Accessing an energy management policy for a plurality of devices is described, wherein the devices are coupled with a first structure. The energy usage of the devices is monitored. An energy usage rule and energy usage is then compared. The energy management policy and energy usage is also compared. Based on the comparing, an instruction is generated to modify an energy usage profile of said device to correlate with the energy usage rule associated with the devices and the energy management policy, thereby enabling efficient energy management.

Embodiments for facility management by a processor. Operations are performed to collect and track environmentally-related data of the facility over time. Predictive analytics are applied to the environmentally-related data to generate decisions that are dynamically applied to environmental settings of the facility.

Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

Systems and methods for orchestrating the operation of energy-consuming loads, so as to minimize power consumption, are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or COP. In certain aspects, a COP uses specifically programmed application programming interfaces, or APIs, to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud-based control platform, through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud-based control platforms. By these and other means, the operation of a variety of energy-consuming loads can be more easily and efficiently orchestrated.

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.

A system for a plurality of thermostats each located in a different building in a neighborhood. Each thermostat includes a processing circuit configured to receive one or more assigned operating time slots from an analytics service and operate building equipment associated with the thermostat based on the one or more assigned operating time slots. The system further includes the analytics service. The analytics service includes a processing circuit configured to receive weather forecast data from a weather service and predict a period of time during which an energy usage peak will occur for the plurality of buildings based on the weather forecast data, determine the one or more operating time slots based on the period of time, assign the one or more operating time slots to each of the plurality of thermostats, and send the one or more assigned operating time slots to the plurality of thermostats.

Heating and cooling systems at various geographical locations are controlled by a central energy management service unit to maintain comfortable indoor temperatures. In some weather conditions, people may intuitively prefer a slightly warmer or cooler indoor temperature. In systems equipped with environmental learning capabilities, an apparent outdoor temperature is determined based on the geographic location itself, the season at the geographic location, the forecasted actual temperature, and one or more seasonal weather factors such as wind velocity or humidity. The apparent temperature and a trained machine learning system are used to select an automated schedule for the geographic location to be directly transmitted to devices at the location. The automated schedule can vary from typical schedules by causing the heating and cooling systems to maintain a temperature that is slightly warmer or cooler than typical indoor temperatures.

The invention teaches a system and method for reducing energy consumption in commercial buildings. The invention provides development of certain mechanical heat profiles and use of such profiles in an automated optimization method. Outputs communicate with the building management system of the commercial building, and regulate the heating system during a season when the building activates the heating system. Various embodiments are taught.

A load management system including a number of sensors structured to sense characteristics of a managed area, a controller including a processor structured to estimate occupancy of the managed area based on outputs of the number of sensors and to implement a load management scheme, a number of circuit breakers, at least one of the number of circuit breakers being electrically connected to a corresponding load circuit and including a metering circuit structured to meter energy provided to the load circuit and a device control unit structured to control one or more load devices electrically connected to the load circuit based on the load management scheme. The processor is structured to implement the load management scheme based on outputs of the sensors and metering information of one or more of the circuit breakers.

Techniques are described for providing remote device (e.g., thermostat, lighting, appliance, etc.) control and/or energy monitoring. A system monitors sensor data captured by one or more sensors that sense attributes relevant to user presence at one or more monitored properties and status of one or more energy consuming devices associated with the one or more monitored properties. The system analyzes the monitored sensor data and the monitored device status with respect to a set of one or more rules and performs an operation related to controlling the one or more energy consuming devices based on the analysis of the monitored sensor data and the monitored device status with respect to the set of one or more rules.