Systems and methods for detecting changes in energy usage in a building
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-007/60
G06F-017/10
G06Q-010/06
G06Q-050/06
H02J-013/00
H02J-003/00
출원번호
US-0252092
(2011-10-03)
등록번호
US-9286582
(2016-03-15)
발명자
/ 주소
Drees, Kirk H.
Kummer, James P.
Wenzel, Michael J.
출원인 / 주소
Johnson Controls Technology Company
대리인 / 주소
Foley & Lardner LLP
인용정보
피인용 횟수 :
7인용 특허 :
193
초록▼
A computer system for use with a building management system for a building includes a processing circuit configured to determine a building's baseline energy usage model. The processing circuit may be configured to determine one or more automatically selected variables for use in the baseline energy
A computer system for use with a building management system for a building includes a processing circuit configured to determine a building's baseline energy usage model. The processing circuit may be configured to determine one or more automatically selected variables for use in the baseline energy usage model for predicting energy use in a building. The processing circuit may be further configured to cause the display of the one or more automatically selected variables on a user interface device. The processing circuit may be configured to receive, from the user interface, a selection of one or more variables which differ from the one or more automatically selected variables. The processing circuit may be further configured to use the received selection to generate a new baseline energy usage model.
대표청구항▼
1. A method for generating a baseline energy usage model for a building management system comprising: receiving, at a processing circuit, an initial set of variables for potential use in a baseline energy usage model for predicting energy use in a building;performing, by the processing circuit, stat
1. A method for generating a baseline energy usage model for a building management system comprising: receiving, at a processing circuit, an initial set of variables for potential use in a baseline energy usage model for predicting energy use in a building;performing, by the processing circuit, statistical hypothesis testing on each of the initial set of variables to determine which of the initial set of variables are statistically significant to the energy use in the building, the statistical hypothesis testing comprising: generating a first set of coefficients for the baseline energy usage model based on the initial set of variables;removing one of the variables from the initial set of variables to create a subset of the initial set of variables;generating a second set of coefficients for the baseline energy usage model based on the subset of the initial set of variables; andcalculating a test statistic for the removed variable using a difference between the first set of coefficients and the second set of coefficients and comparing the calculated test statistic to a critical value;automatically selecting, by the processing circuit, one or more of the initial set of variables for use in the baseline energy usage model based on a result of the statistical hypothesis testing, wherein a variable is selected for use in the baseline energy usage model when the test statistic calculated for the variable exceeds the critical value;causing the one or more automatically selected variables to be displayed on a user interface device;receiving, at the user interface, a selection of one or more variables which differ from the one or more automatically selected variables; andusing the selection of the one or more variables which differ from the one or more automatically selected variables to generate a new baseline energy usage model. 2. The method of claim 1, wherein the selection of the one or more variables which differ from the one or more automatically selected variables comprises a selection of one or more time periods. 3. The method of claim 1, wherein the new baseline energy usage model is generated by applying regression analysis to the selection of the one or more variables which differ from the one or more automatically selected variables. 4. The method of claim 1, further comprising: receiving, at the user interface device, a selection of an override parameter, wherein the new baseline energy usage model is generated based on the selection of the override parameter. 5. The method of claim 1, further comprising: receiving, at the user interface device, a selection of a data source;retrieving comparison data from memory based on the selection of a data source; andusing the retrieved comparison data to determine an energy consumption. 6. The method of claim 5 further comprising: comparing the comparison data to the baseline energy usage model; andcausing an indication of the comparison to be displayed by the user interface device. 7. The method of claim 1, further comprising: validating that two or more selected variables have overlapping timeframes; andcausing a warning to be displayed by the user interface device based on the comparison. 8. The method of claim 1, further comprising: generating a graph using the baseline energy consumption model; and causing the graph to be displayed by the user interface device. 9. The method of claim 6, further comprising: generating a graph based on the comparison; andcausing the graph to be displayed by the user interface device. 10. The method of claim 1, further comprising: receiving, at the user interface, different selections to test generating different baseline energy usage models. 