Thermodynamic parameter determination method, device, computer equipment and storage medium

Abstract

This application relates to a method, apparatus, computer device, and storage medium for determining thermodynamic parameters. The method includes: constructing a linear thermal parameter equation for the air conditioning load based on a preset thermodynamic model of the air conditioning load; the thermodynamic model is used to characterize the correspondence between the air conditioning thermal power and the indoor temperature; constructing an objective function and constraints for the linear thermal parameter equation using preset optimization conditions; and solving the linear thermal parameter equation based on the objective function and constraints to obtain the thermodynamic parameters of the air conditioning load. This method can accurately obtain the thermodynamic parameters of the air conditioning load, thereby improving the accuracy of the estimation of the thermodynamic parameters of the air conditioning load.

Description

Technical Field

[0001] The present application relates to the field of air conditioning control technology, and in particular to a method, device, computer equipment and storage medium for determining thermodynamic parameters. Background Art

[0002] Air conditioning loads have a certain heat and cold storage capacity, allowing for short-term power adjustments without significantly impacting user comfort, giving them a unique advantage in participating in power demand response. Obtaining the thermodynamic parameters of air conditioning loads allows for the effective calculation of their power adjustment potential, facilitating better control of air conditioning loads.

[0003] Traditional methods mainly use genetic algorithms to obtain the thermodynamic parameters of air conditioning loads. However, the traditional methods have the problem of low accuracy of the obtained thermodynamic parameters of air conditioning loads. Summary of the Invention

[0004] Based on this, it is necessary to provide a thermodynamic parameter determination method, device, computer equipment and storage medium that can improve the accuracy of the obtained air-conditioning load thermodynamic parameters to address the above technical problems.

[0005] In a first aspect, the present application provides a method for determining thermodynamic parameters. The method comprises:

[0006] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0007] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0008] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0009] In one embodiment, the optimization conditions include a first optimization condition and a second optimization condition; using the preset optimization conditions, the objective function and constraint conditions of the linear thermal parameter equation are constructed, including:

[0010] Constructing an objective function based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold;

[0011] According to the second optimization condition and the linear thermal parameter equation, a constraint condition is constructed; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0012] In one embodiment, constructing an objective function based on the first optimization condition, the square integral of the error, and the linear thermal parameter equation includes:

[0013] Use the linear thermal parameter equation to obtain the current indoor air temperature value;

[0014] Get the difference between the current indoor air temperature and the actual indoor air temperature;

[0015] The objective function is constructed based on the sum of squares of the differences and the integral of squared errors of the thermodynamic parameters.

[0016] In one embodiment, based on the objective function and the constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load, including:

[0017] Based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0018] In one embodiment, a linear thermal parameter equation of the air conditioning load is constructed based on a preset thermodynamic model of the air conditioning load, including:

[0019] Perform Euler transformation on the thermodynamic model to obtain the linear thermal parameter equation.

[0020] In one embodiment, the method further comprises:

[0021] Based on the first law of thermodynamics, a thermodynamic model is constructed using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of air-conditioning load.

[0022] In a second aspect, the present application also provides a device for determining thermodynamic parameters. The device comprises:

[0023] The first construction module is used to construct a linear thermal parameter equation of the air conditioning load based on a preset thermodynamic model of the air conditioning load; the thermodynamic model is used to characterize the corresponding relationship between the air conditioning thermal power and the indoor temperature;

[0024] The second construction module is used to construct the objective function and constraint conditions of the linear thermal parameter equation using the preset optimization conditions;

[0025] The acquisition module is used to solve the linear thermal parameter equation based on the objective function and constraint conditions to obtain the thermodynamic parameters of the air conditioning load.

