d'environ 33% en émissions de CO2 par rapport au véhicule conventionnel. / On-going oil stock depletion and growing environmental concerns lead automakers to develop more efficient powertrains. Today, one of the most promising way forward consists in research on hybrid systems. The present work is focused on thermal/electric hybridization for HEV vehicle and presents an optimal methodology to identify key guidelines and design efficient systems. Defining the most promising efficient powertrain requires a systemic design which is based in this study on three main levers : powertrain architecture, energy management and electric components design. Different powertrains architectures are compared to the lowest fuel consumption that can be reached by each powertrain for a given driving cycle. Their optimal energetic performances are determined by using optimal control strategies and dynamic programming. The simulations results show that the most promising hybrid powertrain is the parallel one. At each step of time of the drivings cycles, the parallel hybrid powertrain behavior is more closely analyzed so as to provide technical specifications for an optimal sizing of the electric components. It points out the operating point and the driving cycles for which the electric machine has to be optimized. Two electric machines topologies derived from a starter-alternator architecture, are modeled by using reluctance network to provide losses map and compare CO2 saving of the vehicle. This approach has both identified areas for powertrain architecture improvement and components design optimization to achieve a better global efficiency of the system. It is shown that a starter-alternator could provide 33% of CO2 saving compared to a conventional car.

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The application offloading problem for Mobile Cloud Computing aims at improving the mobile user experience by leveraging the resources of the cloud. The execution of the mobile application is offloaded to the cloud, saving energy at the mobile device or speeding up the execution of the application. We improve the accuracy and performance of application offloading solutions in three main directions. First, we propose a novel fine-grained application model that supports complex module dependencies such as sequential, conditional and parallel module executions. The model also allows for multiple offloading decisions that are tailored towards the current application, network, or user contexts. As a result, the model is more precise in capturing the structure of the application and supports more complex offloading solutions. Second, we propose three cost models, namely, average-based, statistics-based and interval-based cost models, defined for the proposed application model. The average-based approach models each module cost by the expected cost value, and the expected cost of the entire application is estimated considering each of the three module dependencies. The novel statistics-based cost model employs Cumulative Distribution Function (CDFs) to represent the costs of the modules and of the mobile application, which is estimated considering the cost and dependencies of the modules. This cost model opens the doors for new statistics-based optimization functions and constraints whereas the state of the art only support optimizations based on the average running cost of the application. Furthermore, this cost model can be used to perform statistical analysis of the performance of the application in different scenarios such as varying network data rates. The last cost model, the interval-based, represents the module costs via intervals in order to addresses the cost uncertainty while having lower requirements and computational complexity than the statistics-based model. The cost of the application is estimated as an expected maximum cost via a linear optimization function. Finally, we present offloading decision algorithms for each cost model. For the average-based model, we present a fast optimal dynamic programming algorithm. For the statistics-based model, we present another fast optimal dynamic programming algorithm for the scenario where the optimization function meets specific properties. Finally, for the interval-based cost model, we present a robust formulation that solves a linear number of linear optimization problems. Our evaluations verify the accuracy of the models and show higher cost savings for our solutions when compared to the state of the art.

Orientador: Christiano Lyra Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T02:20:44Z (GMT). No. of bitstreams: 1 VizcainoGonzalez_JoseFederico_M.pdf: 972282 bytes, checksum: 652889ccc97d9102a9333902b4169885 (MD5) Previous issue date: 2003 / Resumo: As perdas técnicas de energia nas redes primarias de distribuição são decorrentes das resistências elétricas nas linhas. Pela natureza indutiva de algumas cargas e reatâncias das linhas, parte da energia dissipada é devida aos fluxos de potências reativas entre a subestação e os pontos de carga. Capacitores instalados próximo às cargas podem fornecer energia reativa local, diminuindo as perdas de energia na rede. Este trabalho apresenta inovações conceituais e de implementação que permitem o resgate da abordagem por programação dinâmica para a solução do problema de instalação e dimensionamento de capacitores fixos em redes de distribuição, para perfis de cargas fixos ou variáveis. O trabalho também aborda o problema de controle de capacitores chaveados, propondo duas novas abordagens. A primeira abordagem desenvolve uma versão de sistemas complexos adaptativos, também chamados sistemas classificadores. A segunda abordagem corresponde a uma especialização dos conceitos de programação dinâmica esenvolvidos para o problema de instalação de capacitores. Estudos de casos em redes reais de grande porte ilustram as possibilidades das metodologias desenvolvidas / Abstract: Technical energy losses in primary distribution networks are due to electrical resistances in lines. Due to reactance of power lines and inductive nature of some loads, part of the energy dissipated is due to reactive power that travels back and forth in lines, all the way from power sources to load points. Capacitors installed near load points can provide local complementary reactive power that decrease losses. This work presents conceptual and implementation innovations that allows to rescue the dynamic programming approach for the capacitors sizing and allocation problem in distribution networks, for fixes and variables loads. The work also presents two approaches to the capacitors control problem. The first approach is the development of a complex adaptive system (a classifier systems). The second approach to the capacitor control problem is a specialization of dynamic programming concepts, developed for the capacitors placement problem. Case studies in large real networks illustrate the possibilities of the developed methodologies / Mestrado / Automação / Mestre em Engenharia Elétrica

