Abstract: Embodiments determine the effect of an environmental maintenance device on other environmental maintenance devices in environmentally controlled space. The determined effects may be modeled and graphically represented using, for example, an effectiveness map. In the case of a data center, an exemplary effectiveness map may illustrate the effect that one or more computer room air conditioners (CRACs) have on themselves and on other CRACs in the data center. In the case of an office building, an exemplary effectiveness map may illustrate the effect that one or more selected variable air volume (VAV) terminal units have on their own thermostat readings and the thermostat readings of other VAV terminal units in the office building.

Abstract: Embodiments determine the effect of an environmental maintenance device on other environmental maintenance devices in environmentally controlled space. The determined effects may be modeled and graphically represented using, for example, an effectiveness map. In the case of a data center, an exemplary effectiveness map may illustrate the effect that one or more computer room air conditioners (CRACs) have on themselves and on other CRACs in the data center. In the case of an office building, an exemplary effectiveness map may illustrate the effect that one or more selected variable air volume (VAV) terminal units have on their own thermostat readings and the thermostat readings of other VAV terminal units in the office building.

Abstract: Methods are provided for calculating a reserve value or a risk value for various locations in an environmentally-controlled space such as a data center, and using the reserve value or risk value to allocate environmental maintenance modules and/or load. For example, an influence model can predict a change in a sensor value at a location for a corresponding change in an operation level of an actuator of one of the environmental maintenance modules. Based on the influence model and an operation level of the actuator, a reserve value can be determined for the location. A risk value for the location can be determined using a risk metric that may use the reserve value, a current sensor value at the location, and a threshold sensor value at the location.

Abstract: Systems and methods of stabilizing HVAC systems with multiple HVAC units configured to control return air temperature or discharge air temperature are provided. HVAC units that are controlled by the return air temperature compare the return air temperature to a setpoint that determines whether the HVAC unit's operation increases, decreases, or stays the same. By adjusting the setpoint of an HVAC unit based on certain criteria (e.g., a desired operational effort of an HVAC unit) the system can be stabilized. A temperature setpoint reset (TSPR) system can be included in each HVAC unit that resets the temperature setpoint (TSP) of the HVAC unit so that the HVAC unit operates within a desired operational effort (e.g. compressor speed or valve position). A master feedback loop and optimizer loop may be implemented to further control the behavior of the HVAC system.

Abstract: A method of obtaining an operational redundancy value, for a system having a plurality of environmental maintenance modules for maintaining an environmental value within a specified range, includes monitoring the modules while the modules are running, to receive operational data regarding a level of operation of each of the modules. The method also includes determining an operational weight for each of the modules based on the operational data of each of the modules, computing an available capacity of the system based on the operational weights of the modules, and determining a required capacity for the system to maintain the environmental value within the specified range when a load exists for the modules. The method also includes calculating the operational redundancy value based on the available capacity and the required capacity and providing a message based on the operational redundancy value.

Abstract: Methods are provided for calculating a reserve value or a risk value for various locations in an environmentally-controlled space such as a data center, and using the reserve value or risk value to allocate environmental maintenance modules and/or load. For example, an influence model can predict a change in a sensor value at a location for a corresponding change in an operation level of an actuator of one of the environmental maintenance modules. Based on the influence model and an operation level of the actuator, a reserve value can be determined for the location. A risk value for the location can be determined using a risk metric that may use the reserve value, a current sensor value at the location, and a threshold sensor value at the location.

Abstract: A control strategy for heating, ventilating, and air-conditioning (HVAC) units used to condition the environment in data centers and other commercial buildings such as retail stores with an open-plan design is provided to coordinate the operation of the actuators of the HVAC units. A supervisory controller receives feedback signals from a plurality of environmental sensors and uses a set of references values to determine control signals to the actuators of the HVAC units. A pseudoinverse of a transfer function matrix G may be used to determine the control signals from errors in the feedback signals relative to the reference signals.

