Abstract: A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

Abstract: A method for performing model predictive maintenance (MPM) of building equipment includes obtaining a first objective function that defines a cost of operating the building equipment and at least one of replacing the building equipment or performing maintenance on the building equipment as a function of operating decisions and at least one of replacement decisions or maintenance decisions for the building equipment for multiple short-term time steps within a short-term horizon. The method also includes performing a first optimization of the first objective function to generate a short-term maintenance and replacement schedule for the building equipment over a duration of the short-term horizon. The method also includes using a result of the first optimization to perform a second optimization of a second objective function to generate a long-term maintenance and replacement schedule for the building equipment over a duration of a long-term horizon.

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.

Abstract: A building system that operates to receive a plurality of data samples from building equipment of the building and identity whether one or more data samples of the plurality of data samples are anomalous indicating that one or more pieces of the building equipment are possibly experiencing a fault. The building system operates to generate one or more data health scores for the building equipment based on whether the one or more data samples are anomalous, the one or more data health scores indicating quality levels of the plurality of data samples and generate user interface data configured to cause a user device to display a user interface providing indications of the one or more pieces of building equipment that are possibly experiencing the fault and the one or more data health scores.

Abstract: A heating, ventilation, or air conditioning (HVAC) system for a building includes HVAC equipment configured to provide heating or cooling to one or more building spaces and one or more controllers. The one or more controllers include one or more processing circuits configured to generate energy targets for the one or more building spaces using a thermal capacitance of the one or more building spaces to which the heating or cooling is provided by the HVAC equipment, generate setpoints for the HVAC equipment using the energy targets for the one or more building spaces to which the heating or cooling is provided by the HVAC equipment, and operate the HVAC equipment using the setpoints to provide the heating or cooling to the one or more building spaces.

Abstract: A building system operates to receive building data from one or more building data sources associated with the building, wherein at least a portion of the building data is associated with control of the one or more environmental conditions of the building and generate, based on the building data, one or more data quality indicators for the building data received from the one or more building data sources, the one or more data quality indicators indicating quality levels of the building data. The building system operates to generate user interface data configured to cause a user device to display a user interface providing indications of the one or more data quality indicators.

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 method includes obtaining an optimized setpoint schedule for a time period, identifying a pre-cooling or pre-heating segment of the time period of the optimized setpoint schedule, adjusting the optimized setpoint schedule based on a characteristic of the pre-cooling or pre-heating segment to obtain an adjusted setpoint schedule, and operating the building equipment in accordance with the adjusted setpoint schedule.

Abstract: A method includes providing an objective function having a first control objective dependent upon production or use of one or more energy resources, a second control objective accounting for carbon emissions associated with the production or use of the one or more energy resources, and a weighting factor applied to the first control objective or the second control objective. The method includes simulating amounts of carbon emissions over a time period for a plurality of possible values of the weighting factor, selecting a value for the weighting factor based on a comparison of a carbon emissions goal for the time period with the simulated amounts of carbon emissions, performing an optimization of the objective function with the objective function comprising the value for the weighting factor, and controlling equipment to use the one or more energy resources in accordance with a result of the optimization.

Abstract: A cascaded control system for coordinating and controlling carbon emissions associated with operating building equipment distributed across a plurality of subsystems includes a first controller configured to generate carbon emissions targets for each of a plurality of subsystems using a predictive control process that accounts for an aggregate carbon emissions of the plurality of subsystems predicted to result from the carbon emissions targets. The cascaded control system also includes a plurality of second controllers, each corresponding to one of the plurality of subsystems and configured to generate control decisions for building equipment of the corresponding subsystem that are predicted to cause the building equipment to achieve the carbon emissions targets for the corresponding subsystem; and operate the building equipment of the corresponding subsystem using the control decisions.

