Diseño y simulación del Sistema de Control de la Excetatriz de una máquina síncrona mediante un algoritmo de inteligencia artificial
| dc.contributor.advisor | Florez Cediel, Oscar David | |
| dc.contributor.author | Cubillos Cruz, Sara Vanessa | |
| dc.contributor.author | Novoa Pinzón, Johan Alexander | |
| dc.contributor.orcid | Florez Cediel, Oscar David [0000-0002-0653-0577] | |
| dc.date.accessioned | 2025-11-24T20:28:10Z | |
| dc.date.available | 2025-11-24T20:28:10Z | |
| dc.date.created | 2025-05-08 | |
| dc.description | En este trabajo se aborda el diseño e implementación de algoritmos basados en inteligencia artificial para el control de la excitatriz de una máquina síncrona basados en los módelos de excitación de corriente continua DC1A y DC2A del estándar IEEE 421.5 del año 2005 y 2016. Se plantean dos modelos basados en control difuso y otros dos modelos basados en machine learning con el fin de comparar los modelos e identificar cuál es el modelo que mejor prestaciones tiene con respecto a las tres pruebas de evaluación realizadas al cambio dinámico de cargas, al cambio del voltaje de referencia y al voltaje pico de fase cuando se maneja voltaje nominal. A nivel general se observó un mejor rendimiento en los modelos basados en control difuso con respecto a los modelos basados en machine learning. | |
| dc.description.abstract | This work addresses the design and implementation of algorithms based on artificial intelligence for the control of the exciter of a synchronous machine based on the DC1A and DC2A direct current excitation models of the IEEE 421.5 standard of 2005 and 2016. Two models based on fuzzy control and two other models based on machine learning are proposed in order to compare the models and identify which is the model that has the best performance with respect to the three evaluation tests carried out on the dynamic change of loads, the change of the reference voltage and the peak phase voltage when handling nominal voltage. In general, a better performance was observed in the models based on fuzzy control with respect to the models based on machine learning. | |
| dc.format.mimetype | ||
| dc.identifier.uri | http://hdl.handle.net/11349/99918 | |
| dc.language.iso | spa | |
| dc.publisher | Universidad Distrital Francisco José de Caldas | |
| dc.relation.references | Garces R. Alejandro, Gil G. Walter Julian y Montoya G. Oscar Danilo. Introducción a la Estabilidad de Sistemas Eléctricos de Potencia. | |
| dc.relation.references | Li-Xin Wang. A Course in Fuzzy Systems and Control. Pretice-HallInternational, Inc, 1997 | |
| dc.relation.references | IEEE. IEEE Recommended Practice for Excitation System Models for Power System Stability Studies. 2005. url: https://www.researchgate.net/profile/Mohamed_Mourad_Lafifi/post/Hi_what_about_friends_could_you_help_me_with_the_Norm e_115_IEEE_Test_procedures_for_synchronous_machines/attachment/59d650a579197b80779a9681/AS%3A504056167583744%40149 7187764005/download/IEEE+Std+421.5-2005.pdf (visitado 09-05-2024). | |
| dc.relation.references | IEEE. IEEE Recommended Practice for Excitation System Models for Power System Stability Studies. 2005. url: https://www.researchgate.net/profile/Mohamed_Mourad_Lafifi/post/Hi_what_about_friends_could_you_help_me_with_the_Norm e_115_IEEE_Test_procedures_for_synchronous_machines/attachment/59d650a579197b80779a9681/AS%3A504056167583744%40149 7187764005/download/IEEE+Std+421.5-2005.pdf (visitado 09-05-2024). | |
| dc.relation.references | Yuanpeng Zhang y Guanjin Wang. TSK fuzzy system fusion at sensitivity-ensemble-level for imba-lanced data classification. 2014. (visitado 12-05-2024) | |
| dc.relation.references | Sungroh. «Deep learning tutorial. In: Tutorials in International Conference on Machine Learning (ICML’13)». En: Seoul National University 2023.(visitado 03-05-2024) | |
| dc.relation.references | Shirkin Roman. Artificial Intelligence - The complete beginners’ guide to artificial intelligence. url: https://www.amazon.com/Artificial Intelligence-Complete-Beginners-Guide-ebook/dp/B084GTB7WM 2020. (visitado 15-05-2024) | |
| dc.rights.acceso | Abierto (Texto Completo) | |
| dc.rights.accessrights | OpenAccess | |
| dc.subject | Máquina Síncrona | |
| dc.subject | Inteligencia Artifical | |
| dc.subject | Control Excitatriz | |
| dc.subject | Algortimo | |
| dc.subject.keyword | Synchronous Machine | |
| dc.subject.keyword | Artificial Intelligence | |
| dc.subject.keyword | Excitatory Control | |
| dc.subject.keyword | Algorithm | |
| dc.subject.lemb | Ingeniería Electrónica -- Tesis y disertaciones académicas | |
| dc.subject.lemb | Máquinas síncronas | |
| dc.subject.lemb | Inteligencia artificial | |
| dc.subject.lemb | Aprendizaje automático | |
| dc.subject.lemb | Regulaores de voltaje | |
| dc.title | Diseño y simulación del Sistema de Control de la Excetatriz de una máquina síncrona mediante un algoritmo de inteligencia artificial | |
| dc.title.titleenglish | Design and Simulation of the Exciter Control System of a Synchronous Machine Using an Artificial Intelligence Algorithm | |
| dc.type | bachelorThesis | |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
| dc.type.degree | Monografía | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis |
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