В диссертации были изучены особенности использования методов машинного обучения в сфере страхования. Рассмотрены возможности архитектурного подхода в разработке модели машинного обучения. Осуществлен анализ тенденций цифровой трансформации сферы страхования. Осуществлена оценка результативности использования машинного обучения в страховании. Построена полная модель архитектуры ПАО СК «Росгосстрах». Разработана аналитическая модель машинного обучения в сфере тарификации страховой компании. На основе процессного подхода детально рассмотрены все фазы проекта по внедрению модели машинного обучения в деятельность страховой компании. Разработана и реализована имитационная модель управления проектом разработки и внедрения модели машинного обучения в деятельность страховой компании на основе различных сценарием. / The dissertation studied the features of using machine learning methods in the field of insurance. The possibilities of the architectural approach in the development of a machine learning model are considered. The analysis of trends in the digital transformation of the insurance industry has been carried out. The effectiveness of the use of machine learning in insurance has been evaluated. A complete model of the architecture of PJSC IC Rosgosstrakh was built. An analytical model of machine learning in the field of tariffing of an insurance company has been developed. Based on the process approach, all phases of the project to introduce a machine learning model into the activities of an insurance company are considered in detail. A simulation model for project management for the development and implementation of a machine learning model in the activities of an insurance company has been developed and implemented based on various scenarios.

A bilateral teleoperation system makes it possible for a human operator to interact with a remote environment and receive feedback from their actions. In this work, two different teleoperation architectures are studied, one well-established approach called position-force, and another approach called Model-Mediated Teleoperation (MMT). Position-force generates force feedback by measuring forces and sending them over the network, subject to network delay, while MMT generates nondelayed force feedback through a local environment model. The two architectures are compared in terms of transparency (quality of force feedback) and state consistency (equivalence of positions) under different network conditions. Up to 150 ms constant delay in Round Trip Time (RTT) is added. Both architectures are implemented as relatively simple versions of themselves. The case (teleoperation task) under consideration is pushing a cuboid object on a planar surface in a single direction. The MMT architecture is also studied in further detail, in terms of model complexity. Two versions of an MMT model are investigated, one simpler model that has a linear representation of energy loss and one less simple model that has a non-linear representation of energy loss. The purpose is to see what implications there are of increasing or decreasing model complexity. The results indicate that position-force has better performance in terms of both transparency and state consistency than both MMT models for all investigated network conditions. The simple version of MMT (linear model) performs better than the non-linear model, in terms of transparency and state consistency of cuboid positions, for all network conditions except the largest added delay. In terms of state consistency for the device positions, the non-linear model only performs better than the linear model with no added delay. / En distansstyrt system med tvåsidig kommunikation gör det möjligt för en mänsklig operatör att interragera med en avlägsen miljö och få återkoppling. I detta arbete studeras två olika arkitekturer för dessa typer av system. Ett väletablerat tillvägagångssätt som kallas position-force, och ett annat som kallas Model-Mediated Teleoperation (MMT). Position-force genererar kraftåterkoppling genom att mäta krafter och skicka dem över nätverket, utsatt för nätverksfördröjningar, medan MMT genererar en icke-fördröjd kraftåterkoppling från en lokalt modellerad miljö. De två arkitekturerna jämförs med avseende på ”transparency” (kvalitén på kraftåterkopplingen) och ”state consistency” (matchning av positioner) under olika nätverksförhållanden. De studerade förhållandena innefattar upp till 150 ms konstant fördröjning i tur och returtid. Båda arkitekturer implementeras som förhållandevis enkla versioner av sig själva. Det studerade fallet (operatörens uppgift) innefattar puttande på ett rätblock på en plan yta i en enkel riktning. MMT arkitekturen studeras även i vidare detalj med avseende på komplexitet hos den lokala modellen. Två versioner av MMT modellen undersöks, en enklare model som har en linjär representation av energiförlust, och en mer avancerad model som har en icke-linjär representation av energiförlust. Avsikten bakom detta är undersöka vilka implikationer som finns när komplexiteten hos modellen höjs eller sänks. Resultaten indikerar att position-force presterar bättre än MMT med avseende på både transparency och state consistency för alla undersökta nätverksfördröjningar. Den linjära MMT modellen presterar bättre än den icke-linjära modellen, med avseende på transparency och state consistency i rätblockspositioner, för alla nätverksförhållnaden utom den största pålagda fördröjningen. Vidare presterar den icke-linjära modellen bättre än den linjära modellen, med avseende på state consistency för styrande/styrd apparat, endast då ingen nätverksfördröjning läggs på.

