Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable storing instructions for operating an energy plant comprised of heating, ventilation and air conditioning (HVAC) devices. In one aspect, the system generates gradient data indicating a gradient of operating performance of the energy plant with respect to values of a plurality of control variables of HVAC devices. The system determines, from the plurality of control variables, a reduced group of control variables of the HVAC devices based on the gradient data. The system determines a set of values of the reduced group of control variables. The system operates the energy plant according to the determined set of values of the reduced group of control variables.

Abstract: A building management includes building equipment operable to affect a variable state or condition of a building and a controller. The controller is configured to identify one or more facility improvement measures (FIMS), each of the FIMS representing a potential upgrade or addition to the building equipment. The controller is further configured to perform a design of experiments analysis to determine a plurality of combinations of the FIMS, each combination including one or more of the FIMS and a level for each FIM in the combination. The controller is configured to generate an objective function based on the combinations of the FIMS. The objective function indicates an economic value as a function of the FIMS and optimize the objective function to determine an optimal combination of the FIMS.

Abstract: An energy optimization system for a building includes a processing circuit configured to generate a user interface including an indication of one or more economic load demand response (ELDR) operation parameters, one or more first participation hours, and a first load reduction amount for each of the one or more first participation hours. The processing circuit is configured to receive one or more overrides of the one or more first participation hours from the user interface, 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 for the one or more pieces of building equipment based on the received one or more overrides, and operate the one or more pieces of building equipment to affect an environmental condition of the building based on the one or more second equipment loads.

Abstract: A controller for equipment that operate to provide heating or cooling to a building or campus includes a processing circuit configured to obtain utility rate data indicating a price of resources consumed by the equipment to serve energy loads of the building or campus, obtain an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the resources consumed by the equipment, determine a relationship between resource consumption and load production of the equipment, optimize the objective function over the optimization subject to a constraint based on the relationship between the resource consumption and the load production of the equipment to determine a distribution of the load production across the equipment, and operate the equipment to achieve the distribution.

Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable storing instructions for operating an energy plant comprised of heating, ventilation and air conditioning (HVAC) devices. In one aspect, the system generates gradient data indicating a gradient of operating performance of the energy plant with respect to values of a plurality of control variables of HVAC devices. The system determines, from the plurality of control variables, a reduced group of control variables of the HVAC devices based on the gradient data. The system determines a set of values of the reduced group of control variables. The system operates the energy plant according to the determined set of values of the reduced group of control variables.

Abstract: Systems and methods for distributing load of an energy plant are disclosed herein. A target load of at least a first device and a second device of the energy plant is obtained. A first power consumption of the first device and the second device predicted to result from operating the first device and the second device according to a first combination of set points to satisfy the target load is predicted. A second power consumption of the first device and the second device predicted to result from operating the first device and the second device according to a second combination of set points to satisfy the target load is predicted. The first power consumption and the second power consumption are compared, and a combination of set points rendering lower power consumption is selected to operate the energy plant.

Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

Abstract: A controller for equipment obtains utility rate data indicating a price of one or more resources consumed by the equipment to serve energy loads. The controller generates an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the one or more resources consumed by the equipment at each of a plurality of time steps. The controller optimizes the objective function to determine a distribution of predicted energy loads across the equipment at each of the plurality of time steps. Load equality constraints on the objective function ensure that the distribution satisfies the predicted energy loads at each of the plurality of time steps. The controller operates the equipment to achieve the distribution of the predicted energy loads at each of the plurality of time steps.

Abstract: In one aspect, a system for operations an energy plant obtains thermal energy load allocation data indicating time dependent thermal energy load of the energy plant. The system determines, for a time period, an operating state of the energy plant from a plurality of predefined operating states based on the thermal energy load allocation data. The system determines operating parameters of the energy plant according to the determined operating state. The system operates the energy plant according to the determined operating parameters.

Abstract: A control system includes equipment and a controller. The equipment produces a resource by executing a first process when in a first state, and produces the resource by executing a second process when in a second state. The controller calculates a minimum second state operating time based on estimated cost savings resulting from operating in the second state relative to the first state. The minimum second state operating time is a minimum time amount that the equipment must operate in the second state for the estimated cost savings to offset cost of transitioning into the second state. The controller predicts whether the second process will be available for the minimum second state operating time during future time steps. The controller transitions the equipment from the first state to the second state in response to predicting that the second process will be available for the minimum second operating state time.

Abstract: A refrigeration cycle including at least one outdoor unit including a plurality of compressors and indoor units each placed in indoor spaces comprises a plurality of compressors for supplying refrigerant to indoor units; and a controller for controlling cooperatively a plurality of the compressors in the outdoor unit to provide a capacity for air-conditioning in the indoor spaces through the indoor units, wherein the controller controls operation of the compressors so as to minimize a cost including start/stop of each compressor by prediction of an air-conditioning requirement in a next time chunk.

Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

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 method for testing a cooling component in a building HVAC system uses a state-based testing procedure. The method includes providing a control signal to the cooling component. The control signal instructs the cooling component to activate. The method includes monitoring feedback from a temperature sensor configured to measure temperature affected by the cooling component and evaluating a state transition condition by comparing the feedback from the temperature sensor to a threshold value. The state transition condition is satisfied if the feedback is less than the threshold value and not satisfied if the feedback is not less than the threshold value. The method includes transitioning into a pass state in response to the feedback from the temperature sensor satisfying the state transition condition and transitioning into a fail state in response to the feedback from the temperature sensor not satisfying the state transition condition.

Abstract: A controller for an energy plant includes a processing circuit having a processor and memory which stores instructions executed by the processor. The processing circuit is configured to identify, from a plurality of thermodynamic states affected by a plurality of heat, ventilation, and air conditioning (HVAC) devices, a reduced subset of the plurality of thermodynamic states to be predicted based on connections between the plurality of HVAC devices. The processing circuit is configured to predict values of the reduced subset of the plurality of thermodynamic states and operate the plurality of HVAC devices based on the predicted values of the reduced subset of the plurality of thermodynamic states.

Abstract: Systems and methods for predicting a plurality of thermodynamic states of a plurality of heat, ventilation, and air conditioning (HVAC) devices of an energy plant are disclosed. The system includes a processor and a non-transitory computer readable medium storing instructions when executed causing the processor to: obtain plant netlist data describing the plurality of HVAC devices of the energy plant and connections of the plurality of HVAC devices to corresponding nodes; identify, from the first reduced subset, a second reduced subset of the plurality of thermodynamic states to be predicted by propagating a known value of the plurality of thermodynamic states using a linear solver; predict the second reduced subset of the plurality of thermodynamic states using a non-linear solver; and determine the plurality of thermodynamic states of the energy plant at the plurality of nodes based on the predicted second reduced subset of the plurality of thermodynamic states.

Abstract: Systems and methods for predicting a plurality of thermodynamic states of a plurality of heat, ventilation, and air conditioning (HVAC) devices of an energy plant are disclosed. The system includes a processor and a non-transitory computer readable medium storing instructions when executed causing the processor to: obtain plant netlist data describing the plurality of HVAC devices of the energy plant and connections of the plurality of HVAC devices to corresponding nodes; identify, from the plurality of thermodynamic states of the energy plant at a plurality of nodes, a reduced subset of the plurality of thermodynamic states to be predicted based on the connections of the plurality of HVAC devices; predict the reduced subset of the plurality of thermodynamic states using a non-linear solver; and determine the plurality of thermodynamic states of the energy plant based on the reduced subset of the predicted thermodynamic states.

Abstract: Systems and methods for distributing load of an energy plant are disclosed herein. A target load of at least a first device and a second device of the energy plant is obtained. A first power consumption of the first device and the second device predicted to result from operating the first device and the second device according to a first combination of set points to satisfy the target load is predicted. A second power consumption of the first device and the second device predicted to result from operating the first device and the second device according to a second combination of set points to satisfy the target load is predicted. The first power consumption and the second power consumption are compared, and a combination of set points rendering lower power consumption is selected to operate the energy plant.

Abstract: Disclosed herein are related to a method, a system, and a non-transitory computer readable medium storing instructions for operating a group of central plant equipment to serve thermal energy loads of a building or building system. In one approach, a base capacity of one or more devices of the group of central plant equipment is identified. A change in requested load allocated to the one or more devices crossing the base capacity at a crossover time may be detected. In one approach, an adjusted capacity of the one or more devices is set such that the adjusted capacity is offset from the base capacity before the crossover time and decays toward the base capacity during a decay period after the crossover time. The requested load allocated may be compared with the adjusted capacity after the crossover time. The group of central plant equipment may be operated according to the comparison.

Abstract: A control system includes equipment and a controller. The equipment produces a resource by executing a first process when in a first state, and produces the resource by executing a second process when in a second state. The controller calculates a minimum second state operating time based on estimated cost savings resulting from operating in the second state relative to the first state. The minimum second state operating time is a minimum time amount that the equipment must operate in the second state for the estimated cost savings to offset cost of transitioning into the second state. The controller predicts whether the second process will be available for the minimum second state operating time during future time steps. The controller transitions the equipment from the first state to the second state in response to predicting that the second process will be available for the minimum second operating state time.