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

Abstract

To provide an ON-timer operation that can strike a balance between comfort and low power consumption.SOLUTION: A control system for controlling an air conditioner includes: a setting receiving part for receiving a target temperature and a setting of designated time to achieve the target temperature; an optimum operation calculation part for calculating such the time-series air conditioning capacity of the air conditioner as minimizing the power consumed by the air conditioner to achieve the target temperature at the designated time; and a controller for operating the air conditioner on the basis of the time-series air conditioning capacity.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a control system, an air conditioning system, a control method, and a program. [Background technology]

[0002] A function called ON timer operation is provided, which automatically starts the operation of an air conditioner before a designated time specified by a user, and performs cooling or heating operation so that the room temperature reaches a target temperature by the designated time. By using the ON timer operation, for example, by specifying the user's return time at a designated time, the user can air-condition the house to a desired target temperature when the user returns home. Patent Document 1 discloses an air conditioning system that learns the indoor temperature, outdoor temperature, and air conditioning capacity of the air conditioner to generate a building load prediction model, predicts the building load by inputting the predicted values ​​of the indoor temperature, air conditioning capacity, and outdoor temperature at the designated time when determining the air conditioning start time into the building load prediction model, determines the pre-operation start time in 5-minute increments from a range of, for example, 0 to 40 minutes before the designated time according to the predicted building load, and starts operation at the determined pre-operation start time. According to the air conditioning system of Patent Document 1, air conditioning can be automatically started earlier for rooms with a large building load than for rooms with a small building load, so that it is possible to reduce the possibility that the room temperature will not reach the target temperature at the designated time even if ON timer operation is performed when the building load is large. However, even if the target temperature can be achieved by this control, there is a possibility that power consumption will increase, for example, by starting air conditioning earlier than necessary. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-125868 A Summary of the Invention [Problem to be solved by the invention]

[0004] There is a demand for a control method that can achieve both comfort and low power consumption in timer operation.

[0005] The present invention provides a control system, an air conditioning system, a control method, and a program that can solve the above problems. [Means for solving the problem]

[0006] The control system disclosed herein is a control system for controlling an air conditioner, and includes a setting reception unit that receives settings of a target temperature and a designated time at which the target temperature should be achieved, an optimal operation calculation unit that calculates the time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the designated time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity.

[0007] An air conditioning system according to the present disclosure includes an air conditioner and the above-described control system.

[0008] The control method disclosed herein is a method for controlling an air conditioner, and includes the steps of accepting settings of a target temperature and a designated time at which the target temperature should be achieved, calculating a time-series air conditioning capacity of the air conditioner such that the power consumption used by the air conditioner to achieve the target temperature at the designated time is minimized, and operating the air conditioner based on the time-series air conditioning capacity.

[0009] The program disclosed herein causes a computer to execute the steps of accepting settings of a target temperature and a specified time at which the target temperature should be achieved, calculating a time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the specified time is minimized, and operating the air conditioner based on the time-series air conditioning capacity. Effect of the Invention

[0010] According to the above-mentioned control system, air conditioning system, control method, and program, a target temperature can be achieved by a specified time with low power consumption. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an example of an air conditioning system according to an embodiment. [Diagram 2] FIG. 4 is a diagram illustrating an example of a room temperature prediction model in the embodiment. [Diagram 3] 4 is a block diagram showing a detailed configuration example of an optimal operation calculation unit in the embodiment. FIG. [Figure 4A] FIG. 1 is a first diagram illustrating a method for calculating an optimal air conditioning capacity in an embodiment. [Figure 4B] FIG. 2 is a second diagram illustrating a method for calculating an optimal air conditioning capacity in the embodiment. [Diagram 5] 5 is a flowchart showing an example of control of an on timer operation in the embodiment. [Figure 6] FIG. 2 is a diagram illustrating an example of a hardware configuration of an air conditioning system according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] <Embodiment> Hereinafter, a method for controlling the timer-on operation according to an embodiment of the present disclosure will be described with reference to Figs.

