JPWO2019035218A1 - Air conditioning system and air conditioning method - Google Patents

Abstract

A room temperature detecting unit (13) for detecting the room temperature in the building (2), an outside air temperature detecting unit (14) for detecting the outside air temperature, and a surface temperature detecting unit for detecting a surface temperature inside the window glass building (2). Unit (15), an air conditioning capability estimating unit (164) that estimates the air conditioning capability based on the amount of heat generated from the air conditioner (11), and based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning capability. A load coefficient learning unit (168) for learning a window load coefficient and an outside air load coefficient of the window glass; and an air conditioning load of the building (2) based on the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient. An air conditioning system (1) including an air conditioning load estimation unit (166) for estimating and a control unit for controlling the air conditioner (11) based on the air conditioning load.

Description

  The present invention relates to an air conditioning system and an air conditioning method for controlling an air conditioner.

  The air conditioning system realizes energy saving while maintaining a comfortable indoor environment for houses, office buildings and the like. For this reason, it is requested | required that the room | chamber interior is overcooled and the useless energy by overheating etc. should be reduced. In order to control the amount of heat supplied from the air conditioning system without excess or deficiency, the heat load in the room subject to air conditioning is estimated in real time using data from air conditioners and other equipment. It is necessary to adjust the air conditioning control amount appropriately according to the heat load.

  In particular, in a room with a large house window and in the vicinity of a window (perimeter zone) of an office building, solar radiation entering from the window greatly affects the air conditioning load. For this reason, in consideration of the heat load due to solar radiation, a method of selecting an appropriate window glass for a building window (for example, Patent Document 1) and a system for estimating the indoor heat load have been proposed (for example, Patent Document 2). Patent Document 3).

  Patent document 1 calculates solar heat load (window surface heat-receiving solar radiation amount) by the difference in construction area, season, time, window orientation, and window glass configuration.

  Patent document 2 uses a thermo camera and a solar radiation sensor to measure the temperature distribution and solar radiation amount of the outer wall surface including the window glass, and estimates the thermal load near the window (perimeter zone) according to the measurement result. is there.

  Patent Document 3 estimates the thermal load in the vicinity of the window (perimeter zone) based on the output characteristics of a light-transmissive organic thin-film solar cell installed on the window surface.

JP2008-107910 JP2011-202877 JP2015-218991A

  According to the method of Patent Document 1, it is necessary to input the construction area, season, time, orientation of the opening, and the configuration (performance) of the window glass. Based on these input data, the stored weather data is selected to calculate the solar heat load. For this reason, the solar heat load which penetrate | invades from a window glass in real time in real environment cannot be estimated.

  Moreover, according to the method of patent document 2, in order to estimate a heat load, the thermo camera which detects the temperature distribution of an outer wall surface, and the solar radiation sensor which is an exclusive apparatus which detects the amount of solar radiation are installed outside a building. This will increase equipment maintenance and costs.

  Furthermore, according to the technique of Patent Document 3, it is necessary to install a light transmissive organic thin film solar cell on each window surface. Light transmissive organic thin film solar cells are currently in the research and development stage, and light transmissive organic thin film solar cells for installation in windows are not yet widespread and are not practical.

  This invention learns the performance of the window glass without providing a dedicated detection device for detecting the amount of solar radiation, such as a solar radiation sensor, and a light-transmitting organic thin-film solar cell, and in real time according to changes in the environment An object of the present invention is to provide an air conditioning system and an air conditioning method capable of estimating the amount of solar radiation entering from a window glass and estimating the indoor solar heat load with high accuracy.

  An air conditioning system according to the present invention includes a room temperature detection unit that detects a room temperature in a building, an outside air temperature detection unit that detects an outside air temperature, a surface temperature detection unit that detects a surface temperature inside the building of the window glass, A window heat performance learning unit that learns the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature; an air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner; A window load coefficient learning unit that learns the window load coefficient of the window glass based on room temperature, outside air temperature, surface temperature, window heat performance, and air conditioning capability, and room temperature, outside air temperature, surface temperature, window heat performance, and window load coefficient It is an air conditioning system provided with the solar heat load estimation part which estimates the solar heat load by the solar radiation which injects from window glass based on these, and the control part which controls an air conditioner based on a solar heat load.

  An air conditioning system according to the present invention includes a room temperature detection unit that detects a room temperature in a building, an outside air temperature detection unit that detects an outside air temperature, a surface temperature detection unit that detects a surface temperature inside the building of the window glass, Air conditioning capability estimator that estimates the air conditioning capability based on the amount of heat generated from the air conditioner, and learns the window load coefficient and the outside air load coefficient of the window glass based on room temperature, outside temperature, surface temperature, and air conditioning capability A load coefficient learning unit that performs an air condition load estimation unit that estimates a building air condition load based on room temperature, outside air temperature, surface temperature, window load coefficient, and outside air load coefficient, and an air conditioner based on the air condition load It is an air conditioning system provided with the control part which controls.

  An air conditioning system according to the present invention includes a room temperature detection unit that detects a room temperature in a building, an outside air temperature detection unit that detects an outside air temperature, a surface temperature detection unit that detects a surface temperature inside the building of the window glass, A window heat performance learning unit that learns the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature, the window optical performance relational expression according to the unit solar radiation amount and the window glass structure, the room temperature, the outside air temperature, and the surface temperature. A window optical performance learning unit that learns the window optical performance of the window glass based on the window thermal performance, and from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance. An air conditioning system including a solar heat load estimating unit that estimates a solar heat load due to incident solar radiation, and a control unit that controls the air conditioner based on the solar heat load.

  The air conditioning method according to the present invention includes a room temperature detecting step for detecting a room temperature in a building, an outside air temperature detecting step for detecting an outside air temperature, a surface temperature detecting step for detecting a surface temperature inside the building of the window glass, and A window heat performance learning step for learning the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature; an air conditioning capability estimation step for estimating the air conditioning capability based on the amount of heat generated from the air conditioner; A window load coefficient learning step for learning a window load coefficient of a window glass based on room temperature, outside air temperature, surface temperature, window heat performance, and air conditioning capacity, and room temperature, outside air temperature, surface temperature, window heat performance, and window load coefficient. An air conditioning method comprising: a solar heat load estimating step for estimating a solar heat load due to solar radiation incident from the window glass based on the above; and a control step for controlling the air conditioner based on the solar heat load A.

  The air conditioning method according to the present invention includes a room temperature detecting step for detecting a room temperature in a building, an outside air temperature detecting step for detecting an outside air temperature, a surface temperature detecting step for detecting a surface temperature inside the building of the window glass, and Air conditioning capability estimation step that estimates the air conditioning capability based on the amount of heat generated from the air conditioner, and learns the window load coefficient and the outside air load coefficient of the window glass based on the room temperature, outside temperature, surface temperature, and air conditioning capability A load coefficient learning step, an air condition load estimation step for estimating an air condition load of the building based on room temperature, outside air temperature, surface temperature, window load coefficient, and outside air load coefficient, and an air conditioner based on the air condition load It is an air conditioning method provided with the control step which controls.

  The air conditioning method according to the present invention includes a room temperature detecting step for detecting a room temperature in a building, an outside air temperature detecting step for detecting an outside air temperature, a surface temperature detecting step for detecting a surface temperature inside the building of the window glass, and The window thermal performance learning step for learning the window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature, the window optical performance relational expression by the unit solar radiation amount and the structure of the window glass, the room temperature, the outside air temperature, and the surface temperature. A window optical performance learning step for learning the window optical performance of the window glass based on the window heat performance, and from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance. An air conditioning method comprising a solar heat load estimating step for estimating a solar heat load due to incident solar radiation, and a control step for controlling the air conditioner based on the solar heat load.