Our society is becoming more and more electrified every day. However, a significant portion of the world’s electricity generation relies on the combustion of fossil fuels to produce heat, which is subsequently harnessed to generate electricity. One way of generating electricity from heat is by utilizing a Rankine cycle. The basis of a Rankine cycle is to heat a liquid to its boiling point, which causes an increase in pressure that is used to spin a turbine and a generator. Many industries, such as transportation and manufacturing, produce large amounts of waste heat that needs to be removed from the main process. A Rankine cycle variant called an organic Rankine cycle can be used in a heat power system to generate electricity from lower-temperature waste heat, which increases efficiency since less heat is wasted. This thesis focuses on constructing a dynamic model of Climeon’s heat power system called HP300. The HP300 utilizes an organic Rankine cycle to generate electricity. Dynamic modeling is valuable because it provides a deeper understanding of the system, which is beneficial for its development and improvement. Moreover, a system model has the potential to enhance the system’s performance by using advanced control methods. The HP300 consists of four main components: a pump, a turbine, an evaporator, and a condenser. Each component will be modeled individually, and the complete model will be constructed by combining the component models. Additionally, an in-depth investigation of an advanced modeling method for heat exchangers is to be conducted. The constructed model in this thesis has an average error of 4%. The pump and turbine were modeled as steady-state models, and the evaporator and condenser were modeled with data-driven state-space models. The most important output of the model is the power generated by the turbine. The power was modeled with an average error of 6%. The turbine model performs best for pressure ratios of 1.75 and above. The model for the condenser had larger errors than the evaporator since it had fewer input variables. Improving the model of the condenser would decrease the overall errors of the model. / Vårt samhälle blir mer och mer elektrifierat för varje dag som går. En betydande del av världens elproduktion är dock beroende av förbränning av fossila bränslen för att producera värme, som sedan utnyttjas för att generera el. Ett sätt att generera el från värme är att använda en Rankine-cykel. Grundprincipen för en Rankine-cykel är att värma upp en vätska till dess kokpunkt, vilket orsakar en tryckökning som används för att snurra en turbin, kopplad till en generator. Många industrier, som exempelvis transport och tillverkning, producerar stora mängder restvärme som måste avlägsnas från huvudprocessen. En variant av Rankine-cykeln som kallas organisk Rankinecykel kan användas i ett värmekraftsystem för att generera elektricitet från restvärme med lägre temperatur, vilket ökar effektiviteten eftersom mindre värme går förlorad. Detta examensarbete fokuserar på att konstruera en dynamisk modell av Climeons värmekraftsystem vid namn HP300. HP300 använder en organisk Rankine-cykel för att generera elektricitet. Dynamisk modellering är värdefull eftersom den ger en djupare förståelse av systemet, vilket är fördelaktigt för dess utveckling och förbättring. Dessutom har en systemmodell potentialen att förbättra systemets prestanda genom att använda avancerade reglermetoder. HP300 består av fyra huvudkomponenter: en pump, en turbin, en förångare och en kondensor. Varje komponent modelleras individuellt och hela modellen konstrueras genom att komponentmodellerna kombineras. Dessutom utförs en fördjupad undersökning av en avancerad modelleringsmetod av värmeväxlare. Den konstruerade modelled i detta arbete har ett genomsnittligt fel på 4%. Pumpen och turbinen modellerades som stationära modeller, medan förångaren och kondensorn modellerades med datadrivna state-space-modeller. Modellens viktigaste variabel är den effekt som genereras av turbinen. Den modellerade effekten hade ett genomsnittligt fel på 6%. Turbinmodellen presterar bäst för tryck-kvoter på 1, 75 och högre. Kondensor modellen hade större fel än förångaren eftersom den hade färre ingångsvariabler. En förbättring av kondensorns modell skulle förbättra modellens övergripande noggrannhet.

