As our electric power distribution infrastructure has aged, considerable investment has been applied to modernizing the electrical power grid through weatherization and in deployment of real-time monitoring systems. A key question is whether or not these investments are reducing the number and duration of power outages, leading to improved reliability. Statistical methods are applied to analyze electrical disturbance data (from the Department of Energy, DOE) and reliability index data (from state utility public service commission regulators) to detect signs of improvement. The number of installed smart meters provided by several utilities is used to determine whether the number of smart meters correlate with a reduction in outage frequency. Indication emerged that the number of power outages may be decreasing over time. The magnitude of power loss has decreased from 2003 to 2007, and behaves cyclically from 2008 to 2014, with a few outlier points in both groups. The duration also appears to be decreasing between 2003-2014. Large blackout events exceeding 5 GW continue to be rare, and certain power outage events are seasonally dependent. There was a linear relationship between the number of customers and the magnitude of a power outage event. However, no relationship was found between the magnitude of power outages and time to restore power. The frequency of outages maybe decreasing as the number of installed smart meters has increased. Recommendations for inclusion of additional metrics, changes to formatting and semantics of datasets currently provided by federal and state regulators are made to help aid researchers in performing more effective analysis. Confounding variables and lack of information that has made the analysis diffcult is also discussed.

The matrix-inversion-lemma based recursive least squares (RLS) approach is of a recursive form and free of matrix inversion, and has excellent performance regarding computation and memory in solving the classic least-squares (LS) problem. It is important to generalize RLS for generalized LS (GLS) problem. It is also of value to develop an efficient initialization for any RLS algorithm. In Chapter 2, we develop a unified RLS procedure to solve the unconstrained/linear-equality (LE) constrained GLS. We also show that the LE constraint is in essence a set of special error-free observations and further consider the GLS with implicit LE constraint in observations (ILE-constrained GLS). Chapter 3 treats the RLS initialization-related issues, including rank check, a convenient method to compute the involved matrix inverse/pseudoinverse, and resolution of underdetermined systems. Based on auxiliary-observations, the RLS recursion can start from the first real observation and possible LE constraints are also imposed recursively. The rank of the system is checked implicitly. If the rank is deficient, a set of refined non-redundant observations is determined alternatively. In Chapter 4, base on [Li07], we show that the linear minimum mean square error (LMMSE) estimator, as well as the optimal Kalman filter (KF) considering various correlations, can be calculated from solving an equivalent GLS using the unified RLS. In Chapters 5 & 6, an approach of joint state-and-parameter estimation (JSPE) in power system monitored by synchrophasors is adopted, where the original nonlinear parameter problem is reformulated as two loosely-coupled linear subproblems: state tracking and parameter tracking. Chapter 5 deals with the state tracking which determines the voltages in JSPE, where dynamic behavior of voltages under possible abrupt changes is studied. Chapter 6 focuses on the subproblem of parameter tracking in JSPE, where a new prediction model for parameters with moving means is introduced. Adaptive filters are developed for the above two subproblems, respectively, and both filters are based on the optimal KF accounting for various correlations. Simulations indicate that the proposed approach yields accurate parameter estimates and improves the accuracy of the state estimation, compared with existing methods.

In recent years, power demands around the world and particularly in North America increased rapidly due to increase in customer’s demand, while the development in transmission system is rather slow. This stresses the present transmission system and voltage stability becomes an important issue in this regard. Pattern recognition in conjunction with voltage stability analysis could be an effective tool to solve this problem In this thesis, a methodology to detect the voltage stability ahead of time is presented. Dynamic simulation software PSS/E is used to simulate voltage stable and unstable cases, these cases are used to train and test the pattern recognition algorithms. Statistical and algorithmic pattern recognition methods are used. The proposed method is tested on IEEE 39 bus system. Finally, the pattern recognition models to predict the voltage stability of the system are developed.

The purpose of this dissertation is to analyze dynamic behavior of a stressed power system and to correlate the dynamic responses to a near future system voltage abnormality. It is postulated that the dynamic response of a stressed power system in a short period of time-in seconds-contains sufficient information that will allow prediction of voltage abnormality in future time-in minutes. The PSSE dynamics simulator is used to study the dynamics of the IEEE 39 Bus equivalent test system. To correlate dynamic behavior to system voltage abnormality, this research utilizes two different pattern recognition methods one being algorithmic method known as Regularized Least Square Classification (RLSC) pattern recognition and the other being a statistical method known as Classification and Regression Tree (CART). Dynamics of a stressed test system is captured by introducing numerous contingencies, by driving the system to the point of abnormal operation, and by identifying those simulated contingencies that cause system voltage abnormality. Normal and abnormal voltage cases are simulated using the PSSE dynamics tool. The results of simulation from PSSE dynamics will be divided into two sets of training and testing set data. Each of the two sets of data includes both normal and abnormal voltage cases that are used for development and validation of a discriminator. This research uses stressed system simulation results to train two RLSC and CART pattern recognition models using the training set obtained from the dynamic simulation data. After the training phase, the trained pattern recognition algorithm will be validated using the remainder of data obtained from simulation of the stressed system. This process will determine the prominent features and parameters in the process of classification of normal and abnormal voltage cases from dynamic simulation data. Each of the algorithmic or statistical pattern recognition methods have their advantages and disadvantages and it is the intention of this dissertation to use them only to find correlations between the dynamic behavior of a stressed system in response to severe contingencies and the outcome of the system behavior in a few minutes into the future.