11. A system for generating a baseline energy usage model for a building management system comprising: a processing circuit configured to receive an initial set of variables for potential use in a baseline energy usage model for predicting energy use in a building,wherein the processing circuit is further configured to perform statistical hypothesis testing on each of the initial set of variables to determine which of the initial set of variables are statistically significant to the energy use in the building, the statistical hypothesis testing comprising: generating a first set of coefficients for the baseline energy usage model based on the initial set of variables;removing one of the variables from the initial set of variables to create a subset of the initial set of variables;generating a second set of coefficients for the baseline energy usage model based on the subset of the initial set of variables; andcalculating a test statistic for the removed variable using a difference between the first set of coefficients and the second set of coefficients and comparing the calculated test statistic to a critical value;wherein the processing circuit is further configured to automatically select one or more of the initial set of variables for use in the baseline energy usage model based on a result of the statistical hypothesis testing, wherein a variable is selected for use in the baseline energy usage model when the test statistic calculated for the variable exceeds the critical value,wherein the processing circuit is further configured to cause the one or more automatically selected variables to be displayed on a user interface device,wherein the processing circuit is further configured to receive, from the user interface, a selection of one or more variables which differ from the one or more automatically selected variables, andwherein the processing circuit is further configured to use the selection of the one or more variables which differ from the one or more automatically selected variables to generate a new baseline energy usage model. 12. The system of claim 11, wherein the selection of the one or more variables which differ from the one or more automatically selected variables comprises a selection of one or more time periods. 13. The system of claim 11, wherein the new baseline energy usage model is generated by applying regression analysis to the selection of the one or more variables which differ from the one or more automatically selected variables. 14. The system of claim 11, wherein the processing circuit is further configured to receive, from the user interface device, a selection of an override parameter, wherein the new baseline energy usage model is generated based on the selection of the override parameter. 15. The system of claim 11, wherein the processing circuit is further configured to receive, from the user interface device, a selection of a data source; wherein the processing circuit is configured to retrieve comparison data from memory based on the selection of a data source; and wherein the processing circuit is further configured to use the retrieved comparison data to determine an energy consumption. 16. The system of claim 15, wherein the processing circuit is further configured to compare the comparison data to the baseline energy usage model and to cause an indication of the comparison to be displayed by the user interface device. 17. The system of claim 11, wherein the processing circuit is further configured to validate that two or more selected variables have overlapping timeframes and to cause a warning to be displayed by the user interface device based on the comparison. 18. The system of claim 11, wherein the processing circuit is further configured to generate a graph using the baseline energy consumption model and to cause the graph to be displayed by the user interface device. 19. The system of claim 11, wherein the processing circuit is further configured to receive, from the user interface device, different selections to test generating different baseline energy usage models. 20. Non-transitory computer-readable storage 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 receiving an initial set of variables for potential use in a baseline energy usage model for predicting energy use in a building;instructions for performing statistical hypothesis testing on each of the initial set of variables to determine which of the initial set of variables are statistically significant to the energy use in the building, the statistical hypothesis testing comprising: generating a first set of coefficients for the baseline energy usage model based on the initial set of variables;removing one of the variables from the initial set of variables to create a subset of the initial set of variables;generating a second set of coefficients for the baseline energy usage model based on the subset of the initial set of variables; andcalculating a test statistic for the removed variable using a difference between the first set of coefficients and the second set of coefficients and comparing the calculated test statistic to a critical value;instructions for automatically selecting one or more of the initial set of variables for use in the baseline energy usage model based on a result of the statistical hypothesis testing, wherein a variable is selected for use in the baseline energy usage model when the test statistic calculated for the variable exceeds the critical value;instructions for causing the one or more automatically selected variables to be displayed on a user interface device;instructions for receiving a selection of one or more variables which differ from the one or more automatically selected variables; andinstructions for using the selection of the one or more variables which differ from the one or more automatically selected variables to generate a new baseline energy usage model.
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Borah, Frederic M.; Gavarian, Richard J.; Leib, Jr., Anthony; Venable, James, Actuator controller for monitoring health and status of the actuator and/or other equipment.
Shaw Allan (5th Floor ; Security House ; 233 North Terrace Adelaide AUX) Luxton Russell E. (5th Floor ; Security House ; 233 North Terrace Adelaide AUX), Air conditioner and method of dehumidifier control.
Shaw Allan (5th Floor ; Security House ; 233 North Terrace Adelaide AUX) Luxton Russell E. (5th Floor ; Security House ; 233 North Terrace Adelaide AUX) Luxton Russell E. (Adelaide AUX), Air conditioning and method of dehumidifier control.
Warashina Yoshitaka (Fuji JPX) Mochizuki Kazuo (Fuji JPX) Kumagai Noboru (Shizuoka JPX) Morita Keiichi (Fujinomiya JPX) Nagasawa Atsushi (Mishima JPX), Air conditioning apparatus having louver for changing the direction of air into room.
Huddleston Paul M. (Stone Mountain GA) Porter ; Jr. G. Burns (Doraville GA) Rooney David T. (Marietta GA), Apparatus and method for monitoring an energy management system.
Hedlund, Eric H.; Roddy, Nicholas Edward; Gibson, David Richard; Bliley, Richard G.; Pander, James E.; Puri, Ashish; O'Camb, Thomas E.; Lovelace, II, John Howard; Loncher, Steven, Apparatus and method for performance and fault data analysis.