  According to this invention, without providing a dedicated detection device for detecting the amount of solar radiation or a light-transmitting organic thin-film solar cell, air for estimating an indoor solar heat load or air-conditioning load and controlling the air conditioner A conditioning system and an air conditioning method can be obtained.

It is a perspective view for demonstrating the internal example of the building to which the air conditioning system by Embodiment 1 of this invention is applied. It is an example of the block diagram of the air conditioning system by Embodiment 1 of this invention. It is an example of the processing flow of the air conditioning system by Embodiment 1 of this invention. It is an example of the temperature gradient figure by the presence or absence of the solar radiation by Embodiment 1 of this invention. It is an example of the indoor thermal image and photograph by Embodiment 1 of this invention. It is an example of the figure which shows the relationship between the solar radiation absorptivity (alpha) of the window glass by Embodiment 1 of this invention, and the solar heat acquisition rate (eta). It is an example of the block diagram of the air conditioning system by Embodiment 2 of this invention. It is an example of the external view of the air conditioner by Embodiment 2 of this invention. It is an example of the processing flow of the air conditioning system by Embodiment 2 of this invention. It is an example of the block diagram of the air conditioning system by Embodiment 3 of this invention. It is an example of the processing flow of the air conditioning system by Embodiment 3 of this invention. It is an example of the block diagram of the air conditioning system by Embodiment 4 of this invention. It is an example of the processing flow of the air conditioning system by Embodiment 4 of this invention.

Embodiment 1 FIG.
FIG. 1 is a perspective view for explaining an internal example of a building 2 to which an air conditioning system according to Embodiment 1 of the present invention is applied. The building 2 represents a house, and the air conditioner 11 provided on the wall 3 is a wall-mounted air conditioner 11. Solar radiation from the sun passes through the window 4 of the building 2 and reaches the floor 5 and the wall 3. The building 2 is not limited to a house, and the air conditioning system of the present embodiment can be installed in an office building or the like. The air conditioner 11 is not limited to a wall-hanging type, and a device that harmonizes indoor air, such as a ceiling cassette type or a duct connection type, can be used as the air conditioner 11.

  FIG. 2 is an example of a configuration diagram of the air-conditioning system according to Embodiment 1 of the present invention. The air conditioning system 1 detects an air conditioner 11, an input device 12 to which information from the outside is input, a room temperature detection device 13 that detects a room temperature Tz of the building 2, and an outside air temperature Ta outside the building 2. An outside air temperature detection device 14, a surface temperature detection device 15 that detects the surface temperature Tg of the window glass, a calculation device 16 that performs various calculations, and a memory that stores information on various detection devices and calculation results of the calculation device 16. The apparatus 17 is comprised from the input device 12 into which the information from the outside is input, the control apparatus 19 which controls the air conditioner 11, and the communication path 18 which exchanges information between various apparatuses.

  The surface temperature detection device 15 is a thermal image sensor (infrared temperature sensor), a thermo camera, or the like installed indoors so as to detect the surface temperature Tg of the window glass inside the building 2 to be air-conditioned. To do. In the following description, unless otherwise specified, the surface temperature is the surface temperature Tg of the window glass inside the building 2. The computing device 16 includes a window heat performance learning unit 161, a window optical performance learning unit 162, and a solar heat load estimation unit 163, and is specifically a CPU.

  The storage device 17 includes a unit unit solar radiation amount 171, a window optical performance relational expression 172, a window area 173, a window heat performance 174, a window optical performance 175, and the like, and is specifically a storage medium such as a hard disk or a RAM. . The communication path 18 is for communication connecting the air conditioner 11, the input device 12, the room temperature detection device 13, the outside air temperature detection device 14, the surface temperature detection device 15, the arithmetic device 16, the storage device 17, and the control device 19. Network. The communication path 18 is not particularly limited with respect to the type of cable, the communication protocol, and the like. Further, the control device 19 determines a control command for the air conditioner 11 based on the estimated solar heat load value via the communication path 18.

  FIG. 3 is an example of a processing flow of the air-conditioning system according to Embodiment 1 of the present invention. Hereinafter, each step will be described.

[S11: Whether there is solar radiation or not]
In S11, it is determined whether there is solar radiation. Thereafter, if there is solar radiation, the process proceeds to S13, and if there is no solar radiation, the process proceeds to S12. An example of how to determine whether there is solar radiation is shown below.

  In order to learn the window heat performance 174, it is necessary to use data when there is no influence of solar radiation. When solar radiation directly hits the window glass surface, heat is absorbed by the window glass and the surface temperature Tg of the window glass rises.

  FIG. 4 is an example of a temperature gradient diagram according to presence or absence of solar radiation according to Embodiment 1 of the present invention. More specifically, it is a diagram showing the temperature gradient of the outside air temperature Ta, the window glass surface temperature Tg, and the room temperature Tz, with or without solar radiation in summer and winter. In the case where there is no solar radiation in the upper stage, in the case where there is solar radiation in the lower stage, the cooling operation is performed on the left side in the summer, and the heating operation is performed in the winter on the right side. Further, Ta is the outside air temperature Ta, Tz is the room temperature, Tg is the surface temperature Tg on the indoor side of the window 4, and the upper part indicates that the temperature is high and the lower part indicates that the temperature is low. Furthermore, when there is solar radiation at the lower stage, window absorption solar radiation is indicated by a thick arrow.

  Using the room temperature Tz detected by the room temperature detection device 13, the outside air temperature Ta detected by the outside air temperature detection device 14, and the surface temperature Tg of the window glass detected by the surface temperature detection device 15, the surface temperature Tg of the window glass is room temperature. When it is higher than Tz and the surface temperature Tg of the window glass is higher than the outside air temperature Ta, it is determined that there is solar radiation (the upper part of the formula 1 group). In addition, when the time when the air conditioning system 1 is in operation is known, nighttime data can be used as data for conditions without solar radiation. When there is no solar radiation, the temperature increases in the order of the room temperature Tz, the window glass surface temperature Tg, and the outside air temperature Ta during cooling in the summer (the middle part of Formula 1 group). On the other hand, when there is no solar radiation, the temperature increases in the order of the outside temperature Ta, the surface temperature Tg of the window glass, and the room temperature Tz during heating in winter (lower part of Formula 1 group).

  FIG. 5 is an example of an indoor thermal image and photograph according to Embodiment 1 of the present invention. The thermal image in the state of the lower photograph is the upper section. FIG. 5 shows experimental equipment brought into an actual house, and a plurality of support columns are installed. Moreover, the right side of FIG. 5 is a curtain, and the back left is a radiation panel. Here, it can be seen that the position of the window 4 can be detected even when a lace curtain, a blind or the like is used. Thus, the presence or absence of solar radiation can be determined by regarding the surface temperature of the lace curtain, blind, etc. at the position of the window 4 as the surface temperature Tg of the window glass.

[S12: Window thermal performance learning]
The window thermal performance learning unit 161 learns the window thermal performance of the window glass based on the room temperature Tz, the outside air temperature Ta, and the surface temperature Tg of the window glass (S12). Specifically, the window heat performance learning unit 161 calculates the heat flow resistance R of the window glass using data when it is determined that there is no solar radiation in S11. The window thermal performance is not limited to the heat flow resistance R, and may include performance based on the thermal resistance.

