Patent classifications
G05D23/1923
Methods and apparatus for achieving energy consumption goals through model-based simulations
A facility implementing systems and/or methods for achieving energy consumption/production and cost goals is described. The facility identifies various components of an energy system and assesses the environment in which those components operate. Based on the identified components and assessments, the facility generates a model to simulate different series/schedules of adjustments to the system and how those adjustments will effect energy consumption or production. Using the model, and based on identified patterns, preferences, and forecasted weather conditions, the facility can identify an optimal series or schedule of adjustments to achieve the user's goals and provide the schedule to the system for implementation. The model may be constructed using a time-series of energy consumption and thermostat states to estimate parameters and algorithms of the system. Using the model, the facility can simulate the behavior of the system and, by changing simulated inputs and measuring simulated output, optimize use of the system.
OPTIMIZATION OF ENERGY USE THROUGH MODEL-BASED SIMULATIONS
A facility implementing systems and/or methods for achieving energy consumption/production and cost goals is described. The facility identifies various components of an energy system and assesses the environment in which those components operate. Based on the identified components and assessments, the facility generates a model to simulate different series/schedules of adjustments to the system and how those adjustments will effect energy consumption or production. Using the model, and based on identified patterns, preferences, and forecasted weather conditions, the facility can identify an optimal series or schedule of adjustments to achieve the user's goals and provide the schedule to the system for implementation. The model may be constructed using a time-series of energy consumption and thermostat states to estimate parameters and algorithms of the system. Using the model, the facility can simulate the behavior of the system and, by changing simulated inputs and measuring simulated output, optimize use of the system.
SMART ENERGY SCHEDULING
Systems and techniques are described for monitoring energy use habits of consumers. In some implementations, a method includes obtaining temperature data from a monitored property. An energy model of the monitored property is generated based on the obtained temperature data. The current temperature data is obtained from the monitored property. The current temperature data is provided to the generated energy model to generate a duty-cycle for turning an HVAC system of the monitored property off an on during the on-peak hours. The HVAC system of the monitored property is instructed to cycle off and on during the on-peak hours based on the generated duty-cycle.
Smart thermostat with model predictive control and demand response integration
A system includes a plurality of thermostats corresponding to a plurality of HVAC systems that serve a plurality of spaces and a computing system communicable with the plurality of thermostats via a network. The computing system is configured to, for each space of the plurality of spaces, obtain a set of training data relating to thermal behavior of the space, identify a model of thermal behavior of the space based on the set of training data, perform a model predictive control process using the model of thermal behavior of the space to obtain a temperature setpoint for the space, and provide the temperature setpoint to the thermostat corresponding to the HVAC system serving the space. The plurality of thermostats are configured to control the plurality of HVAC systems in accordance with the temperature setpoints.
METHODS AND CIRCUITS CONFIGURED TO DETECT LOW HOT WATER RESERVE CONDITION AND RELATED ARTICLES OF MANUFACTURE
A method of operating a water heater in a load shed mode can include detecting that an upper water heater thermostat control module in a water heater is calling for heat to be provided via an upper heating element of the water heater while the water heater is in a load shed mode of operation wherein a first leg of power to the water heater is decoupled from an input to the upper water heater thermostat control module and responsive to the upper water heater thermostat control module calling for heat, transmitting a signal to end the load shed mode of operation at the water heater so that the first leg of power to the water heater is coupled to the input of the upper water heater thermostat control module so that the upper heating element of the water heater is enabled to heat water responsive to the upper water heater thermostat control module calling for heat.
Thermal energy storage apparatus, controllers and thermal energy storage control methods
Thermal energy storage apparatus, controllers and thermal energy storage control methods are described. According to one aspect, a thermal energy storage apparatus controller includes processing circuitry configured to access first information which is indicative of surpluses and deficiencies of electrical energy upon an electrical power system at a plurality of moments in time, access second information which is indicative of temperature of a thermal energy storage medium at a plurality of moments in time, and use the first and second information to control an amount of electrical energy which is utilized by a heating element to heat the thermal energy storage medium at a plurality of moments in time.
Cascaded systems and methods for controlling energy use during a demand limiting period
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.
HVAC system using model predictive control with distributed low-level airside optimization
A building HVAC system includes an airside system having a plurality of airside subsystems, a high-level model predictive controller (MPC), and a plurality of low-level airside MPCs. Each airside subsystem includes airside HVAC equipment configured to provide heating or cooling to the airside subsystem. The high-level MPC is configured to perform a high-level optimization to generate an optimal airside subsystem load profile for each airside subsystem. The optimal airside subsystem load profiles optimize energy cost. Each of the low-level airside MPCs corresponds to one of the airside subsystems and is configured to perform a low-level optimization to generate optimal airside temperature setpoints for the corresponding airside subsystem using the optimal airside subsystem load profile for the corresponding airside subsystem. Each of the low-level airside MPCs is configured to use the optimal airside temperature setpoints for the corresponding airside subsystem to operate the airside HVAC equipment of the corresponding airside subsystem.
Demand response technology utilizing a simulation engine to perform thermostat-based demand response simulations
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a thermostat-based demand response event. In one aspect, a method includes accessing, for sites, historical readings of HVAC activity, indoor temperature, and outdoor temperature and building a model for each of the sites using the historical readings of HVAC activity, indoor temperature, and outdoor temperature. The method also includes using a simulation engine to achieve a target load shed and load reduction shape for a thermostat-based demand response event, and performing the thermostat-based demand response event based on results of the simulation engine.
HVAC selective zone setpoint scheduling systems and methods
The present disclosure describes techniques for improving configuration of a heating, ventilation, and air conditioning (HVAC) system. In some embodiments, a control system of a heating, ventilation, and air conditioning (HVAC) system includes control circuitry and memory. The memory stores instructions that, when executed by the control circuitry, causes the control circuitry to control air flow supplied to a first building zone by the HVAC system based on a temperature setpoint schedule associated with the first building zone; and control air flow supplied to a second building zone by the HVAC system based on a constant temperature setpoint associated with the second building zone.