Operation loop formation for adaptive power grid management

Patent metadata

Field	Value
Publication number	US-12596341-B2
Application number	US-202318131770-A
Country	US
Kind code	B2
Filing date	Apr 6, 2023
Priority date	Apr 6, 2023
Publication date	Apr 7, 2026
Grant date	Apr 7, 2026

Abstract

A system for adaptive power grid management includes a formation construct module configured to receive a formation plan and a logistics list comprising a plurality of assets for executing an operation loop in the formation plan, retrieve a matching schema based on comparing the tasks of the operation loop and the logistics list with the plurality of meta objects in the historical meta object database, construct meta objects for plurality of assets based on the matching schema and the formation plan, and cause the plurality of the network of devices to execute the formation plan based on meta objects assigned to the plurality of assets of the network of devices.

First claim

What is claimed is:

1 . An adaptive power grid management system, the system comprises:
a historical meta object database storing a plurality of historical meta objects configured to cause an asset in a network of devices to execute a task; and a processor coupled to the historical meta object database and the network of devices, the processor being configured to execute a formation construct module which causes the processor to:
receive a formation plan and a logistics list comprising a plurality of assets for executing an operation loop in the formation plan;
for the operation loop, retrieve a matching schema based on comparing tasks of the operation loop and the logistics list with the plurality of meta objects in the historical meta object database;
construct meta objects for the plurality of assets based on the matching schema and the formation plan; and
cause the plurality of the network of devices to execute the formation plan based on meta objects assigned to the plurality of assets of the network of devices.

2 . The system of claim 1 , wherein the matching schema is identified based on the assigned task, a context of the formation plan, asset function, and/or asset attributes.

3 . The system of claim 1 wherein the processor is further configured to:
determine operation correlations of the plurality of assets based on the formation plan and the logistics list, wherein the matching schema is retrieved further based on an operation correlation associated with the asset.

4 . The system of claim 3 , wherein the operation correlations of assets are determined by using a learning engine that simulates the formation plan using asset data stored in an asset portfolio database and historical logistic files stored in a logistics file historical archive database.

5 . The system of claim 1 , wherein the processor is further configured to identify operation loops in the formation plan with two or more participating assets, wherein the matching schema is retrieved further based on roles of the assets in the operation loop.

6 . The system of claim 5 , wherein the two or more participating assets comprise a host asset of an operation loop of the formation plan and the meta objects identifies the host asset of the operation loop.

7 . The system of claim 1 , wherein the processor is further configured to:
determine a correlation and interdependency level of one or more assets in the operation loop; perform operational index analysis of the one or more assets and the matching schema in relation to a host asset of the operation loop based on the correlation and interdependency level; and determine a logistic gap file based on the operational index analysis.

8 . The system of claim 7 , wherein the processor is further configured to:
validate the operation loop of the formation plan based on logistic gap files associated with participating assets of the operation loop.

9 . The system of claim 7 , wherein the operational index analysis verifies operational indexes comprising observability, reachability, adaptability, controllability, security, sustainability, and stability indexes.

10 . The system of claim 1 , wherein the processor is further configured to:
validate meta objects associated with assets in the logistics list based on tasks in the formation plan prior to causing the execution of the formation plan by the network of devices.

11 . A method for adaptive power grid management comprising:
storing a plurality of historical meta objects in a historical meta object database, where each meta object is configured to cause an asset in a network of devices to execute a task; receiving, at a processor executing a formation construct module, a formation plan and a logistics list comprising a plurality of assets for executing an operation loop in the formation plan; for the operation loop, retrieving a matching schema based on comparing tasks of the operation loop and the logistics list with the plurality of meta objects in the historical meta object database; constructing meta objects for the plurality of assets based on the matching schema and the formation plan; and causing the plurality of the network of devices to execute the formation plan based on meta objects assigned to the plurality of assets of the network of devices.

12 . The method of claim 11 , wherein the matching schema is identified based on the assigned task, a context of the formation plan, asset function, and/or asset attributes.

13 . The method of claim 11 , further comprising:
determining operation correlations of assets based on the formation plan and the logistics list; and retrieving the matching schema based on the operation correlation associated with the asset.

14 . The method of claim 13 , wherein the operation correlations of the assets are determined by using a learning engine that simulates the formation plan using asset data stored in an asset portfolio database and historical logistic files stored in a logistics file historical archive database.

15 . The method of claim 11 , further comprising identifying operation loops in the formation plan with two or more participating assets and retrieving the matching schema based on a role of the asset in the operation loop.

16 . The method of claim 15 , wherein the two or more participating assets comprise a host asset of an operation loop of the formation plan, and the meta objects identify the host asset of the operation loop.

17 . The method of claim 11 , further comprising:
determining a correlation and interdependency level of the asset in the operation loop; performing operational index analysis of the asset and the matching schema in relation to a host asset of the operation loop based on the correlation and interdependency level; and determining a logistic gap file based on the operational index analysis.

18 . The method of claim 17 , further comprising validating the operation loop of the formation plan based on logistic gap files associated with participating assets of the operation loop.

19 . The method of claim 17 , wherein the operational index analysis verifies operational indexes comprising observability, reachability, adaptability, controllability, security, sustainability, and stability indexes.

20 . The method of claim 11 , further comprising validating meta objects associated with assets in the logistics list based on tasks in the formation plan prior to causing the execution of the formation plan by the network of devices.

Assignees

• Ge Vernova Infrastructure Tech Llc

Inventors

• Sharif-Askary Jamshid

Classifications

• G05B2219/2639

  Energy management, use maximum of cheap power, keep peak load low · CPC title

• G05B19/042 Primary

  using digital processors (G05B19/05 takes precedence) · CPC title