Air conditioning control device and air conditioning control method

Abstract

To further reduce discomfort of a resident to a thermal environment.SOLUTION: According to this embodiment, an air conditioning control device includes a prediction model storage part, a control variable target value storage part, a constraint condition storage part, a control variable current value acquisition part, and an operation variable target value calculation part. The prediction model storage part stores a prediction model that represents an influence exerted on a control variable by an operation variable. The control variable target value storage part stores the target value of each index constituting the control variable. The constraint condition storage part stores information on a constraint condition in calculating a target value of each operation variable. The control variable current value acquisition part acquires respective current values of control variables. The operation variable target value calculation part calculates the target values of the operation variable so as to standardize the magnitude of deviation between prediction values and target values of a plurality of control variables by the prediction model on the basis of the prediction model, the respective target values of the control variables, the constraint condition and the respective current values of the control variables.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an air conditioning control device and an air conditioning control method. [Background technology]

[0002] Conventionally, there is known a technology for controlling the air environment in a certain range of spaces (hereinafter referred to as a zone or spatial position). This technology controls the air supply volume for each zone to reduce the difference between the target temperature and the current temperature for each zone.

[0003] In the above-mentioned conventional technology, when the heat load and target temperature are different for each zone, there may be a zone where the deviation between the target temperature and the current temperature is large. This is because each supply air volume has an upper limit and a lower limit, and each supply air volume is controlled only by considering the tracking of the target temperature of the zone in charge. Therefore, the occupants in the zone with the large deviation feel uncomfortable.

[0004] Therefore, in order to reduce the discomfort felt by residents, a technology has been proposed in which air conditioning equipment in a capacity shortage state is assisted by air conditioning equipment in other zones (see, for example, Patent Document 1). Note that a capacity shortage state refers to a state in which, for example, during cooling (heating), the temperature of a certain zone is higher (lower) than the target value, but the supply air volume of that zone is already at its upper limit, so the supply air volume cannot be increased and the temperature cannot be brought any closer to the target value. Conversely, a state in which, for example, during cooling (heating), the temperature of a certain zone is lower (higher) than the target value, but the supply air volume of that zone is already at its lower limit, so the supply air volume cannot be reduced and the temperature cannot be brought any closer to the target value is called an overcapacity state. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2020 / 003447 Summary of the Invention [Problem to be solved by the invention]

[0006] However, conventional technology has room for improvement in reducing discomfort felt by occupants in the thermal environment. For example, the increased supply air volume for assistance affects zones other than the assisted zone with insufficient capacity, so if there is a zone other than the assisted zone that is experiencing excess capacity, the air conditioning capacity will become even more excessive, causing discomfort to occupants. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, the air conditioning control device of the present invention is characterized in that it includes a prediction model memory unit that stores a prediction model that represents the influence of a manipulated variable on a control variable, for each of which a parameter related to the supply air volume of the air outlet that affects the control variable is used as a manipulated variable, a control variable target value memory unit that stores target values ​​of each control variable, a constraint condition memory unit that stores constraint conditions related to the manipulated variables, a control variable current value acquisition unit that acquires current values ​​of each control variable, and a manipulated variable target value calculation unit that calculates target values ​​of the manipulated variables based on the prediction model, the target values ​​of each control variable, the constraint conditions, and the current values ​​of each control variable, so that the magnitude of deviation between the predicted values ​​and target values ​​of the multiple control variables predicted by the prediction model is leveled out. Effect of the Invention

[0008] According to the present invention, it is possible to further reduce discomfort felt by occupants due to the thermal environment. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing an overview of an air conditioning control system including an air conditioning control device according to an embodiment. [Diagram 2]FIG. 2 is a diagram showing an example of targets controlled by the air conditioning control device according to the embodiment and the control results. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of an air conditioning control device according to an embodiment. [Figure 4] FIG. 4 is a flowchart showing an example of a processing procedure of the air conditioning control device according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of an air conditioning control device and an air conditioning control method according to the present application will be described in detail below with reference to the drawings. Note that the air conditioning control device and the air conditioning control method according to the present application are not limited to the embodiment.

[0011] [1. Overview of the air conditioning control system] First, an overview of a system including an air conditioning control device 100 according to this embodiment will be described. FIG. 1 is a diagram showing an overview of an air conditioning control system including an air conditioning control device according to this embodiment. The air conditioning control system according to this embodiment relates to a technique for controlling the air environment of each zone by adjusting the supply air volume of each of a plurality of spaces within a certain range. The air conditioning control device 100 in this system is a controller that calculates a target value of an operation variable using the supply air volume for each zone or the state of equipment that affects the supply air volume (such as the opening degree of an air supply damper) as an operation variable. The air conditioning control device 100 basically calculates the operation variable target value of each zone so as to reduce the difference between the target temperature set for each zone and the current temperature.

[0012] 1, the air conditioning control device 100 is connected to the air conditioning equipment monitoring and control device 200 by wire or wirelessly, and transmits and receives information between them. The air conditioning equipment monitoring and control device 200 is also connected to one air conditioner 210, VAVs 220-1 to 220-3, and temperature sensors 230-1 to 230-3 by signal lines or the like, acquires information on the status of each, and controls the air conditioner and VAV. The air conditioner 210 supplies temperature-adjusted air to each of the VAVs 220-1 to 220-3 via an intake air duct.

[0013] In the example of Fig. 1, a configuration consisting of one air conditioner 210 and multiple VAVs (Variable Air Volumes) is shown, but the present invention is not limited to this. Also, in Fig. 1, an example is shown in which air conditioning control is performed for three zones, but the number of zones can be increased or decreased to any number, and the number of VAVs 220 and temperature sensors 230 may be increased or decreased in accordance with an increase or decrease in the number of zones. Furthermore, the number of zones and the number of VAVs do not need to match, and the number of VAVs does not need to be multiple.

[0014] For each control variable, which is a collection of indices related to comfort at multiple different spatial positions in the indoor environment, the air conditioning control device 100 stores a predictive model that represents the influence of the manipulated variable on the control variable, a target value for each control variable, and constraints related to the manipulated variable, using parameters related to the supply air volume of the air outlet that affects the control variable as manipulated variables.

[0015] Then, the air conditioning control device 100 acquires the current values ​​of each of the controlled variables, and calculates the target values ​​of the manipulated variables based on the prediction model, the target values ​​of each of the controlled variables, the constraint conditions, and the current values ​​of each of the controlled variables, so that the magnitude of the deviation between the predicted values ​​of the multiple controlled variables by the prediction model and the target values ​​is leveled. Note that in the following description, the absolute value of the deviation between the predicted value and the target value of the controlled variable (hereinafter referred to as the absolute deviation value of the controlled variable) is used as the magnitude of the deviation between the predicted value and the target value of the controlled variable.

[0016] The air conditioning control device 100 stores a prediction model that represents the influence of the manipulated variables on the controlled variables. Here, for example, the aforementioned comfort index is the air temperature, and the parameter related to the supply air volume of the air outlet is the supply air volume of the VAV.

[0017] The air conditioning control device 100 also stores target values ​​for each of the control variables and constraint conditions for the manipulated variables. For example, the air conditioning control device 100 stores a target value for the temperature in a zone set externally, and also stores constraint conditions for calculating the target value for each manipulated variable, such as the upper and lower limits of the supply air volume of the VAV 220.

