Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-04-28T17:57:49Z No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-05-02T01:13:24Z (GMT) No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) / Made available in DSpace on 2016-05-02T01:13:24Z (GMT). No. of bitstreams: 1 erasmotalesfonseca.pdf: 866120 bytes, checksum: 042a0c3210df8046171b1593162cde44 (MD5) Previous issue date: 2015-11-06 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho apresentamos um estudo da influência dos parâmetros de um algoritmo de pontos interiores e direções viáveis para solução de problemas de otimização não linear. Esse algoritmo, denominado FDIPA, tem por objetivo encontrar dentre os pontos de um conjunto definido por restrições de igualdade e/ou desigualdade, aqueles que minimizam uma função diferenciável. O FDIPA baseia-se na resolução de dois sistemas de equações lineares com a mesma matriz de coeficientes, obtidos das condições necessárias de primeira ordem de Karush-Kuhn-Tucker. A partir de um ponto inicial no interior do conjunto viável, o FDIPA gera uma sequência de pontos também interiores ao conjunto. Em cada iteração, uma nova direção de descida é obtida e, em seguida, produz-se uma deflexão da direção de descida no sentido do interior do conjunto viável, de modo a se obter uma nova direção que seja de descida e viável. Realiza-se então uma busca linear para obter um novo ponto interior e garantir a convergência global do método. Uma família de algoritmos pode ser obtida variando-se as regras de atualização dos parâmetros do FDIPA. O estudo apresentado neste trabalho foi feito considerando-se um único algoritmo e com restrições de desigualdade somente. Testes numéricos apontaram para uma escolha de parâmetros que levou a um número menor de iterações na resolução dos problemas teste. / This work presents a study on the influence of the parameters of an interior point and feasible directions algorithm for solving non-linear problems. The algorithm, named FDIPA, aims to find among the points of a set defined by equality and/or inequality constraints, those which minimize a differentiable function. The FDIPA is based on two linear systems with the same coefficient matrix, obtained from the Karush-Kuhn-Tucker first order necessary conditions. From a initial point in the interior of the feasible set, FDIPA generates a sequence of points which are also interior to the set. At each iteration, FDIPA produces a descent direction which is deflected towards the interior of the feasible set in order to create a new descent and feasible direction. Then, a linear search is performed to get a new interior point and assure the global convergence of the method. A family of algorithms can be obtained varying the rules used to update the parameters of the FDIPA. The study presented here has been done considering just one particular algorithm and inequality constraints only. Numerical tests pointed to a certain choice of parameters which led to a fewer number of iterations when solving some test problems.

Humanitarian aid and disaster relief are delivered in times of crises or natural disasters, such as after a conflict or in response to a hurricane, typhoon, or tsunami. Different from regular aid programs, aid and relief are provided to deal with emergency and immediate local areas, and to shelter affected people and refugees impacted by sudden traumatic events. There is evidence that natural and man-made disasters are increasing in numbers all around the world, affecting hundreds of millions of people every year. In spite of this fact, only in recent years – beginning in 2005 – has management of the supply chain of resources and materials for humanitarian aid and disaster relief been a topic of interest for researchers. Consequently, the academic literature in this field is comparatively new and still sparse, indicating a requirement for more academic studies. As a key part of the C-Change International Community-University Research Alliance (ICURA) project for managing adaptation to environmental change in coastal communities of Canada and the Caribbean, this thesis develops a framework and analytical model for domestic supply chain management in humanitarian aid and disaster relief in the event of severe storm and flooding in the Canadian C-Change community of Charlottetown, Prince Edward Island. In particular, the focus includes quantitative modeling of two specific aspects during the preparedness phase for emergency management: (1) inventory prepositioning and (2) transportation planning. In addition, this thesis proposes and analyses the characteristics of an effective supply chain management framework in practice to assist Canadian coastal communities in improving their preparation and performance in disaster relief efforts. The results indicate Charlottetown system effectiveness and decreased time to assist affected people are improved by distributing central emergency supply among more than one base station.

