M
Meng Yen Shih
Researcher at Autonomous University of Campeche
Publications - 20
Citations - 432
Meng Yen Shih is an academic researcher from Autonomous University of Campeche. The author has contributed to research in topics: Overcurrent & Relay. The author has an hindex of 8, co-authored 19 publications receiving 290 citations. Previous affiliations of Meng Yen Shih include University of Quintana Roo & Universidad Autónoma de Nuevo León.
Papers
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Journal ArticleDOI
Adaptive directional overcurrent relay coordination using ant colony optimisation
TL;DR: In this article, the relay coordination is formulated as an optimisation problem and the ant colony algorithm is used to coordinate the directional overcurrent relays based on an adaptive protection scheme.
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An Adaptive Overcurrent Coordination Scheme to Improve Relay Sensitivity and Overcome Drawbacks due to Distributed Generation in Smart Grids
TL;DR: In this paper, the authors proposed the mitigation of DG impact on DOCR coordination employing adaptive protection scheme (APS) using differential evolution algorithm while improving overall sensitivity of relays, which is the most implemented protective device in the electrical network, also suffers performance degradation in the presence of DG.
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Enhanced differential evolution algorithm for coordination of directional overcurrent relays
TL;DR: The enhanced-DE (eDE) shown best result in terms of execution time, result quality, robustness and convergence ability compared to the others analyzed in this research.
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Improvement of non-standardized directional overcurrent relay coordination by invasive weed optimization
TL;DR: Overall results expose the enhancement of relay coordination when using non-standardized inverse time curves and IWO.
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On-line coordination of directional overcurrent relays: Performance evaluation among optimization algorithms
TL;DR: The principal objective of this paper is to perform on-line coordination of the directional overcurrent relays in order to enhance speed and sensitivity and to formulate the differential evolution algorithm and compare it with the genetic algorithm and ant colony algorithm.