[0013] (Air conditioning system configuration) FIG. 1 is a diagram showing an example of an air conditioning system in an 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), but the installation locations of the outdoor air temperature sensor 2 and the indoor temperature sensor 3 are not limited to these. 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 and the control device 10 are connected, and the control device 10 controls the compressor 4 and detects their operating states. 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 used to calculate the air conditioning start time for on-timer operation. The user terminal 30 is a smartphone or the like owned by a user of the air conditioner 1, and the user can set a target temperature and a designated time for the on-timer operation, give instructions to execute the on-timer operation, and the like 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] (Control device configuration) The control device 10 includes a sensor information acquisition unit 11 , a setting reception unit 12 , an optimal operation calculation unit 13 , a control unit 14 , and a communication unit 15 . 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 . The setting reception unit 12 receives settings such as a target temperature for the space to be air conditioned and a designated time at which the target temperature should be achieved. For example, the target temperature and the designated time are set using a remote control or a user terminal 30 (not shown).

[0015] The optimal operation calculation unit 13 calculates the time (referred to as the arrival time) required for the indoor temperature of the air-conditioned space to reach the target temperature and the air-conditioning capacity required at that time. The air-conditioning capacity refers to the strength of heating or cooling exerted by the air conditioner 1. The air-conditioning capacity has a positive correlation with the power used by the air conditioner 1 for air-conditioning, and can be calculated, for example, from the rotation speed of the compressor 4. The optimal operation calculation unit 13 calculates the transition of the time-series air-conditioning capacity that can achieve the target temperature by the specified time with the lowest power consumption based on the room temperature prediction model 131 created by the room temperature prediction model creation unit 21 described later and the outdoor air temperature and the indoor temperature measured by the air conditioner 1, and calculates the arrival time from the result. In addition, the optimal operation calculation unit 13 converts the above-mentioned time-series air-conditioning capacity into the rotation speed of the compressor 4, and calculates the time-series rotation speed of the compressor 4 for achieving the target temperature by the specified time with the lowest power consumption. Furthermore, the optimal operation calculation unit 13 predicts the time series change in indoor temperature when the target temperature can be achieved by the specified time with the lowest power consumption, and provides the predicted progress of the indoor temperature during on-timer operation to the user terminal 30, for example.

[0016] The control unit 14 controls the compressor 4 and the like to perform air conditioning. During on-timer operation, the control unit 14 starts operation of the compressor 4 and the like the arrival time calculated by the optimal operation calculation unit 13 before the designated time set by the user, and operates the compressor 4 according to the rotation speed of the compressor 4 in a time series calculated by the optimal operation calculation unit 13 to perform cooling operation or heating operation.

[0017] The communication unit 15 communicates with the server 20 and the user terminal 30. For example, the communication unit 15 transmits to the server 20 the outdoor air temperature and the room temperature acquired by the sensor information acquisition unit 11, the number of revolutions of the compressor 4 detected by the control unit 14, and the designated time and the target temperature acquired by the setting reception unit 12 as learning data required for creating the room temperature prediction model 131. The communication unit 15 acquires the room temperature prediction model 131 and the like from the server 20. The communication unit 15 acquires the target temperature, the designated time settings, and the like transmitted from the user terminal 30.

[0018] (Server configuration) The server 20 includes 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 room temperature of the space to be air-conditioned to reach a 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 ), a prediction model is created that outputs the future indoor temperature. An example of the room temperature prediction model 131 is shown in FIG.

[0019] (Room temperature prediction model) The ARX model (Auto-Regressive with eXogenous model) shown in Figure 2 calculates the indoor temperature T in (k) and the outside air temperature T O (k) from the indoor temperature T in The deviation T obtained by subtracting (k) O―in (k) and air conditioning capacity φ h This is a linear multiple regression model showing the relationship with (k). By rearranging the ARX model in Figure 2, we obtain the following equation (1).

[0020] T in (k)=a1T in (k-1)+a2T 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)+w0···(1)

[0021] The room temperature prediction model creation unit 21 uses the past operation data of the air conditioner 1, that is, the outside air temperature measured by the outside air temperature sensor 2, the room temperature measured by the room temperature sensor 3, and the rotation speed of the compressor 4 instructed by the control unit 14, which were collected at a predetermined cycle during a past predetermined period, to calculate the coefficients a1, a2, ···, a m , b 11 , b 12 , ···, b 1m , b 21 , b 22 , ···, b 2m of Equation (1), the bias term w0 which is a constant representing noise and disturbance, and the step length m that can maintain high prediction accuracy. Note that the rotation speed of the compressor 4 can be converted into the air conditioning capacity (W / m 2 ) according to the following Equations (2) to (4).

