Method and apparatus for delivering power using external data

• US 9,418,392 B2
• Filed: 08/23/2013
• Issued: 08/16/2016
• Est. Priority Date: 08/14/2012
• Status: Active Grant

• Current Assignee: Stem, Inc.
• Original Assignee: Stem, Inc.
• Inventors: Kearns, Ben, Burlinson, Jon, Stevens, Drew
• Primary Examiner(s): Masinick, Michael D
• Application Number:
  US13/975,204
• Publication Number:
  US 20140052305A1
• Time in Patent Office: 1,089 Days
• Field of Search: 307/52, 700/295, 700/297
• US Class Current: 1/1
• CPC Class Codes: G05B 13/026 using a predictor
• CPC Class Codes: G05B 2219/39361 Minimize time-energy cost
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 13/00 Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/32 using batteries with converting means
• CPC Class Codes: H02J 4/00 Circuit arrangements for mains or distribution networks not specified as ac or dc
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02P 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• CPC Class Codes: Y04S 10/14 Energy storage units
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

A control system for an energy storage system located behind a utility meter uses a unique, feedback-based, communication and control method to reliably and efficiently maximize economic return of the energy storage system. Operating parameters for the energy storage system are calculated at an external, centralized data center, and are selected to prevent electrical power demand of an electric load location from exceeding a specified set-point by discharging energy storage devices, such as DC batteries, through a bidirectional energy converter during peak demand events. The control system can operate autonomously in the case of a communications failure.

Claims

1. A method of controlling energy transferred between an electric grid and an electric load location, comprising:

monitoring a first rate of energy transfer from an electric line to the electric load location, wherein the electric line is coupled to an electric meter adapted to measure power transferred between the electric load location and the electric grid;

receiving a first set of operating parameters that are created based on one or more received external inputs; and

based on the first set of operating parameters, varying the energy transfer from an energy storage device to the electric line to cause the first rate of energy transfer to remain below a threshold value,

wherein the threshold value varies with time.

2. The method of claim 1, wherein the first set of operating parameters are determined by an optimization engine located remotely from the electric load location.

3. The method of claim 1, wherein the one or more external inputs are received by a processor configured to determine the first set of operating parameters and are selected from a group consisting of weather information, sunrise and sunset information, power usage cost information, utility'"'"'s billing period, electric load location'"'"'s geographic location, local solar production, local incident light, electric load location customer type, electric load location building specifications, grid operator data and time data.

4. The method of claim 1, wherein the method further comprises:

transmitting information used to control the first rate of energy transfer to an optimization engine;

receiving a second set of operating parameters from the optimization engine, wherein the second set of operating parameters are derived from the transmitted information; and

controlling the second rate of energy transfer based on the second set of operating parameters.

5. The method of claim 1, wherein receiving the first set of operating parameters further comprises:

receiving one or more operating control curves comprises a battery curve or a demand set-point curve,

wherein varying the second rate of energy transfer comprises;

comparing the one or more operating control curves with the first rate of energy transfer; and

controlling the transfer of energy between the energy storage device based on the comparison.

6. The method of claim 1, wherein receiving the first set of operating parameters further comprises:

receiving one or more battery curves, and

wherein varying the second rate of energy transfer includes comparing the one or more battery curves with a measured state-of-charge of the energy storage device.

7. A method of controlling fluctuations in energy use at an electric load location, comprising:

generating control parameters based on a simulation that is performed using forecast information;

monitoring a first rate of energy transfer from an electric line to an electric load location; and

controlling a second rate of energy transfer between the electric line and an energy storage device based on the control parameters, wherein controlling the second rate of energy transfer alters the first rate of energy transfer.

8. The method of claim 7, further comprising creating a list of control coefficients that are used to generate the control parameters.

9. The method of claim 8, further comprising validating the list of coefficients by performing a simulation using the created control coefficients.

10. The method of claim 7, further comprising:

creating a list of control coefficients that are used to generate the control parameters; and

generating forecast information by creating a forecast for a first time period for each of the listed control coefficients based on one or more received external inputs.

11. The method of claim 7, further comprising generating the forecast information by creating a forecast for a first time period, wherein the forecast is based on one or more received external inputs.

12. The method of claim 11, wherein the external inputs are selected from a group consisting of weather information, sunrise and sunset information, power usage cost information, utility'"'"'s billing period, electric load location'"'"'s geographic location, local solar production, local incident light, electric load location customer type, electric load location building specifications, grid operator data and time data.

13. The method of claim 7, wherein generating control parameters further comprises:

generating forecast information by creating a forecast for a first time period based on one or more received external inputs; and

cleansing the one or more received external inputs by adjusting the information received from a first external input so that a time scale associated with the information received from the first external input matches a time scale associated with information received from a second external input.

14. The method of claim 7, wherein the control parameters comprise demand set-point curves and one or more battery curves.

15. The method of claim 14, wherein the one or more battery curves comprise a flat battery curve, a stepped battery curve or a continuously varying battery curve.

16. The method of claim 7, wherein generating the control parameters further comprises:

receiving electrical power tariff information for the first time period; and

generating the control parameters based on the electrical power tariff information.

17. The method of claim 16, wherein generating the control parameters comprises performing a simulation that contains the electrical power tariff information.

18. The method of claim 16, wherein generating the control parameters comprises:

receiving electrical power tariff information for the first time period;

receiving energy storage device operation information, wherein the energy storage device operation information comprises at least one of the following;

state-of-charge information received from the energy storage device;

total charge capacity information received from the energy storage device;

charge discharge efficiency rating information received from the energy storage device;

or

current energy capacity information received from the energy storage device; and

generating the control parameters based on a simulation that includes the electrical power tariff information.

19. A method of controlling fluctuations in the energy use at an electric load location, comprising:

monitoring power fluctuations in an electric line that is coupled to an electric load location; and

controlling a transfer of energy from or to the electric line from an energy source, wherein controlling the transfer of energy is adapted to control the amount of variation in time of power delivered through the electric line, wherein controlling the transfer of energy comprises;

controlling the transfer of energy to a first set-point; and

then

controlling the transfer of energy to a second set-point, wherein the second set-point is selected based on a change in the electrical tariff.

20. The method of claim 19, wherein the selection of the second set-point is based on a simulation that contains the electrical power tariff information.

21. The method of claim 19, wherein the selection of the second set-point is based on state-of-charge data received from the energy source.

22. The method of claim 19, wherein the selection of the second set-point comprises:

receiving forecast information that is derived from forecasted coefficient data or historical coefficient data.