The heat flow resistance R of the window glass is calculated based on Equation 2 using the room temperature Tz, the outside air temperature Ta, and the window glass surface temperature Tg. In Equation 2, Ri represents the inner surface heat transfer resistance of the window glass, and 0.116 [m ² K / W] is used according to JIS R3107. Further, the calculated heat flow resistance R of the window glass is stored in the window heat performance 174 of the storage device 17.

[S13: Absorption solar radiation amount estimation]
The solar heat load estimation unit 163 estimates the amount of solar radiation Iα absorbed by the window glass using the data when it is determined that there is solar radiation in S11 (S13).

[S14: Window optical performance learning]
The window optical performance learning unit 162 calculates the solar radiation absorption rate α and the solar heat acquisition rate η of the window glass. The window optical performance is not limited to the solar radiation absorption rate α and the solar heat acquisition rate η, and may include other performances related to solar radiation. The unit-specific solar radiation amount 171 indicates a theoretical value calculated from the longitude, latitude, and date of the region. The date can be input from the input device. If the storage device 17 has a timer function, the date of the timer is used.

  First, the solar radiation absorptance α of the window glass is calculated from the absorbed solar radiation amount calculated using the formula 3 group and the unit solar radiation amount Ir in order to obtain the solar radiation absorptance α from the formula 4. In Equation 4, the unit solar radiation Ir is calculated based on the region input from the input device 12, the region-specific unit solar radiation 171 stored in the storage device 17, the room temperature Tz, the outside air temperature Ta, and the surface temperature of the window glass. It is determined based on the date when Tg is detected. The unit-specific solar radiation amount 171 indicates a theoretical value calculated from the longitude, latitude, and date of the region. For example, the date can be input from the input device 12, and if the storage device 17 has a timer function, the date of the timer can be used.

  The solar radiation absorptance α of the window glass calculated by Expression 4 is stored in the window optical performance 175 of the storage device 17. For example, the solar radiation absorption rate α of the window glass initially takes the maximum estimated value, is updated with the learned result, and is stored in the window optical performance 175 (S14).

  FIG. 6 is an example of a diagram showing the relationship between the solar radiation absorption rate α and the solar heat acquisition rate η of the window glass according to Embodiment 1 of the present invention. More specifically, the solar absorptance α is plotted on the horizontal axis and the solar heat gain η is plotted on the vertical axis, and the relationship between the two is approximated by a linear linear expression. Note that the relationship between the solar radiation absorption rate α and the solar heat acquisition rate η is not limited to the approximation method based on the linear linear equation, and the approximation equation shown in FIG. 6 is merely an example.

The window glass shown in FIG. 6 uses window glass of many types and thickness as follows. This is because, depending on the type of window glass, the heat flow resistance R, the solar radiation absorption rate α, and the solar heat acquisition rate η are different, and the window optical performance 175 is different.
・ Single plate glass: Transparent plate glass, heat ray absorbing plate glass, heat ray reflecting glass ・ Laminated glass: Glass in which two single plate glasses are bonded by an adhesive (transparent plate glass + transparent plate glass, heat ray absorbing plate glass + transparent plate glass, heat ray reflecting glass + transparent Flat glass)
-Multi-layer glass: Glass composed of two single-plate glasses having a hollow layer (transparent plate glass + hollow layer + transparent plate glass, heat ray absorbing plate glass + hollow layer + transparent plate glass, heat ray reflective glass + hollow layer + transparent plate glass)
These include nine glasses having a thickness of 3 mm to 8 mm.

  The solar absorptance α obtained by Equation 4 is applied to the relational expression with the solar heat acquisition rate η shown in FIG. 6 to calculate the solar heat acquisition rate η. In addition, the relational expression of solar radiation absorption rate (alpha) and solar heat acquisition rate (eta) can be changed by the change and addition of the structure of a window glass. Further, before learning the window optical performance 175, the formula stored in the window optical performance relational expression 172 of the storage device 17 may be used.

  As described above, the window optical performance learning unit 162 determines the window glass window based on the unit solar radiation amount and the window optical performance relational expression 172 based on the configuration of the window glass, the room temperature Tz, the outside temperature Ta, the surface temperature Tg, and the window heat performance. The optical performance is learned (S14).

[S15: Solar heat load estimation]
In the solar heat load estimation unit 163, based on the absorption solar radiation amount Iα of the window glass estimated in S13, the solar radiation absorption rate α of the window glass stored in the window optical performance 175 of the storage device 17, and the solar heat acquisition rate η. Then, the solar heat load Qs is estimated using Equation 5 (S15). In Equation 5, Ag represents the area of the window glass. As the window area Ag, for example, a window area value input from the input device, a window area value estimated from the surface temperature detection device, or the like may be used. More specifically, the value of the window area Ag stored in the window area 173 of the storage device 17 is used.

  If the input condition is expressed in another form, the solar heat load estimating unit 163 is incident from the window glass based on the window area 173, the room temperature Tz, the outside air temperature Ta, the surface temperature Tg, the window heat performance 174, and the window optical performance 175. The solar heat load due to solar radiation will be estimated.

[S16: Air conditioning control command determination]
The control device 19 determines a control command for the air conditioning capability Qhvac of the air conditioner 11 based on the solar heat load Qs estimated in S15 (S16). Thereafter, the process returns to S11.

  The control command is not limited to the air conditioning capability Qhvac, and the command value of the blowout temperature of the air conditioner, the direction of the blowout, and the like can be controlled as the control command value.

  As described above, the room temperature detection unit for detecting the room temperature in the building, the outside air temperature detection unit for detecting the outside air temperature, the surface temperature detection unit for detecting the surface temperature inside the building of the window glass, the room temperature and the outside air temperature Window thermal performance learning unit that learns the window thermal performance of the window glass based on the surface temperature and the window optical performance relational expression according to the unit solar radiation amount and the configuration of the window glass, room temperature, outside temperature, surface temperature, and window thermal performance Window optical performance learning unit that learns the window optical performance of the window glass based on the window, and the solar radiation incident from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance An air conditioning system including a solar heat load estimating unit that estimates a solar heat load and a control unit that controls the air conditioner based on the solar heat load.

  Also, a room temperature detecting step for detecting the room temperature in the building, an outside air temperature detecting step for detecting the outside air temperature, a surface temperature detecting step for detecting the surface temperature inside the building of the window glass, the room temperature, the outside air temperature, and the surface temperature. Based on the window thermal performance learning step to learn the window thermal performance of the window glass based on the above, the window optical performance relational expression by the unit solar radiation amount and the configuration of the window glass, the room temperature, the outside air temperature, the surface temperature, and the window thermal performance A window optical performance learning step for learning the window optical performance of the window glass, and a solar heat load due to solar radiation incident from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance It is an air conditioning method provided with the solar heat load estimation step which estimates this, and the control step which controls an air conditioner based on a solar heat load.

  For this reason, an air conditioning system and an air conditioning method for estimating an indoor solar heat load and controlling an air conditioner without providing a dedicated detection device for detecting the amount of solar radiation and a light-transmissive organic thin film solar cell. Can be obtained.

  Furthermore, the window thermal performance is a performance based on the heat flow resistance R, and the window optical performance is a performance based on the solar radiation absorption rate α and the solar heat acquisition rate η. For this reason, the air conditioning system can estimate the solar heat load of the building to be air conditioned with high accuracy.

