Abstract: An energy optimization system for participating in a capacity market program (CMP) includes one or more memory devices storing instructions, that, when executed on one or more processors, cause the one or more processors to receive a nominated capacity value, generate an objective function and one or more CMP constraints, wherein the one or more CMP constraints cause an optimization of the objective function with the CMP constraints to generate a resource allocation that reduces the load of the facility by the nominated capacity value in response to receiving the dispatch from the utility, receive the dispatch from the utility, optimize the objective function based on the nominated capacity value, the dispatch, and the one or more CMP constraints to determine the resource allocation, and control one or more pieces of building equipment based on the determined resource allocation.

Abstract: A building analysis system includes a communications interface that receives energy consumption data for a building site including energy-consuming building equipment. A processing circuit of the building analysis system calculates first and second regression statistics indicating a fit of an energy use model to the energy consumption data under a null hypothesis that the energy use model has a first parameter order and an alternative hypothesis that the energy use model has a second parameter order different from the first parameter order. The processing circuit generates a test statistic indicating an improvement between the first regression statistic and the second regression statistic, compares the test statistic to a threshold value to determine whether the improvement warrants rejecting the null hypothesis, and determines an appropriate parameter order for the energy use model based on a result of the comparison.

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: 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 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: 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: Systems and methods for implementing an economic model predictive control (EMPC) strategy in any resource-based system include an EMPC tool. The EMPC tool is configured to present user interfaces to a client device. The EMPC tool is further configured to receive first user input including resources and subplants associated with a central plant. The EMPC tool is also configured to receive second user input including sinks and connections between central plant equipment. The EMPC tool also includes a data model extender configured to extend a data model to define new entities and/or relationships specified by user input. The EMPC tool also includes a high level EMPC algorithm configured to generate an optimization problem and an asset allocator configured to solve the resource optimization problem in order to determine optimal control decisions used to operate the central plant.

Abstract: A frequency response controller includes a high level controller configured to receive a regulation signal from an incentive provider, determine statistics of the regulation signal, and use the statistics of the regulation signal to generate a frequency response midpoint. The controller further includes a low level controller configured to use the frequency response midpoint to determine optimal battery power setpoints and use the optimal battery power setpoints to control an amount of electric power stored or discharged from a battery during a frequency response period.

Abstract: A frequency response optimization system includes a battery configured to store and discharge electric power, a power inverter configured to control an amount of the electric power stored or discharged from the battery, and a frequency response controller. The frequency response controller includes receiving a regulation signal from an incentive provider, determining statistics of the regulation signal, using the statistics of the regulation signal to generate a frequency response midpoint, and using the frequency response midpoint to determine optimal battery power setpoints for the power inverter. The power inverter is configured to use the optimal battery power setpoints to control the amount of the electric power stored or discharged from the battery.

Abstract: An automatic work order generation system for model predictive maintenance (MPM) of building equipment including an MPM system including an equipment controller to operate the building equipment to affect an environmental condition of a building. The MPM system can perform a predictive optimization to determine a service time at which to service the building equipment. The automatic work order generation system includes an equipment service scheduler that can determine whether any service providers are available to perform equipment service within a predetermined time range of the service time. In response to determining that service providers are available to perform the equipment service, the equipment service scheduler can select a service provider and an appointment time based on one or more service provider attributes. The equipment service scheduler can generate a service work order and transmit the service work order to the service provider to schedule a service appointment.

Abstract: A building management system includes building equipment, a sensor, and a saturation detector. The building equipment is configured to operate at an operating capacity to drive a variable state or condition of a building zone toward a setpoint. The operating capacity and the setpoint vary over time. The sensor is in the building zone and is configured to provide a zone measurement of the variable state or condition of the building zone. The saturation detector is configured to determine whether the operating capacity is in a non-transient region for a threshold amount of a time period upon determining that an error for the building zone exists for the time period, and, in response to a determination that the operating capacity is in the non-transient region for at least the threshold amount of the time period, indicate the time period as a saturation period.

Abstract: An optimization system for a central plant includes a processing circuit configured to receive load prediction data indicating building energy loads and utility rate data indicating a price of one or more resources consumed by equipment of the central plant to serve the building energy loads. The optimization system includes a high level optimization module configured to generate an objective function that expresses a total monetary cost of operating the central plant over an optimization period as a function of the utility rate data and an amount of the one or more resources consumed by the central plant equipment. The optimization system includes a demand charge module configured to modify the objective function to account for a demand charge indicating a cost associated with maximum power consumption during a demand charge period. The high level optimization module is configured to optimize the objective function over the demand charge period.

