Automatic detection of grid-connected distributed energy resources

Patent metadata

Field	Value
Publication number	US-2024388100-A1
Application number	US-202318197574-A
Country	US
Kind code	A1
Filing date	May 15, 2023
Priority date	May 15, 2023
Publication date	Nov 21, 2024
Grant date	—

Abstract

Methods, systems, and apparatus, including computer programs encoded on a storage device, for determining whether a distributed energy resource is connected at a location. Electrical load data is obtained for a location over a time period. The electrical load data is analyzed to determine one or more signals from the electrical load data. The signals are compared to one or more load profiles for the location. Each load profile can indicate one or more baseline electrical patterns for the location. A likelihood that at least one distributed energy resource is in use at the location is determined based on the comparison. In response to determining that the likelihood is more than a threshold, one or more actions are performed.

First claim

What is claimed is:

1 . A computer-implemented method for determining whether a distributed energy resource is connected at a location, comprising:
obtaining electrical load data for a location over a time period; analyzing the electrical load data to determine at least one signal from the electrical load data; comparing the at least one signal to at least one load profile for the location, wherein each load profile indicates one or more baseline electrical patterns for the location; determining a likelihood that at least one distributed energy resource is in use at the location based on the comparison; and in response to determining that the likelihood is more than a threshold, performing one or more actions.

2 . The method of claim 1 , wherein the location corresponds to a single address served by a component of an electrical grid.

3 . The method of claim 1 , wherein the location corresponds to multiple addresses served by a component of an electrical grid.

4 . The method of claim 1 , wherein the at least one signal comprises electrical load per time of day at the location, electrical load per day of week at the location, or electrical load given particular weather patterns at the location.

5 . The method of claim 1 , wherein the load profile is a historical load profile for the location.

6 . The method of claim 1 , wherein the load profile for the location comprises an expected load profile determined based on an assumption of one or more context parameters for the load data for the location.

7 . The method of claim 6 , wherein the expected load profile is determined based on an assumption of no distributed energy resources being connected at the location.

8 . The method of claim 6 , wherein the expected load profile is determined based on an assumption of a certain number or certain capacity of distributed energy resources being connected at the location.

9 . The method of claim 6 , wherein the expected load profile reflects expected load for the location assuming one or more of certain weather conditions, a given time of day, a given day of week, a given time of year.

10 . The method of claim 9 , wherein the certain weather conditions comprise one or more of a given amount of sun exposure, a given temperature, or given wind conditions.

11 . The method of claim 6 , wherein comparing the at least one signal to a load profile for the location comprises:
identifying a first load profile that has context parameters that match context parameters associated with the obtained electrical load data for the location; and comparing the first load profile to the at least one signal.

12 . The method of claim 1 , wherein distributed energy resources comprise one or more of solar panels, community wind farms, stationary batteries, vehicle batteries, or vehicle-to-grid systems.

13 . The method of claim 1 , further comprising:
obtaining image data for the location; analyzing the image data for the location; and adjusting the likelihood that at least one distributed energy resource is in use at the location based on analyzing the image data for the location.

14 . 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 electrical load data for a location over a time period; analyzing the electrical load data to determine at least one signal from the electrical load data; comparing the at least one signal to at least one load profile for the location, wherein each load profile indicates one or more baseline electrical patterns for the location; determining a likelihood that at least one distributed energy resource is in use at the location based on the comparison; and in response to determining that the likelihood is more than a threshold, performing one or more actions.

15 . The system of claim 14 , wherein the location corresponds to a single address served by a component of an electrical grid.

16 . The system of claim 14 , wherein the location corresponds to multiple addresses served by a component of an electrical grid.

17 . The system of claim 14 , wherein the at least one signal comprises electrical load per time of day at the location, electrical load per day of week at the location, or electrical load given particular weather patterns at the location.

18 . 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 electrical load data for a location over a time period; analyzing the electrical load data to determine at least one signal from the electrical load data; comparing the at least one signal to at least one load profile for the location, wherein each load profile indicates one or more baseline electrical patterns for the location; determining a likelihood that at least one distributed energy resource is in use at the location based on the comparison; and in response to determining that the likelihood is more than a threshold, performing one or more actions.

19 . The computer storage medium of claim 18 , wherein the location corresponds to a single address served by a component of an electrical grid.

20 . The computer storage medium of claim 18 , wherein the location corresponds to multiple addresses served by a component of an electrical grid.

Assignees

• X Dev Llc

Inventors

• Wong Sze Mei Cat
• Casey Leo Francis

Classifications

• H02J2103/35

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

• H02J2101/28

  Wind energy · CPC title

• H02J2101/22

  Solar energy · CPC title

• H02J2101/24

  Photovoltaics · CPC title

• H02J3/003

  Load forecast, e.g. methods or systems for forecasting future load demand · CPC title