The thesis describes various modifications of the predator-prey model. The modifications are considering several harvesting methods. At the beginning a solution and a sensitivity analysis of the basic model are provided. The first modification is the percentage harvesting model, which could be easily converted to the basic model. Secondly a constant harvesting including a linearization is derived. A significant part is devoted to regulation models with special a focus on environmental applications and the stability of the system. Optimization algorithms for one and both species harvesting are derived and back-tested. One species harvesting is based on econometrical tools; the core of two species harvesting is the modified Newton's method. The economic applications of the model in macroeconomics and oligopoly theory are expanded using the methods derived in the thesis.

No description available.

Small and medium-scale companies are trying to minimise their carbon footprint and improve their cash flow, renewable installations are increasing all over the Europe and are expected to do so in following years. However, their dependency on the weather cause pressure on matching the production with demand. An option how to challenge this problem is by using energy storage. The aim of this project is to determine techno-economic benefits of Stirling engine and high temperature thermal energy storage for installation in energy user system and identify key factors that affect the operation of such system. In order to determine these factors simulations in Matlab were conducted. The Matlab linear programming tool Optisolve using dual-simplex algorithm was used. The sensitivity analysis was conducted to test the energy system behaviour. Economic evaluation was done calculating discounted savings. From the results, it can be seen the significant benefit of SE-HT-TES installation is the increased self-consumption of the electricity from PV installation. While the self-consumption in cases when there was no energy storage implemented was around 67 % and in one case as low as 50 % with the SE-HT-TES the value has increased up to 100 %. Energy cost savings are 4.7 % of the cost for the original data set and go up to 6.2 % when simulation with load shift was executed. Simulations have also shown that energy customer with predictable energy demand pattern can achieve higher savings with the very same system. It was also confirmed that for users whose private renewable production does not match load potential savings are 30 % higher compared to the system where energy load peak is matching the PV production peak. Simulations also shown that the customers located in areas with higher electricity price volatility can benefit from such system greatly.

An accurate satellite attitude and orbit control is a key factor for a successful mission. It guarantees for example sun acquisition on solar panels, fine pointing for optimal telescope usage or satellite lifting to reach higher orbits, when required. Furthermore attitude and orbit control is applied to compensate any occurring disturbances within the space environment. The problem tackled in the present thesis is the optimization of thruster commanding to perform spacecraft orbital manoeuvres. The main objective is to develop different algorithms that are suitable for on-board implementation and to compare their performance. For an optimal thruster command distribution the algorithms shall solve linear programming (or optimization) problems, more exact they shall compute thruster on-times to generate desired torques and/or forces, which are requested by the on-board software. In total three different algorithms are developed of which the first one is based on the pseudoinverse of a matrix, the second one is a variation of the Simplex method and the third one is based on Karmarkar’s algorithm, which belongs to the interior-point methods. The last two methods are well known procedures to solve linear programming problems and in theory they have been analyzed before. However this paper proves their practical application and industrial feasibility for orbital manoeuvres of the weather satellites of ESA’s MTG project and their scalability to any number of thrusters on a generic satellite for 6 degrees of freedom manoeuvres. There are 6 MTG satellites and each has 16 one-sided reaction control thrusters, placed at specific positions and pointed towards defined directions. Physical mechanisms limit the thrusters output to minimum on- and off-times. The focus of this thesis will be on the orbital transfer mode, due to the high disturbances that arise during four motor firing sessions at the apogee, executed to reach higher orbits and finally GEO. The firing sessions are performed by a liquid apogee engine and while this engine is in boost mode, the thrusters shall be used for attitude control only. The technique (nominal case) developed by OHB for this maneuver and currently operational uses 4 thrusters only, which are all pointing in the engine’s direction. They are also used to settle the fuel before the engine is turned on. For control the Pseudoinverse method is applied. If one of the 4 thrusters fails, the backup