{
  "$type": "site.standard.document",
  "description": "The present disclosure relates to a system (100) and a method (300) for predicting failure in a power system (102) in real-time. The method comprises obtaining, by a processing unit (204), state estimation data corresponding to electrical quantities of the power system (102) received from one or…",
  "path": "/patents/1405761",
  "publishedAt": "2023-10-11T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G05B23/0283",
    "SIEMENS AG [DE]"
  ],
  "textContent": "The present disclosure relates to a system (100) and a method (300) for predicting failure in a power system (102) in real-time. The method comprises obtaining, by a processing unit (204), state estimation data corresponding to electrical quantities of the power system (102) received from one or more sources in real-time, extracting a feature vector from the received state estimation data based on contingency analysis information using a trained machine learning model, wherein the feature vector corresponds to one or more parameters pertaining to the power system (102) 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 (102) based on the determined security index.",
  "title": "SYSTEM AND METHOD FOR PREDICTING FAILURE IN A POWER SYSTEM IN REAL-TIME"
}