Skaaning, Claus; Jensen, Finn V.; Kj.ae butted.rulff, Uffe; Pelletier, Paul A.; Jensen, Lasse Rostrup; Parker, Marilyn A.; Boborad, Janice L., Automated diagnosis of printer systems using Bayesian networks.
Kon Akihiko,JPX ; Naruse Akihiko,JPX, Building management system having set offset value learning and set bias value determining system for controlling therma.
Gloudeman Jeffrey J. ; Gottschalk Donald A. ; Kraemer C. Richard ; Rasmussen David E., Common object architecture supporting application-centric building automation systems.
Cebasek Gregory B. ; Gloudeman Jeffrey J. ; Gottschalk Donald A. ; Rasmussen David E., Communication system for distributed-object building automation system.
Crooks Gerry ; Arnhold Ed ; Battista John ; Boni Ken ; Bowers Dan ; Feichtner Mark ; French Blaine ; Genzberger Janna ; Holmes David D. ; Kippenhan Larry ; Miller Dave ; Nanto Shawn ; Orr Teri ; Schl, Computerized resource accounting methods and systems, computerized utility management methods and systems, multi-user u.
Kettler John P. (Shawnee KS) Reese James A. (Overland Park KS), Control system for air quality and temperature conditioning unit with high capacity filter bypass.
Jensen Howard A. (Mequon WI) Seem John E. (Menomonee Falls WI), Controller for use in an environment control network capable of storing diagnostic information.
Mathur Anoop (Shoreview MN) MacArthur Ward J. (Minneapolis MN) Gabel Steven D. (Golden Valley MN) Taracks Donald (Minneapolis MN) Zhao Jianliang (Albany CA) Spethman Donald H. (Northbrook IL), Cool storage supervisory controller.
Fukai Hisanori (Tokyo JPX) Yamazaki Hiroshi (Tokyo JPX) Kawano Kenji (Tokyo JPX) Kawano Shinichiro (Tokyo JPX) Okamoto Hajime (Tokyo JPX), Data acquisition system for the analysis of elevator trouble.
Seidl Neal John ; Divjak August Antony ; Kelkar Uday Ramchandra, Data structure for scheduled execution of commands in a facilities management control system.
West Jonathan D. ; Estill Brian T. ; Chen Jiade, Detection of saturation status for non-synchronous incremental actuators using a variable position estimate window.
Kahn Gary S. (Pittsburgh PA) Pepper Jeffrey A. (Verona PA) Kepner Al N. (Pittsburgh PA) Richer William (Pittsburgh PA) Enand Rajiv (Deerborn MI), Domain independent shell for building a diagnostic expert system.
Bilas Ronald J. (Cedar Rapids IA) Reid Drew A. (Cedar Rapids IA), Electrical distribution system having controller responsive to multiple command paths.
Cretella, Joaquim Geraldo; Herrig, Doyle G.; Rustad, Leslie D.; Gast, Randal; Schmidt, Richard W.; Flanagan, Thomas A., Environment-controlled transport unit.
Figley, Donald A.; Figley, Chase R.; Figley, Sarah A.; Figley, Curtis M., Humidity monitoring and alarm system for unattended detection of building moisture management problems.
Castelli, Vittorio; Hamilton, II, Rick A.; Pickover, Clifford A.; Wisniewski, Robert, Indicating physical site energy usage through a virtual environment.
Shah Dipak J. (Eden Prairie MN) Krueger James H. (Plymouth MN) Strand Rolf L. (Crystal MN), Indoor climate controller system adjusting both dry-bulb temperature and wet-bulb or dew point temperature in the enclos.
Wang Hsu-Pin (Tallahassee FL) Huang Hsin-Hao (Kaohsiung TWX) Knapp Gerald M. (Baton Rouge LA) Lin Chang-Ching (Tallahassee FL) Lin Shui-Shun (Tallahassee FL) Spoerre Julie K. (Tallahassee FL), Machine fault diagnostics system and method.
Spoerre Julie K. (Tallahassee FL) Lin Chang-Ching (Tallahassee FL) Wang Hsu-Pin (Tallahassee FL), Machine performance monitoring and fault classification using an exponentially weighted moving average scheme.
Erbstein Robert S. (New London County CT) Richard Gary R. (New London County CT) Palmatier Roland T. (Washington County RI) McGill Robert W. (Hilversum NLX), Management and analysis system for web machines and the like.
Wedekind Gilbert L. (698 McGill Rochester Hills MI 48309), Method and apparatus for adaptively optimizing climate control energy consumption in a building.
Seem,John E.; Huth,William A.; Fraune,Robert J.; Lewis,Anita M.; Ky,Tri V., Method and apparatus for assessing performance of an environmental control system.
