A generalized m-bus case study to test the computational efficiency of a PMU-based 4-Wire DSSE procedure

The following document discusses the use of phasor measurement units (PMU) in state estimation, and it is focused in a distribution system using the 4-wire detailed model. Initially, the necessary concepts to the right understanding of the document will be presented, such as state estimation, which...

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Autores:
Rodríguez Pérez, Néstor Alfonso
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2019
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/45324
Acceso en línea:
http://hdl.handle.net/1992/45324
Palabra clave:
Impedancia (Electricidad)
Sistemas de energía eléctrica
Transmisión de potencia
Ingeniería
Rights
openAccess
License
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
Description
Summary:The following document discusses the use of phasor measurement units (PMU) in state estimation, and it is focused in a distribution system using the 4-wire detailed model. Initially, the necessary concepts to the right understanding of the document will be presented, such as state estimation, which is a mathematical method used to estimate voltages and currents in a power system. In this work it will be assumed the use of PMU's to acquire measurements of voltage, current, and also grounding impedance. The document presents a generalization of a method of parameter estimation that could be use in distribution systems to identify failures in multi-grounded systems measurements. Followed by the generalization of an algorithm in the software MATLAB, which can be used to implement the parameter estimation of the system. Finally, the results will be presented and discussed. The main objective of this project is to develop a m-node study case, in order to test the algorithm developed by DeOliviera-Ramos-Celeita. Therefore, a study case based in the Kersting Nev system as developed, in order to include a growing number of nodes. Later, a generalization of the state estimation algorithm was developed, Finally, the computational efficiency and parameter estimation efficiency were tested.