Embodiment 2. FIG.
FIG. 7 is an example of a configuration diagram of an air-conditioning system according to Embodiment 2 of the present invention. Differences from the first embodiment are as follows.

  First, the functions of the air conditioner 11 are subdivided. Specifically, the indoor unit 111 of the air conditioner 11 includes a room temperature detection device 1111 that detects the room temperature Tz of the building 2 and a surface temperature detection device 1112 that detects the surface temperature Tg inside the building of the window glass. Moreover, the outdoor unit 112 includes an outside air temperature detection device 1121 that detects an outside air temperature Ta outside the building 2.

  The room temperature detection device 1111 is an alternative to the room temperature detection device 13 of the first embodiment. Further, the surface temperature detection device 1112 is a substitute for the surface temperature detection device 15 of the first embodiment. Further, the outside air temperature detecting device 1121 is an alternative to the outside air temperature detecting device 14 of the first embodiment. As long as it has an equivalent function, it does not matter whether it is provided as a function of the air conditioner 11 or provided separately. This is the same in other embodiments.

  Next, the difference from the first embodiment is that the computing device 16 includes an indoor heat generation load estimation unit 160, an air conditioning capability estimation unit 164, a total heat loss coefficient learning unit 165, and an air conditioning load estimation unit 166. In addition, the storage device 17 is different in that a total heat loss coefficient 176 for storing the total heat loss coefficient KA is added.

  In the drawings, the same reference numerals denote the same or corresponding parts, and this is common to the entire text of the specification and all the drawings. Furthermore, the form of the constituent elements appearing in the whole specification is merely an example, and is not limited to these descriptions.

  FIG. 8 is an example of an external view of the air conditioner 11 according to the second embodiment of the present invention. The air conditioner 11 is an example of a wall-mounted indoor unit 111. An indoor unit 111 including a room temperature detection device 1111 and a surface temperature detection device 1112 and an outdoor unit 112 including an outside air temperature detection device 1121 are connected by a connection pipe 113. Connect and harmonize the interior of the room. When the air conditioner 11 includes a remote controller, a remote controller can be used as the input device 12.

  In addition, a calculation device 16 that performs various calculations, a storage device 17 that stores information on various detection devices and calculation results of the calculation device 16, an input device 12 that receives external information, and an air conditioner 11 And a communication path 18 for exchanging information between various devices.

(Processing flow)
FIG. 9 is an example of a processing flow of the air-conditioning system according to Embodiment 2 of the present invention. It is an example of the processing flow implemented during operation | movement of the air conditioning system. The processing related to the operation of estimating the solar heat load is the same as that in the first embodiment. Specifically, S31 is S11, S32 is S12, S34 is S13, S35 is S14, S36 is S15, and S38 is S16. (Embodiment 1 is the 10th step) The second embodiment is the 30th generation step), and since it is the same process, detailed description thereof is omitted.

[S30: Indoor heat generation load estimation]
In S30, the indoor heat generation load estimation unit 160 estimates the indoor heat generation load Qin when a person is present in the building 2 (living room), or when a heating device such as lighting or a television is turned on. The indoor heat generation load Qin is the total of those due to human body heat generation (human body heat load), those due to illumination heat generation (lighting load), and those due to device heat generation (device heat generation load). The indoor heat generation load Qin increases the load during cooling, and decreases the load during heating.

  The indoor heat generation load Qin can be estimated as the total amount of each heat generation from the number of people in the room (human body heat load) measured by the surface temperature detection device 1112 and the ON state (lighting load, appliance heat generation load) of the device that generates heat. it can. For example, the indoor heat generation load Qin can be estimated from the sum of each heat generation amount using the heat generation amount 98 [W / person] of the person described in the Air Conditioning / Hygiene Engineering Handbook and the heat generation amount 90 [W] of the lighting.

  Further, the indoor heat generation load Qin is not limited to the estimation using the total amount of each heat generation, but the indoor heat generation load Qin is treated as a coefficient, and the total heat loss coefficient KA and the indoor heat generation load Qin are expressed using the following formula 6 group. Can also be obtained using regression analysis. Thus, how to obtain the indoor heat generation load Qin is not limited to a specific method. When there is no person in the building 2 (living room) corresponding to room heat generation, or when a device that generates heat such as lighting is turned off, etc., the room heat generation load is 0, the room heat generation load Qin is 0. To do.

  In S31, it is determined whether or not there is solar radiation. Thereafter, if there is no solar radiation, the process proceeds to S32, and if there is solar radiation, the process proceeds to S34. In S32, the window thermal performance learning unit 161 learns the window thermal performance 174 of the window glass based on the room temperature Tz, the outside air temperature Ta, and the surface temperature Tg of the window glass. Thereafter, the process proceeds to S33.

  On the other hand, in S34, the solar heat load estimation unit 163 estimates the amount of solar radiation Iα absorbed by the window glass using data when it is determined that there is solar radiation in S31. Thereafter, the window optical performance learning unit 162 determines the window optical performance of the window glass based on the unit solar radiation amount Ir, the window optical performance relational expression based on the configuration of the window glass, the room temperature Tz, the outside air temperature Ta, the surface temperature Tg, and the window heat performance 174. Is learned (S35). Then, in the solar heat load estimation part 163, it is based on the solar radiation which injects from a window glass based on window area Ag, room temperature Tz, external temperature Ta, surface temperature Tg, window thermal performance (S32), and window optical performance (S35). The solar heat load Qs is estimated (S36), the process proceeds to S37 and S38, and the process returns to S30.

[S33: Total heat loss coefficient learning]
When there is no solar radiation, the total heat loss coefficient learning unit 165 detects the room temperature Tz detected by the room temperature detection device 1111 of the indoor unit 111 of the air conditioner 11 when it is determined in S31 that there is no solar radiation, and the outdoor of the air conditioner 11 Using the outside air temperature Ta detected by the outside air temperature detection device 1121 of the machine 112 and the indoor heat generation load Qin estimated by the indoor heat generation load estimation unit 160 in S30, the total heat loss coefficient KA is calculated from the equation 6 group. Learn (S33). However, the indoor heat generation load Qin is positive using the upper stage of the formula 6 group during cooling, and the indoor heat generation load Qin is negative using the lower stage of the formula 6 group during heating.

  When the indoor heat generation load Qin is handled as a predetermined coefficient, the step of estimating the indoor heat generation load Qin in the indoor heat generation load estimation unit 160 is omitted in S30, and the total heat loss coefficient KA and the indoor heat generation are calculated from the group 6 in S33. The load Qin can also be learned by regression analysis. Note that the learning of the window heat performance 174 in S32 and the learning of the total heat loss coefficient KA in S33 do not matter.

  Here, the method of estimating the indoor heat generation load Qin is shown, but the air conditioner 11 can also be controlled without considering the indoor heat generation load Qin. For example, it is a case where the influence of the indoor heat generation load Qin is considered to be small with respect to solar radiation. In this case, the term of the indoor heat generation load Qin may be handled as zero in an equation such as Equation 6 group. This also applies to Embodiment 3 and Embodiment 4 described later.

  The total heat loss coefficient learning unit 165 learns the total heat loss coefficient KA of the building 2 based on the room temperature Tz, the outside air temperature Ta, the air conditioning capability Qhvac, and the indoor heat generation load Qin. The total heat loss coefficient KA is a through flow that flows into the room from the wall 3 or window 4 or flows out from the room to the wall 3 or window 4 when the temperature difference between the inside and outside of the building 2 (living room) subject to air conditioning is 1 degree. It is the sum of heat transfer due to heat and ventilation, and its unit is [W / K].

