Patent Publication Number: US-2023160596-A1

Title: Hvac system for reducing intra-space variation of controlled environmental conditions

Description:
BACKGROUND 
     Buildings are increasingly implementing variable refrigerant flow (VRF) systems into the building heating, ventilation, and air conditioning (HVAC) systems. This can generally increase efficiency compared to other techniques (e.g., duct-based HVAC systems, etc.) as the refrigerant can be supplied directly to the indoor units (IDU&#39;s) of the VRF system. Certain building zones may be equipped with multiple IDU&#39;s that are all configured to serve a single zone. These multiple IDU&#39;s may also be supplied conditioned air to reach a single setpoint, rather than individual setpoint for each of the multiple IDU&#39;s. 
     In such an example, each IDU may serve a particular zone of the building space, and each IDU is conditioning the air in their respective zone to reach a single setpoint. However, several factors (e.g., number of occupants, fenestration, location of occupants within the space, time of day, outside air temperature, etc.) can affect the spatial distribution of the temperature within the particular zones, creating an uneven heat map for the building space. To limit this, one or more of the setpoints of the particular zones in the building space may need to be adjusted. However, changing the zone temperature setpoint of a particular zone in a building space can have indirect effect on adjacent zones. Cost, occupant comfort, and energy efficiency may also be considered when adjusting the zone temperatures. Accordingly, there exists a need to determine the optimal IDU temperature distribution for all IDUs within a single space based on the heat map within the space. 
     SUMMARY 
     This summary is illustrative only and is not intended to be in any way limiting. Other aspects, inventive features, and advantages of the devices or processes described herein will become apparent in the detailed description set forth herein, taken in conjunction with the accompanying figures, wherein like reference numerals refer to like elements. 
     One implementation of the present disclosure is a heating, ventilation, or air conditioning (HVAC) system for reducing temperature variation within a building space. The HVAC system includes a plurality of heat transfer devices distributed across a plurality of zones of the building space and operable to transfer heat into or out of the plurality zones. The HVAC system further includes a controller comprising one or more processing circuits configured to obtain a heat map indicating zone temperatures of the plurality of zones, use a thermal model of the building space to predict the zone temperatures as a function of control decisions indicating an amount of heat to transfer into or out of each of the plurality of zones by the plurality of heat transfer devices, determine the amount of heat to transfer into or out of each of the plurality of zones subject to a constraint or penalty based on differences between the zone temperatures predicted to result from the control decisions, operate the plurality of heat transfer devices to transfer the amount of heat into or out of each of the plurality of zones in accordance with the control decisions. 
     In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones includes performing an optimization of an objective function subject to the constraint or penalty based on the differences between the zone temperatures predicted to result from the control decisions. In some embodiments, the control decisions indicating the amount of heat to transfer into or out of each of the plurality of zones by the plurality of heat transfer devices are generated as a result of performing the optimization. 
     In some embodiments, the heat map indicates which of the plurality of zones are located adjacent to each other and capable of exchanging heat with each other. In some embodiments, the thermal model of the building space is used to predict the zone temperatures as a function of an amount of heat transfer between two or more of the plurality of zones that are located adjacent to each other. 
     In some embodiments, the constraint or penalty includes a penalty term. In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones comprises calculating a value of the penalty term based on the differences between the zone temperatures predicted to result from the control decisions. 
     In some embodiments, the constraint or penalty includes a temperature variation constraint that requires the differences between the zone temperatures predicted using the thermal model to be less than or equal to one or more threshold values. In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones includes using the temperature variation constraint to prevent the controller from generating control decisions that would violate the temperature variation constraint. 
     In some embodiments, the one or more processing circuits are configured to determine an occupancy status of a zone of the plurality of zones, the occupancy status indicating whether the zone is occupied and adjust a value of the constraint or penalty associated with the zone based on the occupancy status. 
     In some embodiments, the one or more processing circuits are configured to estimate a plurality of heat load disturbances affecting the plurality of zones. In some embodiments, the thermal model of the building space is used to predict the zone temperatures as a function of the heat load disturbances. 
     In some embodiments, the plurality of heat transfer devices include indoor units of a variable refrigerant flow system, each of the indoor units located within a different zone of the plurality of zones. 
     Another implementation of the present disclosure is a method for operating a heating, ventilation, or air conditioning (HVAC) system to reduce temperature variation within a building space. The method includes obtaining a heat map indicating zone temperatures of a plurality of zones of the building space, using a thermal model of the building space to predict the zone temperatures as a function of control decisions indicating an amount of heat to transfer into or out of each of the plurality of zones, determining the amount of heat to transfer into or out of each of the plurality of zones subject to a constraint or penalty based on differences between the zone temperatures predicted to result from the control decisions, and operating a plurality of heat transfer devices distributed across the plurality of zones to transfer the amount of heat into or out of each of the plurality of zones in accordance with the control decisions. 
     In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones includes performing an optimization of an objective function subject to the constraint or penalty based on the differences between the zone temperatures predicted to result from the control decisions. In some embodiments, the control decisions indicating the amount of heat to transfer into or out of each of the plurality of zones by the plurality of heat transfer devices are generated as a result of performing the optimization. 
     In some embodiments, the heat map indicates which of the plurality of zones are located adjacent to each other and capable of exchanging heat with each other. In some embodiments, the thermal model of the building space is used to predict the zone temperatures as a function of an amount of heat transfer between two or more of the plurality of zones that are located adjacent to each other. 
     In some embodiments, the constraint or penalty includes a penalty term. In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones includes calculating a value of the penalty term based on the differences between the zone temperatures predicted to result from the control decisions. 
     In some embodiments, the constraint or penalty includes a temperature variation constraint that requires the differences between the zone temperatures predicted using the thermal model to be less than or equal to one or more threshold values and determining the amount of heat to transfer into or out of each of the plurality of zones includes using the temperature variation constraint to prevent the controller from generating control decisions that would violate the temperature variation constraint. 
     In some embodiments, the method includes determining an occupancy status of a zone of the plurality of zones, the occupancy status indicating whether the zone is occupied and adjusting a value of the constraint or penalty associated with the zone based on the occupancy status. 
     In some embodiments, the method includes estimating a plurality of heat load disturbances affecting the plurality of zones. In some embodiments, the thermal model of the building space is used to predict the zone temperatures as a function of the heat load disturbances. 
     Another implementation of the present disclosure is a heating, ventilation, or air conditioning (HVAC) controller for reducing temperature variation within a building space. The HVAC controller including one or more processing circuits configured to obtain a heat map indicating zone temperatures of a plurality of zones of the building space, use a thermal model of the building space to predict the zone temperatures as a function of control decisions indicating an amount of heat to transfer into or out of each of the plurality of zones, determine the amount of heat to transfer into or out of each of the plurality of zones subject to a constraint or penalty based on differences between the zone temperatures predicted to result from the control decisions, and operate a plurality of heat transfer devices distributed across the plurality of zones to transfer the amount of heat into or out of each of the plurality of zones in accordance with the control decisions. 
     In some embodiments, determining the amount of heat to transfer into or out of each of the plurality of zones includes performing an optimization of an objective function subject to the constraint or penalty based on the differences between the zone temperatures predicted to result from the control decisions. In some embodiments, the control decisions indicating the amount of heat to transfer into or out of each of the plurality of zones by the plurality of heat transfer devices are generated as a result of performing the optimization. 
     In some embodiments, the heat map indicates which of the plurality of zones are located adjacent to each other and capable of exchanging heat with each other. In some embodiments, the thermal model of the building space is used to predict the zone temperatures as a function of an amount of heat transfer between two or more of the plurality of zones that are located adjacent to each other. 
     In some embodiments, the constraint or penalty includes a penalty term, and determining the amount of heat to transfer into or out of each of the plurality of zones includes calculating a value of the penalty term based on the differences between the zone temperatures predicted to result from the control decisions. 
     In some embodiments, the one or more processing circuits are configured to determine an occupancy status of a zone of the plurality of zones, the occupancy status indicating whether the zone is occupied, and adjust a value of the constraint or penalty associated with the zone based on the occupancy status. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a drawing of a building with a heating, ventilation, or air conditioning (HVAC) system, according to some embodiments. 
         FIG.  2    is a schematic of a waterside system which can be used as part of the HVAC system of  FIG.  1   , according to some embodiments, 
         FIG.  3    is a diagram of an airside system, which can be used as part of the HVAC system of  FIG.  1   , according to some embodiments. 
         FIG.  4    is a block diagram of a building management system (BMS) which can be used in the building of  FIG.  1   , according to some embodiments. 
         FIG.  5    is a diagram of a variable refrigerant flow (VRF) system, which can be implemented in the building of  FIG.  1   , according to some embodiments. 
         FIG.  6    is a diagram of a piping configuration for a VRF system, which can be implemented in the VRF system of  FIG.  5   , according to some embodiments. 
         FIG.  7    is a diagram of an outdoor unit in communication with multiple indoor units, which can be implemented in the VRF system of  FIG.  5   , according to some embodiments. 
         FIG.  8    is a block diagram of a controller for reducing intra-space variation of controlled environmental conditions, which can be implemented in the VRF system of  FIG.  5   , according to some embodiments. 
         FIG.  9 A  is a block diagram of a controller performing setpoint optimization using a received heat map, which can be implemented by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  9 B  is a block diagram of a controller performing setpoint optimization using a generated heat map, which can be implemented by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  10    is a diagram of a heat map of a building space with rooms, which can be generated by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  11    is a diagram of a heat map of a building space with rooms, which can be generated by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  12    is a diagram of a heat map of an open floor building space, which can be generated by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  13    is a diagram of an air index map, which can be generated by the controller of  FIG.  8   , according to some embodiments. 
         FIG.  14    is a flow diagram of a process for performing temperature distribution within a building space, which can be performed by the controller of  FIG.  8   , according to some embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     Overview 
     Before turning to the FIGURES, which illustrate certain exemplary embodiments in detail, it should be understood that the present disclosure is not limited to the details or methodology set forth in the description or illustrated in the FIGURES. It should also be understood that the terminology used herein is for the purpose of description only and should not be regarded as limiting. 
     Referring generally to the FIGURES, systems and methods for obtaining (e.g., receiving, generating, etc.) a heat map for a building space (e.g., a building region including one or more zones, etc.) served by two or more indoor units (IDUs) and determining an optimal setpoint for the IDUs in the building space is shown, according to some embodiments. The determination of the setpoints for some or all of the IDUs may be dependent on heat data associated with the building space (e.g., via the obtained heat map, etc.). In some embodiments, an objective of the systems and methods described herein is to minimize the temperature variation throughout the heat map of the building space. Temperature variation in a building space may be caused by a host of factors, such as the number of building occupants present in a building space, the amount of sunlight entering the building space, and one or more windows being open in the building space. 
