US 12,259,722 B2
System and method for predicting failure in a power system in real-time
Bharadwaj Ranganathan Sathyanarayana, Karnataka (IN)
Assigned to Siemens Aktiengesellschaft, Munich (DE)
Filed by Bharadwaj Ranganathan Sathyanarayana, Karnataka (IN)
Filed on Mar. 25, 2022, as Appl. No. 17/704,349.
Claims priority of application No. 21165553 (EP), filed on Mar. 29, 2021.
Prior Publication US 2022/0308573 A1, Sep. 29, 2022
Int. Cl. G05B 23/02 (2006.01); G06N 20/00 (2019.01); G06Q 50/06 (2024.01)
CPC G05B 23/0283 (2013.01) [G06N 20/00 (2019.01); G06Q 50/06 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for predicting failure in a power system in real-time, the method comprising:
obtaining, by a processing unit, state estimation data corresponding to electrical quantities of the power system received from one or more sources in real-time;
obtaining contingency analysis information for a plurality of states of the power system from at least one analyzer over a period of time, wherein the contingency analysis information comprises a plurality of contingency analysis paths pertaining to failure status of each component of the power system, and wherein each contingency analysis path comprises cascaded state contingency information for each cascaded state;
extracting a feature vector from the received state estimation data based on the contingency analysis information using a trained machine learning model, wherein the feature vector corresponds to one or more parameters pertaining to the power system in real-time;
determining a security index for the received state estimation data based on the extracted feature vector using the trained machine learning model; and
predicting a failure of the power system based on the determined security index.