Eduardo M. Modiano and Jeremy F. Shapiro. / Bibliography: p. 57-58.

by Silvia Pariente. / Research supported by the Energy Research and Development Administration through Contract 421072-S. / Bibliography: leaf 37.

The dissertation presents a new robust method for estimating the standardized distances of the data points associated with the weighted Jacobian matrix in power system state estimation. These distances, called robust Mahalanobis distances, can be used as weight functions to robustify the residuals of both the M-estimators and the least median of squares estimators for outlier diagnostics. They can also be used for leverage diagnostics and for alleviating the ill-conditioning problem of the Jacobian matrix. The robust Mahalanobis distances are calculated in three steps. First, projection distances are calculated and statistical tests applied to them to identify leverage points. Then, the sample covariance matrix is estimated from the data set without the identified leverage points. Finally robust Mahalanobis distances are calculated from the estimated covariance matrix. The projection distances are provided by a new version of the projection algorithm proposed by Donoho and Stahel, which has been specially adapted for power systems. The new projection algorithm consists of selecting relevant directions for each measurement in the factor space and projecting on these directions only the subset of data points that have non-zero projections. It is shown that this subset is the union of the fundamental sets containing the selected measurement. The fundamental set of a state variable consists of all those measurements that observe this state variable. The probability distributions of the projection distances and the statistical cutoff values for leverage point identification have been determined through Monte Carlo simulations and Q-Q plots. It is found that the projection distances follow x²-distributions with degrees of freedom much smaller than the dimension of the factor space. Simulation results performed on various test systems have revealed that the projection algorithm can handle a large fraction of leverage points, whatever their positions in the factor space. In addition, it is very fast and compatible with real-time environment, even for very large systems. Its computing times grow linearly with system size. / Ph. D.

One of the greatest challenges that will face humanity in the 21st century is the issue of climate change brought about by emissions of greenhouse gases. Energy use is one of the primary sources of greenhouse gas emissions. However, it is also one of the most important contributors to improved human welfare over the past two centuries and will continue to be so for years to come. This quandary has led a number of researchers to suggest that geoengineering may be required in order to allow for continued use of fossil fuels while at the same time mitigating the effects of the associated greenhouse gas emissions on the global climate. The goal of this research was to develop a model that would allow decision-makers and policy analysts to assess the optimal mix of energy and geoengineering resources needed to meet global or regional energy demand at the lowest cost while accounting for appropriate emissions, greenhouse gas concentration, or temperature rise constraints. The resulting software model is called the Combined Energy and Geoengineering Optimization Model (CEAGOM). CEAGOM was then used to analyze the recently announced U.S.-China emissions agreement and to assess what the optimal global energy resource mix might be over the course of the 21st century, including the associated potential need for geoengineering. These analyses yielded optimal mixes of energy and geoengineering resources that could be used to inform regional and global energy and climate management strategies.

Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1984. / Bibliography: leaves 177-189. / Photocopy. / Microfilm. / xiii, 189 leaves, bound ill

The need for smaller and more efficient power supplies steadily grows. Many power supplies incorporate high-frequency dc-to-dc switching converters to meet these demands. Recently, a new class of switching converters has been introduced which can operate at very high frequencies to further reduce size and increase efficiency. They are called quasi-resonant converters. Previously, the dc characteristics of many of these converters had been determined, assuming ideal components and circuit operating conditions. However, as the frequency of operation increases, the circuit behavior becomes less ideal causing changes in the expected characteristics. This is because resistive losses, semiconductor junction capacitances, and other parasitic (undesirable) elements become more pronounced at higher frequencies. This thesis investigates the effects of parasitic elements on the dc characteristics of several zero-current-switched, buck-derived quasi-resonant converters. For the quasi-resonant buck converter, it is demonstrated that for certain operating conditions the dc voltage gain can increase when parasitic losses are increased. Design guidelines are given for maximizing this converter's efficiency. Various forward quasi-resonant topologies are investigated, and the effects of parasitic elements on circuit operation are highlighted. A dc analysis is performed for the secondary-resonance forward converter, which has not previously been analyzed. This converter can operate either in full-wave or half-wave mode. Its dc voltage gain in full-wave mode is less sensitive to load variations than other resonant forward topologies that only operate in half-wave mode. / Master of Science