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This paper presents a novel methodology based on machine learning for assessing the power system transient stability (TS) in real-time using synchronized phasor measurements as input in order to predict the power system TS status related to the single machine equivalent (SIME) results. Based on the probabilistic models of input parameters, such as load variation and the occurrence of contingencies,...
An estimator of the dynamic state of an electric power system (EPS) is presented in this paper. The developed algorithm involves two stages which are based on the weighted least square (WLS) technique. The first stage uses conventional measurements (delivered by RTU — SCADA meters) and synchronized phasor measurements (delivered by PMU meters) in order to estimate the state of the system forming an...
A two stage state estimator (SE) of an Electric Power System (EPS) is presented in this paper. It combines SCADA (Supervisory Control and Data Acquisition) and PMU (Phasor Measurement Unit) measurements. This feature gives it more accuracy on estimation over conventional algorithms based on SCADA measurements and also the possibility to obtain dynamic information of the system behavior. In the first...
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