scenario takes place, which includes using 4 totally different thrusters and no fuel settling, due to their unfavorable position with respect to the engine. The initial idea of this work was to develop a controller for 6 thrusters, using only 2 of the 4 nominal case thrusters, to have a better control performance in the backup case. The Pseudoinverse method was developed by OHB before, thus only small changes needed to be applied to work with 6 thrusters. The two other algorithms, based on the Simplex and Karmarkar method, were completely developed from scratch. To analyze their performance several tests were executed. This includes unit tests on a simple computer hardware with different input, Monte Carlo simulations on a cluster to test if the algorithms are suitable for MTG orbital manoeuvres and the application to 12 thrusters, mounted on a generic satellite to generate torques and forces at the same time for 6 degrees of freedom manoeuvres. For each thruster configuration the worst case outputs are shown in so called minimum control authority plots. The performance analysis consists of the maximum and average deviation between requested and generated torque/force, the average computed thruster on-times, the algorithms computation(running) time and iteration steps. For MTG the test results clearly confirm that the usage of 6 thrusters leads to more accurate generated torques and better control authority, than using only 4 thrusters. The Simplex method stands out here in particular, showing excellence performance regarding torque precision. Nevertheless the accuracy goes at the expense of computation effort. While the Pseudoinverse method is very fast and needs only one iteration step, the Simplex is half a magnitude, the Karmarkar one magnitude slower. But the latter lead to lower thruster on-times in terms of firing duration and thus fuel consumption is reduced. Also it is shown that Simplex and Karmarkar can control 12 thrusters at the same time to generate torques and forces, which proves their scalability to any thruster distribution. In the end it comes to the question whether generating a more accurate torque/force or the computational effort, which is strongly hardware dependent, is more important. A decision which depends on the mission’s objective. This paper shows that all three implemented algorithms are able to handle attitude control in the MTG backup scenario and beyond.

With the ever-increasing adoption of renewable energy sources, the seamless integration of PV systems into existing grids becomes imperative. Therefore, this study investigates the integration of a PV-ESS system into sustainable urban living. It entails the development and evaluation of forecasting models for PV production and electricity consumption using artificial neural network models, as well as the analysis of linear optimization algorithms. These investigations give insight into the benefits, challenges, and implications of implementing a PV-ESS system. The photovoltaic generation forecasting model demonstrates high accuracy in winter months while encountering complexity in dynamic summer conditions. The model for estimating power demand poses challenges due to a variety of factors, including human behaviour and data quality.Moreover, the study focuses on the formulation and assessment of linear optimization models with two aims: minimizing costs and optimizing self-consumption. The first continually reduces electricity costs while increasing self-consumption, whereas the second maximizes self-consumption, with limitations in winter battery use. Finally, forecast precision appears as a crucial factor for optimization models. Forecast errors have an impact on the system’s operation. Improving forecasting accuracy and adaptive control strategies are therefore critical. / Med den ständigt ökande användningen av förnybara energikällor blir sömlös integration av solcellssystem i befintliga elnät nödvändig. Därför undersöker denna studie integrationen av ett solcellsenergilagringssystem (PV-ESS) i hållbart stadsboende. Det innefattar utveckling och utvärdering av prognosmodeller för solcellsproduktion och elförbrukning med hjälp av artificiella neurala nätverksmodeller, samt analys av linjär optimeringsalgoritmer. Dessa undersökningar ger insikt om fördelarna, utmaningarna och konsekvenserna av att implementera ett PV-ESS-system. Modellen för prognostisering av solcellsgeneration visar hög noggrannhet under vintermånaderna men stöter på komplexitet under dynamiska sommarförhållanden. Modellen för att uppskatta elförbrukning står inför utmaningar på grund av olika faktorer, inklusive mänskligt beteende och datakvalitet. Dessutom fokuserar studien på formulering och utvärdering av linjära optimeringsmodeller med två mål: att minimera kostnader och optimera självkonsumtion. Den första minskar kontinuerligt elkostnader samtidigt som den ökar självkonsumtionen, medan den andra maximerar självkonsumtionen med begränsningar i vinterbatterianvändning. Slutligen framstår precision i prognoser som en avgörande faktor för optimeringsmodeller. Prognosfel påverkar systemets drift. Därför är förbättring av prognosnoggrannhet och adaptiva kontrollstrategier avgörande.