[0022] During heating operation, when the outside air temperature T O is in the non-frosting temperature region (T O ≤ -7°C, 5.5°C < T O ), φ h (T O ) = φ(-7) + ((φ(7) - φ(-7)) ÷ (7 - (-7))) × (T O - (-7)) ··· (2)

[0023] During heating operation, when the outside air temperature T O is in the frosting temperature region (-7°C < T0 ≤ 5.5°C), φ h (T O ) = φ(-7) + ((φ(2) - φ(-7)) ÷ (2 - (-7))) × (T O - (-7)) ··· (2´) Here, φ(-7), φ(2), and φ(7) are the air conditioning capacities at the outside air temperatures of -7°C, 2°C, and 7°C, respectively.

[0024] In the case of cooling operation φ h (T O ) = φ(35) + ((φ(29) - φ(35)) ÷ (35 - 29)) × (35 - T O ) ··· (3) Here, φ(35) and φ(29) are the air conditioning capacities at outside temperatures of 35°C and 29°C, respectively.

[0025] Furthermore, if the rotation speed of compressor 4 is ncmp, and K1, K2, K3, K4, and K5 are predetermined constants, the relationship between ncmp and φ(-7), φ(2), φ(7), φ(29), and φ(35) is as follows. φ(35)=K1×ncmp, φ(29)=K2×ncmp, φ(-7)=K3×ncmp, φ(2)=K4×ncmp, φ(-7)=K5×ncmp...(4)

[0026] The room temperature prediction model creation unit 21 converts the rotation speed of the compressor 4 into φ(-7), φ(2), φ(7), φ(29), and φ(35) using the formula (4), and calculates the outdoor air temperature T O By using any one of the formulas (2), (2'), and (3) according to the above, the rotation speed of the compressor 4 is adjusted to the air conditioning capacity φ h (T O )

[0027] For example, the room temperature prediction model creation unit 21 may use the least squares method to calculate coefficients a1, etc. that minimize 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). Alternatively, when appropriate values ​​for coefficients a1, etc. cannot be calculated by the least squares method due to multicollinearity between explanatory variables or when overlearning occurs, coefficients a1, etc. may be calculated by ridge regression. If the input data matrix is ​​X, the output data matrix is ​​Y, and the coefficient matrix is ​​W, the least squares method is expressed as follows: W=(X 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 TThe coefficient W is calculated by Y. When the coefficients a1, etc. are calculated by ridge regression, the room temperature prediction model creation unit 21 appropriately sets the step length m and the parameter d of the ridge regression to calculate the coefficients a1, etc. For example, various values ​​may be set for m and d, and the coefficients a1, etc. may be calculated for each combination of m and d, and the m and d that have the smallest RMSE may be adopted from among them. The method of calculating the coefficients a1, etc. is not limited to the above, and any other method may be used. In addition, it is preferable to use the operating data of the air conditioner 1 installed in the actual air-conditioned space for the time series data of the indoor temperature, outdoor temperature, and rotation speed of the compressor 4 used as learning data, but this is not limited thereto, and for example, the operating data of another air conditioner with the same capacity installed in a space having similar properties to the air-conditioned space may be used. When the room temperature prediction model creation unit 21 calculates the coefficients a1, etc., it applies the calculated coefficients a1, etc. to formula (1) to create the room temperature prediction model 131.

[0028] 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, and the like 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 these data as learning data for calculating the coefficient a1, etc. The communication unit 22 also transmits the room temperature prediction model 131 created by the room temperature prediction model creation unit 21 to the control device 10.

[0029] The user terminal 30 is a mobile terminal such as a smartphone owned by a user of the air conditioner 1. The user operates the user terminal 30 to set a target temperature and a specified time, and to instruct on timer operation. The user terminal 30 then transmits this setting information and instruction information to the control device 10 of the air conditioner 1.

[0030] 1 is an example. For example, the optimal operation calculation unit 13 may be provided in the server 20, and the calculation results may be transmitted to the control device 10, so that the server 20 performs processes with a large amount of calculations, or the room temperature prediction model creation unit 21 may be provided in the control device 10. Information on humidity and solar radiation may be transmitted to the room temperature prediction model creation unit 21, which may learn time-series data on the indoor temperature, outdoor temperature, the number of revolutions of the compressor 4, humidity, and solar radiation to create the room temperature prediction model 131.

