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    Systems and methods for generating an energy usage model for a building
    81.
    发明授权
    Systems and methods for generating an energy usage model for a building 有权
    用于生成建筑物能量使用模型的系统和方法

    公开(公告)号：US09575475B2

    公开(公告)日：2017-02-21

    申请号：US15016243

    申请日：2016-02-04

    Applicant: Johnson Controls Technology Company

    Inventor： Kirk H. Drees ,  James P. Kummer ,  Michael J. Wenzel

    IPC: G06F7/60 ,  G06F17/10 ,  G05B13/04 ,  G06Q10/06 ,  G06Q50/06 ,  G05F1/66 ,  G06F17/50 ,  H02J13/00 ,  H02J3/00

    CPC classification number: G05B13/048 ,  G05F1/66 ,  G06F17/5009 ,  G06Q10/06 ,  G06Q50/06 ,  H02J13/0013 ,  H02J2003/003 ,  H02J2003/007 ,  Y02B90/2607 ,  Y02E60/76 ,  Y04S10/54 ,  Y04S40/12 ,  Y04S40/22

    Abstract: A building management system (BMS) includes a baseline model generator configured to receive an initial set of predictor variables for potential use in an energy usage model for a building, generate a first set of coefficients for the baseline energy usage model based on the initial set of predictor variables, remove one of the predictor variables from the initial set of predictor variables to create a subset of the initial set of predictor variables, generate a second set of coefficients for the baseline energy usage model based on the subset of the initial set of predictor variables, calculate a test statistic for the removed variable using a difference between the first set of coefficients and the second set of coefficients, and automatically select the removed predictor variable for use in the baseline energy usage model in response the test statistic exceeding a critical value.

    Abstract translation: 建筑物管理系统（BMS）包括基准模型发生器，其被配置为接收用于建筑物的能量使用模型中的潜在用途的初始预测变量集合，基于初始设置生成用于基线能量使用模型的第一组系数 从预测变量的初始集合中去除预测变量中的一个，以创建初始预测变量集合的子集，基于初始集合的初始集合的子集生成用于基线能量使用模型的第二组系数 预测变量，使用第一组系数和第二组系数之间的差异来计算移除的变量的检验统计量，并且自动选择用于基线能量使用模型中的去除的预测变量，以响应超过临界值的检验统计量 值。

    SYSTEM IDENTIFICATION AND MODEL DEVELOPMENT
    82.
    发明申请
    SYSTEM IDENTIFICATION AND MODEL DEVELOPMENT 审中-公开
    系统识别与模式开发

    公开(公告)号：US20160098022A1

    公开(公告)日：2016-04-07

    申请号：US14970187

    申请日：2015-12-15

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel ,  Robert D. Turney

    IPC: G05B13/02

    CPC classification number: G05B13/0265 ,  G05B13/048 ,  G05B15/02 ,  G05B2219/2642 ,  G06F17/50 ,  G06F17/5004

    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.

    Abstract translation: 用于建筑系统的控制器接收包括输入数据和输出数据的训练数据。 输出数据测量受输入数据和外部干扰影响的建筑系统的状态。 控制器执行两阶段优化过程，以识别建筑系统的动态模型的系统参数和卡尔曼增益参数。 在第一阶段，控制器对训练数据进行过滤，以消除输出数据中的外部干扰的影响，并使用过滤的训练数据来识别系统参数。 在第二阶段期间，控制器使用未滤波的训练数据来识别卡尔曼增益参数。 控制器使用具有识别的系统参数和卡尔曼增益参数的动态模型来为建筑系统生成设定值。 建筑系统使用设定值来影响输出数据测量的状态。

    System identification and model development
    84.
    发明授权
    System identification and model development 有权
    系统识别和模型开发

    公开(公告)号：US09235657B1

    公开(公告)日：2016-01-12

    申请号：US13802233

    申请日：2013-03-13

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel ,  Robert D. Turney

    IPC: G06F17/50

    CPC classification number: G05B13/0265 ,  G05B13/048 ,  G05B15/02 ,  G05B2219/2642 ,  G06F17/50 ,  G06F17/5004

    Abstract: Methods for system identification are presented using model predictive control to frame a gray-box parameterized state space model. System parameters are identified using an optimization procedure to minimize a first error cost function within a range of filtered training data. Disturbances are accounted for using an implicit integrator within the system model, as well as a parameterized Kalman gain. Kalman gain parameters are identified using an optimization procedure to minimize a second error cost function within a range of non-filtered training data. Recursive identification methods are presented to provide model adaptability using an extended Kalman filter to estimate model parameters and a Kalman gain to estimate system states.

    Abstract translation: 使用模型预测控制来呈现系统识别的方法来构建灰盒参数化状态空间模型。 使用优化程序来识别系统参数，以使过滤的训练数据的范围内的第一误差成本函数最小化。 使用系统模型中的隐式积分器以及参数化卡尔曼增益来解决干扰。 使用优化过程来识别卡尔曼增益参数，以使非滤波训练数据的范围内的第二误差成本函数最小化。 提出递归识别方法，以使用扩展卡尔曼滤波器来估计模型参数和卡尔曼增益来估计系统状态来提供模型适应性。

    INCORPORATING A DEMAND CHARGE IN CENTRAL PLANT OPTIMIZATION
    85.
    发明申请
    INCORPORATING A DEMAND CHARGE IN CENTRAL PLANT OPTIMIZATION 审中-公开
    在中央工厂优化中纳入需求费用