The focus of this thesis is to find, visualize and analyze the optimal flow of autonomous electric vehicles with charge constraints in urban traffic with respect to energy consumption. The traffic has been formulated as a static multi-commodity network flow problem, for which two different models have been implemented to handle the charge constraints. The first model uses a recursive algorithm to find the optimal solution fulfilling the charge constraints, while the second model discretizes the commodities’ battery to predetermined battery levels. An implementation of both methods is provided through simulations on scenarios of three different sizes. The results show that both methods are capable of representing the traffic flow with charge constraints, with limitations given by the size of the problem. In particular, the recursive model has the advantage of considering the charge as a continuous quantity. On the other hand the discretization of battery levels allows to handle charge constraint setups with higher complexity, that is when longer detours are needed to fulfill the charge constraints.

Die Dissertationsschrift untersucht die Interaktion zwischen Strom- und Wärmemarkt mit einem besonderen Fokus auf Wärmepumpen und Wärmenetzen. Vor dem Hintergrund des steigenden Ausbaus erneuerbarer Energien und der langfristigen Klimaziele stellt sich dabei die Frage der Wirkung, welche die Kopplung von Strom- und Wärmemarkt auf die Reduktion der CO2-Emissionen, die Energiesystemkosten und die Integration der erneuerbaren Energien hat. Zur Beantwortung der Forschungsfrage wird das lineare Optimierungsmodell Enertile um zwei Wärmemodule zur Berücksichtigung von Wärmepumpen und Wärmenetzen erweitert. Im Unterschied zu anderen Modellen wird in der Implementierung für diese Arbeit der Ausbau und der Einsatz der erneuerbaren Energien, der KWK und der weiteren fossilen Kraftwerkskapazitäten gleichzeitig optimiert, wodurch eine Analyse der Wechselwirkungen zwischen dem Ausbau erneuerbarer Energien und der Kopplung von Strom- und Wärmemarkt möglich ist. Die in dieser Arbeit vorgenommene modellgestützte Analyse zeigt die große Bedeutung der Interaktion zwischen Strom- und Wärmemarkt. Im Rahmen einer langfristigen Dekarbonisierung der Energieversorgung durch einen verstärkten Ausbau von erneuerbaren Energien ergeben sich sowohl Chancen als auch Herausforderungen für die Interaktion zwischen Strom- und Wärmemarkt. Die Modellierung der Wärmepumpen zeigt für den gesamten Zeitraum ab 2020 deutlich geringere spezifische CO2-Emissionen gegenüber der Wärmeerzeugung in modernen Gasbrennwertkesseln. Die Ergebnisse zeigen auch, dass bivalente Systeme – die kombinierte Nutzung verschiedener Wärmeerzeugungstechnologien wie beispielsweise KWK, Gasheizkessel und Elektroheizkessel – vor dem Hintergrund der Umstrukturierung des Stromsektors eine wichtige Rolle spielen. Langfristig stellt die flexible Wärmebereistellung durch elektrische Heizungstechnologien insbesondere bei hohen Anteilen erneuerbarer Energien eine kostengünstige und CO2-arme Alternative zur fossilen Wärmeerzeugung dar.:1 Einleitung 1 1.1 Ausgangslage 1 1.2 Problemstellung 3 1.3 Zielsetzung und Vorgehen 4 2 Rahmenbedingungen auf dem Strom- und Wärmemarkt in Deutschland 7 2.1 Rahmenbedingungen auf dem Strommarkt 7 2.2 Rahmenbedingungen auf dem Wärmemarkt 12 2.3 Schlussfolgerungen für diese Arbeit 16 3 Modellierung der Interaktionen von Strom- und