Governance engines for energy- and power-related facilities and systems
Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a set of edge devices is configured to communicate with at least one energy generation facility, energy storage facility, and/or energy consumption system and automatically execute a set of preconfigured policies that govern energy generation, energy storage, or energy consumption of the respective energy generation facilities, energy storage facilities, or energy consumption systems. In some embodiments, the automatically executed policies are a set of contextual policies that adjust based on the current status of a set of energy generation entities in an energy grid.
1 . An artificial intelligence-based (AI-based) platform for enabling intelligent orchestration and management of power and energy, the AI-based platform comprising:
a set of edge devices configured to,
communicate with an energy system associated with an energy use,
store a set of preconfigured policies, wherein,
the set of preconfigured policies encodes a set of operational priorities,
the energy use is associated with an energy use priority, and
the energy use includes at least one of,
energy generation of an energy generation facility,
energy storage of an energy storage facility, or
energy consumption of an energy consumption system,
adapt at least one communication parameter of a communication system for transport of a dataset, wherein, the dataset is associated with the energy use priority, and
transport the dataset, via the communication system, using the at least one communication parameter, wherein transporting the dataset includes:
determining whether a set of transmission criteria has been met,
in response to a determination that the set of transmission criteria has been met, transport the dataset, and
in response to a determination that the set of transmission criteria has not been met:
comparing the energy use priority to the set of operational priorities, and
in response to a determination that the energy use priority is aligned with the set of operational priorities, transport the dataset, and, otherwise, delay the transport of the dataset.
2 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy generation entities in an energy grid.
3 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy generation entities in an energy generation environment that includes an energy grid and a set of distributed energy resources that operate independently of the energy grid.
4 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy storage entities in an energy grid.
5 . The AI-based platform of claim 1 , wherein,
the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy storage entities in an energy storage environment that includes an energy grid and a set of distributed energy resources that operate independently of the energy grid, and
the set of preconfigured policies is a set of contextual policies that adjusts based on the current status of a set of energy delivery entities in an energy grid.
6 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy transmission entities in an energy transmission environment that includes an energy grid and a set of distributed energy resources that operate independently of the energy grid.
7 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy consumption entities that consume energy from an energy grid.
8 . The AI-based platform of claim 1 , wherein the set of preconfigured policies is a set of contextual policies that adjusts based on a current status of a set of energy consumption entities that consume energy from an energy grid and from a set of distributed energy resources that operate independently of the energy grid.
9 . The AI-based platform of claim 1 , wherein,
at least one edge device of the set of edge devices is further configured to adjust the set of preconfigured policies based on at least one contextual factor, and
the at least one contextual factor includes at least one of,
historical data of energy transactions,
at least one operational factor,
at least one market factor,
at least one anticipated market behavior, or
at least one anticipated customer behavior.
10 . The AI-based platform of claim 1 , wherein the adapting the at least one communication parameter is based on at least one of,
the priority associated with the energy use,
at least one market factor,
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, or
a user configuration condition.
11 . The AI-based platform of claim 1 , further comprising an adaptive energy digital twin that 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.
12 . The AI-based platform of claim 1 , further comprising an adaptive energy digital twin that is configured to perform at least one of,
providing at least one of a visual or an analytic indicator of energy consumption by at least one energy consumer,
filtering energy data,
highlighting energy data, or
adjusting energy data.
13 . The AI-based platform of claim 1 , further comprising an adaptive energy digital twin that is configured to generate at least one of a visual or an analytic indicator of energy consumption by at least one of,
at least one machine,
at least one factory, or
at least one vehicle in a vehicle fleet.
14 . The AI-based platform of claim 1 , wherein at least one edge device of the set of edge devices is further configured to perform at least one of,
extracting energy-related data,
detecting errors in energy-related data,
correcting errors in energy-related data,
transforming energy related-data,
converting energy related-data,
normalizing energy-related data,
cleansing energy-related data,
parsing energy-related data,
detecting patterns in energy-related data,
detecting content in energy-related data,
detecting objects in energy-related data,
compressing energy-related data,
streaming energy-related data,
filtering energy-related data,
loading energy-related data,
storing energy-related data,
routing energy-related data,
transporting energy-related data, or
maintaining security of energy-related data.
15 . The AI-based platform of claim 1 , wherein:
at least one policy of the set of preconfigured policies 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 resource,
a population resource,
a demographic resource,
a psychographic data resource,
a market data resource, or
an ecommerce data resource.
