Source: http://www.google.com/patents/US7894943?dq=oakley+D523,461
Timestamp: 2017-03-26 03:56:54
Document Index: 45983629

Matched Legal Cases: ['art 3', 'art 3', 'art 2', 'art 2', 'art 4', 'art 4']

Patent US7894943 - Real-time global optimization of building setpoints and sequence of operation - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsA building heating/cooling system energy optimization method for a building having a heating/cooling system includes the steps of providing a mathematical model of the heating/cooling system, obtaining real-time weather information, reading the input water temperature (IWT), the output water temperature...http://www.google.com/patents/US7894943?utm_source=gb-gplus-sharePatent US7894943 - Real-time global optimization of building setpoints and sequence of operationAdvanced Patent SearchTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents.Publication numberUS7894943 B2Publication typeGrantApplication numberUS 11/171,603Publication dateFeb 22, 2011Filing dateJun 30, 2005Priority dateJun 30, 2005Fee statusPaidAlso published asUS20070005191, WO2008100241A2, WO2008100241A3Publication number11171603, 171603, US 7894943 B2, US 7894943B2, US-B2-7894943, US7894943 B2, US7894943B2InventorsCharles J. Sloup, Daniel Karnes, Gregor P. HenzeOriginal AssigneeSloup Charles J, Daniel Karnes, Henze Gregor PExport CitationBiBTeX, EndNote, RefManPatent Citations (45), Non-Patent Citations (21), Referenced by (69), Classifications (14), Legal Events (3) External Links: USPTO, USPTO Assignment, EspacenetReal-time global optimization of building setpoints and sequence of operation
US 7894943 B2Abstract
generating reports using said calibrated mathematical model in coordination with a weather template based on historical norms for a location of said building. Description
i. The number of independent variables is limited by actual operating conditions based on real-time data. For example, the independent variables being evaluated during the winter heating season are different than the independent variables used in the summer cooling season. Also, the input water temperature (IWT) of the heating/cooling system may be understood to be the condenser water temperature before cooling and the pre-heating temperature before heating, and likewise the output water temperature (OWT) may be understood to be the chiller water temperature after cooling and the post-heating temperature after heating. ii. The range of the independent variables is limited in order to reduce processing time as well as give the automation controllers small step changes that do not result in significant disturbances to control system stability. iii. It is at this stage that underlying constraints, such as system capacities, are taken into account. Boundaries (box constraints) can be imposed on the independent variables as well as dependent variables being limited by penalty or barrier functions as a result of programming. b. Optimization is performed.
i. The optimization engine automatically writes the input files for the simulation. The generated input files are based on the input template files. The simulation calculation is performed. ii. The optimization engine automatically retrieves the output of the simulation package, checks to make sure results are within predefined constraints and stores the results in an output log. iii. The optimization engine then determines the new set of input parameters for the next run, utilizing the optimization algorithm to determine the lowest operational cost. iv. Once the lowest cost of operation is determined, the system setpoints associated with the lowest operational cost are delivered to the BAS.
a. In the BAS the existing setpoints are replaced by the new optimized setpoints for utilization in the control loops. b. Example:
i. Current building operation has a chiller evaporator outlet water temperature of 45° F., a condenser inlet water temperature of 85° F., an AHU discharge temperature of 55° F. and a building load of “X”. These variables are moved from the building automation system to the optimization engine. ii. The optimization engine runs a simulation utilizing current conditions described above to establish an energy use baseline and stores the results. iii. The optimization engine then runs a simulation utilizing a chiller evaporator outlet water temperature of 46° F., all other variables remain the same and stores the results. This is repeated for all variables and all combinations of variables until an overall minimum cost is found by solving the equation of minimum cost for all three values at the same time cooperatively. iv. The optimization engine might then determine that keeping the evaporator outlet water temperature of 45° F. at its current setpoint, changing the condenser inlet water temperature to a setpoint of 84° F. and changing the AHU discharge temperature to 54° F. will satisfy the load imposed by “X” and thus save the most energy when compared to the baseline. v. These setpoints are then sent back to and utilized by the building automation system which updates the settings to optimize operation of the heating/cooling system.
a. Energy Plus gets information from Genopt. b. Energy Plus calculates energy usage. c. Sends results back to Genopt.
