Abstract: A controller for a building control system includes processors and memory storing instructions that, when executed by the processors, cause the processors to perform operations including identifying zones within a building, analyzing data associated with the zones, and generating zone groupings based on the data associated with the zones. Each of the zone groupings define zone groups and specify which of the zones are grouped together to form each of the zone groups. The operations also include identifying a particular zone grouping from zone groupings based on the data associated with zones and using the particular zone grouping to generate control signals to operate equipment of the building control system to provide heating or cooling to the zones.

Abstract: Granular assets of a building are identified. Each granular asset represents one or more devices of that operate to produce, consume, or store resources in the building. General assets are defined by grouping the granular assets into groups. A non-granular optimization is performed to determine a non-granular allocation of the resources among the general assets. Non-granular allocation defines an amount of each of the resources consumed, produced, or stored by each of the general assets at each time step in a time period. A granular optimization is performed for each general asset to determine a granular allocation of the resources among the granular assets. The granular allocation defines an amount of each resource consumed, produced, or stored by the granular assets at each time step in the time period. The equipment of the building are operated to consume, produce, or store the amount of each resource defined by granular allocation.

Abstract: A central plant control system configured to serve one or more energy loads in a building comprises equipment configured to consume, produce, or store one or more resources including electricity, water, natural gas, steam, hot thermal energy, cold thermal energy, or electrical energy. The central plant control system further comprises an asset allocator configured to receive an input model that describes a physical layout of the equipment of the central plant and create a net list that defines connections between the equipment of the central plant using the input model. The asset allocator is further configured to discover one or more systems of interconnected equipment and one or more groups of equipment using the net list, formulate an optimization problem for the central plant using the systems and groups of equipment, and operate the equipment of the central plant according to the optimization problem.

Abstract: Systems and methods for implementing an economic strategy such as a model predictive control (EMPC) strategy. An EMPC tool is configured to present to receive sinks and connections between central plant equipment. The EMPC tool also includes a data model extender configured to extend a data model to define new entities and/or relationships. The EMPC tool also includes a high level EMPC algorithm configured to generate an optimization problem and an asset allocator configured to solve the resource optimization problem in order to determine optimal control decisions used to operate the central plant.

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.

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.

Abstract: A method for dynamic cloud based control of building equipment via a cloud based building management system includes instantiating a sequencer in response to receiving a startup request, receiving, via the cloud based building management system, a sequence package, wherein the sequence package includes configuration information for interfacing the cloud based building management system with the building site, collecting building data from the building equipment of the building site based on the sequence package, causing a control process to execute based on the collected data, and dispatching a command to the building equipment based on a result of the execution of the control process, wherein the command includes a command to control the building equipment to control an environmental condition of the building site.

Abstract: A method for controlling production of one or more refined resources by an energy provider includes predicting a demand for the refined resources by one or more consumers of the refined resources as a function of an incentive offered by the energy provider. The method further includes performing an optimization of an objective function subject to a constraint based on the predicted demand for the refined resources to determine an amount of the refined resources for the energy provider to produce and a value of the incentive at multiple times within a time period. The method also includes providing setpoints for equipment of the energy provider that cause the equipment to produce the amount of the refined resources determined by performing the optimization.

Abstract: A controller for a plurality of heating, ventilation, or air conditioning (HVAC) devices includes a processing circuit that includes one or more processors and memory. The controller detects a change in condition that affects an operating status of a first HVAC device of the plurality of HVAC devices. The controller uses schematic relationships between the plurality of HVAC devices to determine a reduced subset of the plurality of HVAC devices for which operating parameters are to be generated based on the operating status of the first HVAC device. The controller generates operating parameters for the reduced subset of the plurality of HVAC devices and operates the plurality of HVAC devices using the operating parameters.

Abstract: Systems and methods for implementing an economic model predictive control (EMPC) strategy in any resource-based system include an EMPC tool. The EMPC tool is configured to present user interfaces to a client device. The EMPC tool is further configured to receive first user input including resources and subplants associated with a central plant. The EMPC tool is also configured to receive second user input including sinks and connections between central plant equipment. The EMPC tool also includes a data model extender configured to extend a data model to define new entities and/or relationships specified by user input. The EMPC tool also includes a high level EMPC algorithm configured to generate an optimization problem and an asset allocator configured to solve the resource optimization problem in order to determine optimal control decisions used to operate the central plant.

Abstract: A method for verifying and running a script for a building management system of a building includes receiving, by the building management system, the script, wherein the script indicates one or more operations to be performed with one or more data points of a data model of the building, determining, by the building management system, whether there is unit cohesion within the received script, wherein the unit cohesion indicates that a result value of executing the script with the one or more data points include units that match desired units, and determining, by the building management system, the result value by executing the script with the one or more data points in response to determining that there is unit cohesion.