     One or more processing circuits may be configured to process the information from the obtained heat map and determine an optimal setpoint for each IDU in the building space such that the heat map with subsequently have uniform distribution (e.g., in order to avoid having very cold or very hot spots within the building space). The process may require near-continuous and/or continuous measurement of the heat map, which may serve as feedback for the one or more processing circuits for determining the control action. Advantageously, the techniques described herein increase comfort within the building spaces while allowing for a reduction in energy costs. In addition, the one or more processing circuits may be configured to “ignore” certain areas of the heat map where no occupants are located (e.g., for large building spaces, etc.) to avoid unnecessary cooling or heat in an unused area within the building space. 
     As described herein, the term “space” may refer to any general region located within a building, campus, home, or other structure. Typically, the term “space” refers to a region that includes multiple zones (e.g., smaller regions within the space, etc.). In some embodiments, these zones can be served by any number of heat transfer devices (e.g., IDUs, etc.) that can be configured to provide or remove heat from the zone(s). Zones may be served by one heat transfer device or multiple devices at a time. In particular, the term “zone” is not limited to a room (e.g., a zone surrounded by walls, etc.) within the space. In some embodiments, the term “space” refers to an open floor plan space (e.g., a cafeteria, etc.) and the zones within the space are areas within the space. For example, the northeast corner of the open floor space, the southeast corner, the northwest corner, and the southwest corner are each a zone within the space. In some embodiments, the zones within a space may include both areas that are confined at least partially by walls—such as rooms, offices, etc.—and areas that are not confined by walls, such as open areas within an open floor space. 
     As described herein, the term “substantially equalize” may refer to substantially equalizing temperature and/or heat distribution throughout a building space. Substantially equalize may include equalizing the temperature completely (e.g., the entire building space is 71° at each location within the space), and may include equalizing the temperature substantially. Substantially, as referred to herein, may include the temperatures within multiple areas of the zone being within a predetermined threshold/range of one another. In one non-limiting example, this includes each of the temperatures within the space limited to a difference of 5% in variation. Of course, 5% is exemplary and should not be considered limiting, and the example could include any percentage (e.g., 10%, 20%, etc.). In another non-limiting example, this includes each of the temperatures being above or below a predetermined value, such as above 70° and below 72°. 
     It should be noted that while the systems and methods disclosed herein are generally using heat maps to achieve substantially equal temperature distribution within a space, this is merely meant to be exemplary and should not be considered limiting. In various other embodiments, other types of maps can be used either independently or in conjunction with heat maps to make control decisions. For example, the systems and methods disclosed herein may utilize air quality index maps to improve the air quality within the building (e.g., by reducing fine particulate matter, PM 2.5 , by optimizing CO 2  mixing between zones within the building, etc.). This is described in greater detail with reference to  FIG.  13   . 
     Building Management System and HVAC System 
     Building Site 
     Referring now to  FIG.  1   , a perspective view of a building  10  is shown. Building  10  is served by a building management system (BMS). A BMS is, in general, a system of devices configured to control, monitor, and manage equipment in or around a building or building area. A BMS can include, for example, a HVAC system, a security system, a lighting system, a fire alerting system, any other system that is capable of managing building functions or devices, or any combination thereof. 
     The BMS that serves building  10  includes a HVAC system  100 . HVAC system  100  may include a plurality of HVAC devices (e.g., heaters, chillers, air handling units, pumps, fans, thermal energy storage, etc.) configured to provide heating, cooling, ventilation, or other services for building  10 . For example, HVAC system  100  is shown to include a waterside system  120  and an airside system  130 . Waterside system  120  may provide a heated or chilled fluid to an air handling unit of airside system  130 . Airside system  130  may use the heated or chilled fluid to heat or cool an airflow provided to building  10 . In some embodiments, waterside system  120  is replaced with a central energy plant such as central plant  200 , described with reference to  FIG.  2   . 
     Still referring to  FIG.  1   , HVAC system  100  is shown to include a chiller  102 , a boiler  104 , and a rooftop air handling unit (AHU)  106 . Waterside system  120  may use boiler  104  and chiller  102  to heat or cool a working fluid (e.g., water, glycol, etc.) and may circulate the working fluid to AHU  106 . In various embodiments, the HVAC devices of waterside system  120  may be located in or around building  10  (as shown in  FIG.  1   ) or at an offsite location such as a central plant (e.g., a chiller plant, a steam plant, a heat plant, etc.). The working fluid may be heated in boiler  104  or cooled in chiller  102 , depending on whether heating or cooling is required in building  10 . Boiler  104  may add heat to the circulated fluid, for example, by burning a combustible material (e.g., natural gas) or using an electric heating element. Chiller  102  may place the circulated fluid in a heat exchange relationship with another fluid (e.g., a refrigerant) in a heat exchanger (e.g., an evaporator) to absorb heat from the circulated fluid. The working fluid from chiller  102  and/or boiler  104  may be transported to AHU  106  via piping  108 . 
     AHU  106  may place the working fluid in a heat exchange relationship with an airflow passing through AHU  106  (e.g., via one or more stages of cooling coils and/or heating coils). The airflow may be, for example, outside air, return air from within building  10 , or a combination of both. AHU  106  may transfer heat between the airflow and the working fluid to provide heating or cooling for the airflow. For example, AHU  106  may include one or more fans or blowers configured to pass the airflow over or through a heat exchanger containing the working fluid. The working fluid may then return to chiller  102  or boiler  104  via piping  110 . 
     Airside system  130  may deliver the airflow supplied by AHU  106  (i.e., the supply airflow) to building  10  via air supply ducts  112  and may provide return air from building  10  to AHU  106  via air return ducts  114 . In some embodiments, airside system  130  includes multiple variable air volume (VAV) units  116 . For example, airside system  130  is shown to include a separate VAV unit  116  on each floor or zone of building  10 . VAV units  116  may include dampers or other flow control elements that can be operated to control an amount of the supply airflow provided to individual zones of building  10 . In other embodiments, airside system  130  delivers the supply airflow into one or more zones of building  10  (e.g., via air supply ducts  112 ) without using intermediate VAV units  116  or other flow control elements. AHU  106  may include various sensors (e.g., temperature sensors, pressure sensors, etc.) configured to measure attributes of the supply airflow. AHU  106  may receive input from sensors located within AHU  106  and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU  106  to achieve setpoint conditions for the building zone. 
     Waterside System 
     Referring now to  FIG.  2   , a block diagram of a central plant  200  is shown, according to an exemplary embodiment. In brief overview, central plant  200  may include various types of equipment configured to serve the thermal energy loads of a building or campus (i.e., a system of buildings). For example, central plant  200  may include heaters, chillers, heat recovery chillers, cooling towers, or other types of equipment configured to serve the heating and/or cooling loads of a building or campus. Central plant  200  may consume resources from a utility (e.g., electricity, water, natural gas, etc.) to heat or cool a working fluid that is circulated to one or more buildings or stored for later use (e.g., in thermal energy storage tanks) to provide heating or cooling for the buildings. In various embodiments, central plant  200  may supplement or replace waterside system  120  in building  10  or may be implemented separate from building  10  (e.g., at an offsite location). 
     Central plant  200  is shown to include a plurality of subplants  202 - 212  including a heater subplant  202 , a heat recovery chiller subplant  204 , a chiller subplant  206 , a cooling tower subplant  208 , a hot thermal energy storage (TES) subplant  210 , and a cold thermal energy storage (TES) subplant  212 . Subplants  202 - 212  consume resources from utilities to serve the thermal energy loads (e.g., hot water, cold water, heating, cooling, etc.) of a building or campus. For example, heater subplant  202  may be configured to heat water in a hot water loop  214  that circulates the hot water between heater subplant  202  and building  10 . Chiller subplant  206  may be configured to chill water in a cold water loop  216  that circulates the cold water between chiller subplant  206  and building  10 . Heat recovery chiller subplant  204  may be configured to transfer heat from cold water loop  216  to hot water loop  214  to provide additional heating for the hot water and additional cooling for the cold water. Condenser water loop  218  may absorb heat from the cold water in chiller subplant  206  and reject the absorbed heat in cooling tower subplant  208  or transfer the absorbed heat to hot water loop  214 . Hot TES subplant  210  and cold TES subplant  212  may store hot and cold thermal energy, respectively, for subsequent use. 
     Hot water loop  214  and cold water loop  216  may deliver the heated and/or chilled water to air handlers located on the rooftop of building  10  (e.g., AHU  106 ) or to individual floors or zones of building  10  (e.g., VAV units  116 ). The air handlers push air past heat exchangers (e.g., heating coils or cooling coils) through which the water flows to provide heating or cooling for the air. The heated or cooled air may be delivered to individual zones of building  10  to serve the thermal energy loads of building  10 . The water then returns to subplants  202 - 212  to receive further heating or cooling. 
     Although subplants  202 - 212  are shown and described as heating and cooling water for circulation to a building, it is understood that any other type of working fluid (e.g., glycol, CO 2 , etc.) may be used in place of or in addition to water to serve the thermal energy loads. In other embodiments, subplants  202 - 212  may provide heating and/or cooling directly to the building or campus without requiring an intermediate heat transfer fluid. These and other variations to central plant  200  are within the teachings of the present invention. 
     Each of subplants  202 - 212  may include a variety of equipment configured to facilitate the functions of the subplant. For example, heater subplant  202  is shown to include a plurality of heating elements  220  (e.g., boilers, electric heaters, etc.) configured to add heat to the hot water in hot water loop  214 . Heater subplant  202  is also shown to include several pumps  222  and  224  configured to circulate the hot water in hot water loop  214  and to control the flow rate of the hot water through individual heating elements  220 . Chiller subplant  206  is shown to include a plurality of chillers  232  configured to remove heat from the cold water in cold water loop  216 . Chiller subplant  206  is also shown to include several pumps  234  and  236  configured to circulate the cold water in cold water loop  216  and to control the flow rate of the cold water through individual chillers  232 . 
     Heat recovery chiller subplant  204  is shown to include a plurality of heat recovery heat exchangers  226  (e.g., refrigeration circuits) configured to transfer heat from cold water loop  216  to hot water loop  214 . Heat recovery chiller subplant  204  is also shown to include several pumps  228  and  230  configured to circulate the hot water and/or cold water through heat recovery heat exchangers  226  and to control the flow rate of the water through individual heat recovery heat exchangers  226 . Cooling tower subplant  208  is shown to include a plurality of cooling towers  238  configured to remove heat from the condenser water in condenser water loop  218 . Cooling tower subplant  208  is also shown to include several pumps  240  configured to circulate the condenser water in condenser water loop  218  and to control the flow rate of the condenser water through individual cooling towers  238 . 
     Hot TES subplant  210  is shown to include a hot TES tank  242  configured to store the hot water for later use. Hot TES subplant  210  may also include one or more pumps or valves configured to control the flow rate of the hot water into or out of hot TES tank  242 . Cold TES subplant  212  is shown to include cold TES tanks  244  configured to store the cold water for later use. Cold TES subplant  212  may also include one or more pumps or valves configured to control the flow rate of the cold water into or out of cold TES tanks  244 . 