[0018] Then, the air conditioning control device 100 acquires the current values ​​of each of the control variables. For example, the air conditioning control device 100 acquires, as the current values ​​of the control variables, the measured values ​​of the air temperature in the zone at the time of processing, measured by the temperature sensor 230, via the air conditioning equipment monitoring and control device 200.

[0019] Then, the air conditioning control device 100 calculates the target values ​​of the manipulated variables based on the prediction model, the target values ​​of each of the controlled variables, the constraint conditions, and the current values ​​of each of the controlled variables so that the absolute deviations of the multiple controlled variables according to the prediction model are averaged.

[0020] For example, the air conditioning control device 100 calculates a target value for the supply air volume of the VAV 220 in each zone based on a predictive model, the target value for the temperature in the zone, the upper and lower limits of the supply air volume, and the measured value of the temperature in the zone, so that the absolute deviation of the control variables in each zone is averaged out.

[0021] Here, referring to FIG. 2, the characteristics of the control target assumed by the air conditioning control device 100 will be described. FIG. 2 shows an example in which cooling is performed in zones 1 to 3, where zones 1 and 3 are zones with relatively low air conditioning loads, and zone 2 is a zone with a relatively high air conditioning load. As shown in the example of FIG. 2, the air conditioning loads of the zones controlled by the air conditioning control device 100 usually differ from one another due to differences in heat loads such as heat dissipation by the occupants, temperature target values, and the like. The purpose of the control device according to this embodiment is to reduce discomfort felt by occupants in the thermal environment compared to conventional control by appropriately manipulating the supply air volume for such control targets.

[0022] Returning to the explanation of Fig. 1, the air conditioning equipment monitoring and control device 200 monitors the state of air conditioning equipment such as the air conditioner 210 and VAV 220, and also controls the air conditioning equipment by changing the target values ​​of the air conditioning equipment. The air conditioning equipment monitoring and control device 200 is connected to the air conditioning control device 100 to obtain the calculated target values ​​of each manipulated variable, and controls the VAV 220 etc. according to the target values, thereby controlling the temperature of each zone.

[0023] The air conditioner 210 is an air conditioning facility composed of, for example, a cooling coil, a heating coil, and a blower, and its operation is controlled by the air conditioning facility monitoring and control device 200. In addition, conditioned air blown out by the air conditioner 210 is supplied to each zone via an air supply duct. The VAV 220 is an air conditioning facility that controls the amount of conditioned air supplied from the air conditioner 210 to each zone so as to eliminate the air conditioning load. In addition, the VAV 220 can control the amount of supply air supplied to each zone by controlling the opening degree of a damper.

[0024] 2. Configuration of the Air Conditioning Control Device 100 and Operation of Each Component Next, the configuration of the air conditioning control device 100 shown in Fig. 1 and the operation of each component will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of the air conditioning control device according to the embodiment. As shown in Fig. 3, the air conditioning control device 100 according to the embodiment has a communication unit 110, a control unit 120, and a storage unit 130.

[0025] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to the air conditioning equipment monitoring and control device 200 by wire or wirelessly, and transmits and receives information.

[0026] The storage unit 130 is realized by a storage device such as a RAM (Random Access Memory) or a hard disk. The storage unit 130 stores data and programs necessary for various processes by the control unit 120, and includes a prediction model storage unit 131, a control variable target value storage unit 132, a constraint condition storage unit 133, a deviation allowable value storage unit 134, and a supply air consumption energy evaluation function storage unit 135 as units closely related to the present invention.

[0027] The prediction model storage unit 131 stores a prediction model that represents the influence of each of the controlled variables, which are a set of indexes related to comfort at a plurality of different spatial positions in the indoor environment, on the controlled variables, with parameters related to the supply air volume of the air outlet that influences the controlled variables being treated as manipulated variables. For example, the prediction model storage unit 131 stores a prediction model based on a step response using the following formulas (1) to (6).

[0028] Here, the formulas (1) to (6) relating to the prediction model will be explained in order. In the following explanation, as a specific example, a case will be explained in which the air-conditioned space is formed of Nz zones, each zone is provided with an air outlet, and the temperature of each zone is controlled. In addition, in each of the following formulas, u i (t) is the manipulated variable, which represents the supply air volume at the outlet of zone i at time t. Furthermore, y j (t) is a controlled variable and represents the temperature of zone j at time t. Note that (i=1, , Nm) and (j=1, , Nc), where Nm is the manipulated variable and Nc is the number of controlled variables. In this embodiment, the following explanation will be given assuming that Nm=Nc=Nz holds, but in general, this equality does not necessarily need to hold.

[0029]

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[0030] In this embodiment, the air conditioning control device 100 uses the above formula (1) to calculate the predicted value of the controlled variable in the prediction model. Note that the formula used to calculate the predicted value of the controlled variable is not limited to the above formula (1), and a formula different from the above formula (1) may be used depending on the prediction model used. In the above formula (1), τ represents the current time, y j ^(t) is y j It represents the predicted value of (t). j ^ is y j In this example, r = 1 (Nh = 1). In other words, only one step ahead is predicted. Also, Δu i (t) represents the change in the manipulated variable at time t, and the following equation (2) holds.

[0031]

number

[0032] The above formula (2) shows that the change in the manipulated variable is calculated by the difference between the manipulated variable at time t and the manipulated variable at time t-1, which is one step before time t. Also, u i For (t), the following equation (3) holds: i ~(t) is u i represents the measured value at time t. i ~ is u i It indicates that there is a ~ directly above s ij is the number of time steps until the step response reaches a steady state, and s ij The following equation (4) holds true.

[0033]

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[0034]

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[0035] Also, a ij k u i (t) for y j It represents the coefficient of the step response model of (t), and is a parameter obtained by collecting step response data for each pair of manipulated variables and controlled variables in the actual environment or a CFD (Computational Fluid Dynamics) model representing the actual environment, assuming that the following equation (5) holds. ij k teeth, ij Directly below k In addition, the step response data is collected, for example, when the environment is in a steady state. i is changed stepwise, and each control variable y j Response data is collected and this process is carried out for each manipulated variable u i This is carried out by implementing the following:

[0036]

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[0037] And d j (t) represents the disturbance term, which is given here as the difference between the current value of the controlled variable and the predicted value at the current time of the previous prediction, as expressed in the following equation (6). Note that the current value of the controlled variable y j For example, the measured value of the control variable (temperature) is used for (τ). Also, the disturbance term d j (t) is not limited to the following formula (6) and may be defined by another formula.

[0038]

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[0039] In other words, the above formula (1) is the predicted value of the temperature (control variable) r steps ahead from the current time, calculated by multiplying the predicted value of the temperature at the current time by the effect of the change in the manipulated variables in all zones from the current time to r-1 steps ahead, and the effect of the change in the manipulated variables from the current time to s ij The calculation is performed by adding the effect of the change in the manipulated variable up to the previous -1 step and the disturbance term.

[0040] The prediction model stored in the prediction model storage unit 131 is not limited to the model based on the step response model described above, and may be, for example, a state space model, an impulse response model, an ARX model, a transfer function model, etc. In the above description, a model created based on input / output data is used, but, for example, a first-principles model created based on a physical law such as the law of conservation of energy may be used.

