Abstract: A model predictive maintenance (MPM) system for building equipment includes one or more processing circuits including 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 obtaining one or more performance indicators for the building equipment and determining whether a trigger condition has been satisfied based on the one or more performance indicators. The operations include triggering a model predictive maintenance process to generate a maintenance schedule for the building equipment in response to determining that the trigger condition has been satisfied. The operations include initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

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: A building energy system includes HVAC equipment, green energy generation, a battery, and a predictive controller. The HVAC equipment provide heating or cooling for a building. The green energy generation collect green energy from a green energy source. The battery stores electric energy including at least a portion of the green energy provided by the green energy generation and grid energy purchased from an energy grid and discharges the stored electric energy for use in powering the HVAC equipment. The predictive controller generates a constraint that defines a total energy consumption of the HVAC equipment at each time step of an optimization period as a summation of multiple source-specific energy components and optimizes the predictive cost function subject to the constraint to determine values for each of the source-specific energy components at each time step of the optimization period.

Abstract: A building HVAC system includes an airside system having a plurality of airside subsystems, a high-level controller, and a plurality of low-level airside controllers. Each airside subsystem includes airside HVAC equipment configured to provide heating or cooling to one or more building spaces. The high-level controller is configured to generate a plurality of airside subsystem energy targets, each airside subsystem energy target corresponding to one of the plurality of airside subsystems and generated based on a thermal capacitance of the one or more building spaces to which heating or cooling is provided by the corresponding airside subsystem. Each low-level airside controller corresponds to one of the airside subsystems and is configured to control the airside HVAC equipment of the corresponding airside subsystem in accordance with the airside subsystem energy target for the corresponding airside subsystem.

Abstract: A heating, ventilation, or air conditioning (HVAC) system for a building includes indoor subsystems, a high-level controller, and low-level controllers. Each indoor subsystem includes one or more indoor units configured to provide heating or cooling to one or more building spaces. The high-level controller generates a plurality of indoor subsystem energy targets, each indoor subsystem energy target corresponding to one of the plurality of indoor subsystems and generated based on a thermal capacitance of one or more building spaces to which heating or cooling is provided by the corresponding indoor subsystem. Each low-level indoor controller corresponds to one of the indoor subsystems and generates indoor setpoints for the one or more indoor units of the corresponding indoor subsystem using the indoor subsystem energy target for the corresponding indoor subsystem and operates the one or more indoor units of the corresponding indoor subsystem using the indoor setpoints.

Abstract: A refrigeration cycle, an air conditioning system, and a method for controlling a refrigeration cycle are provided. The refrigeration cycle includes an outdoor unit, an indoor unit, a controller, and an inverter. The controller controls a compressor and an outdoor fan of the air conditioning system so as to minimize a total electric power consumption of the air conditioning system. The inverter controls the outdoor fan in a rotation state predicted from a capacity demand in an air conditioning space depending on an operation mode and sensor values. The controller predicts the capacity demand and controls a rotation rate of the outdoor fan based on a prediction of the capacity demand.

Abstract: A model predictive maintenance (MPM) system for building equipment includes one or more processing circuits having 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 including estimating a degradation state of the building equipment, using a degradation impact model to predict an amount of one or more input resources consumed by the building equipment to produce one or more output resources based on the degradation state of the building equipment, generating a maintenance schedule for the building equipment based on the amount of the one or more input resources predicted by the degradation impact model, and initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

Abstract: An air conditioner controller for an air conditioner is configured to obtain a first value of a performance value from a predetermined component of the air conditioner, and estimate a total cost. The controller is configured to estimate the total cost including an operation cost and a renewal cost of the air conditioner based on the first value of the performance variable obtained from the predetermined component of the air conditioner and a second value of the performance variable estimated by an operational model of the air conditioner. The total cost is a total cost of operating and renewing the air conditioner for a time period after a time at which the first value of the performance variable is obtained. The controller is configured to output the total cost via a user interface.

Abstract: A building HVAC system includes a waterside system and an airside system. The waterside system consumes one or more resources from utility providers to generate a heated and/or chilled fluid. The airside system uses the heated and/or chilled fluid to heat and/or cool a supply airflow provided to the building. A HVAC controller performs an integrated airside/waterside optimization process to simultaneously determine control outputs for both the waterside system and the airside system. The optimization process includes optimizing a predictive cost model that predicts the cost of the resources consumed by the HVAC system, subject to a set of optimization constraints including temperature constraints for the building. The HVAC controller uses the determined control outputs to control the HVAC equipment of the waterside system and the airside system.

