SYSTEMS AND METHODS FOR DETECTING CHANGES IN ENERGY USAGE IN A BUILDING

• US 20110257911A1
• Filed: 06/23/2011
• Published: 10/20/2011
• Est. Priority Date: 06/22/2009
• Status: Active Grant

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Drees, Kirk H., Wenzel, Michael J.
• Granted Patent: US 9,196,009 B2
• Time in Patent Office: Days
• US Class Current: 702/61
• CPC Class Codes: G01R 21/133 by using digital technique
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: G06Q 50/163 Real estate management
• CPC Class Codes: H02J 13/00001 characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
• CPC Class Codes: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 13/00006 characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
• CPC Class Codes: H02J 13/00016 using a wired telecommunication network or a data transmission bus
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/12 The local stationary network supplying a household or a building
• 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: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/20 End-user application control systems
• CPC Class Codes: Y04S 20/221 General power management systems
• CPC Class Codes: Y04S 20/222 : Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/12 : characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
• CPC Class Codes: Y04S 40/124 : using wired telecommunication networks or data transmission busses
• CPC Class Codes: Y04S 40/20 : Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

A computer system for use with a building management system for a building includes a processing circuit configured to automatically identify a change in a building'"'"'s energy usage model based on data received from the building management system. The processing circuit may be configured to communicate the identified change in the static factor to at least one of (a) a module for alerting a user to the identified change and (b) a module for initiating an adjustment to the energy model for a building in response to the identified change.

Claims

1. A computer system for use with a building management system in a building, comprising:

a processing circuit configured to automatically identify a change in the building'"'"'s energy usage model based on data received from the building management system;

wherein the processing circuit is configured to communicate the identified change in the building'"'"'s energy usage model to at least one of (a) a module for alerting a user to the identified change and (b) a module for initiating an adjustment to the energy model for the building in response to the identified change.

2. The computer system of claim 1, wherein the processing circuit identifies the change in the building'"'"'s energy usage model by comparing a coefficient of the energy usage model to a calculated energy model coefficient for a more recent time period.

3. The computer system of claim 2, wherein, to conduct the comparison, the processing circuit creates a test statistic representing at least one of:

(a) the difference between the model coefficients,

(b) an F-statistic that is related to the difference between the model coefficients, and

(c) a Z-statistic that is formed by standardizing an F-statistic that is related to the difference between the model coefficients;

wherein the processing circuit determines autocorrelation of a plurality of such test statistics for varying windows of time; and

wherein the processing circuit uses the autocorrelation to determine whether the baseline model has changed in a significant way.

4. The computer system of claim 3, wherein the processing circuit using the autocorrelation to determine whether the baseline model has changed in a significant way comprises:

the processor calculating a critical value such that the probability that any given test statistic is greater than the critical value matches a predefined probability of falsely determining that the baseline model has changed in a significant way;

wherein the critical value is calculated using a cumulative probability distribution inverse approximated via Monte Carlo simulation of the test statistics for the varying windows of time; and

wherein the samples used to approximate the inverse are simulated by simulating the actual process used to detect the change with a randomly generated model or are simulated from a multivariable normal distribution.

5. The computer system of claim 1, wherein the comparison is conducted after installation of an energy conservation measure and while the system is in a measurement and verification reporting period.

6. The computer system of claim 1, wherein the processing circuit is further configured to determine and report an additional cost or savings attributable to the identified change in the building'"'"'s energy use model;

wherein the processing circuit is further configured to use the additional cost or savings to determine a non-routine adjustment to the baseline model estimated to provide an accurate calculation of savings attributable to an energy conservation measure;

wherein the energy use factor is a static factor.

7. The computer system of claim 1, wherein the comparison is conducted on based on data from a time period prior to installation of the energy conservation measure and wherein the energy use model will serve as a baseline model for a measurement and verification process.

8. A method for identifying changes that affect a building'"'"'s energy usage during a baseline period being used to generate a baseline energy usage model, comprising:

calculating energy usage models for varying windows of time within the baseline period;

comparing coefficients of the calculated energy usage models for varying windows of time;

outputting an indication that the change has occurred based on the comparison.

9. The method of claim 8, wherein comparing coefficients of the calculated energy usage models comprises creating a test statistic representing at least one of:

(a) the difference between the model coefficients,

(b) an F-statistic that is related to the difference between the model coefficients, and

(c) a Z-statistic that is formed by standardizing an F-statistic that is related to the difference between the model coefficients;

and wherein the method further comprises;

determining an autocorrelation of a plurality of such test statistics for the varying windows of time within the baseline period; and

using the autocorrelation to determine whether the baseline model has changed in a significant way.

10. The method of claim 9, wherein outputting an indication that the change has occurred comprises outputting an indication of the timing of the change;

and

wherein the method further comprises, in response to the output indication, calculating the latest baseline energy usage model using data gathered after the change.

11. A method for identifying changes that affect a building'"'"'s energy usage during a reporting period after an energy conservation measure has been applied to the building, comprising:

calculating a first energy usage model for a first portion of the reporting period;

calculating a second energy usage model a second portion of the reporting period;

determining whether a change that affects the building'"'"'s energy usage has occurred by on comparing the model coefficients as associated with the first energy usage model to the model coefficients as associated with the second energy usage model; and

outputting the result of the determination to a building management system component.

