Control system, air conditioning system, control method, and program

Abstract

Provided is a technique for performing air conditioning while taking into consideration the thermal insulation performance of a space. The control system is provided with: an evaluation unit that predicts an indoor temperature in a space that will be reached, as a result of air conditioning by the air conditioner, when a first predetermined time has elapsed, and evaluates the effect of the air conditioning with respect to the space in accordance with the indoor temperature; and a control unit that corrects a target temperature set by a user and performs air conditioning, on the basis of the evaluation.

Description

Control system, air conditioning system, control method and program

[0001] The present disclosure relates to a control system, an air conditioning system, a control method, and a program. This disclosure claims priority based on Japanese Patent Application No. 2024-065218 filed on April 15, 2024, the contents of which are incorporated herein by reference.

[0002] In a house with high insulation performance, cooling can result in excessive cooling, and heating can result in excessive heating. Excessive cooling and heating can also lead to wasted electricity consumption. Patent Document 1 discloses an air conditioner control method that takes into account the effect on indoor temperature of the amount of heat flowing into the room through the exterior walls, by estimating the amount of heat flowing into the room based on indoor temperature data and outside air temperature data from a predetermined time ago, and correcting the air conditioning set temperature based on the estimated amount of heat.

[0003] Japanese Patent Application Laid-Open No. 2021-050851

[0004] There is a need for technology that can curb excessive cooling and heating by taking into account the effects of air conditioning, such as the insulation performance of a home.

[0005] The present disclosure provides a control system, an air conditioning system, a control method, and a program that can solve the above-mentioned problems.

[0006] According to one aspect of the present disclosure, the control system is a control system for controlling an air conditioner, and includes an evaluation unit that predicts the indoor temperature that the indoor temperature of a space will reach after a first predetermined time has elapsed through air conditioning by the air conditioner, and evaluates the effect of the air conditioning on the space based on the indoor temperature, and a control unit that corrects the target temperature set by the user based on the evaluation and performs air conditioning.

[0007] According to one aspect of the present disclosure, an air conditioning system includes the above-described control system and an air conditioner controlled by the control system.

[0008] According to one aspect of the present disclosure, the control method is a control method for an air conditioner, which predicts the indoor temperature that the indoor temperature of a space will reach after a first predetermined time has elapsed through air conditioning by the air conditioner, evaluates the effect of the air conditioning on the space based on the indoor temperature, and corrects a target temperature set by a user based on the evaluation to perform air conditioning.

[0009] According to one aspect of the present disclosure, the program causes a computer to function as a means for predicting the indoor temperature that a space will reach after a first predetermined time has elapsed through air conditioning by an air conditioner, evaluating the effect of the air conditioning on the space based on the indoor temperature, and correcting the target temperature set by the user based on the evaluation to perform air conditioning.

[0010] According to the above-described control system, air conditioning system, control method, and program, excessive cooling and heating can be suppressed by performing air conditioning taking into consideration the insulation performance of the house, etc.

[0011] FIG. 1 is a diagram illustrating an example of an air conditioning system in a first embodiment. FIG. 2 is a first diagram illustrating an example of a room temperature prediction model in the first embodiment. FIG. 3 is a second diagram illustrating an example of a room temperature prediction model in the first embodiment. FIG. 4 is a diagram illustrating processing in the first embodiment. FIG. 5 is a flowchart illustrating an example of insulation evaluation processing and target temperature correction processing in the first embodiment. FIG. 6 is a flowchart illustrating an example of air conditioning control in the first embodiment. FIG. 7 is a diagram illustrating processing in a second embodiment. FIG. 8 is a diagram illustrating an example of the hardware configuration of an air conditioning system in each embodiment.

[0012] First Embodiment Hereinafter, air conditioning control according to a first embodiment of the present disclosure will be described with reference to FIGS. 1 to 5. FIG.

[0013] (Configuration of Air Conditioning System) FIG. 1 is a diagram illustrating an example of an air conditioning system according to a first embodiment. As shown in FIG. 1 , the air conditioning system 100 includes an air conditioner 1, a server 20, and a user terminal 30. The air conditioner 1 includes an outdoor air temperature sensor 2, an indoor temperature sensor 3, a compressor 4, and a control device 10. For example, the outdoor air temperature sensor 2 is provided in an outdoor unit (not shown), and the indoor temperature sensor 3 is provided in an indoor unit (not shown). However, the installation locations of the outdoor air temperature sensor 2 and the indoor temperature sensor 3 are not limited thereto. The outdoor air temperature sensor 2 and the indoor temperature sensor 3 are connected to the control device 10, and the control device 10 acquires the temperatures measured by the outdoor air temperature sensor 2 and the indoor temperature sensor 3. The compressor 4 is connected to the control device 10, and the control device 10 controls the compressor 4 and detects its operating state. For example, the control device 10 can operate the compressor 4 at a desired rotation speed and can also detect the rotation speed. The server 20 creates a room temperature prediction model 131 used to calculate the insulation performance of a house. The user terminal 30 is a smartphone or a remote control for the air conditioner owned by a user of the air conditioner 1. The user can set a target temperature for the room, give instructions to perform cooling or heating, etc. from the user terminal 30. The control device 10, the server 20, and the user terminal 30 are connected to each other so as to be able to communicate with each other via a network NW.

[0014] (Configuration of Control Device) The control device 10 includes a sensor information acquisition unit 11 , a setting reception unit 12 , a thermal insulation performance evaluation unit 13 , a target temperature correction unit 14 , a control unit 15 , and a communication unit 16 .

[0015] The sensor information acquisition unit 11 acquires the outdoor temperature measured by the outdoor temperature sensor 2 and the indoor temperature measured by the indoor temperature sensor 3 .

[0016] The setting receiving unit 12 receives settings such as a target temperature for a space to be air-conditioned in a house. The target temperature is set using a user terminal 30.

[0017] The insulation performance evaluation unit 13 includes a room temperature prediction model 131 and an insulation performance evaluation table 132. The insulation performance evaluation unit 13 evaluates the insulation performance of the air-conditioned space by performing a benchmark using the room temperature prediction model 131, and converts the evaluation result into an evaluation value by referring to the insulation performance evaluation table 132. The target temperature correction unit 14 includes a target temperature correction table 141. The target temperature correction unit 14 corrects the target temperature set by the user based on the target temperature correction table 141 and the evaluation result of the insulation performance, and sets the corrected target temperature as the internal target temperature.