i. The majority of the simulation package would be of the standard type used in the prior art but a critical feature of the present invention is the ability to bypass the room load calculation and “warmup” cycles. FIG. 2 indicates that room load calculation consists of the Surface Heat Balance Manager which in the preferred embodiment would require reprogramming of the simulation manager. ii. The room load calculation can be bypassed by utilizing a direct measurement of the cooling or heating load by utilizing a air terminal unit discharge sensor described in the BAS section above in lieu of calculating heat transfer functions for each surface involved, thereby significantly increasing calculation speed. However, the inclusion of any such reconfiguration is believed to be inventive in nature and is an important feature of the present invention, as the specifics of the reconfiguration do not impact the inventive features that the reconfiguration itself affords. iii. Because the room load calculation is eliminated, the calculation of room load, which is dependent on time delays due to mass effects of the physical system, “warmup cycles” are also eliminated as unnecessary to prime the calculations, thereby further increasing calculation speed, the reconfiguration of which will be determined through further experimentation. iv. If a particular building owner makes the decision to only optimize the cooling side of the energy use equation it may be possible to eliminate the air terminal unit discharge sensor and utilize the VAV box damper position as an indicator of building cooling load and subsequent limit of the supply air temperature based on the measured sensitivity of the maximum damper position with supply air temperature. 5. Advantages
a. The computing platform and interface is specifically designed for estimating elements. b. The programs are tested for interaction. c. The system utilizes calibrated models with a high degree of accuracy and does not require a learning curve. 6. Controls Loops
Constraints/Boundaries: a. Optimization range is higher and lower than design setpoint. b. Raising temperature does not have a high limit defined in absolute terms. The upper boundary is found via polling the AHUs attached to the system to determine the cooling coil with highest percentage open value. c. Lowering temperature does not have a low limit defined in absolute terms. The lower boundary is found via polling the attached AHUs to determine if the cooling coil delta Ts are falling below design criteria which would be an indication that laminar flow is taking place in the cooling coil water circuit. d. Effects at ATU: No direct effects. e. Effects at AHU: Raising the chilled water temperature will cause the cooling coil valve to open until it is 100% open. Conversely lowering the temperature will cause the cooling coil valve to close. f. Effects on Chiller: Raising the chilled water temperature will cause the chiller to run more efficiently and the pumping to run less efficiently. g. Base Case sequence of operation is a fixed setpoint. h. Optimized Case: Ability to coordinate setpoint with other setpoints to realize savings. i. Correlation of BAS points with loads program input points: Direct Correlation. ii. Condenser Water Control Loop
Constraints/Boundaries: a. Optimization range is higher and lower than design setpoint. b. Raising temperature does not have a high limit defined in absolute terms. Upper boundary is found via polling the attached chillers. c. Lowering temperature does not have a low limit defined in absolute terms. Lower boundary is found via polling the attached chillers. d. Effects at ATU: No direct effects. e. Effects at AHU: No direct effects. f. Effects on Chiller: Raising condenser water inlet temperature temperature will cause the chiller to run less efficiently. g. Base Case sequence of operation is a fixed setpoint. h. Optimized Case: Ability to coordinate setpoint with other setpoints to realize savings. i. Correlation of BAS points with loads program input points: Direct Correlation. iii. AHU discharge air temperature control loop
Constraints/Boundaries: a. Optimization range is higher and lower than design setpoint. b. Raising temperature does not have a high limit defined in absolute terms. Upper boundary is found via polling the ATU's attached to the system to determine if space temperatures are being maintained. c. Lowering temperature does not have a low limit defined in absolute terms. Lower boundary is found via balancing the reheat needs against the fan power savings associated with lower airflow requirements. d. Effects at ATU: Raising AHU discharge temperature will cause the air-terminal unit dampers to open till 100% open. e. Effects at AHU: Raising discharge temperature will cause chilled water valves to close f. Effects on Chiller: Raising AHU discharge temperature will cause the chiller to run more efficiently and the pumping more efficiently because delta T can be increased. g. Base Case sequence of operation is a fixed setpoint. h. Optimized Case: Ability to coordinate setpoint with other setpoints to realize savings. i. Correlation of BAS points with loads program input points: Direct Correlation. [0102]. 7. Three additional features of the present invention which are not critical to the operation of the invention but have been proven to be beneficial are the ability to integrate real-time utility costs into simulation, the ability to generate a design phase report and further the ability to demand reports from the system.
