公开(公告)号：US10175681B2

公开(公告)日：2019-01-08

申请号：US14634609

申请日：2015-02-27

Applicant: Johnson Controls Technology Company

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

IPC: G06F19/00 ,  G05B19/418 ,  G05B13/02 ,  G05F1/66 ,  G05B13/04 ,  G05B15/02 ,  G06N99/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q50/06

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 high level optimization module is configured to optimize the objective function over the optimization period subject to load equality constraints and capacity constraints on the central plant equipment to determine an optimal distribution of the building energy loads over multiple groups of the central plant equipment.

公开(公告)号：US10146237B2

公开(公告)日：2018-12-04

申请号：US15625830

申请日：2017-06-16

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: G05D23/19 ,  G05B19/048 ,  G05B19/042 ,  F24F11/30 ,  F24F11/62 ,  F24F110/10 ,  F24F110/12 ,  F24F140/50 ,  F24F11/46 ,  F24F11/65 ,  F24F140/60

Abstract: A thermostat includes an equipment controller and a model predictive controller. The equipment controller is configured to drive the temperature of a building zone to an optimal temperature setpoint by operating HVAC equipment to provide heating or cooling to the building zone. The model predictive controller is configured to determine the optimal temperature setpoint by generating a cost function that accounts for a cost operating the HVAC equipment during each of a plurality of time steps in an optimization period, using a predictive model to predict the temperature of the building zone during each of the plurality of time steps, and optimizing the cost function subject to a constraint on the predicted temperature of the building zone to determine optimal temperature setpoints for each of the time steps.

公开(公告)号：US10120375B2

公开(公告)日：2018-11-06

申请号：US14694660

申请日：2015-04-23

Applicant: Johnson Controls Technology Company

Inventor： Andrew J. Przybylski ,  Michael J. Wenzel ,  Andrew J. Boettcher

IPC: F24F11/00 ,  G05B23/02 ,  F24F11/30 ,  F24F110/20

Abstract: A building management system (BMS) includes a controller that monitors performance values for a controlled process during a first time period relative to initial outlier detection limits and generates new outlier detection limits for the controlled process in response to a detected change in the controlled process during the first time period. The controller monitors the performance values relative to the new outlier detection limits during a second time period to detect outliers during the second time period. The controller calculates a confidence difference for an estimated confidence parameter based on a number of outliers detected using the new outlier detection limits during the second time period. The controller adjusts the new outlier detection limits in response to the confidence difference dropping below a threshold value.

公开(公告)号：US10007259B2

公开(公告)日：2018-06-26

申请号：US15068470

申请日：2016-03-11

Applicant: Johnson Controls Technology Company

Inventor： Robert D. Turney ,  Michael J. Wenzel

IPC: G05B15/02 ,  G05B19/042 ,  G05B23/02

CPC classification number: G05B23/02 ,  G05B15/02 ,  G05B19/042 ,  G05B2219/2639 ,  G05B2219/2642 ,  Y02B70/32 ,  Y02B70/3225 ,  Y02B70/3241 ,  Y04S20/20 ,  Y04S20/222 ,  Y04S20/224 ,  Y04S20/40 ,  Y04S20/44 ,  Y04S20/46

Abstract: A controller is configured to use an energy cost function to predict a total cost of energy purchased from an energy provider as a function of one or more setpoints provided by the controller. The energy cost function includes a demand charge term defining a cost per unit of power corresponding to a maximum power usage of the building system. The controller is configured to linearize the demand charge term by imposing demand charge constraints and to mask each of the demand charge constraints that applies to an inactive pricing period. The controller is configured to determine optimal values of the one or more setpoints by performing an optimization procedure that minimizes the total cost of energy subject to the demand charge constraints and to provide the optimal values of the one or more setpoints to equipment of the building system that operate to affect the maximum power usage.

公开(公告)号：US20180075549A1

公开(公告)日：2018-03-15

申请号：US15808388

申请日：2017-11-09

Applicant: Johnson Controls Technology Company

Inventor： Robert D. Turney ,  Michael J. Wenzel

IPC: G06Q50/06 ,  G06Q20/14

CPC classification number: G06Q50/06 ,  G06Q20/085 ,  G06Q20/145

Abstract: A cascaded model predictive control system includes an inner controller and an outer controller. The outer controller determines an amount of power to defer from a predicted power usage to optimize a total cost of power usage. A power setpoint is calculated based on a difference between the predicted power usage and the amount of power to defer. The inner controller determines an operating setpoint for building equipment in order to achieve the power setpoint.

公开(公告)号：US20180054061A1

公开(公告)日：2018-02-22

申请号：US15663496

申请日：2017-07-28

Applicant: Johnson Controls Technology Company

Inventor： Radu Dorneanu ,  Michael J. Wenzel ,  MOHAMMAD N. ELBSAT ,  Kirk H. Drees ,  Andrew J. Przybylski

IPC: H02J3/38 ,  H02J7/00 ,  H02J7/04 ,  G05B13/02

Abstract: An optimization controller for a battery includes a high level controller configured to receive a regulation signal from an incentive provider at a data fusion module, determine statistics of the regulation signal, and use the statistics of the regulation signal to generate a frequency response midpoint. The optimization controller further includes a low level controller configured to use the frequency response midpoint to determine optimal battery power setpoints and use the optimal battery power setpoints to control an amount of electric power stored or discharged from the battery during a frequency response period.