[0018] The control unit 15 performs air conditioning by controlling the compressor 4 etc. The control unit 15 performs cooling operation or heating operation, with the internal target temperature set by the target temperature correction unit 14 as the target.

[0019] The communication unit 16 communicates with the server 20 and the user terminal 30. For example, the communication unit 16 transmits to the server 20 the outdoor air temperature and indoor temperature acquired by the sensor information acquisition unit 11, the rotation speed of the compressor 4 detected by the control unit 15, and the internal target temperature set by the target temperature correction unit 14 as learning data required to create the room temperature prediction model 131. The communication unit 16 acquires the room temperature prediction model 131 and the like from the server 20. The communication unit 16 acquires the target temperature setting and the like transmitted from the user terminal 30.

[0020] (Configuration of the Server) The server 20 comprises a room temperature prediction model creation unit 21 and a communication unit 22. The room temperature prediction model creation unit 21 creates a room temperature prediction model 131 for predicting the time required for the indoor temperature of the air-conditioned space to reach the target temperature. The room temperature prediction model 131 is based on the indoor temperature (K), the outdoor temperature (K), and the air conditioning capacity (W / m ２ ) is input, a prediction model is created that outputs the future indoor temperature. An example of the room temperature prediction model 131 is shown in FIG.

[0021] (Room Temperature Prediction Model) The ARX model (Auto-Regressive with eXogenous model) shown in FIG. 2A predicts the room temperature T ｉｎ (k) and the outside air temperature T ｏ (k) from the indoor temperature T ｉｎThe deviation T obtained by subtracting (k) ｏ―ｉｎ (k) and air conditioning capacity φ ｈ 2 is a linear multiple regression model showing the relationship between (k) and (k). When the ARX model in FIG. 2 is rearranged, the following equation (1) is obtained.

[0022] T ｉｎ (k) = a １ T ｉｎ (k-1)+a ２ T ｉｎ (k-2)+...+a ｍ T ｉｎ (km) + b １１ φ ｈ (k-1)+b １２ φ ｈ (k-2)+...+b １ｍ φ ｈ (km) + b ２１ T ｏ―ｉｎ (k-1)+b ２２ T ｏ―ｉｎ (k-2)+...+b ２ｍ T ｏ―ｉｎ (km-m)+w ０ ...(1)

[0023] The room temperature prediction model creation unit 21 calculates the coefficient a of the formula (1) using past operation data of the air conditioner 1, that is, the outdoor air temperature measured by the outdoor air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the rotation speed of the compressor 4 instructed by the control unit 15, which are collected at predetermined intervals during a predetermined period in the past. １ , a ２ , ..., a ｍ , b １１ , b １２ , ..., b １ｍ , b ２１ , b ２２ , ..., b ２ｍ and the bias term w, which is a constant representing noise and disturbances. ０ The step length m can be set to any design value. The rotation speed of the compressor 4 is calculated using the following formulas (2) to (4) to calculate the air conditioning capacity (W / m ２ ) can be converted to

[0024] Outside temperature T Ｏ is the non-frost temperature range (T Ｏ ≦-7℃, 5.5℃<TＯ ) in the case of φ ｈ (T Ｏ )=φ(-7)+(φ(7)-φ(-7)÷(7-(-7)))×(T Ｏ -(-7)) ... (2)

[0025] Outside temperature T Ｏ When φ is in the frost temperature range (-7℃<T0≦5.5℃) ｈ (T Ｏ )=φ(-7)+(φ(2)-φ(-7)÷(2-(-7)))×(T Ｏ -(-7)) (3) where φ(-7), φ(2), and φ(7) are the air conditioning capacities at outside temperatures of -7°C, 2°C, and 7°C, respectively.

[0026] If the rotation speed of the compressor 4 is ncmp, and K1, K2, and K3 are predetermined constants, the relationship between ncmp and φ(-7), φ(2), and φ(7) is as follows. K1, K2, and K3 are determined based on the results of performance tests. φ(7) = K1 × ncmp, φ(2) = K2 × ncmp, φ(-7) = K3 × ncmp... (4)

[0027] The room temperature prediction model creation unit 21 converts the rotation speed of the compressor 4 into φ(−7), φ(2), and φ(7) using equation (4), and calculates the outdoor air temperature T Ｏ By using the formula (2) or (3) according to the air conditioning capacity φ ｈ (T Ｏ The above formulas (2) to (4) are formulas for calculating the air conditioning capacity during heating, but the same procedure is used for cooling, where the rotation speed of the compressor 4 is converted into the air conditioning capacity φ ｈ (T Ｏ ) can be converted to

[0028] For example, the room temperature prediction model creation unit 21 may use a coefficient a that minimizes the square of the difference (RMSE: Root Mean Squared Error) between the actual indoor temperature measurement value included in the operation data of the air conditioner 1 and the predicted indoor temperature value obtained by substituting the actual indoor temperature measurement value included in the operation data, the outdoor air temperature measurement value, and the rotation speed of the compressor 4 into equation (1). １Alternatively, due to multicollinearity between explanatory variables, the least squares method may be used to calculate the appropriate coefficient a １ In cases where values ​​such as the coefficient a cannot be calculated or where overfitting occurs, ridge regression is used. １ If the matrix of input data is X, the matrix of output data is Y, and the matrix of coefficients is W, the least squares method is Ｔ X) －１ X Ｔ The coefficient W is calculated using Y, but ridge regression uses the unit matrix I to calculate W = (X Ｔ X-dI) －１ X Ｔ The coefficient W is calculated using Y. The coefficient a is calculated using ridge regression. １ When calculating the above, the room temperature prediction model creation unit 21 appropriately sets the step length m and the ridge regression parameter d, and calculates the coefficient a １ For example, various values ​​are set for m and d, and the coefficient a is calculated for each combination of m and d. １ etc., and then, from among them, m and d that minimize the RMSE may be adopted. １ The method for calculating the coefficients a, b, c, and c etc. is not limited to the above, and any other method can be used. For the time-series data of the indoor temperature, outdoor temperature, and rotation speed of the compressor 4 used as learning data, it is preferable to use the operating data of the air conditioner 1 installed in the actual space to be air-conditioned, but this is not limited thereto, and for example, operating data of another air conditioner with equivalent capacity installed in a space with similar properties to the space to be air-conditioned may be used. The room temperature prediction model creation unit 21 calculates the coefficient a １ When the above is calculated, the calculated coefficient a １ etc. are applied to equation (1) to create a room temperature prediction model 131.