[0041] Furthermore, in the above-mentioned model, the past values ​​of the manipulated variables are used, but this is not limiting. For example, a prediction model created by linearizing a nonlinear physical model around a certain control point can be used. In this case, it is sufficient to use the values ​​of the manipulated variables at that control point. j Although a measured value is used for (τ), for example, an estimated value calculated based on other measurement data may be used.

[0042] Furthermore, the equation expressing the predicted value of the controlled variable in the prediction model does not have to be a function of the manipulated variable itself, but may be a function of the change in the manipulated variable over time, as in equation (1) above, and may be expressed as a function of the supply air heat quantity instead of the supply air volume, and a separate conversion equation between the supply air heat quantity and the supply air volume may be used.

[0043] The control variable target value storage unit 132 stores the target value of each control variable. For example, the control variable target value storage unit 132 stores the target value of the room temperature set in each zone to be controlled in association with each zone.

[0044] The constraint condition storage unit 133 stores constraint conditions related to the manipulated variables. For example, the constraint condition storage unit 133 stores the constraint inequalities of the following equations (7) and (8) and information defining parameters used therein as data of constraint conditions representing the upper and lower limits of the supply airflow rate, which is the manipulated variable.

[0045]

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[0046]

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[0047] Here, u i ￣ and u i u are parameters that represent the upper and lower limits of the supply air volume, which are the manipulated variables, and are set in advance. i ￣ is u i Show that there is a ￣ directly above u i _ is u i In addition to the above, the constraint condition storage unit 133 may store data on various constraint conditions, such as upper and lower limits for the total supply airflow rate and upper and lower limits for the amount of change in the supply airflow rate.

[0048] The deviation tolerance storage unit 134 stores a tolerance for the absolute value of the deviation of each controlled variable from its target value, or a tolerance for the amount by which each controlled variable exceeds its target value and a tolerance for the amount by which each controlled variable does not reach its target value. For example, the deviation tolerance storage unit 134 stores a tolerance ε j Remember about.

[0049] The supply air consumption energy evaluation function storage unit 135 stores a supply air consumption energy evaluation function that evaluates the consumption energy that depends on the supply air volume from the values ​​of the manipulated variables. For example, the supply air consumption energy evaluation function storage unit 135 stores the following formula 9 that is predefined on the assumption that the energy consumption of the fan of the air conditioner increases monotonically in response to the supply air volume.

[0050]

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[0051] The control unit 120 is realized by a CPU (Central Processing Unit), MPU (Micro Processing Unit), etc., executing various programs stored in a storage device inside the air conditioning control device 100 using a RAM as a working area. The control unit 120 is also realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0052] The control unit 120 has a control variable current value acquisition unit 121 and an operation variable target value calculation unit 122, and may also have an operation feasibility signal acquisition unit 123, a human detection data acquisition unit 124, a deviation tolerance adjustment unit 125, a control variable exclusion processing unit 126, a declaration data acquisition unit 127, and a declaration data aggregation unit 128, as necessary.

[0053] The controlled variable current value acquisition unit 121 acquires the current values ​​of the controlled variables. For example, the controlled variable current value acquisition unit 121 acquires the temperatures measured by the temperature sensors 230 installed in each zone via the air conditioning equipment monitoring and control device 200 and the communication unit 110. Here, the controlled variable current value acquisition unit 121 acquires, as the controlled variable current value, for example, the temperature measured immediately before the manipulated variable target value calculation process described below, or a value estimated as the temperature immediately before the manipulated variable target value calculation process.

[0054] The manipulated variable target value calculation unit 122 calculates the target values ​​of the manipulated variables based on the prediction model, the target values ​​of each of the controlled variables, the constraint conditions, and the current values ​​of each of the controlled variables so that the absolute value of the deviation between the predicted values ​​and the target values ​​of multiple controlled variables based on the prediction model is leveled out.

[0055] In this embodiment, the values ​​of the manipulated variables that average the absolute values ​​of the deviations of the control variables from their target values ​​are calculated using linear programming.

[0056] More specifically, the manipulated variable target value calculation unit 122 solves the following optimization problem 1 using a linear programming solver or the like. That is, the operation is performed to minimize the objective function indicated by "Minimize" by using the equality and inequality indicated by "Subject to" as constraints. i The value of (τ) is calculated and output as the target value of the manipulated variable. sp j is a parameter representing the target value of the control variable in zone j, and y sp j teeth sp Directly below j Here, equations (1) to (3) and (6) that represent the prediction model are stored as constraint equations for optimization problem 1. In addition, equations (7) and (8) that represent constraint conditions related to the manipulated variables are also stored as constraint equations for optimization problem 1.

[0057]

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[0058] Note that err max is a variable that represents the maximum absolute value of the deviation of each control variable one control step ahead from the current time, and equations (11) and (12) are constraint equations that represent this.

[0059] By calculating the above optimization problem 1, the manipulated variable target value calculation unit 122 can calculate manipulated variable target values ​​for all controlled variables such that the absolute deviation value of a specific controlled variable does not become extremely large compared to the absolute deviation values ​​of the other controlled variables, in other words, such that the absolute deviation values ​​of the controlled variables in each zone are leveled out.

[0060] In addition, since the above equation (1) takes into account the influence of the manipulated variables of each zone on the control variables of zones other than the own zone, the manipulated variable target value calculation unit 122 can use the above equation (1) to calculate the manipulated variable target value so as to assist the other zones.

[0061] In addition, the manipulated variable target value calculation unit 122 may calculate the target value of the manipulated variable so that the absolute value of the deviation between the predicted value of the multiple control variables by the prediction model and the target value is smoothed according to the deviation tolerance.

[0062] For example, instead of solving the optimization problem 1, the manipulated variable target value calculation unit 122 calculates the deviation allowance ε j The following optimization problem 2a is solved using the above. As a result, the deviation absolute value of each control variable one step ahead is calculated based on the deviation allowance ε j The target value of the manipulated variable is calculated so as to be equalized so as not to exceed the above as much as possible.

[0063]

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[0064] Here, overerr j is the control variable y j The deviation tolerance ε of the absolute deviation j is a variable that represents the excess amount relative to , and the above equations (14) to (16) are constraint equations that represent this.

[0065] Note that the manipulated variable target value calculation unit 122 may calculate, for example, the following optimization problem 2b instead of the above optimization problem 2a, to calculate manipulated variable target values ​​that level out the absolute deviation values ​​of the control variables of each zone so that they do not exceed the deviation allowable values ​​as much as possible.

[0066]

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[0067] Here, normalr j is the time for each control variable y j The absolute deviation of the deviation tolerance ε j is a variable that represents a value normalized by , and the above equations (18) and (19) are constraint equations that represent this. max is normalr j is a variable that represents the maximum value of , and the above equation (20) is a constraint equation that represents this.

[0068] Note that calculating optimization problem 2b is expected to result in smaller variance in the absolute deviation values ​​of the control variables in each zone than when calculating optimization problem 2a, but this may result in a higher calculation load.

