Building control system with smart edge devices having embedded model predictive control

    公开(公告)号:US11445024B2

    公开(公告)日:2022-09-13

    申请号:US16695519

    申请日:2019-11-26

    Abstract: A smart edge controller for building equipment that operates to affect a variable state or condition within 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 including obtaining sensor data indicating environmental conditions of the building and include determining an amount of available processing resources at the smart edge controller or at the building equipment. The operations include automatically scaling a level of complexity of an optimization of a cost function based on the available processing resources and include performing the optimization of the cost function at the automatically scaled level of complexity to generate a first setpoint trajectory. The first setpoint trajectory includes operating setpoints for the building equipment at time steps within an optimization period. The operations include operating the building equipment based on the first setpoint trajectory.

    Central plant control system with equipment maintenance evaluation

    公开(公告)号:US11379935B2

    公开(公告)日:2022-07-05

    申请号:US16112582

    申请日:2018-08-24

    Abstract: A control system for cost optimal operation of an energy facility including equipment covered by a maintenance contract includes equipment configured to operate during an optimization period and a controller. The controller modifies a cost function to include a maintenance cost term that defines a maintenance cost as a function of a rate variable and an equipment usage variable. The controller simulates a cost of operating the energy facility over the optimization period at each of a plurality of different values of the rate variable, selects a value of the rate variable that results in a lowest cost of operating the energy facility over the optimization period, performs an online optimization of the cost function with the rate variable set to the selected value to generate one or more setpoints for the equipment, and operates the equipment during the optimization period in accordance with the generated setpoints.

    Model predictive maintenance system with incentive incorporation

    公开(公告)号:US11120411B2

    公开(公告)日:2021-09-14

    申请号:US16449198

    申请日:2019-06-21

    Abstract: A model predictive maintenance system for building equipment including an equipment controller to operate the building equipment to affect a variable state or condition in a building. The system includes an operational cost predictor to predict a cost of operating the building equipment over a duration of an optimization period, a maintenance cost predictor to predict a cost of performing maintenance on the building equipment, and a cost incentive manager to determine whether any cost incentives are available and, in response to a determination that cost incentives are available, identify the cost incentives. The system includes an objective function optimizer 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, the predicted cost of performing maintenance on the building equipment, and, if available, the cost incentives.

    Central plant with asset allocator
    186.
    发明授权

    公开(公告)号:US10956842B2

    公开(公告)日:2021-03-23

    申请号:US16601377

    申请日:2019-10-14

    Abstract: A controller for central plant equipment obtains a model of one or more sources configured to supply input resources, one or more subplants configured to convert the input resources to output resources, and one or more sinks configured to consume the output resources. The controller generates a resource balance constraint that requires balance between a first amount of each resource and a second amount of each resource. The first amount of each resource includes a sum of an amount of the resource supplied by the sources and an amount of the resource produced by the subplants. The second amount of each resource includes a sum of an amount of the resource consumed by the subplants and an amount of the resource consumed by the sinks. The controller performs an optimization of an objective function subject to the resource balance constraint to determine target amounts of each resource to be produced or consumed by the central plant equipment at a plurality of times within an optimization period. The controller controls the central plant equipment to produce or consume the target amounts of each resource at the plurality of times within the optimization period.

    CENTRAL PLANT CONTROL SYSTEM WITH GEOMETRIC MODELING OF OPERATIONAL SEQUENCES

    公开(公告)号:US20210055702A1

    公开(公告)日:2021-02-25

    申请号:US16692346

    申请日:2019-11-22

    Abstract: A method for operating equipment according to sequence of operation using geometric models including obtaining a first geometric model for a first set of equipment and a second geometric model for a second set of equipment, the first set of equipment and the second set of equipment defined by the sequence of operation for the equipment, locating, on the first geometric model, a first nearest operating point based on a desired operating point, generating a first modified geometric model by removing one or more operating points that do not satisfy the first nearest operating point, generating a merged geometric model by merging the first modified geometric model with the second geometric model, locating a second nearest operating point based on a modified desired operating point, and operating the equipment in accordance with the first nearest operating point and the second nearest operating point.

    BUILDING CONTROL SYSTEM WITH HEAT LOAD ESTIMATION USING DETERMINISTIC AND STOCHASTIC MODELS

    公开(公告)号:US20200371482A1

    公开(公告)日:2020-11-26

    申请号:US16418715

    申请日:2019-05-21

    Abstract: An environmental control system for a building including building equipment operable to affect a variable state or condition of the building. The system includes a controller including a processing circuit. The processing circuit can obtain training data relating to operation of the building equipment and can perform a system identification process to identify parameters of a system model using the training data. The processing circuit can augment the system model with a disturbance model and estimate values of a historical heat disturbance in the training data based on the augmented system model. The processing circuit can train one or more heat disturbance models based on the training data and the estimated values. The processing circuit can predict a heat disturbance using the augmented system model along with the one or more heat disturbance models and can control the building equipment based on the predicted heat disturbance.

    BUILDING CONTROL SYSTEM WITH HEAT DISTURBANCE ESTIMATION AND PREDICTION

    公开(公告)号:US20200370771A1

    公开(公告)日:2020-11-26

    申请号:US16590783

    申请日:2019-10-02

    Abstract: An environmental control system for a building including heating, ventilation, or air conditioning (HVAC) equipment that operates to affect a zone of the building and a controller including a processing circuit. The processing circuit is configured to estimate a thermal resistance between air of the zone and of an external space using values of a temperature of the zone air, a temperature of the external space air, and a heat transfer rate of the HVAC equipment, each value corresponding to a different time step within a time period. The processing circuit is configured to use the thermal resistance, time step specific values of the temperatures, and time step specific values of the heat transfer rate to estimate corresponding values of a heat disturbance. The processing circuit is configured to operate the HVAC equipment using a model-based control technique based on the heat disturbance values.

Patent Agency Ranking