WO2019035218A1

WO2019035218A1 - Air conditioning system and air conditioning method

Info

Publication number: WO2019035218A1
Application number: PCT/JP2017/036589
Authority: WO
Inventors: アンナ成; 隆也山本; 恵美竹田; 淳一岡崎
Original assignee: 三菱電機株式会社
Priority date: 2017-08-17
Filing date: 2017-10-10
Publication date: 2019-02-21
Also published as: CN110914605A; JPWO2019035218A1; CN110914605B; JP6727446B2

Abstract

An air conditioning system (1) comprising: a room temperature detection unit (13) that detects room temperature inside a building (2); an outside air temperature detection unit (14) that detects outside air temperature; a surface temperature detection unit (15) that detects surface temperature of window glass, on the inside of the building (2); an air conditioning capacity estimation unit (164) that estimates air conditioning capacity on the basis of the amount of heat generated from an air conditioner (11); a load coefficient learning unit (168) that learns a window load coefficient for the window glass and an outside air load coefficient, on the basis of the room temperature, the outside air temperature, the surface temperature, and the air conditioning capacity; an air conditioning load estimation unit (166) that estimates the air conditioning load for the building (2) on the basis of the room temperature, the outside air temperature, the surface temperature, the window load coefficient, and the outside air load coefficient; and a control unit that controls the air conditioner (11) on the basis of the air conditioning load.

Description

Air conditioning system and air conditioning method

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 a house, an office building and the like. For this reason, it is required to reduce useless energy due to overcooling and overheating of the room. In order to perform control without excess or deficiency of the amount of heat supplied from the air conditioning system, the heat load in the room to be air conditioned was estimated in real time using data from the air conditioner, other devices, etc. It is necessary to properly adjust the air conditioning control amount according to the heat load.

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

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

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

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

Patent document 1: JP 2008-107910 JP, 2011-202877, A Japanese Patent Application Publication No. 2015-218991

According to the method of Patent Document 1, it is necessary to input the construction area, the season, the time, the 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, it is not possible to estimate the solar radiation heat load intruding from the window glass in real time in a real environment.

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

Furthermore, according to the method of Patent Document 3, it is necessary to install a light transmitting organic thin film solar cell on each window surface. The light transmitting organic thin film solar cells are currently in the research and development stage, and the light transmitting organic thin film solar cells for being installed in the windows are not widely used yet and are not practical.

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

The air conditioning system according to the present invention comprises 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, and a surface temperature detection unit that detects a surface temperature inside a building of a window glass A window thermal performance learning unit that learns the window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature, and an air conditioning capability estimation unit that estimates the air conditioning capability based on the heat quantity generated from the air conditioner; Window load factor learning unit that learns window load factor of window glass based on room temperature, ambient temperature, surface temperature, window thermal performance and air conditioning ability, room temperature, ambient temperature, surface temperature, window thermal performance and window load factor And a control unit for controlling an air conditioner based on the solar heat load, and a solar heat load estimation unit for estimating a solar heat load due to solar radiation incident from the window glass on the basis of the control unit.

The air conditioning system according to the present invention comprises 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, and a surface temperature detection unit that detects a surface temperature inside a building of a window glass The air conditioning ability estimation unit estimates the air conditioning ability based on the heat generated from the air conditioner, and learns the window load factor and the external air load factor of the window glass based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning ability Load factor learning section, an air conditioning load estimation section for estimating the air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load factor and the outside air loading factor, and the air conditioner based on the air conditioning load And a control unit that controls the air conditioning system.

The air conditioning system according to the present invention comprises 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, and a surface temperature detection unit that detects a surface temperature inside a building of a window glass Window thermal performance learning unit to learn window thermal performance of window glass based on room temperature, outside air temperature and surface temperature, window optical performance relational expression by unit solar radiation and window glass configuration, room temperature, outside air temperature and surface temperature Window optical performance learning section to learn window optical performance of window glass based on window thermal performance, and from window glass based on window glass area, room temperature, ambient temperature, surface temperature, window thermal performance and window optical performance It is an air conditioning system provided with a solar radiation heat load estimating part which presumes solar radiation heat load by incidence solar radiation, and a control part which controls an air harmony machine based on solar radiation heat load.

An air conditioning method according to the present invention comprises: a room temperature detection step of detecting a room temperature in a building; an outside air temperature detection step of detecting an outside air temperature; and a surface temperature detection step of detecting a surface temperature inside a building of a window glass; A window thermal performance learning step of learning window thermal performance of the window glass based on the room temperature, the outside air temperature and the surface temperature, and an air conditioning ability estimation step of estimating the air conditioning ability based on the heat quantity generated from the air conditioner; Window load factor learning step to learn window load factor of window glass based on room temperature, ambient temperature, surface temperature, window thermal performance and air conditioning ability, room temperature, ambient temperature, surface temperature, window thermal performance and window load factor Air conditioning method comprising a solar heat load estimation step of estimating a solar heat load due to solar radiation incident from a window glass based on the above and a control step of controlling an air conditioner based on the solar heat load It is.

An air conditioning method according to the present invention comprises: a room temperature detection step of detecting a room temperature in a building; an outside air temperature detection step of detecting an outside air temperature; and a surface temperature detection step of detecting a surface temperature inside a building of a window glass; The air conditioning ability estimation step of estimating the air conditioning ability based on the heat quantity generated from the air conditioner, and learning the window load factor and the outdoor air load factor of the window glass based on the room temperature, the outside air temperature, the surface temperature and the air conditioning ability Load factor learning step, 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 factor and the outside air loading factor, an air conditioner based on the air conditioning load And a control step of controlling the air conditioning method.

