Transients in Power Systems

Power system engineering largely focuses on steady state analysis. The main areas of power system engineering are power flow studies and fault studies - both steady state technologies. But the world is largely transient, and power systems are always subject to time varying and short lived signals. This technical report concerns several important topics in transient analyses of power systems. The leading chapter deals with a new analytical tool-wavelets-for power system transients. Flicker and electric are furnace transients are discussed in Chapters I1 and IV. Chapter 111 deals with transients from shunt capacitor switching. The concluding chapters deal with transformer inrush current and non simultaneous pole closures of circuit breakers. This report was prepared by the students in EE532 at Purdue University. When I first came to Purdue in 1965, Professor El-Abiad was asking for student term projects which were turned into technical reports. I have \u27borrowed\u27 this idea and for many years we have produced technical reports from the power systems courses. The students get practice in writing reports, and the reader is able to get an idea of the coverage of our courses. I think that the students have done a good job on the subject of transients in power systems

Analog, hybrid, and digital simulation

Analog, hybrid, and digital computerized simulation technique

Energy and area efficient techniques for data converters

Data converters are ubiquitous building blocks of a signal chain. The rapid increase in communication and connectivity devices presents new avenues for pushing the state of the art analog to digital converters. Techniques for improving resolution, bandwidth, linearity and bit-error rate, while reducing the power, energy and area is the motivation for this research. This research focuses on achieving this goal by enabling circuit techniques, architecture techniques and calibration methods. The following techniques are proposed for enabling power, area and energy efficient analog to digital converter techniques. 1. A capacitor switching scheme for successive approximation ADC is introduced to enable 93.4% energy reduction and 75 % reduction in capacitor area as compared to a conventional SAR ADCs. 2. Asynchronous correlated level shifting technique for improving current source linearity and power supply rejection ratio of zero crossing based circuits is proposed. This technique enables asynchronous ADC architectures for energy efficient system. 3. Unified gain enhancement model is proposed to catalogue gain enhancement techniques. Class-A+ and Replicated Parallel Gain Enhancement (RPGe) amplifiers are introduced as parallel gain enhancement techniques for switched capacitor circuits. A prototype pipelined ADC using RPGE amplifier achieves 74.9 dB SNDR, 90.8 dB SFDR, 87 dB THD at 20 MS/s. Built in 1P4M 0.18 μm technology and operating at 1.3 V supply, the ADC consumes 5.9 mW. The ADC occupies 3.06 sq. mm and has a figure of merit of 65 fJ /conversion step. Extracted simulation results of the prototype pipeline ADC using dynamic RPGE amplifier achieve 74 dB SNDR, 90 dB SFDR, and 85 dB THD at 30 MS /s in a 0.18 μm process. The ADC consumes 6.6 mW from a 1.3 V supply and achieves a figure of merit of 40 fJ/C-S. 4. A low-gain amplifier based V-T converter is utilized along with a TDC to replace the function of flash ADC and the DAC references in a pipeline ADC. The simulated/ extracted performance of the chip is 12bit, 100 MHz in 65nm process while consuming approximately 8-9 mA from 1 V supply. 5. A measurement technique for detecting and correcting bit-error rate in ADCs is proposed. This multi-path ADC technique squares the bit-error rate of the ADC without consuming additional analog power. The area increase is negligible compared to the conventional modular redundancy techniques. This technique can be applied to digitally detect and correct single event transients for ADCs. A three-path ADC can restore the ADC performance independent of the input frequency and number of errors in a single path. 6. LMS algorithm is used to estimate the VCO non-linearity by using the VCO as a Nyquist ADC and utilizing a slow but accurate ADC. The simulated ADC performance improves from 5 bits to 7.8 bits by using a second order fit to the VCO non-linearity