Abstract: An energy optimization system for a building includes a processing circuit configured to provide a first bid including one or more first participation hours and a first load reduction amount for each of the one or more first participation hours to a computing system. The processing circuit is configured to operate one or more pieces of building equipment based on one or more first equipment loads and receive one or more awarded or rejected participation hours from the computing system responsive to the first bid. The processing circuit is configured to generate one or more second participation hours, a second load reduction amount for each of the one or more second participation hours, and one or more second equipment loads based on the one or more awarded or rejected participation hours and operate the one or more pieces of building equipment based on the one or more second equipment loads.

Abstract: A mobile commissioning device for commissioning building equipment in or around a building includes a processing circuit. The processing circuit includes a processor and memory storing instructions executed by the processor. The processing circuit establishes location of the mobile commissioning device and building equipment within the building. The processing circuit also detects and receives commissioning data from building equipment located within a building zones of the building as the mobile commissioning device moves between the building zones. The processing circuit further stores the commissioning data from the building equipment in a temporary commissioning database within the mobile commissioning device and transmits the commissioning data from the temporary commissioning database to a permanent server.

Abstract: A variable refrigerant flow system includes one or more outdoor units and a first indoor unit of a plurality of indoor units configured to receive refrigerant from the one or more outdoor units. The first indoor unit is configured to serve a first building zone. The variable refrigerant flow system also includes a user input device configured to receive a user command requesting heating or cooling of the first building zone by the first indoor unit. The variable refrigerant flow system also includes a controller configured to receive the command from the user input device, receive an indication of a current price of energy, in response to receiving the command generate a constraint on a capacity of the one or more outdoor units based on the current price of energy, and control the one or more outdoor units to operate in accordance with the constraint.

Abstract: A variable refrigerant flow (VRF) system for a building. The VRF system includes at least one outdoor VRF unit configured to heat or cool a refrigerant for use in heating or cooling the building. The at least one outdoor VRF unit includes a sub-cooler and a bypass expansion valve configured to control a flow of the refrigerant through the sub-cooler and an extremum-seeking controller configured to generate a sub-cooling temperature setpoint for the at least one outdoor VRF unit. The extremum-seeking controller is configured to determine a total power consumption of the at least one outdoor VRF unit, generate a sub-cooling temperature setpoint for the at least one outdoor VRF unit using an extremum-seeking control technique that drives the total power consumption toward an extremum, and use the sub-cooling temperature setpoint to operate the at least one outdoor VRF unit.

Abstract: An air handling unit (AHU) or rooftop unit (RTU) or other building device in a building includes one or more powered components and is used with a battery, and a predictive controller The battery is configured to store electric energy and discharge the stored electric energy for use in powering the powered components. The predictive controller is configured to optimize a predictive cost function to determine an optimal amount of electric energy to purchase from an energy grid and an optimal amount of electric energy to store in the battery or discharge from the battery for use in powering the powered components at each time step of an optimization period.

Abstract: A method for controlling HVAC equipment includes using a dynamic thermal model that describes heat transfer characteristics of a building to predict a temperature of the building as a function of control inputs to HVAC equipment that operate to affect the temperature of the building. The method includes obtaining time-varying utility prices and a predicted heating or cooling load for the building and performing a predictive control process using the dynamic thermal model, the time-varying utility prices, and the predicted heating or cooling load to generate the control inputs to the HVAC equipment subject to constraints on the temperature of the building.

Abstract: A controller for heating, ventilation, or air conditioning (HVAC) equipment including a processing circuit configured to perform a first optimization to generate a first set of control decisions for HVAC equipment including waterside HVAC equipment that consume resources from utility providers to generate a heated or chilled fluid and airside HVAC equipment that receive and use the fluid from the waterside HVAC equipment to heat or cool a supply of airflow for a building. The processing circuit is configured to perform a second optimization subject to a constraint based on a result of the first optimization to generate a second set of control decisions for the HVAC equipment and to combine the first and second sets to generate a combined set of control decisions for the HVAC equipment. The processing circuit is configured to operate the HVAC equipment in accordance with the combined set of control decisions.

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 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 variable refrigerant flow system includes one or more outdoor units and a first indoor unit of a plurality of indoor units configured to receive refrigerant from the one or more outdoor units. The first indoor unit is configured to serve a first building zone. The variable refrigerant flow system also includes a user input device configured to receive a user command requesting heating or cooling of the first building zone by the first indoor unit. The variable refrigerant flow system also includes a controller configured to receive the command from the user input device, receive an indication of a current price of energy, in response to receiving the command generate a constraint on a capacity of the one or more outdoor units based on the current price of energy, and control the one or more outdoor units to operate in accordance with the constraint.

Abstract: A cascaded model predictive control system includes an inner controller and an outer controller. The outer controller determines an amount of power to defer from a predicted power usage to optimize a total cost of power usage. A power setpoint is calculated based on a difference between the predicted power usage and the amount of power to defer. The inner controller determines an operating setpoint for building equipment in order to achieve the power setpoint.