[0031] (Details of optimal operation calculation) 3 shows a detailed configuration example of the optimal operation calculation unit 13. As shown in the figure, the optimal operation calculation unit 13 includes an optimal air conditioning capacity calculation unit 132, an optimal indoor temperature calculation unit 133, and an optimal rotation speed calculation unit 134. The optimal air conditioning capacity calculation unit 132 has a solver that solves linear programming problems and a room temperature prediction model 131, and receives the upper and lower limits of the air conditioning capacity, the outside air temperature, the indoor temperature, the target temperature, and the time until the specified time (the time until the on timer operation) as input data, analyzes what kind of air conditioning operation can be performed to achieve the target temperature with the lowest power consumption by the specified time, and calculates the time-series air conditioning capacity (power consumption per unit time) and the arrival time at that time. The function of the optimal air conditioning capacity calculation unit 132 will be specifically described using FIGS. 4A and 4B.

[0032] As an example, let us assume that the step length m=1 is obtained as the one that provides good prediction accuracy for the indoor temperature. In this case, by rearranging the above equation (1), we obtain the following equation (1´). T in (k+1)=a1T in (k)+b 11 φ h (k)+b 21 T0(k)+w0 (1´) The coefficients a1, etc. in formula (1') are not exactly the same as a1, etc. in formula (1). For example, if the coefficient a1 is T in formula (1), o-in T O -T in After replacing and rearranging, for example, (a1-b 21 ) is replaced by a1. T in formula (1')in is the indoor temperature, φ h is the heating capacity, T0 is the outside air temperature, and w0 is the bias term. Equation (1´) is an example of the room temperature prediction model 131 possessed by the optimal air conditioning capacity calculation unit 132. The heating capacity φ until N - 1 minutes later h , the outside temperature T O being given, the room temperature T^ until N minutes later in can be expressed by Equation (5) in FIG. 4A.

[0033] The optimal air conditioning capacity calculation unit 132 solves the linear programming problem (Equation (6)) shown in FIG. 4B using Equation (5), so that the upper and lower limit values of the heating capacity and the target temperature T min are satisfied, and the optimal heating capacity φ that minimizes the total heating capacity until the target temperature T min is achieved is calculated. Note that Equation (6) is, as an example, an equation for performing heating operation by an input timer operation and achieving the target temperature by a specified time, and in the case of a cooling operation, a linear programming problem can be formulated in the same way of thinking. c in Equation (6) represents a matrix in which all elements of 1 × N are 1, φ h is the lower limit value of the heating capacity, φ min is the upper limit value of the heating capacity. φ max and φ min and φ max are arbitrarily set by a designer or the like. Minimize represents minimizing the objective function c T φ h (minimizing the heating capacity), and subject to represents the constraint conditions. The first from the top of the constraint conditions restricts that the heating capacity is equal to or greater than the lower limit value φ min , the second restricts that the heating capacity is equal to or less than the upper limit value φ max , and the third uses Equation (5) to restrict that the future indoor temperature is equal to or greater than T min (in the case of cooling, it is set to be equal to or less than T min ). For example, when the target temperature is T SP (°C) and the indoor temperature reaches T SP (°C) at M (<N) minutes later (M minutes later is the target time), in order to make the future indoor temperature satisfy the room temperature lower limit T min is set as follows. T min=[0, , 273.15+T sp , , 273.15+T sp ] T Here, if the length of one control step is, for example, one minute, the matrix T min The first 0 in indicates the lower limit of the room temperature that should be met in 1 minute. In this example, there are M 0s in a row from the beginning. And the M+1th to Nth elements are 273.15+T sp (K). By setting in this way and solving the linear programming problem of equation (6), the indoor temperature T sp (°C) and minimize power consumption. For example, the optimal operation calculation unit 13 calculates the heating capacity per minute when the initial indoor temperature T in (0) is used as the indoor temperature measured by the indoor temperature sensor 3 at the time of prediction (when starting to solve this linear programming problem), and 0 is used as the initial value φ h (0), and the outdoor air temperature measured by the outdoor air temperature sensor 2 at the time of prediction is used as the initial value T O (0), and the indoor temperature after one minute is predicted using equation (1´), and the heating capacity after one minute is φ h Set an arbitrary value in (1) and calculate the indoor temperature one minute later, which was predicted by formula (1´), as the indoor temperature T in (1) is used as the predicted outdoor temperature, and the indoor temperature T O (1), and the indoor temperature two minutes later is predicted using equation (1´). This calculation is repeated for the rest of the time series, and the indoor temperature T in , outside temperature T O , heating capacityφ h Search for a set of time series T that satisfies equation (6). in , T O , φ h As a method for efficiently searching for a combination of, the simplex method, the interior point method, etc. are known. The optimal operation calculation unit 13 solves the linear programming problem of Fig. 4B using, for example, the simplex method, the interior point method, etc. By solving the linear programming problem, for example, the heating capacity for each minute from the prediction time until N minutes later can be obtained. φ h = [0, 0, 0, φ h1, φ h2 , φ h3、 ... (7) For example, assume that the calculation result shown in formula (7) is obtained. Time periods when the heating capacity is 0 are time periods when the unit is not operating, and the time corresponding to a control step where a value greater than 0 is set is the operation start time for timer operation. In the case of formula (7), the air conditioner 1 remains stopped until two minutes later (the first 0 indicates that the heating capacity is 0 minutes later, the second 0 indicates that the heating capacity is 0 one minute later, and the third 0 indicates that the heating capacity is 0 two minutes later), and then three minutes later the heating capacity φ h1 Air conditioner 1 starts operation at φ h2 After 5 minutes, the heating capacity is increased to φ h3 By controlling the temperature at , the power consumption is minimized and the room temperature is raised to T sp (°C) can be achieved. The optimal operation calculation unit 13 solves the linear programming problem exemplified in equation (6) to calculate a time-series air conditioning capacity (for example, equation (7)), and outputs this data to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134. The time-series air conditioning capacity calculated by the optimal operation calculation unit 13 is referred to as the optimal air conditioning capacity.