    公开(公告)号：US20150316901A1

    公开(公告)日：2015-11-05

    申请号：US14634599

    申请日：2015-02-27

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel ,  Kirk H. Drees

    IPC: G05B13/02 ,  G05F1/66

    CPC classification number: G05B19/418 ,  G05B13/021 ,  G05B13/048 ,  G05B15/02 ,  G05B2219/2642 ,  G05B2219/31414 ,  G05B2219/32021 ,  G05F1/66 ,  G06N20/00 ,  G06N99/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q50/06 ,  Y02P70/161 ,  Y02P80/114 ,  Y02P90/86

    Abstract: An optimization system for a central plant includes a processing circuit configured to receive load prediction data indicating building energy loads and utility rate data indicating a price of one or more resources consumed by equipment of the central plant to serve the building energy loads. The optimization system includes a high level optimization module configured to generate an objective function that expresses a total monetary cost of operating the central plant over an optimization period as a function of the utility rate data and an amount of the one or more resources consumed by the central plant equipment. The optimization system includes a demand charge module configured to modify the objective function to account for a demand charge indicating a cost associated with maximum power consumption during a demand charge period. The high level optimization module is configured to optimize the objective function over the demand charge period.

    Abstract translation: 用于中央设备的优化系统包括处理电路，其被配置为接收指示建筑物能量负载的负荷预测数据和表示中央设备的设备消耗的一个或多个资源的价格的效用率数据，以用于建筑物能量负荷。 优化系统包括高级优化模块，其被配置为生成目标函数，该目标函数表示在优化周期内操作中央工厂的总货币成本，作为效用率数据的函数，以及所述一个或多个资源消耗的量 中央工厂设备。 所述优化系统包括需求费用模块，所述需求费用模块被配置为修改所述目标函数以考虑在需求充电期间指示与最大功耗相关联的成本的需求费用。 高级优化模块被配置为在需求充电期间优化目标函数。

    SYSTEMS AND METHODS FOR CONTROLLING ENERGY USE IN A BUILDING MANAGEMENT SYSTEM USING ENERGY BUDGETS
    86.
    发明申请
    SYSTEMS AND METHODS FOR CONTROLLING ENERGY USE IN A BUILDING MANAGEMENT SYSTEM USING ENERGY BUDGETS 有权
    使用能源预算控制建筑管理系统能源使用的系统和方法

    公开(公告)号：US20140249680A1

    公开(公告)日：2014-09-04

    申请号：US14276745

    申请日：2014-05-13

    Applicant: Johnson Controls Technology Company

    Inventor： Michael J. Wenzel

    IPC: G05F1/66 ,  G05D23/19

    CPC classification number: G05F1/66 ,  F24F11/30 ,  F24F11/62 ,  G05D23/1917 ,  H02J3/14 ,  H02J2003/007 ,  Y02B70/3225 ,  Y02B70/3275 ,  Y04S20/222 ,  Y04S20/244

    Abstract: Systems and methods for limiting power consumption by a heating, ventilation, and air conditioning (HVAC) subsystem of a building are shown and described. A mathematical linear operator is found that transforms the unused or deferred cooling power usage of the HVAC system based on pre-determined temperature settings to a target cooling power usage. The mathematical operator is applied to the temperature settings to create a temperature setpoint trajectory expected to provide the target cooling power usage.

    Abstract translation: 显示和描述了用于限制建筑物的加热，通风和空调（HVAC）子系统的功率消耗的系统和方法。 发现一种数学线性运算符，其将基于预定温度设置的HVAC系统的未使用或延迟的冷却功率使用转换为目标冷却功率使用。 将数学运算符应用于温度设置，以创建预期提供目标冷却功率使用的温度设定点轨迹。

    SYSTEMS AND METHODS FOR EVALUATING A FAULT CONDITION IN A BUILDING
    87.
    发明申请
    SYSTEMS AND METHODS FOR EVALUATING A FAULT CONDITION IN A BUILDING 有权
    用于评估建筑物中的故障状态的系统和方法

    公开(公告)号：US20140222394A1

    公开(公告)日：2014-08-07

    申请号：US13759933

    申请日：2013-02-05

    Applicant: JOHNSON CONTROLS TECHNOLOGY COMPANY

    Inventor： Kirk H. Drees ,  Michael J. Wenzel

    IPC: G06F17/50

    CPC classification number: G06F17/5009 ,  G06Q10/0635

    Abstract: Systems and methods for evaluating a fault condition in a building include determining a change to energy use model parameters attributable to the fault condition. The change to the energy use model parameters are used to calculate a corresponding change to the building's energy consumption.

    Abstract translation: 用于评估建筑物中的故障状况的系统和方法包括确定归因于故障状况的能量使用模型参数的变化。 能源使用模型参数的变化用于计算建筑物能源消耗的相应变化。

    Model predictive maintenance system with integrated measurement and verification functionality
    90.
    发明授权
    Model predictive maintenance system with integrated measurement and verification functionality 有权

    公开(公告)号：US11416955B2

    公开(公告)日：2022-08-16

    申请号：US16687571

    申请日：2019-11-18

    Applicant: Johnson Controls Technology Company

    Inventor： Mohammad N. Elbsat ,  Michael J. Wenzel ,  Jingduo Fan ,  Robert D. Turney

    IPC: G06Q10/04 ,  G06Q10/00 ,  G06Q50/16 ,  G06N5/02

    Abstract: A model predictive maintenance system for building equipment including one or more processing circuits including processors and memory storing instructions that, when executed by the processors, cause the processors to perform operations. The operations include obtaining an objective function that defines a cost of operating the building equipment and performing maintenance on the building equipment as a function of operating decisions and maintenance decisions for the building equipment for time steps within a time period. The operations include performing an optimization of the objective function to generate a maintenance and replacement strategy for the building equipment over a duration of an optimization period. The operations include estimating a savings loss predicted to result from a deviation from the maintenance and replacement strategy. The operations include adjusting an amount of savings expected to be achieved by energy conservation measures for the building equipment based on the savings loss.

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