Abstract: Methods and systems for controlling environmental maintenance modules (e.g. HVAC units) using sensors are provided. Values measured by the sensors can be used to determine a change in operation levels of the modules to keep the sensor values within a desired range. For example, a stopped module can be increased or started for more cooling when a sensor temperature is too hot. The module predicted to have the greatest effect on the temperature of hot sensor can be started. As another example, a module can be stopped (or otherwise have an operation level decreased), if the sensor temperatures are within range, and the decrease in operation level is predicted not to cause an out-of-range condition.

Abstract: Methods, systems, and apparatuses are provided for controlling an environmental maintenance system that includes a plurality of sensors and a plurality of actuators. The operation levels of the actuators can be determined by optimizing a penalty function. As part of the penalty function, the sensor values can be compared to reference values. The optimized values of the operation levels can account for energy use of actuators at various operation levels and predicted differences of the sensor values relative to the reference values at various operation levels. The predicted difference can be determined using a transfer model. An accuracy of the transfer model can be determined by comparing predicted values to measured values. This accuracy can be used in determining new operational levels from an output of the transfer model (e.g., attenuating the output of the transfer model based on the accuracy).

Abstract: Methods, systems, and apparatuses are provided for controlling an environmental maintenance system that includes a plurality of sensors and a plurality of actuators. The operation levels of the actuators can be determined by optimizing a penalty function. As part of the penalty function, the sensor values can be compared to reference values. The optimized values of the operation levels can account for energy use of actuators at various operation levels and predicted differences of the sensor values relative to the reference values at various operation levels. The predicted difference can be determined using a transfer model. An accuracy of the transfer model can be determined by comparing predicted values to measured values. This accuracy can be used in determining new operational levels from an output of the transfer model (e.g., attenuating the output of the transfer model based on the accuracy).

Abstract: Methods, systems, and apparatuses are provided for controlling an environmental maintenance system that includes a plurality of sensors and a plurality of actuators. The operation levels of the actuators can be determined by optimizing a penalty function. As part of the penalty function, the sensor values can be compared to reference values. The optimized values of the operation levels can account for energy use of actuators at various operation levels and predicted differences of the sensor values relative to the reference values at various operation levels. The predicted difference can be determined using a transfer model. An accuracy of the transfer model can be determined by comparing predicted values to measured values. This accuracy can be used in determining new operational levels from an output of the transfer model (e.g., attenuating the output of the transfer model based on the accuracy).

Abstract: Methods and systems for controlling environmental maintenance modules (e.g. HVAC units) using sensors are provided. Values measured by the sensors can be used to determine a change in operation levels of the modules to keep the sensor values within a desired range. For example, a stopped module can be increased or started for more cooling when a sensor temperature is too hot. The module predicted to have the greatest effect on the temperature of hot sensor can be started. As another example, a module can be stopped (or otherwise have an operation level decreased), if the sensor temperatures are within range, and the decrease in operation level is predicted not to cause an out-of-range condition.

Abstract: Systems, apparatus, and methods for controlling environmental maintenance modules (e.g. HVAC units) using sensors are provided. Values measured by the sensors can be used to determine a change in operation levels of the modules to keep the sensor values within a desired range. For example, a stopped module can be increased or started for more cooling when a sensor temperature is too hot. The module predicted to have the greatest effect on the temperature of hot sensor can be started. A transfer matrix, which provides a relation between a change in operation level and resulting sensor changes, can be used to perform the above predictions. As another example, a module can be stopped (or otherwise have an operation level decreased), if the sensor temperatures are within range, and the decrease in operation level is predicted not to cause an out-of-range condition.

Abstract: A control strategy for heating, ventilating, and air-conditioning (HVAC) units used to condition the environment in data centers and other commercial buildings such as retail stores with an open-plan design is provided to coordinate the operation of the actuators of the HVAC units. A supervisory controller receives feedback signals from a plurality of environmental sensors and uses a set of references values to determine control signals to the actuators of the HVAC units. A pseudoinverse of a transfer function matrix G may be used to determine the control signals from errors in the feedback signals relative to the reference signals.