This study critically examines the (UHI) effect in urban and suburban neighbourhoods of Quito, Ecuador, over a 19-year period, focusing on the interplay between atmospheric pollution and urban/ suburban temperature. Utilizing Empirical Dynamic Modeling(EDM) and Convergent Cross-Mapping (CCM), this study dives into the nonlinear dynamics of environmental factors, a method that traditional linear models fail to address effectively.The results unveil a consistent and strong positive correlation across various neighbourhoods, with temperature fluctuations indicating a typical UHI effect. This is most noticeable in urbanized areas where the temperature is significantly higher due to dense infrastructure and reduced greenery, a pattern that diminishes as one moves towards the outskirts. Specifically, pollutants like PM2.5 exhibit a non-uniform positive correlation, suggesting their collective increase or decrease across different regions, whereas CO shows a very slight and inconsistent inverse relationship across locations. The causal analysis further substantiates a significant interaction between PM2.5 concentrations and temperature, with the data revealing a reciprocal predictive capacity between these variables. The CCM analysis, through its graphical representation of predictive skills, confirms the causal effect of PM2.5 on urban temperature, marking an essential contribution to understanding the UHI effect and its implications for urban environmental dynamics. This study provides a comprehensive overview of the UHI phenomenon, highlighting the intricate relationship between urbanization, atmospheric pollution, and climate. The findings emphasize the necessity for urban planning and policy to consider these complex interactions to mitigate the effects of climate change on urban environments.

no / The optimal operation policy of flexible RO systems is studied in this work. The design and operation of RO process is optimized and controlled considering variations in water demands and changing seawater temperature throughout the day. A storage tank is added to the system layout to provide additional operational flexibility and to ensure the availability of freshwater to customer at all times. A steady state model for the RO process is developed and linked with a dynamic model for the storage tank. The membrane modules are divided into a number of groups to add flexibility in operation to RO network. The total operating cost of the RO process is minimized in order to find the optimal layout and operating variables at discreet time intervals for three design scenarios. (C) 2013 Elsevier Ltd. All rights reserved.

Das Verhalten Biologischer Systeme wird durch eine Vielzahl regulatorischer Prozesse beeinflusst, die sich auf verschiedenen Ebenen abspielen. Die Forschung an diesen Regulationen hat stark von den großen Mengen von Hochdurchsatzdaten profitiert, die in den letzten Jahren verfügbar wurden. Um diese Daten zu interpretieren und neue Erkenntnisse aus ihnen zu gewinnen, hat sich die mathematische Modellierung als hilfreich erwiesen. Allerdings müssen die Daten vor der Integration in Modelle aggregiert und analysiert werden. Wir präsentieren vier Studien auf unterschiedlichen zellulären Ebenen und in verschiedenen Organismen. Zusätzlich beschreiben wir zwei Computerprogramme die den Vergleich zwischen Modell und Experimentellen Daten erleichtern. Wir wenden diese Programme in zwei Studien über die MAP Kinase (MAP, engl. mitogen-acticated-protein) Signalwege in Saccharomyces cerevisiae an, um Modellalternativen zu generieren und unsere Vorstellung des Systems an Daten anzupassen. In den zwei verbleibenden Studien nutzen wir bioinformatische Methoden, um Hochdurchsatz-Zeitreihendaten von Protein und mRNA Expression zu analysieren. Um die Daten interpretieren zu können kombinieren wir sie mit Netzwerken und nutzen Annotationen um Module identifizieren, die ihre Expression im Lauf der Zeit ändern. Im Fall der humanen somatischen Zell Reprogrammierung führte diese Analyse zu einem probabilistischen Boolschen Modell des Systems, welches wir nutzen konnten um neue Hypothesen über seine Funktionsweise aufzustellen. Bei der Infektion von Säugerzellen (Canis familiaris) mit dem Influenza A Virus konnten wir neue Verbindungen zwischen dem Virus und seinem Wirt herausfinden und unsere Zeitreihendaten in bestehende Netzwerke einbinden. Zusammenfassend zeigen viele unserer Ergebnisse die Wichtigkeit von Datenintegration in mathematische Modelle, sowie den hohen Grad der Verschaltung zwischen verschiedenen Regulationssystemen. / The behavior of all biological systems is governed by numerous regulatory mechanisms, acting on different levels of time and space. The study of these regulations has greatly benefited from the immense amount of data that has become available from high-throughput experiments in recent years. To interpret this mass of data and gain new knowledge about studied systems, mathematical modeling has proven to be an invaluable method. Nevertheless, before data can be integrated into a model it needs to be aggregated, analyzed, and the most important aspects need to be extracted. We present four Systems Biology studies on different cellular organizational levels and in different organisms. Additionally, we describe two software applications that enable easy comparison of data and model results. We use these in two of our studies on the mitogen-activated-protein (MAP) kinase signaling in Saccharomyces cerevisiae to generate model alternatives and adapt our representation of the system to biological data. In the two remaining studies we apply Bioinformatic methods to analyze two high-throughput time series on proteins and mRNA expression in mammalian cells. We combine the results with network data and use annotations to identify modules and pathways that change in expression over time to be able to interpret the datasets. In case of the human somatic cell reprogramming (SCR) system this analysis leads to the generation of a probabilistic Boolean model which we use to generate new hypotheses about the system. In the last system we examined, the infection of mammalian (Canis familiaris) cells by the influenza A virus, we find new interconnections between host and virus and are able to integrate our data with existing networks. In summary, many of our findings show the importance of data integration into mathematical models and the high degree of connectivity between different levels of regulation.