     In some embodiments, one or more of the pumps in central plant  200  (e.g., pumps  222 ,  224 ,  228 ,  230 ,  234 ,  236 , and/or  240 ) or pipelines in central plant  200  include an isolation valve associated therewith. Isolation valves may be integrated with the pumps or positioned upstream or downstream of the pumps to control the fluid flows in central plant  200 . In various embodiments, central plant  200  may include more, fewer, or different types of devices and/or subplants based on the particular configuration of central plant  200  and the types of loads served by central plant  200 . 
     Airside System 
     Referring now to  FIG.  3   , a block diagram of an airside system  300  is shown, according to an example embodiment. In various embodiments, airside system  300  can supplement or replace airside system  130  in HVAC system  100  or can be implemented separate from HVAC system  100 . When implemented in HVAC system  100 , airside system  300  can include a subset of the HVAC devices in HVAC system  100  (e.g., AHU  106 , VAV units  116 , duct  112 , duct  114 , fans, dampers, etc.) and can be located in or around building  10 . Airside system  300  can operate to heat or cool an airflow provided to building  10  using a heated or chilled fluid provided by waterside system  200 . 
     In  FIG.  3   , airside system  300  is shown to include an economizer-type air handling unit (AHU)  302 . Economizer-type AHUs vary the amount of outside air and return air used by the air handling unit for heating or cooling. For example, AHU  302  can receive return air  304  from building zone  306  via return air duct  308  and can deliver supply air  310  to building zone  306  via supply air duct  312 . In some embodiments, AHU  302  is a rooftop unit located on the roof of building  10  (e.g., AHU  106  as shown in  FIG.  1   ) or otherwise positioned to receive both return air  304  and outside air  314 . AHU  302  can be configured to operate exhaust air damper  316 , mixing damper  318 , and outside air damper  320  to control an amount of outside air  314  and return air  304  that combine to form supply air  310 . Any return air  304  that does not pass through mixing damper  318  can be exhausted from AHU  302  through exhaust damper  316  as exhaust air  322 . 
     Each of dampers  316 - 320  can be operated by an actuator. For example, exhaust air damper  316  can be operated by actuator  324 , mixing damper  318  can be operated by actuator  326 , and outside air damper  320  can be operated by actuator  328 . Actuators  324 - 328  can communicate with an AHU controller  330  via a communications link  332 . Actuators  324 - 328  can receive control signals from AHU controller  330  and can provide feedback signals to AHU controller  330 . Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information (e.g., results of diagnostic tests performed by actuators  324 - 328 ), status information, commissioning information, configuration settings, calibration data, and/or other types of information or data that can be collected, stored, or used by actuators  324 - 328 . AHU controller  330  can be an economizer controller configured to use one or more control algorithms (e.g., state-based algorithms, extremum seeking control (ESC) algorithms, proportional-integral (PI) control algorithms, proportional-integral-derivative (PID) control algorithms, model predictive control (MPC) algorithms, feedback control algorithms, etc.) to control actuators  324 - 328 . 
     Still referring to  FIG.  3   , AHU  302  is shown to include a cooling coil  334 , a heating coil  336 , and a fan  338  positioned within supply air duct  312 . Fan  338  can be configured to force supply air  310  through cooling coil  334  and/or heating coil  336  and provide supply air  310  to building zone  306 . AHU controller  330  can communicate with fan  338  via communications link  340  to control a flow rate of supply air  310 . In some embodiments, AHU controller  330  controls an amount of heating or cooling applied to supply air  310  by modulating a speed of fan  338 . 
     Cooling coil  334  can receive a chilled fluid from waterside system  200  (e.g., from cold water loop  216 ) via piping  342  and can return the chilled fluid to waterside system  200  via piping  344 . Valve  346  can be positioned along piping  342  or piping  344  to control a flow rate of the chilled fluid through cooling coil  334 . In some embodiments, cooling coil  334  includes multiple stages of cooling coils that can be independently activated and deactivated (e.g., by AHU controller  330 , by BMS controller  366 , etc.) to modulate an amount of cooling applied to supply air  310 . 
     Heating coil  336  can receive a heated fluid from waterside system  200  (e.g., from hot water loop  214 ) via piping  348  and can return the heated fluid to waterside system  200  via piping  350 . Valve  352  can be positioned along piping  348  or piping  350  to control a flow rate of the heated fluid through heating coil  336 . In some embodiments, heating coil  336  includes multiple stages of heating coils that can be independently activated and deactivated (e.g., by AHU controller  330 , by BMS controller  366 , etc.) to modulate an amount of heating applied to supply air  310 . 
     Each of valves  346  and  352  can be controlled by an actuator. For example, valve  346  can be controlled by actuator  354  and valve  352  can be controlled by actuator  356 . Actuators  354 - 356  can communicate with AHU controller  330  via communications links  358 - 360 . Actuators  354 - 356  can receive control signals from AHU controller  330  and can provide feedback signals to controller  330 . In some embodiments, AHU controller  330  receives a measurement of the supply air temperature from a temperature sensor  362  positioned in supply air duct  312  (e.g., downstream of cooling coil  334  and/or heating coil  336 ). AHU controller  330  can also receive a measurement of the temperature of building zone  306  from a temperature sensor  364  located in building zone  306 . 
     In some embodiments, AHU controller  330  operates valves  346  and  352  via actuators  354 - 356  to modulate an amount of heating or cooling provided to supply air  310  (e.g., to achieve a setpoint temperature for supply air  310  or to maintain the temperature of supply air  310  within a setpoint temperature range). The positions of valves  346  and  352  affect the amount of heating or cooling provided to supply air  310  by cooling coil  334  or heating coil  336  and may correlate with the amount of energy consumed to achieve a desired supply air temperature. AHU controller  330  can control the temperature of supply air  310  and/or building zone  306  by activating or deactivating coils  334 - 336 , adjusting a speed of fan  338 , or a combination of both. 
     Still referring to  FIG.  3   , airside system  300  is shown to include a building management system (BMS) controller  366  and a client device  368 . BMS controller  366  can include one or more computer systems (e.g., servers, supervisory controllers, subsystem controllers, etc.) that serve as system level controllers, application or data servers, head nodes, or master controllers for airside system  300 , waterside system  200 , HVAC system  100 , and/or other controllable systems that serve building  10 . BMS controller  366  can communicate with multiple downstream building systems or subsystems (e.g., HVAC system  100 , a security system, a lighting system, waterside system  200 , etc.) via a communications link  370  according to like or disparate protocols (e.g., LON, BACnet, etc.). In various embodiments, AHU controller  330  and BMS controller  366  can be separate (as shown in  FIG.  3   ) or integrated. In an integrated implementation, AHU controller  330  can be a software module configured for execution by a processor of BMS controller  366 . 
     In some embodiments, AHU controller  330  receives information from BMS controller  366  (e.g., commands, set points, operating boundaries, etc.) and provides information to BMS controller  366  (e.g., temperature measurements, valve or actuator positions, operating statuses, diagnostics, etc.). For example, AHU controller  330  can provide BMS controller  366  with temperature measurements from temperature sensors  362  and  364 , equipment on/off states, equipment operating capacities, and/or any other information that can be used by BMS controller  366  to monitor or control a variable state or condition within building zone  306 . 
     Client device  368  can include one or more human-machine interfaces or client interfaces (e.g., graphical user interfaces, reporting interfaces, text-based computer interfaces, client-facing web services, web servers that provide pages to web clients, etc.) for controlling, viewing, or otherwise interacting with HVAC system  100 , its subsystems, and/or devices. Client device  368  can be a computer workstation, a client terminal, a remote or local interface, or any other type of user interface device. Client device  368  can be a stationary terminal or a mobile device. For example, client device  368  can be a desktop computer, a computer server with a user interface, a laptop computer, a tablet, a smartphone, a PDA, or any other type of mobile or non-mobile device. Client device  368  can communicate with BMS controller  366  and/or AHU controller  330  via communications link  372 . 
     Building Management System 
     Referring now to  FIG.  4   , a block diagram of a building management system (BMS)  400  is shown, according to an example embodiment. BMS  400  can be implemented in building  10  to automatically monitor and control various building functions. BMS  400  is shown to include BMS controller  366  and a plurality of building subsystems  428 . Building subsystems  428  are shown to include a building electrical subsystem  434 , an information communication technology (ICT) subsystem  436 , a security subsystem  438 , a HVAC subsystem  440 , a lighting subsystem  442 , a lift/escalators subsystem  432 , and a fire safety subsystem  430 . In various embodiments, building subsystems  428  can include fewer, additional, or alternative subsystems. For example, building subsystems  428  can also or alternatively include a refrigeration subsystem, an advertising or signage subsystem, a cooking subsystem, a vending subsystem, a printer or copy service subsystem, or any other type of building subsystem that uses controllable equipment and/or sensors to monitor or control building  10 . In some embodiments, building subsystems  428  include waterside system  200  and/or airside system  300 , as described with reference to  FIGS.  2  and  3   . 
     Each of building subsystems  428  can include any number of devices, controllers, and connections for completing its individual functions and control activities. HVAC subsystem  440  can include many of the same components as HVAC system  100 , as described with reference to  FIGS.  1 - 3   . For example, HVAC subsystem  440  can include a chiller, a boiler, any number of air handling units, economizers, field controllers, supervisory controllers, actuators, temperature sensors, and other devices for controlling the temperature, humidity, airflow, or other variable conditions within building  10 . Lighting subsystem  442  can include any number of light fixtures, ballasts, lighting sensors, dimmers, or other devices configured to controllably adjust the amount of light provided to a building space. Security subsystem  438  can include occupancy sensors, video surveillance cameras, digital video recorders, video processing servers, intrusion detection devices, access control devices (e.g., card access, etc.) and servers, or other security-related devices. 
     Still referring to  FIG.  4   , BMS controller  366  is shown to include a communications interface  407  and a BMS interface  409 . Interface  407  can facilitate communications between BMS controller  366  and external applications (e.g., monitoring and reporting applications  422 , enterprise control applications  426 , remote systems and applications  444 , applications residing on client devices  448 , etc.) for allowing user control, monitoring, and adjustment to BMS controller  366  and/or subsystems  428 . Interface  407  can also facilitate communications between BMS controller  366  and client devices  448 . BMS interface  409  can facilitate communications between BMS controller  366  and building subsystems  428  (e.g., HVAC, lighting security, lifts, power distribution, business, etc.). 
