{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/52623"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/52623","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Transient Stability Prediction based on Synchronized Phasor Measurements and Controlled Islanding","abstract":"Traditional methods for predicting transient stability of power systems such as the direct method, the time domain approach, and the energy function methods do not work well for online transient stability predictions problems. With the advent of Phasor Measurement Units (PMUs) in power systems, it is now possible to monitor the behavior of the system in real time and provide important information for transient stability assessment and enhancement. Techniques such as the rotor oscillation prediction method based on time series have made the prediction of system stability possible for real-time applications. However, methods of this type require more than 300 milliseconds after the start of a transient event to make reliable predictions. The dissertation provides an alternate prediction method for transient stability by taking advantage of the available PMUs data. It predicts transient stability using apparent impedance trajectories obtained from PMUs, decision trees, and FLDSD method. This method enables to find out the strategic locations for PMUs installation in the power system to rapidly predict transient stability. From the simulations performed, it is realized that system stability can be predicted in approximately 200 milliseconds (12 cycles). The main advantage of this method is its simplicity as the PMUs can record the apparent impedance trajectories in real-time without any previous calculations. Moreover, using decision trees built in CART, transient stability prediction becomes straightforward and computationally very fast. The optimum locations for PMUs placement can also be determined using this technique. After the transient instability prediction by the apparent impedance trajectories, a slow- coherency based intelligent controlled islanding scheme is also developed to restore the stability of system. It enables the generators in the same island to stay in synchronism and the imbalance between the generators and load demand is minimized.","abstract_html":"Traditional methods for predicting transient stability of power systems such as the direct method, the time domain approach, and the energy function methods do not work well for online transient stability predictions problems. With the advent of Phasor Measurement Units (PMUs) in power systems, it is now possible to monitor the behavior of the system in real time and provide important information for transient stability assessment and enhancement. Techniques such as the rotor oscillation prediction method based on time series have made the prediction of system stability possible for real-time applications. However, methods of this type require more than 300 milliseconds after the start of a transient event to make reliable predictions. The dissertation provides an alternate prediction method for transient stability by taking advantage of the available PMUs data. It predicts transient stability using apparent impedance trajectories obtained from PMUs, decision trees, and FLDSD method. This method enables to find out the strategic locations for PMUs installation in the power system to rapidly predict transient stability. From the simulations performed, it is realized that system stability can be predicted in approximately 200 milliseconds (12 cycles). The main advantage of this method is its simplicity as the PMUs can record the apparent impedance trajectories in real-time without any previous calculations. Moreover, using decision trees built in CART, transient stability prediction becomes straightforward and computationally very fast. The optimum locations for PMUs placement can also be determined using this technique. After the transient instability prediction by the apparent impedance trajectories, a slow- coherency based intelligent controlled islanding scheme is also developed to restore the stability of system. It enables the generators in the same island to stay in synchronism and the imbalance between the generators and load demand is minimized.","abstract_has_math":false,"creators":["Li, Meiyan"],"institution":"Virginia Tech","degree_name":"Ph. D.","degree_level":"doctoral","degree_discipline":"Electrical Engineering","degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Phadke, Arun G."],"committee_members":["De La Ree, Jaime","Kohler, Werner E.","Centeno, Virgilio A.","Evrenosoglu, Cansin Yaman","Orlowski, Mariusz Kriysztof"],"year":2013,"date_issued":"2013-06-20","date_published":"2013-06-20","updated_at":"2026-07-22T22:19:31Z","subjects":["critical locations","apparent impedance trajectory","complex synchrophasor data","decision trees","dimensional reduction"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:1295"],"render_values":[{"text":"vt_gsexam:1295","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/52623","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Phadke, Arun G."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["De La Ree, Jaime","Kohler, Werner E.","Centeno, Virgilio A.","Evrenosoglu, Cansin Yaman","Orlowski, Mariusz Kriysztof"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical and Computer Engineering"]},{"key":"dc:creator","label":"Author","values":["Li, Meiyan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-05-27T08:02:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-05-27T08:02:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-06-20"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. 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With the advent of Phasor Measurement Units (PMUs) in power systems, it is now possible to monitor the behavior of the system in real time and provide important information for transient stability assessment and enhancement. Techniques such as the rotor oscillation prediction method based on time series have made the prediction of system stability possible for real-time applications. However, methods of this type require more than 300 milliseconds after the start of a transient event to make reliable predictions. The dissertation provides an alternate prediction method for transient stability by taking advantage of the available PMUs data. It predicts transient stability using apparent impedance trajectories obtained from PMUs, decision trees, and FLDSD method. This method enables to find out the strategic locations for PMUs installation in the power system to rapidly predict transient stability. From the simulations performed, it is realized that system stability can be predicted in approximately 200 milliseconds (12 cycles). The main advantage of this method is its simplicity as the PMUs can record the apparent impedance trajectories in real-time without any previous calculations. Moreover, using decision trees built in CART, transient stability prediction becomes straightforward and computationally very fast. The optimum locations for PMUs placement can also be determined using this technique. After the transient instability prediction by the apparent impedance trajectories, a slow- coherency based intelligent controlled islanding scheme is also developed to restore the stability of system. It enables the generators in the same island to stay in synchronism and the imbalance between the generators and load demand is minimized."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Transient Stability Prediction based on Synchronized Phasor Measurements and Controlled Islanding"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Phadke, Arun G."],"dc:contributor.committeemember":["De La Ree, Jaime","Kohler, Werner E.","Centeno, Virgilio A.","Evrenosoglu, Cansin Yaman","Orlowski, Mariusz Kriysztof"],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Li, Meiyan"],"dc:date.accessioned":["2015-05-27T08:02:09Z"],"dc:date.available":["2015-05-27T08:02:09Z"],"dc:date.issued":["2013-06-20"],"dc:description.abstract":["Traditional methods for predicting transient stability of power systems such as the direct method, the time domain approach, and the energy function methods do not work well for online transient stability predictions problems. With the advent of Phasor Measurement Units (PMUs) in power systems, it is now possible to monitor the behavior of the system in real time and provide important information for transient stability assessment and enhancement. Techniques such as the rotor oscillation prediction method based on time series have made the prediction of system stability possible for real-time applications. However, methods of this type require more than 300 milliseconds after the start of a transient event to make reliable predictions. The dissertation provides an alternate prediction method for transient stability by taking advantage of the available PMUs data. It predicts transient stability using apparent impedance trajectories obtained from PMUs, decision trees, and FLDSD method. This method enables to find out the strategic locations for PMUs installation in the power system to rapidly predict transient stability. From the simulations performed, it is realized that system stability can be predicted in approximately 200 milliseconds (12 cycles). The main advantage of this method is its simplicity as the PMUs can record the apparent impedance trajectories in real-time without any previous calculations. Moreover, using decision trees built in CART, transient stability prediction becomes straightforward and computationally very fast. The optimum locations for PMUs placement can also be determined using this technique. After the transient instability prediction by the apparent impedance trajectories, a slow- coherency based intelligent controlled islanding scheme is also developed to restore the stability of system. It enables the generators in the same island to stay in synchronism and the imbalance between the generators and load demand is minimized."],"dc:description.degree":["Ph. D."],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:1295"],"dc:identifier.uri":["http://hdl.handle.net/10919/52623"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["critical locations","apparent impedance trajectory","complex synchrophasor data","decision trees","dimensional reduction"],"dc:title":["Transient Stability Prediction based on Synchronized Phasor Measurements and Controlled Islanding"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Ph. D."],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:31Z"}