The analysis of power systems under fault condition represents one of the most important and complex tasks in power engineering. The study and detection of these faults are necessary to ensure that the reliability and stability of the power system do not suffer a decrement as a result of a critical event such as fault. The purpose of this thesis is to develop and to present an educational tool for students to model FACTS devices using Simulink. Furthermore, the development of this thesis provides the means for students to model different types of faults. The development is based on presenting a power system – the Test System - by its simplest form including generation, transmission, transformers, loads and STATCOM device as an example of the general FACTS devices. The thesis includes modeling of the Test System using Simulink and MATLAB program to produce the results for further analysis. The findings and development included in the thesis is intended to serve as an educational tool for students interested in the study of faults and their impact on FACTS devices. Students may use the thesis as the building block for developing models of larger and more complex power systems using Simulink and MATLAB programs for further study of impacts of FACTS devices in power systems.

A real-time simulator (RTS) with digital and analog input/output modules is used to conduct hardware-in-the-loop simulations to evaluate performance of power system equipment such as protective relays by exposing the equipment to the simulated realistic operating conditions. This work investigates the use of RTS to test relays with single-pole-switching (SPS) feature. Single-pole switching can cause misoperations due to fault arc during reclosing of the breakers. Through this investigation, a test procedure appropriate for the testing SPS relays has been developed. The test procedure includes power system modeling for real time simulation, relay test setup, and test plan. HYPERSIM real-time simulator was used to model an actual power system. Transmission lines, three-winding transformers, and induction motor were modeled with actual parameters. Models for fault arc in HYPERSIM real time simulator were developed. Test set-up for evaluating relay performance and wiring drawings for connecting relay in closed-loop to the simulator were developed.

Novel methods for the construction of dye-sensitized solar cells (DSSCs) were developed. A thin dense underlayer of TiO2 was applied on fluorine-doped tin oxide (FTO) glass using as a precursor Tyzor AA-105. Subsequently a mesoporous film of P-25 TiO2 was applied by spreading a suspension uniformly over the surface of the underlayer and allowing the plate to slowly dry while resting on a level surface. After sintering at 500° C slides were treated with TCPP as a sensitizing dye and assembled into DSSCs. A novel method was used to seal the cells; strips of Parafilm® were used as spacers between the electrodes and to secure the electrodes together. The cells were filled with a redox electrolyte and sealed by dipping into molten paraffin. A series of phosphonic acids and one arsonic acid were employed as coadsorbates in DSSCs. The coadsorbates were found to compete for binding sites, resulting in lower levels of dye adsorption. The resulting loss of photocurrent was not linear with the reduction of dye loading, and in some cases photocurrent and efficiency were higher for cells with lower levels of dye loading. Electrodes were treated with coadsorbates by procedures including pre-adsorption, simultaneous (sim-adsorption), and post-adsorption, using a range of concentrations and treatment times and a variety of solvents. Most cells were tested using an iodide-triiodide based electrolyte (I3I-1) but some cells were tested using electrolytes based on a Co(II)/Co(III) redox couple (CoBpy electrolytes). Phosphonic acid post-adsorbates increased the Voc of cells using CoBpy electrolytes but caused a decrease in the Voc of cells using I3I-1 electrolyte. Phosphonic acids as sim-adsorbates resulted in a significant increase in efficiency and Jsc, and they show promise as a treatment for TCPP DSSCs.