     Interfaces  407 ,  409  can be or include wired or wireless communications interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wire terminals, etc.) for conducting data communications with building subsystems  428  or other external systems or devices. In various embodiments, communications via interfaces  407 ,  409  can be direct (e.g., local wired or wireless communications) or via a communications network  446  (e.g., a WAN, the Internet, a cellular network, etc.). For example, interfaces  407 ,  409  can include an Ethernet card and port for sending and receiving data via an Ethernet-based communications link or network. In another example, interfaces  407 ,  409  can include a Wi-Fi transceiver for communicating via a wireless communications network. In another example, one or both of interfaces  407 ,  409  can include cellular or mobile phone communications transceivers. In one embodiment, communications interface  407  is a power line communications interface and BMS interface  409  is an Ethernet interface. In other embodiments, both communications interface  407  and BMS interface  409  are Ethernet interfaces or are the same Ethernet interface. 
     Still referring to  FIG.  4   , BMS controller  366  is shown to include a processing circuit  404  including a processor  406  and memory  408 . Processing circuit  404  can be communicably connected to BMS interface  409  and/or communications interface  407  such that processing circuit  404  and the various components thereof can send and receive data via interfaces  407 ,  409 . Processor  406  can be implemented as a general purpose processor, an application specific integrated circuit (ASIC), one or more field programmable gate arrays (FPGAs), a group of processing components, or other suitable electronic processing components. 
     Memory  408  (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present application. Memory  408  can be or include volatile memory or non-volatile memory. Memory  408  can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present application. According to an example embodiment, memory  408  is communicably connected to processor  406  via processing circuit  404  and includes computer code for executing (e.g., by processing circuit  404  and/or processor  406 ) one or more processes described herein. 
     In some embodiments, BMS controller  366  is implemented within a single computer (e.g., one server, one housing, etc.). In various other embodiments BMS controller  366  can be distributed across multiple servers or computers (e.g., that can exist in distributed locations). Further, while  FIG.  4    shows applications  422  and  426  as existing outside of BMS controller  366 , in some embodiments, applications  422  and  426  can be hosted within BMS controller  366  (e.g., within memory  408 ). 
     Still referring to  FIG.  4   , memory  408  is shown to include an enterprise integration layer  410 , an automated measurement and validation (AM&amp;V) layer  412 , a demand response (DR) layer  414 , a fault detection and diagnostics (FDD) layer  416 , an integrated control layer  418 , and a building subsystem integration later  420 . Layers  410 - 420  can be configured to receive inputs from building subsystems  428  and other data sources, determine optimal control actions for building subsystems  428  based on the inputs, generate control signals based on the optimal control actions, and provide the generated control signals to building subsystems  428 . The following paragraphs describe some of the general functions performed by each of layers  410 - 420  in BMS  400 . 
     Enterprise integration layer  410  can be configured to serve clients or local applications with information and services to support a variety of enterprise-level applications. For example, enterprise control applications  426  can be configured to provide subsystem-spanning control to a graphical user interface (GUI) or to any number of enterprise-level business applications (e.g., accounting systems, user identification systems, etc.). Enterprise control applications  426  can also or alternatively be configured to provide configuration GUIs for configuring BMS controller  366 . In yet other embodiments, enterprise control applications  426  can work with layers  410 - 420  to optimize building performance (e.g., efficiency, energy use, comfort, or safety) based on inputs received at interface  407  and/or BMS interface  409 . 
     Building subsystem integration layer  420  can be configured to manage communications between BMS controller  366  and building subsystems  428 . For example, building subsystem integration layer  420  can receive sensor data and input signals from building subsystems  428  and provide output data and control signals to building subsystems  428 . Building subsystem integration layer  420  can also be configured to manage communications between building subsystems  428 . Building subsystem integration layer  420  translate communications (e.g., sensor data, input signals, output signals, etc.) across a plurality of multi-vendor/multi-protocol systems. 
     Demand response layer  414  can be configured to optimize resource usage (e.g., electricity use, natural gas use, water use, etc.) and/or the monetary cost of such resource usage in response to satisfy the demand of building  10 . The optimization can be based on time-of-use prices, curtailment signals, energy availability, or other data received from utility providers, distributed energy generation systems  424 , from energy storage  427  (e.g., hot TES  242 , cold TES  244 , etc.), or from other sources. Demand response layer  414  can receive inputs from other layers of BMS controller  366  (e.g., building subsystem integration layer  420 , integrated control layer  418 , etc.). The inputs received from other layers can include environmental or sensor inputs such as temperature, carbon dioxide levels, relative humidity levels, air quality sensor outputs, occupancy sensor outputs, room schedules, and the like. The inputs can also include inputs such as electrical use (e.g., expressed in kWh), thermal load measurements, pricing information, projected pricing, smoothed pricing, curtailment signals from utilities, and the like. 
     According to an example embodiment, demand response layer  414  includes control logic for responding to the data and signals it receives. These responses can include communicating with the control algorithms in integrated control layer  418 , changing control strategies, changing set points, or activating/deactivating building equipment or subsystems in a controlled manner. Demand response layer  414  can also include control logic configured to determine when to utilize stored energy. For example, demand response layer  414  can determine to begin using energy from energy storage  427  just prior to the beginning of a peak use hour. 
     In some embodiments, demand response layer  414  includes a control module configured to actively initiate control actions (e.g., automatically changing set points) which minimize energy costs based on one or more inputs representative of or based on demand (e.g., price, a curtailment signal, a demand level, etc.). In some embodiments, demand response layer  414  uses equipment models to determine an optimal set of control actions. The equipment models can include, for example, thermodynamic models describing the inputs, outputs, and/or functions performed by various sets of building equipment. Equipment models can represent collections of building equipment (e.g., subplants, chiller arrays, etc.) or individual devices (e.g., individual chillers, heaters, pumps, etc.). 
     Demand response layer  414  can further include or draw upon one or more demand response policy definitions (e.g., databases, XML files, etc.). The policy definitions can be edited or adjusted by a user (e.g., via a graphical user interface) so that the control actions initiated in response to demand inputs can be tailored for the user&#39;s application, desired comfort level, particular building equipment, or based on other concerns. For example, the demand response policy definitions can specify which equipment can be turned on or off in response to particular demand inputs, how long a system or piece of equipment should be turned off, what set points can be changed, what the allowable set point adjustment range is, how long to hold a high demand setpoint before returning to a normally scheduled setpoint, how close to approach capacity limits, which equipment modes to utilize, the energy transfer rates (e.g., the maximum rate, an alarm rate, other rate boundary information, etc.) into and out of energy storage devices (e.g., thermal storage tanks, battery banks, etc.), and when to dispatch on-site generation of energy (e.g., via fuel cells, a motor generator set, etc.). 
     Integrated control layer  418  can be configured to use the data input or output of building subsystem integration layer  420  and/or demand response later  414  to make control decisions. Due to the subsystem integration provided by building subsystem integration layer  420 , integrated control layer  418  can integrate control activities of the subsystems  428  such that the subsystems  428  behave as a single integrated supersystem. In an example embodiment, integrated control layer  418  includes control logic that uses inputs and outputs from a plurality of building subsystems to provide greater comfort and energy savings relative to the comfort and energy savings that separate subsystems could provide alone. For example, integrated control layer  418  can be configured to use an input from a first subsystem to make an energy-saving control decision for a second subsystem. Results of these decisions can be communicated back to building subsystem integration layer  420 . 
     Integrated control layer  418  is shown to be logically below demand response layer  414 . Integrated control layer  418  can be configured to enhance the effectiveness of demand response layer  414  by enabling building subsystems  428  and their respective control loops to be controlled in coordination with demand response layer  414 . This configuration may advantageously reduce disruptive demand response behavior relative to conventional systems. For example, integrated control layer  418  can be configured to assure that a demand response-driven upward adjustment to the setpoint for chilled water temperature (or another component that directly or indirectly affects temperature) does not result in an increase in fan energy (or other energy used to cool a space) that would result in greater total building energy use than was saved at the chiller. 
     Integrated control layer  418  can be configured to provide feedback to demand response layer  414  so that demand response layer  414  checks that constraints (e.g., temperature, lighting levels, etc.) are properly maintained even while demanded load shedding is in progress. The constraints can also include setpoint or sensed boundaries relating to safety, equipment operating limits and performance, comfort, fire codes, electrical codes, energy codes, and the like. Integrated control layer  418  is also logically below fault detection and diagnostics layer  416  and automated measurement and validation layer  412 . Integrated control layer  418  can be configured to provide calculated inputs (e.g., aggregations) to these higher levels based on outputs from more than one building subsystem. 
     Automated measurement and validation (AM&amp;V) layer  412  can be configured to verify that control strategies commanded by integrated control layer  418  or demand response layer  414  are working properly (e.g., using data aggregated by AM&amp;V layer  412 , integrated control layer  418 , building subsystem integration layer  420 , FDD layer  416 , or otherwise). The calculations made by AM&amp;V layer  412  can be based on building system energy models and/or equipment models for individual BMS devices or subsystems. For example, AM&amp;V layer  412  can compare a model-predicted output with an actual output from building subsystems  428  to determine an accuracy of the model. 
     Fault detection and diagnostics (FDD) layer  416  can be configured to provide on-going fault detection for building subsystems  428 , building subsystem devices (i.e., building equipment), and control algorithms used by demand response layer  414  and integrated control layer  418 . FDD layer  416  can receive data inputs from integrated control layer  418 , directly from one or more building subsystems or devices, or from another data source. FDD layer  416  can automatically diagnose and respond to detected faults. The responses to detected or diagnosed faults can include providing an alert message to a user, a maintenance scheduling system, or a control algorithm configured to attempt to repair the fault or to work-around the fault. 
     FDD layer  416  can be configured to output a specific identification of the faulty component or cause of the fault (e.g., loose damper linkage) using detailed subsystem inputs available at building subsystem integration layer  420 . In other example embodiments, FDD layer  416  is configured to provide “fault” events to integrated control layer  418  which executes control strategies and policies in response to the received fault events. According to an example embodiment, FDD layer  416  (or a policy executed by an integrated control engine or business rules engine) can shut-down systems or direct control activities around faulty devices or systems to reduce energy waste, extend equipment life, or assure proper control response. 
     FDD layer  416  can be configured to store or access a variety of different system data stores (or data points for live data). FDD layer  416  can use some content of the data stores to identify faults at the equipment level (e.g., specific chiller, specific AHU, specific terminal unit, etc.) and other content to identify faults at component or subsystem levels. For example, building subsystems  428  can generate temporal (i.e., time-series) data indicating the performance of BMS  400  and the various components thereof. The data generated by building subsystems  428  can include measured or calculated values that exhibit statistical characteristics and provide information about how the corresponding system or process (e.g., a temperature control process, a flow control process, etc.) is performing in terms of error from its setpoint. These processes can be examined by FDD layer  416  to expose when the system begins to degrade in performance. 