Wärmemarkt 17 3.1 Stand der Forschung und Anforderungen an das Modell 17 3.2 Modelle zur Untersuchung von Strom- und Wärmemarkt 18 3.3 Stromsystemoptimierung Enertile 21 3.3.1 Eingangsdaten und Ergebnisse 23 3.3.2 Problemformulierung 24 3.4 Modellerweiterung zur Integration des Wärmemarktes 26 3.4.1 Wärmepumpen 26 3.4.2 Wärmenetze 32 4 Unsicherheiten in Energiesystemmodellen 42 4.1 Unsicherheiten im Rahmen dieser Arbeit 42 4.2 Methoden zum Umgang mit Unsicherheiten in Energiesystemmodellen 43 4.3 Szenarienentwicklung und Sensitivitäten 47 5 Definition von Szenarien zur Analyse der Wechselwirkungen zwischen Strom- und Wärmemarkt 50 5.1 Szenarienübersicht 50 5.2 Zentrale Annahmen 51 5.3 Strommarkt 56 5.3.1 Erneuerbare Energien 56 5.3.2 Konventionelle Kraftwerke 57 5.3.3 Stromnachfrage 59 5.4 Wärmenetze 59 5.5 Wärmepumpen 63 5.6 Sensitivitäten 65 5.7 Kritische Reflexion der Annahmen 66 6 Modellgestützte Analyse der Wechselwirkungen zwischen Strom- und Wärmemarkt 68 6.1 Einfluss auf die CO2-Emissionen 69 6.1.1 Strommarkt 69 6.1.2 Wärmepumpen 72 6.1.3 Wärmenetze 77 6.2 Entwicklung des Kraftwerksparks und des Erzeugungsmixes 82 6.2.1 Strommarkt 82 6.2.2 Wärmepumpen 95 6.2.3 Wärmenetze 106 6.2.4 Integration erneuerbarer Energien auf dem Strommarkt 128 6.3 Änderung der Systemkosten durch die Kopplung von Strom- und Wärmemarkt 131 6.3.1 Kosten der Stromerzeugung 132 6.3.2 Kosten der Wärmeerzeugung in Wärmepumpen 134 6.3.3 Kosten der Wärmeerzeugung in Wärmenetze 136 6.4 Zusammenfassung der Szenarienanalyse 140 6.4.1 Einfluss der Kopplung von Strom- und Wärmemarkt bei ambitionierten Klimaschutz 140 6.4.2 Einfluss der Kopplung von Strom- und Wärmemarkt bei mäßigem Klimaschutz 141 7 Sensitivitäten 142 7.1 Stabile Brennstoffpreise 142 7.2 Potentiale von erneuerbaren Energien 145 7.3 Isolierte Effekte von Elektroheizkesseln und KWK 148 7.3.1 Keine KWK 148 7.3.2 Keine Elektroheizkessel 150 7.4 Hohe Flexibilität der Wärmepumpen 151 7.5 Zusammenfassung Sensitivitäten 152 8 Zusammenfassung 154 8.1 Motivation und Forschungsfrage 154 8.2 Methodisches Vorgehen 154 8.3 Ergebnisse 155 8.4 Schlussfolgerungen und kritische Reflektion 156 8.4.1 Szenarienanalyse 156 8.4.2 Methodik 157 8.4.3 Ausblick 159

The imminent threat of global catastrophe due to climate change gets more real by each passing year. The Aviation trade association, IATA, claims that Aviation accounts for approximately 2% of the Greenhouse Gases (GHG) caused by human activities, and 3.5% of the total Radiative Forcing. With continuous increase in Aviation industry and subsequent drop in fossil fuel prices, these numbers are only expected to up with time. In Addition, these numbers do not include the effects of altitude of emission and many environmentalists believe that the number for some pollutants could be at least 2-3 times larger than IATA estimates. This rising concern engages the Aviation industry to investigate possible methods to alleviate their environmental impact.  The first part of this thesis provides a framework to support Airlines in monitoring their current environmental footprint during the process of scheduling. This objective is realised by developing a robust system for estimating the fuel consumed (ergo quantity of major Greenhouse Gases emitted) by a particular fleet type operating a certain leg, which is then employed in a Fleet Assignment (FA) Operation to reduce emissions and increase the Contribution. An emissions estimation model for Turbojet Aeroplane fleets is created for Industrial Optimizers AB’sMP2 software. The emissions estimation model uses historic fuel consumption data provided by ICAO for a given fleet type to estimate the quantity (in kg) of environmental pollutants during the Landing and Takeoff operation (below 3000 ft) and the Cruise, Climb and Descent operation (above 3000 ft).  