  The air conditioning capability Qhvac is a value obtained by estimating the amount of heat supplied from the air conditioner 11 during heating by the air conditioning capability estimation unit 164 and the amount of heat removed by the air conditioner 11 during cooling. In the following description, the air conditioning capability Qhvac indicates the amount of heat supplied during heating and the amount of heat removed during cooling. For example, the air conditioning capability Qhvac can be estimated from the difference in enthalpy between the high pressure side and the low pressure side of the refrigerant of the air conditioner 11. In addition, the estimation formula of the air conditioning capability Qhvac is not limited to the calculation based on the enthalpy difference of the refrigerant, and a method of obtaining from the difference of the air enthalpy between the suction and the blowout can be used. Thus, how to obtain is not limited.

  The calculated total heat loss coefficient KA is stored in the total heat loss coefficient 176 of the storage device 17. However, in order to obtain the total heat loss coefficient KA using the formula 6 group, it is necessary to perform calculation using data in which the room temperature Tz is stable. The stability of the room temperature Tz can be determined from the inclination of the room temperature Tz at a predetermined time interval (for example, selected from 30 minutes, 60 minutes, etc.), the variation in the room temperature Tz, and the like.

[S37: Air conditioning load estimation]
After estimating the solar heat load Qs in S36 and learning the total heat loss coefficient KA in S33, the air conditioning load estimation unit 166 uses the indoor heat generation load Qin estimated in S30 and the solar heat load Qs estimated in S36. Based on the total heat loss coefficient KA of the air conditioning target building 2 stored in the total heat loss coefficient 176 of the storage device 17, the room temperature Tz, and the outside temperature Ta, the air conditioner The load Q is estimated (S37). In Formula 7 group, the cooling time is on the upper stage and the heating time is on the lower stage.

  Moreover, it is also possible to estimate and use the amount of heat necessary for air conditioning for each set temperature from Equation 7 using the set temperature Tset of the air conditioner 11 instead of the room temperature Tz. However, during cooling, the solar heat load Qs and the indoor heat generation load Qin are positive using the upper stage of the formula 7 group, and during the heating, the solar heat load Qs and the indoor heat generation load Qin are negative using the lower stage of the formula 7 group. .

[S38: Determination of air conditioning control command]
The control device 19 determines a control command for the air conditioning capability Qhvac of the air conditioner 11 based on the air conditioning load Q estimated in S37 (S38). Thereafter, the process returns to S30. The control command is not limited to the air conditioning capability Qhvac, and the command value of the blowout temperature of the air conditioner 11, the direction of the blowout, and the like can be controlled as the control command value.

  As described above, the room temperature detection unit for detecting the room temperature in the building, the outside air temperature detection unit for detecting the outside air temperature, the surface temperature detection unit for detecting the surface temperature inside the building of the window glass, the room temperature and the outside air temperature Window thermal performance learning unit that learns the window thermal performance of the window glass based on the surface temperature and the window optical performance relational expression according to the unit solar radiation amount and the configuration of the window glass, room temperature, outside temperature, surface temperature, and window thermal performance Window optical performance learning unit that learns the window optical performance of the window glass based on the window, and the solar radiation incident from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance An air conditioning system including a solar heat load estimating unit that estimates a solar heat load and a control unit that controls the air conditioner based on the solar heat load.

  Also, a room temperature detecting step for detecting the room temperature in the building, an outside air temperature detecting step for detecting the outside air temperature, a surface temperature detecting step for detecting the surface temperature inside the building of the window glass, the room temperature, the outside air temperature, and the surface temperature. Based on the window thermal performance learning step to learn the window thermal performance of the window glass based on the above, the window optical performance relational expression by the unit solar radiation amount and the configuration of the window glass, the room temperature, the outside air temperature, the surface temperature, and the window thermal performance A window optical performance learning step for learning the window optical performance of the window glass, and a solar heat load due to solar radiation incident from the window glass based on the window glass area, room temperature, outside air temperature, surface temperature, window heat performance, and window optical performance It is an air conditioning method provided with the solar heat load estimation step which estimates this, and the control step which controls an air conditioner based on a solar heat load.

  For this reason, an air conditioning system and an air conditioning method for estimating an indoor solar heat load and controlling an air conditioner without providing a dedicated detection device for detecting the amount of solar radiation and a light-transmissive organic thin film solar cell. Can be obtained.

  Furthermore, the window thermal performance is a performance based on the heat flow resistance R, and the window optical performance is a performance based on the solar radiation absorption rate α and the solar heat acquisition rate η. For this reason, the air conditioning system can estimate the solar heat load of the building to be air conditioned with high accuracy.

  Moreover, since the surface temperature detection part is provided in the air conditioner, the solar heat load of the building subject to air conditioning can be estimated with high accuracy.

  In addition, an air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner, and a total heat loss coefficient that learns the total heat loss coefficient of the building based on room temperature, outside temperature, and air conditioning capability A learning unit, and an air conditioning load estimation unit that estimates the air conditioning load of the building based on the room temperature, the outside air temperature, the total heat loss coefficient, and the solar heat load, and the control unit performs air conditioning based on the air conditioning load. Since the machine is controlled, it is possible to estimate the solar heat load of the building subject to air conditioning with high accuracy.

Embodiment 3 FIG.
FIG. 10 is an example of a configuration diagram of an air-conditioning system according to Embodiment 3 of the present invention. The major difference from the second embodiment is that the window heat performance and the window optical performance are not individually learned in order to estimate the solar heat load Qs, but the surface temperature Tg of the window glass and the solar heat load Qs. The correlation coefficient is learned, and the solar heat load Qs is estimated from the surface temperature Tg of the window glass. Note that the window load coefficient Hg is a coefficient including window thermal performance, window optical performance, and window area Ag.

  More specifically, the calculation device 16 includes the same indoor heat generation load estimation unit 160, window heat performance learning unit 161, solar heat load estimation unit 163, air conditioning capability estimation unit 164, total heat loss as in the second embodiment. In addition to the coefficient learning unit 165, the air-conditioning load estimation unit 166, and the like, a window load coefficient learning unit 167 is provided. Further, the storage device 17 includes a window load coefficient 177 in addition to the window heat performance 174, the total heat loss coefficient 176, and the like.

  The air conditioning system 1 includes a room temperature detection device 1111 that detects the room temperature Tz of the building 2, a surface temperature detection device 1112 that detects the surface temperature Tg of the window glass, and an outside air temperature detection that detects the outside air temperature Ta outside the building 2. A device 1121, an input device 12 to which information from the outside is input, a calculation device 16 that performs various calculations, a storage device 17 that stores information of various detection devices and calculation results of the calculation device 16, and air conditioning It comprises a control device 19 for controlling the machine 11 and a communication path 18 for exchanging information between various devices.

  In a room where air conditioning is performed on a day with solar radiation, the room temperature Tz is stable (for example, the variation of the room temperature Tz is 0 degree) at a predetermined time interval (for example, selected from 30 minutes, 60 minutes, etc.). ), The heat balance equation of equation 8 holds. When the heat balance equation of Equation 8 holds, the air conditioning capability Qhvac can be obtained based on the total heat loss coefficient KA, the room temperature Tz, the outside air temperature Ta, the solar heat load Qs, and the indoor heat generation load Qin. (Equation 8) In Equation 8, a positive value is selected for the solar heat load Qs and the indoor heat generation load Qin during cooling, and a negative value is selected for the solar heat load Qs and the indoor heat generation load Qin during heating.