     Variable Refrigerant Flow (VRF) Systems 
     Referring now to  FIGS.  5 - 6   , a variable refrigerant flow (VRF) system  500  is shown, according to some embodiments. VRF system  500  is shown to include one or more outdoor VRF units  502  and a plurality of indoor VRF units  504 . Outdoor VRF units  502  can be located outside a building and can operate to heat or cool a refrigerant. Outdoor VRF units  502  can consume electricity to convert refrigerant between liquid, gas, and/or super-heated gas phases. Indoor VRF units  504  can be distributed throughout various building zones within a building and can receive the heated or cooled refrigerant from outdoor VRF units  502 . Each indoor VRF unit  504  can provide temperature control for the particular building zone in which the indoor VRF unit  504  is located. Although the term “indoor” is used to denote that the indoor VRF units  504  are typically located inside of buildings, in some cases one or more indoor VRF units are located “outdoors” (i.e., outside of a building) for example to heat/cool a patio, entryway, walkway, etc. 
     One advantage of VRF system  500  is that some indoor VRF units  504  can operate in a cooling mode while other indoor VRF units  504  operate in a heating mode. For example, each of outdoor VRF units  502  and indoor VRF units  504  can operate in a heating mode, a cooling mode, or an off mode. Each building zone can be controlled independently and can have different temperature setpoints. In some embodiments, each building has up to three outdoor VRF units  502  located outside the building (e.g., on a rooftop) and up to 128 indoor VRF units  504  distributed throughout the building (e.g., in various building zones). Building zones may include, among other possibilities, apartment units, offices, retail spaces, and common areas. In some cases, various building zones are owned, leased, or otherwise occupied by a variety of tenants, all served by the VRF system  500 . 
     Many different configurations exist for VRF system  500 . In some embodiments, VRF system  500  is a two-pipe system in which each outdoor VRF unit  502  connects to a single refrigerant return line and a single refrigerant outlet line. In a two-pipe system, all of outdoor VRF units  502  may operate in the same mode since only one of a heated or chilled refrigerant can be provided via the single refrigerant outlet line. In other embodiments, VRF system  500  is a three-pipe system in which each outdoor VRF unit  502  connects to a refrigerant return line, a hot refrigerant outlet line, and a cold refrigerant outlet line. In a three-pipe system, both heating and cooling can be provided simultaneously via the dual refrigerant outlet lines. An example of a three-pipe VRF system is described in detail with reference to  FIG.  7   . 
     Referring now to  FIG.  7   , a block diagram illustrating a VRF system  700  is shown, according to some embodiments. VRF system  700  is shown to include outdoor VRF unit  702 , several heat recovery units  706 , and several indoor VRF units  704 . Outdoor VRF unit  702  may include a compressor  708 , a fan  710 , or other power-consuming refrigeration components configured to convert a refrigerant between liquid, gas, and/or super-heated gas phases. Indoor VRF units  704  can be distributed throughout various building zones within a building and can receive the heated or cooled refrigerant from outdoor VRF unit  702 . Each indoor VRF unit  704  can provide temperature control for the particular building zone in which the indoor VRF unit  704  is located. Heat recovery units  706  can control the flow of a refrigerant between outdoor VRF unit  702  and indoor VRF units  704  (e.g., by opening or closing valves) and can minimize the heating or cooling load to be served by outdoor VRF unit  702 . 
     Outdoor VRF unit  702  is shown to include a compressor  708  and a heat exchanger  712 . Compressor  708  circulates a refrigerant between heat exchanger  712  and indoor VRF units  704 . The compressor  708  operates at a variable frequency as controlled by outdoor unit controls circuit  714 . At higher frequencies, the compressor  708  provides the indoor VRF units  704  with greater heat transfer capacity. Electrical power consumption of compressor  708  increases proportionally with compressor frequency. 
     Heat exchanger  712  can function as a condenser (allowing the refrigerant to reject heat to the outside air) when VRF system  700  operates in a cooling mode or as an evaporator (allowing the refrigerant to absorb heat from the outside air) when VRF system  700  operates in a heating mode. Fan  710  provides airflow through heat exchanger  712 . The speed of fan  710  can be adjusted (e.g., by outdoor unit controls circuit  714 ) to modulate the rate of heat transfer into or out of the refrigerant in heat exchanger  712 . 
     Each indoor VRF unit  704  is shown to include a heat exchanger  816  and an expansion valve  718 . Each of heat exchangers  716  can function as a condenser (allowing the refrigerant to reject heat to the air within the room or zone) when the indoor VRF unit  704  operates in a heating mode or as an evaporator (allowing the refrigerant to absorb heat from the air within the room or zone) when the indoor VRF unit  704  operates in a cooling mode. Fans  720  provide airflow through heat exchangers  716 . The speeds of fans  720  can be adjusted (e.g., by indoor unit controls circuits  722 ) to modulate the rate of heat transfer into or out of the refrigerant in heat exchangers  716 . 
     In  FIG.  7   , indoor VRF units  704  are shown operating in the cooling mode. In the cooling mode, the refrigerant is provided to indoor VRF units  704  via cooling line  724 . The refrigerant is expanded by expansion valves  718  to a cold, low pressure state and flows through heat exchangers  716  (functioning as evaporators) to absorb heat from the room or zone within the building. The heated refrigerant then flows back to outdoor VRF unit  702  via return line  726  and is compressed by compressor  708  to a hot, high pressure state. The compressed refrigerant flows through heat exchanger  712  (functioning as a condenser) and rejects heat to the outside air. The cooled refrigerant can then be provided back to indoor VRF units  704  via cooling line  724 . In the cooling mode, flow control valves  728  can be closed and expansion valve  730  can be completely open. 
     In the heating mode, the refrigerant is provided to indoor VRF units  704  in a hot state. The hot refrigerant flows through heat exchangers  716  (functioning as condensers) and rejects heat to the air within the room or zone of the building. The refrigerant then flows back to outdoor VRF unit via cooling line  724  (opposite the flow direction shown in  FIG.  7   ). The refrigerant can be expanded by expansion valve  730  to a colder, lower pressure state. The expanded refrigerant flows through heat exchanger  712  (functioning as an evaporator) and absorbs heat from the outside air. The heated refrigerant can be compressed by compressor  708  and provided back to indoor VRF units  704  in a hot, compressed state. In the heating mode, flow control valves  728  can be completely open to allow the refrigerant from compressor  708  to flow into a heating line. 
     As shown in  FIG.  7   , each indoor VRF unit  704  includes an indoor unit controls circuit  722 . Indoor unit controls circuit  722  controls the operation of components of the indoor VRF unit  704 , including the fan  720  and the expansion valve  718 , in response to a building zone temperature setpoint or other request to provide heating/cooling to the building zone. For example, the indoor unit controls circuit  722  can generate a signal to turn the fan  720  on and off. Indoor unit controls circuit  722  also determines a heat transfer capacity required by the indoor VRF unit  704  and a frequency of compressor  708  that corresponds to that capacity. When the indoor unit controls circuit  722  determines that the indoor VRF unit  704  must provide heating or cooling of a certain capacity, the indoor unit controls circuit  722  then generates and transmits a compressor frequency request to the outdoor unit controls circuit  714  including the compressor frequency corresponding to the required capacity. 
     Outdoor unit controls circuit  714  receives compressor frequency requests from one or more indoor unit controls circuits  722  and aggregates the requests, for example, by summing the compressor frequency requests into a compressor total frequency. In some embodiments, the compressor frequency has an upper limit, such that the compressor total frequency cannot exceed the upper limit. The outdoor unit controls circuit  714  supplies the compressor total frequency to the compressor, for example, as an input frequency given to a DC inverter compressor motor of the compressor. The indoor unit controls circuits  722  and the outdoor unit controls circuit  714  thereby combine to modulate the compressor frequency to match heating/cooling demand. The outdoor unit controls circuit  214  may also generate signals to control valve positions of the flow control valves  728  and expansion valve  730 , a compressor power setpoint, a refrigerant flow setpoint, a refrigerant pressure, on/off commands, staging commands, or other signals that affect the operation of compressor  708 , as well as control signals provided to fan  710  including a fan speed setpoint, a fan power setpoint, an airflow setpoint, on/off commands, or other signals that affect the operation of fan  710 . 
     Indoor unit controls circuits  722  and outdoor unit controls circuit  714  may store and/or provide a data history of one or more control signals generated by or provided to the controls circuits  714 ,  722 . For example, indoor unit controls circuits  722  may store and/or provide a log of generated compressor request frequencies, fan on/off times, and indoor VRF unit  704  on/off times. Outdoor unit controls circuit  714  may store and/or provide a log of compressor request frequencies and/or compressor total frequencies and compressor runtimes. 
     The VRF system  700  is shown as running on electrical power provided by an energy grid  750  via an outdoor meter  752  and an indoor meter  754 . According to various embodiments, the energy grid  750  is any supply of electricity (e.g., an electrical grid maintained by a utility company and supplied with power by one or more power plants, etc.). The outdoor meter  752  measures the electrical power consumption over time of the outdoor VRF unit  702 , for example, in kilowatt-hours (kWh). The indoor meter  754  measures the electrical power consumption over time of the indoor VRF units  704 , for example, in kWh. The VRF system  700  incurs energy consumption costs based on the metered electrical power consumption of the outdoor meter  752  and/or the indoor meter  754 , as billed by the utility company that provides the electrical power. The price of electrical power (e.g., dollars per kWh) may vary over time. The VRF system  700  also includes a system manager  715 . In some embodiments, system manager  715  is configured to minimize energy consumption costs for the VRF system  700  while also maintaining occupant comfort. While systems and methods disclosed herein are generally related to VRF systems, other systems may implement the commissioning methods disclosed herein. 
     Predictive Control Using Heat Maps 
     Referring now to  FIG.  8   , a controller  800  for reducing temperature variations within a building space served by multiple heat transfer devices is shown, according to some embodiments. Controller  800  may be configured to obtain (e.g., generate, receive, etc.) a heat map and use information from the heat map to adjust control signals to heat transfer devices within the building space to achieve a more uniform temperature distribution. In some embodiments, this is performed to reduce energy costs within a building and to avoid unnecessary pockets of “hot” and/or “cold” regions. 
     It is worth noting that the systems and methods described herein are generally referring to heat transfer devices, such as IDUs. However, IDUs serving the zones described herein is merely meant to be exemplary and should not be considered limiting. Other types of heat transfer devices could be included/considered, such as IDUs, VAV units, radiators, window air conditioners, and resistive heating elements. 
     For example, a floor of building  10  may act as a building space with 6 6 heat transfer devices configured to provide heating/cooling to the space, where each VRF indoor unit serves a specific zone within the building space. Initially, the heat map indicates that there is an uneven heat distribution within the building space. The heat map is proceed to determine adjusted control signals to provide to the VRF indoor units that will better equalize the heat distribution within the building space. 
     Controller  800  is shown to include processing circuit  802  including (processor  804  and memory  806 ) and communications circuit  808 . Processing circuit  802  can be communicably connected to communications interface  808  such that processing circuit  802  and the various components thereof can send and receive data via communications interface  808 . Processor  804  can be implemented as a general purpose processor, an application specific integrated circuit (ASIC), one or more field programmable gate arrays (FPGAs), a group of processing components, or other suitable electronic processing components. 