Frerichs,Donald Karl; Toth,Frank Marvin, Method and apparatus for detecting faults in steam generator system components and other continuous processes.
MacGregor, Paul, Method and apparatus for determining energy savings by using a baseline energy use model that incorporates a neural network algorithm.
Barclay, Kenneth B.; Mattison, Timothy J.; Jones, Melvin A.; MacGregor, Paul, Method and apparatus for determining energy savings by using a baseline energy use model that incorporates an artificial intelligence algorithm.
Jones Jeffrey K. (1861 SE. 148th Ave. Portland OR 97233) White James (2233 SE. 53 Portland OR 97215), Method and apparatus for predictive maintenance of HVACR systems.
Glen David,CAX ; Caruk Gord,CAX ; Verma Raj,CAX ; Lee Keith,CAX, Method and apparatus for processing video data utilizing a palette digital to analog converter.
Chester,Daniel L.; Daniel,Stephen L.; Fickelscherer,Richard J.; Lenz,Douglas H., Method and system of monitoring, sensor validation and predictive fault analysis.
Thybo, Claus; Rasmussen, Bjarne Dindler; Izadi-Zamanabad, Roozbeh, Method for detecting changes in a first media flow of a heat or cooling medium in a refrigeration system.
Gray William F. (512 Herndon Pkwy. Herndon VA 22070), Method of automatically managing a network or remote function-excecuting apparatus from a programable network control ce.
Alex Bernaden, III ; Gaylon M. Decious ; John E. Seem ; Kirk H. Drees ; Jonathan D. West ; William R. Kuckuk, Method of programming and executing object-oriented state machine logic in a controller.
Enstrm Henrik S. (Fyndevgen 5 191 47 Sollentuna SEX), Method primarily for performance control at heat pumps or refrigerating installations and arrangement for carrying out t.
Matsubara,Masahiro; Harada,Yasushi; Sato,Yasuo; Kobayashi,Nobuhisa; Yamada,Junichi, Method, system and computer program for managing energy consumption.
Kountz Kenneth J. (Hoffman Estates IL) Cooper Kenneth W. (York PA) Abendschein Frederic H. (Columbia PA) Sumner ; Jr. Lee E. (Dallastown PA), Microcomputer control for an inverter-driven heat pump.
Seem John (Shorewood WI) Jensen Howard A. (Mequon WI) Monroe Richard H. (West Milwaukee WI), On-line monitoring of controllers in an environment control network.
Bliley, Richard G.; Roddy, Nicholas E., Process and system for analyzing fault log data from a machine so as to identify faults predictive of machine failures.
Cmar Gregory (379 Namant Rd. Namant MA 01908), Process for identifying patterns of electric energy effects of proposed changes, and implementing such changes in the fa.
Morley Richard E. (Mason NH) Bromberg Michael A. (Nashua NH) Taylor William A. (Campton NH), Programmable sequence controller with drum emulation and improved power-down power-up circuitry.
Bernaden ; III Alex ; Decious Gaylon M. ; Seem John E. ; Drees Kirk H. ; West Jonathan D. ; Kuckuk William R., State machine controller for operating variable air volume terminal units of an environmental control system.
Edwards, Reed; McNeely, Sr., James Clyde; Carden, Kevin Daniel; Mullis, Vance, System and method for determining expected unserved energy to quantify generation reliability risks.
Culp, Charles H.; Claridge, David E.; Haberl, Jeffrey S.; Turner, William D.; Liu, Mingsheng, System and method for diagnostically evaluating energy consumption systems and components of a facility.
Culp,Charles H.; Claridge,David E.; Haberl,Jeffrey S.; Turner,William D., System and method for remote identification of energy consumption systems and components.
Culp, Charles H.; Claridge, David E.; Haberl, Jeffrey S.; Turner, William D., System and method for remote monitoring and controlling of facility energy consumption.
Culp,Charles H.; Claridge,David E.; Haberl,Jeffrey S.; Turner,William D., System and method for remote monitoring and controlling of facility energy consumption.
Culp,Charles H.; Claridge,David E.; Haberl,Jeffrey S.; Turner,William D., System and method for remote retrofit identification of energy consumption systems and components.
Burns Thomas J. (Callaway FL) Page Edward C. (Lynn Haven FL) Gregory Rita A. (Panama City FL) Pryor George M. (Panama City FL), Totally integrated construction cost estimating, analysis, and reporting system.
Ahmed, Syed S.; Sawyer, Kevin W.; Herzog, Bryan M.; Hall, Kim L.; Beason, Kirk W., Unit ventilator having a splitter plate and a pivoting damper blade assembly.
Main, Elizabeth J.; Chen, Wendy, Demand response dispatch prediction system including automated validation, estimation, and editing rules configuration engine.
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