  In addition, it is ideal that the room temperature Tz is stable in a state where the variation in the room temperature Tz is 0 degree. For example, if the variation is ± 0.5 degrees and ± 1 degree, the error increases but the allowable range is reached. It can be handled that the room temperature Tz is stable.

  Equation 9 can be derived from Equation 3 and Equation 5, and the solar heat load Qs can be estimated using Equation 9. As shown in Equation 9, the solar heat load Qs includes a window load coefficient Hg, a window glass thermal resistance R, a window glass inner surface heat transfer resistance Ri, a room temperature Tz, an outside temperature Ta, and a window glass surface temperature Tg. It can be expressed using. Note that the right side of the upper expression 9 corresponds to the window load coefficient Hg. Thus, the window load coefficient Hg can be expressed by the heat flow resistance R, the inner surface heat transfer resistance Ri, the solar heat acquisition rate η, the solar radiation absorption rate α, and the window area Ag.

  Further, since the surface temperature Tg of the window glass is affected by the room temperature Tz, the outside air temperature Ta, and the amount of solar radiation Iα, the surface temperature Tg of the window glass can be calculated from Equation 10. In Equation 10, the influence due to solar radiation is the value of the third term, and the first and second terms are the influence of the room temperature Tz and the outside temperature Ta. In a window having good heat insulation performance such as a plurality of glasses, the heat flow resistance R becomes large, and the influence of the second term can be ignored.

  When the influence of the second term can be ignored, the absorbed solar radiation amount can be estimated using Equation 11 in which the second term is omitted, and the solar heat load Qs can be calculated by Equation 12.

(Processing flow)
FIG. 11 is an example of a processing flow of the air-conditioning system according to Embodiment 3 of the present invention. It is a processing flow implemented while the air conditioning system 1 is in operation. In contrast to the processing flow of the second embodiment (FIG. 9), the processing S50 related to the operation of estimating the indoor heat generation load Qin is S30, the processing related to the operation of learning the total heat loss coefficient KA is S51 to S31, S53 is a step corresponding to S33, and is a similar process, and thus detailed description thereof is omitted. Further, the process S52 for learning the window heat performance corresponds to S32, the process S56 for estimating the air conditioning load Q to S37, and the process S57 for determining the air conditioning control command to S38. Therefore, detailed description thereof is omitted (the second embodiment is a step in the 30th generation and the third embodiment is a step in the 50th generation).

  In S50, the indoor heat generation load Qin is estimated, and the process proceeds to S51. When there is no solar radiation in S51, it progresses to S52 and the window thermal performance learning part 161 learns the window thermal performance of a window glass based on the room temperature Tz, the external temperature Ta, and the window glass surface temperature Tg. Thereafter, the process proceeds to S53, where the total heat loss coefficient learning unit 165 learns the total heat loss coefficient KA of the building 2 based on the room temperature Tz, the outside air temperature Ta, the air conditioning capability Qhvac, and the indoor heat generation load Qin. The air conditioning capability estimation unit 164 can estimate the air conditioning capability Qhvac based on the amount of heat generated from the air conditioner 11 (the amount of heat to be removed).

[S54: Window load coefficient learning]
The window load coefficient learning unit 167 detects the room temperature Tz detected by the room temperature detection device 1111 of the indoor unit 111 of the air conditioner 11 and the surface temperature detection of the indoor unit 111 of the air conditioner 11 when it is determined that there is solar radiation in S51. The surface temperature Tg of the window glass detected by the device 1112, the outside air temperature Ta detected by the outside air temperature detection device 1121 of the outdoor unit 112 of the air conditioner 11, the indoor heat generation load Qin estimated by the indoor heat generation load estimation unit 160, The window load coefficient Hg is calculated from Equation 13 using the air conditioning capacity Qhvac estimated by the air conditioning capacity estimation unit 164 and the total heat loss coefficient KA stored in the total heat loss coefficient 176 of the storage device 17. To do. Equation 13 group can be derived from Equation 8 and Equation 9. Formula 13 group uses the upper stage during cooling and the lower stage during heating.

  Further, in the formula 13 group, the simultaneous heat equation may be calculated with the total heat loss coefficient KA and the window load coefficient Hg as unknowns, or regression analysis may be used. When the total heat loss coefficient KA is treated as an unknown, the window load coefficient Hg can be learned even if the step of learning the total heat loss coefficient theory in S53 is omitted.

  Furthermore, in the case of glass with good heat insulation performance, the window load coefficient Hg can be calculated from the group of formulas 14, and the window load coefficient Hg can be calculated even if the step of learning the window heat performance in S52 is omitted. Formula 14 group uses the upper stage during cooling and the lower stage during heating. The window load coefficient Hg is solar heat acquisition from the window glass to the room when the difference between the surface temperature Tg and the room temperature Tz of the window glass of the building 2 to be air-conditioned is 1 degree, and the unit is [W / K].

  In this way, the window load coefficient learning unit 167 learns the window load coefficient Hg of the window glass based on the air conditioning capability Qhvac, the room temperature Tz, the outside air temperature Ta, and the surface temperature Tg. The calculated window load coefficient Hg is stored in the window load coefficient 177 of the storage device 17. It should be noted that the room temperature Tz needs to be stable at a predetermined time interval (for example, selected from 30 minutes, 60 minutes, etc.) as a precondition for the expressions 13 and 14 to be satisfied, and the slope of the room temperature Tz and the room temperature Tz Whether or not the room temperature Tz is stable can be determined from variations and the like.

[S55: Solar heat load estimation]
In the solar heat load estimation unit 163, the window load coefficient Hg stored in the window load coefficient 177 of the storage device 17 calculated in S54, the heat flow resistance R of the window glass, and the inner surface heat transfer resistance Ri of the window glass Based on the room temperature Tz, the outside air temperature Ta, and the surface temperature Tg of the window glass, the solar heat load Qs is calculated using Equation 9 (S55). The solar heat load Qs can also be estimated using the set temperature Tset of the air conditioner 11 instead of the room temperature Tz.

  Next, the air-conditioning load estimation unit 166 becomes an air-conditioning target stored in the indoor heat generation load Qin estimated in S50, the solar heat load Qs estimated in S55, and the total heat loss coefficient 176 of the storage device 17. Based on the total heat loss coefficient KA of the building 2, the room temperature Tz, and the outside air temperature Ta, the air-conditioning load Q is estimated according to Formula 7 (S56).

  Finally, the control device 19 determines a control command for the air conditioning capability Qhvac of the air conditioner 11 based on the air conditioning load Q estimated in S56 (S57). Thereafter, the process returns to S50. The control command is not limited to the air conditioning capability Qhvac, and the command value of the blowout temperature of the air conditioner 11, the direction of the blowout, and the like can be controlled as the control command value. Therefore, the solar heat load by the solar radiation which penetrates into the living room in the building 2 from the window glass can be estimated with high accuracy in real time according to the environmental change.

