O crescimento da demanda de energia e das interligações entre os Sistemas Elétricos de Potência, assim como a necessidade de prestação de melhores serviços exigem que as técnicas de análise destes sejam cada vez mais rápidas e refinadas. Dentre estas técnicas, as análises de estabilidade transitória através de métodos energéticos são estudadas e o desenvolvimento de técnicas computacionais que permitam a análise em tempo real da estabilidade transitória é o principal objetivo deste trabalho. Os métodos energéticos são métodos diretos adequados à aplicações em tempo real, pois obtém informações a respeito da estabilidade diretamente das equações diferenciais do sistema, sem a necessidade do conhecimento das soluções das equações diferenciais. A aplicação de métodos energéticos aos estudos de estabilidade transitória evoluiu significativamente nos últimos anos. Esta evolução culminou com o desenvolvimento do método BCU. Este método está fundamentado no conceito de ponto de equilíbrio de controle e portanto, garante apenas a existência ou a estabilidade do primeiro \"swing\". Embora este seja um método eficiente, existe uma grande quantidade de casos que são estáveis no primeiro \"swing\", mas o sistema perde a estabilidade em \"swings\" subseqüentes. Para resolver este problema, desenvolveu-se uma técnica de estimativa do parâmetro amortecimento para o caso de uma máquina versus barramento infinito. Estima-se o amortecimento necessário que a máquina deverá possuir tal que a estabilidade nos \"swings\" subseqüentes seja garantida. Esta metodologia é utilizada em conjunto com o BCU garantindo a satisfação da condição de transversalidade exigida no desenvolvimento teórico deste método. Maiores investigações serão necessárias para estimar os amortecimentos em sistemas multimáquinas. / The increase of load demand and interconnection between power systems as well as the necessity of offering better customer services require fast and refined techniques to analyze these systems. In particular, the transient stability analysis is studied and the development of computational techniques suitable to real-time transient stability analysis is the main aim of this work. The energetic methods are direct methods suitable to real-time applications because they obtain qualitative information about the system without the knowledge of the differential equation solutions. The application of energetic methods to the transient stability analysis developed significantly in the last years. This evolution culminated with the development of the BCU method. This method is based on the concept of controlling equilibrium point, therefore it only guarantees the existence of the first swing. In spite of the efficiency of this method, there exists a high number of cases where the BCU predicts stability to the first swing but the system becomes unstable or loses synchronism in future swings. In order to solve this problem, a methodology to estimate the damping coefficient was developed to the machine versus infinite bus case. The damping coefficient that must be applied to the machine to guarantee the stability in future swings is estimated. This methodology is used together with the BCU method guaranteeing the satisfying of the transversality condition required by the BCU theory. Further investigations must be carried out to extend the methodology to multimachine systems.

O crescimento da demanda de energia e das interligações entre os Sistemas Elétricos de Potência, assim como a necessidade de prestação de melhores serviços exigem que as técnicas de análise destes sejam cada vez mais rápidas e refinadas. Dentre estas técnicas, as análises de estabilidade transitória através de métodos energéticos são estudadas e o desenvolvimento de técnicas computacionais que permitam a análise em tempo real da estabilidade transitória é o principal objetivo deste trabalho. Os métodos energéticos são métodos diretos adequados à aplicações em tempo real, pois obtém informações a respeito da estabilidade diretamente das equações diferenciais do sistema, sem a necessidade do conhecimento das soluções das equações diferenciais. A aplicação de métodos energéticos aos estudos de estabilidade transitória evoluiu significativamente nos últimos anos. Esta evolução culminou com o desenvolvimento do método BCU. Este método está fundamentado no conceito de ponto de equilíbrio de controle e portanto, garante apenas a existência ou a estabilidade do primeiro \"swing\". Embora este seja um método eficiente, existe uma grande quantidade de casos que são estáveis no primeiro \"swing\", mas o sistema perde a estabilidade em \"swings\" subseqüentes. Para resolver este problema, desenvolveu-se uma técnica de estimativa do parâmetro amortecimento para o caso de uma máquina versus barramento infinito. Estima-se o amortecimento necessário que a máquina deverá possuir tal que a estabilidade nos \"swings\" subseqüentes seja garantida. Esta metodologia é utilizada em conjunto com o BCU garantindo a satisfação da condição de transversalidade exigida no desenvolvimento teórico deste método. Maiores investigações serão necessárias para estimar os amortecimentos em sistemas multimáquinas. / The increase of load demand and interconnection between power systems as well as the necessity of offering better customer services require fast and refined techniques to analyze these systems. In particular, the transient stability analysis is studied and the development of computational techniques suitable to real-time transient stability analysis is the main aim of this work. The energetic methods are direct methods suitable to real-time applications because they obtain qualitative information about the system without the knowledge of the differential equation solutions. The application of energetic methods to the transient stability analysis developed significantly in the last years. This evolution culminated with the development of the BCU method. This method is based on the concept of controlling equilibrium point, therefore it only guarantees the existence of the first swing. In spite of the efficiency of this method, there exists a high number of cases where the BCU predicts stability to the first swing but the system becomes unstable or loses synchronism in future swings. In order to solve this problem, a methodology to estimate the damping coefficient was developed to the machine versus infinite bus case. The damping coefficient that must be applied to the machine to guarantee the stability in future swings is estimated. This methodology is used together with the BCU method guaranteeing the satisfying of the transversality condition required by the BCU theory. Further investigations must be carried out to extend the methodology to multimachine systems.