[0029] As an example, let us assume that the step length is m=1. In this case, rearranging the above equation (1) yields the following equation (1'): T ｉｎ (k+1)=a １ T ｉｎ (k) + b １１ φ ｈ (k) + b ２１ T Ｏ (k) + w ０...(1') Coefficient a of equation (1') １ etc. are a in formula (1) １ etc., for example, coefficient a １ If so, T in Eq. (1) ｏ－ｉｎ T Ｏ -T ｉｎ After replacing and rearranging, for example, (a １ -b ２１ ) to a １ T in formula (1') ｉｎ is the indoor temperature, φ ｈ is the heating capacity, T Ｏ is the outside temperature, w ０ is a bias term. According to equation (1'), the room temperature at the next control step k+1 can be obtained using the room temperature at a certain control step k. Equation (1') is an example of the room temperature prediction model 131.

[0030] The room temperature prediction model 131 may be constructed using, for example, machine learning or a neural network instead of the ARX model. For example, as shown in Fig. 2B, the room temperature prediction model creation unit 21 constructs, through learning using a neural network, a room temperature prediction model 131 based on the operation data of the air conditioner 1, which outputs the measured value of the room temperature at time t+1 included in the operation data when the room temperature prediction model creation unit 21 receives the measured value of the indoor temperature at time t included in the operation data, the measured value of the outdoor air temperature at time t, and the air conditioning capacity calculated from the rotation speed of the compressor 4 at time t.

[0031] The communication unit 22 communicates with the control device 10 and the like. For example, the communication unit 22 receives the indoor temperature, the outdoor temperature, the rotation speed of the compressor 4, etc. from the control device 10 and outputs these values ​​to the room temperature prediction model creation unit 21. The room temperature prediction model creation unit 21 stores and accumulates this data as learning data for calculating the coefficient a1, etc. The communication unit 22 transmits the room temperature prediction model 131 created by the room temperature prediction model creation unit 21 to the control device 10.

[0032] The user terminal 30 is a mobile terminal such as a smartphone owned by a user of the air conditioner 1, or a remote control for the air conditioner 1. The user operates the user terminal 30 to set the target temperature, operation mode, etc., and issue instructions to perform air conditioning. The user terminal 30 then transmits this setting information and instruction information to the control device 10 of the air conditioner 1.

[0033] 1 is an example. For example, the room temperature prediction model creation unit 21 may be provided in the control device 10.

[0034] (Insulation Evaluation and Correction of Target Temperature) Next, various processes of the air conditioning system 100 will be described with reference to FIG. 3. The insulation performance evaluation unit 13 uses the room temperature prediction model 131 to predict how long it will take for the room temperature to reach the target temperature under certain air conditioning conditions. For example, the insulation performance evaluation unit 13 uses a predetermined air conditioning capacity φ (W / m ２ ), a predetermined outside temperature T Ｏ (K), the predetermined indoor temperature T ｉｎ (t)(K) is input to the room temperature prediction model 131, and the room temperature T at time t+1 is calculated. ｉｎ Next, the heat insulation performance evaluation unit 13 predicts the air conditioning condition at time t+1, using a predetermined air conditioning capacity φ (W / m ２ ), a predetermined outside temperature T Ｏ (K), predicted indoor temperature T ｉｎ (t+1)(K) is input to the room temperature prediction model 131, and the room temperature T at time t+2 is calculated. ｉｎ The thermal insulation performance evaluation unit 13 predicts the indoor temperature T (t+2) at time t+n predicted by the room temperature prediction model 131. ｉｎThe above process is repeated until (t + n) reaches a predetermined target temperature, and the time required to reach the target temperature (target temperature arrival time) is calculated. The target temperature arrival time serves as a benchmark indicating the insulation performance and air conditioning effectiveness of the house. After calculating the target temperature arrival time, the insulation performance evaluation unit 13 refers to the insulation performance evaluation table 132 and evaluates the insulation performance of the house as high, medium, or low. The insulation performance evaluation unit 13 has an insulation performance evaluation table 132 in which the target temperature arrival time and the evaluation value of the insulation performance are registered in association with each other. For example, if the target temperature arrival time is 5 minutes or less, the insulation performance is high; if the target temperature arrival time is more than 5 minutes but less than 10 minutes, the insulation performance is medium; and if the target temperature arrival time is longer than 10 minutes, the insulation performance is low. If the target temperature arrival time calculated as the benchmark is 10 minutes, the insulation performance evaluation unit 13 evaluates the insulation performance of the house as medium. The evaluation value may be evaluated in more stages than the three stages of high, medium, and low, or may be set to be evaluated in two stages of high and low. The setting of the target temperature arrival time shown in FIG. 3 is also one example, and can be set arbitrarily. In calculating the target temperature arrival time, the air conditioning capacity at each time T+i (i=0 to n) is set to a predetermined air conditioning capacity φ (W / m ２ ) (constant), but for example, if the air conditioning conditions at time t+i are input to the room temperature prediction model 131 and the room temperature T ｉｎ When predicting (t+i+1), the predicted value of the indoor temperature at time t+i is T ｉｎ The air conditioning capacity may be changed based on the difference between (t+i) and the target temperature. For example, when the initial indoor temperature is 30° C. and the target temperature is 25° C., the air conditioning capacity φ ０ The air conditioning capacity φ(t+i) when the air conditioning progresses and the indoor temperature at time t+i reaches 26°C may be set smaller than the above, and input into room temperature prediction model 131 to calculate the time to reach the target temperature. For example, a table may be prepared that associates indoor temperatures, target temperatures (or the difference between the indoor temperature and the target temperature), and air conditioning capacity, and the air conditioning capacity φ(t+i) at time t+i may be set based on the indoor temperature and target temperature (or the difference between the indoor temperature and the target temperature) at time t+i.