Un coeur de pile à combustible est un système multi-physique couplant des phénomènes de transport de matière et de charges (dans les électrodes et l'électrolyte), et de cinétique électrochimique (au niveau des sites réactionnels) ; phénomènes auxquels s'ajoutent des problèmes de thermique et de distribution des gaz réactifs. De nombreux modèles permettent de décrire localement ces phénomènes, par le biais d'équations aux dérivées partielles faisant intervenir l'espace et le temps. Ces modèles, aussi précis soient-ils, ne sont en pratique guère utilisables dans une approche système, dès lors que l'on cherche à étudier un ensemble complexe dans lequel le coeur de pile n'est qu'un élément parmi d'autres. Il existe bien des modèles dynamiques semi-empiriques pour lesquels la cellule électrochimique est représentée par un circuit électrique équivalent dont certains paramètres sont déterminés expérimentalement, par des mesures spectroscopiques en particulier. L'inconvénient de cette approche vient de ce que les modèles obtenus, de type "petits signaux", ne sont en toute rigueur valables qu'autour d'un point de fonctionnement. Les travaux présentés dans ce mémoire traite du développement, de la validation expérimentale et de l'exploitation d'un modèle électrique local 1D de cellule de pile à combustible PEM, de type circuit pour une implantation directe dans les logiciels de simulation des systèmes électriques (Saber® dans notre cas), et dont les éléments sont calculés par analogie électrique à partir des phénomènes physiques dont la pile est le siège. Ce modèle est dynamique, il rend compte du phénomène de couche double électrique, et de l'influence des conditions opératoires, notamment l'alimentation en gaz (sur-alimentation, sous-alimentation transitoire), sur le comportement électrique et les performances de la cellule. Le premier chapitre fait un état des lieux des modèles de pile existants, et permet de situer notre travail dans ce contexte. Le chapitre 2 est consacré à la mise en équation traduisant les phénomènes : transport des gaz dans les couches de diffusion et de l'eau dans la membrane, transport des charges dans les électrodes et la membrane, cinétique électrochimique aux interfaces membrane-électrode, couche double électrique, conditions aux limites. Nous y détaillons également la représentation analogique permettant de traiter les équations de transport dans un environnement de calcul dédié à la simulation des systèmes électriques, ainsi que le modèle électrique complet. Une comparaison avec un modèle similaire implanté dans un logiciel utilisant la méthode des éléments finis, est proposée, de même qu'une validation expérimentale, en régime stationnaire et en régime transitoire. Le dernier chapitre traite de l'exploitation du modèle à des fins d'étude paramétrique (conditions opératoires, paramètres physiques), et de simulation "systèmes" (fonctionnements particuliers, mise en série, association avec un convertisseur) / A heart of a fuel cell is a multi-physics system that couples mass and charge transport phenomena (in electrodes and electrolyte), and electrochemical kinetics at reactive sites ; to these phenomena, are added thermal transfer, and gas distribution problems. Many mathematical models have already been developed in order to describe locally these phenomena, through partial differential equations involving space and time. Theses models are often accurate, but they are hardly used in a system approach, since one aims to study a complex system in which the fuel cell is only one element among others. Many semi-empirical dynamics models have also been developed, with an electrochemical cell represented by an equivalent electrical circuit, the parameters of which are often determined experimentally, by spectroscopy measurements in particular. The main drawback of this approach is that it results in small signal models, which are theoretically only available around an operating point. The works presented in this thesis deals with the development, the experimental validation and the use of a 1D local PEM fuel cell model, of circuit type for a direct implementation in simulation software commonly used in electrical engineering (Saber® in our case). The elements of the model are determined by using electrical analogy of physical phenomena that occur in the fuel cell. The model is dynamic, and takes into account electric double layer, and influence of operating conditions (notably gas supply effects, such as over-feeding or transient gas starvation) on fuel cell performances. The first chapter presents literature review on existing fuel cell models, and enable to situate our work in this context. We give in chapter 2 local equations on which our model is based: gas transport in diffusion layers, water transport in the membrane, charge transport in electrodes and membrane, electrochemical kinetics at the membrane-electrode interfaces, electric double layer, boundary conditions. Then we detail the analogy representation that allows to compute transport equations by means of electrical engineering simulation software, as well as to complete electrical model. A comparison with a similar model implemented in a software using the finite element method is proposed, then an experimental validation in steady and transient state is carried out. The last chapter deals with the exploitation of the model for parametric study purposes (operating conditions, physical parameters), and for system simulation purposes (specific operations of a single cell, multi-cells in series, association with a power electronic converter)

