Abstract: A model predictive maintenance system for building equipment. The system 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 performing an optimization of an objective function that defines a present value of a total 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 total cost includes one or more costs incurred during one or more future time steps of the time period. The operations include operating the building equipment and performing maintenance on the building equipment in accordance with decisions defined by the result of the optimization.

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 method for detecting faults in a building management system (BMS) is shown. The method includes receiving time series data characterizing an operating performance of one or more BMS devices. The method further includes processing the time series data using multiple different fault detection methods to generate multiple fault detection results. The method includes providing the multiple fault detection results as outputs from the multiple different fault detection methods. The method includes applying the multiple fault detection results as inputs to a neural network that determines whether the multiple fault detection results are indicative of a fault condition in the BMS.

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 model predictive maintenance system for building equipment. The system 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 performing an optimization of an objective function that defines a present value of a total 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 total cost includes one or more costs incurred during one or more future time steps of the time period. The operations include operating the building equipment and performing maintenance on the building equipment in accordance with decisions defined by the result of the optimization.