Implementation of a non-conventional method to characterize voltage sags and swells
Voltage sags and swells are among the power quality disturbances that represent the biggest economic losses for affected users. It is therefore necessary to undertake a suitable characterization of those events to conduct studies that permit the causes and possible mitigation techniques to be identi...
- Autores:
-
Celis-Montero, Jorge Enrique
Fernando-Navas, Diego
Castro-Aranda, Ferley
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60580
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60580
http://bdigital.unal.edu.co/58912/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Electromagnetic transient analysis
parameter estimation
power distribution faults
power quality
power system modeling
simulation
simulation software
time-domain analysis.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | Voltage sags and swells are among the power quality disturbances that represent the biggest economic losses for affected users. It is therefore necessary to undertake a suitable characterization of those events to conduct studies that permit the causes and possible mitigation techniques to be identified. This work describes the development of monitoring modules to characterize voltage sags and swells that could be used in Electromagnetic Transients Programs - EMTP (for example the ATP – Alternative Transients Program). The implemented module uses a novel method to characterize these disturbances. The results of the implementation show that the voltage sags and swells are appropriately characterized; furthermore, less sampled data is required from a voltage signal with respect to the conventional RMS voltage method. This could optimize the capture and analysis process of information in power quality monitoring. |
---|