[0035] Next, the target temperature correction unit 14 calculates a correction value for the target temperature according to the insulation performance of the house. The target temperature correction unit 14 has a target temperature correction table 141, as shown in FIG. 3. The target temperature correction table 141 has evaluation values ​​for insulation performance and correction values ​​for the target temperature set separately for cooling and heating. For example, for cooling, if the insulation performance is high, the correction value is set to +1.0°C; if the insulation performance is medium, the correction value is set to +0.5°C; and if the insulation performance is low, the correction value is set to 0°C. Similarly, for heating, if the insulation performance is high, the correction value is set to -1.0°C; if the insulation performance is medium, the correction value is set to -0.5°C; and if the insulation performance is low, the correction value is set to 0°C. The correction values ​​shown in FIG. 3 are merely examples and are not limited thereto; they can be set arbitrarily. For example, if the insulation performance is evaluated as medium, the target temperature correction unit 14 obtains a cooling correction value of +0.5°C and a heating correction value of -0.5°C from the target temperature correction table 141 and stores these values.

[0036] For example, a user sets a target temperature of 28°C and starts air conditioning. The target temperature correction unit 14 then corrects the user-set target temperature of 28°C to calculate the internal target temperature, and performs air conditioning operation using this temperature as the set temperature. In the above example, the user-set target temperature of 28°C is added with a cooling correction value of +0.5°C, and air conditioning is performed using a set temperature of 28.5°C. This prevents overcooling due to air conditioning. During air conditioning, cold air sinks and warm air rises. Therefore, a difference occurs between the indoor temperature recognized by the air conditioner and the temperature at the user's location. For example, if the air conditioner is installed above the room, the air conditioner recognizes the temperature of the air higher than the user's location as the indoor temperature during cooling. This can result in the air conditioner continuing air conditioning even though the target temperature has already been achieved at the user's height, resulting in overcooling in a highly insulated home. When heating, the air above the room warms, and the air conditioner recognizes that the set temperature has been reached, even though the air where people are located has not yet reached the set temperature. Therefore, in actual control, taking into account that the upper air warms first during heating operation, heating operation may be performed with a corrected target temperature Tα, which is calculated by adding a predetermined value to the target temperature set by the user. In such a case, if the home is highly insulated, heating operation with the corrected target temperature Tα as the target temperature may result in overheating. In contrast, according to this embodiment, the target temperature is corrected after evaluating the insulation of the air-conditioned space, thereby preventing overcooling during cooling operation and overheating during heating operation. As in the example of the target temperature Tα described above, air conditioners are provided that perform air conditioning by correcting the target temperature set by the user to compensate for the difference in indoor temperature between the user's location and the location where the air conditioner is installed. However, such air conditioners can also be combined with the control according to this embodiment that corrects the target temperature set by the user based on the insulation performance (in the above example, the target temperature set by the user is corrected during cooling operation, and the higher corrected target temperature Tα is corrected during heating operation).

[0037] When the target temperature correction unit 14 sets the internal target temperature, the control unit 15 controls the compressor and other components to perform cooling operation. If the user subsequently sets a target temperature of 26°C and starts cooling, the target temperature correction unit 14 sets the internal target temperature to 26.5°C. The control unit 15 performs cooling operation so that the temperature measured by the indoor temperature sensor 3 becomes 26.5°C. Time-series operating data during operation of the air conditioner 1 (including the indoor temperature measured by the indoor temperature sensor 3, the outdoor temperature measured by the outdoor temperature sensor 2, and the rotation speed of the compressor 4) is transmitted to the server 20 via the communication unit 16 and accumulated in the server 20 as learning data. The room temperature prediction model creation unit 21 then re-learns using the accumulated operating data at predetermined intervals or when a predetermined amount of operating data has been accumulated, and updates the room temperature prediction model 131. The updated room temperature prediction model 131 is transmitted to the control device 10 via the communication unit 22. The control device 10 receives the updated room temperature prediction model 131. The insulation performance evaluation unit 13 uses the updated room temperature prediction model 131 to evaluate the insulation performance of the home. For example, suppose a user uses only the air conditioner 1 for air conditioning in the summer and uses the air conditioner 1 in combination with another heating appliance for air conditioning in the winter. In such a case, it is desirable to obtain a benchmark in the summer using the room temperature prediction model 131 constructed based on operating data acquired from actual cooling operation in the home in the summer, and to perform insulation performance evaluation. In the winter, it is desirable to obtain a benchmark using the room temperature prediction model 131 constructed based on operating data collected in a situation where other heating appliances are also used, and to perform insulation performance evaluation (in this case, an evaluation of the air conditioning effect in the air-conditioned environment of the home taking into account not only the insulation performance of the home but also the use of other heating appliances). In the case of this home, for example, an evaluation such as low insulation performance in the summer and high insulation performance in the winter would be appropriate. However, if the room temperature prediction model 131 is used without updating, the insulation performance will be low even in the winter, which may result in overheating and increased power consumption.In contrast, by appropriately updating the room temperature prediction model 131 using operating data collected in the recent past, it is possible to obtain a room temperature prediction model 131 that reflects seasonality and the unique conditions of each home, and by using the appropriately updated room temperature prediction model 131, it is possible to accurately evaluate the insulation performance (air conditioning effectiveness performance) of the home.

[0038] (Operation) Next, the operation of the air conditioning system 100 according to the first embodiment will be described with reference to Figs. 4 and 5. Fig. 4 is a flowchart showing an example of the process of heat insulation evaluation and target temperature correction according to the embodiment. As a premise, the heat insulation performance evaluation unit 13 includes a heat insulation performance evaluation table 132, and stores air conditioning conditions (predetermined air conditioning capacity φ, predetermined outside air temperature T Ｏ , room temperature T ｉｎ The initial values ​​of the temperature (T a ) and the target indoor temperature (Ta) are also set in advance in the insulation performance evaluation unit 13. The target temperature correction unit 14 includes a target temperature correction table 141.

[0039] First, the room temperature prediction model creation unit 21 creates or updates the room temperature prediction model 131 (step S11). The room temperature prediction model creation unit 21 creates the room temperature prediction model 131 based on past operating data of the air conditioner 1, such as time-series indoor temperature, outdoor temperature, and rotation speed of the compressor 4, as well as the ARX model or neural network illustrated in Fig. 2A. The room temperature prediction model creation unit 21 transmits the created room temperature prediction model 131 to the control device 10 via the communication unit 22. In the control device 10, the insulation performance evaluation unit 13 acquires and stores the transmitted room temperature prediction model 131.

