METHOD AND SYSTEM FOR USING DEMAND SIDE RESOURCES TO PROVIDE FREQUENCY REGULATION USING A DYNAMIC ALLOCATION OF ENERGY RESOURCES

• US 20150295402A1
• Filed: 12/06/2013
• Published: 10/15/2015
• Est. Priority Date: 12/07/2012
• Status: Active Grant

• Current Assignee: Battelle Memorial Institute
• Original Assignee: Battelle Memorial Institute
• Inventors: Black, Jason W., McCullough, Jason J., Rehberg, Eric, Dvorsky, James E., Mansouri, Seyed A.
• Granted Patent: US 10,243,359 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 13/00022 using wireless data transmission
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 2310/58 The condition being electrical
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02A 30/00 Adapting or protecting infrastructure or their operation
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 Home appliances

Abstract

In a direct load control system supporting frequency control of an electrical grid, loads are grouped into a plurality of load aggregations based on electrical power draw characteristics of the loads, e.g. power draw magnitude characteristic and transient slew rate. A best-fit dispatch signal is generated for each load aggregation to match a desired load response with a sum of predicted load responses of the aggregations each operating in accord with its best-fit dispatch signal. For each load aggregation, its best-fit dispatch signal is communicated to the loads of the load aggregation, and the loads of the load aggregation are operated in accord with the best-fit dispatch signal communicated to the loads. The desired load response may be generated based on historical Automatic Generation Control (AGC) signal data and at least one of (1) a weather forecast and (2) daily, weekly, and seasonal cycles.

Claims

1. A method comprising:

grouping loads into a plurality of load aggregations based on electrical power draw characteristics of the loads;

generating a best-fit dispatch signal for each load aggregation to match a desired load response with a sum of predicted load responses of the aggregations each operating in accord with its best-fit dispatch signal; and

for each load aggregation, communicating its best-fit dispatch signal to the loads of the load aggregation.

2. The method of claim 1 further comprising:

for each load aggregation, operating the loads of the load aggregation in accord with the best-fit dispatch signal communicated to the loads.

3. The method of claim 2 wherein the grouping and the generating are performed at an aggregation dispatch controller, the communicating comprises, for each load aggregation, communicating its best-fit dispatch signal from the aggregation dispatch controller to the loads of the load aggregation, and the operating comprises:

for each load aggregation, operating each load of the load aggregation in accord with the best-fit dispatch signal communicated to the load.

4. The method of claim 3 further comprising:

at each load of each load aggregation, computing a load status report including at least one pair (n,kW) where n is an urgency metric indicating how critical it is for the load to run and kW indicates a power draw level of the load if it runs;

wherein the generating comprises generating the best-fit dispatch signal for each load aggregation to (i) match the desired load response and (ii) optimally satisfy the load status reports of the loads of the plurality of load aggregations.

5. The method of claim 1 wherein the generating comprises:

(i) generating a best-fit dispatch signal for a first load aggregation of the plurality of load aggregations to match the desired load response with the load response of the first aggregation;

(ii) computing a residual load response as a difference between the desired load response and the predicted load response of the first aggregation operating at its best-fit dispatch signal; and

(iii) generating a best-fit dispatch signal for a second load aggregation of the plurality of load aggregations to match the residual load response with the load response of the second aggregation.

6. The method of claim 5 wherein the generating further comprises:

repeating operations (ii) and (iii) at least once to generate a best-fit dispatch signal for at least a third load aggregation of the plurality of load aggregations.

7. The method of claim 6 further comprising:

(iv) for each load aggregation, operating the loads of the load aggregation in accord with the best-fit dispatch signal communicated to the loads;

(v) during the operating, generating a load response error signal as a difference between the desired load response and the sum of actual load responses of the aggregations generated by the operating;

(vi) updating the dispatch signal for an error correction load aggregation of the plurality of load aggregations based on the load response error signal, wherein the communicating includes communicating the updated dispatch signal to the error correction aggregation and the operating includes operating the error correction aggregation in accord with the updated dispatch signal.

8. The method of claim 5 further comprising:

generating the desired load response based on historical Automatic Generation Control (AGC) signal data and at least one of (1) a weather forecast and (2) daily, weekly, and seasonal cycles.