Orientadores: Christiano Lyra Filho, Fábio Luiz Usberti / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-27T03:25:56Z (GMT). No. of bitstreams: 1 Bacalhau_EduardoTadeu_D.pdf: 1630102 bytes, checksum: 258db7b09d8ce71b7d9a577e1993a3c2 (MD5) Previous issue date: 2015 / Resumo: Este trabalho explora alternativas para a determinação das melhores políticas de planejamento das ações de manutenção preventiva em redes de distribuição de energia elétrica. O problema é uma extensão de abordagens da área de manutenção centrada em confiabilidade (MCC), que vem sendo objeto de pesquisas ao longo das últimas décadas. Por se tratar de um problema de otimização combinatória de difícil solução, são poucos os artigos publicados que envolvem sistemas de escala real, e a maioria dentre esses utiliza meta-heurísticas como estratégia de solução. A abordagem desenvolvida neste trabalho é baseada na técnica de otimização denominada programação dinâmica. Duas estratégias para a redução do espaço de busca são adotadas: uma delas procura identificar e eliminar soluções dominadas; a segunda estratégia envolve a aplicação do processo de otimização da programação dinâmica em torno de uma vizinhança de uma solução promissora, movendo iterativamente em um espaço de soluções --- uma abordagem inspirada na programação dinâmica diferencial discreta. A combinação dessas duas estratégias é denominada Programação Dinâmica com Reduções de Espaço de Estados (PDREE). O trabalho investiga também a construção de estratégias híbridas. Uma das alternativas utiliza um algoritmo genético híbrido para a construção de planos de manutenção iniciais de boa qualidade, posteriormente otimizados pela PDREE. A segunda estratégia híbrida utiliza a PDREE para a construção de boas populações iniciais de soluções, posteriormente otimizada pelo algoritmo genético híbrido. As abordagens desenvolvidas são aplicadas a problemas de escala real e comparadas à abordagem por algoritmo genético híbrido. Os resultados mostram que as ideias desenvolvidas na tese estendem o estado-da-arte sobre a otimização de políticas de manutenção em redes de distribuição de grande porte / Abstract: This work explores alternatives to determine the best planning policies for preventive maintenance on electric power distribution systems. The problem is an extension of approaches of the reliability-centered maintenance area that has been studied allong the last decades. Since this problem is a hard combinatorial optimization problem, there are few works that address real-life systems, and most of these works use methods based on metaheuristic as solution strategy. The approaches proposed in this work are based on the optimization technique named dynamic programming. Two strategies are developed to reduce the search space of dynamic programming: the first strategy seeks to identify and eliminate dominated solutions; the second strategy confines the dynamic programming optimization procedures to the neighborhood of good solutions that move iteratively in the solution space---an approach inspired by the discrete differential dynamic programming method. The combination of both strategies is denominated Dynamic Programming with State Space Reductions (DPSSR). The work also investigates the development of hybrid strategies. One of the alternatives uses a hybrid genetic algorithm to obtain a promising initial maintenance strategy, further optimized by the DPSSR. The second hybrid strategy uses the DPSSR for constructing an initial good population, further optimized by a hybrid genetic algorithm. All the approaches are applied to real-life problems and compared to a pure hybrid genetic algorithm approach. The results show that the ideas developed in the thesis improve the state-of-the-art in obtaining the best maintenance policies for large distribution networks / Doutorado / Automação / Doutor em Engenharia Elétrica

