SYSTEMS AND METHODS FOR CONTROLLING ENERGY USE IN A BUILDING MANAGEMENT SYSTEM USING ENERGY BUDGETS

• US 20130085616A1
• Filed: 02/14/2012
• Published: 04/04/2013
• Est. Priority Date: 09/30/2011
• Status: Active Grant

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Wenzel, Michael J.
• Granted Patent: US 8,755,943 B2
• Time in Patent Office: Days
• US Class Current: 700/278
• 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 11/47 Responding to energy costs
• CPC Class Codes: F24F 11/58 using Internet communication
• 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 11/63 Electronic processing
• CPC Class Codes: F24F 2120/00 Control inputs relating to users or occupants
• CPC Class Codes: G05D 23/1917 using digital means
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• 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 20/244 the home appliances being or involving heating ventilating and air conditioning [HVAC] units

Abstract

Systems and methods for limiting power consumption by a heating, ventilation, and air conditioning (HVAC) subsystem of a building are shown and described. A mathematical linear operator is found that transforms the unused or deferred cooling power usage of the HVAC system based on pre-determined temperature settings to a target cooling power usage. The mathematical operator is applied to the temperature settings to create a temperature setpoint trajectory expected to provide the target cooling power usage.

Claims

1. A method for controlling power consumption of a cooling system of a building space during a limited power period of a day, comprising:

using a controller of the cooling system to observe cooling power use resulting from a temperature setpoint trajectory of a first day, wherein the temperature setpoint trajectory of the first day comprises a pre-cooling period and a limited power period;

using a controller of the cooling system to calculate a deferred cooling power use resulting from a temperature setpoint trajectory of a first day, wherein the deferred cooling power use is identified by comparing the observed cooling power use to an expected cooling power use for a constant temperature setpoint during the limited power period of the first day;

finding a target deferred cooling power use for a second day;

finding a linear operator that transforms the deferred cooling power use observed during the limited power period of the first day to the target deferred cooling power use; and

applying the linear operator to a changing temperature setpoint trajectory of the first day'"'"'s limited power period to create a temperature setpoint trajectory of a second day.

2. The method of claim 1, wherein applying the linear operator to the temperature setpoint trajectory of the first day'"'"'s limited power period comprises operating the cooling system using open loop control while a measured temperature stays below a maximum temperature.

3. The method of claim 1, wherein finding a linear operator comprises determining calculus operators to describe the linear operator, wherein the calculus operators comprise integral and derivative terms.

4. The method of claim 1, wherein finding a linear operator that transforms the deferred cooling power use observed during the limited power period of the first day to the target deferred cooling power use comprises:

defining the linear operator as a weighted sum the proportional, integral, and derivative of the deferred cooling power use during the limited power period of the first day; and

calculating relative weights of the proportional, integral, and derivative of the deferred cooling power use by minimizing a function of the integral of the difference of (a) the deferred cooling power use operated on by the linear operator, and (b) the optimal cooling power use, over the pre-cooling and limited power periods of the first day; and

wherein applying the linear operator to the temperature setpoint trajectory comprises;

applying the linear operator defined by the relative weights to the temperature setpoint trajectory of the first day.

5. The method of claim 4, wherein calculating the relative weights comprises:

finding output basis vectors for the proportional, integral, and derivative of the deferred cooling power use based on samples of the deferred cooling power use;

finding a set of input basis vectors for the proportional, integral, and derivative of temperature setpoint derivative of the first day based on samples of the temperature setpoint derivative; and

scaling the input basis vectors so each has an average value equal to the average temperature setpoint derivative.

6. The method of claim 1, wherein finding a target deferred cooling power use for a second day comprises:

finding a total deferred cooling energy use during the pre-cooling and limited power period;

dividing the total deferred cooling energy use over the limited power period;

finding the average cooling power use during parts of the limited power period that have a constant energy cost; and

transforming at least one constraint on a measured temperature of the building space to a constraint on deferred cooling power use; and

performing an optimization routine that finds the target deferred cooling power use comprising, for each period of constant energy cost during the limited power period, minimizing the total cost of the deferred cooling power use, the total cost in terms of a cost of the energy and a cost of the demand for the energy, and subject to the constraint on deferred cooling power use.