[0040] Next, the thermal insulation performance evaluation unit 13 executes a benchmark (step S12). The thermal insulation performance evaluation unit 13 inputs the room temperature prediction model 131 into the room temperature prediction model 131, and calculates the initial value T ｉｎ and the outside temperature T Ｏ and the air conditioning capacity φ, the indoor temperature after a predetermined time is predicted, and the predicted indoor temperature and the outdoor temperature T Ｏand the air conditioning capacity φ are input to the room temperature prediction model 131, and the indoor temperature after a predetermined time is predicted. By repeating this process, the target temperature arrival time until the predicted indoor temperature reaches the target indoor temperature Ta is predicted. The room temperature prediction model 131 is updated as appropriate, but the air conditioning conditions used for the benchmark are constant. This allows the target temperature arrival time to be obtained, indicating the latest insulation performance (air conditioning effectiveness performance) at any given time.

[0041] Next, the insulation performance evaluation unit 13 evaluates the insulation performance of the house based on the benchmark results and the insulation performance evaluation table 132 (step S13). The insulation performance evaluation unit 13 references the insulation performance evaluation table 132 to obtain an evaluation value of the insulation performance corresponding to the target temperature arrival time obtained by the benchmark in step S12. The insulation performance evaluation unit 13 outputs the evaluation value of the insulation performance (for example, high, medium, or low) to the target temperature correction unit 14.

[0042] Next, the target temperature correction unit 14 sets a correction value for the target temperature based on the evaluation value of the insulation performance and the target temperature correction table 141 (step S14). The target temperature correction unit 14 refers to the target temperature correction table 141, obtains the cooling correction value and the heating correction value corresponding to the evaluation value obtained in step S13, and stores these values.

[0043] The above process is performed, for example, when the room temperature prediction model 131 is created or updated (for example, every one to two weeks). The evaluation value of the insulation performance and the correction values ​​for cooling and heating are updated at that time and are held until the next time the room temperature prediction model 131 is updated.

[0044] Next, the flow of air conditioning control using the cooling and heating correction values ​​set in the above process will be described. FIG. 5 is a flowchart showing an example of air conditioning control in this embodiment. First, a user sets a target temperature and the like using the user terminal 30 and issues an instruction to start operation (step S21). In the control device 10, the control unit 15 acquires the target temperature and operation mode (cooling or heating) set by the user and an instruction to start operation via the communication unit 16. The control unit 15 outputs the target temperature and operation mode to the target temperature correction unit 14. The target temperature correction unit 14 corrects the target temperature set by the user using the correction value set in step S14 (step S22). For example, if the operation mode is cooling, the target temperature set by the user is 28°C, and the cooling correction value set in step S14 is +1.0°C, the internal target temperature is set to 29.0°C. The target temperature correction unit 14 outputs the corrected internal set temperature, which is the target temperature, to the control unit 15. The control unit 15 starts air conditioning with the internal set temperature set to 29.0°C (step S23). During operation of the air conditioner 1, the outdoor temperature sensor 2 and the indoor temperature sensor 3 transmit the measured temperatures to the control device 10. These temperatures are used to control the air conditioner 1, and are also transmitted to the server 20 by the communication unit 16 in association with time as learning data. The control unit 15 transmits time-series data on the rotation speed of the compressor 4 to the server 20 via the communication unit 16. In the server 20, the communication unit 22 acquires time-series data on the indoor temperature, outdoor temperature, and compressor rotation speed, and the room temperature prediction model creation unit 21 stores this operating data as learning data (step S24). Next, the user issues an instruction to end operation using the user terminal 30. The control unit 15 ends the air conditioning based on this instruction (step S25). Next, the room temperature prediction model creation unit 21 determines whether to update the room temperature prediction model (step S26). For example, if it is decided that the room temperature prediction model 131 is to be updated once every two weeks, the room temperature prediction model creation unit 21 determines that the room temperature prediction model 131 should be updated when two weeks have passed since the previous update. Alternatively, the room temperature prediction model creation unit 21 may determine that the room temperature prediction model 131 should be updated when the amount of accumulated operating data is equal to or greater than a threshold (for example, when X hours' worth of operating data has already been accumulated).If it is determined that the room temperature prediction model 131 should be updated (step S26; Yes), the process described with reference to Fig. 4 is executed (step S27). If the room temperature prediction model 131 should not be updated (step S26; No), the process of Fig. 5 is terminated.

[0045] (Effects) As described above, according to this embodiment, the air conditioning effectiveness of a home, such as insulation performance, is evaluated, and the set temperature is corrected according to the evaluation results. This makes it possible to prevent overcooling during cooling operation and overheating during heating operation. By suppressing excessive cooling or heating, air conditioning operation can be performed with low power consumption. According to this embodiment, even if the user does not know the insulation performance of the home, etc., it is possible to automatically evaluate the insulation performance (air conditioning effectiveness performance) and perform air conditioning according to the evaluation results, thereby reducing wasted power consumption due to overcooling or overheating without causing any trouble to the user.

[0046] Second Embodiment A second embodiment will be described with reference to Fig. 6. An air conditioning system 100A according to the second embodiment includes an insulation performance evaluation unit 13A instead of the insulation performance evaluation unit 13. The insulation performance evaluation unit 13A includes an insulation performance evaluation table 132A instead of the insulation performance evaluation table 132. Furthermore, the target temperature correction unit 14 includes a target temperature correction table 141A illustrated in Fig. 6 instead of the target temperature correction table 141. Unlike the first embodiment, in S13 of Fig. 4, instead of calculating the time until the target temperature is reached using the room temperature prediction model 131, the insulation performance evaluation unit 13A calculates the indoor temperature after a predetermined time has elapsed to evaluate the insulation performance of the house.