  As described above, the room temperature detection unit for detecting the room temperature in the building, the outside air temperature detection unit for detecting the outside air temperature, the surface temperature detection unit for detecting the surface temperature inside the building of the window glass, the room temperature and the outside air temperature Window heat performance learning unit that learns the window heat performance of the window glass based on the surface temperature and the air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner, and the room temperature and the outside air temperature A window load coefficient learning unit that learns the window load coefficient of the window glass based on the surface temperature, the window thermal performance, and the air conditioning capability, and based on the room temperature, the outside air temperature, the surface temperature, the window thermal performance, and the window load coefficient An air conditioning system including a solar heat load estimating unit that estimates a solar heat load due to solar radiation incident from a window glass and a control unit that controls the air conditioner based on the solar heat load. This makes it possible to estimate the solar heat load of the building that is subject to air conditioning with high accuracy.

  Also, a room temperature detecting step for detecting the room temperature in the building, an outside air temperature detecting step for detecting the outside air temperature, a surface temperature detecting step for detecting the surface temperature inside the building of the window glass, the room temperature, the outside air temperature, and the surface temperature. Window heat performance learning step for learning the window heat performance of the window glass based on the above, an air conditioning capability estimation step for estimating the air conditioning capability based on the amount of heat generated from the air conditioner, the room temperature, the outside temperature, and the surface temperature A window load coefficient learning step for learning the window load coefficient of the window glass based on the window heat performance and the air conditioning capacity; and from the window glass based on the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the window load coefficient. An air conditioning method comprising a solar heat load estimating step for estimating a solar heat load due to incident solar radiation, and a control step for controlling the air conditioner based on the solar heat load. This makes it possible to estimate the solar heat load of the building that is subject to air conditioning with high accuracy.

  Moreover, since the surface temperature detection part is provided in the air conditioner, the solar heat load of the building subject to air conditioning can be estimated with high accuracy.

  In addition, a total heat loss coefficient learning unit that learns the total heat loss coefficient of the building based on room temperature, outside air temperature, and air conditioning capability, room temperature, outside air temperature, surface temperature, window heat performance, window load coefficient, and total heat loss An air conditioning load estimation unit that estimates an air conditioning load of a building based on a coefficient, and an air conditioning system that controls the air conditioner based on the air conditioning load. This makes it possible to estimate the solar heat load of the building that is subject to air conditioning with high accuracy.

Embodiment 4 FIG.
FIG. 12 is an example of a configuration diagram of an air-conditioning system according to Embodiment 4 of the present invention. Unlike Embodiment 3, Embodiment 4 does not determine whether there is solar radiation. In the third embodiment, the total heat loss coefficient KA, the window heat performance, and the window load coefficient Hg are learned in different steps in order to estimate the solar heat load Qs. The main difference is that the air conditioning load Q is estimated by learning the load coefficient Ha and the window load coefficient Hg. The window load coefficient Hg is a coefficient including the window heat performance, the window optical performance, and the window area Ag, and the outside air load coefficient Ha is a coefficient including the total heat loss coefficient KA and the window load coefficient Hg.

  More specifically, the arithmetic unit 16 includes a load coefficient learning unit 168 in addition to the indoor heat generation load estimation unit 160, the air conditioning capability estimation unit 164, the air conditioning load estimation unit 166, and the like similar to those of the third embodiment. It has. Further, the storage device 17 includes an outside air load coefficient 178 in addition to the window load coefficient 177 and the like.

  The air conditioning system 1 includes a room temperature detection device 1111 that detects the room temperature Tz of the building 2, a surface temperature detection device 1112 that detects the surface temperature Tg of the window glass, and an outside air temperature detection that detects the outside air temperature Ta outside the building 2. A device 1121, an input device 12 to which information from the outside is input, a calculation device 16 that performs various calculations, a storage device 17 that stores information of various detection devices and calculation results of the calculation device 16, and air conditioning It comprises a control device 19 for controlling the machine 11 and a communication path 18 for exchanging information between various devices.

  In a room where air conditioning is performed, when the room temperature Tz is stable (for example, the variation in the room temperature Tz is 0 degree) at a predetermined time interval (for example, selected from 30 minutes, 60 minutes, etc.). Is a heat balance equation of the fifteenth group. In addition, Formula 15 group can be derived from Formula 8 and Formula 9. When the heat balance equation of Equation 15 holds, the air temperature is based on the room temperature Tz, the outside air temperature Ta, the window glass surface temperature Tg, the outside air load coefficient Ha, the window load coefficient Hg, and the indoor heat generation load Qin. The harmony ability Qhvac can be obtained (Formula 15 group). In the formula 15 group, the upper stage is during cooling and the lower stage is during heating.

  In addition, it is ideal that the room temperature Tz is stable in a state where the variation in the room temperature Tz is 0 degree. For example, if the variation is ± 0.5 degrees and ± 1 degree, the error increases but the allowable range is reached. It can be handled that the room temperature Tz is stable.

(Processing flow)
FIG. 13 is an example of a processing flow of the air-conditioning system according to Embodiment 4 of the present invention. It is a processing flow implemented while the air conditioning system 1 is in operation. Comparing with the processing flow of the third embodiment (FIG. 11), the processing S60 related to the operation of estimating the indoor heat generation load Qin corresponds to S50, and the processing S63 for determining the air conditioning control command corresponds to S57. Embodiment 3 is a step of the 50th generation, and Embodiment 4 is a step of the 60th generation), and since it is the same processing, detailed description is omitted.

  In S60, the indoor heat generation load estimation unit 160 estimates the indoor heat generation load Qin, and the process proceeds to S61.

[S61: Load coefficient learning]
In the load coefficient learning unit 168, the room temperature Tz detected by the room temperature detection device 1111 of the indoor unit 111 of the air conditioner 11, and the surface temperature Tg of the window glass detected by the surface temperature detection device 1112 of the indoor unit 111 of the air conditioner 11 The outside air temperature Ta detected by the outside air temperature detection device 1121 of the outdoor unit 112 of the air conditioner 11, the air conditioning capacity Qhvac estimated by the air conditioning capacity estimation unit 164, and the indoor heat generation estimated by the indoor heat generation load estimation unit 160. Using the load Qin, the outside air load coefficient Ha and the window load coefficient Hg are learned from the equation 16 group. In the equation 16 group, the outdoor air load coefficient Ha and the window load coefficient Hg may be calculated as unknowns and a simultaneous equation may be established, or regression analysis may be used. In Formula 16, the upper stage is used during cooling, and the lower stage is used during heating.

[S62: Air conditioning load estimation]
In the air conditioning load estimation unit 166, the room heat generation load Qin estimated in S60, the outside air load coefficient Ha and the window load coefficient Hg learned in S61, and the room temperature detection device 1111 of the indoor unit 111 of the air conditioner 11 detected. Tz, the surface temperature Tg of the window glass detected by the surface temperature detecting device 1112 of the indoor unit 111 of the air conditioner 11, and the outside temperature Ta detected by the outside air temperature detecting device 1121 of the outdoor unit 112 of the air conditioner 11 Based on the group of formulas 16, the air conditioning load Q is estimated (S62). However, the upper stage of Formula 16 group is used during cooling, and the lower stage of Formula 16 group is used during heating.

  Finally, the control device 19 controls the air conditioner 11 based on the air conditioning control command estimated in S63. Thereafter, the process returns to S60.

  As described above, from the room temperature detection unit that detects the room temperature in the building, the outside air temperature detection unit that detects the outside air temperature, the surface temperature detection unit that detects the surface temperature inside the building of the window glass, and the air conditioner An air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated, and a load factor learning that learns the window load coefficient and the outside air load coefficient of the window glass based on room temperature, outside air temperature, surface temperature, and air conditioning capability Air conditioning load estimation unit for estimating the air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient, and the control for controlling the air conditioner based on the air conditioning load It is an air conditioning system provided with a part.

