京都大学 / 新制・課程博士 / 博士(工学) / 甲第23887号 / 工博第4974号 / 新制||工||1777(附属図書館) / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 藤本 健治, 教授 泉田 啓, 教授 大塚 敏之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The content of this dissertation consists of three parts. In the first part, optimal control strategies are developed for Unified Power Flow Controller (UPFC) following the clearance of fault conditions. UPFC is one of the most versatile Flexible AC Transmission devices (FACTs) that have been implemented thus far. The optimal control scheme is composed of two parts. The first is an optimal stabilization control, which is an open-loop ‘Bang’ type of control. The second is an suboptimal damping control, which consists of segments of ‘Bang’ type control with switching functions the same as those of a corresponding approximate linear system. Simulation results show that the proposed control strategy is very effective in maintaining stability and damping out transient oscillations following the clearance of the fault. In the second part, a new power market structure is proposed. The new structure is based on a two-level optimization formulation of the market. It is shown that the proposed market structure can easily find the optimal solutions for the market while takeing factors such as demand elasticity into account. In the last part, a mathematical programming problem is formulated to obtain the maximum value of the loadibility factor, while the power system is constrained by steady-state dynamic security constraints. An iterative solution procedure is proposed for the problem, and the solution gives a slightly conservative estimate of the loadibility limit for the generation and transmission system.

Frames have been useful in signal transmission due to the built in redundancy. In recent years, the erasure problem in data transmission has been the focus of considerable research in the case the error estimate is measured by operator (or matrix) norm. Sample results include the characterization of one-erasure optimal Parseval frames, the connection between two-erasure optimal Parseval frames and equiangular frames, and some characterization of optimal dual frames. If iterations are allowed in the reconstruction process of the signal vector, then spectral radius measurement for the error operators is more appropriate then the operator norm measurement. We obtain a complete characterization of spectrally one-uniform frames (i.e., one-erasure optimal frames with respect to the spectral radius measurement) in terms of the redundancy distribution of the frame. Our characterization relies on the connection between spectrally optimal frames and the linear connectivity property of the frame. We prove that the linear connectivity property is equivalent to the intersection dependence property, and is also closely related to the well-known concept of k-independent set. For spectrally two-uniform frames, it is necessary that the frame must be linearly connected. We conjecture that it is also necessary that a two-uniform frame must be n-independent. We confirmed this conjecture for the case when N = n+1, n+2, where N is the number of vectors in a frame for an n-dimensional Hilbert space. Additionally we also establish several necessary and sufficient conditions for the existence of an alternate dual frame to make the iii iterated reconstruction to work.

This thesis aims to produce a control strategy that minimizes the energy usage of the pumps in the sewer system of Växjö City. The pumps are located in a small number of pumping stations. These are connected by a network of pipes in a way that requires the control of the pumps to be coordinated, both within and between the pumping stations. A model of the system based on fluid mechanics is proposed and from this an optimization problem is constructed for the control problem. When the optimization problem is reformulated as a hierarchy of smaller problems these problems can be solved sequentially and the computational requirements are low. The resulting control strategy gives an optimal control at each flow rate to the waste water treatment plant, and the results show that an optimal control can yield significant energy savings. The control strategy is also shown to be stable with regards to errors in the model. / Detta arbete syftar till att beräkna en energieffektiv styrstrategi för pumpar i spillvattensystemet i Växjö stad. Pumparna finns i ett fåtal pumpstationer som är sammankopplade via ett rörsystem så att styrningen av pumparna behöver koordineras, både inom och mellan pumpstationerna. Utifrån en framtagen fysikalisk modell av systemet formuleras ett optimeringsproblem för att finna en energieffektiv styrning. Detta problem kan lösas på korta beräkningstider genom att det delas upp i en hierarki av mindre delproblem som löses sekventiellt. Den resulterande styrstrategin ger en optimal styrning för olika totala flöden i spillvattensystemet, och resultaten visar att en effektiv styrstrategi kan ge påtagliga besparingar i pumparnas energiförbrukning. Styrstrategin har även studerats gällande känslighet för viss osäkerhet i modellen och uppvisar stabilitet.

