A method for improving the effectiveness of a building air circulation system having motorized blower and a contamination filter. The method including predicting a cost of operation of the system over an operational duration based on at least electricity consumption of the motor (115), and an operational cost to operate the filter (148), predicting a cost of maintenance of the system over the operational duration based on at least one of, a condition of the filter (148), a cost of a filter (148), a cost of labor to clean or replace the filter (148), and an effectiveness of the filter (148) over the operational duration, and balancing the cost of operation of the circulation system versus the cost of maintenance of the circulation system over the duration to recommend at least one of a filter use/bypass schedule, a filter maintenance schedule, and a fresh air input schedule satisfying an operation objective and an operational constraint.

The invention concerns predominantly enclosed spaces, typically buildings, which are exposed to directionally and temporally varying levels of solar electromagnetic radiation, as well as temporally varying levels of ambient air temperature, flow velocity and direction. Such a building comprising at least one primary compartment and at least one secondary compartment. The primary compartment predominantly serves to achieve the primary purpose of the building. An electronic controller can modulate throughput or speed of active or passive air flow to and from the secondary compartment. The controller uses a descriptive model to predict thermal behavior of the building and to derive control signals. The control system acquires data from one or more sensors. In some embodiments the disclosed methods are at least partially incorporated in a home automation system, including internet connectivity.

Systems and methods are provided for predicting inefficient HVAC operation, by obtaining first training data for HVACs in a training set of households during a first period of moderate weather; obtaining second training data for HVACs in the training set of households during a subsequent period of harsher weather; generating classification labels of the household locations of the training set according to the second training data; applying the first training data and the classification labels to train a supervised machine learning algorithm, to generate an HVAC classification model predictive of inefficiency during periods of harsher weather conditions; obtaining operational data pertaining to HVACs in an operational set of households during a second period of moderate weather; and applying the HVAC classification model to predict inefficiency of HVACs at individual households in the operational set during a second subsequent period of harsher weather.

A building energy management system includes building equipment, a data collector, an analytics service, a timeseries database, and an energy management application. The building equipment monitor and control one or more variables in the building energy management system and provide data samples of the one or more variables. The data collector collects the data samples from the building equipment and generates a data timeseries including a plurality of the data samples. The analytics service performs one or more analytics using the data timeseries and generates a results timeseries including a plurality of result samples indicating results of the analytics. The timeseries database stores the data timeseries and the results timeseries. The energy management application retrieves the data timeseries and the results timeseries from the timeseries database in response to a request for timeseries data associated with the one or more variables.

An expectation module determines an expected average power consumption of a heat pump for a predetermined period as a function of indoor and outdoor temperatures of the building during the predetermined period. A difference module determines a power difference between an average power consumption of the heat pump during the predetermined period and the expected average power consumption of the heat pump for the predetermined period. A grade determination module determines a grade of the heat pump for the predetermined period based on the power difference of the predetermined period. A reporting module generates a displayable report including the grade of the heat pump for the predetermined period.

A system is disclosed and includes an air-conditioning load prediction unit for predicting a load of an air-conditioning unit in a future time period based on past data; an indoor temperature and humidity sensing module for sensing temperature and humidity of a building at a first time; a fan-speed sensing module for sensing a fan-speed of the air-conditioning unit at the first time; and a comfort-degree prediction module for calculating a comfort-degree that the air-conditioning unit is required to reach at a second time based on the sensed temperature, sensed humidity and sensed fan-speed; an energy management unit for controlling a central monitoring computer to set a temperature and an fan-speed of the air conditioning unit, and compare the predicted load and an actual load of the air conditioning unit for adjusting the set temperature and the set fan-speed in real time. A method of adjusting is also provided.

A temperature controlling apparatus includes a display configured to present an operating condition of the apparatus, and a communication module configured to communicate with at least one mobile device associated with the apparatus. The apparatus includes a processor in communication with a proximity detection module configured to determine a location of the at least one mobile device relative to the apparatus based on data received and initiate implementation of a home mode or an away mode of the apparatus in response to the determined location of the mobile device. The processor configured to initiate implementation of the away mode of the apparatus in response to a manual input received from a graphical user interface of the at least one mobile device.

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.

The invention comprises systems and methods for evaluating changes in the operational efficiency of an HVAC system over time. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system, and status of said HVAC system. One or more processors receives measurements of outside temperatures from at least one source other than said HVAC system and compares said temperature measurements from said first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements.

A temperature controlling apparatus includes a display configured to present an operating condition of the apparatus, and a communication module configured to communicate with at least one mobile device associated with the apparatus. The apparatus includes a processor in communication with a proximity detection module configured to determine a location of the at least one mobile device relative to the apparatus based on data received and initiate implementation of a home mode or an away mode of the apparatus in response to the determined location of the mobile device. The processor configured to initiate implementation of the away mode of the apparatus in response to a manual input received from a graphical user interface of the at least one mobile device.