Abstract: A control strategy for heating, ventilating, and air-conditioning (HVAC) units used to condition the environment in data centers and other commercial buildings such as retail stores with an open-plan design is provided to coordinate the operation of the actuators of the HVAC units. A supervisory controller receives feedback signals from a plurality of environmental sensors and uses a set of references values to determine control signals to the actuators of the HVAC units. A pseudoinverse of a transfer function matrix G may be used to determine the control signals from errors in the feedback signals relative to the reference signals.

Abstract: Methods, systems, and apparatuses are provided for controlling an environmental maintenance system that includes a plurality of sensors and a plurality of actuators. The operation levels of the actuators can be determined by optimizing a penalty function. As part of the penalty function, the sensor values can be compared to reference values. The optimized values of the operation levels can account for energy use of actuators at various operation levels and predicted differences of the sensor values relative to the reference values at various operation levels. The predicted difference can be determined using a transfer model. An accuracy of the transfer model can be determined by comparing predicted values to measured values. This accuracy can be used in determining new operational levels from an output of the transfer model (e.g., attenuating the output of the transfer model based on the accuracy).

Abstract: Systems, apparatus, and methods for controlling environmental maintenance modules (e.g. HVAC units) using sensors are provided. Values measured by the sensors can be used to determine a change in operation levels of the modules to keep the sensor values within a desired range. For example, a stopped module can be increased or started for more cooling when a sensor temperature is too hot. The module predicted to have the greatest effect on the temperature of hot sensor can be started. A transfer matrix, which provides a relation between a change in operation level and resulting sensor changes, can be used to perform the above predictions. As another example, a module can be stopped (or otherwise have an operation level decreased), if the sensor temperatures are within range, and the decrease in operation level is predicted not to cause an out-of-range condition.

Abstract: A control strategy for heating, ventilating, and air-conditioning (HVAC) units used to condition the environment in data centers and other commercial buildings such as retail stores with an open-plan design is provided to coordinate the operation of the actuators of the HVAC units. A supervisory controller receives feedback signals from a plurality of environmental sensors and uses a set of references values to determine control signals to the actuators of the HVAC units. A pseudoinverse of a transfer function matrix G may be used to determine the control signals from errors in the feedback signals relative to the reference signals.

Abstract: A differential pressure based flow rate measurement device is provided which is coupled to surfaces of a blade 30 within a damper assembly 10, such as that provided within a variable air volume (VAV) box or within a liquid valve assembly. A blade 30 which includes a leading surface 32 opposite a trailing surface 34 is fitted with a sensing structure 50. The sensing structure 50 includes portions 52, 54 which extend away from the leading surface 32. Sensing holes 56 pass into a hollow interior of the sensing structure 50 and pass on to a pressure sensor 60. A similar sensing structure 50 is also provided extending from the trailing surface 34 which also has sensing holes 56 located therein. The sensing holes 56 coupled to the trailing surface 34 also lead to the pressure sensor 60 so that a differential pressure between the sensing holes 56 on either sides of the blade 30 can be measured.

Abstract: A differential pressure based flow rate measurement device is provided which is coupled to surfaces of a blade 30 within a damper assembly 10, such as that provided within a variable air volume (VAV) box or within a liquid valve assembly. A blade 30 which includes a leading surface 32 opposite a trailing surface 34 is fitted with a sensing structure 50. The sensing structure 50 includes portions 52, 54 which extend away from the leading surface 32. Sensing holes 56 pass into a hollow interior of the sensing structure 50 and pass on to a pressure sensor 60. A similar sensing structure 50 is also provided extending from the trailing surface 34 which also has sensing holes 56 located therein. The sensing holes 56 coupled to the trailing surface 34 also lead to the pressure sensor 60 so that a differential pressure between the sensing holes 56 on either sides of the blade 30 can be measured.