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A robust machine learning model for monitoring online voltage stability
Published in Informa UK Limited
Pages: 1 - 15

Continuous assessment of voltage stability (VS) is an important aspect to safeguard electrical power system (EPS) operation. The conservative methods for online assessment in terms of stability check for voltage are extremely time consuming and also absurd for supervising any application online. In agreement with this, a model which is an amalgamation of the Salp swarm algorithm (SSA) and support vector machine (SVM) is aimed at supervising the VS in the paper. The method anticipated for the aforesaid problem utilises the magnitude of voltage and its corresponding phase angle which are attained from the PMU as the inputs to the ML model and the respective output are considered to be the voltage stability margin index (VSMI). The proficiency of the anticipated model (SSA–SVM) is verified by means of various test cases under the real-time scenario and compared with the same data set to attest its pre-eminence. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

About the journal
JournalInternational Journal of Ambient Energy
PublisherInforma UK Limited
Open Access0