[0069] In the above explanation, the same deviation allowable value is used for both the excess side and the shortfall side from the target value, but different values ​​may be used, and a term other than the term for leveling the deviation of the controlled variable may be added to the objective function of the above optimization problem. In addition, in the above calculation, the manipulated variable target value may be calculated by nonlinear programming using a nonlinear prediction model, objective function, and constraint equation, or the calculation may be performed using a general optimization algorithm (metaheuristics, etc.) or a unique search algorithm (rule-based, etc.) that is a means other than linear programming or nonlinear programming.

[0070] Furthermore, in order to improve the robustness of control, a method may be used in which a prediction model for a period including multiple future time steps is stored, a trajectory (reference trajectory) of the control variable that asymptotically approaches a set target value from the current value is calculated, and at any timing during the period, manipulated variable values ​​for multiple future steps are calculated that smooth out the absolute deviation value of the control variable using the reference trajectory as the target value of the control variable, and the initial manipulated variable value is then adopted as the target value of the current manipulated variable.

[0071] In the above description, the manipulated variable is not limited to the supply air volume, and for example, the VAV opening degree may be used as the manipulated variable on the assumption that the duct pressure is controlled to a constant value. Furthermore, the controlled variable is not limited to the temperature, and for example, the PMV (Predicted Mean Vote) may be used as the controlled variable using temperature and other parameters and measured values, and a target value and a deviation allowable value may be set for the PMV. However, the prediction model used is a model according to the manipulated variable and controlled variable used.

[0072] Furthermore, the manipulated variable target value calculation unit 122 may use a supply air consumption energy evaluation function to calculate the target values ​​of the manipulated variables so that the consumption energy depending on the supply air volume is as small as possible. For example, the manipulated variable target value calculation unit 122 calculates the following optimization problem 1' instead of the above optimization problem 1.

[0073]

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[0074] Here, α in the above formula (21) is a preset positive coefficient parameter. The manipulated variable target value calculation unit 122 calculates the above optimization problem 1' to minimize the sum of the maximum absolute value of the deviation of the controlled variables and the supply air consumption energy evaluation function, and can calculate the manipulated variable target value in which the supply air consumption energy is as small as possible and the deviation absolute value of the controlled variable is leveled.

[0075] When calculating the manipulated variable target value taking into account the supply air consumption energy as well as the above-mentioned deviation tolerance, the following optimization problem 2a' or 2b' can be calculated to calculate the manipulated variable target value in which the supply air consumption energy is as small as possible and the absolute deviation value of the control variable is smoothed to an extent that it does not exceed the deviation tolerance as much as possible.

[0076]

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[0077]

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[0078] So far, we have described an embodiment with a basic configuration in which the control unit 120 is composed of only the controlled variable current value acquisition unit 121 and the manipulated variable target value calculation unit 122. Hereinafter, we will describe an embodiment in which the control unit 120 has additional components.

[0079] First, a configuration will be described in which the control unit 120 has an operation feasibility signal acquisition unit 123. In this configuration, the operation variable target value calculation unit 122 calculates a target value of the operation variable by setting an operation variable corresponding to an operation impossible signal acquired by the operation feasibility signal acquisition unit 123 as a predetermined fixed value. For example, when an operation impossible signal is acquired by the operation feasibility signal acquisition unit 123 described later, the operation variable target value calculation unit 122 adds the constraint equation of the following equation (24) to the above optimization problem 1 and performs calculation.

[0080]

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[0081] Here, in the above equation (24), the operating variable u p is the operation variable of zone p corresponding to the VAV that transmitted the signal indicating that it cannot be operated. By adding the condition of equation (24) above, the following equation (25) is established based on equations (2) and (3) above.

[0082]

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[0083] That is, the manipulated variable target value calculation unit 122 calculates the manipulated variable u p Since the calculation can be performed while fixing the current value (most recent measured value), the manipulated variable target value can be calculated while taking into account the influence of the VAV that has become inoperable.

[0084] The operation feasibility signal acquisition unit 123 acquires an operation feasibility signal indicating whether the operation variable can be operated. For example, the operation feasibility signal acquisition unit 123 acquires an operation feasibility signal identifying whether the supply air volume of the VAV 220 to be controlled can be operated from the air conditioning equipment monitoring and control device 200 via the communication unit 110. Then, when the operation feasibility signal acquisition unit 123 acquires an operation impossible signal, it notifies the operation variable target value calculation unit 122 of the zone that is not operable.

[0085] In addition, when the air conditioning equipment monitoring and control device 200 determines that the status of the VAV 220 to be controlled has become stopped or broken due to a malfunction or other reason, the inoperable signal may be sent to the air conditioning control device 100 in the form of information about the zone corresponding to the VAV 220 that has become inoperable.

[0086] Next, an embodiment of a configuration in which the control unit 120 has a human detection data acquisition unit 124 and a deviation tolerance adjustment unit 125 will be described. The human detection data acquisition unit 124 acquires human detection data that indicates the number of people present at a spatial position or the presence or absence of people. For example, the human detection data acquisition unit 124 uses a human detection algorithm to calculate the number of people n present in each zone from information acquired by a thermal image sensor installed in each zone. j Get the.

[0087] The deviation tolerance adjustment unit 125 adjusts the deviation tolerance of the control variable corresponding to the spatial position where the number of people is relatively small, and adjusts the deviation tolerance of the control variable corresponding to the spatial position where the number of people is relatively large, based on the human detection data acquired by the human detection data acquisition unit 124. For example, the deviation tolerance adjustment unit 125 adjusts the deviation tolerance of the control variable corresponding to the spatial position where the number of people is relatively large, based on the human detection data acquired by the human detection data acquisition unit 124. j Using the deviation tolerance ε j is adjusted using the following equation (26).

[0088]

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[0089] Here, in the above equation (26), ε j ￣ is a parameter that represents the upper limit of the deviation tolerance εj of zone j, γ is a positive parameter, and e is the Napier's constant. j ￣ is ε j The symbol (^) is located directly above the number of people n. In addition, both parameters are preset arbitrary parameters. j This indicates that the deviation tolerance is calculated by multiplying an exponential function whose value decreases as the deviation increases by the upper limit of the deviation tolerance.

[0090] The deviation tolerance adjustment unit 125 can adjust the deviation tolerance of zones with a large number of people to be smaller and the deviation tolerance of zones with a small number of people to be larger using the above equation (26), and can therefore calculate the manipulated variable target value that brings the temperature in zones with a large number of people closer to the target value.

[0091] As a method for automatically adjusting the deviation allowable value corresponding to a zone with a relatively large number of people to be smaller, the following formula (27) or (28) can also be used.

[0092]

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[0093]

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[0094] Here, the above formula (27) is the upper limit value ε of the deviation tolerance j ￣ is 1 and the number of people n j The deviation tolerance ε is calculated by dividing the sum of j In the above formula (28), β is a positive coefficient parameter, εj_ is the lower limit of the deviation tolerance and is greater than 0. j ̄ is a parameter smaller than . j _ is ε j The symbol _ is located just below the parameter. Both parameters are preset arbitrary parameters. The above formula (28) expresses the upper limit ε j ￣ to βn j and the lower limit of the deviation tolerance ε j _ indicates that the larger number is calculated as the deviation tolerance.