Abstract: A frequency response optimization system includes a battery, a power inverter, and a frequency response controller. The battery is configured to store and discharge electric power. The power inverter is configured to control an amount of the electric power stored or discharged from the battery. The frequency response controller includes a high level controller configured to determine values of clipping parameters and a low level controller configured to use the values of the clipping parameters to modify battery power setpoints. The power inverter is configured to use the modified battery power setpoints to control the amount of the electric power stored or discharged from the battery.

Abstract: An energy cost optimization system for a building includes HVAC equipment and a controller. The controller is configured to generate a cost function defining a cost of operating the HVAC equipment as a function of one or more energy load setpoints. The controller is configured to modify the cost function to account for both an initial purchase cost of a new asset to be added to the HVAC equipment and an effect of the new asset on the cost of operating the HVAC equipment. Both the initial purchase cost of the new asset and the effect of the new asset on the cost of operating the HVAC equipment are functions of one or more asset size variables. The controller is configured to perform an optimization using the modified cost function to determine optimal values for decision variables including the energy load setpoints and the asset size variables.

Abstract: A frequency response optimization system includes a battery configured to store and discharge electric power, a power inverter configured to control an amount of the electric power stored or discharged from the battery at each of a plurality of time steps during a frequency response period, and a frequency response controller. The frequency response controller is configured to receive a regulation signal from an incentive provider, determine statistics of the regulation signal, use the statistics of the regulation signal to generate an optimal frequency response midpoint that achieves a desired change in a state-of-charge (SOC) of the battery while participating in a frequency response program, and use the midpoints to determine optimal battery power setpoints for the power inverter. The power inverter is configured to use the optimal battery power setpoints to control the amount of the electric power stored or discharged from the battery.

Abstract: A control system for a central energy facility with distributed energy storage includes a high level coordinator, a low level airside controller, a central plant controller, and a battery controller. The high level coordinator is configured to perform a high level optimization to generate an airside load profile for an airside system, a subplant load profile for a central plant, and a battery power profile for a battery. The low level airside controller is configured to use the airside load profile to operate airside HVAC equipment of the airside subsystem. The central plant controller is configured to use the subplant load profile to operate central plant equipment of the central plant. The battery controller is configured to use the battery power profile to control an amount of electric energy stored in the battery or discharged from the battery at each of a plurality of time steps in an optimization period.

Abstract: A method for operating HVAC equipment includes obtaining building data for each of a plurality of time steps. The building data relates to resource usage of HVAC equipment. The method also includes calculating a recursive residual for each of a plurality of overlapping time periods using the building data. Each overlapping time period includes a subset of the plurality of time steps. The method also includes, for each of the plurality of time steps, calculating a metric based on the recursive residuals for overlapping time periods that end on or before the time step and automatically detecting a change in static factors for one or more buildings served by the HVAC equipment by comparing the metrics for the plurality of time steps based on a statistical property of the metrics.

Abstract: An energy storage system includes a battery and an energy storage controller. The battery is configured to store electrical energy purchased from a utility and to discharge the stored electrical energy for use in satisfying a building energy load. The energy storage controller is configured to generate a cost function including multiple demand charges. Each of the demand charges corresponds to a demand charge period and defines a cost based on a maximum amount of the electrical energy purchased from the utility during any time step within the corresponding demand charge period. The controller is configured to modify the cost function by applying a demand charge mask to each of the multiple demand charges. The demand charge masks cause the controller to disregard the electrical energy purchased from the utility during any time steps that occur outside the corresponding demand charge period when calculating a value for the demand charge.

Abstract: A building energy system includes a controller configured to obtain representative loads and rates for a plurality of scenarios and generate a cost function comprising a risk attribute and multiple demand charges. Each of the demand charges corresponds to a demand charge period and defines a cost based on a maximum amount of at least one of the energy resources purchased within the corresponding demand charge period. The controller is configured to determine, for each of the multiple demand charges, a peak demand target for the corresponding demand charge period by performing a first optimization of the risk attribute over the plurality of the scenarios, allocate an amount of the one or more energy resources to be consumed, produced, stored, or discharged by the building equipment by performing a second optimization subject to one or more constraints based on the peak demand target for each of the multiple demand charges.

Abstract: A system for allocating one or more resources including electrical energy across equipment that operate to satisfy a resource demand of a building. The system includes electrical energy storage including one or more batteries configured to store electrical energy purchased from a utility and to discharge the stored electrical energy. The system further includes a controller configured to determine an allocation of the one or more resources by performing an optimization of a value function. The value function includes a monetized cost of capacity loss for the electrical energy storage predicted to result from battery degradation due to a potential allocation of the one or more resources. The controller is further configured to use the allocation of the one or more resources to operate the electrical energy storage.