Parameter estimation for transformer modeling

Large Power transformers, an aging and vulnerable part of our energy infrastructure, are at choke points in the grid and are key to reliability and security. Damage or destruction due to vandalism, misoperation, or other unexpected events is of great concern, given replacement costs upward of $2M and lead time of 12 months. Transient overvoltages can cause great damage and there is much interest in improving computer simulation models to correctly predict and avoid the consequences. EMTP (the Electromagnetic Transients Program) has been developed for computer simulation of power system transients. Component models for most equipment have been developed and benchmarked. Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Thus, transformer modeling is not a mature field and newer improved models must be made available. In this work, improved topologically-correct duality-based models are developed for three-phase autotransformers having five-legged, three-legged, and shell-form cores. The main problem in the implementation of detailed models is the lack of complete and reliable data, as no international standard suggests how to measure and calculate parameters. Therefore, parameter estimation methods are developed here to determine the parameters of a given model in cases where available information is incomplete. The transformer nameplate data is required and relative physical dimensions of the core are estimated. The models include a separate representation of each segment of the core, including hysteresis of the core, λ-i saturation characteristic, capacitive effects, and frequency dependency of winding resistance and core loss. Steady-state excitation, and de-energization and re-energization transients are simulated and compared with an earlier-developed BCTRAN-based model. Black start energization cases are also simulated as a means of model evaluation and compared with actual event records. The simulated results using the model developed here are reasonable and more correct than those of the BCTRAN-based model. Simulation accuracy is dependent on the accuracy of the equipment model and its parameters. This work is significant in that it advances existing parameter estimation methods in cases where the available data and measurements are incomplete. The accuracy of EMTP simulation for power systems including three-phase autotransformers is thus enhanced. Theoretical results obtained from this work provide a sound foundation for development of transformer parameter estimation methods using engineering optimization. In addition, it should be possible to refine which information and measurement data are necessary for complete duality-based transformer models. To further refine and develop the models and transformer parameter estimation methods developed here, iterative full-scale laboratory tests using high-voltage and high-power three-phase transformer would be helpful.

Nongovernmental organization staff views of global water privatization

More than 1 billion people lack access to clean water and proper sanitation. As part of efforts to solve this problem, there is a growing shift from public to private water management led by The World Bank and the International Monetary Fund (IMF). This shift has inspired much related research. Researchers have assessed water privatization related perceptions of consumers, government officials, and multinational company agents. This thesis presents results of a study of nongovernmental (NGO) staff perceptions of water privatization. Although NGOs are important actors in sustainable water related development through water provision, we have little understanding of their perceptions of water privatization and how it impacts their activities. My goal was to fill this gap. I sampled international and national development NGOs with water, sanitation, and hygiene (WASH) foci. I conducted 28 interviews between January and June of 2011 with staff in key positions including water policy analysts, program officers, and project coordinators. Their perceptions of water privatization were mixed. I also found that local water privatization in most cases does not influence NGO decisions to conduct projects in a region. I found that development NGO staff base their beliefs about water privatization on a mix of personal experience and media coverage. My findings have important implications for the WASH sector as we work to solve the worsening global water access crisis.