[0026] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are performed:

[0027] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0028] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0029] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0030] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0031] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0032] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0033] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0034] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0035] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0036] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0037] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0038] The above-mentioned thermodynamic parameter determination method, device, computer equipment and storage medium can construct a linear thermal parameter equation of the air-conditioning load through a preset thermodynamic model of the air-conditioning load that characterizes the correspondence between the air-conditioning thermal power and the indoor temperature. Therefore, by using the preset optimization conditions, the objective function and constraint conditions of the linear thermal parameter equation can be constructed. Based on the above-mentioned objective function and constraint conditions, the linear thermal parameter equation can be accurately solved to obtain accurate thermodynamic parameters of the air-conditioning load, which is conducive to improving the accuracy of the estimation of the thermodynamic parameters of the air-conditioning load. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A diagram showing an application environment of a method for determining thermodynamic parameters in one embodiment;

[0040] Figure 2 Schematic diagram of a process for determining thermodynamic parameters in one embodiment;

[0041] Figure 3 Schematic diagram of a process for determining thermodynamic parameters in another embodiment;

[0042] Figure 4 Schematic diagram of a process for determining thermodynamic parameters in another embodiment;

[0043] Figure 5 Schematic diagram of a process for determining thermodynamic parameters in another embodiment;

[0044] Figure 6 is a structural block diagram of a device for determining thermodynamic parameters in one embodiment;

[0045] Figure 7 is a structural block diagram of a device for determining thermodynamic parameters in another embodiment;

[0046] Figure 8 It is a structural block diagram of a device for determining thermodynamic parameters in another embodiment;

[0047] Figure 9 is a structural block diagram of a device for determining thermodynamic parameters in another embodiment;

[0048] Figure 10 It is a structural block diagram of a device for determining thermodynamic parameters in another embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0050] The method for determining thermodynamic parameters provided in the embodiments of the present application can be applied to Figure 1 In the application environment shown. Figure 1 A computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 1As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store medical image data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for determining thermodynamic parameters is implemented.

[0051] In one embodiment, Figure 2 As shown, a method for determining thermodynamic parameters is provided, which is applied to Figure 1 The computer device in the example is used to illustrate the process, including the following steps:

[0052] S201 : constructing a linear thermal parameter equation of the air conditioning load according to a preset thermodynamic model of the air conditioning load; the thermodynamic model is used to characterize the corresponding relationship between the air conditioning thermal power and the indoor temperature.

[0053] Among them, the air conditioning load is a control system composed of special instruments and devices to replace manual operation to adjust the air conditioning parameters to maintain them at a given value or change according to a given rule to meet the requirements of the air-conditioned room.

[0054] Specifically, in this embodiment, a thermodynamic model of the air conditioning load can be constructed using parameters such as indoor and outdoor temperature parameters and thermodynamic parameters. The constructed thermodynamic model includes indoor and outdoor temperature parameters that affect the air conditioning load. The thermodynamic model can be used to characterize the corresponding relationship between the air conditioning thermal power and the indoor temperature. For example, the constructed thermodynamic model of the air conditioning load can be:

[0055]

[0056] In formula (1), T a (t) represents the indoor air temperature, T m (t) represents the indoor solid temperature, T o (t) represents the outdoor air temperature, R a Indicates the equivalent thermal resistance of indoor air, C a represents the equivalent heat capacity of the indoor air, R m Indicates the equivalent thermal resistance of the indoor solid, C m represents the equivalent heat capacity of indoor solids, Q(t) represents the thermal power of air conditioning load, and I(t) represents the heat generated by other heat sources in the room.

[0057] Optionally, in this embodiment, a linear thermal parameter equation of the air-conditioning load can be constructed by performing mathematical transformation on the thermodynamic model of the air-conditioning load; or, a linear thermal parameter equation of the air-conditioning load can be constructed based on the expression of the corresponding relationship between the air-conditioning thermal power and the indoor temperature in the thermodynamic model of the air-conditioning load.

[0058] S202, using preset optimization conditions, constructing the objective function and constraint conditions of the linear thermal parameter equation.

