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.

Abstract: A cascaded control system is configured to control power consumption of a building during a demand limiting period. The cascaded control system includes an energy use setpoint generator and a feedback controller. The energy use setpoint generator is configured to use energy pricing data and measurements of a variable condition within the building to generate an energy use setpoint during the demand limiting period. The feedback controller is configured to use a difference between the energy use setpoint and a measured energy use to generate a control signal for building equipment that operate to affect the variable condition within the building during the demand limiting period.

Abstract: A system for measuring and verifying energy savings resulting from energy conservation measures in a building includes one or more energy meters and a controller. The energy meters are configured to measure an actual amount of building energy usage The controller is configured to determine an actual amount of energy savings resulting from the energy conservation measures during the measurement and verification period and to calculate a least amount of energy savings resulting from the energy conservation measures. The least amount of energy savings is a lower confidence bound on the actual amount of energy savings. The controller is configured to cause a building management system for the building to stop performing a measurement and verification process before a normal end of the measurement and verification period in response to the least amount being greater than a target amount of energy savings to be achieved by the energy conservation measures.

Abstract: A system for generating and using a predictive model to control building equipment includes building equipment operable to affect one or more variables in a building and an operating data aggregator that collects a set of operating data for the building equipment. The system includes an autocorrelation corrector that removes an autocorrelated model error from the set of operating data by determining a residual error representing a difference between an actual output of the building equipment and an output predicted by the predictive model, using the residual error to calculate an autocorrelation for the model error, and transforming the set of operating data using the autocorrelation. The system includes a model generator module that generates a set of model coefficients for the predictive model using the transformed set of operating data and a controller that controls the building equipment by executing a model-based control strategy that uses the predictive model.

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: A power control system includes a battery, a battery power inverter configured to control an amount of the electric power stored or discharged from the battery, a photovoltaic power inverter configured to control a power output of a photovoltaic field, and a controller. The power outputs of the battery power inverter and the photovoltaic power inverter combine at a point of interconnection. The controller adjusts a setpoint for the photovoltaic power inverter in response to a determination that the total power at the point of interconnection exceeds a point of interconnection power limit.

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 computer system for use with a building management system for a building includes a processing circuit configured to automatically identify a change in a building's energy usage model based on data received from the building management system. The processing circuit may be configured to communicate the identified change in the static factor to at least one of (a) a module for alerting a user to the identified change and (b) a module for initiating an adjustment to the energy model for a building in response to the identified change.

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: A cascaded control system is configured to control power consumption of a building during a demand limiting period. The cascaded control system includes an energy use setpoint generator and a feedback controller. The energy use setpoint generator is configured to use energy pricing data and measurements of a variable condition within the building to generate an energy use setpoint during the demand limiting period. The feedback controller is configured to use a difference between the energy use setpoint and a measured energy use to generate a control signal for building equipment that operate to affect the variable condition within the building during the demand limiting period.

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: A building energy system includes equipment configured to consume, store, or discharge one or more energy resources purchased from a utility supplier. At least one of the energy resources is subject to a demand charge. The system further includes a controller configured to determine an optimal allocation of the energy resources across the equipment over a demand charge period. The controller includes a stochastic optimizer configured to obtain representative loads and rates for the building or campus for each of a plurality of scenarios, generate a first objective function comprising a cost of purchasing the energy resources over a portion of the demand charge period, and perform a first optimization to determine a peak demand target for the optimal allocation of the energy resources. The peak demand target minimizes a risk attribute of the first objective function over the plurality of the scenarios. The controller is configured to control the equipment to achieve the optimal allocation of energy resources.

Abstract: A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

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, and a controller. The controller is configured to generate optimal values for the battery power setpoints as a function of both an estimated amount of battery degradation and an estimated amount of frequency response revenue that will result from the battery power setpoints.

Abstract: A central plant includes an electrical energy storage subplant configured to store electrical energy, a plurality of generator subplants configured to consume one or more input resources, including discharged electrical energy, and a controller. The controller is configured to determine, for each time step within a time horizon, an optimal allocation of the input resources. The controller is configured to determine optimal allocation of the output resources for each of the subplants in order to optimize a total monetary value of operating the central plant over the time horizon.

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 frequency response optimization includes a battery that stores and discharges electric power, a power inverter that uses battery power setpoints to control an amount of the electric power stored or discharged from the battery, and a frequency response controller. The frequency response controller receives a regulation signal from an incentive provider, predicts future values of the regulation signal, and uses the predicted values of the regulation signal to generate the battery power setpoints for the power inverter.

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: Disclosed herein are a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system 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: 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.