公开(公告)号：US20180034285A1

公开(公告)日：2018-02-01

申请号：US15406593

申请日：2017-01-13

Applicant: Johnson Controls Technology Company

Inventor： Ryan A. Baumgartner ,  Michael J. Wenzel

IPC: H02J7/00 ,  H02J7/35

CPC classification number: H02J7/007 ,  H01M10/441 ,  H01M10/48 ,  H01M2220/10 ,  H02J3/32 ,  H02J7/0021 ,  H02J7/35

Abstract: An electrical energy storage system includes a battery configured to store electrical energy and discharge the stored electrical energy to an external system, a switch electrically connected to the battery and operable to connect the battery to the external system and disconnect the battery from the external system, a sensor configured to measure an open circuit voltage of the battery while the battery is disconnected from the external system, and a controller. The controller is configured to predict usage of the battery at a plurality of future times, schedule a time to disconnect the battery from the external system based on the predicted usage of the battery at the plurality of future times, operate the switch to disconnect the battery at the scheduled time, and obtain a measurement of the open circuit voltage of the battery while the battery is disconnected.

公开(公告)号：US20180004173A1

公开(公告)日：2018-01-04

申请号：US15635754

申请日：2017-06-28

Applicant: Johnson Controls Technology Company

Inventor： Nishith R. Patel ,  Matthew J. Ellis ,  Michael J. Wenzel ,  Robert D. Turney ,  Brett M. Lenhardt

IPC: G05B13/04 ,  F24F11/00 ,  G05D7/06

Abstract: A model predictive control system is used to optimize energy cost in a variable refrigerant flow (VRF) system. The VRF system includes an outdoor subsystem and a plurality of indoor subsystems. The model predictive control system includes a high-level model predictive controller (MPC) and a plurality of low-level indoor MPCs. The high-level MPC performs a high-level optimization to generate an optimal indoor subsystem load profile for each of the plurality of indoor subsystems. The optimal indoor subsystem load profiles optimize energy cost. Each of the low-level indoor MPCs performs a low-level optimization to generate optimal indoor setpoints for one or more indoor VRF units of the corresponding indoor subsystem. The indoor setpoints can include temperature setpoints and/or refrigerant flow setpoints for the indoor VRF units.

公开(公告)号：US20170102433A1

公开(公告)日：2017-04-13

申请号：US15247777

申请日：2016-08-25

Applicant: Johnson Controls Technology Company

Inventor： Michael J. Wenzel ,  Kirk H. Drees

IPC: G01R31/36 ,  H02J3/38 ,  G05B13/04 ,  H02M7/44

CPC classification number: G01R31/3651 ,  G05B13/048 ,  G06Q50/06 ,  H02J3/32 ,  H02J3/383 ,  H02J2003/007 ,  H02M7/44 ,  Y02B10/14 ,  Y02E40/76 ,  Y02E60/76 ,  Y04S10/545 ,  Y04S40/22

Abstract: A frequency response optimization includes a battery that stores and discharges electric power, a power inverter that uses battery power setpoints to control an amount of the electric power stored or discharged from the battery, and a frequency response controller. The frequency response controller receives a regulation signal from an incentive provider, predicts future values of the regulation signal, and uses the predicted values of the regulation signal to generate the battery power setpoints for the power inverter.

公开(公告)号：US20170102162A1

公开(公告)日：2017-04-13

申请号：US15247875

申请日：2016-08-25

Applicant: Johnson Controls Technology Company

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

IPC: F24F11/00 ,  G05B13/02 ,  G05B19/042 ,  H02J7/00 ,  H02J3/38

CPC classification number: F24F11/65 ,  F24F11/30 ,  G05B13/0205 ,  G05B13/048 ,  G05B15/02 ,  G05B19/0428 ,  G05B2219/2614 ,  G05B2219/2642 ,  G05B2219/39361 ,  H02J3/00 ,  H02J3/008 ,  H02J3/14 ,  H02J3/28 ,  H02J3/32 ,  H02J3/383 ,  H02J7/007 ,  H02J7/35 ,  H02J13/0086 ,  H02J15/00 ,  H02J2003/003 ,  H02J2003/007 ,  H02J2003/146 ,  Y02B10/14 ,  Y02B70/3225 ,  Y02B70/3241 ,  Y02B90/222 ,  Y02E10/563 ,  Y02E10/566 ,  Y02E40/72 ,  Y02E70/30 ,  Y04S10/123 ,  Y04S20/12 ,  Y04S20/222 ,  Y04S20/224 ,  Y04S20/227

Abstract: A central plant that generates and provides resources to a building. The central plant includes an electrical energy storage subplant configured to store electrical energy purchased from a utility and to discharge the stored electrical energy. The central plant includes a plurality of generator subplants that consume one or more input resources. The central plant includes a controller configured to determine, for each time step within a time horizon, an optimal allocation of the input resources and the output resources for each of the subplants in order to optimize a total monetary value of operating the central plant over the time horizon. The total monetary value includes revenue from participating in incentive-based demand response programs as well as costs associated with resource consumption, equipment degradation, and losses in battery capacity.