SYSTEMS AND METHODS FOR AUTOMATIC REAL-TIME CAPACITY ASSESSMENT FOR USE IN REAL-TIME POWER ANALYTICS OF AN ELECTRICAL POWER DISTRIBUTION SYSTEM
First Claim
1. A system for conducting a real-time power capacity assessment of an electrical system, comprising:
- a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system;
a power analytics server communicatively connected to the data acquisition component, comprising, a virtual system modeling engine configured to generate predicted data output for the electrical system utilizing a virtual system model of the electrical system, an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, the analytics engine further configured to initiate a calibration and synchronization operation to update the virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold, and a machine learning engine configured to store and process patterns observed from the real-time data output and the predicted data output, the machine learning engine further configured to forecast power capacity of the electrical system subjected to a contingency event; and
a client terminal communicatively connected to the power analytics server, the client terminal configured to allow for the selection of the contingency event and display a report of the forecasted power capacity.
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Abstract
A system for conducting a real-time power capacity assessment of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The power analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine. The machine learning engine is configured to store and process patterns observed from the real-time data output and the predicted data output, forecasting power capacity of the electrical system subjected to a simulated contingency event.
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Citations
25 Claims
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1. A system for conducting a real-time power capacity assessment of an electrical system, comprising:
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a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system;
a power analytics server communicatively connected to the data acquisition component, comprising, a virtual system modeling engine configured to generate predicted data output for the electrical system utilizing a virtual system model of the electrical system, an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, the analytics engine further configured to initiate a calibration and synchronization operation to update the virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold, and a machine learning engine configured to store and process patterns observed from the real-time data output and the predicted data output, the machine learning engine further configured to forecast power capacity of the electrical system subjected to a contingency event; and
a client terminal communicatively connected to the power analytics server, the client terminal configured to allow for the selection of the contingency event and display a report of the forecasted power capacity. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method for conducting real-time power capacity assessment of an electrical system subjected to a contingency event, comprising:
updating a virtual system model of the electrical system in response to real-time data, wherein the virtual system model includes voltage stability model data for components comprising the electrical system;
choosing a contingency event to simulate;
determining power capacity of the electrical system by running an analysis of the updated virtual system model operating under conditions simulating the contingency event chosen; and
generating a report that forecasts the power capacity of the electrical system. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
Specification