System and method for optimal aggregation of small-scale energy storage

Patent metadata

Field	Value
Publication number	US-10608436-B2
Application number	US-201715834412-A
Country	US
Kind code	B2
Filing date	Dec 7, 2017
Priority date	Dec 7, 2017
Publication date	Mar 31, 2020
Grant date	Mar 31, 2020

Abstract

A system for optimal aggregation of small-scale energy storage capacity includes a processor operatively coupled to memory. The processor is configured to implement the steps of: generating predicted energy consumption data based on a model of expected energy usage within a given electrical network; generating predicted energy generation data based on a model of expected energy generation for the given electrical network; generating dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network; determining a set of energy storage devices that need to be dispatched for the given electrical network; comparing the predicted energy consumption data with the predicted energy generation data; and dispatching the set of energy storage devices for the given electrical network.

First claim

What is claimed is:

1. A method for aggregation of small-scale energy storage capacity comprising:
generating predicted energy consumption data based on a model of expected energy usage within a given electrical network;
generating predicted energy generation data based on a model of expected energy generation for the given electrical network;
generating dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network;
determining a set of energy storage devices that need to be dispatched for the given electrical network;
in response to a user of the energy storage device accepting or rejecting a request to be dispatched, comparing the predicted energy consumption data with the predicted energy generation data; and
dispatching the accepted set of energy storage devices for the given electrical network,
wherein the steps of the method are performed in accordance with a processor and a memory.

2. The method of claim 1 , further comprising creating the model for expected energy usage based on one or more sets of data.

3. The method of claim 2 , wherein the model for expected energy usage is created as a function of one or more variables.

4. The method of claim 2 , wherein the one or more sets of data comprise one or more of a set of historical electricity usage data, a set of demographic data, a set of traffic data and a set of weather data.

5. The method of claim 1 , further comprising creating the model for expected energy generation based on one or more sets of data.

6. The method of claim 5 , wherein the model for expected energy generation is created as a function of one or more variables.

7. The method of claim 5 , wherein the one or more sets of data comprise one or more of a set of historical electricity generation data, a set of demographic data, a set of historical traffic data, a set of satellite or radar data and a set of historical weather data.

8. The method of claim 1 , wherein the step of comparing comprises calculating a difference between the predicted energy consumption data and the predicted energy generation data.

9. The method of claim 8 , wherein when the predicted energy generation data is greater than the predicted energy consumption data, the step of dispatching the set of energy storage devices comprises discharging the set of energy storage devices.

10. The method of claim 8 , wherein when the predicted energy generation data is less than the predicted energy consumption data, the step of dispatching the set of energy storage devices comprises charging the set of energy storage devices.

11. The method of claim 8 , wherein when the predicted energy generation data is greater than the predicted energy consumption data, the method further comprises rewarding a user of the energy storage device.

12. The method of claim 1 , wherein the step of generating dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network comprises generating a score for each energy storing device.

13. The method of claim 12 , wherein the step of determining a set of energy storage devices that need to be dispatched for the given electrical network comprises ranking each energy storing device based on the score.

14. A system comprising:
a memory and a processor operatively coupled to the memory and configured to implement the steps of:
generating predicted energy consumption data based on a model of expected energy usage within a given electrical network;
generating predicted energy generation data based on a model of expected energy generation for the given electrical network;
generating dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network;
determining a set of energy storage devices that need to be dispatched for the given electrical network;
in response to a user of the energy storage device accepting or rejecting a request to be dispatched, comparing the predicted energy consumption data with the predicted energy generation data; and
dispatching the accepted set of energy storage devices for the given electrical network.

15. The system of claim 14 , further comprising creating the model for expected energy usage based on one or more sets of data comprising one or more of a set of historical electricity usage data, a set of demographic data, a set of traffic data and a set of weather data.

16. The system of claim 14 , further comprising creating the model for expected energy generation based on one or more sets of data comprising one or more of a set of historical electricity generation data, a set of demographic data, a set of historical traffic data, a set of satellite or radar data and a set of historical weather data.

17. The system of claim 14 , wherein the step of generating dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network comprises generating a score for each energy storing device.

18. The system of claim 17 , wherein the step of determining a set of energy storage devices that need to be dispatched for the given electrical network comprises ranking each energy storing device based on the score.

19. The system of claim 17 , wherein the step of comparing comprises calculating a difference between the predicted energy consumption data and the predicted energy generation data.

20. A computer program product comprising a non-transitory computer readable storage medium for storing computer readable program code which, when executed, causes a computer to:
generate predicted energy consumption data based on a model of expected energy usage within a given electrical network;
generate predicted energy generation data based on a model of expected energy generation for the given electrical network;
generate dispatchable energy storage capacity for one or more energy storing devices having a small-scale energy storage capacity for the given electrical network;
determine a set of energy storage devices that need to be dispatched for the given electrical network;
in response to a user of the energy storage device accepting or rejecting a request to be dispatched, compare the predicted energy consumption data with the predicted energy generation data; and
dispatch the set of energy storage devices for the given electrical network.

Assignees

• IBM

Inventors

• De Hoog Julian
• Vishwanath Arun
• Lynar Timothy M
• Eberbach Adam

Classifications

• H02J3/003 Primary

  Load forecast, e.g. methods or systems for forecasting future load demand · CPC title

• H02J3/00

  Circuit arrangements for AC mains or AC distribution networks · CPC title

• G05B13/048

  using a predictor · CPC title

• H02J3/32 Primary

  using batteries or super capacitors with converting means · CPC title

• H02J2003/007

  Electricity · mapped topic