Today increasing amounts of data are available for analysis purposes and often times for resource allocation. One method for analysis is linear regression which utilizes the least squares estimation technique to estimate a model's parameters. This research investigated, from a user's perspective, the ability of linear regression to estimate the parameters' confidence intervals at the usual 95% level for medium sized data sets. A controlled environment using simulation with known data characteristics (clean data, bias and or multicollinearity present) was used to show underlying problems exist with confidence intervals not including the true parameter (even though the variable was selected). The Elder/Pregibon rule was used for variable selection. A comparison of the bootstrap Percentile and BCa confidence interval was made as well as an investigation of adjustments to the usual 95% confidence intervals based on the Bonferroni and Scheffe multiple comparison principles. The results show that linear regression has problems in capturing the true parameters in the confidence intervals for the sample sizes considered, the bootstrap intervals perform no better than linear regression, and the Scheffe method is too wide for any application considered. The Bonferroni adjustment is recommended for larger sample sizes and when the t-value for a selected variable is about 3.35 or higher. For smaller sample sizes all methods show problems with type II errors resulting from confidence intervals being too wide.

Lack of drivers knowledge about the abrupt changes in pavement friction and poor performance of the vehicle stability, traction and ABS controllers on the low friction surfaces are the most important factors affecting car crashes. Due to its direct relation to vehicle stability, accurate estimation of tire-road characteristics is of interest to all vehicle and tire companies. Many studies have been conducted in this field and researchers have used different tools and have proposed different algorithms. One such concept is the Intelligent Tire. The application of intelligent tire in tire-road characterization is investigated in this study. Three different test setups were used in this research to study the application of the intelligent tires to improve mobility; first, a wheeled ground robot was designed and built. A Fuzzy Logic algorithm was developed and validated using the robot for classifying different road surfaces such as asphalt, concrete, grass, and soil. The second test setup is a portable tire testing trailer, which is a quarter car test rig installed in a trailer and towed by a truck. The trailer was equipped with different sensors including an accelerometer attached to the center of the tire inner-liner. Using the trailer, acceleration data was collected under varying conditions and a Neural Network (NN) algorithm was developed and trained to estimate the contact patch length, effective tire rolling radius and tire normal load. The third test setup developed for this study was an instrumented Volkswagen Jetta. Different sensors were installed to measure vehicle dynamic response. Additionally, one front and one rear tire was instrumented with an accelerometer attached to their inner-liner. Two intelligent tire based algorithms, a tire pressure estimation algorithm and a road condition monitoring algorithm, were developed and trained using the experimental data from the instrumented VW Jetta. The two-step pressure monitoring algorithm uses the acceleration signal from the intelligent tire and the wheel angular velocity to monitor the tire pressure. Also, wet and dry surfaces are distinguished using the acceleration signal from the intelligent tire and the wheel angular velocity through the surface monitoring algorithm. Some of the model based tire-road friction estimation algorithms, which are widely used for tire-road friction estimation, were also introduced in this study and the performance of each algorithm was evaluated in high slip and low slip maneuvers. Finally a new friction estimation algorithm was developed, which is a combination of experiment based and vehicle dynamic based approaches and its performance was also investigated. / PHD