  Also, a room temperature detecting step for detecting the room temperature in the building, an outside air temperature detecting step for detecting the outside air temperature, a surface temperature detecting step for detecting the surface temperature inside the building of the window glass, and the amount of heat generated from the air conditioner An air conditioning capability estimation step for estimating the air conditioning capability based on the following: a load factor learning step for learning the window load coefficient and the outside air load coefficient of the window glass based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning capability; An air conditioning load estimation step for estimating the air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient, and a control step for controlling the air conditioner based on the air conditioning load. An air conditioning method provided.

  An air conditioning system and an air conditioning method for estimating an indoor air conditioning load and controlling an air conditioner can be obtained.

  Finally, the present invention is not limited to the embodiments described so far, and can be variously modified within the scope of the present invention. That is, the configuration of the embodiment described so far may be improved as appropriate, and at least a part of the configuration may be replaced with another configuration. Further, the configuration requirements that are not particularly limited with respect to the arrangement are not limited to the arrangement disclosed in the embodiment, and can be arranged at a position where the function can be achieved. Further, the invention may be formed by appropriately combining a plurality of constituent elements disclosed in the embodiments described so far. Further, the present invention is shown not by the scope of the embodiments described so far but by the scope of the claims, and includes all modifications within the meaning and scope equivalent to the scope of the claims.

DESCRIPTION OF SYMBOLS 1 Air conditioning system, 2 buildings, 3 walls, 4 windows, 5 floors, 11 air conditioner, 12 input device, 13 room temperature detection device, 14 outside air temperature detection device, 15 surface temperature detection device, 16 arithmetic device, 17 storage device , 18 communication path, 19 control device, 111 indoor unit, 112 outdoor unit, 160 indoor heat generation load estimation unit, 161 window thermal performance learning unit, 162 window optical performance learning unit, 163 solar heat load estimation unit, 164 air conditioning capability estimation Part, 165 total heat loss coefficient learning part, 166 air conditioning load estimation part, 167 window load coefficient learning part, 168 load coefficient learning part, 171 unit solar radiation amount by region, 172 window optical performance relational expression, 173 window area, 174 windows Thermal performance, 175 window optical performance, 176 total heat loss coefficient, 177 window load coefficient, 178 outside air load coefficient, 1111 room temperature detector, 11 2 surface temperature detector, 1121 outside air temperature detection device.

Claims (11)

A room temperature detector for detecting the room temperature in the building;
An outside air temperature detector for detecting outside air temperature,
A surface temperature detector for detecting the surface temperature of the window glass inside the building;
A window heat performance learning unit that learns the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
An air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner;
A window load coefficient learning unit that learns a window load coefficient of the window glass based on the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the air conditioning capability;
A solar heat load estimating unit for estimating a solar heat load due to solar radiation incident from the window glass based on the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the window load coefficient;
An air conditioning system comprising: a control unit that controls the air conditioner based on the solar heat load. The air conditioning system according to claim 1,
A total heat loss coefficient learning unit that learns a total heat loss coefficient of the building based on the room temperature, the outside air temperature, and the air conditioning capability;
An air conditioning load estimator for estimating an air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window heat performance, the window load coefficient, and the total heat loss coefficient;
An air conditioning system comprising: a control unit that controls the air conditioner based on the air conditioning load. A room temperature detector for detecting the room temperature in the building;
An outside air temperature detector for detecting outside air temperature,
A surface temperature detector for detecting the surface temperature of the window glass inside the building;
An air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner;
A load coefficient learning unit that learns a window load coefficient and an outside air load coefficient of the window glass based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning capability;
An air conditioning load estimator for estimating an air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient;
An air conditioning system comprising: a control unit that controls the air conditioner based on the air conditioning load. A room temperature detector for detecting the room temperature in the building;
An outside air temperature detector for detecting outside air temperature,
A surface temperature detector for detecting the surface temperature of the window glass inside the building;
A window heat performance learning unit that learns the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
Window optical performance learning unit that learns the window optical performance of the window glass based on the unit solar radiation amount and the window optical performance relational expression based on the configuration of the window glass, the room temperature, the outside air temperature, the surface temperature, and the window thermal performance When,
A solar heat load estimating unit for estimating a solar heat load due to solar radiation incident from the window glass based on the area of the window glass, the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the window optical performance; ,
An air conditioning system comprising: a control unit that controls the air conditioner based on the solar heat load. The air conditioning system according to claim 4,
The window thermal performance is a performance based on heat flow resistance,
The window optical performance is a performance based on a solar radiation absorption rate and a solar heat acquisition rate. The air conditioning system according to claim 4 or 5, wherein
An air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner;
A total heat loss coefficient learning unit that learns a total heat loss coefficient of the building based on the room temperature, the outside air temperature, and the air conditioning capability;
An air-conditioning load estimation unit that estimates the air-conditioning load of the building based on the room temperature, the outside air temperature, the total heat loss coefficient, and the solar heat load,
The said control part controls the said air conditioner based on the said air conditioning load, The air conditioning system characterized by the above-mentioned. It is an air conditioning system of any one of Claim 2, Claim 3, and Claim 6, Comprising:
The air conditioning system is characterized in that the air conditioning load is estimated based on an indoor heat generation load. The air conditioning system according to any one of claims 1 to 7,
The air temperature system is characterized in that the surface temperature detector is provided in the air conditioner. A room temperature detection step for detecting the room temperature in the building;
An outside air temperature detecting step for detecting the outside air temperature;
A surface temperature detecting step for detecting a surface temperature inside the building of the window glass;
A window heat performance learning step of learning the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
An air conditioning capability estimation step for estimating the air conditioning capability based on the amount of heat generated from the air conditioner;
A window load coefficient learning step of learning a window load coefficient of the window glass based on the room temperature, the outside air temperature, the surface temperature, the window thermal performance, and the air conditioning capability;
A solar heat load estimating step for estimating a solar heat load due to solar radiation incident from the window glass based on the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the window load coefficient;
And a control step of controlling the air conditioner based on the solar heat load. A room temperature detection step for detecting the room temperature in the building;
An outside air temperature detecting step for detecting the outside air temperature;
A surface temperature detecting step for detecting a surface temperature inside the building of the window glass;
An air conditioning capability estimation step for estimating the air conditioning capability based on the amount of heat generated from the air conditioner;
A load coefficient learning step of learning a window load coefficient and an outside air load coefficient of the window glass based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning capability;
An air conditioning load estimation step of estimating an air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient;
An air conditioning method comprising: a control step of controlling the air conditioner based on the air conditioning load. A room temperature detection step for detecting the room temperature in the building;
An outside air temperature detecting step for detecting the outside air temperature;
A surface temperature detecting step for detecting a surface temperature inside the building of the window glass;
A window heat performance learning step of learning the window heat performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
A window optical performance learning step for learning the window optical performance of the window glass based on the unit solar radiation amount and the window optical performance relational expression based on the configuration of the window glass, the room temperature, the outside air temperature, the surface temperature, and the window heat performance. When,
A solar heat load estimating step for estimating a solar heat load caused by solar radiation incident from the window glass based on the area of the window glass, the room temperature, the outside air temperature, the surface temperature, the window heat performance, and the window optical performance; ,
And a control step of controlling the air conditioner based on the solar heat load.

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