This Patent application is based on a new method for calculating the hourly heating load for the heating elements of HVAC systems, with a potential for saving over 50% of the current fuel use by these systems. The method is based on using hourly outside air temperature from one or more thermometer installed along the vertical center of each of the building's orientations, and at the roof center. The temperature data, the building surface areas with different heat transmission characteristics in each orientation, plus hourly air infiltration rate into the building, adjusted for overall system efficiency, and Codes and regulatory requirements would yield the total hourly heating load. The fuel feed would then be automatically adjusted to release the hourly required fuel volume, or wattage, to the heating elements. The installed thermometer system could also be used to calculate the hourly cooling load for the building's air conditioning system, during the summer season.

An HVAC system within a building including an HVAC device having an air filter, a number of sensors, and a control device. The control device has a processor that is configured to determine a current air quality metric based on air quality measurements received by the sensor. The control device is further configured to calculate an average air quality metric based on the current air quality metric and a set of previous air quality metrics. The control device is further configured to store the average air quality metric. The control device is further configured to generate an air filter type recommendation based on the average air quality metric.

A system is disclosed to obtain energy consumption data for an energy monitored property. An identification module is configured to identify, based on first actual energy usage data for the energy-monitored property, one or more daily, weekly, or monthly future time periods when energy consumption is not likely to occur or is likely minimal within the energy-monitored property. A calibration module is configured to transmit electrical signals to open and close at least one of the gas valve and an AC unit switch in accordance with the calibration schedule during a period of time within the one or more daily, weekly, or monthly future periods of time. A computational module may be utilized to calculate a first computed flow rate for the at least one of the gas valve and the AC unit switch. A method and computer program product related to the foregoing system are also disclosed.

A system, method and apparatus for augmenting a building control system domain. A sensor network platform can be configured to collect data based on measurements from sensors outside of a legacy building control system domain, and to present information based on the collected data to a known interface supported by the legacy building control system. In one embodiment, the collected data can undergo customized processing by an operation center outside of the legacy building control system domain.

HVAC load can be shifted to change indoor temperature. A time series change in HVAC load data is used as input modified scenario values that represent an HVAC load shape. The HVAC load shape is selected to meet desired energy savings goals, such as reducing or flattening peak energy consumption load to reduce demand charges, moving HVAC consumption to take advantage of lower utility rates, or moving HVAC consumption to match PV production. Time series change in indoor temperature data can be calculated using only inputs of time series change in the time series HVAC load data combined with thermal mass, thermal conductivity, and HVAC efficiency. The approach is applicable for both winter and summer and can be applied when the building has an on-site renewable power system.

An energy management system is configured to calculate a percentage of satisfied based on the report data for each of the plurality of buildings; create, for each of the plurality of buildings, a plan for operating each of the air-conditioning facilities based on the percentage of satisfied and a predetermined target percentage of satisfied; calculate a first energy consumption amount based on the first piece of data; calculate a second energy consumption amount based on the second piece of data, the third piece of data, and the fourth piece of data, the second energy consumption amount being obtained when the each of the air-conditioning facilities is operated after a lapse of a predetermined time period; and control, when the first energy consumption amount is larger than the second energy consumption amount, the operation of the each of the air-conditioning facilities so as to achieve the second energy consumption amount.

A variable refrigerant flow system for a building includes a plurality of indoor units, a first outdoor unit, an outdoor meter, and a variable refrigerant flow management system. The plurality of indoor units configured to generate activation requests. The first outdoor unit is configured to receive the activation requests and, in response to the activation requests, provide a refrigerant to the plurality of indoor units. The outdoor meter is configured to provide an outdoor unit electricity consumption measurement. The variable refrigerant flow management system is configured to receive the outdoor unit electricity consumption measurement and activation data indicating the activation requests and apportion an outdoor share of the outdoor electricity consumption measurement to each of the plurality of indoor units based on the activation data.

An air conditioning capacity presenting system presents a capacity of an air conditioning apparatus including at least one outdoor unit, at least one indoor unit, and a connection pipe that connects the outdoor unit and the indoor unit. The air conditioning capacity presenting system includes first acquisition unit, a measurement unit, a second acquisition unit, and a capacity calculating unit. The first acquisition unit acquires outdoor unit capacity information, which is a rated capacity of the outdoor unit or information related to the rated capacity. The measurement unit measures power consumption of the outdoor unit. The second acquisition unit acquires an outside air temperature, which is a temperature of air around the outdoor unit. The capacity calculating unit obtains a calculation value of the capacity of the air conditioning apparatus based on the outdoor unit capacity information, the power consumption, and the outside air temperature.

An HVAC system within a building including an HVAC device having an air filter, a number of sensors, and a control device. The control device has a processor that is configured to determine a current air quality metric based on air quality measurements received by the sensor. The control device is further configured to calculate an average air quality metric based on the current air quality metric and a set of previous air quality metrics. The control device is further configured to store the average air quality metric. The control device is further configured to generate an air filter type recommendation based on the average air quality metric.

A bi-level optimization scheduling method for an air conditioning system based on demand response includes: constructing a lumped heat capacity model to describe a heat storage capacity of a building to thereby obtain a building heat storage model; obtaining a function relational expression of describing an indoor dry bulb temperature and a cooling and heating load of the building based on the building heat storage model; constructing a power consumption calculation model under a working condition of demand response based on the function relational expression; constructing optimization objective functions based on the power consumption calculation model; and substituting the optimization objective functions into a bi-level optimization process, and optimizing the bi-level optimization process to obtain an optimal scheduling strategy for the air conditioning system participating in demand response. The method can achieve a global optimization of demand response scheduling strategy, and improve economy and energy saving of system operation.