SYSTEMS AND METHODS FOR FORWARD MARKET ENERGY PRICE PREDICTION AND MACHINE FORWARD ENERGY PURCHASE

Abstract

A transaction-enabling system includes a machine having an energy requirement for a task; and a controller, comprising: a resource requirement circuit structured to determine an amount of an energy resource for the machine to service the energy requirement; a market forecasting circuit structured to predict a forward market price on a forward resource market based on the determined amount of the energy resource and at least one external data source; a forward resource market circuit structured to access the forward resource market; and a resource distribution circuit structured to execute a transaction on the forward resource market in response to the determined amount of the energy resource and the predicted forward market price.

Claims

1. A transaction-enabling system, comprising: a machine having an energy requirement for a task; and a controller, comprising: a resource requirement circuit structured to determine an amount of an energy resource for the machine to service the energy requirement; a market forecasting circuit structured to predict a forward market price on a forward resource market based on the determined amount of the energy resource and at least one external data source; a forward resource market circuit structured to access the forward resource market; and a resource distribution circuit structured to execute a transaction on the forward resource market in response to the determined amount of the energy resource and the predicted forward market price.

2. The transaction-enabling system of claim 1, wherein the energy resource comprises an energy credit resource, and wherein the forward resource market comprises a forward market for energy credits.

3. The transaction-enabling system of claim 1, wherein the at least one external data source is an internet-of-things (IoT) data source.

4. The transaction-enabling system of claim 1, wherein the forward resource market comprises at least one of a forward market for energy corresponding to the energy resource, or a forward market for energy corresponding to a substitute energy resource.

5. The transaction-enabling system of claim 1, wherein the transaction of the energy resource on the forward resource market comprises one of buying or selling the energy resource.

6. The transaction-enabling system of claim 1, wherein the resource distribution circuit is further structured to adaptively improve a cost of operation of the machine using executed transactions on the forward resource market.

7. The transaction-enabling system of claim 6, 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.

8. The transaction-enabling system of claim 1, wherein the resource requirement circuit is further structured to determine an amount of a resource for the machine to service a resource utilization requirement, wherein the resource is selected from the resources consisting of: a compute resource, a network bandwidth resource, a spectrum resource, a data storage resource, and an energy credit resource.

9. The transaction-enabling system of claim 1, wherein the market forecasting circuit is further structure to predict the forward market price as one of a price for energy corresponding to the energy resource or a price for energy corresponding to a substitute energy resource.

10. The transaction-enabling system of claim 1, 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 the energy resource in response to the historical external data.

11. The transaction-enabling system of claim 1, wherein the task comprises at least one of a compute task, a networking task, or an energy consumption task.

12. The transaction-enabling system of claim 1, further comprising a forecasting circuit structured to adaptively improve a forecast for an energy resource price on the forward resource market using a machine learning component, an artificial intelligence component, or a neural network component.

13. A method, comprising: determining an amount of an energy resource for a machine to service at least one task; predicting a forward market price on a forward resource market based on the determined amount of the energy resource and at least one external data source; accessing a forward resource market; and executing a transaction on the forward resource market in response to the determined amount of the energy resource and the predicted forward market price.

14. The method of claim 13, wherein the at least one external data source is an internet-of-things (IoT) data source.

15. The method of claim 13, wherein the forward resource market further comprises a forward market for energy.

16. The method of claim 15, wherein the forward market for energy comprises one of a forward market for energy corresponding to the energy resource, or a forward market for energy corresponding to a substitute energy resource.

17. The method of claim 13, further comprising adaptively improving a utilization of the energy resource.

18. The method of claim 13, wherein the at least one task comprises at least one of a compute task, a networking task, or an energy consumption task.

19. The method of claim 13, wherein executing the transaction on the forward resource market comprises one of buying or selling the energy resource.

20. The method of claim 13, further comprising adaptively improving a cost of operation of the machine using executed transactions on the forward resource market.

21. The method of claim 13, further comprising forecasting to adaptively improve a forecast for an energy resource price on the forward resource market using a machine learning component, an artificial intelligence component, or a neural network component.

22. The method of claim 13, further comprising interpreting historical external data from at least one external data source, and further adaptively improving a utilization of the energy resource in response to the historical external data.