[0095] The number of people represented by the human detection data may be an approximate number, and the deviation tolerance may be adjusted depending on the size of the number. For example, the human detection data is data that indicates whether the number of people at each spatial position is approximately 4 or less, approximately 5 to 9, or approximately 10 or more, and when the human detection data indicates that the number of people is approximately 4 or less, the deviation tolerance may be adjusted according to the size of the number of people. j When you want to express a number between 5 and 9 people, use n j is set to 5, and to indicate 10 or more people, use n j is set to 10, calculate the deviation tolerance ε j may be adjusted.

[0096] The human detection data may be data obtained by a pyroelectric sensor or the like that indicates the presence or absence of a person at each spatial position, that is, data that cannot distinguish the number of people greater than one, but can distinguish between 0 people and one or more people. In that case, for example, when the human detection data indicates absence, n j is set to 0, and n is used to indicate the presence jis set to 1, calculate one of the above formulas (26) to (28), and obtain the deviation tolerance ε j may be adjusted.

[0097] Next, an embodiment in which the control unit 120 has a human detection data acquisition unit 124 and a control variable exclusion processing unit 126 will be described. Note that the operation of the human detection data acquisition unit 124 in this embodiment is the same as the operation in the embodiment in which the control unit 120 has a human detection data acquisition unit 124 and a deviation tolerance adjustment unit 125 (paragraphs

[0086] to

[0096] ), and therefore a description of the human detection data acquisition unit 124 will be omitted.

[0098] The control variable exclusion processing unit 126 excludes from the control variables an index corresponding to a spatial position where the number of people is indicated to be equal to or less than a predetermined number based on the human detection data acquired by the human detection data acquisition unit 124. For example, the control variable exclusion processing unit 126 excludes from the control variables an air temperature corresponding to a zone where the number of people present in each zone acquired by the above-mentioned human detection data acquisition unit 124 is determined to be equal to or less than a predetermined number (e.g., 0; a value greater than 0 is also acceptable). In other words, when solving optimization problem 1, for example, the control variable exclusion processing unit 126 performs processing to convert the above formulas (11) and (12) into the following formulas (29) and (30) before solving the problem.

[0099]

number

[0100]

number

[0101] In the above formulas (29) and (30), Sn represents a set of indexes of control variables for which the number of people detected in the corresponding zone is equal to or less than a predetermined number. The above formulas (29) and (30) indicate that the constraint equations corresponding to Sn are excluded from the above formulas (11) and (12).

[0102] According to the above formulas (29) and (30), the comfort-related index for the zone where the number of people is equal to or less than the predetermined number is excluded from the control variables, and the manipulated variable target values ​​are calculated. Note that when solving other optimization problems, such as any of formulas 11 to 15, similarly, by excluding the index that appears in the formula of the optimization problem and corresponds to the above set Sn, the comfort-related index for the zone where the number of people is equal to or less than the predetermined number is excluded from the control variables, and the manipulated variable target values ​​are calculated.

[0103] When the human detection data is data indicating the presence or absence of a person for each zone, the index of the zone in which the human detection data indicates that a person is absent may be used as an element of Sn to perform similar processing.

[0104] Finally, an embodiment in which the control unit 120 has a deviation tolerance adjustment unit 125, a declaration data acquisition unit 127, and a declaration data compilation unit 128 will be described. The deviation tolerance adjustment unit 125 in this embodiment is common to the deviation tolerance adjustment unit 125 in the embodiment in which the control unit 120 has a human detection data acquisition unit 124 and a deviation tolerance adjustment unit 125 (paragraphs

[0086] to

[0096] ) in that it adjusts the deviation tolerance, but differs in that it adjusts the deviation tolerance based on the declaration data. The operation of the deviation tolerance adjustment unit 125 in this embodiment will be described later.

[0105] First, the report data acquisition unit 127 acquires report data consisting of a report of discomfort from a resident present at a spatial position and information on the spatial position where the resident who made the report is present. For example, the report data acquisition unit 127 associates the report information indicating discomfort from a resident present in each zone with information on the zone where the report was made, and acquires it as report data.

[0106] Here, the resident may report discomfort by using a reporting terminal distributed to the resident in advance, for example, and report a signal such as "hot" or "cold." The reporting data acquisition unit 127 determines, for example, the zone in which the receiver with the strongest received radio wave strength of the reporting signal is installed among receivers installed in each zone that receive the reporting signal transmitted from the reporting terminal, as the zone in which the resident who made the report is present. In addition, for example, information indicating the report of discomfort may be transmitted from an information processing terminal such as a PC or smartphone used by the resident to the air conditioning control device 100 directly or via the air conditioning equipment monitoring and control device 200 together with location information of the terminal, thereby reporting discomfort from the resident.

[0107] The declaration data aggregation unit 128 aggregates the declaration data of each spatial position acquired by the declaration data acquisition unit 127. For example, the declaration data aggregation unit 128 aggregates the above-mentioned declaration data for each zone at a certain control period, and notifies the deviation allowable value adjustment unit 125 described above.

[0108] The deviation tolerance adjustment unit 125 adjusts the deviation tolerance of the control variable corresponding to the spatial position where the number of reported discomfort sensations has increased, so as to decrease it for a predetermined period of time, based on the reported data collected by the reported data collection unit 128. For example, the deviation tolerance adjustment unit 125 adjusts the deviation tolerance ε j is adjusted as shown in the following equation (23).

[0109]

number

[0110] In the above formula 23, μ is a parameter that is greater than 0 and less than 1, and is set in advance. The above formula 23 is used to calculate the deviation allowable value of zone q by ε q and μ.

[0111] Furthermore, the deviation allowable value adjustment unit 125 may perform an adjustment such that the deviation allowable value is smaller as the number of reported data items reported during a certain control period increases, for example, according to the following equation (24).

[0112]

number

[0113] Here, in the above formula 24, n q represents the total number of declaration data in zone q, and η represents a preset parameter greater than 0. The above equation 24 is expressed as q and the deviation tolerance ε stored in the deviation tolerance storage unit 134. q This indicates that the deviation tolerance is calculated by multiplying with

[0114] The deviation tolerance adjustment unit 125 can adjust the deviation tolerance of a zone where a report has been made or where there are many reports by using the above formula 23 or formula 24, so that it can calculate an manipulated variable target value that brings the temperature in a zone where there are many reports closer to the target value.

[0115] Generally, when air conditioning is controlled based on the discomfort declaration data described above, the target value of the indoor temperature may be changed for a certain period of time in response to the declaration (hot, cold), and the target value of the indoor temperature may be restored when the certain period has elapsed. Therefore, the deviation allowable value adjustment unit 125 may adjust the deviation allowable value, setting the time from when the target value of the indoor temperature is changed until the target value is restored as a predetermined time, and may restore the deviation allowable value when the predetermined time has elapsed.

[0116] [3. Processing procedure by air conditioning control device] Next, an example of a processing procedure by the air conditioning control device 100 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing an example of a processing procedure in the air conditioning control device according to the embodiment.

[0117] First, in step S101, the prediction model is stored in the prediction model storage unit 131. Then, in step S102, the target value of each controlled variable is stored in the control variable target value storage unit 132. Then, in step S103, the constraint condition including the constraint condition related to the manipulated variable is stored in the constraint condition storage unit 133. Then, in step S104, the controlled variable current value acquisition unit 121 acquires the current value of each controlled variable. Then, in step S105, the manipulated variable target value calculation unit 122 calculates the target value of each manipulated variable based on the prediction model stored in step S101, the target value of each controlled variable stored in step S102, the constraint condition stored in step S103, and the current value of each controlled variable acquired in step S104, so that the magnitude of the deviation between the predicted value and the target value of the multiple controlled variables according to the prediction model is leveled while satisfying the constraint condition.