[0047] (Insulation Evaluation and Correction of Target Temperature) Next, various processes of the air conditioning system 100A in step S13 will be described with reference to FIG. 6. The control before step S13 is the same as in the first embodiment, and therefore description thereof will be omitted. The insulation performance evaluation unit 13 uses the room temperature prediction model 131 to predict the indoor temperature after a predetermined time has elapsed under certain air conditioning conditions. For example, the insulation performance evaluation unit 13 uses a predetermined air conditioning capacity φ (W / m ２ ), a predetermined outside temperature T Ｏ (K), the predetermined indoor temperature T ｉｎ(t)(K) is input to the room temperature prediction model 131, and the room temperature T at time t+1 is calculated. ｉｎ Next, the heat insulation performance evaluation unit 13 predicts the air conditioning condition at time t+1, using a predetermined air conditioning capacity φ (W / m ２ ), a predetermined outside temperature T Ｏ (K), predicted indoor temperature T ｉｎ (t+1)(K) is input to the room temperature prediction model 131, and the room temperature T at time t+2 is calculated. ｉｎ The insulation performance evaluation unit 13 predicts (t+2). The insulation performance evaluation unit 13 repeats the above process until a predetermined time has elapsed from time t, and calculates the indoor temperature at the predetermined time. The indoor temperature after the predetermined time elapses serves as a benchmark indicating the insulation performance and air conditioning effectiveness of the house. After calculating the indoor temperature after the predetermined time elapses, the insulation performance evaluation unit 13 refers to an insulation performance evaluation table 132A illustrated in FIG. 6 and evaluates the insulation performance of the house as high, medium, or low. The insulation performance evaluation unit 13 has an insulation performance evaluation table 132A, which stores the indoor temperature after the predetermined time elapses and the evaluation value of the insulation performance in association with each other. For example, if the indoor temperature after the predetermined time elapses is 27°C or less, the insulation performance is set to high; if the indoor temperature after the predetermined time elapses is higher than 27°C but lower than 29°C, the insulation performance is set to medium; and if the indoor temperature after the predetermined time elapses is higher than 29°C, the insulation performance is set to low.

[0048] The insulation performance evaluation table 132A illustrated in FIG. 6 is an example. For example, the values ​​of 27°C and 29°C in FIG. 6 may be set according to the outdoor air temperature and indoor temperature at the start of air conditioning. If the indoor temperature calculated as a benchmark after a predetermined time has elapsed is 28°C, the insulation performance evaluation unit 13A will evaluate the insulation performance of the house as medium. The evaluation value may be evaluated in more stages rather than in three stages of high, medium, and low, or may be set to be evaluated in two stages of high and low. The setting of the indoor temperature after the target predetermined time has elapsed shown in FIG. 6 is also an example and can be set arbitrarily. In calculating the indoor temperature after the predetermined time has elapsed, the air conditioning capacity at each time t+i (i=0 to n) is set to a predetermined air conditioning capacity φ (W / m ２) (constant), but for example, if the air conditioning conditions at time t+i are input to the room temperature prediction model 131 and the room temperature T ｉｎ When predicting (t+i+1), the predicted value of the indoor temperature at time t+i is T ｉｎ The air conditioning capacity may be changed based on the difference between (t+i) and the target temperature. For example, when the initial indoor temperature is 30° C. and the target temperature is 25° C., the air conditioning capacity φ ０ The air conditioning capacity φ(t+i) when the air conditioning progresses and the indoor temperature at time t+i reaches 26°C may be set smaller than this, input into room temperature prediction model 131, and the indoor temperature after a predetermined time has elapsed may be calculated. For example, a table may be prepared that associates indoor temperatures, target temperatures (or the difference between the indoor temperatures and the target temperatures), and air conditioning capacities, and the air conditioning capacity φ(t+i) at time t+i may be set based on the indoor temperature and target temperature (or the difference between the indoor temperature and the target temperature) at time t+i.

[0049] The control from S13 onward described above is the same as in the first embodiment, and therefore detailed description thereof will be omitted. The target temperature correction unit 14 references the target temperature correction table 141A to obtain cooling correction values ​​and heating correction values ​​corresponding to the evaluation values ​​obtained in step S13 of the second embodiment described above, and stores these values ​​(step S14). The target temperature correction table 141A contains evaluation values ​​of insulation performance and correction values ​​for the target temperature, separately for cooling and heating. For example, for cooling, if insulation performance is high, the correction value is set to +1.0°C; if insulation performance is medium, the correction value is set to 0°C; and if insulation performance is low, the correction value is set to -1.0°C. Similarly, for heating, if insulation performance is high, the correction value is set to -1.0°C; if insulation performance is medium, the correction value is set to 0°C; and if insulation performance is low, the correction value is set to +1.0°C.

[0050] (Effects) In the first embodiment, the calculation steps for the indoor temperature calculated by the room temperature prediction model 131 to reach the target temperature are carried out randomly, which poses a problem of not knowing the time required for the calculation. In addition, there is a problem that the calculation does not end under conditions where the calculation of the room temperature prediction model 131 does not converge. Generally, air conditioners have a control function that reduces the compressor rotation speed when the difference between the target temperature and the indoor temperature becomes small. If this control function is incorporated into the room temperature prediction model 131, the amount of change in the indoor temperature calculated by the room temperature prediction model 131 decreases as the indoor temperature calculated by the room temperature prediction model 131 approaches the target temperature, which makes the above problem more likely to occur. On the other hand, in the second embodiment, the evaluation standard for insulation performance is the indoor temperature after a predetermined time has elapsed, so the problem of not knowing the time required for the calculation does not arise. Furthermore, since the calculation result after the predetermined time has elapsed is used to evaluate the insulation performance, the problem of divergence in the calculation does not arise. Furthermore, when determining the evaluation value of the insulation performance evaluation table 132A, insulation performance can be evaluated based on the indoor temperature after the predetermined time has elapsed. This makes it possible to set an evaluation value that is more in line with the user's sensibilities than in the first embodiment.

[0051] FIG. 7 is a diagram showing an example of the hardware configuration of an air conditioning system according to an embodiment. The computer 900 includes a CPU 901, a main storage device 902, an auxiliary storage device 903, an input / output interface 904, and a communication interface 905. The control device 10, the server 20, and the user terminal 30 described above are implemented in the computer 900. The functions described above are stored in the auxiliary storage device 903 in the form of a program. The CPU 901 reads the program from the auxiliary storage device 903, loads it into the main storage device 902, and executes the above processing in accordance with the program. The CPU 901 allocates a storage area in the main storage device 902 in accordance with the program. The CPU 901 allocates a storage area in the auxiliary storage device 903 for storing data being processed in accordance with the program.