a. The first feature provides information regarding electrical demand and what can be done to influence this dominant factor in the energy cost equation. b. Upon initiation at the BAS workstation, the optimization preprocessor will retrieve a post design weather/load file from an archive. This weather load file will contain a weather template for the location based on historical norms and this will not be adjusted for building specifics. The weather/load file will also contain a load template for the specific building which has been modified with archived realtime data provided by the building automation system. This adjustment based on realtime data calibrates the energy model rather than relying on educated guesses by the design engineer. This will require all of the simulation computing elements found in FIG. 2. This weather/modified load file will be used in lieu of the realtime data from the BAS (base configuration) so it can project out beyond current conditions. c. Example: The facility operations manager wants to know if it is cost-effective to change out filters thereby lowering static and in turn horsepower and in turn demand and in turn demand ratchet. If the cost of the filters and the labor to replace the filters is known, the simulation program can project the cost impact of the change in demand projected over the demand ratchet period brought back to a net present value. The same approach can be used to determine the speed at which emergency generators can be run in order to shed demand without exceeding emissions limits. d. The second feature is to provide a design phase report that can be used to project savings afforded by implementing the technique of the present invention and in turn calculate return on investment necessary for justification of additional capital costs. Upon initiation at the optimization workstation, the optimization preprocessor will retrieve a design phase weather/load file from an archive. This weather load file will contain a weather template for the location based on historical norms, this is not adjusted for building specifics. The weather/load file will also contain a load template for the specific building which has been generated by the facility design engineer This will require all of the simulation computing elements found in FIG. 2. This weather/modified load file will be used in lieu of the realtime data from the BAS (base configuration) so it can project out beyond current conditions. e. The third feature would reference future preferred embodiments, in which the optimization preprocessor would be connected to the Internet in order to obtain realtime utility cost information. Currently, real time pricing is only used by a few utilities but its use is growing. It is expected that use of realtime pricing will lead to further efficiency gains through use of the present invention, and thus its inclusion herewith is desirable. Results Graph
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS2842311Mar 24, 1955Jul 8, 1958Honeywell Regulator CoControl apparatusUS2972447Jun 14, 1956Feb 21, 1961White Roby ByronOptimal controllerUS3916445 *Feb 23, 1973Oct 28, 1975Westinghouse Electric CorpTraining simulator for nuclear power plant reactor coolant system and methodUS4040565Apr 20, 1976Aug 9, 1977Jorn Uffe ChristiansenControl unit for thermal conditioning systemsUS4089462Feb 19, 1976May 16, 1978International Telephone & Telegraph CorporationTemperature control system including K-Factor adjustmentUS4176785Sep 27, 1978Dec 4, 1979Amf IncorporatedAutomatic temperature controller with night setback and operating as a function of outside airUS4200910Jan 30, 1978Apr 29, 1980Hall Burness CProgrammable time varying control system and methodUS4210957May 8, 1978Jul 1, 1980Honeywell Inc.Operating optimization for plural parallel connected chillersUS4215408Dec 12, 1977Jul 29, 1980United Technologies CorporationTemperature control of unoccupied living spacesUS4217646Dec 21, 1978Aug 12, 1980The Singer CompanyAutomatic control system for a buildingUS4276925Sep 19, 1979Jul 7, 1981Fuel