     Communications interface  808  can be or include wired or wireless communications interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wire terminals, etc.) for conducting data communications. In various embodiments, communications via communications interface  808  can be direct (e.g., local wired or wireless communications) or via a communications network (e.g., a WAN, the Internet, a cellular network, etc.). For example, communications interface can include an Ethernet card and port for sending and receiving data via an Ethernet-based communications link or network. In another example, communications interface  808  can include a Wi-Fi transceiver for communicating via a wireless communications network. In another example, communications interface  808  can include cellular or mobile phone communications transceivers. 
     Memory  806  (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present disclosure. Memory  806  can be or include volatile memory or non-volatile memory. Memory  806  can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. According to an example embodiment, memory  806  is communicably connected to processor  806  via processing circuit  802  and includes computer code for executing (e.g., by processing circuit  802  and/or processor  804 ) one or more processes described herein. In some embodiments, controller  800  is implemented within a single computer (e.g., one server, one housing, etc.). In various other embodiments controller  800  can be distributed across multiple servers or computers (e.g., that can exist in distributed locations). Memory  806  is shown to include zone temperature collector  810 , heat map generator  812 , model generator  818 , historical database  824 , and setpoint manager  826 . 
     Zone temperature collector  810  may be configured to receive temperature data from temperature sensors within space  828 . In some embodiments, space  828  is a space (e.g., floor, area, region, large room such as an auditorium, cafeteria, theater, gymnasium, etc.) of building  10  that can include any number of zones. For example, space  828  can be an entire floor of building  10  with each office acting as a zone within space  828 . As another example, space  828  can be a single large room with no internal walls within space  828  or minimal internal walls within space  828  dividing the different zones within space  828 . Minimal internal walls may be defined as internal walls that do not interrupt or prevent airflow or air circulation between the different zones within space  828 . As such, the air within space  828  may be permitted to flow between the different zones unimpeded. Of course while not shown, controller  800  may also be aware of the temperature setpoints currently set on any of the heat transfer devices and/or ODUs within space  828 . In some embodiments, controller  800  obtains sufficient temperature measurements and other temperature data (e.g., from one or more thermal imaging devices, etc.) to adequately generate a heat map of space  828 . Zone temperature collector may be configured to provide the temperature data from each and any zone within space  828  to heat map generator  812 . 
     Heat map generator  812  may be configured to generate one or more heat maps of space  828 . It should be noted that a variety of thermal imaging devices can be used to generate a heat map of a building space. In general, a thermal imaging device can detect infrared energy emitted, reflected, or transmitted by all materials. Thermal imaging devices can factor in emissivity of various materials and can have an emissivity table stored in memory and accessible by users. Thermal imaging devices can detect temperatures of various objects as well as atmospheric temperature. Thermal imaging devices can also detect other information such as distance to various objects and relative humidity levels. In some embodiments, multiple thermal imaging devices (e.g., cameras, etc.) are used in a building and data from the devices is stitched together to generate a thermal image of a larger building space (see  FIGS.  10 - 11    for reference). Moreover, these thermal imaging devices can be integrated with other types of cameras such as security cameras throughout a building. Thermal imaging devices can be deployed in various configurations throughout building  10  to perform one or more of the functions described herein. The systems and methods for generating heat maps may be similar or identical to systems and methods disclosed in U.S. Patent Application Publication No. 2021/0011443, published Jan. 14, 2021, the entire disclosure of which is incorporated by reference herein. 
     Heat map generator  812  may be configured to provide one or more heat maps to model generator  818 . In some embodiments, controller  800  can receive a heat map or partial information associated with a heat map (e.g., infrared energy emitted, reflected, and/or transmitted from a zone or space, etc.), which can be directly provided to model generator  818 . In such embodiments, heat map generator  812  may not be responsible for generating, either partially or entirely, the heat map for space  828 . In some embodiments, heat map generator  812  is substantially similar or identical to heat map generator  906 , described in detail below with reference to  FIG.  9   . 
     Model generator  818  may be configured dynamic thermal model that is used to predict how the temperatures at the different regions within space  828  will change as function of the control decisions. This type of model may be used in the optimization process to predict the impact of the control decisions. In some embodiments, model generator  818  generates a temperature model of space  828  based on previous heat map data and/or previous setpoint adjustments to IDUs within space  828 . For example, model generator  818  may be able to create a model that represents how the heat distribution will occur in response to changing certain temperature setpoints of the IDUs within space  828 . The model may consider a number of factors, such as a number of occupants within space  828  and/or the location of the occupants (e.g., within particular zones, etc.), the amount of sunlight entering space  828  and/or the location at which sunlight enters space  828 , and the weather outside of space  828 . 
     In some embodiments, model generator  818  may be configured to generate a model that can represent the temperature of each zone, which may consider the factors listed above and/or additional factors, such as zone coupling. The zone may be located within building  10  and may include a room, a set of rooms, a floor, a space, or any other location within building  10 . In some embodiments, the zone refers to any instance or location within building  10  that includes a single control loop or multiple control loops. In some embodiments, the zone refers to any building location with one or more HVAC units and/or HVAC equipment (e.g., boilers, AC units, chillers, etc.) implemented within one or more control loops. The zone may be served by HVAC equipment, which may include some or all of the equipment of HVAC system  100 , central plant  200 , airside system  300 , or BMS  400  (e.g., boilers, chillers, air handling units, etc.) and/or some or all of the equipment of VRF system  500 , or VRF system  700  (e.g., outdoor VRF units  502 , indoor VRF units  604 , etc.) as described with reference to  FIGS.  5 - 7   . The HVAC equipment may operate to provide heating or cooling {dot over (Q)} HVAC  to the zone to maintain the temperature T z  of the zone at or near a desired temperature (e.g., at a temperature setpoint, within a setpoint range, etc.) to promote the comfort of occupants within the zone and/or to meet other needs of the zone. {dot over (Q)} HVAC  may include heat flow into the zone when the HVAC equipment operates in a heating mode or heat flow out of the zone when the HVAC equipment operate in a cooling mode. {dot over (Q)} HVAC  may have a positive value when the HVAC equipment operates in the heating mode and a negative value when the HVAC equipment operates in the cooling mode. 
     Controller  800  and the various components therein may include any and all functionality from the systems and methods disclosed in U.S. patent application Ser. No. 16/906,562 filed Jun. 19, 2020, the entire disclosure of which is incorporated by reference herein. Furthermore, space  328  may be modeled using any and all functionality from the systems and methods disclosed in U.S. patent application Ser. No. 17/388,776, filed Jul. 29, 2021, the entire disclosure of which is incorporated by reference herein. 
     The zone air may include air within the zone and can be modeled as having a zone air temperature T ia  and a thermal capacitance C ia . Zone air temperature T ia  may be affected by several sources of heat transfer including heating or cooling {dot over (Q)} HVAC  provided by HVAC equipment, heat {dot over (Q)} m  exchanged between the zone air and the building mass, heat {dot over (Q)} a  exchanged between the zone air and the ambient air outside the zone, and heat {dot over (Q)} other  generated by the heat load within the zone. A temperature sensor  830  may be positioned within the zone and configured to measure the zone air temperature T ia . Temperature sensor  830  may communicate the zone air temperature T ia  to controller  800 , which operates to control the HVAC equipment. 
     In some embodiments, the building mass includes non-air mass within the zone (e.g., walls, floors, ceilings, furniture, solid objects, etc.) which can exchange heat {dot over (Q)} m  with the zone air. The building mass can be modeled as having a mass temperature T m  and a thermal capacitance C m . The building mass may reject heat {dot over (Q)} m  to the zone air when the mass temperature T m  is greater than the zone air temperature T ia  or may absorb heat {dot over (Q)} m  from the zone air when the mass temperature T m  is less than the zone air temperature T ia . Accordingly, the value of {dot over (Q)} m  may be positive when the building mass rejects heat to the zone air and negative when the building mass absorbs heat from the zone air. 
     In some embodiments, the heat load may include occupants within the zone (e.g., people, animals, etc.) that produce body heat as well as computers, lighting, and/or other electronic devices that generate heat through electrical resistance. In some embodiments, the heat load includes sunlight that transfers heat into zone via solar irradiance or other sources of heat transfer into the zone via thermal radiation. The total amount of heat generated by the heat load can be modeled as {dot over (Q)} other . 
     The ambient air within a zone of space  828  may include outdoor air or air within another building zone (e.g., of space  328 , outside of space  328 , etc.) that exchanges heat {dot over (Q)} a  with the zone air. The temperature T oa  of the ambient air may be measured by a temperature sensor (e.g., sensor  830 , etc.) and provided as an input to controller  800 . The ambient air may reject heat {dot over (Q)} a  to the zone air when the ambient air temperature T oa  is greater than the zone air temperature T ia  or may absorb heat {dot over (Q)} a  from the zone air when the ambient air temperature T oa  is less than the zone air temperature T ia . Accordingly, the value of {dot over (Q)} a  may be positive when the ambient air rejects heat to the zone air or negative when the ambient air absorbs heat from the zone air. 
     Controller  800  may receive the temperature measurements T ia  and T oa  from sensors  830 - 834  and provide control signals to the IDUs serving space  828  based on a model generated by model generator  818 . In some embodiments, the control signals include heating or cooling duties for HVAC equipment (e.g., the IDUs serving space  828 , etc.). Advantageously, controller  800  may consider the sources of heat transfer provided by the heat load (e.g., {dot over (Q)} other ), the building mass (e.g., {dot over (Q)} m ), and the ambient air (e.g., {dot over (Q)} a ) on the zone air temperature T z  and may operate HVAC equipment to provide a suitable amount of heating or cooling {dot over (Q)} HVAC  to maintain the zone air temperature T ia  within an acceptable range. 
     For example, model generator  818  may generate a model that represents the temperature of a zone within space  828  as: 
     
       
         
           
             
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     Where T z,i,k  is the ith zone temperature at instant k, T m,i,k  is the ith zone shallow mass temperature at instant k, and β i,j  is the degree of coupling between two adjacent zones. In the above example, if two zones are not adjacent, β i,j =0. The addition of the coupling between the zones may maintain the linearity of the zone dynamics constraints in the optimization problem. 
     Although the above example applies to a single building zone, the systems and methods described herein are also applicable to multi-zone systems (e.g., multi-zone systems within space  828 , etc.). In the case of a multi-zone system, each zone may have its own values of T ia , C ia , T m , and C m , which could be aggregated or averaged to determine the value to use in the model. 
     Still referring to  FIG.  8   , optimizer  820  may then be configured to use the heat map information received externally or generated to represent space  828  and/or a model generated by model generator  818  of space  828 , along with any received constraints and an objective function to perform an optimization process to provide substantially equal temperature distribution within space  828 . The model may be used in conjunction with the current heat map data to make determinations that are not provided in the real-time data. For example, the model of building space  828  may be used to predict the zone temperatures as a function of an amount of heat transfer between two or more adjacent zones within space  828 . 
