Abstract: A controller for maintaining occupant comfort in a space of 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. The operations include obtaining building data and obtaining occupant comfort data. The operations include generating an occupant comfort model relating the building data to a level of occupant comfort within the space based on the building data and the occupant comfort data. The operations include generating time-varying comfort constraint for an environmental condition of the space using the occupant comfort model and include performing a cost optimization of a cost function of operating building equipment over a time duration to determine a setpoint for the building equipment. The operations include operating the building equipment based on the setpoint to affect the variable state or condition of the space.

Abstract: A model predictive maintenance system for building equipment including one or more processing circuits including processors and memory storing instructions that, when executed by the processors, cause the processors to perform operations. The operations include obtaining an objective function that defines a cost of operating the building equipment and performing maintenance on the building equipment as a function of operating decisions and maintenance decisions for the building equipment for time steps within a time period. The operations include performing an optimization of the objective function to generate a maintenance and replacement strategy for the building equipment over a duration of an optimization period. The operations include estimating a savings loss predicted to result from a deviation from the maintenance and replacement strategy. The operations include adjusting an amount of savings expected to be achieved by energy conservation measures for the building equipment based on the savings loss.

Abstract: A model predictive maintenance system for building equipment that performs operations including obtaining an objective function defining a cost of operating and performing maintenance on the equipment as a function of operating and maintenance decisions for time steps within a time period of a life cycle horizon and including performing a first computation of the objective function under a first scenario where maintenance is performed on the equipment during the period, a result of the first computation indicating a first cost. The operations include performing a second computation under a second scenario in which maintenance is not performed during the period, a result indicating a second cost. The operations include initiating an automated action to perform maintenance on the equipment in accordance with decisions defined by the first scenario if the first cost is less than or equal to the second cost.

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 environmental control system of a building including a first building device operable to affect environmental conditions of a zone of the building by providing a first input to the zone. The system includes a second building device operable to independently affect a subset of the environmental conditions by providing a second input to the zone and further includes a controller including a processing circuit. The processing circuit is configured to perform an optimization to generate control decisions for the building devices. The optimization is performed subject to constraints for the environmental conditions and uses a predictive model that predicts an effect of the control decisions on the environmental conditions. The processing circuit is configured to operate the building devices in accordance with the control decisions.

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.

Abstract: A system includes a plurality of thermostats corresponding to a plurality of HVAC systems that serve a plurality of spaces and a computing system communicable with the plurality of thermostats via a network. The computing system is configured to, for each space of the plurality of spaces, obtain a set of training data relating to thermal behavior of the space, identify a model of thermal behavior of the space based on the set of training data, perform a model predictive control process using the model of thermal behavior of the space to obtain a temperature setpoint for the space, and provide the temperature setpoint to the thermostat corresponding to the HVAC system serving the space. The plurality of thermostats are configured to control the plurality of HVAC systems in accordance with the temperature setpoints.

Abstract: A controller is provided for building equipment including a plurality of devices that operate in parallel to affect an environmental condition of a building. The controller includes one or more processing circuits including one or more processors and memory. The memory store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include lowering an upper bound or raising a lower bound of one or more constraints based on a minimum off schedule or a minimum on schedule for the building equipment, performing an optimization of an objective function subject to the one or more constraints to generate control decisions for the building equipment, and operating the building equipment in accordance with the control decisions to affect the environmental condition of the building.

Abstract: A building control system includes one or more controllers configured to obtain comfort feedback provided by one or more occupants of a building in response to exposing the one or more occupants to a first set of environmental conditions of the building. The one or more controllers are also configured to generate, based on the comfort feedback, one or more thresholds defining a range of values for an environmental condition of the building within which the one or more occupants are predicted to be comfortable, execute a predictive control process subject to one or more constraints based on the one or more thresholds to generate setpoints for building equipment, and operate the building equipment to drive the environmental condition of the building toward the setpoints.

Abstract: Systems and methods for modeling and controlling entities of a building system are provided. An exemplary method includes comparing an input indicating a new entity or connection between entities of a building system to a data model for the building system to determine whether the new entity or connection is represented in the data model, extending the data model to define the new entity or connection in response to determining that the new entity or connection is not represented in the data model, and using the data model with the new entity or connection in a control strategy to generate control decisions for the entities of the building system.

Abstract: A predictive controller for building equipment associated with a building includes one or more processing circuits configured to control electric energy used by the building equipment. The building equipment includes an electric energy using component. The one or more processing circuits are configured to utilize a predictive cost function to determine a first amount of the electric energy supplied from an energy grid source and a second amount of the electric energy supplied from a second energy source to the electric energy using component.

