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    HVAC controller with integrated airside and waterside cost optimization
    31.
    发明授权
    HVAC controller with integrated airside and waterside cost optimization 有权

    公开(公告)号：US10761547B2

    公开(公告)日：2020-09-01

    申请号：US14694633

    申请日：2015-04-23

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Risbeck ,  Robert D. Turney ,  Christos T. Maravelias

    IPC: G05D23/19 ,  G05B15/02 ,  G05B13/04

    Abstract: A building HVAC system includes a waterside system and an airside system. The waterside system consumes one or more resources from utility providers to generate a heated and/or chilled fluid. The airside system uses the heated and/or chilled fluid to heat and/or cool a supply airflow provided to the building. A HVAC controller performs an integrated airside/waterside optimization process to simultaneously determine control outputs for both the waterside system and the airside system. The optimization process includes optimizing a predictive cost model that predicts the cost of the resources consumed by the HVAC system, subject to a set of optimization constraints including temperature constraints for the building. The HVAC controller uses the determined control outputs to control the HVAC equipment of the waterside system and the airside system.

    VARIABLE REFRIGERANT FLOW SYSTEM WITH CAPACITY LIMITS
    33.
    发明申请
    VARIABLE REFRIGERANT FLOW SYSTEM WITH CAPACITY LIMITS 审中-公开

    公开(公告)号：US20200072543A1

    公开(公告)日：2020-03-05

    申请号：US16122399

    申请日：2018-09-05

    Applicant: Johnson Controls Technology Company

    Inventor： Robert D. Turney ,  Liming Yang

    IPC: F25D29/00 ,  G06Q50/06 ,  F24F1/32

    Abstract: A variable refrigerant flow system includes one or more outdoor units and a first indoor unit of a plurality of indoor units configured to receive refrigerant from the one or more outdoor units. The first indoor unit is configured to serve a first building zone. The variable refrigerant flow system also includes a user input device configured to receive a user command requesting heating or cooling of the first building zone by the first indoor unit. The variable refrigerant flow system also includes a controller configured to receive the command from the user input device, receive an indication of a current price of energy, in response to receiving the command generate a constraint on a capacity of the one or more outdoor units based on the current price of energy, and control the one or more outdoor units to operate in accordance with the constraint.

    MODEL PREDICTIVE MAINTENANCE SYSTEM WITH AUTOMATIC SERVICE WORK ORDER GENERATION
    35.
    发明申请
    MODEL PREDICTIVE MAINTENANCE SYSTEM WITH AUTOMATIC SERVICE WORK ORDER GENERATION 审中-公开

    公开(公告)号：US20190271978A1

    公开(公告)日：2019-09-05

    申请号：US16418686

    申请日：2019-05-21

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. ElBsat ,  Michael J. Wenzel ,  Zhigang Wu ,  Yasutaka Yoshida ,  Robert D. Turney ,  Liming Yang

    IPC: G05B23/02 ,  G06Q30/02

    Abstract: An automatic work order generation system for model predictive maintenance (MPM) of building equipment including an MPM system including an equipment controller to operate the building equipment to affect an environmental condition of a building. The MPM system can perform a predictive optimization to determine a service time at which to service the building equipment. The automatic work order generation system includes an equipment service scheduler that can determine whether any service providers are available to perform equipment service within a predetermined time range of the service time. In response to determining that service providers are available to perform the equipment service, the equipment service scheduler can select a service provider and an appointment time based on one or more service provider attributes. The equipment service scheduler can generate a service work order and transmit the service work order to the service provider to schedule a service appointment.

    MODEL PREDICTIVE MAINTENANCE SYSTEM FOR BUILDING EQUIPMENT
    38.
    发明申请
    MODEL PREDICTIVE MAINTENANCE SYSTEM FOR BUILDING EQUIPMENT 审中-公开

    公开(公告)号：US20180341255A1

    公开(公告)日：2018-11-29

    申请号：US15895836

    申请日：2018-02-13

    Applicant: Johnson Controls Technology Company

    Inventor： Robert D. Turney ,  Sudhi R. Sinha

    IPC: G05B23/02 ,  G06Q10/00 ,  G06Q30/02

    Abstract: A model predictive maintenance (MPM) system for building equipment includes an equipment controller configured to operate the building equipment to affect a variable state or condition in a building and an operational cost predictor configured to predict a cost of operating the building equipment over a duration of an optimization period. The MPM system includes a maintenance cost predictor configured to predict a cost of performing maintenance on the building equipment over the duration of the optimization period and an objective function optimizer configured to optimize an objective function to predict a total cost associated with the building equipment over the duration of the optimization period. The objective function includes the predicted cost of operating the building equipment and the predicted cost of performing maintenance on the building equipment.

    System identification and model development
    40.
    发明授权
    System identification and model development 有权

    公开(公告)号：US10088814B2

    公开(公告)日：2018-10-02

    申请号：US14970187

    申请日：2015-12-15

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel ,  Robert D. Turney

    IPC: G06F17/50 ,  G05B13/02

    Abstract: A controller for a building system receives training data that includes input data and output data. The output data measures a state of the building system affected by both the input data and an extraneous disturbance. The controller performs a two-stage optimization process to identify system parameters and Kalman gain parameters of a dynamic model for the building system. During the first stage, the controller filters the training data to remove an effect of the extraneous disturbance from the output data and uses the filtered training data to identify the system parameters. During the second stage, the controller uses the non-filtered training data to identify the Kalman gain parameters. The controller uses the dynamic model with the identified system parameters and Kalman gain parameters to generate a setpoint for the building system. The building system uses the setpoint to affect the state measured by the output data.

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