7. The method of claim 1, furthering comprising using a capacitive model to estimate the way energy is stored and released in the building space and to adjust the temperature setpoint trajectory of the second day using the capacitive model.

8. The method of claim 1, wherein observing cooling power use resulting from a temperature setpoint trajectory of a first day comprises applying a smoothing filter to the observed cooling power use to reduce inaccuracies from the observation.

9. The method of claim 1, wherein creating a temperature setpoint trajectory of a second day comprises accounting for variations in the cooling power use due to non-constant setpoint by isolating cooling power use due to constant setpoint.

10. The method of claim 1, wherein the first day comprises one or more past days, and wherein the second day comprises a next demand limiting day.

11. A controller for controlling power consumption of a cooling system of a building space during a limited power period of a day, comprising:

a processing circuit configured to observe cooling power use resulting from a temperature setpoint trajectory over a pre-cooling period and a limited power period of a first day, the processing circuit configured to compute a deferred cooling power use resulting from a temperature setpoint trajectory of a first day, wherein the deferred cooling power use is identified by comparing the observed cooling power use to an expected cooling power use for a constant temperature setpoint during the limited power period of the first day, to compute a target deferred cooling power use for a second day, and to compute a linear operator that transforms the deferred cooling power use observed during the limited power period of the first day to the target deferred cooling power use, the processing circuit further configured to apply the linear operator to a changing temperature setpoint trajectory of the first day'"'"'s limited power period to create a temperature setpoint trajectory of a second day.

12. The controller of claim 11, wherein the system is configured to operate the cooling system using open loop control while a measured temperature stays below a maximum temperature.

13. The controller of claim 11, wherein the processing circuit is configured to compute calculus operators to describe the linear operator, wherein the calculus operators comprise integral and derivative terms.

14. The controller of claim 11, wherein the processing circuit is configured to:

compute the linear operator as a weighted sum the proportional, integral, and derivative of the deferred cooling power use on the first day and the relative weights of the proportional, integral, and derivative of the deferred cooling power use, the processing circuit further configured to compute relative weights of the proportional, integral, and derivative of the deferred cooling power use by minimizing a function of the integral of the difference of (a) the deferred cooling power use operated on by the linear operator, and (b) the optimal cooling power use, over the pre-cooling and limited power periods of the first day; and

apply the linear operator to the temperature setpoint trajectory by applying the linear operator defined by the relative weights to the temperature setpoint trajectory of the first day.

15. The controller of claim 14, wherein computing the relative weights comprises:

calculating output basis vectors for the proportional, integral, and derivative of the deferred cooling power use based on samples of the deferred cooling power use;

calculating input basis vectors for the proportional, integral, and derivative of temperature setpoint derivative of the first day based on samples of the temperature setpoint derivative;

scaling the output basis vectors and input basis vectors so each has an average value equal to the average temperature setpoint derivative.

16. The controller of claim 11, wherein computing the target deferred cooling power use comprises:

computing a total deferred cooling energy use during the pre-cooling and limited power period;

dividing the total deferred cooling energy use over the limited power period;

computing the average cooling power use during parts of the limited power period that have a constant energy cost;

transforming at least one constraint on a measured temperature of the building space to a constraint on deferred cooling power use; and

performing an optimization routine that finds the target deferred cooling power use by minimizing the total cost of the deferred cooling power use, the total cost in terms of a cost of the energy and a cost of the demand for the energy, and subject to the constraint on cooling power use.

17. The controller of claim 11, wherein the processing circuit is configured to a utilize a capacitive model to estimate the way energy is stored and released in the building space and to adjust the temperature setpoint trajectory of the second day using the capacitive model.

18. The controller of claim 11, wherein the processing circuit is configured to apply a smoothing filter to the observed cooling power use to reduce inaccuracies from the observation.

19. The controller of claim 11, wherein the processing circuit is configured to account for variations in the cooling power use due to non-constant setpoint by isolating cooling power use due to constant setpoint.

20. The controller of claim 11, wherein the first day comprises one or more past days, and wherein the second day comprises a next demand limiting day.