Electric grid connection mapping

Patent metadata

Field	Value
Publication number	US-2022375219-A1
Application number	US-202217740873-A
Country	US
Kind code	A1
Filing date	May 10, 2022
Priority date	May 19, 2021
Publication date	Nov 24, 2022
Grant date	—

Abstract

Methods, systems, and apparatus, including computer programs encoded on a storage device, for predicting connections in electric grid models are disclosed. A method includes obtaining geospatial data representing a geographic area that includes an electrical distribution system; and generating, from the geospatial data, asset data that represents characteristics of electrical distribution system assets. The asset data includes: load data representing electrical loads of the electrical distribution system; and node data representing nodes of the electrical distribution system. The method includes processing the asset data using a connection model that is configured to predict electrical connections between assets of the electrical distribution system; and obtaining, from the connection model; output data indicating predicted electrical connections between assets of the electrical distribution system. The geospatial data includes at least one of overhead imagery or street level imagery of the geographic area.

First claim

What is claimed is:

1 . A method comprising:
obtaining geospatial data representing a geographic area that includes an electrical distribution system; generating, from the geospatial data, asset data that represents characteristics of electrical distribution system assets, the asset data including:
load data that represents electrical loads of the electrical distribution system; and
node data that represents nodes of the electrical distribution system;
processing the asset data using a connection model configured to predict electrical connections between assets of the electrical distribution system; and obtaining, from the connection model, output data indicating predicted electrical connections between assets of the electrical distribution system.

2 . The method of claim 1 , wherein:
the geospatial data includes imagery of the geographic area; and the asset data represents characteristics of electrical distribution system assets that are visible in the imagery of the geographic area.

3 . The method of claim 2 , wherein the output data indicates predicted electrical connections that are not visible in the imagery of the geographic area.

4 . The method of claim 1 , comprising:
generating, from the geospatial data, above-ground connection data representing above-ground connections between assets of the electrical distribution system; and processing the above-ground connection data and the asset data using the connection model, wherein the output data comprises data indicating predicted underground connections between the assets of the electrical distribution system.

5 . The method of claim 1 , wherein the geospatial data includes overhead imagery of the geographic area.

6 . The method of claim 5 , comprising identifying electrical distribution system assets in the overhead imagery of the geographic area using image analysis.

7 . The method of claim 1 , wherein the geospatial data includes street level imagery of the geographic area.

8 . The method of claim 7 , comprising identifying electrical distribution system assets in the street level imagery of the geographic area using image analysis.

9 . The method of claim 1 , wherein the load data includes at least one of a location of an electrical load, a type of the electrical load, or a size of the electrical load.

10 . The method of claim 1 , wherein the node data includes at least one of a location of a node, an elevation of the node, a type of the node, or an electrical rating of the node.

11 . The method of claim 1 , wherein the output data includes at least one of vector data or raster data.

12 . The method of claim 1 , wherein the connection model comprises a convolutional neural network model.

13 . The method of claim 1 , wherein processing the asset data using a connection model comprises determining, for each electrical load, a predicted connected node.

14 . The method of claim 1 , wherein processing the asset data using a connection model comprises determining, for each electrical load, a connection path between the electrical load and a connected node.

15 . The method of claim 1 , comprising:
providing, to the connection model, auxiliary data; and processing the asset data and the auxiliary data using the connection model.

16 . The method of claim 15 , wherein the auxiliary data includes at least one of geographic information system data, aerial imagery, street level imagery, property boundaries, transportation routes, or topological features within the geographic area.

17 . The method of claim 15 , wherein the auxiliary data includes at least one of electric grid sensor data or historical power outage data within the geographic area.

18 . The method of claim 1 , wherein the connection model is trained to predict electrical connections between assets of the electrical distribution system.

19 . A system comprising one or more computers and one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
obtaining geospatial data representing a geographic area that includes an electrical distribution system; generating, from the geospatial data, asset data that represents characteristics of electrical distribution system assets, the asset data including:
load data that represents electrical loads of the electrical distribution system; and
node data that represents nodes of the electrical distribution system;
processing the asset data using a connection model configured to predict electrical connections between assets of the electrical distribution system; and obtaining, from the connection model, output data indicating predicted electrical connections between assets of the electrical distribution system.

20 . A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:
obtaining geospatial data representing a geographic area that includes an electrical distribution system; generating, from the geospatial data, asset data that represents characteristics of electrical distribution system assets, the asset data including:
load data that represents electrical loads of the electrical distribution system; and
node data that represents nodes of the electrical distribution system;
processing the asset data using a connection model configured to predict electrical connections between assets of the electrical distribution system; and obtaining, from the connection model, output data indicating predicted electrical connections between assets of the electrical distribution system.

Assignees

• X Dev Llc

Inventors

• Gupta Ananya
• Evans Peter
• Casey Leo Francis
• Stahlfeld Phillip Ellsworth

Classifications

• H02J2103/30

  Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks · CPC title

• H02J2103/35

  Grid-level management of power transmission or distribution systems, e.g. load flow analysis or active network management · CPC title

• G06Q50/06

  Energy or water supply · CPC title

• G06V20/182 Primary

  Network patterns, e.g. roads or rivers · CPC title

• H02J3/0012 Primary

  characterised by the contingency detection means in AC networks, e.g. using phasor measurement units [PMU], synchrophasors or contingency analysis · CPC title