SYSTEMS AND METHODS FOR MACHINE FORWARD ENERGY AND ENERGY STORAGE TRANSACTIONS

Abstract

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.

Claims

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.