Abstract: Systems and methods for automatically commissioning and operating a heating, ventilation, or air conditioning (HVAC) system for a building site are provided. An exemplary method includes constructing a model using physical equipment of the HVAC system and relationships between the physical equipment. The model indicates connections between the physical equipment and one or more resources produced or consumed by the physical equipment. The method includes generating a mapping between points of the physical equipment at the building site and corresponding variables of the model, using the model to generate values of one or more control variables of the model, and operating the physical equipment by providing the values of the control variables to corresponding points of the physical equipment based on the mapping.

Abstract: A thermal energy production and control system includes a heat recovery chiller, thermal energy storage, and a controller. The controller uses thermal energy load targets to generate control decisions for the heat recovery chiller and the thermal energy storage for a plurality of time steps of a time period. The control decisions include a first amount of hot thermal energy or cold thermal energy to be generated by the heat recovery chiller at a first time step of the time period and stored in the thermal energy storage and a second amount of the hot thermal energy or the cold thermal energy to be discharged from the thermal energy storage and used to satisfy one or more of the thermal energy load targets for a second time step of the time period. The controller operates the heat recovery chiller and the thermal energy storage in accordance with the control decisions.

Abstract: A controller includes a processing circuit comprising one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include determining a gradient of an objective function with respect to a constraint variable used to define a constraint on a control process that uses the objective function and modifying the constraint variable to have a modified value in response to determining that a trigger condition is satisfied. The trigger condition is based on the gradient. The operations include performing the control process subject to the constraint using the modified value of the constraint variable and operating equipment in accordance with a result of the control process.

Abstract: A building management system (BMS) for filtering a fluid within a building is shown. The system includes one or more sensors configured to measure one or more characteristics of a first fluid within an air duct of the BMS and measure one or more characteristics of a second fluid after the second fluid has been filtered. The system further includes a pollutant management system configured to receive data from the one or more sensors and control a filtration process. The filtration process selects a filter of a plurality of filters based on at least one of a level of the one or more characteristics of the first fluid or the one or more characteristics of the second fluid.

Abstract: An electrical energy storage system includes a battery configured to store and discharge electric power to an energy grid, a power inverter configured to use battery power setpoints to control an amount of the electric power stored or discharged from the battery, the battery power setpoints comprising at least one of frequency regulation power setpoints and ramp rate control power setpoints, and a controller. The controller is configured to use a battery life model to generate the battery power setpoints for the power inverter. The battery life model includes one or more variables that depend on the battery power setpoints.

Abstract: An energy storage system for a building includes a battery asset configured to store electricity and discharge the stored electricity for use in satisfying a building electric load. The system includes a planning tool configured to identify one or more selected functionalities of the energy storage system and generate a cost function defining a cost of operating the energy storage system over an optimization period. The cost function includes a term for each of the selected functionalities. The planning tool is configured to generate optimization constraints based on the selected functionalities, attributes of the battery asset, and the electric energy load to be satisfied. The planning tool is configured to optimize the cost function to determine optimal power setpoints for the battery asset at each of a plurality of time steps of the optimization period.

Abstract: A method includes operating equipment to consume energy resources including energy or power purchased from a utility, and obtaining a block-and-index rate profile for a future time period. The block-and-index rate profile includes a block rate and a block size for each of a plurality of sub-periods in the future time period. The block size for a sub-period identifies an amount of energy or power priced at the block rate for the sub-period. The method also includes applying the block-and-index rate profile in an optimization process for the equipment over the time period, running the optimization process, and allocating energy resources to the equipment over the time period in accordance with a result of the optimization process.

Abstract: A control system includes building equipment configured to consume electrical energy and generate thermal energy, electrical energy storage configured to store and discharge electrical energy, and a controller. The controller is configured to determine, for a plurality of time steps within a time horizon, an amount of electrical energy to store in the electrical energy storage or discharge from the electrical energy storage using a value function. The value function includes an expected revenue from participating in an incentive-based demand response (IBDR) program, an expected cost of participating in the IBDR program, and a penalty cost based on an amount by which a predicted output of the building equipment or the electrical energy storage changes between time steps within the time horizon. The controller is configured to control the electrical energy storage to store or discharge the amount of electrical energy determined using the value function.

Abstract: An environmental control system of a building including a first building device operable to affect environmental conditions of a zone of the building by providing a first input to the zone. The system includes a second building device operable to independently affect a subset of the environmental conditions by providing a second input to the zone and further includes a controller including a processing circuit. The processing circuit is configured to perform an optimization to generate control decisions for the building devices. The optimization is performed subject to constraints for the environmental conditions and uses a predictive model that predicts an effect of the control decisions on the environmental conditions. The processing circuit is configured to operate the building devices in accordance with the control decisions.