12. The method of claim 11, wherein the first and second energy usage models are generated by:

using data from the first and second portions of the reporting period, respectively, to select a set of variables estimates to be significant to energy usage in the building; and

applying a regression analysis to each selected set of variables to generate a first and second energy usage models.

13. The method of claim 11, wherein outputting the result of the determination to a building management system component comprises:

outputting at least one of;

(a) an indication that an energy use factor of the building has changed, (b) an indication that a baseline for estimating energy use in the building should be adjusted, and (c) an amount by which the baseline should be adjusted.

14. The method of claim 11, wherein determining whether a coefficient has changed based on comparing the coefficients comprises:

creating a test statistic representing differences between model coefficients of the first energy usage model and model coefficients of the second energy usage model; and

determining the autocorrelation of the test statistic and a plurality of such test statistics for varying windows of time within the reporting period;

using the autocorrelation to determine whether the first model has changed in a significant way during the reporting period.

15. The method of claim 14, wherein using the autocorrelation to determine whether the model has changed in a significant way during the reporting period comprises:

calculating a critical value such that the probability that any given test statistic is greater than the critical value matches a predefined probability of falsely determining that the model has changed in a significant way;

wherein the critical value is calculated using a cumulative probability distribution inverse approximated via Monte Carlo simulation of the test statistics for the varying windows of time; and

wherein the samples used to approximate the inverse are simulated by simulating the actual process used to detect the change with a randomly generated model or are simulated from a multivariable normal distribution.

16. The method of claim 15, further comprising:

determining and reporting an additional cost or savings attributable to the identified change in the building'"'"'s energy use model;

using the additional cost or savings to determine a non-routine adjustment to the baseline model estimated to provide an accurate calculation of savings attributable to an energy conservation measure;

wherein the energy use factor is a static factor.

17. Computer-readable media with computer-executable instructions embodied thereon that when executed by a computer system perform a method for use with a building management system in a building, wherein the instructions comprise:

instructions for using historical data from the building management system to select a set of variables estimated to be significant to energy usage in the building;

instructions for applying a regression analysis to the selected set of variables to generate a baseline model for predicting energy usage in the building;

instructions for monitoring data of the building management system after installation of energy conservation measures to determine whether the baseline model can accurately be used to estimate the energy that would have been used by the building prior to the installation of energy conservation measures; and

instructions for outputting at least one of;

(a) an indication that an energy use factor of the building has changed, and (b) an indication that the baseline model should be adjusted.

18. The computer-readable media of claim 17, wherein the instructions for monitoring comprise:

instructions for applying a regression analysis to at least two windows of building management system data from a reporting period that is post installation of the energy conservation measure; and

instructions for comparing model coefficients of the different regression analyses.

19. The computer-readable media of claim 18, wherein the instructions for monitoring comprise:

instructions for creating a plurality of test statistics, each test statistic representing at least one of;

(a) the difference between the model coefficients,

(b) an F-statistic that is related to the difference between the model coefficients, and

(c) a Z-statistic that is formed by standardizing an F-statistic that is related to the difference between the model coefficients;

instructions for determining an autocorrelation of the plurality of such test statistics, wherein the plurality of test statistics comprises a test statistic of the baseline model coefficients and at least one test statistic of relating to the at least two windows of building management system data from the reporting period that is post installation of the energy conservation measure;

instructions for using the autocorrelation to determine whether the test statistic has changed in a significant way during the reporting period.

20. The computer-readable media of claim 19, wherein the instructions for using the autocorrelation to determine whether the baseline model has changed in a significant way during the reporting period comprises:

instructions for calculating a critical value such that the probability that any given test statistic is greater than the critical value matches a predefined probability of falsely determining that the baseline model has changed in a significant way;

wherein the critical value is calculated using a cumulative probability distribution inverse approximated via Monte Carlo simulation of the test statistics for the different windows of time; and

wherein the samples used to approximate the inverse are simulated by simulating the actual process used to detect the change with a randomly generated model or are simulated from a multivariable normal distribution.

21. The computer-readable media of claim 17, wherein the instructions further comprise:

instructions for determining and reporting an additional cost or savings attributable to the identified change in the building'"'"'s energy use model;

instructions for using the additional cost or savings to determine a non-routine adjustment to the baseline model estimated to provide an accurate calculation of savings attributable to an energy conservation measure;

wherein the energy use factor is a static factor.

22. A computer system for use with a building management system in a building, comprising:

a processing circuit configured to automatically identify a change in the building'"'"'s resource consumption model based on data received from the building management system;

wherein the processing circuit is configured to communicate the identified change in the building'"'"'s resource consumption model to at least one of (a) a module for alerting a user to the identified change and (b) a module for initiating an adjustment to the resource consumption model for the building in response to the identified change.

23. The computer system of claim 22, wherein the resource consumption model corresponds to at least one of water usage, gas usage, and electrical energy usage.