SYSTEMS AND METHODS FOR MACHINE FORWARD ENERGY AND ENERGY STORAGE TRANSACTIONS
Systems and methods for machine forward energy and energy storage transactions are disclosed. An example transaction-enabling system may include a resource requirement circuit to aggregate a resource requirement for a fleet of machines to perform a task, wherein the resource requirement comprises an energy storage capacity requirement, a forward resource market circuit to access a forward market for energy, and a machine resource acquisition circuit to execute a transaction on the forward market for energy in response to the aggregated resource requirement.
1 . A transaction-enabling system, comprising:
a resource requirement circuit structured to aggregate a resource requirement for a fleet of machines to perform a task, wherein the resource requirement comprises an energy storage capacity requirement;
a forward resource market circuit structured to access a forward market for energy;
a machine resource acquisition circuit structured to execute a transaction on the forward market for energy in response to the aggregated resource requirement.
2 . The system of claim 1 , wherein the resource requirement is a requirement selected from a group consisting of: a compute task requirement, a networking task requirement, and an energy consumption task requirement.
3 . The system of claim 1 , wherein the transaction on the forward market of energy comprises one of buying or selling energy.
4 . The system of claim 1 , wherein the transaction on the forward market of energy comprises one of buying or selling energy storage capacity.
5 . The system of claim 1 , further comprising a resource distribution circuit structured to adaptively improve one of an aggregate output value of the fleet of machines or a cost of operation of the fleet of machines using a plurality of the transactions on the forward market for energy.
6 . The system of claim 5 , wherein the resource distribution circuit further comprises a component selected from a list of components consisting of a machine learning component, an artificial intelligence component, and a neural network component.
7 . The system of claim 1 , further comprising a market forecasting circuit structured to predict a forward market price of energy on the forward market for energy.
8 . The system of claim 5 , wherein the resource distribution circuit is further structured to interpret historical external data from at least one external data source, and to further adaptively improve a utilization of energy in response to the historical external data.
9 . The system of claim 8 , wherein the at least one external data source is selected from a list consisting of: a market condition data source, a behavioral data source, an agent data source, and an historical outcome data source.
10 . The system of claim 1 , further comprising a forecasting circuit structured to adaptively improve a forecast for an energy resource price on the forward market for energy using a machine learning component, an artificial intelligence component, or a neural network component.
11 . The system of claim 5 , further comprising a market forecasting circuit structured to predict a forward market price of energy storage capacity on the forward market for energy.
12 . The system of claim 11 , wherein the resource distribution circuit is further structured to interpret historical external data from at least one external data source, and to further adaptively improve a utilization of energy storage capacity in response to the historical external data.
13 . The system of claim 12 , wherein the at least one external data source is selected from a list consisting of: a market condition data source, a behavioral data source, an agent data source, and an historical outcome data source.
14 . A method, comprising:
determining an aggregated resource amount for a fleet of machines to service at least one task, wherein the aggregated resource amount comprises an energy storage capacity;
accessing a forward market for energy; and
executing a transaction on the forward market for energy in response to the aggregated resource amount.
15 . The method of claim 14 , further comprising adaptively improving a utilization of the aggregated resource amount utilizing a plurality of transactions on the forward market for energy.
16 . The method of claim 14 , wherein the at least one task comprises at least one of a compute task, a networking task, and an energy consumption task;
17 . The method of claim 14 , wherein executing the transaction on the forward market for energy comprises one of buying or selling energy storage capacity.
18 . The method of claim 14 , wherein executing the transaction on the forward market for energy comprises one of buying or selling energy.
19 . The method of claim 14 , further comprising adaptively improving a cost of operation of the fleet of machines utilizing a plurality of transactions on the forward market for energy.
20 . The method of claim 14 , further comprising forecasting to adaptively improve a forecast for an energy resource price on the forward market for energy using a machine learning component, an artificial intelligence component, or a neural network component.
21 . The method of claim 14 , further comprising interpreting historical external data from at least one external data source, and further adaptively improving a utilization of the aggregated resource amount in response to the historical external data.
22 . The method of claim 21 , wherein the at least one external data source is selected from a list consisting of: a market condition data source, a behavioral data source, an agent data source, and an historical outcome data source.
23 . The method of claim 14 , further comprising adaptively improving a utilization of the energy storage capacity utilizing a plurality of transactions on the forward market for energy.