Esta dissertação aborda o problema de redução do consumo de combustível para veículos. Com esse objetivo, realiza-se o levantamento de um modelo estocástico e de seus parâmetros, o desenvolvimento de um controlador para o veículo, e análise dos resultados. O problema considera a interação com o trânsito de outros veículos, que limita a aplicação de resultados antes disponíveis. Para isto, propõe-se modelar a dinâmica do problema de maneira aproximada, usando sistemas com saltos markovianos, e levantar as probabilidades de transição dos estados da cadeia através de um modelo mais completo para o trânsito no percurso. / This dissertation deals with control of vehicles aiming at the fuel consumption optimization, taking into account the interference of traffic. Stochastic interferences like this and other real world phenomena prevents us from directly applying available results. We propose to employ a relatively simple system with Markov jumping parameters as a model for the vehicle subject to traffic interference, and to obtain the transition probabilities from a separate model for the traffic. This dissertation presents the model identification, the solution of the new problem using dynamic programming, and simulation of the obtained control.

Neste trabalho, apresenta-se um método para o Planejamento de Redes de Distribuição Secundária. O modelo básico desenvolvido baseia-se em técnica de programação dinâmica a fim de selecionar a política de evolução de trocas de transformadores de distribuição e rede secundária, com mínimo custo operacional dentro de limites de qualidade de serviço, para o atendimento de carga crescente no tempo em uma área de estudo restrita. Inicialmente, apresenta-se a filosofia básica do método, incluindo-se os dados necessários, critérios de planejamento e metodologia para o cálculo elétrico de redes secundárias. Em sequência, são apresentados três modelos para a solução do problema; tais modelos são diferenciados pela eliminação progressiva de hipóteses simplificativas. Nos dois primeiros modelos, a carga e seu crescimento são supostos uniformemente distribuídos ao longo dos trechos da rede secundária. No terceiro modelo, a distribuição da carga dos pontos presentes na rede secundária, durante o período de estudo, é estabelecida por procedimento randômico, com o único vínculo de serem mantidos os mercados globais de demanda e número de consumidores na área em estudo. Posteriormente, estabelece-se um exemplo de aplicação que permite proceder à comparação entre os três modelos desenvolvidos. Finalizando o trabalho, são estabelecidas as conclusões, possibilidades de aplicação do método em diversos estudos do sistema de Distribuição Secundária e são tecidos comentários sobre tópicos para ulterior desenvolvimento. / This work focuses on a method for the Planning of Secondary Distribution Systems. The basic model deals with dynamic programming in order to get an optimized design - Distribution Transformer and Secondaries - which presents the lowest operation cost within service quality limits in order to supply growing load on a restricted area. Initially the basic concepts of the method are presented, including the establishment of the data base, planning criteria and methodology in order to get operating conditions at secondary networks. Concerning this method, three computational models were established. These models differ form each other as far as some of the simplified hypothesis are eliminated. The first two models consider a uniform distribution of loads along the secondary system. The third model establishes a randomic distribution of loads on the restricted studying area. Following an application example, comparison is proceeded among the developed models. Eventually the conclusions, some possible applications of the method on Distribution system studies and research topics for further developments are settled.

