US-12619205-B1 - Systems and methods for automatically determining indexes for evaluating an electric power grid

US12619205B1US 12619205 B1US12619205 B1US 12619205B1US-12619205-B1

Abstract

A method for automatically determining a composite index for evaluating an electric power grid includes (a) receiving a time series of sensor measurements from one or more sensors within an area served by the electric power grid, (b) generating, from the time series of sensor measurements, a plurality of indexes for evaluating the electric power grid, and (c) generating the composite index based on the plurality of indexes for evaluating the electric power grid.

Inventors

Scott H. Clearwater
SCOTT L. CARUSO

Assignees

CABLE TELEVISION LABORATORIES, INC.

Dates

Publication Date: 20260505
Application Date: 20220712

Claims (20)

1 . A method for automatically determining a composite index for evaluating an electric power grid, the method comprising: at each communication node of a plurality of communication nodes, generating a respective time series of sensor measurements for the communication node at least partially using a respective power supply of the communication node, each sensor measurement representing one or more parameters of the electric power grid at a location of the respective communication node generating the sensor measurement; receiving the time series of sensor measurements from the plurality of communication nodes at least partially via one or more communication networks incorporating the plurality of communication nodes; generating, from the time series of sensor measurements, a plurality of indexes for evaluating the electric power grid, the plurality of indexes for evaluating the electric power grid including an outage index, a reliability index, a stability index, and a quality index; and generating the composite index based on the plurality of indexes for evaluating the electric power grid at least partially by generating the composite index as a function of an average of the outage index, the reliability index, the stability index, and the quality index.
2 . The method of claim 1 , wherein generating the plurality of indexes for evaluating the electric power grid comprises generating the plurality of indexes with respect to one or more reference values.
3 . The method of claim 2 , wherein each reference value is a statistical metric of the power supply of a respective one of the plurality communication nodes.
4 . The method of claim 1 , wherein the time series of sensor measurements comprises a time series of voltages measured by the respective power supplies of the plurality of communication nodes.
5 . The method of claim 1 , wherein the plurality of indexes for evaluating the electric power grid further include one or more of an omega index and a risk-reward index.
6 . The method of claim 5 , wherein the omega index is based on a ratio of cumulative probability distributions of the time series of sensor measurements.
7 . The method of claim 5 , wherein the risk-reward index includes first and second components, the first and second components being based on different respective functions of a Normal cumulative distribution function.
8 . The method of claim 1 , wherein the outage index is based on an outage time divided by a time period being sampled.
9 . The method of claim 1 , wherein the reliability index is based on a product of two Beta probability distributions.
10 . The method of claim 1 , wherein the stability index is based on one or more standard deviations of the time series of sensor measurements.
11 . The method of claim 1 , wherein the quality index is based on a sum of two hazard functions.
12 . The method of claim 1 , wherein: the outage index is based on an outage time divided by a time period being sampled; the reliability index is based on a product of two Beta probability distributions; the stability index is based on one or more standard deviations of the time series of sensor measurements; and the quality index is based on a sum of two hazard functions.
13 . The method of claim 1 , wherein each sensor measurement represents one or more parameters of the electric power grid at the location of the respective communication node generating the sensor measurement at least partially by specifying an operating state of an inverter of the respective communication node generating the sensor measurement.
14 . The method of claim 1 , wherein each sensor measurement further represents an operating state of an inverter of the respective communication node generating the sensor measurement.
15 . A method for automatically determining an omega index for evaluating an electric power grid, the method comprising: at each communication node of a plurality of communication nodes, generating a respective time series of voltage measurements for the communication node at least partially using a respective power supply of the communication node, each voltage measurement representing voltage of the electric power grid at a location of the respective communication node generating the voltage measurement; receiving the time series of voltage measurements from the plurality of communication nodes at least partially via one or more communication networks incorporating the plurality of communication nodes; generating, from the time series of voltage measurements, a first omega function associated with undervoltage of the electric power grid; generating, from the time series of voltage measurements, a second omega function associated with overvoltage of the electric power grid; and generating the omega index at least partially from a product of the first omega function and the second omega function.
16 . The method of claim 15 , wherein the first omega function comprises a ratio of (a) an integral of one minus a cumulative distribution function over (b) one plus an integral of the cumulative distribution function.
17 . The method of claim 15 , wherein the second omega function comprises a ratio of (a) an integral of one minus a cumulative distribution function over (b) an integral of the cumulative distribution function.
18 . A method for automatically determining a risk-reward index for evaluating an electric power grid, the method comprising: at each communication node of a plurality of communication nodes, generating a respective time series of voltage measurements for the communication node at least partially using a respective power supply of the communication node, each voltage measurement representing voltage of the electric power grid at a location of the respective communication node generating the voltage measurement; receiving the time series of voltage measurements from the plurality of communication nodes at least partially via one or more communication networks incorporating the plurality of communication nodes; generating, from the time series of voltage measurements, a first component of the risk-reward index using a first function of a Normal cumulative distribution function; and generating, from the time series of voltage measurements, a second component of the risk-reward index using a second function of a Normal cumulative distribution function.
19 . The method of claim 18 , wherein each of the first function of a Normal cumulative distribution function and the second function of a Normal cumulative distribution function is a function of a standard deviation of the time series of voltage measurements.
20 . The method of claim 18 , wherein each of the first function of a Normal cumulative distribution function and the second function of a Normal cumulative distribution function is a function of a lookback time.