[0034] The optimum indoor temperature calculation unit 133 has a room temperature prediction model 131. When the optimum air conditioning capacity is input, the optimum indoor temperature calculation unit 133 inputs the optimum air conditioning capacity, the outdoor air temperature at the time of prediction, and the indoor temperature at the time of prediction to the room temperature prediction model 131 (the indoor temperature at the time of prediction is input as the initial value of the indoor temperature, and the outdoor air temperature is input as the outdoor air temperature for each time after the time of prediction), and predicts the indoor temperature for each control step up to M minutes later (or up to N minutes later) using the room temperature prediction model 131. As a result, for example, the transition of the indoor temperature for each minute from the present (time of prediction) to the specified time is predicted. The time series indoor temperature predicted in this way is called the optimum indoor temperature. The optimum indoor temperature calculation unit 133 transmits the optimum indoor temperature to the user terminal 30 via the communication unit 15. The user terminal 30 acquires the optimum indoor temperature and displays it on the display unit. As a result, the user can check the prediction of the transition of the indoor temperature for the on-timer operation instructed by the user.

[0035] When the optimum air conditioning capacity is input, the optimum rotation speed calculation unit 134 converts it into a time-series rotation speed of the compressor 4 (referred to as optimum compressor rotation speed) and outputs the converted rotation speed to the control unit 14. The optimum rotation speed calculation unit 134 calculates the rotation speed of the compressor 4 backward from the air conditioning capacity using the above-mentioned formulas (2) to (4), and converts the time-series air conditioning capacity into a time-series rotation speed of the compressor 4. When the on timer operation is set, the control unit 14 controls the compressor 4 based on the optimum compressor rotation speed (for example, the above-mentioned formula (7)) acquired from the optimum rotation speed calculation unit 134. The control unit 14 may control the compressor 4 according to the optimum compressor rotation speed, or may correct the optimum compressor rotation speed by deviation feedback control (for example, PID control or PI control) so as to bring the difference between the optimum indoor temperature and the actual indoor temperature closer to 0, and then control the compressor 4 using the corrected rotation speed.

[0036] (operation) Next, the operation of the air conditioning system 100 according to this embodiment will be described with reference to FIG. FIG. 5 is a flowchart showing an example of control of the on timer operation in the embodiment. First, the room temperature prediction model creation unit 21 creates a 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 operation data of the air conditioner 1, for example, a time series of indoor temperature, outdoor temperature, and the rotation speed of the compressor 4, and the ARX model illustrated in Fig. 2. 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 optimal operation calculation unit 13 acquires and stores the transmitted room temperature prediction model 131.

[0037] Next, the user sets the operation mode (cooling operation or heating operation), target temperature, and designated time to the control device 10 using the user terminal 30 or a remote control (not shown), and instructs the ON timer operation (step S12). The setting reception unit 12 acquires the operation mode, target temperature, designated time, and instruction to execute the ON timer operation via the communication unit 15, and outputs this information to the optimal operation calculation unit 13.

