<p dir="ltr">A broad scope of this dissertation is to verify that a nearby loss of generation event in power system can be distinguished from similar remote disturbances by analyzing the resulting local modes of oscillation. An oscillation-based index derived from methods like Fourier transform, sinc filters and resonant filters is devised and experimented in combination with a variant of df/dt index to jointly classify if a loss of generation event is nearby or remote. A phenomenon widely observed during a loss of generation event is the average decrease in the system’s frequency, typically monitored using the df/dt index. Under-frequency load-shedding (UFLS) relays that are based on df/dt are highly likely to trip for nearby frequency events when combined with the oscillation-based index we propose. Nearby in our context refers to geographical distance, which is correlated with electrical distance, and includes buses within about 50-100 miles of the event location.</p>

Severe disturbances in a large electrical interconnection cause a large mismatch in generation and load in the network, leading to frequency instability. If the mismatch is not rectified quickly, the system may disintegrate into multiple islands. Though the Automatic Generation Controls (AGC) perform well in correcting frequency deviation over a period of minutes, they are ineffective during a rolling blackout. While traditional Under Frequency Load Shedding Schemes (UFLS) perform quick control actions to arrest frequency decline in an islanded network, they are not designed to prevent unplanned islanding. The proposed Intelligent Load Shedding algorithm combines the effectiveness of AGC Scheme by observing tie line flows and the speed of operation of the UFLS Scheme by shedding loads intelligently, to preserve system integrity in the event of an evolving cascading failure. The proposed scheme detects and estimates the size of an event by monitoring the tie lines of a control area using Wide Area Measurement Systems (WAMS) and initiates load shedding by removing loads whose locations are optimally determined by a sensitivity analysis. The amount and location of the load shedding depends on the location and size of the initiating event, making the proposed algorithm adaptive and selective. Case Studies have been presented to show that control actions of the proposed scheme can directly mitigate a cascading blackout. / Ph. D.

The radical changes that are currently occurring in the nature of power systems means that in the future it may no longer be possible to guarantee security of supply using offline security assessment and planning. The increased uncertainty, particularly the reduction and variation in system inertia that will be faced in the future must be overcome through the use of adaptive online solutions for ensuring system security. The introduction of synchronised measurement technology means that the wide area real time measurements that are necessary to implement these online actions are now available.The objective of the research presented in this thesis was to create methods for predicting the post-disturbance frequency behaviour of a power system with the intent of contributing to the development of real time adaptive corrective control for future power systems. Such a prediction method would generate an online prediction based on wide area measurements of frequency and active power that are recorded within the period of approximately one second after a disturbance to the active power balance of the system. Predictions would allow frequency control to respond more quickly and efficiently as it would no longer be necessary to wait for the system frequency behaviour to violate pre-determined thresholds.The research presented in this thesis includes the creation of an online method for the simultaneous detection of the time at which a disturbance occurred in a power system, or area of a power system, and the estimation of the inertia of that system, or area. An existing prediction method based on approximate models has been redesigned to eliminate its dependence on offline information. Furthermore, the thesis presents the novel application of pattern classification theory to frequency prediction and a five class example of pattern classification is implemented.

Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation. / Ph. D.

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The electric power supply industry has evolved into one of the largest industries. Even though secure and reliable operation of the electric power system is fundamental to economy, social security and quality of modern life, the complicated power grid is now facing severe challenges to meet the high-level secure and reliable operation requirements. New technologies will play a major role in helping today's electric power industry to meet the above challenges. This dissertation has focused on some key technologies among them, including the emerging technologies of energy storage, controlled power electronics and wide area measurement technologies. Those technologies offer an opportunity to develop the appropriate objectives for power system control. The use of power electronics based devices with energy storage system integrated into them, such as FACTS/ESS, can provide valuable added benefits to improve stability, power quality, and reliability of power systems. The study in this dissertation has provided several guidelines for the implementation of FACTS/ESS in bulk power systems. The interest of this study lies in a wide range of FACTS/ESS technology applications in bulk power system to solve some special problems that were not solved well without the application of FACTS/ESS. The special problems we select to solve by using FACTS/ESS technology in this study include power quality problem solution by active power compensation, electrical arc furnace (EAF) induced problems solution, inter-area mode low frequency oscillation suppression, coordination of under frequency load shedding (UFLS) and under frequency governor control (UFGC), wide area voltage control. From this study, the author of this dissertation reveals the unique role that FACTS/ESS technology can play in the bulk power system stability control and power quality enhancement in power system. In this dissertation, almost all the studies are based on the real system problems, which means that the study results are special valuable to certain utilities that have those problems. The study in this dissertation can assist power industry choose the right FACTS/ESS technology for their intended functions, which will improve the survivability, minimize blackouts, and reduce interruption costs through the use of energy storage systems. / Ph. D.