Modeling and identification of power electronic converters

Nowadays, many industries are moving towards more electrical systems and components. This is done with the purpose of enhancing the efficiency of their systems while being environmentally friendlier and sustainable. Therefore, the development of power electronic systems is one of the most important points of this transition. Many manufacturers have improved their equipment and processes in order to satisfy the new necessities of the industries (aircraft, automotive, aerospace, telecommunication, etc.). For the particular case of the More Electric Aircraft (MEA), there are several power converters, inverters and filters that are usually acquired from different manufacturers. These are switched mode power converters that feed multiple loads, being a critical element in the transmission systems. In some cases, these manufacturers do not provide the sufficient information regarding the functionality of the devices such as DC/DC power converters, rectifiers, inverters or filters. Consequently, there is the need to model and identify the performance of these components to allow the aforementioned industries to develop models for the design stage, for predictive maintenance, for detecting possible failures modes, and to have a better control over the electrical system. Thus, the main objective of this thesis is to develop models that are able to describe the behavior of power electronic converters, whose parameters and/or topology are unknown. The algorithms must be replicable and they should work in other types of converters that are used in the power electronics field. The thesis is divided in two main cores, which are the parameter identification for white-box models and the black-box modeling of power electronics devices. The proposed approaches are based on optimization algorithms and deep learning techniques that use non-intrusive measurements to obtain a set of parameters or generate a model, respectively. In both cases, the algorithms are trained and tested using real data gathered from converters used in aircrafts and electric vehicles. This thesis also presents how the proposed methodologies can be applied to more complex power systems and for prognostics tasks. Concluding, this thesis aims to provide algorithms that allow industries to obtain realistic and accurate models of the components that they are using in their electrical systems.En la actualidad, el uso de sistemas y componentes eléctricos complejos se extiende a múltiples sectores industriales. Esto se hace con el propósito de mejorar su eficiencia y, en consecuencia, ser más sostenibles y amigables con el medio ambiente. Por tanto, el desarrollo de sistemas electrónicos de potencia es uno de los puntos más importantes de esta transición. Muchos fabricantes han mejorado sus equipos y procesos para satisfacer las nuevas necesidades de las industrias (aeronáutica, automotriz, aeroespacial, telecomunicaciones, etc.). Para el caso particular de los aviones más eléctricos (MEA, por sus siglas en inglés), existen varios convertidores de potencia, inversores y filtros que suelen adquirirse a diferentes fabricantes. Se trata de convertidores de potencia de modo conmutado que alimentan múltiples cargas, siendo un elemento crítico en los sistemas de transmisión. En algunos casos, estos fabricantes no proporcionan la información suficiente sobre la funcionalidad de los dispositivos como convertidores de potencia DC-DC, rectificadores, inversores o filtros. En consecuencia, existe la necesidad de modelar e identificar el desempeño de estos componentes para permitir que las industrias mencionadas desarrollan modelos para la etapa de diseño, para el mantenimiento predictivo, para la detección de posibles modos de fallas y para tener un mejor control del sistema eléctrico. Así, el principal objetivo de esta tesis es desarrollar modelos que sean capaces de describir el comportamiento de un convertidor de potencia, cuyos parámetros y/o topología se desconocen. Los algoritmos deben ser replicables y deben funcionar en otro tipo de convertidores que se utilizan en el campo de la electrónica de potencia. La tesis se divide en dos núcleos principales, que son la identificación de parámetros de los convertidores y el modelado de caja negra (black-box) de dispositivos electrónicos de potencia. Los enfoques propuestos se basan en algoritmos de optimización y técnicas de aprendizaje profundo que utilizan mediciones no intrusivas de las tensiones y corrientes de los convertidores para obtener un conjunto de parámetros o generar un modelo, respectivamente. En ambos casos, los algoritmos se entrenan y prueban utilizando datos reales recopilados de convertidores utilizados en aviones y vehículos eléctricos. Esta tesis también presenta cómo las metodologías propuestas se pueden aplicar a sistemas eléctricos más complejos y para tareas de diagnóstico. En conclusión, esta tesis tiene como objetivo proporcionar algoritmos que permitan a las industrias obtener modelos realistas y precisos de los componentes que están utilizando en sus sistemas eléctricos.Postprint (published version