[0038] Next, the optimal operation calculation unit 13 calculates the optimal air conditioning capacity using the optimal air conditioning capacity calculation unit 132 (step S13). The optimal air conditioning capacity calculation unit 132 acquires the outdoor air temperature measured by the outdoor air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, the target temperature and designated time set by the user, and the upper and lower limits of the air conditioning capacity, and calculates the optimal air conditioning capacity by solving a linear programming problem as exemplified in FIG. 4B. The upper and lower limits of the air conditioning capacity are set in advance, and the optimal operation calculation unit 13 stores these values. The optimal air conditioning capacity calculation unit 132 outputs the optimal air conditioning capacity to the optimal indoor temperature calculation unit 133 and the optimal rotation speed calculation unit 134.

[0039] Next, the optimal operation calculation unit 13 calculates the optimal indoor temperature using the optimal indoor temperature calculation unit 133 (step S14). The optimal indoor temperature calculation unit 133 inputs the outdoor air temperature measured by the outdoor air temperature sensor 2, the indoor temperature measured by the indoor temperature sensor 3, and the initial value of the air conditioning capacity into the room temperature prediction model 131 (for example, formula (1')) to predict the indoor temperature after one control step. The optimal indoor temperature calculation unit 133 inputs the outdoor air temperature measured by the outdoor air temperature sensor 2, the predicted value of the indoor temperature after one control step, and the air conditioning capacity after one control step based on the optimal air conditioning capacity into formula (1') to predict the indoor temperature after two control steps. Similarly, for the third control step and onwards, the optimal indoor temperature calculation unit 133 inputs the predicted indoor temperature and the air conditioning capacity specified by the optimal air conditioning capacity into the room temperature prediction model 131, and sequentially predicts the future indoor temperature for each control step.

[0040] Next, the optimal operation calculation unit 13 notifies the user of the optimal indoor temperature (step S15). The optimal operation calculation unit 13 transmits the optimal indoor temperature calculated by the optimal indoor temperature calculation unit 133 to the user terminal 30 via the communication unit 15. The user terminal 30 receives the optimal indoor temperature and outputs the received optimal indoor temperature to the display unit. This allows the user to understand how the indoor temperature will change to the target temperature due to the on-timer operation. The optimal indoor temperature may be transmitted to a remote control (not shown), and a predicted change in the indoor temperature may be displayed on the display unit of the remote control.

[0041] Next, the optimal operation calculation unit 13 calculates the optimal compressor rotation speed using the optimal rotation speed calculation unit 134 (step S16). The optimal rotation speed calculation unit 134 converts the optimal air-conditioning capacity acquired from the optimal air-conditioning capacity calculation unit 132 into the rotation speed of the compressor 4 using equations (2) to (4) to calculate the optimal compressor rotation speed. The optimal operation calculation unit 13 outputs the optimal compressor rotation speed to the control unit 14.

[0042] Next, the control unit 14 starts air conditioning (step S17). The control unit 14 controls the refrigerant circuit (not shown) so that air conditioning can be performed in the operation mode specified by the on timer operation, and starts air conditioning based on the optimal compressor rotation speed. The optimal compressor rotation speed is set to the rotation speed of the compressor 4 for each minute, for example, from the present (prediction time) until N minutes from now. The control unit 14 starts air conditioning at the time when a value greater than 0 is set as the rotation speed of the compressor 4, and thereafter drives the compressor 4 at the rotation speed set to the optimal compressor rotation speed. Alternatively, when there is a difference between the optimal indoor temperature and the actual room temperature, the control unit 14 may drive the compressor 4 at a rotation speed obtained by correcting the optimal compressor rotation speed by deviation feedback control using the difference.

[0043] 5 is an example. For example, steps S16, S14, S15, and S17 may be performed in this order, or steps S14 to S15 and steps S16 to S17 may be performed in parallel. In addition, in step S13, the outdoor air temperature at the time of prediction is always used as the outdoor air temperature, but in cases where a change in the outdoor air temperature is predicted, a predicted value of the outdoor air temperature for each predetermined time up to N minutes from now may be obtained, or a change in the outdoor air temperature for each predetermined time up to N minutes from now may be predicted, and the predicted value of the outdoor air temperature corresponding to the time when the indoor temperature is predicted may be input to room temperature prediction model 131 to predict the future indoor temperature. Furthermore, the room temperature prediction model 131 may be created by learning time-series data on the indoor temperature, the outdoor temperature, the rotation speed of the compressor 4, humidity, and the amount of solar radiation. In that case, in steps S13 and S14, in addition to the outdoor temperature measured by the outdoor temperature sensor 2 and the indoor temperature measured by the indoor temperature sensor 3, each process is performed using, for example, the measurement values ​​of a humidity sensor and an actinometer (not shown) provided in the room.

