CENTRAL PLANT WITH ASSET ALLOCATOR
    61.
    发明申请

    公开(公告)号:US20200042918A1

    公开(公告)日:2020-02-06

    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.

    BUILDING ENERGY COST OPTIMIZATION SYSTEM WITH ASSET SIZING

    公开(公告)号:US20190340709A1

    公开(公告)日:2019-11-07

    申请号:US16518314

    申请日:2019-07-22

    Abstract: A controller is configured to obtain a cost function defining a cost of operating building equipment over a time period. The cost function includes a revenue term defining revenue to be obtained by operating the equipment to participate in an incentive program over the time period. The controller is configured to modify the cost function to account for an initial purchase cost of a new asset to be added to the equipment and an effect of the new asset on the cost of operating the equipment. The initial purchase cost of the new asset and the effect of the new asset on the cost of operating the equipment are functions of asset size variables. The controller is also configured to perform an optimization of the modified cost function to determine values for energy load setpoints, the asset size variables, and participation in the incentive program over the time period.

    MODEL PREDICTIVE MAINTENANCE SYSTEMS AND METHODS WITH AUTOMATIC PARTS RESUPPLY

    公开(公告)号:US20190295034A1

    公开(公告)日:2019-09-26

    申请号:US16438961

    申请日:2019-06-12

    Abstract: An automatic parts resupply system for building equipment including a model predictive maintenance system configured to determine a service time at which to perform service on the building equipment by performing a predictive optimization of a total cost of operating and servicing the building equipment over a time period. The service time is a decision variable in the predictive optimization. The automatic parts resupply system includes a resupply manager. The resupply manager is configured to generate a parts resupply order for the building equipment based on a result of the predictive optimization. The resupply manager is configured to determine a transmission time at which to transmit the parts resupply order to a parts supplier. The resupply manager is configured to transmit the parts resupply order to the parts supplier at the transmission time.

    Incorporating a demand charge in central plant optimization

    公开(公告)号:US10386820B2

    公开(公告)日:2019-08-20

    申请号:US14634599

    申请日:2015-02-27

    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.

    CENTRAL PLANT CONTROL SYSTEM BASED ON LOAD PREDICTION THROUGH MASS STORAGE MODEL

    公开(公告)号:US20190033800A1

    公开(公告)日:2019-01-31

    申请号:US16048162

    申请日:2018-07-27

    Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

    DYNAMIC CENTRAL PLANT CONTROL BASED ON LOAD PREDICTION

    公开(公告)号:US20190032944A1

    公开(公告)日:2019-01-31

    申请号:US16048165

    申请日:2018-07-27

    Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

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