[0118] The above-mentioned processing of steps S101 to S105 is executed for each control cycle. However, steps S101 to S103 may be omitted if there are no changes in the prediction model, the target values ​​of each controlled variable, and the constraint conditions. In this case, the manipulated variable target value calculation unit uses the prediction model, the target values ​​of each controlled variable, and the constraint conditions that were last stored.

[0119] 4. Effects of the embodiment As described above, the air conditioning control device 100 according to this embodiment has a prediction model storage unit 131, a controlled variable target value storage unit 132, a constraint condition storage unit 133, a controlled variable current value acquisition unit 121, and a manipulated variable target value calculation unit 122. The prediction model storage unit 131 stores a prediction model that represents the influence of the manipulated variables on the controlled variables. The controlled variable target value storage unit 132 stores target values ​​of each index that constitutes the controlled variables.

[0120] The constraint condition storage unit 133 stores information on the constraint conditions when calculating the target value of each manipulated variable. The controlled variable current value acquisition unit 121 acquires the current value of each controlled variable. The manipulated variable target value calculation unit 122 calculates the target value of the manipulated variable based on the prediction model, the target value of each controlled variable, the constraint condition, and the current value of each controlled variable such that the magnitude of deviation between the predicted value of the multiple controlled variables by the prediction model and the target value is leveled.

[0121] As a result, the air conditioning control device 100 calculates manipulated variable target values ​​that smooth out the absolute values ​​of deviations of comfort indices, which are controlled variables, from the target values ​​of each index in multiple zones, thereby reducing the phenomenon in which the absolute values ​​of deviations of each index from the target values ​​for all zones become unacceptably large, thereby achieving the effect of further reducing discomfort felt by occupants due to the thermal environment.

[0122] The above effects will be described based on a more specific example with reference to Fig. 2. Fig. 2 is a diagram showing a specific example of the control result by the air conditioning control device 100 according to this embodiment. Fig. 2 shows an example of the result of controlling the temperature in each of zones 1 to 3 by cooling. In Fig. 2, zone 1 and zone 3 are zones with relatively low air conditioning loads, and zone 2 is a zone with relatively high air conditioning loads.

[0123] In the example of FIG. 2, the target temperature values ​​for zone 1 and zone 3 are "26.5°C", and the target temperature value for zone 2 is "25.5°C". The air conditioning control device 100 calculates the target value of the supply air volume so as to level out the absolute deviation value of the control variable based on the prediction model, the current temperature value of each zone, and the target temperature value of each zone. In this calculation, the supply air volumes for zone 1 and zone 3 are calculated so that zone 2 does not become too warm with respect to the target temperature, and so that zone 1 and zone 3 do not become too cold with respect to the target temperature. In addition, the supply air volume for zone 2 is calculated so that zone 1 and zone 3 do not become too cold with respect to the target temperature, and so that zone 2 does not become too warm with respect to the target temperature.

[0124] As a result of supplying air with the supply air volume calculated in this way, in the example of Figure 2, the measured temperature values ​​of zone 1 and zone 3 are "26.2°C", and the measured temperature value of zone 2 is "25.8°C", and the absolute deviation value of the control variable in each zone is leveled at "0.3°C". If the supply air volumes of zone 1 and zone 3 are increased, the temperature of zone 2 approaches the target value and the absolute deviation value decreases, but the absolute deviation values ​​of the temperatures of zone 1 and zone 3 increase, so the leveling degree decreases. Also, if the supply air volumes of zone 1 and zone 3 are decreased, the temperatures of zone 1 and zone 3 approach the target value and the absolute deviation value decreases, but the absolute deviation value of zone 2 increases, so the leveling degree also decreases. The same can be said when the supply air volume of zone 2 is increased or decreased.

[0125] 2, the air conditioning control device 100 takes into consideration the overall balance for all zones and calculates the target value of the VAV supply air volume for all zones so that no zone has an exceptionally large absolute deviation value of the control variable compared to other zones, thereby reducing the discomfort of the occupants. Note that, although the above example describes the control for cooling, the same control (warming control and cooling control are appropriately matched) is also performed for heating.

[0126] In addition, in the conventional technology, there is a problem that no particular improvement is made to the zone of the air conditioning equipment in an overcapacity state. In contrast, the present invention calculates the manipulated variable target value that averages out the absolute value of the deviation from the target value of each index, but since the absolute value of the deviation is large in both an undercapacity state and an overcapacity state, it has the effect of being able to improve not only the undercapacity state but also the overcapacity state.

[0127] For example, control is realized to increase the supply air volume of a relatively low-load zone to assist a relatively high-load zone, while not increasing the supply air volume too much so as not to excessively impair the comfort of the relatively low-load zone (so as not to become too cold in the case of cooling, and too warm in the case of heating). Also, control is realized to reduce the supply air volume of a relatively high-load zone to assist a relatively low-load zone. Furthermore, at that time, control is also realized to not reduce the supply air volume too much so as not to excessively impair the comfort of the relatively high-load zone (so as not to become too warm in the case of cooling, and too cold in the case of heating).

[0128] In addition, in conventional technology, the supply air volume is changed only after a capacity shortage or excess is recognized based on the current value of the control variable, which causes a time lag and can lengthen the time it feels uncomfortable. In contrast, the present invention is a method in which the air conditioning control device 100 works with the air conditioning equipment monitoring and control device 200 to control the supply air volume based on predictions, and if it is predicted that a capacity shortage or excess will occur in the near future, the supply air volume is changed, which has the effect of shortening the time lag compared to conventional technology and shortening the time it feels uncomfortable.

[0129] The air conditioning control device 100 further includes a deviation tolerance storage unit 134. The deviation tolerance storage unit 134 stores deviation tolerances that represent tolerances for absolute values ​​of deviations from the target values ​​of the respective controlled variables, or tolerances for excess amounts and tolerances for underachievement amounts from the target values ​​of the respective controlled variables. The manipulated variable target value calculation unit 122 then calculates the target values ​​of the manipulated variables such that the absolute values ​​of deviations between the target values ​​and predicted values ​​of the multiple controlled variables according to the prediction model are smoothed out in accordance with the deviation tolerances.

[0130] In air conditioning control for each zone, uniformly equalizing the absolute deviation values ​​of the control variables for all zones may not lead to a reduction in the number of occupants feeling uncomfortable in some cases. For example, if control is performed to uniformly equalize the absolute deviation values ​​of the control variables for zones where people are usually frequently present and zones where people are rarely present, there is a risk that an unnecessarily large number of occupants will feel uncomfortable in zones where people are usually frequently present.

[0131] Therefore, by setting a low deviation tolerance in advance for zones where people are usually frequently present, the air conditioning control device 100 can keep the absolute deviation value of the control variable for zones where people are usually less likely to be present within a certain range while relatively reducing the absolute deviation value of the control variable for zones where people are usually more likely to be present, thereby reducing the occurrence of people feeling uncomfortable. In other words, the air conditioning control device 100 has the effect of being able to flexibly control the temperature according to the characteristics of each zone.