[0044] (effect) As described above, according to this embodiment, the target temperature can be achieved with low power consumption by the designated time during ON timer operation. More specifically, taking into consideration the indoor temperature, outdoor temperature, etc. at the time of setting ON timer operation, the change in room temperature is predicted based on the room temperature prediction model 131, while the time series air conditioning capacity (the number of revolutions of the compressor 4) that can simultaneously minimize power consumption and achieve the target temperature at the designated time is calculated, and the operation start time is calculated by calculating backwards from the calculated air conditioning capacity. Then, after the operation start time, the air conditioner 1 is operated based on the calculated time series air conditioning capacity. This makes it possible to calculate the operation start time and the time series air conditioning capacity corresponding to disturbances such as changes in the target temperature and outdoor temperature, so that the target temperature can be reliably achieved with low power consumption by the designated time.

[0045] FIG. 6 is a diagram illustrating an example of a hardware configuration of an air conditioning system according to an embodiment. The computer 900 includes a CPU 901, a main memory device 902, an auxiliary memory device 903, an input / output interface 904, and a communication interface 905. The above-mentioned control device 10, server 20, and user terminal 30 are implemented in the computer 900. The above-mentioned functions are stored in the auxiliary memory device 903 in the form of a program. The CPU 901 reads the program from the auxiliary memory device 903, loads it in the main memory device 902, and executes the above-mentioned processing according to the program. The CPU 901 also secures a storage area in the main memory device 902 according to the program. The CPU 901 also secures a storage area in the auxiliary memory device 903 for storing data being processed according to the program.

[0046] A program for realizing all or part of the functions of the control device 10, the server 20, and the user terminal 30 may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read 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. In addition, if a WWW system is used, the term "computer system" also includes a homepage providing environment (or display environment). In addition, the term "computer-readable recording medium" refers to a portable medium such as a CD, DVD, or USB, and a storage device such as a hard disk built into a computer system. In addition, if the program is distributed to the computer 900 via a communication line, the computer 900 that receives the program may deploy the program in the main storage device 902 and execute the above processing. In addition, the above program may be for realizing part of the above-mentioned functions, and may further be capable of realizing the above-mentioned functions in combination with a program already recorded in the computer system.

[0047] As described above, several embodiments according to the present disclosure have been described, but 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 gist of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and gist of the invention. The controller 10 and / or the server 20 are an example of a control system. The past operation data of the air conditioner 1 is an example of performance data. Equations (1) and (1') are examples of linear equations.

[0048] <Additional Notes> The control system, the air conditioning system, the control method, and the program described in each embodiment can be understood, for example, as follows.

[0049] (1) A control system according to a first aspect is a control system for controlling an air conditioner, and includes a setting receiving unit that receives settings of a target temperature and a designated time at which the target temperature should be achieved, an optimal operation calculation unit that calculates a time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the designated time is minimized, and a control unit that operates the air conditioner based on the time-series air conditioning capacity. This makes it possible to achieve the target temperature by the set time with low power consumption.

[0050] (2) A control system according to a second aspect is a control system according to (1), further comprising a room temperature prediction model that predicts the indoor temperature in a control step following a control step based on the indoor temperature, outdoor temperature, and air conditioning capacity in a control step, and the optimal operation calculation unit uses the room temperature prediction model to search for a combination of the indoor temperature, the outdoor temperature, and the air conditioning capacity in a time series such that the power consumption for achieving the target temperature at the specified time is minimized. This makes it possible to calculate a time-series air conditioning capacity that can achieve the target temperature by a set time with low power consumption.

[0051] (3) A control system according to a third aspect is a control system according to (1) to (2), wherein the optimal operation calculation unit searches for the combination by solving a linear programming problem having an objective function of minimizing the power consumption and a constraint condition of achieving the target temperature at the specified time. This makes it possible to calculate a time-series air conditioning capacity that can achieve the target temperature by a set time with low power consumption.

[0052] (4) A control system according to a fourth aspect is a control system according to any one of (1) to (3), wherein the room temperature prediction model is a linear equation showing the relationship between the indoor temperature, the outdoor temperature, the air conditioning capacity, and the indoor temperature in the next control step, and further includes a room temperature prediction model creation unit that creates the room temperature prediction model by calculating coefficients of the linear equation so as to minimize a difference between actual data of the indoor temperature, the outdoor temperature, and the air conditioning capacity, the indoor temperature predicted by the linear equation, and the indoor temperature included in the actual data. This makes it possible to create a room temperature prediction model.

