Providing demand response

• US 10,495,333 B2
• Filed: 02/24/2017
• Issued: 12/03/2019
• Est. Priority Date: 02/24/2017
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Berka, Jan, Holub, Ondrej, Finger, Richard, Endel, Petr
• Primary Examiner(s): Brown, Michael J
• Application Number:
  US15/442,093
• Publication Number:
  US 20180245810A1
• Time in Patent Office: 1,012 Days
• Field of Search: 700286, 700297
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/65 for selecting an operating mode
• CPC Class Codes: F24F 11/70 Control systems characterised by their outputs; Constructional details thereof
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2140/50 Load
• CPC Class Codes: F24F 2140/60 Energy consumption
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: G05D 23/1917 using digital means

Abstract

Devices, systems, and methods for providing demand response are described herein. One device includes instructions executable to receive thermostat data associated with an operating thermostat of a heating, ventilation, and air conditioning (HVAC) system in a structure over a period of time, determine a first portion of the thermostat data corresponding to steady-state operation periods of the thermostat, determine a second portion of the thermostat data corresponding to operation periods of the thermostat that are responding to temperature setpoint changes, determine a third portion of the thermostat data corresponding to operation periods of the thermostat that are transitions between the steady-state operation periods and the operation periods that are responding to temperature setpoint changes, and create a steady-state model of the thermostat based on the first portion of the thermostat data, a setpoint-change model of the thermostat based on the second portion of the thermostat data, and a transition model of the thermostat based on the third portion of the thermostat data.

Claims

1. A non-transitory computer-readable medium having instructions stored thereon which, when executed by a processor, cause the processor to:

receive thermostat data associated with an operating thermostat of a heating, ventilation, and air conditioning (HVAC) system in a structure over a period of time including measured temperatures inside the structure and conditions external to the structure;

determine a first portion of the thermostat data corresponding to steady-state operation periods of the thermostat;

determine a second portion of the thermostat data corresponding to operation periods of the thermostat that are responding to temperature setpoint changes;

determine a third portion of the thermostat data corresponding to operation periods of the thermostat that are transitions between the steady-state operation periods and the operation periods that are responding to temperature setpoint changes; and

create a steady-state model of the thermostat based on the first portion of the thermostat data, a setpoint-change model of the thermostat based on the second portion of the thermostat data, and a transition model of the thermostat based on the third portion of the thermostat data, wherein the setpoint change-model of the thermostat includes;

a rate of temperature change of the structure in response to the HVAC system

activating or deactivating as a static function of the measured temperatures inside the structure and the conditions external to the structure.

2. The medium of claim 1, wherein the thermostat data includes:

setpoints of the thermostat;

signals associated with HVAC devices of the structure;

demand response signals received by the thermostat;

contextual information associated with the HVAC devices and the structure; and

conditions external to the structure.

3. The medium of claim 2, wherein the steady-state model of the thermostat includes an average on-time of the thermostat as a static function of the setpoints of the thermostat and the conditions external to the structure.

4. The medium of claim 2, wherein the transition model of the thermostat includes:

a probability density function associated with a length of an on-time of the thermostat based on a length of a previous off-time of the thermostat and the conditions external to the structure; and

a probability density function associated with a length of an off-time of the thermostat based on a length of a previous on-time of the thermostat and the conditions external to the structure.

5. The medium of claim 1, including instructions to determine a cooling inefficiency associated with the HVAC system based on a determination that the setpoint-change model exceeds a cooling threshold.

6. The medium of claim 1, including instructions to determine an insulation inefficiency associated with the structure responsive to a determination that the setpoint-change model of the thermostat meets or exceeds a self-heating threshold.

7. The medium of claim 1, including instructions to provide a recommendation associated with a change in customer behavior responsive to a determination that the setpoint-change model of the thermostat meets or exceeds a self-heating threshold.

8. A computing device for providing demand response, comprising:

a processor; and

a memory configured to store instructions which, when executed by the processor, cause the processor to;

receive thermostat data associated with each of a plurality of sites over a period of time, wherein each respective site includes an operating thermostat of a heating, ventilation, and air conditioning (HVAC) system in a structure;

determine an HVAC usage pattern for each of the plurality of sites;

receive contextual information associated with each of the plurality of sites;

sort the plurality of sites into a plurality of segments based on the HVAC usage pattern and the contextual information; and

for each segment;

determine a control group of sites; and

determine a total baseline energy consumption of sites of the segment active in a demand response event based on an average baseline energy consumption of sites of the control group and a quantity of sites in the segment.

9. The computing device of claim 8, wherein the instructions to determine the HVAC usage pattern include instructions to determine the HVAC usage patterns on a same day as the demand response event.

10. The computing device of claim 8, wherein each segment includes a plurality of sites in a respective geographical region.

11. The computing device of claim 8, including instructions to determine the control group of sites from a plurality of sites not participating in the demand response event.

12. The computing device of claim 8, wherein the contextual information for each site includes:

a rated power of each of a plurality of devices of the HVAC system;

a location of the structure;

a size of the structure;

a type of the structure; and

an age of the HVAC system.

13. The computing device of claim 8, including instructions to determine an energy shed associated with the demand response event in a particular segment based on the total baseline energy consumption for the particular segment and an aggregated energy consumption resulting from the demand response event.

14. The computing device of claim 8, wherein the HVAC usage pattern for each of the plurality of sites includes an on-time for the HVAC system of each of the plurality of sites during a particular period of time prior to the demand response event.

15. A method for providing demand response, comprising:

receiving thermostat data associated with an operating thermostat of a heating, ventilation, and air conditioning (HVAC) system in a structure over a period of time;

determine a cooling rate associated with the structure based on the thermostat data;

determine a self-heating rate associated with the structure based on the thermostat data; and

recommend a demand response program type to apply to the HVAC system based on the cooling rate and the self-heating rate,

wherein the method includes recommending the duty-cycle program to apply to the HVAC system responsive to a determination that the self-heating rate is above a self-heating threshold and the cooling rate is below a cooling threshold.

16. The method of claim 15, wherein the demand response program type is selected from a group of demand response program types including:

a duty-cycle program;

an offset program; and

a precooling program.

17. The method of claim 16, wherein the method includes recommending the offset program to apply to the HVAC system responsive to a determination that the self-heating rate is below the self-heating threshold and the cooling rate is above the cooling threshold.

18. The method of claim 17, wherein the method includes recommending the precooling to apply to the HVAC system responsive to a determination that the self-heating rate is below the self-heating threshold and the cooling rate is above the cooling threshold.