An air conditioning method according to the present invention comprises: a room temperature detection step of detecting a room temperature in a building; an outside air temperature detection step of detecting an outside air temperature; and a surface temperature detection step of detecting a surface temperature inside a building of a window glass; Window thermal performance learning step of learning window thermal performance of window glass based on room temperature, ambient temperature and surface temperature, window optical performance relational expression by unit solar radiation amount and configuration of window glass, room temperature, ambient temperature and surface temperature Window optical performance learning step to learn window optical performance of window glass based on window thermal performance and from window glass based on window glass area, room temperature, ambient temperature, surface temperature, window thermal performance and window optical performance It is an air conditioning method provided with the control step of controlling the air conditioner based on the solar radiation heat load estimation step which estimates the solar radiation heat load by the incident solar radiation, and the solar radiation heat load.

According to this invention, the air which controls the indoor solar heat load or the air conditioning load and controls the air conditioner without providing a dedicated detecting device for detecting the amount of solar radiation or the light transmitting organic thin film solar cell Harmonized systems and air conditioning methods can be obtained.

BRIEF DESCRIPTION OF THE DRAWINGS It is a perspective view for demonstrating the inside example of the building where 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 chart by the presence or absence of the solar radiation by Embodiment 1 of this invention. It is an example of the thermal image and the photograph of the room by Embodiment 1 of the present invention. It is an example of the figure which shows the relationship between the solar radiation absorptivity a of the window glass and the solar radiation heat acquisition rate eta by Embodiment 1 of this invention. 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. 1 is a perspective view for explaining an example of the interior of a building 2 to which an air conditioning system according to a first embodiment of the present invention is applied. The building 2 shows 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 windows 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. In addition, the air conditioner 11 is not limited to a wall hanging type, The apparatus which adjusts indoor air, such as a ceiling cassette type and a duct connection type, can be used as the air conditioner 11.

FIG. 2 is an example of the block diagram of the air conditioning system by Embodiment 1 of this 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 for detecting a room temperature Tz of the building 2, and an outside air temperature Ta outside the building 2. An external air temperature detection device 14, a surface temperature detection device 15 for detecting the surface temperature Tg of the window glass, an arithmetic device 16 for performing various calculations, a memory for storing information of the various detection devices and calculation results of the arithmetic device 16 It comprises an apparatus 17, an input device 12 to which information from the outside is input, a control device 19 for controlling the air conditioner 11, and a communication path 18 for exchanging information between various devices.

The surface temperature detection device 15 is a thermal image sensor (infrared temperature sensor) installed in the room, a thermo camera or the like, and installed so as to detect the surface temperature Tg of the window glass inside the building 2 to be air conditioned. Do. In the following description, the term “surface temperature” refers to the surface temperature Tg of the window glass inside the building 2 unless otherwise specified. In addition, the arithmetic unit 16 includes a window thermal performance learning unit 161, a window optical performance learning unit 162, and a solar radiation heat load estimation unit 163, and specifically, is a CPU.

The storage unit 17 is composed of regional unit solar radiation amount 171, window optical performance relational expression 172, window area 173, window thermal performance 174, window optical performance 175, etc. Specifically, it is a storage medium such as a hard disk or RAM. . The communication path 18 is for communication that connects 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. It is a network of The type of cable, the communication protocol, and the like of the communication path 18 are not particularly limited. Further, the control device 19 determines a control command for the air conditioner 11 based on the solar radiation heat load estimated value via the communication path 18.

FIG. 3 is an example of a process flow of the air conditioning system according to Embodiment 1 of the present invention. Each step will be described below.

[S11: solar radiation presence / absence judgment]
In S11, it is determined whether or not there is solar radiation. Thereafter, when there is solar radiation, the process proceeds to S13, and when there is no solar radiation, the process proceeds to S12. The example of the judgment method of the presence or absence of solar radiation is shown below.

In order to learn the window thermal performance 174, it is necessary to use data when there is no influence of solar radiation. When the surface of the window glass is exposed to direct sunlight, 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 with and without solar radiation according to Embodiment 1 of the present invention. More specifically, it is a figure showing the temperature gradient of the outside temperature Ta, the surface temperature Tg of the window glass, and the room temperature Tz depending on the presence or absence of solar radiation in summer and winter. When the upper stage is without solar radiation, when the lower stage is with solar radiation, the left side shows the case where the cooling operation is performed in summer, and the right side shows the case where the heating operation is performed in winter. Further, Ta indicates the outside air temperature Ta, Tz the room temperature, Tg the surface temperature Tg on the indoor side of the window 4, the upper side indicates that the temperature is high, and the lower side indicates that the temperature is low. Furthermore, when there is solar radiation at the bottom, the 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 It is determined that there is solar radiation when the surface temperature Tg of the window glass is higher than Tz and the surface temperature Tg of the window glass is higher than the outside temperature Ta (the upper stage of the formula 1 group). Moreover, when the time in operation of the air conditioning system 1 is known, the data at night can be used as the data of the no solar radiation condition. When there is no solar radiation, the temperature rises in the order of the room temperature Tz, the surface temperature Tg of the window glass, and the outside air temperature Ta at the time of cooling in summer (the middle row of the formula 1 group). On the other hand, when there is no solar radiation, the temperature rises in the order of the outside temperature Ta, the surface temperature Tg of the window glass, and the room temperature Tz at the time of heating in winter (the lower part of Formula 1 group).