Long Term Evolution (LTE) is enormously adopted by several mobile operators and has been introduced as a solution to fulfil ever-growing Users (UEs) data requirements in cellular networks. Enlarged data demands engage resource blocks over prolong time interval thus results into more dynamic power consumption at downlink in Basestation. Therefore, realisation of UEs requests come at the cost of increased power consumption which directly affects operator operational expenditures. Moreover, it also contributes in increased CO2 emissions thus leading towards Global Warming. According to research, Global Information and Communication Technology (ICT) systems consume approximately 1200 to 1800 Terawatts per hour of electricity annually. Importantly mobile communication industry is accountable for more than one third of this power consumption in ICT due to increased data requirements, number of UEs and coverage area. Applying these values to global warming, telecommunication is responsible for 0.3 to 0.4 percent of worldwide CO2 emissions. Moreover, user data volume is expected to increase by a factor of 10 every five years which results in 16 to 20 percent increase in associated energy consumption which directly effects our environment by enlarged global warming. This research work focuses on the importance of energy saving in LTE and initially propose bandwidth expansion based energy saving scheme which combines two resource blocks together to form single super RB, thereby resulting in reduced Physical Downlink Control Channel Overhead (PDCCH). Thus, decreased PDCCH overhead helps in reduced dynamic power consumption up to 28 percent. Subsequently, novel reduced early handover (REHO) based idea is proposed and combined with bandwidth expansion to form enhanced energy ii saving scheme. System level simulations are performed to investigate the performance of REHO scheme; it was found that reduced early handover provided around 35% improved energy saving while compared to LTE standard in 3rd Generation Partnership Project (3GPP) based scenario. Since there is a direct relationship between energy consumption, CO2 emissions and vendors operational expenditure (OPEX); due to reduced power consumption and increased energy efficiency, REHO subsequently proven to be a step towards greener communication with lesser CO2 footprint and reduced operational expenditure values. The main idea of REHO lies in the fact that it initiate handovers earlier and turn off freed resource blocks as compare to LTE standard. Therefore, the time difference (Transmission Time Intervals) between REHO based early handover and LTE standard handover is a key component for energy saving achieved, which is estimated through axiom of Euclidean geometry. Moreover, overall system efficiency is investigated through the analysis of numerous performance related parameters in REHO and LTE standard. This led to a key finding being made to guide the vendors about the choice of energy saving in relation to radio link failure and other important parameters.

Presently, there are concerns that buildings in the USA under-performs in terms of energy efficiency when compared with the original design specifications. A significant percentage of the energy loss in these buildings is associated with the building’s envelope. This study provides a qualitative and analytical understanding of the R-value, which indicates the thermal performance of the elements that make up a building envelope. Infrared thermography is used as a methodology to assess the thermal performance of envelopes of ten buildings on East Tennessee State University Campus. A Fluke Ti25 infrared hand-held camera and a DJI phantom-2 drone mounted with FLIR Vue Pro infrared camera were used for data collection. Data analyses were carried out using ‘Smartview’ and ‘FLIR Reporter Pro’ software. The data analyses revealed energy loss, insulation deficiencies, the associated energy costs of the inefficiencies and the potential savings that could result from correcting these deficiencies in the evaluated building’s envelopes.

The synchronous machine is one of the critical components of electric power systems. Modeling of synchronous machines is essential for power systems analyses. Electric machines are often interfaced with power electronic components. This work presents an advanced synchronous machine modeling, which emphasis on the modeling and simulation of systems that contain a mixture of synchronous machines and power electronic components. Such systems can be found in electric drive systems, dc power systems, renewable energy, and conventional synchronous machine excitation. Numerous models and formulations have been used to study synchronous machines in different applications. Herein, a unified derivation of the various model formulations, which support direct interface to external circuitry in a variety of scenarios, is presented. Selection of the formulation with the most suitable interface for the simulation scenario has better accuracy, fewer time steps, and less run time. Brushless excitation systems are widely used for synchronous machines. As a critical part of the system, rotating rectifiers have a significant impact on the system behavior. This work presents a numerical average-value model (AVM) for rotating rectifiers in brushless excitation systems, where the essential numerical functions are extracted from the detailed simulations and vary depending on the loading conditions. The proposed AVM can provide accurate simulations in both transient and steady states with fewer time steps and less run time compared with detailed models of such systems and that the proposed AVM can be combined with AVM models of other rectifiers in the system to reduce the overall computational cost. Furthermore, this work proposes an alternative formulation of numerical AVMs of machine-rectifier systems, which makes direct use of the natural dynamic impedance of the rectifier without introducing low-frequency approximations or algebraic loops. By using this formulation, a direct interface of the AVM is achieved with inductive circuitry on both the ac and dc sides allowing traditional voltage-in, current-out formulations of the circuitry on these sides to be used with the proposed formulation directly. This numerical AVM formulation is validated against an experimentally validated detailed model and compared with previous AVM formulations. It is demonstrated that the proposed AVM formulation accurately predicts the system's low-frequency behavior during both steady and transient states, including in cases where previous AVM formulations cannot predict accurate results. Both run times and numbers of time steps needed by the proposed AVM formulation are comparable to those of existing AVM formulations and significantly decreased compared with the detailed model.