Description

RELATED APPLICATIONS This application is a continuation in part of U.S. patent application Ser. No. 17/452,543, filed on Oct. 27, 2021, which claims benefit of priority to (a) U.S. Provisional Patent Application Ser. No. 63/106,052, filed on Oct. 27, 2020, (b) U.S. Provisional Patent Application Ser. No. 63/164,330, filed on Mar. 22, 2021, and (c) U.S. Provisional Patent Application Ser. No. 63/220,618, filed on Jul. 12, 2021. This application also claims benefit of priority to (a) U.S. Provisional Patent Application Ser. No. 63/220,616, filed on Jul. 12, 2021, (b) U.S. Provisional Patent Application Ser. No. 63/220,614, filed on Jul. 12, 2021, and (c) U.S. Provisional Patent Application Ser. No. 63/350,787, filed on Jun. 9, 2022. Each of the aforementioned patent applications is incorporated herein by reference. BACKGROUND An electric power grid may experience a power event, such as a power outage, an abnormal voltage, or an abnormal frequency. A power event may be caused, for example, by severe weather, equipment failure, equipment damage, or extreme load conditions. Many parties have an interest in being notified of a power event. For example, electric utilities want to be notified of power failures and other power events so that they can quickly address these issues. Additionally, electric utilities are interested in historical power events so that they can investigate these events and take steps to prevent their reoccurrence. Furthermore, public safety agencies have great interest in timely notification of power outages, as well as timely notification of power restoration, so that the agencies can quickly and accurately deploy resources to areas experiencing a power outage. Moreover, insurance companies have an interest in historical power events, such as when adjusting claims associated with past power outages. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of a power event notification system, according to an embodiment. FIG. 2 is an illustration of an electric power grid that is monitored by sensors that are incorporated in communication network nodes, according to an embodiment. FIG. 3 illustrates an example of data set assignment to a map of an electric power grid. FIG. 4 is a flow chart of a method for identifying occurrence of an electric power event in an electric power grid, according to an embodiment. FIG. 5 is a flow chart of a method for identifying an electric power event from a change in sensor operating state, according to an embodiment. FIG. 6 is a flow chart of a method for evaluating a correlation between a sensor's state change and an existing electric power event, according to an embodiment. FIG. 7 illustrates an example data structure corresponding to an electric power event, according to an embodiment. FIG. 8 illustrates a geographic information system map with electric power event notification information overlaid thereon, according to an embodiment. FIG. 9 is a block diagram of an alternate embodiment of the FIG. 1 power event notification system further including a reliability index subsystem, according to an embodiment. FIG. 10 is a block diagram of a power index generating system configured to automatically generate a plurality of indexes for evaluating an electric power grid, according to an embodiment. FIG. 11 illustrates a geographic information system map with electric power indexes overlaid thereon, according to an embodiment. FIG. 12 illustrates an example of a daily report generated by certain embodiments of the FIG. 10 power index generating system. DETAILED DESCRIPTION OF THE EMBODIMENTS Conventional power outage notification systems typically operate by “scraping,” i.e., collecting, information from electric utility web sites, to provide information on power outages. While these conventional systems are valuable, they have their shortcomings. For example, conventional power outage notification systems are only capable of providing a high-level overview of power outages, such as by indicating that a particular state or a particular county is experiencing a power outage. Consequently, these systems are incapable of providing detailed locations of power outages, which makes these systems of limited use in addressing power outages. For instance, a public safety agency generally cannot rely on a conventional power outage notification system to determine whether to deploy resources to address a power outage because the conventional system does not provide a sufficiently detailed location of the outage. Additionally, conventional power outage notification systems are generally incapable of providing real time notification of power outages (or real time notification of power restoration). Consequently, data from conventional systems may be significantly out-of-date, which further limits usefulness of the data. Furthermore, conventional power outage notification systems often cannot provide information on distribution-level power outages, due to lack of electric