Computer Corporation Of AmericaElectronic temperature control systemUS4363441Apr 23, 1980Dec 14, 1982Emanuel FeinbergThermal energy usage meter for multiple unit buildingUS4463574Mar 15, 1982Aug 7, 1984Honeywell Inc.Optimized selection of dissimilar chillersUS4522333Sep 16, 1983Jun 11, 1985Fluidmaster, Inc.Scheduled hot water heating based on automatically periodically adjusted historical dataUS4623969Jan 5, 1984Nov 18, 1986David BensoussanElectronic temperature controller for householdingUS4674027Jun 19, 1985Jun 16, 1987Honeywell Inc.Thermostat means adaptively controlling the amount of overshoot or undershoot of space temperatureUS4784212Nov 21, 1986Nov 15, 1988Transmet Engineering, Inc.Building perimeter thermal energy control systemUS5105366May 3, 1990Apr 14, 1992Honeywell Inc.Comfort control system and method factoring mean radiant temperatureUS5148977Jun 19, 1991Sep 22, 1992Hitachi, Ltd.Control system for air-conductionerUS5236477Oct 23, 1992Aug 17, 1993Kabushiki Kaisha ToshibaMicrocomputer-based control deviceUS5261483 *Jan 15, 1992Nov 16, 1993Kabushiki Kaisha Toyo Techno Corp.Control system for a fan coil of an air-conditionerUS5289362Dec 15, 1989Feb 22, 1994Johnson Service CompanyEnergy control systemUS5337955 *Mar 12, 1993Aug 16, 1994Burd Alexander LCombined boiler water temperature controlUS5682949May 18, 1993Nov 4, 1997Globalmic, Inc.Energy management systemUS5817958 *Aug 5, 1996Oct 6, 1998Hitachi, Ltd.Plant monitoring and diagnosing method and system, as well as plant equipped with the systemUS5909378Apr 9, 1997Jun 1, 1999De Milleville; HuguesControl apparatus and method for maximizing energy saving in operation of HVAC equipment and the likeUS5950709Jul 21, 1995Sep 14, 1999Honeywell Inc.Temperature control with stored multiple configuration programsUS6095426Nov 7, 1997Aug 1, 2000Siemens Building TechnologiesRoom temperature control apparatus having feedforward and feedback control and methodUS6098893Oct 22, 1998Aug 8, 2000Honeywell Inc.Comfort control system incorporating weather forecast data and a method for operating such a systemUS6263260May 20, 1997Jul 17, 2001Hts High Technology Systems AgHome and building automation systemUS6366832Nov 24, 1998Apr 2, 2002Johnson Controls Technology CompanyComputer integrated personal environment systemUS6402043Oct 18, 2001Jun 11, 2002John F. CockerillMethod for controlling HVAC unitsUS6418728 *May 10, 2000Jul 16, 2002Jerry MonroeThermoelectric water pre-cooling for an evaporative coolerUS6449533May 25, 2000Sep 10, 2002Emerson Electric Co.Thermostat and method for controlling an HVAC system with remote temperature sensorUS6454177Mar 9, 2001Sep 24, 2002Hitachi, Ltd.Air-conditioning controlling systemUS6591620Feb 6, 2002Jul 15, 2003Hitachi, Ltd.Air conditioning equipment operation system and air conditioning equipment designing support systemUS6628997Apr 28, 2000Sep 30, 2003Carrier CorporationMethod for programming a thermostatUS6726113Feb 25, 2002Apr 27, 2004Carrier CorporationTemperature control strategy utilizing neural network processing of occupancy and activity level sensingUS6785592 *Jul 13, 2000Aug 31, 2004Perot Systems CorporationSystem and method for energy managementUS6976366 *Oct 29, 2003Dec 20, 2005Emerson Retail Services Inc.Building system performance analysisUS7343226 *Oct 26, 2006Mar 11, 2008Robertshaw Controls CompanySystem and method of controlling an HVAC systemUS20030102383Nov 19, 2002Jun 5, 2003Omron CorporationController, temperature controller and heat processor using sameUS20030216837Mar 6, 2003Nov 20, 2003Daniel ReichArtificial environment control systemUS20040173690Mar 16, 2004Sep 9, 2004Kitz CorporationControl system with communication function and facility control systemUS20090210081 *Sep 30, 2008Aug 20, 2009Rockwell Automation Technologies, Inc.System and method for dynamic multi-objective optimization of machine selection, integration and utilization* Cited by examinerNon-Patent CitationsReference1ASHRAE, Building Energy Monitoring. ASHRAE Fundamentals 2003, Chapter 40, 2001, 41 pg.2ASHRAE, Supervisory Control Strategies and