     In some embodiments, the optimization process includes optimizing an objective function or cost function to determine optimal values for the temperatures in the respective zones. In some embodiments, the objective function may consider both the comfort level each temperature, the energy prices, and the energy required to achieve that temperature, as well as any constraints on the system (e.g., temperatures must be within 66°-74°, etc.). The constraints (e.g., prices, penalties, etc.) can be used within the objective function can be updated while the model is running closed-loop and controlling the process (e.g., while processing the heat map in real time, etc.). Changes in desired comfort level, energy prices, etc. can cause the model to manipulate the operating conditions to yield to most desirable environment (e.g., one that has mostly equal temperature distribution at a relatively low cost of energy, etc.). 
     In some embodiments, the optimization process is using an objective function to minimize the cost of energy. In such embodiments, the cost of energy consumed over a duration of time is minimized by selecting temperatures that also conform to the imposed constraints (e.g., temperature max. and temperature min., etc.). In some embodiments, the optimization process is using an objective function to minimize the total energy consumed over the duration of the optimization period. In other embodiments, optimization process may attempt to minimize greenhouse gas emissions and/or carbon emissions. In some embodiments, the primary objective of the optimization is something other than temperature (e.g., cost, energy consumption, carbon, etc.) so that the temperature-related considerations can be imposed as penalties or constraints as described. Of course, the temperatures of various heat transfer devices within space  828  may be adjusted to optimize any number of processes with various constraints and/or penalties, and are not limited to the examples disclosed herein. 
     In some embodiments, optimizer  820  may use a cost model to define the cost incurred (either in terms of monetary cost, energy, carbon emissions, etc.) as a function of the control decisions and also predicts temperature within each zone as a function of the control decisions using the thermal model of the space. These two models together (i.e., cost model and thermal model) may then be used by optimizer  820  to minimize cost while achieving the uniform temperature distribution. In such an example, a constraint may be placed on the system that prevents the adjusted temperature from falling outside of the range of 68°-73°, and thus optimizer  820  needs to determine the cheapest (e.g., energy cost-wise) way to provide substantially equal temperature distribution within this range. 
     In some embodiments, the constraint or penalty of the objective function is implemented as an additional fictitious cost term in the objective function that is not a true financial/energy cost, but rather imposes an additional “cost penalty” based on the differences between the zone temperatures. Therefore, the objective function as a whole would may be minimizing the sum of actual cost (financial, energy, carbon, etc.) plus penalty cost (e.g., based on temperature differences between zones). 
     In some embodiments, the constraint or penalty of the objective function includes a temperature variation constraint that requires the differences between the zone temperatures predicted using the model to be less than or equal to one or more threshold values. Optimizer  820  may determine the amount of heat to transfer into or out of each of the plurality of zones by using the temperature variation constraint to prevent setpoint manager  824  from generating control decisions that would violate the temperature variation constraint. 
     In some embodiments, optimizer  820  may determine an occupancy status of a zone within space  828  that indicates whether the zone is occupied. In some embodiments, the penalty or constraint can be dynamically updated based on occupancy status to drop any unoccupied zones (e.g., or assign them a lower penalty or less restrictive constraint) so that the optimization process would not care so much about the temperature of those unoccupied zones being different from the occupied zones. Optimizer  820  may then adjust a value of a constraint or penalty associated with the zone based on the occupancy status. This data may be provided to optimizer  820  externally or via one or more occupancy sensors (not shown). 
     In some embodiments, in order to minimize cost and/or maximize comfort by having an equal (e.g., or substantially equal, etc.) temperature distribution in space  328  consisting of multiple zones, additional constraints may be added to the optimization problem and/or penalty terms may be added to the cost function in order to avoid infeasibility. For example, the following component may be added to a cost function for solving the optimization problem: 
         J= . . . +Σc   l δ l + . . .
 
     Such that 
     
       
         
           
             
               
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     Where J represents the cost function with the additional penalty term, c is the cost penalty imposed per unit of the delta variable δ, and the delta variables are defined as the temperature differences between zones in the subsequent equations. In some embodiments, number of auxiliary variables, cost terms, and set of constraints may be dependent on the combinations of adjacent zones. 
     The optimization problem may take into account additional factors (e.g., occupancy of zones, zone/space schedules, etc.) to determine which constraints to be added to the optimization problem. For example, if a zone within space  328  is not occupied, it may be determined that there is not a need to maintain a uniform temperature across that particular zone. A multiplicative flag may be applied to the constraints which can be set to zero to turn off these constraints and set to 1, when the space is occupied. In some embodiments, the flag may be set to some value between zero and one as well. 
     Setpoint manager  824  may be configured to manage the multiple updates to set points for one or more of the IDUs within space  828 . In some embodiments, setpoint manager  826  may be configured to continually provide different control signals to a variety of the IDUs in space  828  to maintain substantially equal heat distribution. 
     Referring now to  FIG.  9 A , a block diagram of controller  800  performing some or all of the processing for determining equal (e.g., or substantially equal) heat distribution within space  328 . Model generator  818  and/or optimizer  822 , may be configured to perform some or all of the processes of controller  800  shown in  FIG.  9 A . Additionally, some or all of heat map processor  902  and setpoint distribution optimizer  904  and the functionality thereof can be incorporated partially or entirely within model generator  818 .  FIG.  9 A  shows heat map processor receiving a measured heat map (e.g., data indicating the infrared energy emitted, reflected, and/or transmitted by materials within space  328 , etc.). 
     In some embodiments, heat map processor  902  provides heat data to setpoint distribution optimizer  904 . Heat map processor  902  may modulate the received heat map and determine an estimated modular temperature at multiple locations within space  328 , based on the colors provided on the heat map. These modular temperatures at multiple locations within space  328  may then be provided to setpoint distribution optimizer  904  for optimization. It should be noted that this embodiment for processing a received heat map is merely meant to be exemplary and should not be considered limiting. 
     Setpoint distribution optimizer  904  may be configured to receive the data from heat map processor  902 , receive additional data relating to variables affecting heat within space  328  (e.g., occupant location, solar effects, weather, etc.) and generate temperature setpoints for the one or more IDUs within space  328 . Setpoint distribution optimizer  904  may determine temperature setpoints for one or more of the IDUs using a variety of methods. 
     Referring now to  FIG.  9 B , a block diagram of controller  800  generating a heat map, processing a heat map, and determining temperature setpoints for one or more IDUs within space  328 . The processing of controller  800  as shown in  FIG.  9 B  may be similar to that of the processing of controller  800  as shown in  FIG.  9 A , but may further include generating a heat map as opposed to receiving an already generated heat map.  FIG.  9 B  is shown to include heat map generator  906 , heat map processor  902 , and setpoint distribution optimizer  904 . 
     Heat map generator  906  may be or include processing that receives data from one or more thermal imaging devices to generate a representation of data in the form of a map or diagram in which data values (e.g., temperature values, heat values, etc.) are represented as colors. In some embodiments, heat map generator  906  receives temperature measurements from sensors (e.g., sensors  830 - 834 , etc.) and uses this temperature data to generate the colors within the heat map. Then, heat map generator  906  may provide the heat map data to heat map processor  902 , which may resemble the process outlined in  FIG.  9 A . 
     Referring now to  FIGS.  10 - 11   , a diagram of heat map  1000  is shown, according to some embodiments. In some embodiments, heat map  1000  represents a color-based map of space  1000 , which may be substantially similar or identical to space  828 . Referring specifically to  FIG.  11   , heat map  1020  may be configured to show unequal temperature distribution within space  1000 . Space  1000  is shown to include rooms  1002 ,  1004 ,  1006 ,  1008 ,  1010 ,  1012 ,  1014 ,  1016 , and  1018 . Heat map  1020  is shown to include heat regions  1020   a,    1020   b,  and  1020   c.  Heat regions  1020   a - c  may show regions of space  1000  at a significantly greater temperature (e.g., as shown within the center of region  1020   c,  etc.) than other areas within space  1000  (e.g., within room  1006 , etc.). The systems and methods disclosed herein may be utilized to substantially equalize the heat distribution throughout space  1000 . 
     In some embodiments, after these processes have been implemented to substantially equalize the heat distribution throughout space  1000 , a new heat map is generated or heat map  1020  is updated, to result in heat map  1120 , as shown in  FIG.  11   . Heat map  1120  as shown in  FIG.  11    shows a more equalized heat distribution in space  1000  than as shown in heat map  1020 . Specifically, a greater portion of space  1000  maintains a more uniform heat distribution, while there are less intense pockets of higher temperatures. 
     While  FIGS.  10 - 11    generally refer to space  1000  including multiple rooms, this is merely meant to be exemplary and should not be considered limiting. Any of the spaces considered herein, including space  1000 , can be a single space (e.g., cafeteria, auditorium, etc.), a space with multiple rooms, and anything in between. 
     Referring now to  FIG.  12   , another diagram of heat map  1020  is shown, according to some embodiments. Diagram  1200  is shown to include heat map  1210  and open space  1202 . As shown in  FIG.  12   , open space  1202  is an open floor space, such that the zones within the space are not limited to regions enclosed (either partially or entirely) by walls, or other obstructions (e.g., cubicle walls, etc.). While the systems and methods disclosed herein are generally referring to spaces containing zones, where the zones are separate rooms within the space, this is merely meant to be exemplary and should not be considered limiting. 
     As clearly shown in  FIG.  12   , the zones can be areas within an open floor space. Heat map  1210  shows substantially equal temperature distribution throughout multiple areas of open space  1202 . While not shown, these temperature distributions can be across multiple zones, in separate zones, or a combination thereof. In some embodiments, the multiple zones span different areas of open space  1202  and are modeled as such. 
     Referring now to  FIG.  13   , an air quality index (AQI) map  1300  is shown, according to some embodiments.  FIG.  13    is shown to include AQI map  1300  and graph  1320 . AQI map  1300  is shown to include zones  1302 ,  1304 ,  1306 ,  1308 ,  1310 ,  1312 ,  1314 ,  1316 , AQI region  1330 , and space  1318 . In some embodiments space  1318  is the entire space (e.g., the floor, entire region) in which all of the zones are located therein. For example, all of zones  1302 - 1316  are within space  1318 . 
     As mentioned above, while the systems and methods disclosed herein are generally referring to heat maps being utilized and/or processed to perform substantially equal temperature distribution, this is merely meant to be exemplary and should not be considered limiting. In some embodiments, such as those described with reference to  FIG.  13   , other types of maps, such as AQI maps, can be processed to determine air quality data regarding a space. The AQI data can then be used in conjunction with an objective function to optimize a control process. Examples of this are described in detail below. 