[0052] A program for implementing all or part of the functions of the control device 10, server 20, and user terminal 30 may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed to perform processing by each functional unit. The term "computer system" as used herein includes hardware such as an OS and peripheral devices. If a WWW system is used, the term "computer system" also includes the homepage provision environment (or display environment). A "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, as well as storage devices such as hard disks built into the computer system. If the program is distributed to the computer 900 via a communication line, the computer 900 may load the program into the main storage device 902 and execute the processing described above. The program may be for implementing part of the functions described above, or may be capable of implementing the functions described above in combination with a program already stored in the computer system.

[0053] As described above, several embodiments according to the present disclosure have been described. However, all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as the invention described in the claims and their equivalents. The control device 10 and / or server 20 are an example of a control system. Past operating data of the air conditioner 1 is an example of a performance value.

[0054] <Additional Notes> The control system, air conditioning system, control method, and program described in each embodiment can be understood, for example, as follows.

[0055] (1) A control system according to a first aspect includes an evaluation unit that predicts the time required for the temperature of a space to be air-conditioned to reach a predetermined target temperature from a predetermined initial temperature through air conditioning by an air conditioner, and evaluates the effect of air conditioning on the space based on the time, and a control unit that corrects the target temperature set by a user based on the evaluation result and performs air conditioning. This allows air conditioning to be performed taking into account the insulation properties of the space, and prevents excessive cooling or heating.

[0056] (2) A control system according to a second aspect is the control system of (1), further comprising a room temperature prediction model that, when inputting the indoor temperature, the outdoor temperature, and the air conditioning capacity of the air conditioner, predicts the indoor temperature after a predetermined time when the air conditioner is operated at the air conditioning capacity, wherein the evaluation unit inputs the predetermined initial temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predetermined initial temperature and the air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model to predict the indoor temperature after the predetermined time, and then inputs the predicted indoor temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predicted indoor temperature and the air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model, and further predicts the indoor temperature after the predetermined time, thereby predicting the time required for the indoor temperature of the space to change from the initial temperature to the predetermined target temperature. This makes it possible to calculate the time required to achieve the target temperature.

[0057] (3) A control system according to a third aspect includes an evaluation unit that predicts the indoor temperature that the temperature of a space to be air-conditioned will reach after a predetermined time has elapsed through air conditioning by an air conditioner, and evaluates the effect of air conditioning on the space based on the indoor temperature; and a control unit that corrects the target temperature set by the user based on the evaluation results and performs air conditioning. This allows air conditioning to be performed taking into account the insulation properties of the space, and prevents excessive cooling or heating. Furthermore, it prevents situations where the required calculation time is unknown or the calculation diverges. In addition, the evaluation unit can have an evaluation value that is in line with the user's sensibilities.

[0058] (4) A fourth aspect of the control system is the control system of (3), further comprising a room temperature prediction model that, when inputted with the indoor temperature, the outdoor temperature, and the air conditioning capacity of the air conditioner, predicts the indoor temperature after a predetermined time when the air conditioner is operated at the air conditioning capacity, wherein the evaluation unit inputs the predetermined initial temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predetermined initial temperature and the air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model to predict the indoor temperature after the predetermined time, and then inputs the predicted indoor temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predicted indoor temperature and the air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model, and further predicts the indoor temperature after the predetermined time. By repeating this process, the control system predicts the indoor temperature that the temperature of the space to be air-conditioned will reach after the predetermined time has elapsed. This makes it possible to calculate the indoor temperature after the predetermined time has elapsed.

[0059] (5) A control system according to a fifth aspect is the control system of any one of (1) to (4), further comprising a correction unit that corrects the target temperature set by the user based on the evaluation result, wherein the evaluation unit calculates an evaluation value of the air conditioning effectiveness, and when the evaluation value is equal to or greater than a threshold value indicating a high air conditioning effectiveness, the correction unit corrects the target temperature set by the user to a higher value for cooling and a lower value for heating. This prevents excessive cooling during cooling operation and excessive heating during heating operation, enabling air conditioning with low power consumption.

[0060] (6) A sixth aspect of the control system is the control system of (5), wherein the correction unit includes a table that associates the evaluation value with a correction value for the target temperature setting for cooling or heating. This allows calculation of a correction value for the target temperature setting according to the effect of air conditioning.

[0061] (7) A seventh aspect of the control system is the control system of any one of (1) to (6), wherein the evaluation unit includes a table that associates the evaluation value with the time required to reach the target temperature, thereby enabling calculation of an evaluation value of the air conditioning effect in the space.

[0062] (8) The control system according to an eighth aspect is the control system of any one of (2), (4) to (7), further comprising a room temperature prediction model learning unit that accumulates time-series data of actual values ​​of indoor temperature, actual values ​​of outdoor temperature, and actual values ​​of air conditioning capacity measured while the air conditioner is in operation, and that constructs the room temperature prediction model by learning to output the actual value of the indoor temperature at time t+1 when the actual value of the indoor temperature, actual value of the outdoor temperature, and actual value of the air conditioning capacity at time t are input. This makes it possible to create and update the room temperature prediction model.

[0063] (9) A ninth aspect of the control system is the control system of (8), wherein the room temperature prediction model creation unit constructs the room temperature prediction model at a predetermined cycle or when a predetermined amount of the time-series data has been accumulated, and once the room temperature prediction model has been constructed, the evaluation unit re-evaluates the effect of air conditioning on the space using the updated room temperature prediction model. This allows for an updated evaluation of the insulation properties of the space, etc.

[0064] (10) An air conditioning system according to a tenth aspect includes an air conditioner and the control system according to any one of (1) to (9).

[0065] (11) A control method according to an eleventh aspect predicts the time it will take for the temperature of a space to be air-conditioned to rise from a predetermined initial temperature to a predetermined target temperature through air conditioning by an air conditioner, evaluates the effect of air conditioning on the space based on the time, and corrects the target temperature set by the user based on the evaluation to perform air conditioning.

[0066] (12) A program according to the twelfth aspect causes a computer to function as a means for predicting the time required for the temperature of a space to be air-conditioned to rise from a predetermined initial temperature to a predetermined target temperature through air conditioning by an air conditioner, and as a means for evaluating the effect of air conditioning on the space based on the time, and as a means for correcting the target temperature set by the user based on the evaluation results and performing air conditioning.

[0067] (13) A control method according to a thirteenth aspect predicts the indoor temperature that the temperature of a space to be air-conditioned will reach after a predetermined time has elapsed through air conditioning by an air conditioner, evaluates the effect of air conditioning on the space based on the indoor temperature, and corrects the target temperature set by the user based on the evaluation to perform air conditioning.

