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Method for predicting symmetric, automated, real-time ARC flash energy within a real-time monitoring system

  • US 9,886,535 B2
  • Filed: 04/04/2016
  • Issued: 02/06/2018
  • Est. Priority Date: 06/29/2007
  • Status: Active Grant
First Claim
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1. A system for making real-time predictions about an arc flash event on an electrical system, comprising:

  • a computer processor and at least one memory;

    an analytics server communicatively connected to a data acquisition component, wherein the analytics server comprises;

    a virtual system modeling engine configured to create a virtual system model reflecting current network topology of the electrical system, wherein the electrical system comprises at least one unobservable motor and at least one uninterrupted power supply (UPS);

    an analytics engine configured to monitor predicted output data from the virtual system model and real-time output data from the electrical system acquired by the data acquisition component and update the virtual system model when a difference between the real-time output data and the predicted output data exceeds a threshold;

    an arc flash simulation engine configured to forecast at least one aspect of an arc flash event based on the updated virtual system model, wherein the at least one UPS is transferred to a by-pass position in the virtual system model and wherein the arc flash simulation engine is configured to calculate and compare arcing energy for each significant location in the virtual system model when the at least one unobservable motor in the virtual system model is set to an ON position, and calculate and comparing arcing energy for each significant location in the virtual system model when the at least one unobservable motor in the virtual system model is set to an OFF position, respectively, to determine a highest arcing energy for each significant location, wherein a virtual no load is generated and used as second critical input to determine the highest arcing energy for each significant location in the virtual system model; and

    a central analytics server configured to control an aspect of a monitored system, when its corresponding analytics server is out of operation, wherein the central analytics server is further configured to take over functionality of the analytics server and to modify operating parameters of one or more sensors that are interfaced with the monitored system.

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