We study optimal order placement in a limit order book. By modelling the limit order book dynamics as a Markov chain, we can frame the purchase of a single share as a Markov Decision Process. Within the framework of the model, we can estimate optimal decision policies numerically. The trade rate is varied using a running cost control variable. The optimal policy is found to result in a lower cost of trading as a function of the trade rate compared to a market order only strategy. / Vi studerar optimal orderläggning i en limit orderbok. Genom att modellera dynamiken av inkommande ordrar som en Markov kedja så kan vi formula optimal orderläggning som en Markov Decision Process. Inom ramverket av modellen så kan vi skatta optimala strategier numeriskt. En löpande kostnad används som en kontrollvariabel för handelstakten av den optimala strategin. Vi finner att den optimala strategin resulterar i en lägre handelskostnad som funktion av deltagande jämfört med en marknadsorder strategi.

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Elite athletes often risk their health to achieve the highest level of performance, but this might instead result in decreased performance and health over time. Over the last few years, multiple elite athletes have expressed their struggles with mental health (MH), and it seems like the prevalence for mental illness in elite athletes is comparable to the general population. Multiple factors influence the balance between MH and performance, and it is known that elite athletes experience unique stressors in their careers. The purpose of the study is to explore career narratives of Swedish elite tennis players to learn about how, at different periods of their careers, they searched for, maintained, lost, and restored their perceived optimal balance between MH and performance. The methodology used is narrative inquiry with thematic analysis and composite vignettes to analyze and present the data. Three Swedish elite tennis players were interviewed. The findings show five different themes that create a thematic map which demonstrate the stages the athletes faced and experienced as they attempt to balance MH and high-level performance. It is concluded that sport psychology professionals are obligated to understand how athletes can work towards an optimal balance between MH and performance, and this study provides a step towards that goal. / Elitidrottare riskerar ofta sin hälsa genom att göra allt de kan för att uppnå den högsta möjliga prestationsnivån, men det kan tyvärr resultera i försämrad prestation och hälsa i längden. Under de senaste åren har flera elitidrottare uttryckt deras problem med mental hälsa, och det verkar som att prevalensen av psykisk ohälsa hos elitidrottare är jämförbar med den allmänna befolkningen. Flera faktorer påverkar balansen mellan mental hälsa och prestation, och det är även känt att elitidrottare upplever unika stressfaktorer i sina karriärer. Syftet med studien är att utforska karriärberättelser från svenska elittennisspelare för att lära sig hur de, under olika perioder i karriären, sökte efter, bibehöll, förlorade, och återställde sin balans mellan mental hälsa och prestation. Metodiken som används är narrativ undersökning där tematisk analys och sammansatta vinjetter användes för att analysera och presentera resultatet. Tre svenska elittennisspelare intervjuades. I resultatet hittades fem olika teman som tillsammans skapar en tematisk karta, vilket visar de stadier som spelarna stod inför och upplevde när de försökte balansera mental hälsa och prestation på hög nivå. Slutsatsen är att arbetare och forskare inom idrottspsykologi är skyldiga att förstå hur idrottare kan jobba för en optimal balans mellan mental hälsa och prestation, och denna studie tar ett steg i rätt riktning mot det målet.

The ongoing financial crisis has had major adverse impact on the credit market. As the financial crisis progresses, the skyrocketing unemployment rate puts more and more customers in such a position that they cannot pay back their credit debts. The deteriorating economic environment and growing pressures for revenue generation have led creditors to re-assess their existing portfolios. The credit re-assessment is to accurately estimate customers' behavior and distill information for credit decisions that differentiate bad customers from good customers. Lending institutions often need a specific rule for defining an optimal cut-off value to maximize revenue and minimize risk. In this dissertation research, I consider a problem in the broad area of credit risk management: the selection of critical thresholds, which comprises of the "optimal cut-off point" and an interval containing cut-off points near the optimal cut-off point (a "near-optimal interval"). These critical thresholds can be used in practice to adjust credit lines, to close accounts involuntarily, to re-price, etc. Better credit re-assessment practices are essential for banks to prevent loan loss in the future and restore the flow of credit to entrepreneurs and individuals. The Profit Function is introduced to estimate the optimal cut-off and the near-optimal interval, which are used to manage the credit risk in the financial industry. The credit scores of the good population and bad population are assumed from two distributions, with the same or different dispersion parameters. In a homoscedastic Normal-Normal model, a closed-form solution of optimal cut-off and some properties of optimal cut-off are provided for three possible shapes of the Profit Functions. The same methodology can be generalized to other distributions in the exponential family, including the heteroscedastic Normal-Normal Profit Function and the Gamma-Gamma Profit Function. It is shown that a Profit Function is a comprehensive tool in the selection of critical thresholds, and its solution can be found using easily implemented computing algorithms. The estimation of near-optimal interval is developed in three possible shapes of the bi-distributional Profit Function. The optimal cut-off has a closed-form formula, and the estimation results of near-optimal intervals can be simplified to this closed-form formula when the tolerance level is zero. Two nonparametric methods are introduced to estimate critical thresholds if the latent risk score is not from some known distribution. One method uses the Kernel density estimation method to derive a tabulated table, which is used to estimate the values of critical thresholds. A ROC Graphical method is also developed to estimate critical thresholds. In the theoretical portion of the dissertation, we use Taylor Series and the Delta method to develop the asymptotic distribution of the non-constrained optimal cut-off. We also use the Kernel density estimator to derive the asymptotic variance of the Profit function. / Statistics