FIG. 5 is an example of a thermal image and a photograph of the room according to the first embodiment of the present invention. The thermal image of the state of the lower photograph is in the upper row. Fig. 5 shows the experimental installation brought into a real house, and a plurality of columns are installed. Moreover, the right side of FIG. 5 is a curtain, and the left back is a radiation panel. Here, it can be seen that the position of the window 4 can be detected even when using a race curtain, a blind or the like. Thus, by regarding the surface temperature of the lace curtain, the blind or the like at the position of the window 4 as the surface temperature Tg of the window glass, it is possible to determine the presence or absence of solar radiation.

[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, in the window thermal performance learning unit 161, the heat penetration resistance R of the window glass is calculated using the data when it is determined that there is no solar radiation in S11. The window thermal performance is not limited to the heat penetration resistance R, but may include performance based on the thermal resistance.

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

[S13: absorbed solar radiation amount estimation]
The solar heat load estimation unit 163 uses the data when it is determined that there is solar radiation in S11 to estimate the solar radiation amount Iα absorbed by the window glass according to Equation 3 (S13).

[S14: Window optical performance learning]
The window optical performance learning unit 162 calculates the solar radiation absorptivity α of the window glass and the solar radiation heat acquisition rate η. The window optical performance is not limited to the solar radiation absorptivity α and the solar radiation heat acquisition rate η, but may include other performances related to solar radiation. The regional unit 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, and in the case where the storage device 17 has a timer function, the date of the timer is used.

First, the solar radiation absorptivity α of the window glass is calculated from the equation 4 using the absorbed solar radiation amount calculated using the equation 3 group and the unit solar radiation amount Ir in order to obtain the solar radiation absorptance α. In Equation 4, the unit solar radiation Ir is 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 of detection of Tg. The regional unit 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 also be used.

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

FIG. 6 is an example of a diagram showing the relationship between the solar radiation absorptance rate α and the solar radiation heat gain rate による according to Embodiment 1 of the present invention. More specifically, the solar radiation absorptance α is taken on the horizontal axis, and the solar radiation heat acquisition rate η is taken on the vertical axis, and the relationship between the two is approximated by a linear first-order equation. In addition, the relationship between the solar radiation absorptivity a and the solar radiation heat acquisition rate η is not limited to the approximation method by the linear first-order equation, and the approximate equation shown in FIG. 6 is merely an example.

The window glass shown in FIG. 6 uses window glass of many types and thicknesses as follows. The window glass is different in the heat transmission resistance R, the solar radiation absorptivity α and the solar radiation heat acquisition rate η depending on the type, and the window optical performance 175 is different.
Single sheet glass: transparent sheet glass, heat ray absorbing sheet glass, heat ray reflective glass, laminated glass: glass to which two pieces of single sheet glass are adhered by an adhesive (transparent sheet glass + transparent sheet glass, heat ray absorbing sheet glass + transparent sheet glass, heat ray reflective glass + transparent Flat glass)
-Double-layered glass: Glass composed of two single sheet glass having a hollow layer (transparent sheet glass + hollow layer + transparent sheet glass, heat absorbing glass sheet + hollow layer + transparent sheet glass, heat reflecting glass + hollow layer + transparent sheet glass)
9 types of glass, and the thickness of one sheet of glass contains glass from 3 mm to 8 mm.

The solar heat absorptivity 当てはめ is calculated by applying the solar absorptivity a calculated by the equation 4 to the relational expression with the solar heat acquistion rate η shown in FIG. In addition, the relational expression of the solar radiation absorptivity a and the solar radiation heat acquisition rate eta can be changed by the change and addition of a structure of a window glass. In addition, before learning the window optical performance 175, an equation 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 is based on the unit solar radiation amount and the window optical performance relation equation 172 by the configuration of the window glass, the room temperature Tz, the outside temperature Ta, the surface temperature Tg, and the window thermal performance. The optical performance is learned (S14).

[S15: solar radiation heat load estimation]
In the solar heat load estimation unit 163, based on the absorbed solar radiation amount Iα of the window glass estimated in S13, the solar radiation absorptivity α of the window glass stored in the window optical performance 175 of the storage device 17, and the solar radiation heat acquisition rate η. The solar heat load Qs is estimated using Equation 5 (S15). In addition, in Formula 5, Ag represents the area of a window glass. As the window area Ag, for example, a window area value input from an input device, a window area value estimated from a surface temperature detection apparatus, 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.

When representing the input conditions in another form, the solar radiation heat load estimation unit 163 is incident from the window glass based on the window area 173, the room temperature Tz, the outside temperature Ta, the surface temperature Tg, the window thermal performance 174, and the window optical performance 175. It is to estimate the solar radiation heat load due to the solar radiation.

