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    Building energy storage system with multiple demand charge cost optimization
    161.
    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.

    HIGH LEVEL CENTRAL PLANT OPTIMIZATION
    163.
    发明申请
    HIGH LEVEL CENTRAL PLANT OPTIMIZATION 审中-公开

    公开(公告)号：US20190107825A1

    公开(公告)日：2019-04-11

    申请号：US16214984

    申请日：2018-12-10

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel ,  Robert D. Turney ,  Kirk H. Drees ,  Matthew J. Asmus

    IPC: G05B19/418 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q50/06 ,  G05B15/02 ,  G05F1/66 ,  G05B13/02 ,  G05B13/04 ,  G06N20/00

    Abstract: A controller for equipment obtains utility rate data indicating a price of one or more resources consumed by the equipment to serve energy loads. The controller generates an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the one or more resources consumed by the equipment at each of a plurality of time steps. The controller optimizes the objective function to determine a distribution of predicted energy loads across the equipment at each of the plurality of time steps. Load equality constraints on the objective function ensure that the distribution satisfies the predicted energy loads at each of the plurality of time steps. The controller operates the equipment to achieve the distribution of the predicted energy loads at each of the plurality of time steps.

    SMART THERMOSTAT WITH MODEL PREDICTIVE CONTROL
    164.
    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
    165.
    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.

    Systems and methods for implementing energy conservation measures in a building
    167.
    发明授权
    Systems and methods for implementing energy conservation measures in a building 有权

    公开(公告)号：US10095820B2

    公开(公告)日：2018-10-09

    申请号：US14853957

    申请日：2015-09-14

    Applicant: Johnson Controls Technology Company

    Inventor： Kirk H. Drees ,  Michael J. Wenzel

    IPC: G06F17/50 ,  G06Q50/08 ,  G06Q10/06 ,  G06F17/10

    Abstract: A set of energy use model parameters for each of a plurality of buildings is used to determine a typical set of energy use model parameters for the plurality of buildings. A distance between the typical set of energy use model parameters and the set of energy use model parameters for each of the plurality of buildings is determined. Each distance is compared to a critical value. A building is identified as a candidate for energy conservation measures in response to the distance for the building exceeding the critical value. Energy conservation measures are implemented in the identified building. Implementing energy conservation measures may include replacing existing HVAC equipment in the identified building with new energy-efficient HVAC equipment.

    BUILDING AUTOMATION SYSTEM WITH AN ENERGY OPTIMIZATION BUILDER AND GENERIC DATA MODEL DESIGNER
    168.
    发明申请
    BUILDING AUTOMATION SYSTEM WITH AN ENERGY OPTIMIZATION BUILDER AND GENERIC DATA MODEL DESIGNER 审中-公开

    公开(公告)号：US20180260101A1

    公开(公告)日：2018-09-13

    申请号：US15896745

    申请日：2018-02-14

    Applicant: Johnson Controls Technology Company

    Inventor： Andrew J. Przybylski ,  Todd Schluechtermann ,  John H. Burroughs ,  Jon T. Mueller ,  Michael J. Wenzel ,  Matthew J. Ellis

    IPC: G06F3/0484 ,  H04L12/28 ,  G06F3/0481

    Abstract: A building management system for generating a building model for a building and operating building equipment of the building based on the building model. The system includes a processing circuit configured to receive a context, wherein the context includes metadata defining the building model for the building and generate a building model editor interface for viewing and editing the received context, wherein the building model interface includes building elements for the building model, wherein the building elements are based on the received context and represent the building equipment. The processing circuit is configured to receive user edits of the context via the building model interface, wherein the user edits include edits to the building elements, generate an updated context based on the user edits of the context, and deploy the updated context to control environmental conditions of the building with the building equipment based on the updated context.

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