Abstract: A method for executing computations in parallel for a building management system of a building includes receiving a computing job request to determine values for one or more particular properties, receiving a property model indicating dependencies between a plurality of properties, the plurality of properties including the one or more particular properties, wherein the plurality of properties include building data for the building, and generating one or more computing threads based on the property model, wherein each computing thread includes a sequence of computations for determining values for the plurality of properties. The method further includes executing the computing threads in parallel to determine the values for the particular properties.

Abstract: A method for dynamically updating a building management system (BMS) control platform for a building includes receiving, by the BMS control platform, a context, wherein the context includes metadata defining a data model for the building and equipment of the building, wherein the metadata describes the data model with a common modeling language (CML). The method further includes implementing, by the BMS control platform, the data model of the context via the CML, wherein the BMS control platform implements the data model during the runtime of the BMS control platform and does not require redeployment of the BMS control platform, and controlling, by the BMS control platform, the equipment of the building based on the implemented data model to control an environmental condition of the building.

Abstract: A building management system includes building equipment operable to affect a variable state or condition of a building and a control system configured to receive a user input indicating a model form. The model form includes a plurality of matrices having a plurality of elements defined in terms of a plurality of parameters. The control system is configured to parse the model form to generate a sequence of machine-executable steps for determining a value of each of the plurality of elements based on a set of potential parameter values, identify a system model by executing the sequence of machine-executable steps to generate a set of parameter values for the plurality of parameters, generate a graphical user interface that illustrates a fit between predictions of the identified system model and behavior of the variable state or condition of the building, and control the building equipment using the identified system model.

Abstract: Systems and methods for implementing an economic model predictive control (EMPC) strategy in any resource-based system include an EMPC tool. The EMPC tool is configured to present user interfaces to a client device. The EMPC tool is further configured to receive first user input including resources and subplants associated with a central plant. The EMPC tool is also configured to receive second user input including sinks and connections between central plant equipment. The EMPC tool also includes a data model extender configured to extend a data model to define new entities and/or relationships specified by user input. The EMPC tool also includes a high level EMPC algorithm configured to generate an optimization problem and an asset allocator configured to solve the resource optimization problem in order to determine optimal control decisions used to operate the central plant.

Abstract: A control system for a central energy facility with distributed energy storage includes a high level coordinator, a low level airside controller, a central plant controller, and a battery controller. The high level coordinator is configured to perform a high level optimization to generate an airside load profile for an airside system, a subplant load profile for a central plant, and a battery power profile for a battery. The low level airside controller is configured to use the airside load profile to operate airside HVAC equipment of the airside subsystem. The central plant controller is configured to use the subplant load profile to operate central plant equipment of the central plant. The battery controller is configured to use the battery power profile to control an amount of electric energy stored in the battery or discharged from the battery at each of a plurality of time steps in an optimization period.

Abstract: A central plant control system configured to serve one or more energy loads in a building comprises equipment configured to consume, produce, or store one or more resources including electricity, water, natural gas, steam, hot thermal energy, cold thermal energy, or electrical energy. The central plant control system further comprises an asset allocator configured to receive an input model that describes a physical layout of the equipment of the central plant and create a net list that defines connections between the equipment of the central plant using the input model. The asset allocator is further configured to discover one or more systems of interconnected equipment and one or more groups of equipment using the net list, formulate an optimization problem for the central plant using the systems and groups of equipment, and operate the equipment of the central plant according to the optimization problem.

Abstract: A fiber optic flow sensor includes a fiber optic cable, a light emitter, an optical power meter, and a processing circuit. The fiber optic cable allows light to enter a first end of the fiber optic cable, reflect off a second end of the fiber optic cable and exit the fiber optic cable through the first end. The fiber optic cable is at least partially exposed to fluid flow at the second end. The light emitter emits light at an input power into the first end of the fiber optic cable. The optical power meter measures an output power of the light exiting the fiber optic cable at the first end. The processing circuit calculates a flow rate of the flow of fluid based on the input power of light entering the fiber optic cable and the output power of light exiting the first end of the fiber optic cable.

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.

Abstract: A method for dynamically updating a building management system (BMS) control platform for a building includes receiving, by the BMS control platform, a context, wherein the context includes metadata defining a data model for the building and equipment of the building, wherein the metadata describes the data model with a common modeling language (CML). The method further includes implementing, by the BMS control platform, the data model of the context via the CML, wherein the BMS control platform implements the data model during the runtime of the BMS control platform and does not require redeployment of the BMS control platform, and controlling, by the BMS control platform, the equipment of the building based on the implemented data model to control an environmental condition of the building.