16 . The AI-based platform of claim 1 , wherein:
at least one policy of the set of preconfigured policies 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,
product data, or
operating data.
17 . The AI-based platform of claim 1 , wherein,
at least one edge device of the set of edge devices includes at least one of 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,
at least one human tag,
at least one human label,
at least one human interaction with at least one of a hardware system or 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.
18 . The AI-based platform of claim 1 , wherein,
at least one edge device of the set of edge devices is configured to orchestrate delivery of energy to at least one point of consumption, and
the delivery of the energy includes at least one of,
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.
19 . The AI-based platform of claim 1 , wherein,
at least one edge device of the set of edge devices is configured to record, in a distributed ledger, at least one energy-related event, and
the at least one 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 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.
20 . The AI-based platform of claim 1 , wherein,
at least one edge device of the set of edge devices 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.
21 . A method for enabling intelligent orchestration and management of power and energy, the method comprising:
communicating, by a set of edge devices, with an energy system associated with an energy use;
storing a set of preconfigured policies, wherein,
the set of preconfigured policies encodes a set of operational priorities,
the energy use is associated with an energy use priority, and
the energy use includes at least one of,
energy generation of an energy generation facility,
energy storage of an energy storage facility, or
energy consumption of an energy consumption system;
adapting at least one communication parameter a communication system for a transport of a dataset, wherein,
the dataset is associated the energy use priority, and
transporting the dataset, via the communication system, using the at least one communication parameter, wherein transporting the dataset includes:
determining whether a set of transmission criteria has been met,
in response to a determination that the set of transmission criteria has been met, transporting the dataset, and
in response to a determination that the set of transmission criteria has not been met:
comparing the energy use priority to the set of operational priorities, and
in response to a determination that the energy use priority is aligned with the set of operational priorities, transporting the dataset, and, otherwise, delaying the transport of the dataset.
22 . The method of claim 21 , further comprising adjusting, by at least one edge device of the set of edge devices, the set of preconfigured policies based on at least one contextual factor, wherein the at least one contextual factor includes at least one of,
historical data of energy transactions,
at least one operational factor,
at least one market factor,
at least one anticipated market behavior, or
at least one anticipated customer behavior.
23 . The method of claim 21 , further comprising recording in a distributed ledger, by at least one edge device of the set of edge devices, at least one energy-related event, wherein the at least one 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 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.
24 . The AI-based platform of claim 1 , wherein the adapting the at least one communication parameter for the transport of data includes at least one of,
selecting a network route based on the at least one communication parameter,
selecting a network protocol based on the at least one communication parameter,
filtering of transmitted data based on the at least one communication parameter,
prioritizing transmission of data based on the at least one communication parameter, or
selecting a data storage location based on the at least one communication parameter.
25 . The method of claim 21 , wherein the adapting the at least one communication parameter is based on at least one of,
the priority associated with the energy use,
at least one market factor,
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, or
a user configuration condition.
26 . The method of claim 21 , wherein the adapting the at least one communication parameter for the transport of data includes at least one of,
selecting a network route based on the at least one communication parameter,
selecting a network protocol based on the at least one communication parameter,
filtering of transmitted data based on the at least one communication parameter,
prioritizing transmission of data based on the at least one communication parameter, or
selecting a data storage location based on the at least one communication parameter.
27 . The AI-based platform of claim 1 , wherein the set of transmission criteria includes at least one of,
a criterion based on a set of network conditions,
a criterion based on a context of the dataset, or
a criterion based on a set of cost factors associated with transmitting the dataset.
28 . The AI-based platform of claim 1 , wherein,
the set of preconfigured policies translates a set of energy-related inputs into a set of control instructions that governs an energy use, and
the adapting the at least one communication parameter includes,
receiving the set of energy-related inputs,
translating, using the set of preconfigured policies, the set of energy-related inputs into the set of control instructions, and
adapting the at least one communication parameter based on the set of control instructions.
29 . The method of claim 21 , wherein the set of transmission criteria includes at least one of,
a criterion based on a set of network conditions,
a criterion based on a context of the dataset, or
a criterion based on a set of cost factors associated with transmitting the dataset.
30 . The method of claim 21 wherein,
the set of preconfigured policies translates a set of energy-related inputs into a set of control instructions that governs an energy use, and
the adapting the at least one communication parameter includes,
receiving the set of energy-related inputs,
translating, using the set of preconfigured policies, the set of energy-related inputs into the set of control instructions, and
adapting the at least one communication parameter based on the set of control instructions.