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

Note that the control command is not limited to the air conditioning capability Qhvac, and a command value of the air outlet temperature of the air conditioner, the direction of the air outlet, etc. can also be controlled as a 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 window thermal performance of window glass based on temperature and surface temperature, window optical performance relational expression by unit solar radiation amount and configuration of window glass, room temperature, outside air temperature, surface temperature and window thermal performance By the window optical performance learning unit to learn the window optical performance of the window glass based on the area of the window glass, room temperature, ambient temperature, surface temperature, window thermal performance and window optical performance, and by solar radiation incident from the window glass It is an air conditioning system provided with a solar radiation heat load estimation part which presumes solar radiation heat load, and a control part which controls an air conditioner based on solar radiation heat load.

In addition, a room temperature detection step for detecting the room temperature in the building, an outside air temperature detection step for detecting the outside air temperature, a surface temperature detection step for detecting the surface temperature inside the building of the window glass, room temperature, outside air temperature and surface temperature And the window thermal performance learning step of learning the window thermal performance of the window glass, the window optical performance relational expression by the unit solar radiation amount and the configuration of the window glass, and based on the room temperature, the outside air temperature, the surface temperature and the window thermal performance. Solar thermal load due to solar radiation incident from the window glass based on the window optical performance learning step of learning the window optical performance of the window glass, the area of the window glass, room temperature, ambient temperature, surface temperature, window thermal performance and window optical performance And a control step of controlling the air conditioner based on the solar heat load.

For this reason, an air conditioning system and an air conditioning method for controlling an air conditioner by estimating the indoor solar heat load without providing a dedicated detecting device for detecting the amount of solar radiation and a light transmitting organic thin film solar cell You can get it.

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 absorptivity α and the solar heat gain coefficient 取得. For this reason, the air conditioning system can estimate the solar radiation heat load of the building to be air conditioned with high accuracy.

Second Embodiment
FIG. 7 is an example of the block diagram of the air conditioning system by Embodiment 2 of this invention. The differences from Embodiment 1 are as follows.

First, the functions of the air conditioner 11 are finely divided. Specifically, the indoor unit 111 of the air conditioner 11 is provided with a room temperature detection device 1111 for detecting the room temperature Tz of the building 2 and a surface temperature detection device 1112 for detecting the surface temperature Tg inside the building of the window glass. Also, the outdoor unit 112 is provided with an outside air temperature detection device 1121 that detects the outside air temperature Ta outside the building 2.

The room temperature detection device 1111 replaces the room temperature detection device 13 of the first embodiment. The surface temperature detection device 1112 is an alternative to the surface temperature detection device 15 of the first embodiment. Furthermore, the outside air temperature detection device 1121 replaces the outside air temperature detection device 14 of the first embodiment. It does not matter whether it is provided as a function of the air conditioner 11 or separately provided as long as it has the same function. The same is true for the other embodiments.

Next, the difference from Embodiment 1 is that the indoor heat generation load estimation unit 160, the air conditioning ability estimation unit 164, the total heat loss coefficient learning unit 165, and the air conditioning load estimation unit 166 The difference is that the storage device 17 is additionally provided with a total heat loss coefficient 176 that stores the total heat loss coefficient KA.

In the drawings, the same reference numerals are assigned to the same or corresponding parts, which is common to the whole text of the specification and all the drawings. Furthermore, the form of the component which appears in the whole specification is only an illustration and is not limited to these descriptions.

FIG. 8 is an example of the external view of the air conditioner 11 according to Embodiment 2 of the present invention. The air conditioner 11 is an example of the wall-mounted indoor unit 111, and the indoor unit 111 including the room temperature detection device 1111 and the surface temperature detection device 1112 and the outdoor unit 112 including the outside air temperature detection device 1121 Connect and air-condition the room. When the air conditioner 11 includes a remote controller, the remote controller can be used as the input device 12.

Further, an arithmetic device 16 for performing various calculations, a storage device 17 for storing information of various detection devices and calculation results of the arithmetic device 16, an input device 12 to which information from the outside is input, 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 process flow of the air conditioning system according to Embodiment 2 of the present invention. It is an example of the processing flow implemented while the air conditioning system 1 is in operation. The process relating to the operation of estimating the solar heat load is the same as that of the first embodiment. Specifically, S31 corresponds to S11, S32 to S12, S34 to S13, S35 to S14, S36 to S15, and S38 to S16 (the tenth step in the first embodiment) The second embodiment is the step of No. 30), and is the same processing, so detailed description will be omitted.

[S30: Indoor heat load estimation]
In S30, the indoor heat generation load estimation unit 160 estimates the room heat generation load Qin, for example, when there is a person in the building 2 (living room), or when a heat generator such as a light or a television is turned on. The indoor heat generation load Qin is a total of one due to human body heat generation (human body heat load), one due to illumination heat generation (lighting load), and one due to tool heat generation (device heat load). The indoor heat generation load Qin increases the load at the time of cooling and reduces the load at the time of heating.

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

Further, the indoor heat generation load Qin is not limited to estimation using the sum of the respective heat generation amounts, and 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 And can also be determined using regression analysis. Thus, the method of determining the indoor heat generation load Qin is not limited to a specific method. If there is no person corresponding to indoor heat generation in the building 2 (living room) or if the device that generates heat such as lighting is off, etc., and the indoor heat generation is 0, then the indoor heat generation load Qin is 0. Do.

At S31, it is determined whether or not there is solar radiation. Thereafter, when there is no solar radiation, the process proceeds to S32, and when 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. Then, it progresses to S33.