Bayesian optimal designs have received increasing attention in recent years, especially in biomedical and clinical trials. Bayesian design procedures can utilize the available prior information of the unknown parameters so that a better design can be achieved. However, a difficulty in dealing with the Bayesian design is the lack of efficient computational methods. In this research, a hybrid computational method, which consists of the combination of a rough global optima search and a more precise local optima search, is proposed to efficiently search for the Bayesian D-optimal designs for multi-variable generalized linear models. Particularly, Poisson regression models and logistic regression models are investigated. Designs are examined for a range of prior distributions and the equivalence theorem is used to verify the design optimality. Design efficiency for various models are examined and compared with non-Bayesian designs. Bayesian D-optimal designs are found to be more efficient and robust than non-Bayesian D-optimal designs. Furthermore, the idea of the Bayesian sequential design is introduced and the Bayesian two-stage D-optimal design approach is developed for generalized linear models. With the incorporation of the first stage data information into the second stage, the two-stage design procedure can improve the design efficiency and produce more accurate and robust designs. The Bayesian two-stage D-optimal designs for Poisson and logistic regression models are evaluated based on simulation studies. The Bayesian two-stage optimal design approach is superior to the one-stage approach in terms of a design efficiency criterion. / Ph. D.

Under the envisioned smart city paradigm, there is an increasing demand for the coordinated operation of our infrastructure networks. In this context, this thesis puts forth a comprehensive toolbox for the optimization of electric power and water distribution networks. On the analytical front, the toolbox consists of novel mixed-integer (non)-linear program (MINLP) formulations; convex relaxations with optimality guarantees; and the powerful technique of McCormick linearization. On the application side, the developed tools support the operation of each of the infrastructure networks independently, but also towards their joint operation. Starting with water distribution networks, the main difficulty in solving any (optimal-) water flow problem stems from a piecewise quadratic pressure drop law. To efficiently handle these constraints, we have first formulated a novel MINLP, and then proposed a relaxation of the pressure drop constraints to yield a mixed-integer second-order cone program. Further, a novel penalty term is appended to the cost that guarantees optimality and exactness under pre-defined network conditions. This contribution can be used to solve the WF problem; the OWF task of minimizing the pumping cost satisfying operational constraints; and the task of scheduling the operation of tanks to maximize the water service time in an area experiencing electric power outage. Regarding electric power systems, a novel MILP formulation for distribution restoration using binary indicator vectors on graph properties alongside exact McCormick linearization is proposed. This can be used to minimize the restoration time of an electric system under critical operational constraints, and to enable a coordinated response with the water utilities during outages. / Master of Science / The advent of smart cities has promoted research towards interdependent operation of utilities such as water and power systems. While power system analysis is significantly developed due to decades of focused research, water networks have been relying on relatively less sophisticated tools. In this context, this thesis develops Advanced efficient computational tools for the analysis and optimization for water distribution networks. Given the consumer demands, an optimal water flow (OWF) problem for minimizing the pump operation cost is formulated. Developing a rigorous analytical framework, the proposed formulation provides significant computational improvements without compromising on the accuracy. Explicit network conditions are provided that guarantee the optimality and feasibility of the obtained OWF solution. The developed formulation is next used to solve two practical problems: the water flow problem, that solves the complex physical equations yielding nodal pressures and pipeline flows given the demands/injections; and an OWF problem that finds the best operational strategy for water utilities during power outages. The latter helps the water utility to maximize their service time during power outages, and helps power utilities better plan their restoration strategy. While the increased instrumentation and automation has enabled power utilities to better manage restoration during outages, finding an optimal strategy remains a difficult problem. The operational and coordination requirements for the upcoming distributed resources and microgrids further complicate the problem. This thesis develops a computationally fast and reasonably accurate power distribution restoration scheme enabling optimal coordination of different generators with optimal islanding. Numerical tests are conducted on benchmark water and power networks to corroborate the claims of the developed formulations.