     Graph  1320  shows a key (e.g., legend, etc.) for understanding the different marks/shading represented in diagram  1300 . In some embodiments, graph  1320  shows the AQI levels for multiple AQI attributes (described below) and the varying risk levels thereof. For example a 60 ppb of Ozone within an 8-hr period is considered a “moderate” health risk. In some embodiments, this data is shown on AQI map  1300  can be processed (e.g., by controller  800 , etc.) and information relating to the AQI data for multiple AQI attributes can be used, along with an optimization process, to perform a type of optimization control. 
     For example, controller  800  may be configured to receive AQI data (e.g., from AQI map  1320 ) indicating the amount of carbon dioxide concentrations in the air throughout space  1300 . Optimizer  820  may then use an objective function to minimize the cost of energy by maintaining the levels of carbon dioxide below a predetermined threshold throughout the space. In such embodiments, the cost of energy consumed over a duration of time is minimized by selecting filtering techniques (e.g., air filtration fans/vacuums, etc.) that also conform to the imposed constraints (e.g., maximum CO2 levels, maximum energy costs, etc.). The optimization process may be using an objective function to minimize the total energy consumed over the duration of the optimization period. In other embodiments, optimization process may attempt to minimize CO2 levels as much as possible regardless of the cost. 
     In another example, controller  800  may be configured to receive AQI data relating to Ozone levels within space  1318 , and use the received AQI data, along with an objective function, to minimize health risks associated with Ozone levels. As such, constraints may be placed on the optimization process such that a certain “level” of health risk (e.g., moderate risk, unhealthy risk, etc.) may not be exceeded in any zone of the space  1318  while attempting to minimize ozone within the space  1318  and the multiple zones therein. 
     Of course, CO2 and Ozone are exemplary attributes that can be represented within AQI map  1320  and should not be considered limiting. Other attributes can be monitored, analyzed, optimized and represented within AQI map  1320 , either independently or in combination, such as carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), lead concentrations (Pb), nitrogen dioxide (NO2), particulate matter with a diameter of 10 micrometers or less (PM10), particulate matter with a diameter of 2.5 micrometers or less (PM2.5), and sulfur dioxide (SO2). As described herein, the term “AQI attribute” may be used to refer to one or more of these air quality characteristics described above. 
     In some embodiments, optimizer  820  may use a cost model to define the cost incurred (either in terms of monetary cost, energy, carbon emissions, etc.) as a function of the control decisions and also predicts AQI attribute (e.g., CO2, etc.)levels within each zone as a function of the control decisions using an AQI model of the space (e.g., generated by model generator  810 , etc.). Both models together (i.e., cost model and AQI model) may then be used by optimizer  820  to minimize cost while achieving the uniform CO2 levels. In such an example, a constraint may be placed on the system that prevents the adjusted CO2 levels from being any greater than 400 ppm, and thus optimizer  820  needs to determine the cheapest (e.g., energy cost-wise) way to provide substantially equal CO2 levels while conforming to this constraint. 
     In some embodiments, the constraint or penalty of the objective function is implemented as an additional fictitious cost term in the objective function that is not a true financial/energy cost, but rather imposes an additional “cost penalty” based on the differences between AQI attribute levels within the zones. Therefore, the objective function as a whole would may be minimizing the sum of actual cost (financial, energy, carbon, etc.) plus penalty cost (e.g., based on CO2 differences between zones). 
     In some embodiments, the constraint or penalty of the objective function includes a AQI attribute variation constraint that requires the differences between the AQI attribute levels within the zones predicted using the model to be less than or equal to one or more threshold values. Optimizer  820  may determine the amount of heat to transfer into or out of each of the plurality of zones by using the temperature variation constraint to prevent setpoint manager  824  from generating control decisions that would violate the temperature variation constraint. 
     In some embodiments, optimizer  820  may determine an occupancy status of a zone within space  828  that indicates whether the zone is occupied. In some embodiments, the penalty or constraint can be dynamically updated based on occupancy status to drop any unoccupied zones (e.g., or assign them a lower penalty or less restrictive constraint) so that the optimization process would not care so much about the AQI attribute of those unoccupied zones being different from the occupied zones. Optimizer  820  may then adjust a value of a constraint or penalty associated with the zone based on the occupancy status. This data may be provided to optimizer  820  externally or via one or more occupancy sensors (not shown). 
     The optimization problem may take into account additional factors (e.g., occupancy of zones, zone/space schedules, etc.) to determine which constraints to be added to the optimization problem. For example, if a zone within space  328  is not occupied, it may be determined that there is not a need to perform a substantially equal minimization of harmful AQI attributes within those particular zones. Similar to the heat map processes described above, a multiplicative flag may be applied to the constraints which can be set to zero to turn off these constraints and set to 1, when the space is occupied. In some embodiments, the flag may be set to some value between zero and one as well. 
     Predictive Control Processes Using Heat Maps 
     Referring now to  FIG.  14   , a flow diagram of process  1400  is shown, according to some embodiments. Process  1400  may be performed partially or entirely by any of the processing components described herein. For example, process  1400  may be performed partially or entirely by controller  800 . 
     Process  1400  is shown to include obtaining a heat map indicating zone temperatures of the plurality of zones (step  1402 ). As described herein, obtaining a heat map can include generating a heat map or receiving a heat map from an external source. In some embodiments, heat map processor  902  may obtain heat map  1020  via an external source (e.g., an external server, etc.). In other embodiments, controller  800  obtains heat map  1020  by generating heat map  1020  via heat map generator  906 . The heat map may include information about the intensity of the temperature and/or heat across space  828  using color. In some embodiments, the color acts as a visualization technique that shows the magnitude of the temperature as color in two dimensions (e.g., as shown in  FIGS.  10 - 11   , etc.). 
     Process  1400  is shown to include using a thermal model of the building space to predict the zone temperatures as a function of control decisions indicating an amount of heat to transfer into or out of each of the plurality of zones by the plurality of heat transfer devices (step  1204 ). As described above, model generator  818  may generate a model of space  828  which may represent the temperature effects within space  828 . The model may then be provided to optimizer  820  such that optimizer  820  can perform an optimization process based on the received model, the current heat map data, and one or more constraints to minimize energy cost and/or maximize comfort by having an equal (e.g., or substantially equal, etc.) temperature distribution in space  328 . 
     Process  1400  is shown to include determining the amount of heat to transfer into or out of each of the plurality of zones subject to a constraint or penalty based on differences between the zone temperatures predicted to result from the control decisions (step  1406 ). In some embodiments, optimizer  820  determines the amount of heat to transfer into or out of one or more zones by performing the optimization process. Various optimization processes can be considered and are described above. In one example, optimizer  820  attempts to minimize the amount of energy used over the duration of the optimization process, while conforming to various constraints imposed on the system, such as temperature range constraints (e.g., the temperature cannot exceed 75°, etc.). 
     Process  1400  is shown to include operating the plurality of heat transfer devices to transfer the amount of heat into or out of each of the plurality of zones in accordance with the control decisions (step  1408 ). Setpoint manager  824  may be configured to provide the updated control signals to one or more of the IDUs serving space  828 . In some embodiments the setpoints for one or more of the IDUs can be optimized and provided to the IDUs at periodic intervals (e.g., every 10 minutes, every hour, etc.) or in real time. 
     Configuration of Exemplary Embodiments 
     As utilized herein, the terms “approximately,” “about,” “substantially”, and similar terms are intended to have a broad meaning in harmony with the common and accepted usage by those of ordinary skill in the art to which the subject matter of this disclosure pertains. It should be understood by those of skill in the art who review this disclosure that these terms are intended to allow a description of certain features described and claimed without restricting the scope of these features to the precise numerical ranges provided. Accordingly, these terms should be interpreted as indicating that insubstantial or inconsequential modifications or alterations of the subject matter described and claimed are considered to be within the scope of the disclosure as recited in the appended claims. 
     It should be noted that the term “exemplary” and variations thereof, as used herein to describe various embodiments, are intended to indicate that such embodiments are possible examples, representations, or illustrations of possible embodiments (and such terms are not intended to connote that such embodiments are necessarily extraordinary or superlative examples). 
     The term “coupled” and variations thereof, as used herein, means the joining of two members directly or indirectly to one another. Such joining may be stationary (e.g., permanent or fixed) or moveable (e.g., removable or releasable). Such joining may be achieved with the two members coupled directly to each other, with the two members coupled to each other using a separate intervening member and any additional intermediate members coupled with one another, or with the two members coupled to each other using an intervening member that is integrally formed as a single unitary body with one of the two members. If “coupled” or variations thereof are modified by an additional term (e.g., directly coupled), the generic definition of “coupled” provided above is modified by the plain language meaning of the additional term (e.g., “directly coupled” means the joining of two members without any separate intervening member), resulting in a narrower definition than the generic definition of “coupled” provided above. Such coupling may be mechanical, electrical, or fluidic. 
     The term “or,” as used herein, is used in its inclusive sense (and not in its exclusive sense) so that when used to connect a list of elements, the term “or” means one, some, or all of the elements in the list. Conjunctive language such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is understood to convey that an element may be either X, Y, Z; X and Y; X and Z; Y and Z; or X, Y, and Z (i.e., any combination of X, Y, and Z). Thus, such conjunctive language is not generally intended to imply that certain embodiments require at least one of X, at least one of Y, and at least one of Z to each be present, unless otherwise indicated. 
     References herein to the positions of elements (e.g., “top,” “bottom,” “above,” “below”) are merely used to describe the orientation of various elements in the FIGURES. It should be noted that the orientation of various elements may differ according to other exemplary embodiments, and that such variations are intended to be encompassed by the present disclosure. 
     The hardware and data processing components used to implement the various processes, operations, illustrative logics, logical blocks, modules and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose single- or multi-chip processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, or, any conventional processor, controller, microcontroller, or state machine. A processor also may be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In some embodiments, particular processes and methods may be performed by circuitry that is specific to a given function. The memory (e.g., memory, memory unit, storage device) may include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present disclosure. The memory may be or include volatile memory or non-volatile memory, and may include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. According to an exemplary embodiment, the memory is communicably connected to the processor via a processing circuit and includes computer code for executing (e.g., by the processing circuit or the processor) the one or more processes described herein. 
     The present disclosure contemplates methods, systems and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure may be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions. 
     Although the figures and description may illustrate a specific order of method steps, the order of such steps may differ from what is depicted and described, unless specified differently above. Also, two or more steps may be performed concurrently or with partial concurrence, unless specified differently above. Such variation may depend, for example, on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations of the described methods could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps, and decision steps. 
     It is important to note that the construction and arrangement of various systems (e.g., system  100 , system  200 , etc.) and methods as shown in the various exemplary embodiments is illustrative only. Additionally, any element disclosed in one embodiment may be incorporated or utilized with any other embodiment disclosed herein. Although only one example of an element from one embodiment that can be incorporated or utilized in another embodiment has been described above, it should be appreciated that other elements of the various embodiments may be incorporated or utilized with any of the other embodiments disclosed herein.