{"id":{"repo_id":"must-thes","oai_identifier":"oai:scholarsmine.mst.edu:doctoral_dissertations-2707"},"canonical_url":"https://search.dev.ndltd.org/etd/must-thes/oai:scholarsmine.mst.edu:doctoral_dissertations-2707","repository":{"repo_id":"must-thes","name":"Missouri University of Science and Technology","base_url":"https://scholarsmine.mst.edu/do/oai/"},"display":{"title":"The application of genetic algorithms to identify the worst credible states in a bulk power system","abstract":"\"This research project presents the application of the genetic algorithm to identify the worst credible states in a bulk power system which is very important to engineers who are planning and operating the system. Contingency analysis which is the classical method is applied to analyze all possible states when one to three components is the system are removed or failed at a time\"--Abstract, page iii.","abstract_html":""This research project presents the application of the genetic algorithm to identify the worst credible states in a bulk power system which is very important to engineers who are planning and operating the system. Contingency analysis which is the classical method is applied to analyze all possible states when one to three components is the system are removed or failed at a time"--Abstract, page iii.","abstract_has_math":false,"creators":["Paenyoorat, Prasert"],"institution":"University of Missouri--Rolla","degree_name":"Ph. D. in Electrical Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-02-10T08:00:00Z","date_published":"2016-02-10T08:00:00Z","updated_at":"2026-07-24T03:18:50Z","subjects":["Composite system reliability","Electrical and Computer Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/1705","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Paenyoorat, Prasert"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-02-10T08:00:00Z"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation - Citation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Electrical Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Rolla"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Composite system reliability","Electrical and Computer Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/1705"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"This research project presents the application of the genetic algorithm to identify the worst credible states in a bulk power system which is very important to engineers who are planning and operating the system. Contingency analysis which is the classical method is applied to analyze all possible states when one to three components is the system are removed or failed at a time\"--Abstract, page iii."]},{"key":"dc:title","label":"Title","values":["The application of genetic algorithms to identify the worst credible states in a bulk power system"]}]}],"canonical_facts":{"dc:creator":["Paenyoorat, Prasert"],"dc:date.available":["2016-02-10T08:00:00Z"],"dc:description.abstract":["\"This research project presents the application of the genetic algorithm to identify the worst credible states in a bulk power system which is very important to engineers who are planning and operating the system. Contingency analysis which is the classical method is applied to analyze all possible states when one to three components is the system are removed or failed at a time\"--Abstract, page iii."],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/1705"],"dc:subject":["Composite system reliability","Electrical and Computer Engineering"],"dc:title":["The application of genetic algorithms to identify the worst credible states in a bulk power system"],"dc:type":["Dissertation - Citation"],"thesis:degree_name":["Ph. D. in Electrical Engineering"],"thesis:institution_name":["University of Missouri--Rolla"]},"updated_at":"2026-07-24T03:18:50Z"}