On the other hand, in S34, the solar heat load estimation unit 163 estimates the amount Iα of solar radiation absorbed by the window glass, using the 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 Ir and the window optical performance relational expression by the configuration of the window glass, the room temperature Tz, the outside temperature Ta, the surface temperature Tg, and the window thermal performance 174. Is learned (S35). Thereafter, in the solar heat load estimation unit 163, the solar radiation incident from the window glass based on the window area Ag, the room temperature Tz, the outside temperature Ta, the surface temperature Tg, the window thermal performance (S32) and the window optical performance (S35) The solar heat load Qs is estimated (S36), and the process proceeds to S37 and S38, and 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 that there is no solar radiation in S31 Using the outside air temperature Ta detected by the outside air temperature detection device 1121 of the air conditioner 112 and the indoor heat generation load Qin estimated by the indoor heat generation load estimation unit 160 with the air conditioning ability Qhvac and S30, the total heat loss coefficient KA is Learn (S33). However, at the time of cooling, the indoor heat generation load Qin is positive by using the upper stage of the equation group 6, and at the time of heating, the indoor heat generation load Qin is negative by using the lower stage of the equation group 6.

When the indoor heat generation load Qin is treated as a predetermined coefficient, the step of estimating the indoor heat generation load Qin in the indoor heat generation load estimation unit 160 in S30 is omitted, and the total heat loss coefficient KA and the indoor heat generation are calculated from The load Qin can also be learned by regression analysis. The learning of the window thermal performance 174 in S32 and the learning of the total heat loss coefficient KA in S33 may be performed in any order.

Here, although the method of estimating the indoor heat generation load Qin is shown, the air conditioner 11 can also be controlled without considering the indoor heat generation load Qin. For example, it may be considered that the influence of the indoor heat generation load Qin on solar radiation is considered to be small. In this case, the term of the indoor heat generation load Qin may be treated as zero in an expression such as expression 6 group. The same applies to the third and fourth embodiments 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 flow that flows into the living room from the wall 3 or the window 4 or flows out from the living room to the wall 3 or the window 4 when the temperature difference between the inside and outside of the building 2 (living room) targeted for air conditioning is one degree. The sum of heat transfer by heat and ventilation, and the unit is [W / K].

The air conditioning capacity Qhvac is a value obtained by estimating the amount of heat supplied from the air conditioner 11 at the time of heating by the air conditioning capacity estimation unit 164 and the amount of heat removed by the air conditioner 11 at the time of cooling. In the following description, the air conditioning capacity Qhvac indicates the amount of heat supplied during heating and indicates 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 equation of the air conditioning capacity 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 suction and blow can also be used. Thus, the way of obtaining 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 equation 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 predetermined time intervals (for example, selected from 30 minutes, 60 minutes, etc.), the variation of the room temperature Tz, and the like.

[S37: Air conditioning load estimation]
After the solar heat load Qs is estimated in S36 and the total heat loss coefficient KA is learned in S33, the indoor heat load Qin estimated in S30 and the solar heat load Qs estimated in S36 are calculated by the air conditioning load estimation unit 166. Air conditioning using the equation 7 group based on the total heat loss coefficient KA of the building 2 to be air conditioned stored in the total heat loss coefficient 176 of the storage device 17, the room temperature Tz, and the outside air temperature Ta The load Q is estimated (S37). In the expression 7 group, the cooling time is on the upper side, and the heating time is on the lower side.

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

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

Further, since the surface temperature detection unit is provided in the air conditioner, it is possible to estimate the solar heat load of the building to be subjected to the air conditioning with high accuracy.

Furthermore, an air conditioning ability estimation unit that estimates the air conditioning ability 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 the room temperature, the outside air temperature, and the air conditioning ability. The learning unit includes an air conditioning load estimating 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 the air conditioning based on the air conditioning load. Since the aircraft is controlled, the solar radiation heat load of the building to be air-conditioned can be estimated with high accuracy.

Third Embodiment
FIG. 10 is an example of the block diagram of the air conditioning system by Embodiment 3 of this invention. A major difference between the second embodiment and the second embodiment is that the window thermal performance and the window optical performance are not learned separately to estimate the solar heat load Qs, but the window glass surface temperature Tg and the solar heat load Qs are different. The correlation coefficient is learned, and the solar radiation heat load Qs is estimated from the surface temperature Tg of the window glass. The window load coefficient Hg is a coefficient including the window thermal performance, the window optical performance, and the window area Ag.

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

The air conditioning system 1 includes a room temperature detection device 1111 for detecting the room temperature Tz of the building 2, a surface temperature detection device 1112 for detecting the surface temperature Tg of the window glass, and an outside air temperature detection for detecting the outside air temperature Ta outside the building 2. A device 1121, an input device 12 to which external information is input, an arithmetic device 16 for performing various calculations, a storage device 17 for storing information of various detection devices and calculation results of the arithmetic device 16, 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 when there is solar radiation, room temperature Tz is stable (for example, fluctuation of room temperature Tz is 0 degree) at predetermined time intervals (for example, selected from 30 minutes, 60 minutes, etc.). When this is the case, the heat balance equation of equation 8 holds. When the heat balance equation of equation 8 holds, it is possible to obtain the air conditioning ability Qhvac based on the total heat loss coefficient KA, the room temperature Tz, the outside temperature Ta, the solar heat load Qs, and the indoor heat generation load Qin. (Equation 8). In the equation (8), positive is selected by the solar heat load Qs and the indoor heat generation load Qin during cooling, and negative is selected by the solar heat load Qs and the indoor heat generation load Qin during heating.