[0059] Specifically, when solving the linear thermal parameter equation of the air conditioning load, it is necessary to make the solution result reach the optimization target. Optionally, in this embodiment, the preset optimization conditions can be used to construct the objective function and constraint conditions of the linear thermal parameter equation. For example, the optimization conditions may include that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold, or that the characteristic root of the linear thermal parameter equation can satisfy a preset stability condition, etc. That is, the computer device can use the constraint condition that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold to construct the objective function and constraint conditions of the linear thermal parameter equation; or the computer device can also use the characteristic root of the linear thermal parameter equation to satisfy the preset stability condition to construct the objective function and constraint conditions of the linear thermal parameter equation. Further, as an optional implementation, in this embodiment, the objective function can be established using the mean square error (MSE) or the mean absolute error (MAE).

[0060] S203 , solving the linear thermal parameter equation based on the objective function and the constraint conditions to obtain the thermodynamic parameters of the air conditioning load.

[0061] Optionally, in this embodiment, based on the objective function and constraints, an existing optimization algorithm can be used to solve the linear thermal parameter equation to obtain a highly accurate estimate of the thermodynamic parameters of the air conditioning load. For example, an optimization algorithm such as the monkey swarm algorithm can be used to solve the thermal linear parameter equation to obtain the thermodynamic parameters of the air conditioning load.

[0062] In the above-mentioned thermodynamic parameter determination method, a linear thermal parameter equation of the air-conditioning load can be constructed by using a preset thermodynamic model of the air-conditioning load that characterizes the correspondence between the air-conditioning thermal power and the indoor temperature. Then, by using the preset optimization conditions, the objective function and constraint conditions of the linear thermal parameter equation can be constructed. Based on the above-mentioned objective function and constraint conditions, the linear thermal parameter equation can be accurately solved to obtain accurate thermodynamic parameters of the air-conditioning load, which is beneficial to improving the accuracy of the estimation of the thermodynamic parameters of the air-conditioning load.

[0063] In the above scenario of constructing the objective function and constraint conditions of the linear thermal parameter equation using the preset optimization conditions, the optimization conditions may include a first optimization condition that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold value and a second optimization condition that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition. In one embodiment, Figure 3 As shown, the above S202 includes:

[0064] S301, constructing an objective function based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold.

[0065] The squared integral of the error is a performance indicator expressed as the integral of a function representing the deviation between the system's expected output and actual output or the main feedback signal. The first optimization condition includes the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value being less than a preset threshold. It is understood that the smaller the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value, the better the optimization effect of the objective function. Optionally, in this embodiment, a linear thermal parameter equation can be used to obtain the current indoor air temperature value, and then the squared integral of the error between the current indoor air temperature value, the first optimization condition, and the thermodynamic parameters can be used to construct the objective function.

[0066] S302 , constructing a constraint condition based on the second optimization condition and the linear thermal parameter equation; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0067] Specifically, in order to make the linear thermal parameter equation converge, the characteristic roots of the linear thermal parameter equation must satisfy the stability condition |λ 1,2 |≤1, that is, the second optimization condition is the characteristic root of the linear thermal parameter equation |λ 1,2 |≤1. For example, based on the thermodynamic model of the air-conditioning load, the linear thermal parameter equation of the air-conditioning load is constructed as follows: For example, the characteristic root λ of the linear thermal parameter equation is 1,2 It can be obtained by solving the characteristic equation of formula (2): Further, we can simplify it to get: 2 -(A 11 +A 22 )λ+A 11 A 22 +A 12 A 21 =0, the characteristic roots of the linear thermal parameter equation can be solved as:

[0068]

[0069] Among them, in formula (2) and formula (3), A 11 、A 12 、A 21 、A 22 , B1 and B2 represent thermodynamic parameters, T a (t) represents the actual indoor air temperature at the current moment, T a (t-1) represents the actual indoor air temperature at the previous moment, T m (t) represents the current indoor solid temperature value, T m (t-1) represents the indoor solid temperature value at the previous moment, T o (t-1) represents the outdoor air temperature value at the previous moment, Q(t-1) represents the thermal power of the air conditioning load at the previous moment, and I(t-1) represents the heat generated by other heat sources in the room at the previous moment.

