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.

Abstract: An optimization controller for a battery includes a high level controller configured to receive a regulation signal from an incentive provider at a data fusion module, determine statistics of the regulation signal, and use the statistics of the regulation signal to generate a frequency response midpoint. The optimization 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 the battery during a frequency response period.

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 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, a high level controller, and a low level controller. The high level controller is 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 an optimal frequency response midpoint. The optimal midpoint achieves a desired change in the state-of-charge of the battery while participating in a frequency response program. The low level controller is configured to 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 an amount of the electric power stored or discharged from the battery.

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: A model predictive control system is used to optimize energy cost in a variable refrigerant flow (VRF) system. The VRF system includes an outdoor subsystem and a plurality of indoor subsystems. The model predictive control system includes a high-level model predictive controller (MPC) and a plurality of low-level indoor MPCs. The high-level MPC performs a high-level optimization to generate an optimal indoor subsystem load profile for each of the plurality of indoor subsystems. The optimal indoor subsystem load profiles optimize energy cost. Each of the low-level indoor MPCs performs a low-level optimization to generate optimal indoor setpoints for one or more indoor VRF units of the corresponding indoor subsystem. The indoor setpoints can include temperature setpoints and/or refrigerant flow setpoints for the indoor VRF units.

Abstract: Methods and systems to minimize energy cost in response to time-varying energy prices are presented for a variety of different pricing scenarios. A cascaded model predictive control system is disclosed comprising an inner controller and an outer controller. The inner controller controls power use using a derivative of a temperature setpoint and the outer controller controls temperature via a power setpoint or power deferral. An optimization procedure is used to minimize a cost function within a time horizon subject to temperature constraints, equality constraints, and demand charge constraints. Equality constraints are formulated using system model information and system state information whereas demand charge constraints are formulated using system state information and pricing information. A masking procedure is used to invalidate demand charge constraints for inactive pricing periods including peak, partial-peak, off-peak, critical-peak, and real-time.

Abstract: An operating data aggregator module collects a first set of operating data and a second set of operating data for building equipment. A model generator module generates a first set of model coefficients and a second set of model coefficients for a predictive model for the building equipment using the first set of operating data and the second set of operating data, respectively. A test statistic module generates a test statistic based on a difference between the first set of model coefficients and the second set of model coefficients. A critical value module calculates critical value for the test statistic. A hypothesis testing module compares the test statistic with the critical value using a statistical hypothesis test to determine whether the predictive model has changed. In response to a determination that the predictive model has changed, a fault indication may be generated and/or the predictive model may be adaptively updated.

Abstract: A system for monitoring and controlling a central plant includes a high level optimizer, a subplant monitor, a user interface, and a dispatch graphical user interface (GUI) generator. The central plant includes a plurality of subplants configured to serve a thermal energy load. The high level optimizer is configured to determine recommended subplant loads for each of the plurality of subplants. The subplant monitor is configured to monitor the central plant and identify actual subplant loads for each of the plurality of subplants. The user interface is configured to receive manual subplant loads specified by a user. The dispatch GUI generator is configured to generate a dispatch GUI and present the dispatch GUI via the user interface. The dispatch GUI includes the recommended subplant loads, the actual subplant loads, and the manual subplant loads.

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 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 frequency regulation and ramp rate control system includes a battery configured to store and discharge electric power, a battery power inverter configured to control an amount of the electric power in the battery, a photovoltaic power inverter configured to control an electric power output of a photovoltaic field, and a controller. The controller generates a battery power setpoint for the battery power inverter and a photovoltaic power setpoint for the photovoltaic power inverter. The generated setpoints cause the battery power inverter and the photovoltaic power inverter to simultaneously perform both frequency regulation and ramp rate control.

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: 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: 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 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 predictive power control system includes a battery configured to store and discharge electric power, a battery power inverter configured to control an amount of the electric power stored or discharged from the battery, and a controller. The controller is configured to predict a power output of a photovoltaic field and use the predicted power output of the photovoltaic field to determine a setpoint for the battery power inverter.

Abstract: A central plant that generates and provides resources to a building. The central plant includes an electrical energy storage subplant configured to store electrical energy purchased from a utility and to discharge the stored electrical energy. The central plant includes a plurality of generator subplants that consume one or more input resources. The central plant includes a controller configured to determine, for each time step within a time horizon, an optimal allocation of the input resources and 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. The total monetary value includes revenue from participating in incentive-based demand response programs as well as costs associated with resource consumption, equipment degradation, and losses in battery capacity.

Abstract: A building management system includes building equipment configured to consume electrical energy and generate thermal energy, thermal energy storage configured to store at least a portion of the thermal energy generated by the building equipment and to discharge the stored thermal energy, electrical energy storage configured to store electrical energy purchased from a utility and to discharge the stored electrical energy, and a controller. The controller is configured to determine, for each time step within a time horizon, an optimal amount of electrical energy stored or discharged by the electrical energy storage by optimizing a value function.

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.