[0068] (14) A program according to the fourteenth aspect causes a computer to function as a means for predicting the indoor temperature that the temperature of a space to be air-conditioned will reach after a predetermined time has elapsed through air conditioning by an air conditioner, as well as a means for evaluating the effect of air conditioning on the space based on the indoor temperature, and as a means for correcting the target temperature set by the user based on the evaluation results and performing air conditioning.

[0069] The present disclosure provides a control system, an air conditioning system, a control method, and a program that can solve the above-mentioned problems.

[0070] DESCRIPTION OF SYMBOLS 100, 100A...Air conditioning system 1...Air conditioner 2...Outdoor air temperature sensor 3...Indoor temperature sensor 4...Compressor 10...Control device 11...Sensor information acquisition unit 12...Settings reception unit 13...Insulation performance evaluation unit 131...Room temperature prediction model 132, 132A...Insulation performance evaluation table 14...Target temperature correction unit 141, 141A...Target temperature correction table 15...Control unit 16...Communication unit 20...Server 21...Room temperature prediction model creation unit 22...Communication unit 30...User terminal 900...Computer 901...CPU 902...Main memory device 903...Auxiliary memory device 904...Input / output interface 905...Communication interface

Claims

1. A control system for controlling an air conditioner, comprising: an evaluation unit that predicts the indoor temperature that the indoor temperature of a space will reach after a first predetermined time has elapsed through air conditioning by the air conditioner, and evaluates the effect of the air conditioning on the space based on the indoor temperature; and a control unit that corrects the target temperature set by a user based on the evaluation and performs air conditioning.

2. The control system of claim 1 further comprises a room temperature prediction model that, when inputted with the indoor temperature, outdoor temperature, and air conditioning capacity of the air conditioner, predicts the indoor temperature after a predetermined time when the air conditioner is operated at that air conditioning capacity, wherein the evaluation unit inputs the predetermined initial temperature, predetermined outdoor temperature, and predetermined air conditioning capacity, or the predetermined initial temperature and air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model to predict the indoor temperature after a second predetermined time, and then provides the predicted indoor temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predicted indoor temperature and air conditioning capacity corresponding to the predetermined target temperature, to the room temperature prediction model, and further predicts the indoor temperature after the second predetermined time, thereby predicting the indoor temperature to be reached when the first predetermined time has elapsed.

3. A control system for controlling an air conditioner, comprising: an evaluation unit that predicts the time required for the indoor temperature of a space to rise from a predetermined initial temperature to a predetermined target temperature through air conditioning by the air conditioner, and evaluates the effect of the air conditioning on the space in accordance with the time; and a control unit that corrects the target temperature set by the user based on the evaluation and performs air conditioning.

4. The control system of claim 3, further comprising a room temperature prediction model that, when inputted with the indoor temperature, outdoor temperature, and air conditioning capacity of the air conditioner, predicts the indoor temperature after a predetermined time when the air conditioner is operated at that air conditioning capacity, wherein the evaluation unit inputs the predetermined initial temperature, predetermined outdoor temperature, and predetermined air conditioning capacity, or the predetermined initial temperature and air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model to predict the indoor temperature after a predetermined time, and then feeds the predicted indoor temperature, the predetermined outdoor temperature, and the predetermined air conditioning capacity, or the predicted indoor temperature and air conditioning capacity corresponding to the predetermined target temperature, into the room temperature prediction model, and further predicts the indoor temperature after a predetermined time, thereby predicting the time it will take for the indoor temperature of the space to change from the initial temperature to the predetermined target temperature.

5. A control system as claimed in any one of claims 1 to 4, further comprising a correction unit that corrects the target temperature set by the user based on the evaluation, wherein the evaluation unit calculates an evaluation value of the effectiveness of the air conditioning, and when the evaluation value is equal to or greater than a threshold value indicating that the effectiveness of the air conditioning is high, the correction unit corrects the target temperature value to be higher for cooling and lower for heating.

6. The control system according to claim 5, wherein the correction unit includes a table that associates the evaluation value with a correction value for the target set temperature for cooling or heating.

7. The control system according to claim 5, wherein the evaluation unit includes a table that associates the evaluation value with the time required to reach the target temperature.

8. The control system of claim 2 or 4, further comprising a room temperature prediction model creation unit that accumulates time series data of actual indoor temperature values, actual outdoor temperature values, and actual air conditioning capacity values ​​measured while the air conditioner is in operation, and that constructs the room temperature prediction model by learning to output the actual indoor temperature value at time t+1 when the actual indoor temperature value, actual outdoor temperature value, and actual air conditioning capacity value at time t are input.

9. The control system described in claim 8, wherein the room temperature prediction model creation unit constructs the room temperature prediction model at a predetermined cycle or when a predetermined amount of the time series data has been accumulated, and when the room temperature prediction model has been constructed, the evaluation unit uses the updated room temperature prediction model to re-evaluate the effect of air conditioning on the space.

10. An air conditioning system comprising: a control system according to any one of claims 1 to 4; and an air conditioner controlled by the control system.

11. A control method for an air conditioner, comprising: predicting an indoor temperature that the indoor temperature of a space will reach after a first predetermined time has elapsed through air conditioning by the air conditioner; evaluating the effect of the air conditioning on the space according to the indoor temperature; and correcting a target temperature set by a user based on the evaluation to perform air conditioning.

12. A program for causing a computer to function as: a means for predicting the indoor temperature that a space will reach after a first predetermined time has elapsed through air conditioning by an air conditioner, and for evaluating the effect of the air conditioning on the space based on the indoor temperature; and a means for correcting the target temperature set by the user and performing air conditioning based on the evaluation.

13. A control method for an air conditioner, comprising: predicting the time required for the indoor temperature of a space to rise from a predetermined initial temperature to a predetermined target temperature through air conditioning by the air conditioner; evaluating the effect of the air conditioning on the space in accordance with the time; and correcting the target temperature set by the user based on the evaluation to perform air conditioning.

14. A program for causing a computer to function as: a means for predicting the time it will take for the indoor temperature of a space to rise from a specified initial temperature to a specified target temperature through air conditioning by an air conditioner, and evaluating the effect of the air conditioning on the space in accordance with said time; and a means for correcting the target temperature set by the user and performing air conditioning based on said evaluation.

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