In addition, the room temperature Tz is ideally stable if the fluctuation of the room temperature Tz is 0 degree ideally, but for example, if the fluctuation is ± 0.5 degree, ± 1 degree, the error also increases, but as an allowable range The room temperature Tz can also be treated as stable.

Equations 3 and 5 can lead to equation 9, and the solar heat load Qs can be estimated using equation 9. As shown in equation 9, the solar heat load Qs includes the window load coefficient Hg, the heat penetration resistance R of the window glass, the heat transfer resistance Ri of the inner surface of the window glass, the room temperature Tz, the outside temperature Ta, and the surface temperature Tg of the window glass. It can be expressed using. The right side of the upper equation 9 corresponds to the window load coefficient Hg. As described above, the window load coefficient Hg can be expressed by the heat transmission resistance R, the inner surface heat transfer resistance Ri, the solar radiation heat acquisition rate η, the solar radiation absorptivity 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 temperature Ta, and the amount of solar radiation Iα, the surface temperature Tg of the window glass can be calculated from Expression 10. In the equation (10), the influence by the solar radiation becomes the value of the third term, and the first and second terms are the influence of the room temperature Tz and the outside air temperature Ta. In the case of a window with good thermal insulation performance such as multiple glasses, the heat transmission 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 by using the equation 11 in which the second term is omitted, and the solar heat load Qs can be calculated by the equation 12.

(Processing flow)
FIG. 11 is an example of the process 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. As compared with the process flow of the second embodiment (FIG. 9), the process S50 related to the operation of estimating the indoor heat generation load Qin is S30, and the process related to the operation of learning the total heat loss coefficient KA is S51 is S31, Step S53 is a step corresponding to step S33, and is the same processing as that of step S33. Further, the process S52 for learning the window thermal performance is a step corresponding to S32, the process S56 for estimating the air conditioning load Q is a process corresponding to S37, and the process for determining an air conditioning control command S57 is a step corresponding to S38. Therefore, the detailed description is omitted (the second embodiment is the step of No. 30 and the third embodiment is the step of No. 50).

The indoor heat generation load Qin is estimated in S50, and the process proceeds to S51. If there is no solar radiation in S51, the process proceeds to S52, and the window thermal performance learning unit 161 learns the window thermal performance of the window glass based on the room temperature Tz, the outside temperature Ta, and the surface temperature Tg of the window glass. Thereafter, the process proceeds to S53, and 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 ability estimation unit 164 can estimate the air conditioning ability Qhvac based on the heat quantity (heat quantity to be removed) generated from the air conditioner 11.

[S54: window load coefficient learning]
In the window load coefficient learning unit 167, 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 that there is solar radiation in S51, and the surface temperature detection of the indoor unit 111 of the air conditioner 11. 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, and the indoor heat generation load Qin estimated by the indoor heat generation load estimation unit 160 Using the air conditioning ability Qhvac estimated by the air conditioning ability estimation unit 164 and the total heat loss coefficient KA stored in the total heat loss coefficient 176 of the storage device 17, the window load coefficient Hg is calculated from the equation 13 group Do. The equation group 13 can be derived from the equations 8 and 9. In the equation group 13, the upper stage is used during cooling, and the lower stage is used during heating.

In addition, in the equation group 13, the total heat loss coefficient KA and the window load coefficient Hg may be set as unknowns to calculate simultaneous equations, 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 in S53 is omitted.

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

As described above, the window load coefficient learning unit 167 learns the window load coefficient Hg of the window glass based on the air conditioning ability Qhvac, the room temperature Tz, the outside temperature Ta, and the surface temperature Tg. The calculated window load factor Hg is stored in the window load factor 177 of the storage unit 17. The room temperature Tz needs to be stabilized at a predetermined time interval (for example, selected from 30 minutes, 60 minutes, etc.) as a precondition for the

equations

13 and 14 to hold, 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 the variation or the like.

[S55: solar radiation heat load estimation]
In the solar heat load estimation unit 163, the window load factor Hg stored in the window load factor 177 of the storage device 17 calculated in S54, the heat penetration 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 the equation 9 (S55). Also, the solar heat load Qs can be estimated using the set temperature Tset of the air conditioner 11 instead of the room temperature Tz.

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

Finally, the control device 19 determines a control command of the air conditioning ability Qhvac of the air conditioner 11 based on the air conditioning load Q estimated in S56 (S57). Then, it returns to S50. The control command is not limited to the air conditioning capability Qhvac, and a command value of the blowout temperature of the air conditioner 11, a direction of the blowout, or the like may be controlled as a control command value. Therefore, it is possible to estimate in real time the solar radiation heat load due to the solar radiation entering the room in the building 2 from the window glass with high accuracy according to the change of the environment.

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 air conditioning capability estimation unit that estimates the air conditioning capability based on the amount of heat generated from the air conditioner; And a window load factor learning unit that learns the window load factor of window glass based on surface temperature, window thermal performance and air conditioning ability, and based on room temperature, ambient temperature, surface temperature, window thermal performance and window load factor It is an air conditioning system provided with a solar radiation heat load estimating part which presumes solar radiation heat load by solar radiation which enters from a window glass, and a control part which controls an air harmony machine based on solar radiation heat load. By this, the solar radiation heat load of the building which is the object of air conditioning can be estimated with high accuracy.

