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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Earl Barnes; Committee Member: Arkadi Nemirovski; Committee Member: Faiz Al-Khayyal; Committee Member: Guillermo H. Goldsztein; Committee Member: Joel Sokol. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Orientador: Carlos Alberto Favarin Murari / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T03:01:58Z (GMT). No. of bitstreams: 1 Silva_JoaoAngeloBoscoda_M.pdf: 958285 bytes, checksum: 44930f0b897c664249dfdc6fef42349a (MD5) Previous issue date: 2007 / Resumo: As decisões na operação de sistemas de potência estão associadas com diferentes aspectos, não somente técnicos (segurança, confiabilidade, etc.) senão também econômicos (custos de produção, venda de energia, etc.). Estes objetivos estão inclusos dentro dos modelos de despacho econômico usando o Fluxo de Potência Ótimo (FPO). De outra forma, com o crescente interesse nos aspectos ambientais, outros critérios, tais como a poluição, devem ser incorporados ao modelo de despacho. Outro aspecto importante é a incerteza de algumas variáveis e o problema pode ser modelado usando lógica nebulosa. Nesta dissertação é proposto um esquema simples para a tomada de decisões na operação de sistemas de potência, baseado em um Despacho Econômico Ambiental Nebuloso. É usado um modelo de ¿FPO Nebuloso DC¿ e este consiste de dois cenários, o ambiental versus o econômico e o econômico versus a incerteza. Os problemas de congestão (sobrecarga em ramos) e o corte de carga são também levados em conta. A formulação proposta permite obter, de uma forma simples, informações úteis para a avaliação da melhor decisão na operação levando em conta o critério ambiental. As simulações realizadas em diferentes sistemas, incluindo sistemas teste IEEE (Garver, IEEE30) e real (Piratininga), são mostradas para avaliar o esquema proposto / Abstract: The decisions on power systems operation deal with different issues not only technical (security, reliability, etc.) but also economics (production costs, deregulated electricity markets, etc.). These subjects are included into the generation dispatch models by using an Optimal Power Flow (OPF). On the other hand, with the environmental issues growing up other criteria, such as the pollution, must be added to the dispatch model. Other important aspect is the uncertainty of some variables and the problem can be modeled by using fuzzy logic. In this work an easy scheme for the decisions on power systems operation is proposed, based on Fuzzy Economic and Environmental Dispatch. A ¿DC Fuzzy OPF model¿ is used and it consists of two main stages, the environmental versus the economic and the economic versus the uncertainty. The overloads on branches and the load curtailment are also taken into account. The formulation proposed allows obtaining, in a simple way, useful informations for evaluating the best decision in the operation taking into account the environmental criteria. Simulations for different systems, including IEEE test systems (Garver, IEEE30) and real system (Piratininga), are shown to evaluate the scheme / Mestrado / Engenharia Eletrica / Mestre em Engenharia Elétrica

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This project is concerned with the development and implementation of a novel preconditioning method for the iterative solution of linear systems that arise in the finite element discretisation of the incompressible Navier-Stokes equations with weakly imposed boundary conditions. In this context we studied an augmented approach where the Schur complement associated with the momentum block of the Navier-Stokes equations has special sparse structure. We follow the standard inf-sup stable method of discretising the Navier-Stokes equations by the Taylor-Hood elements with the Lagrange multiplier constraints discretised using the same order approximation on matching grids. The resulting system of nonlinear equations is solved iteratively by Newton's method. The spectrum of the linearised Oseen's problem, preconditioned by the exact augmentation preconditioner was analysed. Then we developed inexact versions of the preconditioner aimed at achieving optimal scaling of the algorithm in terms of computational resources and wall-clock times. The experimental evaluation of the methodology involve a number of benchmark problems in two and three spatial dimensions. The obtained results demonstrate efficiency, robustness and almost optimal scaling of the solution algorithm with respect to the discrete problem size. We used OOMPH-LIB as a testbed for our experiments. The preconditioning strategies were implemented using OOMPH-LIB's Parallel Block Preconditioning Framework. The initial version of the software was significantly upgraded during the course of this project with newly implemented functionalities to facilitate the rapid development of sophisticated hierarchical design of parallel block preconditioners. Parallel performance analysis of the newly introduced functionalities demonstrate negligible overhead in terms of wall-clock time and the framework demonstrate good weak and strong parallel scaling.

By the emergence of electronic commerce and low transaction costs on the Internet, an interest in the design of new auction mechanisms has been arisen. Recently many researchers in computer science, economics, business, and game theory have presented many valuable studies on the subject of online auctions, and auctions theory. When faced from a computational perspective, combinatorial auctions are perhaps the most challenging ones. Combinatorial auctions, that is, auctions where bidders can bid on combinations of items, tend to lead to more efficient allocations than traditional auction mechanisms in multi-item multi-unit situations where the agents&rsquo / valuations of the items are not additive. However, determining the winners to maximize the revenue is NP-complete. In this study, we first analyze the existing approaches for combinatorial auction problem. Based on this analysis, we then choose three different approaches, which are search approach, descending simultaneous auctions approach, and IP (Integer Programming) formulation approach to build our models. The performances of the models are compared using computer simulations, where we model bandwidth allocation system. Finally a combinatorial auction tool is built which can be used for online auctions and e-procurement systems.

This thesis describes the theory of model predictive control and application of the theory to synchronous drives. It shows explicit and on-line solutions and compares the results with classical vector control structure.

Operation of the electricity markets is subject to a number of strict and specific constraints such as continuous load-generation balance, security of supply, and generation technology related limitations. Contributions have been made to two important problems of the Electricity Markets, in the context of this study. In this study, Price Based Unit Commitment problem in the literature, which is a tool for the GENCO for operations planning, is extended considering the interdependencies between the Natural Gas (NG) and Electricity infrastructures and the uncertainty of Wind Power generation. The effect of the NG infrastructure physical limitations is considered via linearized NG transmission system equations, and the Wind energy sources and conventional generation resource uncertainties are simulated by Monte-Carlo simulations. The contribution of the forward energy Bilateral Contracts (BC), as a financial risk hedging tool is also included by modeling these in the proposed PBUC framework. In the case studies , it is observed that a GENCO could prevent its financial losses due to NG interruptions, by depositing only a portion of the midterm interrupted NG in the storage facilities. The Security Constrained Unit Commitment (SCUC) Problem is widely accepted tool in the industry which models the market clearing process. This study integrates two novelties to the SCUC problem / &bull / A discrete demand response model to consider active participation of the consumers, &bull / A hybrid deterministic/stochastic contingency model to represent the N-1 contingencies together with the uncertainties related with the wind power generation and system load. It is observed that the curtailment of available wind power capacity would enable the TSO to take corrective actions against occurrence of the contingencies and realization of the uncertainties in the most possible economical manner.

This thesis describes the theory of model predictive control and application of the theory to synchronous drives. It shows explicit and on-line solutions and compares the results with classical vector control structure.