[0053] (5) A control system according to a fifth aspect is a control system of (1) to (4), wherein the optimal operation calculation unit predicts a trend in indoor temperature according to the time series of air conditioning capacity based on the time series of air conditioning capacity and the room temperature prediction model, and outputs the predicted trend in indoor temperature. This makes it possible to provide the user with a forecast of the indoor temperature change when the on-timer operation is set. By referring to the forecast of the indoor temperature change, the user can confirm that the target temperature will be achieved by the specified time.

[0054] (6) An air conditioning system according to a sixth aspect includes the air conditioner 1 and the control system according to any one of (1) to (5).

[0055] (7) A control method according to a seventh aspect is a control method for an air conditioner, comprising the steps of accepting settings of a target temperature and a designated time at which the target temperature should be achieved, calculating a time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the designated time is minimized, and operating the air conditioner based on the time-series air conditioning capacity.

[0056] (8) A program relating to an eighth aspect causes a computer to execute the steps of accepting settings of a target temperature and a designated time at which the target temperature should be achieved, calculating a time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the designated time is minimized, and operating the air conditioner based on the time-series air conditioning capacity. [Explanation of symbols]

[0057] 100 Air conditioning system 1. Air conditioner 2. Outside air temperature sensor 3. Indoor temperature sensor 4. Compressor 10. Control device 11 Sensor information acquisition unit 12. Settings reception section 13 Optimal operation calculation section 131...Room temperature prediction model 132 Optimum air conditioning capacity calculation unit 133 Optimum indoor temperature calculation unit 134 Optimum rotation speed calculation section 14. Control section 15. Communications Department 20 Server 21. Room temperature prediction model creation section 22. Communications Department 30 User terminal 900...Computer 901···CPU 902...Main memory 903...Auxiliary storage device 904 Input / Output Interface 905 Communication Interface

Claims

1. A control system for controlling an air conditioner, a setting receiving unit that receives a setting of a target temperature and a designated time at which the target temperature should be achieved; an optimal operation calculation unit that calculates a time-series air conditioning capacity of the air conditioner so that the power consumption used by the air conditioner to achieve the target temperature at the specified time is minimized; A control unit that operates the air conditioner based on the time-series air conditioning capacity; A control system comprising:

2. a room temperature prediction model for predicting the room temperature in a control step following a certain control step based on the indoor temperature, the outdoor temperature, and the air conditioning capacity in the certain control step; Further equipped with the optimal operation calculation unit uses the room temperature prediction model to search for a combination of the indoor temperature, the outdoor air temperature, and the air conditioning capacity in a time series such that the power consumption for achieving the target temperature at the specified time is minimized; The control system of claim 1 .

3. the optimal operation calculation unit searches for the combination by solving a linear programming problem having a constraint of minimizing the power consumption and achieving the target temperature at the specified time as an objective function; The control system of claim 2.

4. a room temperature prediction model creation unit that creates the room temperature prediction model by calculating coefficients of the linear equation, the room temperature prediction model being a linear equation that indicates the relationship between the indoor temperature, the outdoor temperature, the air conditioning capacity, and the indoor temperature in the next control step, so that a difference between past data of the indoor temperature, the outdoor temperature, and the air conditioning capacity, the indoor temperature predicted by the linear equation, and the indoor temperature included in the past data is minimized; The control system of claim 2 or claim 3, further comprising:

5. The optimal operation calculation unit predicts a change in the indoor temperature according to the time-series air conditioning capacity based on the time-series air conditioning capacity and the room temperature prediction model, and outputs the predicted change in the indoor temperature. A control system according to claim 2 or 3.

6. An air conditioner, A control system according to any one of claims 1 to 3; An air conditioning system equipped with:

7. A method for controlling an air conditioner, comprising: receiving a setting of a target temperature and a designated time for achieving the target temperature; calculating a time-series air conditioning capacity of the air conditioner such that power consumption used by the air conditioner to achieve the target temperature at the specified time is minimized; operating the air conditioner based on the time-series air conditioning capacity; The control method includes:

8. To your computer receiving a setting of a target temperature and a designated time for achieving the target temperature; A step of calculating a time-series air conditioning capacity of the air conditioner so that power consumption used by the air conditioner to achieve the target temperature at the specified time is minimized; operating the air conditioner based on the time-series air conditioning capacity; A program that executes the following.

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