In addition, a room temperature detection step for detecting the room temperature in the building, an outside air temperature detection step for detecting the outside air temperature, a surface temperature detection step for detecting the surface temperature inside the building of the window glass, room temperature, outside air temperature and surface temperature Window thermal performance learning step of learning the window thermal performance of the window glass based on the air conditioning capability estimation step of estimating the air conditioning capability based on the heat quantity generated from the air conditioner, room temperature, outside air temperature and surface temperature And window load factor learning step to learn window load factor of window glass based on window thermal performance and air conditioning ability, and from window glass based on room temperature, ambient temperature, surface temperature, window thermal performance and window load factor It is an air conditioning method provided with the control step of controlling the air conditioner based on the solar radiation heat load estimation step which estimates the solar radiation heat load by the incident solar radiation, and the solar radiation heat load. By this, the solar radiation heat load of the building which is the object of air conditioning can be estimated with high accuracy.

Furthermore, a total heat loss coefficient learning unit that learns the total heat loss coefficient of the building based on the room temperature, the outside air temperature, and the air conditioning ability, the room temperature, the outside air temperature, the surface temperature, the window thermal performance, the window load coefficient, and the total heat loss The air conditioning load estimation unit estimates a building air conditioning load based on the coefficients, and the air conditioning system controls an air conditioner based on the air conditioning load. By this, the solar radiation heat load of the building which is the object of air conditioning can be estimated with high accuracy.

Fourth Embodiment
FIG. 12 is an example of the block diagram of the air conditioning system by Embodiment 4 of this invention. Unlike the third embodiment, the fourth embodiment does not judge the presence or absence of solar radiation. Further, in the third embodiment, in order to estimate the solar heat load Qs, the total heat loss coefficient KA, the window thermal performance, and the window load coefficient Hg are learned in separate steps, but the fourth embodiment is the outside air. The main difference is that the air conditioning load Q is estimated by learning the load factor Ha and the window load factor Hg. The window load coefficient Hg is a coefficient including the window thermal 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, in addition to the indoor heat generation load estimation unit 160, the air conditioning ability estimation unit 164, the air conditioning load estimation unit 166, etc., which are the same as those of the third embodiment, the load coefficient learning unit 168 Is equipped. In addition to the window load factor 177 and the like, the storage device 17 is provided with an outside air load factor 178.

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

(Processing flow)
FIG. 13 is an example of the process 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. As compared 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. The third embodiment is the 50th step, and the fourth embodiment is the 60th step), and the process is the same as that of the fourth embodiment.

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 factor 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 ability Qhvac estimated by the air conditioning ability estimation unit 164, and the indoor heat generation estimated by the indoor heat generation load estimation unit 160 The outdoor air load coefficient Ha and the window load coefficient Hg are learned from the equation 16 group using the load Qin. In the equation 16 group, the external air load coefficient Ha and the window load coefficient Hg may be set as unknowns to calculate simultaneous equations, or regression analysis may be used. In the equation group 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 heating load Qin estimated in S60, the outdoor air load coefficient Ha and the window load coefficient Hg learned in S61, and the room temperature detected by the room temperature detection device 1111 of the indoor unit 111 of the air conditioner 11. Tz, 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, and the outside temperature Ta detected by the outside air temperature detection device 1121 of the outdoor unit 112 of the air conditioner 11. Based on the equation (16), the air conditioning load Q is estimated (S62). However, at the time of cooling, the upper stage of the equation 16 group is used, and at the time of heating, the lower stage of the equation 16 group is used.

Finally, the control device 19 controls the air conditioner 11 based on the air conditioning control command estimated in S63. Then, it 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 ability estimation unit that estimates the air conditioning ability based on the generated heat amount, and a load factor learning that learns the window load factor and the outdoor air load factor of the window glass based on room temperature, ambient temperature, surface temperature, and air conditioning ability Control unit for controlling the air conditioner based on the air conditioning load, the air conditioning load estimating 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 factor and the outside air loading factor An air conditioning system comprising:

In addition, a room temperature detection step for detecting the room temperature in the building, an outside air temperature detection step for detecting the outside air temperature, a surface temperature detection step for detecting the surface temperature of the window glass inside the building, and heat quantity generated from the air conditioner An air conditioning ability estimating step of estimating the air conditioning ability based on the load factor learning step of learning a window load factor and an outside air load factor of the window glass based on the room temperature, the outside air temperature, the surface temperature and the air conditioning ability; Air conditioning load estimation step of 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 loading coefficient, and a control step of controlling the air conditioner based on the air conditioning load. It is an air conditioning method provided.

It is possible to obtain an air conditioning system and an air conditioning method for controlling an air conditioner by estimating an air conditioning load in a room.

Finally, the present invention is not limited to the embodiments described above, and can be variously modified within the scope of the present invention. That is, the configuration of the embodiment described so far may be appropriately improved, and at least a part may be replaced with another configuration. Furthermore, the configuration requirements without particular limitation on 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. In addition, the invention may be formed by appropriately combining a plurality of components disclosed in the embodiments described above. Furthermore, the present invention is not the scope of the embodiments described above, is shown by the claims, and includes all modifications within the meaning and scope equivalent to the claims.

