IP Library Granted Patent US 12,597,082
Granted Patent B2
US 12,597,082 · App. 18/337,026 · Granted Apr 7, 2026

Intelligent orchestration systems for energy and power management based on monitoring local conditions

Inventors: Charles H. Cella (Pembroke, MA); Andrew Cardno (San Diego, CA)
Assignee: Strong Force EE Portfolio 2022, LLC
G05B19/042G01R21/133G05B13/0265G05B13/04G05B13/042G06F1/26G06N3/08G06N5/043G06N10/00G06N20/00G06Q10/067G06Q30/018G06Q50/02G06Q50/26H02J3/003H02J3/004H02J3/144H02J3/32H02J3/381H02J13/00001H02J13/00002H04L41/0833H04L41/145H04L41/16G05B2219/2639G06F30/27G06Q50/06G06Q2220/00H02J2203/10H02J2203/20H02J2300/40
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Quick Facts
Patent No.
US 12,597,082
App. No.
18/337,026
Granted
Apr 7, 2026
Kind
B2
Abstract

Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, an artificial intelligence system us configured to analyze a data set of monitored local conditions and generate a recommended configuration of at least one distributed system of a set of distributed systems, each distributed system of the set of distributed systems being configurable both to produce energy and to consume energy, wherein the configuration causes the at least one distributed system to produce and/or consume energy based on the monitored local conditions. In some embodiments, the artificial intelligence system configures a plurality of the distributed systems in the set such that a set of aggregate performance requirements are satisfied across the plurality. In some embodiments, the aggregate performance requirements are a set of economic performance requirements and/or a set of regulatory performance requirements.

Claims (142)

1 . An artificial-intelligence-based (AI-based) platform for enabling intelligent orchestration and management of power and energy, the AI-based platform comprising:

an artificial intelligence system that analyzes a data set of monitored local conditions to generate a recommended configuration of a set of distributed systems based on at least one energy-related output of an adaptive energy digital twin that represents a subset of the set of distributed systems, wherein:

each distributed system of the set of distributed systems produces energy and consumes energy,

the recommended configuration causes the set of distributed systems to at least one of produce or consume energy based on the data set of monitored local conditions,

the set of distributed systems is connected with a power grid and at least one of a set of systems, a set of equipment, or a set of facilities,

the set of distributed systems augments the power grid to improve reliability associated with operating the at least one of the set of systems, the set of equipment, or the set of facilities,

the artificial intelligence system configures a plurality of distributed systems of the set of distributed systems to satisfy a set of aggregate performance requirements, and

the set of aggregate performance requirements relates to at least one of carbon generation or emissions.

2 . The AI-based platform of claim 1 , wherein the set of aggregate performance requirements includes a set of economic performance requirements.

3 . The AI-based platform of claim 1 , wherein the set of aggregate performance requirements includes a set of regulatory performance requirements.

4 . The AI-based platform of claim 1 , wherein the set of aggregate performance requirements includes a set of consumption requirements.

5 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system adapts a transport of data over at least one of a network or a communication system; and

the adapting is based on at least one of:

a congestion condition,

a delay condition,

a latency condition,

a packet loss condition,

an error rate condition,

a cost of transport condition,

a quality-of-service (QoS) condition,

a usage condition,

a market factor condition, or

a user configuration condition.

6 . The AI-based platform of claim 1 , wherein the adaptive energy digital twin represents at least one of:

an energy stakeholder entity,

an energy distribution resource,

a stakeholder information technology,

a networking infrastructure entity,

an energy-dependent stakeholder production facility,

a stakeholder transportation system,

a market condition, or

an energy usage priority condition.

7 . The AI-based platform of claim 1 , wherein the adaptive energy digital twin performs at least one of:

providing at least one of a visual or analytic indicator of energy consumption by at least one energy consumer,

filtering energy data,

highlighting energy data, or

adjusting energy data.

8 . The AI-based platform of claim 1 , wherein the adaptive energy digital twin generates at least one of a visual or an analytic indicator of energy consumption by at least one of:

the set of systems,

the set of equipment,

the set of facilities, or

a set of vehicles in a vehicle fleet.

9 . The AI-based platform of claim 1 , wherein the artificial intelligence system performs at least one of:

extracting energy-related data,

detecting errors in energy-related data,

correcting errors in the energy-related data,

transforming the energy-related data,

converting the energy-related data,

normalizing the energy-related data,

cleansing the energy-related data,

parsing the energy-related data,

detecting patterns in the energy-related data,

detecting content in the energy-related data,

detecting objects in the energy-related data,

compressing the energy-related data,

streaming the energy-related data,

filtering the energy-related data,

loading the energy-related data,

storing the energy-related data,

routing the energy-related data,

transporting the energy-related data, or

maintaining security of the energy-related data.