Optimization. ASHRAE Fundamentals 2003, Chapter 41, 2001, 41 pg.3Braun, J.E., Klein, SA, Beckman W.A., & Mitchell, J.W., Methodologies for Optimal Control of Chilled Water Systems without Storage. ASHRAE Transactions, 1989, pp. 652-662, vol. 95, Part I.4Braun, J.E., Klein, SA, Beckman, W.A., & Mitchell, J.W., Applications of Optimal Control to Chilled Water Systems without Storage. ASHRAE Transactions, 1989, pp. 663-675, vol. 95, Part I.5Cascia, Mark A., Implementation of a Near-Optimal Global Set Point Control Method in a DDC Controller, ASHRAE Transactions, vol. 106 Part I. pp. 249-263, described in a printed publication more than one year before Jun. 30, 2005, the effective filing date of the present application.6Gibson, Gerald L, P.E., A Supervisory Controller for Optimization of Building Central Cooling Systems, ASHRAE Transactions, vol. 103 Part I. pp. 486-493, described in a printed publication more than one year before Jun. 30, 2005, the effective filing date of the present application.7Kaya, Azmi & Enterline, Larry, Control and Optimization of Plant Compressors to Save Energy, Proceedings of the 1984 American Control Conference, 1984, pp. 1829-1835, American Automatic Control Council.8 *Khan et al., Performance Analysis of a Residential Ground Source Heat Pump System with Antifreeze Solution 2004, School of Mechanical Engineering, Oklahoma State University, 10 pages.9 *Newman-H.M., "Direct Digital Control of Building Systems, Theory and Practice", 1994, Wiley-Interscience Publication, pp. 39, 70,71,73-81,130-132,162,210-213.10Rob Moult, Control of Cooling-Only VAV Boxes-Part 3, Air Conditioning and Refrigeration Journal, Jul. 1999, pp. 1-8.11Rob Moult, Control of Cooling-Only VAV Boxes—Part 3, Air Conditioning and Refrigeration Journal, Jul. 1999, pp. 1-8.12Rob Moult, Control Strategies for VAV Air Handling Units-Part 2, Air Conditioning and Refrigeration Journal, Apr. 1999, pp. 1-11.13Rob Moult, Control Strategies for VAV Air Handling Units—Part 2, Air Conditioning and Refrigeration Journal, Apr. 1999, pp. 1-11.14Rob Moult, Indoor Air Quantity Control of VAV Air Handling Units-Part 4, Air Conditioning and Refrigeration Journal, Oct. 1999, pp. 1-11.15Rob Moult, Indoor Air Quantity Control of VAV Air Handling Units—Part 4, Air Conditioning and Refrigeration Journal, Oct. 1999, pp. 1-11.16Rob Moult, VAV Systems for office Buildings-Part I, Air Conditioning and Refrigeration Journal, Jan. 1999, pp. 1-7.17Rob Moult, VAV Systems for office Buildings—Part I, Air Conditioning and Refrigeration Journal, Jan. 1999, pp. 1-7.18 *Taesler-R., "Climate and Building Energy Management", 1991, Swedish Meteorology and Hydrological, p. 599-608.19Wetter, Michael, GenOpt® Generic Optimization Program User Manual, version 2.0.0, Technical Report, The Regents of the University of California (through Lawrence Berkeley National Laboratory), Jan. 5, 2004, 109 pages, Technical Report LBNL-54199.20What is EnergyPlus?, The Board of Trustees of the University of Illinois and The Regents of the University of California through the Ernest Orlando Lawrence Berkeley National Laboratory, described in a printed publication more than one year before Jun. 30, 2005, the effective filing date of the present application, 3 pg.21William J. Coad, PE, Vav Systems, Air Conditioning and Refrigeration Journal, Jul. 2003, pp. 1-11.* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS8090477Aug 20, 2010Jan 3, 2012Ecofactor, Inc.System and method for optimizing use of plug-in air conditioners and portable heatersUS8125447 *Dec 18, 2008Feb 28, 2012Alps Electric Co., Ltd.Coordinate input deviceUS8131497Dec 2, 2010Mar 6, 2012Ecofactor, Inc.System and method for calculating the thermal mass of a buildingUS8131506Feb 28, 2011Mar 6, 2012Ecofactor, Inc.System and method for using a network of thermostats as tool to verify peak demand reductionUS8180492Jul 13, 2009May 15, 2012Ecofactor, Inc.System and method for using a networked electronic device as an occupancy sensor for an energy management systemUS8306794 *Jun 26, 2008Nov 6, 2012International Business Machines