[0132] The air conditioning control device 100 further includes a supply air consumed energy evaluation function storage unit 135. The supply air consumed energy evaluation function storage unit 135 stores a supply air consumed energy evaluation function that evaluates consumed energy dependent on the supply air volume from the values ​​of the manipulated variables. Then, the manipulated variable target value calculation unit 122 calculates target values ​​of the manipulated variables so as to minimize the supply air consumed energy evaluation function when the supply air consumed energy evaluation function is a monotonically increasing function of consumed energy, and so as to maximize the supply air consumed energy evaluation function when the supply air consumed energy evaluation function is a monotonically decreasing function of consumed energy.

[0133] In air conditioning control for each zone, when there is freedom of control due to the fact that there are more manipulated variables than controlled variables, there may be multiple manipulated variable target values ​​that average out the absolute deviations of the controlled variables. In such cases, it is desirable to calculate manipulated variable target values ​​that minimize energy consumption as much as possible among the manipulated variable target values. Therefore, the air conditioning control device 100 calculates target values ​​for the manipulated variables that average out the absolute deviations of the controlled variables while minimizing the energy consumption due to the air supply, thereby achieving the effect of reducing energy consumption due to control.

[0134] The air conditioning control device 100 further includes an operation permission signal acquisition unit 123. The operation permission signal acquisition unit 123 acquires an operation permission signal indicating whether the operation variable can be operated. Then, the operation variable target value calculation unit 122 calculates a target value of the operation variable by setting the operation variable corresponding to the operation impossibility signal acquired by the operation permission signal acquisition unit 123 as a predetermined fixed value.

[0135] In air conditioning control for each zone, if an inoperable manipulated variable occurs due to equipment failure or the like, the inoperable manipulated variable cannot track the target value, and the absolute deviation value of the control variables in the zones near the inoperable manipulated variable may become unacceptably large. Therefore, the air conditioning control device 100 performs control to assist the control of the inoperable manipulated variable by setting the inoperable manipulated variable as a fixed value and calculating the target values ​​of the other manipulated variables.

[0136] That is, in the air conditioning control device 100, for example, when a control is being performed by cooling and an operational variable occurs that becomes inoperable while maintaining a small air volume, a calculation is performed to increase the value of the operational variable near the inoperable operational variable (to increase the supply air volume), and control is possible so that the temperature in the zone near the inoperable operational variable does not become too warm. On the other hand, in the air conditioning control device 100, when a control variable occurs that becomes inoperable while maintaining a large air volume, a calculation is performed to decrease the value of the operational variable near the inoperable operational variable (to decrease the supply air volume), and control is possible so that the temperature in the zone near the inoperable operational variable does not become too cold. Note that, although the control in the case of cooling has been described in the above example, the same control (warming control and cooling control are appropriately associated) is also performed in the case of heating.

[0137] Therefore, the air conditioning control device 100 has the effect of being able to appropriately control the air temperatures of all zones, taking into consideration the effect that the inoperable manipulated variable has on nearby zones.

[0138] The air conditioning control device 100 further includes a human detection data acquisition unit 124 and a deviation tolerance adjustment unit 125. The human detection data acquisition unit 124 acquires human detection data indicating the number of people present at a spatial position or the presence or absence of people at a spatial position. The deviation tolerance adjustment unit 125 performs adjustment based on the human detection data acquired by the human detection data acquisition unit 124 to increase the deviation tolerance of a control variable corresponding to a spatial position where the number of people is relatively small and to decrease the deviation tolerance of a control variable corresponding to a spatial position where the number of people is relatively large.

[0139] In air conditioning control for each zone, uniformly leveling the absolute deviation values ​​of the control variables in zones with a large number of occupants and zones with a small number of occupants may result in an unnecessarily large number of occupants feeling uncomfortable in zones with a large number of occupants. Therefore, the air conditioning control device 100 adjusts the allowable deviation values ​​of the control variables in zones with a large number of occupants to be relatively small depending on the number of people present in each zone, thereby calculating manipulated variable values ​​that make the absolute deviation values ​​of the control variables in zones with a large number of occupants relatively small, thereby achieving the effect of reducing the number of occupants feeling uncomfortable.

[0140] The air conditioning control device 100 further includes the above-mentioned human detection data acquisition unit 124 and a control variable exclusion processing unit 126. The control variable exclusion processing unit 126 excludes from the control variables an index corresponding to a spatial position where the human detection data acquired by the human detection data acquisition unit 124 indicates that the number of people is equal to or less than a predetermined number.

[0141] As a result, the air conditioning control device 100 calculates the manipulated variable target value excluding the indicators of zones where the number of people is equal to or less than a predetermined number, thereby achieving the effect of reducing energy consumption by not supplying air to make a zone where there are no people or where the number of people is so small that they could be moved to another zone comfortable. Also, in a situation where the absolute value of the deviation of the controlled variable of zones near a zone where there are no people or where the number of people is so small that they could be moved to another zone becomes large due to insufficient capacity when the supply air volume of the zone where there are no people or where the number of people is so small that they could be moved to another zone is set to 0, the air conditioning control device 100 achieves the effect of performing control to increase the supply air volume of the zone so as to reduce the absolute value of the deviation of the controlled variable of zones near the zone.

[0142] The air conditioning control device 100 also includes a declaration data acquisition unit 127, a declaration data compilation unit 128, and a deviation tolerance adjustment unit 125. The declaration data acquisition unit 127 acquires declaration data consisting of declarations of discomfort by occupants present at spatial positions and information on the spatial positions at which the occupants who made the declarations are present. The declaration data compilation unit 128 compilations the declaration data for each spatial position acquired by the declaration data acquisition unit 127. The deviation tolerance adjustment unit 125 performs an adjustment to reduce the deviation tolerance of the control variable corresponding to the spatial position where the number of discomfort declarations has increased for a predetermined period of time, based on the declaration data compilation unit 128.

[0143] In a reporting-type air conditioning system in which control is performed to change the temperature target value in response to a discomfort report, the supply air volume, which is the manipulated variable, is controlled using the temperature of one designated zone as the control variable, so that the discomfort of the occupant may continue even if a report is made. For example, in this control, for a zone with insufficient or excessive capacity, the supply air volume cannot be improved even if the target value is changed, and the discomfort continues because the control variable cannot follow the changed target value.

[0144] Therefore, the air conditioning control device 100 adjusts the deviation tolerance value according to the number of discomfort reports in each zone, and calculates the values ​​of all manipulated variables so as to reduce the absolute deviation value of the control variables in zones with a large number of reports, while also taking into account the absolute deviation value of the control variables in zones with a small number of reports.This has the effect of preventing zones with a small number of reports from becoming unacceptably uncomfortable, while making it easier for the control variables in zones with a large number of reports to track the target values, thereby reducing the discomfort of the occupants.

[0145] [5. Hardware Configuration] The air conditioning control device 100 according to the embodiment described above is realized, for example, by a computer 1000 configured as shown in Fig. 5. Fig. 5 is a hardware configuration diagram showing an example of a computer that realizes the functions of the air conditioning control device 100. The computer 1000 has a configuration in which a CPU 1100, a RAM 1200, a ROM 1300, an auxiliary storage device 1400, a communication I / F (interface) 1500, and an input / output I / F (interface) 1600 are connected by a bus 1800.

