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Voltage sag assessment using an extended fault positions method and Monte Carlo simulation
In this article, we propose an extended fault positions method combined with the Monte Carlo method to evaluate voltage sags. The distribution function SARFI is obtained by taking into account the randomness of (i) location of faults in lines, (ii) generation dispatch, and (iii) the prefault voltage...
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Published in: | Dyna (Medellín, Colombia) Colombia), 2016-02, Vol.83 (195), p.180-188 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In this article, we propose an extended fault positions method combined with the Monte Carlo method to evaluate voltage sags. The distribution function SARFI is obtained by taking into account the randomness of (i) location of faults in lines, (ii) generation dispatch, and (iii) the prefault voltage. Voltage magnitudes are calculated with power flow, while noting changes in the generation dispatch, the load, and the topology of the area of vulnerability (AOV). The method is tested in the Atlantic coast area of the National Interconnected Power System of Colombia. The distribution of the number of voltage sags per year with the magnitude in bus bars and the impact of generation on the voltage sags are determined. With a higher number of plants dispatched, voltage sags caused by faults are less severe due to the robustness of the power system and the voltage support. Operation with coupled bars had a greater impact on voltage sags compared to uncoupled bars. |
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ISSN: | 0012-7353 2346-2183 |
DOI: | 10.15446/dyna.v83n195.49495 |