الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Power system security studies play a pivotal role in maintaining the security and integrity of the modern interconnected power system network. Understanding the complexity of modern power system operations is vitally important to avoid blackout events or cascading outage events, considering the nature of the vast majority of blackout causes. Blackouts have attracted considerable attention, in both academic and industrial realms. This thesis is dedicated to exploiting the artificial intelligence (AI) techniques and phasor measurement units (PMUs) to advance the power system operator’s knowledge of system states. Depending on the degree of security constraint violations, the power system operating states can be categorized into normal, alert, emergency, extreme emergency, and restorative. Hence, a synchrophasor measurements-based composite insecurity index (CISI) for contingency analysis is developed first. CISI is presented to identify critical components (lines and generation units), initiating events, shortest paths for cascading outage and cascading chains. The developed insecurity index has been obtained in terms of thermal transfer capacity of transmission lines, voltage profile, active and reactive power of generation units. CISI offers a simple method to quantify and rank critical contingencies in an efficient way. The development of cascading outages can be assessed by categorizing and visualizing catastrophic contingencies.The second part addresses the application of unsupervised artificial intelligence techniques equipped with CISI to estimate and identify power system operating states. Two well-known clustering techniques namely k-means (KM) and fuzzy c-means (FCM) are used for contingency screening and ranking. The performance of both algorithms has been investigated and compared. Furthermore, extensive simulations under different scenarios and multiple contingencies (up to N - 3) are performed to ensure the robustness and effectiveness of the developed technique. The numerical investigation covers different IEEE test systems such as 6-bus, IEEE 14-bus, IEEE 24-bus, IEEE 57-bus, and IEEE 118- bus. Finally, the developed technique for power system security investigation is experimentally evaluated using a laboratory-developed 5-bus test system. Including transmission line models, generation sets, busbars, circuit breakers, and several types of loads, the 5-bus test system has been constructed entirely in the lab. Also, SEL manufactured PMUs have been used to construct the synchrophasor measurement system in the power system lab in the faculty of industrial education, Suez University. The synchrophasor measurement system comprises 5 PMUs (1 × SEL-421, and 4 × SEL-351A), phasor data concentrator (1 × SEL-3373), satellite clock with global positioning system (GPS) antenna (1× SEL-2401). The results of both numerical and experimental investigations emphasized the superiority of the developed techniques for power system security investigation.