Abstract—This paper describes the application of the abrupt change detection technologies to detect the abrupt changes in the signals recorded during disturbances in the electrical power network of South Africa for disturbance analysis and relay performance monitoring. The aim is to estimate the time instants of the changes in the signal model parameters during the prefault condition, after initiation of fault, after the circuit-breaker opening and autoreclosure, etc. After these event-specific segmentations, the synchronization of the different digital fault recorder recordings are done based on the fault inception timings. The synchronized signals are segmented again. This synchronized segmentation is the first step toward automatic disturbance recognition, facilitating further complex feature vector analysis and pattern recognition. Besides, the synchronized, segmented recordings can be directly used to analyze certain kinds of disturbances and monitor the relay performance. This paper presents many practical examples from the power network in South Africa.

This dissertation attempts to establish an analytical and comprehensive framework to deal with two critical challenges associated with voltage stability analysis: 1. To study the new competitive environment appropriately and give more incentive for reactive power supports, one has to evaluate the impacts of distributed market forces on voltage stability, which complicates the voltage stability analysis. 2. Accurately estimating voltage stability margin online is always the goal of the industry. Industry used to apply static analysis for its computation speed at the cost of losing accuracy. On the other hand, dynamic analysis can result in more accurate estimation, but generally has a huge computation cost. So a challenge is to estimate the voltage stability margin accurately and efficiently at a reasonable cost, especially for large system. Considering the first challenge, this dissertation applied eigenvalue based bifurcation analysis to allocate the contribution of voltage stability. We investigate how parameters of the system influence the bifurcations. Three bifurcations (singularity induced bifurcation, saddle-node and Hopf bifurcation) and their relationship to several commonly used controllers are analyzed. Their parameters’ impact on these bifurcations have been investigated, from which we found a way to allocate the contribution by analyzing the relative positions of the bifurcations. For the second challenge, a new fast numerical scheme is developed to estimate voltage stability margin by intelligently adjusting the load increase ratio. A criterion, named EMD (Equilibrium Manifold Deviation) criterion, is proposed to gauge the accuracy of the estimation. And based on this criterion, a new computation scheme is proposed. The validity of our new approach is proven based on the well-known Runge-Kutta-Fehlberg method, and can be extended to other explicit single-step methods easily. Numerical tests demonstrate that the new approach is very practical and has great potential for industrial applications. This dissertation extends our new numerical scheme to stiff systems. When a system is ill-conditioned, the implicit method would be applied to achieve numerical stability. We further demonstrate the validity to combine the intelligent load adjustment technique with the implicit method to save the computation cost without loss of accuracy. This dissertation also delves into the auto detection of stiffness of the power system, and extends our new numerical scheme to general sytems.

Wide-area measurement systems (WAMS) enable the monitoring of overall bulk power systems and provide critical information for understanding and responding to power system disturbances and cascading failures. The North American Frequency Monitoring Network (FNET) takes GPS-synchronized wide-area measurements in a low-cost, easily deployable manner at the 120 V distribution level, which presents more opportunities to study power system dynamics. This work explores the topics of power system disturbance analysis and detection by utilizing the wide-area measurements obtained in the distribution networks. In this work, statistical analysis is conducted based on the major disturbances in the North American Interconnections detected by the FNET situation awareness system between 2006 and 2008. Typical frequency patterns of the generation and load loss events are analyzed for the three North American power Interconnections: the Eastern Interconnection (EI), the Western Electricity Coordinating Council (WECC), and the Electric Reliability Council of Texas (ERCOT). The linear relationship between frequency deviation and frequency change rate during generation/loss mismatch events is verified by the measurements in the three Interconnections. The relationship between the generation/load mismatch and system frequency is also examined based on confirmed generation loss events in the EI system. And a power mismatch estimator is developed to improve the current disturbance detection program. Various types of power system disturbances are examined based on frequency, voltage and phase angle to obtain the event signatures in the measurements. To better understand the propagation of disturbances in the power system, an automated visualization tool is developed that can generate frequency and angle replays of disturbances, as well as image snapshots. This visualization tool correlates the wide-area measurements with geographical information by displaying the measurements over a geographical map. This work makes an attempt to investigate the visualization of the angle profile in the wide-area power system to improve situation awareness. This work explores the viability of relying primarily on distribution-level measurements to detect and identify line outages, a topic not yet addressed in previous works. Line outage sensitivity at different voltage levels in the Tennessee Valley Authority (TVA) system is examined to analyze the visibility of disturbances from the point of view of wide-area measurements. The sensor placement strategy is proposed for better observability of the line trip disturbances. The characteristics of line outages are studied extensively with simulations and real measurements. Line trip detection algorithms are proposed that employs the information in frequency and phase angle measurements. In spite of the limited FDR coverage and confirmed training cases, an identification algorithm is developed which uses the information in the real measurements as well as the simulation cases to determine the tripped line. / Ph. D.