9. The method of claim 1 further comprising:

for each load aggregation, operating the loads of the load aggregation in accord with the best-fit dispatch signal communicated to the loads;

during the operating, generating a load response error signal as a difference between the desired load response and the sum of actual load responses of the aggregations generated by the operating; and

updating the dispatch signal for a load aggregation of the plurality of load aggregations that is designated as an error correction aggregation based on the load response error signal;

wherein the communicating includes communicating the updated dispatch signal to the error correction aggregation and the operating includes operating the error correction aggregation in accord with the updated dispatch signal.

10. The method of claim 1 wherein the grouping comprises:

grouping the loads into the plurality of load aggregations based on electrical power draw characteristics of the loads including at least a power draw magnitude characteristic and a transient slew rate characteristic.

11. The method of claim 10 wherein the grouping the loads is further based on an electrical power draw characteristic comprising a lag time between transients in the dispatch signal and those transients appearing in the load response.

12. A system comprising:

an aggregation dispatch controller comprising an electronic data processing device configured to;

generate a best-fit dispatch signal for each load aggregation of a plurality of load aggregations to match a desired load response with a sum of predicted load responses of the aggregations each operating in accord with its best-fit dispatch signal, wherein the loads are grouped into the plurality of load aggregations based on electrical power draw characteristics of the loads including at least a power draw magnitude characteristic and a transient slew rate characteristic; and

communicate the best-fit dispatch signal for each load aggregation to the loads of that load aggregation.

13. The system of claim 12 further comprising:

said plurality of load aggregations grouped based on said electrical power draw characteristics, wherein the loads of each load aggregation are configured to operate in accord with the best-fit dispatch signal for that load aggregation.

14. The system of claim 13 wherein:

the loads of each load aggregation are further configured to generate and communicate to the aggregation dispatch controller a load status report indicative of power draw requirements of the load; and

the aggregation dispatch controller is configured to generate the best-fit dispatch signals for the load aggregations to further satisfy the power draw requirements of the loads as indicated by the load status reports.

15. The system of claim 12 wherein the aggregation dispatch controller is configured to generate the best-fit dispatch signals for the load aggregations by operations including:

(i) generating a best-fit dispatch signal for a first load aggregation of the plurality of load aggregations to match the desired load response with the load response of the first aggregation;

(ii) computing a residual load response as a difference between the desired load response and the predicted load response of the first aggregation operating at its best-fit dispatch signal; and

(iii) iteratively reducing the residual load response by generating best-fit dispatch signals for other load aggregations of the plurality of load aggregations to match the residual load response.

16. The system of claim 12 wherein the aggregation dispatch controller is further configured to generate a load response error as a difference between the desired load response and the sum of actual load responses of the aggregations operating in accord with the communicated best-fit dispatch signals and to update the dispatch signal for an error correction aggregation of the plurality of load aggregations to correct the load response error in real-time.

17. A non-transitory storage medium storing instructions executable by an electronic data processing device to perform power draw control operations for electrical loads that are grouped into the plurality of load aggregations based on electrical power draw characteristics of the loads including at least a power draw magnitude characteristic and a transient slew rate characteristic, the power control operations comprising:

receiving load status reports from the loads at the electronic data processing device;

generating a best-fit dispatch signal for each load aggregation of a plurality of load aggregations to (1) match a desired load response with a sum of predicted load responses of the aggregations each operating in accord with its best-fit dispatch signal, and (2) satisfy electrical draw requirements of the loads indicated by the load status reports; and

transmitting the best-fit dispatch signal for each load aggregation from the electronic data processing device to the loads of that load aggregation.

18. The non-transitory storage medium of claim 17, wherein the power control operations further comprise:

receiving updates to the desired load response;

measuring a sum of actual load responses of the aggregations each operating in accord with its best-fit dispatch signal;

computing a load response error as a difference between the updated desired load response and the measured sum of actual load responses; and

updating the best-fit dispatch signal for one of the load aggregations to correct the load response error.

19. The non-transitory storage medium of claim 18 wherein the generating is performed for a sliding prediction time window with a time lag T_lag respective to the current time t wherein t_lag is at least one minute and the operations of computing a load response error and updating the best-fit dispatch signal for one of the load aggregations to corrected the load response error is performed on a time frame of less than 30 seconds.

20. The non-transitory storage medium of claim 17 wherein the power control operations further comprise:

generating the desired load response based on historical Automatic Generation Control (AGC) signal data and at least one of (1) a weather forecast and (2) daily, weekly, and seasonal cycles.