10 . The AI-based platform of claim 1 , wherein:

the data set of monitored local conditions is based on at least one public data resource; and

the public data resource includes at least one of:

a weather data resource,

a satellite data resource,

a census data resource,

a population data resource,

a demographic data resource,

a psychographic data resource,

a market data resource, or

an ecommerce data resource.

11 . The AI-based platform of claim 1 , wherein:

the data set of monitored local conditions is based on an enterprise data resource; and

the enterprise data resource includes at least one of:

resource planning data,

sales data,

marketing data,

financial planning data,

demand planning data,

supply chain data,

procurement data,

pricing data,

customer data,

product data, or

operating data.

12 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system orchestrates delivery of energy to at least one point of consumption; and

the delivery of the energy includes at least one:

at least one fixed transmission line,

at least one instance of wireless energy transmission,

at least one delivery of fuel, or

at least one delivery of stored energy.

13 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system records, in at least one of a distributed ledger or a blockchain, at least one energy-related event; and

the at least one energy-related event includes at least one of:

an energy purchase event,

a sale event,

a service charge associated with an energy purchase,

a service charge associated with a sale event,

an energy consumption event,

an energy generation event,

an energy distribution event,

an energy storage event,

a carbon emission production event,

a carbon emission abatement event,

a renewable energy credit event,

a pollution production event, or

a pollution abatement event.

14 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system is deployed in an off-grid environment; and

the off-grid environment includes at least one of:

an off-grid energy generation system,

an off-grid energy storage system, or

an off-grid energy mobilization system.

15 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system is trained based on a training data set; and

the training data set is based on at least one of:

at least one human tag,

at least one human label,

at least one human interaction with a hardware system,

at least one human interaction with a software system,

at least one outcome,

at least one AI-generated training data sample,

a supervised learning training process,

a semi-supervised learning training process, or

a deep learning training process.

16 . The AI-based platform of claim 1 , wherein the artificial intelligence system is located in proximity to at least one entity that at least one of generates, stores, delivers, or uses energy.

17 . The AI-based platform of claim 1 , wherein the artificial intelligence system provides information about at least one of an energy state or an energy flow of at least one entity that at least one of generates, stores, delivers, or uses energy.

18 . The AI-based platform of claim 1 , wherein:

the artificial intelligence system governs at least one sensor of a set of sensors; and

the set of sensors is associated with a set of infrastructure assets that at least one of generates, stores, delivers, or uses energy.

19 . A method for enabling intelligent orchestration and management of power and energy, comprising:

analyzing, by an artificial intelligence system, a data set of monitored local conditions to generate a recommended configuration of a set of distributed systems based on at least one energy-related output of an adaptive energy digital twin that represents a subset of the set of distributed systems, wherein:

each distributed system of the set of distributed systems produces energy and consumes energy,

the recommended configuration causes the set of distributed systems to at least one of produce or consume energy based on the data set of monitored local conditions,

the set of distributed systems is connected with a power grid and at least one of a set of systems, a set of equipment, or a set of facilities, and

the set of distributed systems augments the power grid to improve reliability associated with operating the at least one of the set of systems, the set of equipment, or the set of facilities; and

configuring, by the artificial intelligence system, a plurality of distributed systems of the set of distributed systems to satisfy a set of aggregate performance requirements, wherein the set of aggregate performance requirements relates to at least one of carbon generation or emissions.

20 . The method of claim 19 , wherein the artificial intelligence system is located in proximity to at least one entity that at least one of generates, stores, delivers, or uses energy.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 13, 2023
From: CELLA, CHARLES H.; CARDNO, ANDREW
To: STRONG FORCE EE PORTFOLIO 2022, LLC
Reel/Frame 064248/0075 →
Continuity (8)
Continuation PCTUS2022050924 · Nov 23, 2022
Continuation PCTUS2022050932 · Nov 23, 2022
Provisional Application 63375225 · Sep 10, 2022
Provisional Application 63302016 · Jan 21, 2022
Provisional Application 63299727 · Jan 14, 2022
Provisional Application 63291311 · Dec 17, 2021
Provisional Application 63282510 · Nov 23, 2021
Related Publication 20230335997A1 · Oct 19, 2023
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