Abstract: A method for controlling building equipment includes providing a user interface comprising a graphical representation of a relationship between a carbon emissions control objective and a second control objective that competes with the carbon emissions control objective over a range of control strategies for the building equipment, and assigning a weight to the carbon emissions control objective or the second control objective in an objective function. The weight is associated with a control strategy that corresponds to a user selection based on the graphical representation. The method also includes generating control decisions for the building equipment using the objective function with the weight assigned to the carbon emissions control objective or the second control objective and operating the building equipment in accordance with the control decisions.

Abstract: A building management system (BMS) includes sensors that measure time series values of building variables and a deterministic model generator that uses historical values for the time series of building variables to train a deterministic model that predicts deterministic values for the time series. The BMS includes a stochastic model generator that uses differences between actual values for the time series and the predicted deterministic values to train a stochastic model that predicts a stochastic value for the time series. The BMS includes a forecast adjuster that adjusts the predicted deterministic values using the predicted stochastic value to generate an adjusted forecast for the time series. The BMS includes a demand response optimizer that uses the adjusted forecast to generate an optimal set of control actions for building equipment of the BMS. The building equipment operate to affect the building variables.

Abstract: A controller for operating building equipment of a building including processors and non-transitory computer-readable media storing instructions that, when executed by the processors, cause the processors to perform operations including obtaining a first setpoint trajectory from a cloud computation system. The first setpoint trajectory includes setpoints for the building equipment or for a space of the building. The setpoints correspond to time steps of an optimization period. The operations include determining whether a connection between the controller and the cloud computation system is active or inactive at a time step of the optimization period and determining an active setpoint for the time step of the optimization period using either the first or second setpoint trajectory based on whether the connection between the controller and the cloud computation system is active or inactive at the time step. The operations include operating the building equipment based on the active setpoint.

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.

Abstract: A controller for HVAC equipment stores a cascaded model that includes a disturbance model configured to predict a heat disturbance affecting the building zone as a function of one or more exogenous parameters and a physics model configured to predict a temperature of the building zone as a function of the heat disturbance and an amount of heating or cooling provided to the building zone by HVAC equipment. The processing circuit is configured to execute a combined training procedure to determine parameters of the disturbance model and parameters of the physics model, generate control signals for the HVAC equipment using the disturbance model to predict the heat disturbance and applying the heat disturbance as an input to the physics model, and operate the HVAC equipment to provide the heating or cooling to the building zone in accordance with the control signals.

Abstract: A control system for cost optimal operation of an energy facility including equipment includes a controller configured to provide a cost function comprising a cost term defining a cost as a function of a rate variable and an equipment usage variable, simulate the cost of operating the energy facility over an optimization period at each of a plurality of different values of the rate variable which define a plurality of different costs per unit of the equipment usage variable, select a value of the rate variable that results in a lowest cost of operating the energy facility over the optimization period, perform 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 operate the equipment during the optimization period in accordance with the generated setpoints.

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.

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.

Abstract: Systems and methods for controlling building equipment include simulating operation of the building equipment at a plurality of initial points to generate corresponding values of a first control objective and a second control objective that competes with the first control objective, automatically generating a new point at which to run a new simulation based on the plurality of initial points and the corresponding values of the control objectives, running the new simulation at the new point to generate corresponding values of the control objectives, classifying a subset of the plurality of initial points and the new point as Pareto-optimal points based on the corresponding values of the control objectives, and operating the building equipment at a Pareto-optimal point selected from the subset of the plurality of initial points and the new point classified as Pareto-optimal points.

Abstract: A method for controlling an energy production and distribution system includes identifying sources that supply input resources, subplants that produce output resources using the input resources, and sinks that consume the output resources. The method includes obtaining a cost function including a cost of producing the output resources and generating a transit time constraint that requires the input resources be sent from the sources to the subplants at a first departure time that occurs before a first arrival time at which the input resources are predicted to be used by the subplants. The method includes solving an optimization problem to determine an amount of the output resources to produce at each of multiple time steps within a time period. Solving the optimization problem includes performing an optimization of the cost function subject to the transit time constraint.