Uma das tarefas mais básicas em bioinformática é a comparação de seqüências feita por algoritmos de alinhamento, que modelam as alterações evolutivas nas seqüências biológicas através de mutações como inserção, remoção e substituição de símbolos. Este trabalho trata de generalizações nos algoritmos de alinhamento que levam em consideração outras mutações conhecidas como rearranjos, mais especificamente, inversões, duplicações em tandem e duplicações por transposição. Alinhamento com inversões não tem um algoritmo polinomial conhecido e uma simplificação para o problema que considera somente inversões não sobrepostas foi proposta em 1992 por Schöniger e Waterman. Em 2003, dois trabalhos independentes propuseram algoritmos com tempo O(n^4) para alinhar duas seqüências com inversões não sobrepostas. Desenvolvemos dois algoritmos que resolvem este mesmo problema: um com tempo de execução O(n^3 logn) e outro que, sob algumas condições no sistema de pontuação, tem tempo de execução O(n^3), ambos em memória O(n^2). Em 1997, Benson propôs um modelo de alinhamento que reconhecesse as duplicações em tandem além das inserções, remoções e substituições. Ele propôs dois algoritmos exatos para alinhar duas seqüências com duplicações em tandem: um em tempo O(n^5) e memória O(n^2), e outro em tempo O(n^4) e memória O(n^3). Propomos um algoritmo para alinhar duas seqüências com duplicações em tandem em tempo O(n^3) e memória O(n^2). Propomos também um algoritmo para alinhar duas seqüências com transposons (um tipo mais geral que a duplicação em tandem), em tempo O(n^3) e memória O(n^2). / Sequence comparison done by alignment algorithms is one of the most fundamental tasks in bioinformatics. The evolutive mutations considered in these alignments are insertions, deletions and substitutions of nucleotides. This work treats of generalizations introduced in alignment algorithms in such a way that other mutations known as rearrangements are also considered, more specifically, we consider inversions, duplications in tandem and duplications by transpositions. Alignment with inversions does not have a known polynomial algorithm and a simplification to the problem that considers only non-overlapping inversions were proposed by Schöniger and Waterman in 1992. In 2003, two independent works proposed algorithms with O(n^4) time to align two sequences with non-overlapping inversions. We developed two algorithms to solve this problem: one in O(n^3 log n) time and other, considering some conditions in the scoring system, in O(n^3) time, both in O(n^2) memory. In 1997, Benson proposed a model of alignment that recognized tandem duplication, insertion, deletion and substitution. He proposed two exact algorithms to align two sequences with tandem duplication: one in O(n^5) time and O(n^2) memory, and other in O(n^4) time and O(n^3) memory. We propose one algorithm to align two sequences with tandem duplication in O(n^3) time and O(n^2) memory. We also propose one algorithm to align two sequences with transposons (a type of duplication more general than tandem duplication), in O(n^3) time and O(n^2) memory.

Due to the potential impact of next-generation sequencing NGS, we have seen a rapid increase in genomic information and annotation information that can be naturally mapped to genomic locations. In cancer research, for example, there are significant efforts to chart DNA methylation at single-nucleotide resolution. The NIH Roadmap Epigenomics Projects, on the other hand, has set out to chart a large number of different histone modifications. However, throughout the last few years, a very diverse set of aspects has become the aim of large-scale experiments with a genome-wide readout. Therefore, the identification of functional units of the genomic DNA is considered a significant and essential challenge. Subsequently, we have been motivated to implement multi-dimensional segmentation approaches that serve gene variety and genome heterogeneity. The segmentation of multivariate genomic, epigenomic, and transcriptomic data from multiple time points, tissue, and cell types to compare changes in genomic organization and identify common elements form the headline of our research. Next generation sequencing offers a rich material used in bioinformatics research to find answers, solutions, and exploration for the molecular functions, diseases causes, etc. Rapid advances in technology also have led to the proliferation of types of experiments. Although sharing next-generation sequencing as the readout produces signals with an entirely different inherent resolution, ranging from a precise transcript structure at the single-nucleotide resolution to pull-down and enrichment-based protocols with resolutions on order 100 nt to chromosome conformation data that are only accurate at kilobase resolution. Therefore, the main goal of the dissertation project is to design, implement, and test novel segmentation algorithms that work on one- and multi-dimensional and can accommodate data of different types and resolutions. The target data in this project is multivariate genetic, epigenetic, transcriptomic, and proteomic data; the reason is that these datasets can change under the effect of several conditions such as chemical, genetic and epigenetic modifications. A promising approach towards this end is to identify intervals of the genomic DNA that behave coherently in multiple conditions and tissues and could be defined as intervals on which all measured quantities are constant within each experiment. A naive approach would take each data set in isolation and estimate intervals in which the signal at hand is constant. Another approach takes datasets all at once as input without recurring to one-dimensional segmentation. Once implemented, the algorithm should be applied on heterogeneous genomic, transcriptomic, proteomic, and epigenomic data; the aim here is to draw and improve the map of functionally coherent segments of a genome. Current approaches either focus on individual datasets, as in the case of tiling array transcriptomics data; Or on the analysis of comparable experiments such as ChIP-seq data for various histone modifications. The simplest sub-problem in segmentation is to decide whether two adjacent intervals should form two distinct segments or whether they should be combined into a single one. We have to find out how this should be done in the multi-D segmentation; in 1-D, this is relatively well known. This leads to a segmentation of the genome concerning the particular dataset. The intersection of segmentations for different datasets could identify then the DNA elements.