Unidades de conservação possuem o objetivo de preservar a natureza, evitando o desmatamento e promovendo a sustentabilidade do meio ambiente. Contudo, para que estas atendam aos propósitos para os quais foram criadas, sem acarretar prejuízos sociais ou conflitos com as populações locais, estudos aplicados interdisciplinares são essenciais, agregando conhecimento útil à gestão e ao planejamento das unidades de conservação. Sob a ótica da ciência da complexidade, o objetivo principal deste trabalho foi desenvolver modelos que auxiliassem na compreensão das mudanças no uso e cobertura da terra, realizassem simulações de cenários futuros, e permitissem observar os efeitos da implantação de políticas de preservação sobre a paisagem. Construímos modelos dinâmicos baseados em cadeias de Markov e autômatos celulares, aliados a técnicas de geoprocessamento. Os modelos foram aplicados a um estudo de caso, o Parque estadual do Itinguçu, ao longo de uma série temporal de materiais aerofotográficos de quase 50 anos (1962-2010). Os resultados dos modelos mostraram que a implantação da unidade de conservação foi essencial para barrar o desmatamento, mas que as práticas tradicionais de agricultura itinerante não estavam diretamente relacionadas à conversão da área de floresta, indicando que a incompatibilidade entre preservação e presença humana, muitas vezes usada como justificativa para a implantação de unidades de proteção integral, deve ser reavaliada sob outra perspectiva. Os resultados também apontaram para um desempenho satisfatório do modelo de Markov em projetar tendências, apesar de possuir certa aleatoriedade na alocação dos elementos no espaço. O incremento do autômato celular diminuiu tal aleatoriedade, mas não foi tão eficiente em reproduzir as tendências observadas nas matrizes de transição quanto o modelo de Markov. Concluímos que a metodologia aplicada no presente trabalho foi útil para compreendermos as mudanças na paisagem da área de estudo, e que a escolha do modelo (Markov ou Markov com autômato celular) deve ser feita com base em uma análise criteriosa caso a caso, em conformidade com as prioridades do estudo a ser realizado. Espera-se que esta pesquisa possa fomentar a discussão sobre o uso desta metodologia como uma ferramenta para planejamento e análise de políticas de conservação da natureza e gestão do território / Conservation units have the purpose to preserve the nature, avoiding the deforestation and promoting the environment sustainability. However, for these to be effective in that purpose, without causing social injuries or conflicts with the local population, interdisciplinary applied studies are essential and must be made by different areas of science, adding useful knowledge to the management of protected areas. Under the vision of the Complexity Science, the main goal of this research was to develop models that help in understanding the land use and cover changes, perform simulations of future scenarios, and allow observing the effects of the implementation of conservation policies on the landscape. We built Markov and cellular automata models, allied to the geoprocessing techniques. The models were applied to a case study, the Parque Estadual do Itinguçu, over a time series of aero photographic materials of almost 50 years (1962-2010). The results of the models showed that the implementation of the conservation unit was essential to stop the deforestation, but the traditional practices of shifting cultivation were not directly related to the conversion of forest area, indicating that the incompatibility between conservation and human presence, often used as justification for the implementation of some strict protection units, should be reviewed from a different perspective. The results also pointed to a satisfactory performance of the Markov model to project trends, despite having certain randomness in the allocation of elements in space. Add cellular automata to model decreased this randomness, but was not so effective in reproducing the observed trends in transition matrices than the Markov model. We concluded that the methodology applied in this study was useful for understanding the changes in the landscape of the study area, and that the choice of model (Markov or Markov with cellular automata) should be based on a careful analysis in accordance with the priorities of the study to be applied. We hope that this research can encourage the discussion of this methodology as a tool for analysis of conservation policies of nature and land management