[0146] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1300 or the auxiliary storage device 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, programs that depend on the hardware of the computer 1000, and the like.

[0147] The auxiliary storage device 1400 stores programs executed by the CPU 1100, data used by the programs, etc. The communication I / F 1500 receives data from other devices via a predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0148] The CPU 1100 controls output devices such as a display and a printer, and an input / output device 1700 such as a keyboard and a mouse, via the input / output I / F 1600. The CPU 1100 acquires data from the input / output device 1700 via the input / output I / F 1600. The CPU 1100 also outputs generated data to the input / output device 1700 via the input / output I / F 1600.

[0149] For example, when the computer 1000 functions as the air conditioning control device 100 according to this embodiment, the CPU 1100 of the computer 1000 executes a program loaded onto the RAM 1200 to realize the functions of the control unit 120 .

[0150] [6. Other] Of the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0151] In this specification, the absolute value of the deviation between the predicted value and the target value of the controlled variable (absolute value of the deviation of the controlled variable) is used as the magnitude of the deviation between the predicted value and the target value of the controlled variable, and this absolute value is smoothed, but this is not limited to the above. For example, the same effect can be obtained by using the value obtained by squaring the deviation between the predicted value and the target value of the controlled variable and smoothing this squared value. In addition, various modifications are possible, such as using an index that increases monotonically as the absolute value of the deviation of the controlled variable increases.

[0152] In the embodiments of this specification, a method for leveling the magnitude of the deviation of the controlled variables by minimizing the maximum value of the absolute value of the deviation of the controlled variables (or the deviation normalized by the allowable deviation) in Equation 10, Equation 12, Equation 13, and Equation 15 has been described, but a method for minimizing the sum of the absolute value of the deviation of each controlled variable (or the deviation normalized by the allowable deviation) raised to the power of a real number greater than 1 may also be used. The leveling effect can also be obtained in this way.

[0153] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0154] The above-mentioned components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the above-mentioned embodiments can be appropriately combined within a range that does not cause contradictions in the processing contents.

[0155] Moreover, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, a control section can be read as control means or a control circuit.

[0156] Although some of the embodiments of the present invention have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section. [Explanation of symbols]

[0157] 100 Air conditioning control device 110 Communications Department 120 Control section 121 Control variable current value acquisition section 122 Operational variable target value calculation section 123 Operation permission signal acquisition unit 124 Human detection data acquisition unit 125 Deviation tolerance adjustment section 126 Control variable exclusion processing section 127 Declaration Data Acquisition Department 128 Declaration Data Compilation Department 130 Storage section 131 Prediction model memory unit 132 Control variable target value storage unit 133 Constraint condition storage section 134 Deviation tolerance memory section 135 Supply air consumption energy evaluation function memory section 200 Air conditioning equipment monitoring and control device 210 Air conditioner 220, 220-1 to 220-3 VAV 230, 230-1 to 230-3 Temperature sensor

Claims

1. a prediction model storage unit that stores a prediction model representing an influence of a controlled variable, which is a set of indexes relating to comfort at a plurality of different spatial positions in an indoor environment, on the controlled variable, the controlled variable being a parameter relating to an air supply volume of the air outlet that influences the controlled variable, as a manipulated variable; a control variable target value storage unit that stores a target value of each control variable; a constraint condition storage unit that stores a constraint condition related to the manipulated variables; a control variable current value acquisition unit for acquiring current values ​​of the control variables; an manipulated variable target value calculation unit that calculates a target value of the manipulated variable based on the prediction model, the target value of each of the controlled variables, the constraint condition, and the current value of each of the controlled variables such that the magnitude of deviation between the predicted value of the plurality of controlled variables by the prediction model and the target value is leveled; An air conditioning control device comprising:

2. a deviation allowance storage unit that stores an allowance value representing an allowance value for a magnitude of deviation of each of the control variables from a target value, or an allowance value for an excess amount and an allowance value for an underachievement amount of each of the control variables from a target value, The manipulated variable target value calculation unit calculates the target values ​​of the manipulated variables such that the magnitude of deviation between the predicted values ​​of the plurality of controlled variables by the prediction model and the target values ​​is averaged in accordance with the deviation allowable value.

2. The air conditioning control device according to claim 1.

3. a supply air consumption energy evaluation function storage unit that stores a supply air consumption energy evaluation function that evaluates consumption energy depending on a supply air volume from the value of the manipulated variable, The manipulated variable target value calculation unit calculates a target value of the manipulated variable so as to minimize the supply air consumption energy evaluation function when the supply air consumption energy evaluation function is a monotonically increasing function of the consumed energy, and to maximize the supply air consumption energy evaluation function when the supply air consumption energy evaluation function is a monotonically decreasing function of the consumed energy.

2. The air conditioning control device according to claim 1.

4. An operation possibility signal acquisition unit that acquires an operation possibility signal representing whether the operation variable can be operated, The operation variable target value calculation unit calculates a target value of the operation variable by setting an operation variable corresponding to the operation impossible signal acquired by the operation possible / impossible signal acquisition unit as a predetermined fixed value.

2. The air conditioning control device according to claim 1.

5. A human detection data acquisition unit that acquires human detection data representing the number of people present at a spatial position or the presence or absence of people at a spatial position; a deviation tolerance adjustment unit that adjusts, based on the human detection data acquired by the human detection data acquisition unit, to increase the deviation tolerance of a control variable corresponding to the spatial position where the number of people is relatively small and to decrease the deviation tolerance of a control variable corresponding to the spatial position where the number of people is relatively large; The air conditioning control device according to claim 2 , further comprising:

6. A human detection data acquisition unit that acquires human detection data representing the number of people present at a spatial position or the presence or absence of people at a spatial position; a control variable exclusion processing unit that excludes, from the control variables, the index corresponding to a spatial position where the number of people is represented as being equal to or less than a predetermined number based on the human detection data acquired by the human detection data acquisition unit; The air conditioning control device according to claim 3 , further comprising:

7. a declaration data acquisition unit that acquires declaration data including a declaration of discomfort of a resident present at a spatial position and information on the spatial position at which the resident who made the declaration is present; a declaration data counting unit that counts the declaration data of each spatial position acquired by the declaration data acquisition unit; a deviation allowable value adjustment unit that adjusts, for a predetermined period of time, a deviation allowable value of a control variable corresponding to a spatial position where the number of reported discomfort sensations has increased, based on the report data collected by the report data collection unit; The air conditioning control device according to claim 2 , further comprising:

8. a prediction model storage step of storing a prediction model representing an influence of a manipulated variable on each of control variables, the control variables being a set of indexes related to comfort at a plurality of different spatial positions in an indoor environment, the manipulated variable being a parameter related to an air supply volume of the air outlet that influences the control variable; a control variable target value storage step of storing a target value of each control variable; a constraint condition storage step of storing a constraint condition related to the manipulated variables; a control variable current value acquisition step of acquiring a current value of each of the control variables; an manipulated variable target value calculation step of calculating a target value of the manipulated variable based on the prediction model, the target values ​​of the controlled variables, the constraint condition, and the current values ​​of the controlled variables, such that the magnitude of deviation between the predicted values ​​of the multiple controlled variables by the prediction model and the target values ​​is leveled; An air conditioning control method comprising:

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