PSS AND IPFC POD controllers coordinated tuning by an Adaptive Genetic Algorithm with Hyper-mutation
Descripción del Articulo
Flexible AC transmission systems (FACTS) are a modern technology to increase controllability in power systems. This work presents an analysis of Interline Power Flow Controller (IPFC) which is a FACTS device. This device control and manage power flow in transmission lines. Supplementary damping cont...
Autores: | , |
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Formato: | artículo |
Fecha de Publicación: | 2018 |
Institución: | Universidad Nacional de Ingeniería |
Repositorio: | Revistas - Universidad Nacional de Ingeniería |
Lenguaje: | español |
OAI Identifier: | oai:oai:revistas.uni.edu.pe:article/541 |
Enlace del recurso: | https://revistas.uni.edu.pe/index.php/tecnia/article/view/541 |
Nivel de acceso: | acceso abierto |
Materia: | estabilizadores de potencia hyper-mutación algortimo genético adaptativo Small-signal Stability, Power System Stabilizers, Interline Power Flow Controller, Power Oscillation Damping, Adaptive Genetic Algorithm, Hyper-mutation. |
Sumario: | Flexible AC transmission systems (FACTS) are a modern technology to increase controllability in power systems. This work presents an analysis of Interline Power Flow Controller (IPFC) which is a FACTS device. This device control and manage power flow in transmission lines. Supplementary damping controller is installed on IPFC Proportional Integral (PI) control. Power Oscillation Damping (POD) and Power System Stabilizers (PSS) contribute to power system stability. This works represents the electric power system and Interline Power Flow Controller FACTS device by a current sensitivity model (CSM). This work focuses on small-signal stability studies using an Adaptive Genetic Algorithm and Hyper-mutation (AGAH) to design simultaneously controller parameters. Adaptive Genetic Algorithm aims to find optimal controller parameters to enhance greatly stability of the power system. This paper considers two areas 14 bus symmetrical system in order to assess proposed algorithm. Simulations are carried out in MatLab platform in order to compare genetic algorithm with proposed algorithm performance. Results show AGAH outweighed AG by time convergence and accuracy. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).