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    Building control system with empirical uncertainty determination for energy use model parameters
    33.
    发明授权
    Building control system with empirical uncertainty determination for energy use model parameters 有权

    公开(公告)号：US10558180B2

    公开(公告)日：2020-02-11

    申请号：US15144792

    申请日：2016-05-02

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. ElBsat ,  Michael J. Wenzel

    IPC: G05B13/04 ,  G06F17/16 ,  G06N7/00 ,  G05B15/02 ,  G05F1/66

    Abstract: A building control system uses an empirical technique to determine the uncertainty in parameters of an energy use model. The energy use model is used to predict energy consumption of a building site as a function of the model parameters and one or more predictor variables. The empirical technique includes obtaining a set of data points, each of the data points including a value for the one or more predictor variables and an associated energy consumption value for the building site. Multiple samples are generated from the set of data points, each of the multiple samples including a plurality of data points selected from the set of data points. For each of the multiple samples, the model parameters are estimated using the plurality of data points included in the sample. The uncertainty in the model parameters is determined using the multiple estimates of the model parameters.

    BUILDING CONTROL SYSTEM WITH AUTOMATIC COMFORT CONSTRAINT GENERATION
    34.
    发明申请
    BUILDING CONTROL SYSTEM WITH AUTOMATIC COMFORT CONSTRAINT GENERATION 审中-公开

    公开(公告)号：US20190338974A1

    公开(公告)日：2019-11-07

    申请号：US16405724

    申请日：2019-05-07

    Applicant: Johnson Controls Technology Company

    Inventor： Robert D. Turney ,  Mohammad N. ElBsat ,  Matthew J. Ellis ,  Anas W. I. Alanqar ,  Michael J. Wenzel

    IPC: F24F11/47 ,  F24F11/56 ,  F24F11/64 ,  F24F11/65 ,  F24F11/70 ,  G05B19/042

    Abstract: A controller for maintaining occupant comfort in a space of a building. The controller includes processors and non-transitory computer-readable media storing instructions that, when executed by the processors, cause the processors to perform operations. The operations include obtaining building data and obtaining occupant comfort data. The operations include generating an occupant comfort model relating the building data to a level of occupant comfort within the space based on the building data and the occupant comfort data. The operations include generating time-varying comfort constraint for an environmental condition of the space using the occupant comfort model and include performing a cost optimization of a cost function of operating building equipment over a time duration to determine a setpoint for the building equipment. The operations include operating the building equipment based on the setpoint to affect the variable state or condition of the space.

    Building energy cost optimization system with asset sizing
    36.
    发明授权
    Building energy cost optimization system with asset sizing 有权

    公开(公告)号：US10359748B2

    公开(公告)日：2019-07-23

    申请号：US15426962

    申请日：2017-02-07

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. ElBsat ,  Michael J. Wenzel

    IPC: G05B17/02 ,  G05B13/02 ,  F24F11/30 ,  G06Q30/02 ,  F24F140/50 ,  F24F11/47 ,  F24F11/46

    Abstract: An energy cost optimization system for a building includes HVAC equipment and a controller. The controller is configured to generate a cost function defining a cost of operating the HVAC equipment as a function of one or more energy load setpoints. The controller is configured to modify the cost function to account for both an initial purchase cost of a new asset to be added to the HVAC equipment and an effect of the new asset on the cost of operating the HVAC equipment. Both the initial purchase cost of the new asset and the effect of the new asset on the cost of operating the HVAC equipment are functions of one or more asset size variables. The controller is configured to perform an optimization using the modified cost function to determine optimal values for decision variables including the energy load setpoints and the asset size variables.

    Building energy storage system with multiple demand charge cost optimization
    37.
    发明授权
    Building energy storage system with multiple demand charge cost optimization 有权

    公开(公告)号：US10282796B2

    公开(公告)日：2019-05-07

    申请号：US15405236

    申请日：2017-01-12

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. ElBsat ,  Michael J. Wenzel ,  Robert D. Turney

    IPC: G06Q50/06 ,  G05B13/02 ,  G06Q30/02

    Abstract: An energy storage system includes a battery and an energy storage controller. The battery is configured to store electrical energy purchased from a utility and to discharge the stored electrical energy for use in satisfying a building energy load. The energy storage controller is configured to generate a cost function including multiple demand charges. Each of the demand charges corresponds to a demand charge period and defines a cost based on a maximum amount of the electrical energy purchased from the utility during any time step within the corresponding demand charge period. The controller is configured to modify the cost function by applying a demand charge mask to each of the multiple demand charges. The demand charge masks cause the controller to disregard the electrical energy purchased from the utility during any time steps that occur outside the corresponding demand charge period when calculating a value for the demand charge.

    SMART THERMOSTAT WITH MODEL PREDICTIVE CONTROL
    38.
    发明申请
    SMART THERMOSTAT WITH MODEL PREDICTIVE CONTROL 审中-公开

    公开(公告)号：US20190078801A1

    公开(公告)日：2019-03-14

    申请号：US16185274

    申请日：2018-11-09

    Applicant: Johnson Controls Technology Company

    Inventor： Robert D. Turney ,  Matthew J. Ellis ,  Michael J. Wenzel ,  Mohammad N. ElBsat ,  Juan Esteban Tapiero Bernal ,  Brennan H. Fentzlaff

    IPC: F24F11/30 ,  G05D23/19

    Abstract: A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

    BUILDING ENERGY OPTIMIZATION SYSTEM WITH ECONOMIC LOAD DEMAND RESPONSE (ELDR) OPTIMIZATION
    39.
    发明申请
    BUILDING ENERGY OPTIMIZATION SYSTEM WITH ECONOMIC LOAD DEMAND RESPONSE (ELDR) OPTIMIZATION 审中-公开

    公开(公告)号：US20180357577A1

    公开(公告)日：2018-12-13

    申请号：US15616616

    申请日：2017-06-07

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. ElBsat ,  Michael J. Wenzel

    IPC: G06Q10/04 ,  G06Q50/06 ,  F24F11/00

    CPC classification number: G06Q10/04 ,  G06Q50/06 ,  H02J3/008 ,  H02J3/14 ,  H02J2003/007

    Abstract: An energy cost optimization system for a building includes HVAC equipment configured to operate in the building and a controller. The controller is configure to generate a cost function defining a cost of operating the HVAC equipment over an optimization period as a function of one or more electric loads for the HVAC equipment. The controller is further configured to generate participation hours. The participation hours indicate one or more hours that the HVAC equipment will participate in an economic load demand response (ELDR) program. The controller is further configured to generate an ELDR term based on the participation hours, the ELDR term indicating revenue generated by participating in the ELDR program. The controller is further configured to modify the cost function to include the ELDR term and perform an optimization using the modified cost function to determine an optimal electric load for each hour of the participation hours.

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