Representing more than 50% of a worldwide pharmaceutical market of US$ 400 billions, oral drug delivery systems become naturally the focus of many studies. For almost half a century scientists have attempted to develop a theoretical model capable of predicting oral drug absorption in humans. From steady state or quasi-equilibrium models to complex and computationally intractable dynamic modeling approaches, numerous research efforts tried to address the problem of interest. Surprisingly though, no simple insightful first-principle-based dynamic modeling approaches have been reported in the literature. It is the purpose of the present work to provide a simple dynamic distributed-parameter modeling approach for performance monitoring of oral drug delivery systems. As a consequence of the complexity of the gastrointestinal tract, drug oral bioavailability is influenced by many different parameters. These parameters range from the compound's physicochemical properties, the physiological factors of the environment to other factors inherent in the drug form itself known as encapsulation factors. Physicochemical properties account for parameters such as drug stability, solubility or diffusivity. Furthermore, the environment, namely the gastrointestinal tract, influences the drug delivery process to the body with its pH, intestinal transit time and the different transport mechanisms that take place. From a chemical engineering point of view, the human body's anatomy can be analyzed and conceptually realized as a transport-reaction chemical system. Within the proposed modeling framework, the stomach is modeled as a non-ideal continuous-stirred tank reactor (CSTR) and the small intestine is the place where convection-diffusion occurs. The governing transport equations have been solved at steady state conditions in a small intestine represented by the lumen surrounded by its wall. The present work however develops a systematic dynamic first-principle-based distributed-parameter modeling framework where the time-dependent convection-diffusion-reaction model equations are analytically solved, offering the concentration profile in the small intestine lumen and in the wall from the moment the drug is administered until the complete absorption or disintegration of the drug particles. Once the modeling work is performed, a thorough and insightful sensitivity analysis can be conducted in order to assess the impact of the different process parameters on drug bioavailability.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-06-05T13:48:30Z No. of bitstreams: 1 Guilherme Sperling Trapp.pdf: 2436697 bytes, checksum: e28516dbd4b7d9f11a41310b229ce39a (MD5) / Made available in DSpace on 2015-06-05T13:48:30Z (GMT). No. of bitstreams: 1 Guilherme Sperling Trapp.pdf: 2436697 bytes, checksum: e28516dbd4b7d9f11a41310b229ce39a (MD5) Previous issue date: 2015-03-05 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O mercado de geração de energia está em contínua expansão no Brasil. Este mercado é formado por diferentes fontes de geração de energia, as quais acarretam diferentes impactos socioeconômicos e ambientais atreladas as suas operações. Estes impactos geram externalidades na forma de dano para a sociedade e a compensação destes não é de consenso comum entre os atores envolvidos. Neste sentido, a presente dissertação busca, através da aplicação do método do pensamento sistêmico, criar um modelo computacional de dinâmica de sistemas que possibilite a avaliação do custo sistêmico total, considerando as externalidades sociais econômicas e ambientais da geração de energia. Para este fim foi aplicada uma adaptação do método do PSPC - Pensamento Sistêmico e Planejamento por Cenários. Na primeira fase, gerou-se um entendimento maior sobre a temática; em seguida,realizou-se a construção do modelo computacional; e, posteriormente, o modelo foi aplicado a três usinas reais a fim de se fazer uma avaliação da inserção da energia eólica frente a substituição das fontes hidroelétrica e termoelétrica a carvão. Os resultados obtidos apresentaram uma evolução no entendimento na comparação do real custo da energia para sociedade, devido ao aprendizado proporcionado pela utilização do pensamento sistêmico em conjunto com a modelagem dinâmica de sistemas. Os dados encontrados também apontaram para uma mudança nas decisões sobre a matriz energética, se adotado um custo sistêmico para avaliação de novos projetos. / The power generation market still expanding in Brazil. This market consists of different sources of power generation, which cause different socioeconomic and environmental impacts besides its operations. These impacts generate externalities in the form of damage to society and the compensation of these are not common consensus among stakeholders. In this way, this thesis research through the application of systems thinking method, create a computer model of systems dynamic that enable the evaluation of the total systemic cost, considering the externalities of power generation. To this end was applied an adaptation of the method PSPC - Systems Thinking and Planning for Scenarios. In the first phase was generate a greater understanding on the subject. After there was the construction of the computational model, and finally the model was applied to three real plants in order to assessment the option of wind energy against replacement of hydroelectric sources and thermal coal. The results showed an evolution in understanding the comparison of the real cost of energy to society due to the learning provided by the use of systems thinking in conjunction with the systems dynamic modeling. The data also pointed to a change in decisions about energy matrix, if adopted a total systemic cost for evaluation of new projects.