Transient staiblity analysis by adaptive neuro fuzzy inference system and sobol sequence

dc.contributor.authorPhootrakornchai, Witsawa
dc.contributor.authorJiriwibhakorn, Somchat
dc.date.accessioned2026-08-06T10:20:34Z
dc.date.available2026-08-06T10:20:34Z
dc.date.issued2018-07-02
dc.description.abstractIt is known that the time domain is an accurate method that is used for the assessment of transient stability and critical clearing time for any power systems. However, the time domain method normally takes a long time for the calculation due to many differential and non-linear equations, thus it may not be appropriate to apply with the real-time analysis, especially the large power system. We try to find any approaches to minimize the computation time and maximize the accuracy of results as much as possible. This paper therefore proposes a method using adaptive neuro fuzzy inference system and sobol sequence for solving the critical clearing time. The approach proves that it can give us the satisfactory prediction of critical clearing time even for a large power system. The result obtained by adaptive neuro fuzzy inference system are also compared to the result obtained by means of artificial neural network being generally used for the power system analysis.
dc.identifier.citationEcti Con 2018 15th International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology, 49-53, 2018
dc.identifier.doi10.1109/ECTICon.2018.08619962
dc.identifier.other2-s2.0-85062239786
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/8752
dc.sourceEcti Con 2018 15th International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology
dc.subjectAdaptive neuro fuzzy inference system
dc.subjectArtificial neural networks
dc.subjectClassical model
dc.subjectCritical clearing time
dc.subjectSobol sequence
dc.titleTransient staiblity analysis by adaptive neuro fuzzy inference system and sobol sequence
dc.typeConference Paper

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