CorporationTechniques for thermal modeling of data centers to improve energy efficiencyUS8340826Dec 16, 2011Dec 25, 2012Ecofactor, Inc.System and method for optimizing use of plug-in air conditioners and portable heatersUS8355827 *Apr 7, 2011Jan 15, 2013Energy Resource Management CorpEnergy-saving measurement, adjustment and monetization system and methodUS8370283Jul 18, 2011Feb 5, 2013Scienergy, Inc.Predicting energy consumptionUS8412488Mar 1, 2012Apr 2, 2013Ecofactor, Inc.System and method for using a network of thermostats as tool to verify peak demand reductionUS8417391 *Dec 15, 2011Apr 9, 2013Restore NvAutomated demand response energy management systemUS8423322Sep 12, 2011Apr 16, 2013Ecofactor, Inc.System and method for evaluating changes in the efficiency of an HVAC systemUS8498753May 4, 2010Jul 30, 2013Ecofactor, Inc.System, method and apparatus for just-in-time conditioning using a thermostatUS8543244 *Dec 18, 2009Sep 24, 2013Oliver Joe KeelingHeating and cooling control methods and systemsUS8556188May 26, 2010Oct 15, 2013Ecofactor, Inc.System and method for using a mobile electronic device to optimize an energy management systemUS8596550May 11, 2010Dec 3, 2013Ecofactor, Inc.System, method and apparatus for identifying manual inputs to and adaptive programming of a thermostatUS8600571 *Jun 19, 2008Dec 3, 2013Honeywell International Inc.Energy optimization systemUS8620714 *Nov 28, 2006Dec 31, 2013The Boeing CompanyPrognostic condition assessment decision aidUS8712590Dec 21, 2012Apr 29, 2014Ecofactor, Inc.System and method for optimizing use of plug-in air conditioners and portable heatersUS8731883Oct 3, 2012May 20, 2014International Business Machines CorporationTechniques for thermal modeling of data centers to improve energy efficiencyUS8738327Mar 28, 2013May 27, 2014Ecofactor, Inc.System and method for using a network of thermostats as tool to verify peak demand reductionUS8740100May 5, 2010Jun 3, 2014Ecofactor, Inc.System, method and apparatus for dynamically variable compressor delay in thermostat to reduce energy consumptionUS8751186Apr 8, 2013Jun 10, 2014Ecofactor, Inc.System and method for calculating the thermal mass of a buildingUS8793022 *Feb 26, 2010Jul 29, 2014Trane International, Inc.Automated air source and VAV box associationUS8825219Feb 27, 2013Sep 2, 2014Restore NvAutomated demand response energy management systemUS8838281Feb 27, 2013Sep 16, 2014Restore NvAutomated demand response energy management systemUS8840033Oct 8, 2013Sep 23, 2014Ecofactor, Inc.System and method for using a mobile electronic device to optimize an energy management systemUS8849630Jun 26, 2008Sep 30, 2014International Business Machines CorporationTechniques to predict three-dimensional thermal distributions in real-timeUS8886488Mar 1, 2012Nov 11, 2014Ecofactor, Inc.System and method for calculating the thermal mass of a buildingUS8924026 *Aug 22, 2011Dec 30, 2014Vigilent CorporationEnergy-optimal control decisions for systemsUS9002532Jun 26, 2012Apr 7, 2015Johnson Controls Technology CompanySystems and methods for controlling a chiller plant for a buildingUS9057649Apr 11, 2013Jun 16, 2015Ecofactor, Inc.System and method for evaluating changes in the efficiency of an HVAC systemUS9080789May 5, 2011Jul 14, 2015Greensleeves, LLCEnergy chassis and energy exchange deviceUS9134710Aug 26, 2011Sep 15, 2015Ecofactor, Inc.System and method for using ramped setpoint temperature variation with networked thermostats to improve efficiencyUS9171274 *Sep 9, 2010Oct 27, 2015Aniruddha Anil DesaiMethod and system for energy managementUS9188994Apr 28, 2014Nov 17, 2015Ecofactor, Inc.System and method for optimizing use of plug-in air conditioners and portable heatersUS9194597Nov 18, 2013Nov 24, 2015Ecofactor, Inc.System, method and apparatus for identifying manual inputs to and adaptive programming of a thermostatUS9228753 *May 7, 2012Jan 5, 2016Daikin Industries, Ltd.Ventilation systemUS9235657Mar 13, 2013Jan 12, 2016Johnson Controls Technology CompanySystem identification and model developmentUS9244470May 11, 2012Jan 26, 2016Ecofactor, Inc.System