[0070] According to the optimization condition |λ 1,2 |≤1 and the range of thermodynamic parameters, we can get the same result as A 12 、A 21 , B1 and B2 related constraints: In addition, it can be seen that this constraint is a complex nonlinear constraint.

[0071] In this embodiment, since the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than the preset threshold value, the objective function can be accurately constructed according to the first optimization condition, the square integral of the error of the thermodynamic parameters and the linear thermal parameter equation. The second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies the preset stability condition. Therefore, according to the second optimization condition and the linear thermal parameter equation, the constraint condition can be accurately constructed. Under the joint limitation of the objective function and the constraint condition, the linear thermal parameter equation can be accurately solved to obtain the thermodynamic parameters of the air-conditioning load with relatively high accuracy.

[0072] In the scenario where the objective function is constructed based on the first optimization condition, the square integral of the error of the thermodynamic parameters and the linear thermal parameter equation, it is necessary to first obtain the difference between the current indoor air temperature value and the actual indoor air temperature value. In one embodiment, Figure 4 As shown, the above S301 includes:

[0073] S401, using a linear thermal parameter equation to obtain the current indoor air temperature value.

[0074] The current indoor air temperature is calculated using a linear thermal parameter equation. Optionally, the current indoor air temperature can be obtained using the actual indoor air temperature measured at the previous sampling moment, the outdoor air temperature measured, the indoor solid temperature measured, the thermal power measured for the air conditioning load, and the heat generated by other heat sources in the room, and the linear thermal parameter equation. For example, the calculation formula can be used: Get the current indoor air temperature value, where A 11 、A 12 , B1 and B2 represent thermodynamic parameters, Indicates the current indoor air temperature, T a (t-1) represents the actual indoor air temperature at the previous moment, T m (t-1) represents the indoor solid temperature value at the previous moment, T o (t-1) represents the outdoor air temperature value at the previous moment, Q(t-1) represents the thermal power of the air conditioning load at the previous moment, and I(t-1) represents the heat generated by other heat sources in the room at the previous moment. These measured values ​​at the previous moment can be measured using temperature sensors and power sensors.

[0075] S402: Obtain the difference between the current indoor air temperature and the actual indoor air temperature.

[0076] Optionally, in this embodiment, the actual indoor air temperature value can be obtained through an indoor temperature sensor. Optionally, after obtaining the current indoor air temperature value and the actual indoor air temperature value, the difference between the current indoor air temperature value and the actual indoor air temperature value can be obtained by subtracting the current indoor air temperature value from the actual indoor air temperature value: Where, Indicates the current indoor air temperature, T a (t) represents the actual indoor air temperature.

[0077] S403: Construct an objective function based on the sum of squares of the differences and the square integral of the errors of the thermodynamic parameters.

[0078] Optionally, in this embodiment, the objective function may be constructed by integrating the square of the error. For example, the objective function constructed in this embodiment is expressed as:

[0079]

[0080] In formula (5), ISE represents the integral of the square of the error, Indicates the difference between the current indoor air temperature and the actual indoor air temperature.

[0081] In this embodiment, the linear thermal parameter equation of the air-conditioning load can be used to accurately obtain the current indoor air temperature value, thereby obtaining the difference between the current indoor air temperature value and the actual indoor air temperature value. Furthermore, based on the sum of the squares of the difference between the current indoor air temperature value and the actual indoor air temperature value and the square integral of the error of the thermodynamic parameters, the objective function can be accurately constructed, and the linear thermal parameter equation can be solved using the objective function, thereby avoiding the influence of excessive errors on the results of the thermodynamic parameters of the air-conditioning load obtained by the solution.