DESCRIPTION OF SYMBOLS 1 air conditioning system, 2 buildings, 3 walls, 4 windows, 5 floors, 11 air conditioners, 12 input devices, 13 room temperature detection devices, 14 outside air temperature detection devices, 15 surface temperature detection devices, 16 arithmetic devices, 17 storage devices , 18 communication path, 19 control device, 111 indoor unit, 112 outdoor unit, 160 indoor heat generation load estimation unit, 161 window heat performance learning unit, 162 window optical performance learning unit, 163 solar heat load estimation unit, 164 air conditioning ability estimation Part, 165 total heat loss coefficient learning part, 166 air conditioning load estimation part, 167 window load factor learning part, 168 load factor learning part, 171 unit solar radiation amount by area, 172 window optical performance relational expression, 173 window area, 174 window Thermal performance, 175 window optical performance, 176 total heat loss coefficient, 177 window load coefficient, 178 outside air load coefficient, 111 Room temperature detector, 1112 a surface temperature detecting device 1121 outside air temperature detection device.

Claims

A room temperature detection unit for detecting the room temperature in the building;
An outside temperature detection unit that detects the outside temperature,
A surface temperature detection unit that detects a surface temperature of the inside of the building of the window glass;
A window thermal performance learning unit that learns the window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
An air conditioning capability estimation unit configured to estimate an air conditioning capability based on a heat quantity 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 thermal performance, and the air conditioning ability;
A solar heat load estimation unit configured to estimate 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 thermal performance, and the window load coefficient;
And a control unit configured to control the air conditioner based on the solar radiation heat load.
An air conditioning system according to claim 1, wherein
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 ability;
An air conditioning load estimation unit that estimates an air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window thermal performance, the window load coefficient, and the total heat loss coefficient;
And a control unit configured to control the air conditioner based on the air conditioning load.
A room temperature detection unit for detecting the room temperature in the building;
An outside temperature detection unit that detects the outside temperature,
A surface temperature detection unit that detects a surface temperature of the inside of the building of the window glass;
An air conditioning capability estimation unit configured to estimate an air conditioning capability based on a heat quantity generated from the air conditioner;
A load coefficient learning unit that learns 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 ability;
An air conditioning load estimation unit for estimating an air conditioning load of the building based on the room temperature, the outside air temperature, the surface temperature, the window load factor, and the outside air load factor;
And a control unit configured to control the air conditioner based on the air conditioning load.
A room temperature detection unit for detecting the room temperature in the building;
An outside temperature detection unit that detects the outside temperature,
A surface temperature detection unit that detects a surface temperature of the inside of the building of the window glass;
A window thermal performance learning unit that learns the window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
Window optical performance learning unit which learns the window optical performance of the window glass based on the unit solar radiation amount and the window optical performance relational expression by 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 estimation 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 ambient temperature, the surface temperature, the window thermal performance, and the window optical performance ,
And a control unit configured to control the air conditioner based on the solar radiation heat load.
An air conditioning system according to claim 4, wherein
The window thermal performance is a performance based on heat transmission resistance,
The air conditioning system characterized in that the window optical performance is a performance based on a solar radiation absorptivity and a solar heat gain rate.
An air conditioning system according to claim 4 or claim 5, wherein
An air conditioning capability estimation unit configured to estimate an 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 ability;
An air conditioning load estimation unit configured to estimate an air conditioning load of the building based on the room temperature, the outside air temperature, the total heat loss coefficient, and the solar radiation heat load;
An air conditioning system, wherein the control unit controls the air conditioner based on the air conditioning load.
An air conditioning system according to any one of claims 2, 3 and 6.
The air conditioning system, wherein 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, wherein
An air conditioning system, wherein the surface temperature detection unit is provided in the air conditioner.
A room temperature detection step of detecting the room temperature in the building;
Outside temperature detection step to detect outside temperature,
A surface temperature detection step of detecting the surface temperature of the inside of the building of the window glass;
A window thermal performance learning step of learning window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
An air conditioning capability estimation step of estimating the air conditioning capability based on the heat quantity generated from the air conditioner;
A window load factor learning step of learning a window load factor of the window glass based on the room temperature, the outside air temperature, the surface temperature, the window thermal performance, and the air conditioning ability;
A solar heat load estimation step of 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 thermal performance, and the window load coefficient;
A control step of controlling the air conditioner on the basis of the solar heat load.
A room temperature detection step of detecting the room temperature in the building;
Outside temperature detection step to detect outside temperature,
A surface temperature detection step of detecting the surface temperature of the inside of the building of the window glass;
An air conditioning capability estimation step of estimating the air conditioning capability based on the heat quantity generated from the air conditioner;
A load factor learning step of learning a window load factor of the window glass and an external air load factor based on the room temperature, the outside air temperature, the surface temperature, and the air conditioning ability;
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 factor, and the outside air load factor;
A control step of controlling the air conditioner based on the air conditioning load.
A room temperature detection step of detecting the room temperature in the building;
Outside temperature detection step to detect outside temperature,
A surface temperature detection step of detecting the surface temperature of the inside of the building of the window glass;
A window thermal performance learning step of learning window thermal performance of the window glass based on the room temperature, the outside air temperature, and the surface temperature;
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 by 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 estimation step of 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 ambient temperature, the surface temperature, the window thermal performance, and the window optical performance; ,
A control step of controlling an air conditioner based on the solar radiation heat load.