AI-based energy edge platform, systems, and methods having a digital twin of a mining environment
An AI-based platform for enabling intelligent orchestration and management of power and energy is disclosed. The platform includes a digital twin system having a digital twin of a mining environment. The digital twin includes at least one parameter that is detected by a sensor of the mining environment. In some disclosed embodiments, the at least one parameter is associated with one or more of an unmined portion of the mining environment a mining of materials from the mining environment, a smart container event involving a smart container associated with the mining environment, a physiological status of a miner associated with the mining environment, a transaction-related event associated with the mining environment, and a compliance of the mining environment with one or more contractual, regulatory, and/or legal policies.
1. An artificial-intelligence-based (AI-based) platform for enabling intelligent orchestration and management of power and energy, the AI-based platform comprising:
a digital twin system having a digital twin of a mining environment, wherein:
the digital twin includes a set of parameters that is detected by a set of sensors of the mining environment,
an initial parameter of the set of parameters indicates a baseline condition of the mining environment at a previous time,
a real-time parameter of the set of parameters indicates an update of the baseline condition of the mining environment at a current time,
the digital twin is configured to generate an indicator of energy consumption of the mining environment,
the indicator is at least one of analytic or configured for visual display, and
the digital twin is configured to adjust the indicator based on the real-time parameter detected by a sensor of the set of sensors of the mining environment;
a sensing system including at least one of,
ground-penetrating sensing of unmined portions of the mining environment,
mass spectrometry of mined materials, or
computer-vision-based sensing of mined materials;
a system for asset tagging of smart containers associated with the mining environment;
a set of wearable devices for detecting physiological status of miners associated with the mining environment;
a system for secure recording and resolution of transactions and transaction-related events associated with the mining environment; and
an automated system for recording, reporting, and assessing compliance with at least one of contractual policies, regulatory policies, or legal policies.
2. The AI-based platform of claim 1 , wherein a subset of the set of parameters is associated with at least one of:
a smart container event involving at least one of the smart containers,
a physiological status of at least one of the miners,
at least one of the transaction-related events, or
a compliance of the mining environment with the at least one of contractual policies, regulatory policies, or legal policies.
3. The AI-based platform of claim 1 , wherein the digital twin system additionally represents at least one of:
an energy distribution resource,
an energy-dependent stakeholder production facility,
a stakeholder transportation system,
a market condition, or
an energy usage priority condition.
4. The AI-based platform of claim 1 , wherein the digital twin system is further configured to perform at least one of:
providing an indicator of energy consumption by at least one energy consumer,
filtering energy data,
highlighting the energy data, or
adjusting the energy data.
5. The AI-based platform of claim 1 , wherein the digital twin system is further configured to generate an indicator of energy consumption by at least one of:
a set of machines,
a set of factories, or
a set of vehicles in a vehicle fleet.
6. The AI-based platform of claim 1 , wherein:
at least one parameter of the set of parameters is based on at least one public data resource; and
the at least one 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.
7. The AI-based platform of claim 1 , wherein:
at least one parameter of the set of parameters is based on at least one enterprise data resource; and
the at least one 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, or
product data.
8. The AI-based platform of claim 1 , wherein:
the digital twin system includes at least one AI-based model or algorithm,
the at least one AI-based model or algorithm is trained based on a training data set, and
the training data set is based on at least one of:
a set of human tags,
a set of human labels,
a set of human interactions with a hardware system,
a set of human interactions with a software system,
a set of outcomes,
a set of AI-generated training data samples,
a supervised learning training process,
a semi-supervised learning training process, or
a deep learning training process.
9. The AI-based platform of claim 1 , wherein:
the digital twin system is further configured to orchestrate delivery of energy to at least one point of consumption, and
the delivery of the energy includes at least one of:
a set of fixed transmission lines,
a set of instances of wireless energy transmission,
a set of deliveries of fuel, or
a set of deliveries of stored energy.
10. The AI-based platform of claim 1 , wherein;
the digital twin system is further configured to record, in at least one of a distributed ledger or a blockchain, an energy-related event; and
the energy-related event includes at least one of:
an energy purchase event,
an energy sale event,
a service charge associated with an energy purchase event,
a service charge associated with an energy sale 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.
11. The AI-based platform of claim 1 , wherein:
the digital twin 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.
12. The AI-based platform of claim 1 , further comprising:
mine-level Internet of Things (IOT) sensing of the mining environment; and
smart contracts for automatically allocating proceeds derived from the mining environment.
13. The AI-based platform of claim 1 , further comprising:
a set of carbon-aware energy edge solutions,
wherein the set of carbon-aware energy edge solutions performs exploring, configuring, and implementing a set of policies regarding carbon generation.
14. The AI-based platform of claim 13 , wherein the set of carbon-aware energy edge solutions requires energy production by a mining environment to be monitored to track carbon emissions generated by the mining environment.
15. The AI-based platform of claim 13 , wherein the set of carbon-aware energy edge solutions requires energy production by a mining environment to require offsetting carbon generation by the mining environment.
16. The AI-based platform of claim 1 , further comprising:
a user interface; and
a set of automated energy policy deployment solutions,
wherein the set of automated energy policy deployment solutions is configurable via user interaction with the user interface.
17. The AI-based platform of claim 1 , further comprising:
an intelligent agent trained to generate policies related to governance of the mining environment,
wherein the intelligent agent is trained on at least one of a training set of historical data, feedback from a set of outcomes, or a set of human policy-setting interactions.
18. The AI-based platform of claim 1 , wherein the AI-based platform facilitates governance of the mining environment by implementing policies including at least one of:
setting maximum energy usage for an entity for a time period,
setting maximum energy cost for an entity for a time period,
setting maximum carbon production for an entity for a time period,
setting maximum pollution emissions for an entity for a time period,
setting a set of carbon offset requirements,
setting a set of renewable energy credit requirements,
setting a set of energy mix requirements,
setting a set of profit margin minimums based on energy and other marginal costs for a production entity, or
setting minimum storage baselines for a set of energy storage entities.
19. A method for enabling artificial-intelligence-based (AI-based) intelligent orchestration and management of power and energy in a mining environment, the method comprising:
maintaining a digital twin of the mining environment, wherein:
the digital twin includes a set of parameters that is detected by a set of sensors of the mining environment,
an initial parameter of the set of parameters indicates a baseline condition of the mining environment at a previous time, and
a real-time parameter of the set of parameters indicates an update of the baseline condition of the mining environment at a current time;
generating, using the digital twin, an indicator of energy consumption of the mining environment, wherein the indicator is at least one of analytic or configured for visual display;
adjusting, using the digital twin, the indicator based on the real-time parameter detected by a sensor of the set of sensors of the mining environment;
performing sensing, including at least one of,
ground-penetrating sensing of unmined portions of the mining environment,
sensing mined materials using mass spectrometry, or
sensing mined materials using computer vision;
asset tagging smart containers associated with the mining environment;
gathering physiological status of miners associated with the mining environment from a set of wearable devices;
securely recording and resolving transactions and transaction-related events associated with the mining environment; and
using an automated system, recording, reporting, and assessing compliance with at least one of contractual policies, regulatory policies, or legal policies.
20. The method of claim 19 , further comprising:
training an intelligent agent on at least one of (i) a training set of historical data, (ii) feedback from a set of outcomes, or (iii) a set of human policy-setting interactions; and
using the intelligent agent, generating policies related to governance of the mining environment.