The second part of this thesis concerns with assigning monetary weights to the pollutant estimates to calculate an emission cost. This emission cost is then added to MP2’s Fleet Assignment’s objective function as an additional Operational cost to perform a Contribution maximization optimization subjected to the legality constraints. The effects of these monetary weights levied on the results of Fleet Assignment are studied, and utilizing curve-fitting and mathematical optimization, monetary weights are estimated for the desired reduction in GHG emissions.  Finally, a recursive algorithm based on Newton-Raphson method is designed and tested for calculating pollutant weights for untested schedules. / Det omedelbara hotet om en global katastrof pga klimatförändringar blir mer och mer tydligt för varje år som går. IATA, den internationella flyghandelsorganisationen, hävdar att flyget står för runt 2% av växthusgaserna (GHG) som kommer från människans aktiviteter, och 3.5% av den totala avstrålningen. Med den kontinuerliga tillväxten av flygindustrin och prisminskningar av fossila bränslen så förväntas dessa andelar att öka. Dessutom så inkluderar inte dessa siffror effekten av att utsläppen sker på hög höjd, och många miljöaktivister tror att siffrorna för vissa utsläpp kan vara åtminstone 2-3 gånger högre än IATAs uppskattningar. Denna växande oro motiverar flygindustrin till att undersöka metoder för att begränsa dess miljöpåverkan.  Den första delen av denna rapport ger ett ramverk för att hjälpa flygbolag med att bevaka deras aktuella miljöavtryck under schemaläggningsprocessen. Detta mål realiseras genom att utveckla ett robust system för att uppskatta bränsleförbrukningen (och därmed kvantiteten av växthusgasutsläpp) av en specifik flygplanstyp på en given etapp, som sedan kan användas för att allokera flygplanstyper för att minska utsläppen och bidra till att förbättra miljön. En modell för att uppskatta utsläpp för flottor av turbojetflygplan har skapats för Industrial Optimizers AB programvara MP2. Modellen för att uppskatta utsläppen baseras på historiska data om bränsleförbrukning som tillhandahållits av ICAO för en given flygplanstyp som använts för att uppskatta kvantiteten (i kg) av föroreningar vid start (under 3000 fot) och vid sträckflygning, stigning och inflygning (över 3000 fot). Den andra delen av denna rapport handlar om att bestämma monetära vikter till föroreningsskattningarna för att beräkna utsläppskostnader som ska användas i MP2 s målfunktion för allokering av flygplanstyper. Detta ger en ytterligare driftskostnad att beakta i optimeringen för att få med miljöaspekterna och tillåtna lösningar. Effekten som dessa monetära vikter har på resultaten från optimeringen studeras, och genom att använda kurvanpassning och matematisk optimering, de monetära vikterna anpassas för att få den önskade minskningen i växthusgasutsläpp. Slutligen så har en rekursiv algoritm, baserad på Newon-Raphsons metod, designats och testats för att beräkna utsläppsvikter för scheman som inte använts för att beräkna vikterna