Patent application title: SYSTEMS AND METHODS FOR FORWARD MARKET PRICE PREDICTION AND SALE OF ENERGY STORAGE CAPACITY WITH ARBITRAGE
Inventors:
IPC8 Class: AG06Q5006FI
USPC Class:
1 1
Class name:
Publication date: 2020-03-26
Patent application number: 20200098068
Abstract:
Systems and methods for forward market price prediction and sale of
energy storage capacity with arbitrage are disclosed. An example
transaction-enabling system may include a fleet of machines having an
aggregate energy storage capacity, and a controller. The controller may
include an external data circuit to monitor and collect data from an
external data source; an expert system circuit to predict a forward
market price for energy storage capacity; a market testing circuit to
execute a first transaction of the aggregate energy storage capacity in a
forward market for energy storage capacity in response to the predicted
forward market price; and an arbitrage execution circuit to execute a
second transaction of the aggregate energy storage capacity in the
forward market in response to at least one of an arbitrage parameter or
the predicted forward price.Claims:
1. A transaction-enabling system, comprising: a fleet of machines having
an aggregate energy storage capacity; and a controller, comprising: an
external data circuit structured to monitor an external data source and
collect data from the external data source; an expert system circuit
structured to predict a forward market price for energy storage capacity
based on the collected data and the aggregate energy storage capacity; a
market testing circuit structured to execute a first transaction of the
aggregate energy storage capacity in a forward market for energy storage
capacity in response to the predicted forward market price; and an
arbitrage execution circuit structured to execute a second transaction of
the aggregate energy storage capacity in the forward market in response
to at least one of an arbitrage parameter or the predicted forward price.
2. The transaction-enabling system of claim 1, wherein the second transaction comprises a larger transaction than the first transaction.
3. The transaction-enabling system of claim 1, wherein the first transaction is a micro-transaction.
4. The transaction-enabling system of claim 1, wherein the arbitrage parameter comprises at least one parameter selected from the parameters consisting of: a similarity value in a market response of the first transaction and the second transaction; a confidence value of the first transaction to provide test information for the second transaction; an outcome of an execution of the first transaction; and a market effect of the first transaction.
5. The transaction-enabling system of claim 1, wherein the arbitrage execution circuit further comprises at least one of a machine learning component, an artificial intelligence component, or a neural network component.
6. The transaction-enabling system of claim 1, wherein the arbitrage execution circuit is further structured to adaptively improve the arbitrage parameter by adjusting a relative size of the first transaction and the second transaction.
7. The transaction-enabling system of claim 1, wherein the controller further comprises a resource allocation circuit that allocates energy storage capacity among the fleet of machines.
8. The transaction-enabling system of claim 1, wherein the external data source comprises a social media source.
9. The transaction-enabling system of claim 8, wherein the social media source is selected from the list of sources consisting of: information publicly available on a social media site, information publicly available on a mass media platform, information from a public comments section of a news article; information from a review section of an online retailer; information from a publicly available profile; proprietary information properly obtained from a social media site; and proprietary information properly obtained from a mass media platform.
10. The transaction-enabling system of claim 8, wherein the social media source comprises cross referenced information from at least one further data source selected from the list consisting of: an IoT data source, an automated agent behavioral data source, a business entity data source, and a human behavioral data source.
11. The transaction-enabling system of claim 1, wherein the external data source comprises at least one of an automated agent behavioral data source, a business entity behavioral data source, a human entity behavioral data source, or a spot market price for an energy storage capacity.
12. The transaction-enabling system of claim 1, wherein the prediction of forward market price for energy storage capacity is at least partially based on a time value of the energy storage capacity, a geographical origin of energy, a type of energy, or a non-linear consideration of a cost of an energy storage capacity.
13. The transaction-enabling system of claim 1, wherein the controller further comprises an optimization circuit structured to optimize an allocation of energy storage capacity among the fleet of machines.
14. The transaction-enabling system of claim 13, wherein the optimization circuit is further structured to optimize the allocation of energy storage capacity between energy storage for future computing tasks and sale of energy storage capacity on the forward market for energy storage capacity.
15. The transaction-enabling system of claim 1, wherein the expert system circuit is further structured to predict a forward market pricing of energy credits based on the collected data.
16. A method comprising: monitoring an external data source and collecting external data from the external data source; predicting a forward market price for energy storage capacity; allocating an aggregate energy storage capacity among a fleet of machines; testing a forward market for energy storage capacity by executing a first transaction of the aggregate energy storage capacity; and executing a second transaction of the aggregate energy storage capacity in the forward market in response to at least one of an arbitrage parameter or the predicted forward price.
17. The method of claim 16, wherein the second transaction comprises a larger transaction than the first transaction.
18. The method of claim 16, wherein the first transaction is a micro-transaction.
19. The method of claim 16, further comprising optimizing the allocation of energy storage capacity among the fleet of machines.
20. The method of claim 16, wherein the prediction of forward market price for energy storage capacity is at least partially based on a time value of the energy storage capacity, a geographical origin of energy, a type of energy, or a non-linear consideration of a cost of the energy storage capacity.
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