and method for using a wireless device as a sensor for an energy management systemUS9279594May 30, 2014Mar 8, 2016Ecofactor, Inc.System, method and apparatus for use of dynamically variable compressor delay in thermostat to reduce energy consumptionUS9291358Dec 12, 2014Mar 22, 2016Vigilent CorporationAccuracy-optimal control decisions for systemsUS9436179Mar 13, 2013Sep 6, 2016Johnson Controls Technology CompanySystems and methods for energy cost optimization in a building systemUS9519874Aug 30, 2012Dec 13, 2016Honeywell International Inc.HVAC controller with regression model to help reduce energy consumptionUS9581979Aug 7, 2014Feb 28, 2017Restore NvAutomated demand response energy management systemUS20080125933 *Nov 28, 2006May 29, 2008The Boeing CompanyPrognostic Condition Assessment Decision AidUS20090160766 *Dec 18, 2008Jun 25, 2009Kazuhito OhshitaCoordinate input deviceUS20090313083 *Jun 13, 2008Dec 17, 2009Honeywell International Inc.Renewable energy calculatorUS20090319090 *Jun 19, 2008Dec 24, 2009Honeywell International Inc.Energy optimization systemUS20090326879 *Jun 26, 2008Dec 31, 2009International Business Machines CorporationTechniques for Thermal Modeling of Data Centers to Improve Energy EfficiencyUS20090326884 *Jun 26, 2008Dec 31, 2009International Business Machines CorporationTechniques to Predict Three-Dimensional Thermal Distributions in Real-TimeUS20100211224 *Dec 18, 2009Aug 19, 2010EnaGea LLCHeating and cooling control methods and systemsUS20100280667 *Jul 13, 2009Nov 4, 2010John Douglas SteinbergSystem and method for using a networked electronic device as an occupancy sensor for an energy management systemUS20100282857 *May 5, 2010Nov 11, 2010Ecofactor, Inc.System, method and apparatus for dynamically variable compressor delay in thermostat to reduce energy consumptionUS20100308119 *May 11, 2010Dec 9, 2010Ecofactor, Inc.System, method and apparatus for identifying manual inputs to and adaptive programming of a thermostatUS20100318227 *May 4, 2010Dec 16, 2010Ecofactor, Inc.System, method and apparatus for just-in-time conditioning using a thermostatUS20110077896 *Dec 2, 2010Mar 31, 2011Ecofactor, Inc.System and method for calculating the thermal mass of a buildingUS20110166828 *Feb 28, 2011Jul 7, 2011Ecofactor, Inc.System and method for using a network of thermostats as tool to verify peak demand reductionUS20110213502 *Feb 26, 2010Sep 1, 2011Uden David JAutomated air source and vav box associationUS20110251933 *Apr 7, 2011Oct 13, 2011Energy Resource Management CorpEnergy-saving measurement, adjustment and monetization system and methodUS20110295430 *May 26, 2011Dec 1, 2011Andrey KouninskiApparatus And Method For Managing Heating Or Cooling Of An Area In A BuildingUS20120016524 *Jul 16, 2010Jan 19, 2012General Electric CompanyThermal time constraints for demand response applicationsUS20120101648 *Aug 22, 2011Apr 26, 2012Vigilent CorporationEnergy-Optimal Control Decisions for SystemsUS20120215369 *Sep 9, 2010Aug 23, 2012La Trobe UniversityMethod and system for energy managementUS20120259466 *Dec 16, 2011Oct 11, 2012Infosys Technologies LimitedArchitecture and method for centrally controlling a plurality of building automation systemsUS20130303074 *May 7, 2012Nov 14, 2013Daikin Industries, Ltd.Ventilation systemWO2012122234A2 *Mar 7, 2012Sep 13, 2012Callida Energy LlcSystems and methods for optimizing energy and resource management for building systemsWO2012122234A3 *Mar 7, 2012Dec 27, 2012Callida Energy LlcSystems and methods for optimizing energy and resource management for building systemsWO2014138102A1 *Mar 4, 2014Sep 12, 2014Greensleeves, LLCEnergy management systems and methods of use* Cited by examinerClassifications U.S. Classification700/276, 700/2, 236/91.00F, 165/257, 376/217International ClassificationG05B19/04, G05B19/18, G21C7/36, G05D23/19, F25B29/00Cooperative ClassificationG05B17/02, G05B13/041European ClassificationG05B13/04A, G05B17/02Legal EventsDateCodeEventDescriptionOct 3, 2014REMIMaintenance fee reminder 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