[0082] In the above scenario where the linear thermal parameter equation is solved based on the objective function and the constraints to obtain the thermodynamic parameters of the air-conditioning load, in one embodiment, the above S203 includes: based on the objective function and the constraints, using the monkey swarm algorithm to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0083] Specifically, the monkey colony algorithm is used to solve the linear thermal parameter equation. The specific steps include:

[0084] ① Initialization, assuming there are 5 monkeys, each monkey corresponds to an initial position of a thermodynamic parameter {A 11 (i),A 12 (i),A 21 (i),A 22 (i), B1(i), B2(i)}, where i represents the i-th monkey;

[0085] ②Perform the "climb" operation to correct the position of each monkey according to the gradient of the objective function, so that the monkey's position continues to approach the optimal value of the objective function;

[0086] ③ Perform the "look" operation, randomly generate positions within the field of view parameters and calculate the value of the objective function. If a better position exists, the monkey group position is updated to the better position, otherwise continue to perform the "climb" operation;

[0087] ④ Perform the "jump" operation, generate a real number within a certain interval, and calculate the center of gravity of all monkeys. All monkeys flip to the new search range in the direction of the center of gravity and search again;

[0088] ⑤Calculate the value of the objective function and determine whether the search termination condition has been reached. If so, the algorithm ends and outputs the optimal value. Otherwise, continue to perform the "climb" operation. Through the above steps, the thermodynamic parameter A is finally obtained. 11 , A 12 , A 21 , A 22 , B1, B2 estimation results.

[0089] In this embodiment, based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation. Since the monkey swarm algorithm is used to optimize more effectively and avoid falling into local optimality, it can improve the optimization effect of the linear thermal parameter equation, thereby accurately obtaining the thermodynamic parameters.

[0090] In the scenario of constructing a thermal linear parameter equation of the air-conditioning load based on a preset thermodynamic model of the air-conditioning load, in one embodiment, the above S201 includes: performing Euler transformation on the thermodynamic model to obtain a linear thermal parameter equation.

[0091] Among them, the Euler transform is a simple and common discretization method. The bilinear transform can easily discretize the linear continuous equation. Therefore, in this embodiment, in order to convert the differential equation into a difference equation, the thermodynamic model can be subjected to the Euler transform to obtain a discretized recursive calculation formula. For example, the process of performing the Euler transform on the thermodynamic model is described below: For further parameter estimation, the difference equation can be obtained by performing the Euler transform on Equation (1):

[0092]

[0093] It is easy to see from the difference equation (5) that T a (t) and T m (t) and thermodynamic parameter R a 、C a 、R m and C m It presents a complex nonlinear relationship. To facilitate parameter estimation, equation (5) is simplified to obtain the linear thermal parameter equation as follows:

[0094]

[0095] In formula (2), A 11 、A 12 、A 21 、A 22 , B1 and B2 are thermodynamic parameters of air conditioning load, where

[0096] Among them, T a (t) represents the indoor air temperature, T a (t-1) represents the actual indoor air temperature at the previous moment, T m (t) represents the indoor solid temperature, T m (t-1) represents the indoor solid temperature at the previous moment, T o (t-1) represents the outdoor air temperature at the previous moment, R a Indicates the equivalent thermal resistance of indoor air, C arepresents the equivalent heat capacity of the indoor air, R m Indicates the equivalent thermal resistance of the indoor solid, C m represents the equivalent heat capacity of indoor solids, Q(t-1) represents the thermal power of the air-conditioning load at the previous moment, and I(t-1) represents the heat generated by other heat sources in the room at the previous moment.

[0097] In this embodiment, when performing an Euler transformation on the thermodynamic model of the air conditioning load, it is necessary to first establish the thermodynamic model. The process of establishing the thermodynamic model is described below. Optionally, in this embodiment, a thermodynamic model can be constructed based on the first law of thermodynamics using indoor temperature parameters, outdoor temperature parameters, and the thermal power parameters of the air conditioning load. The first law of thermodynamics is a law of energy conservation and transformation within the field of thermal phenomena, reflecting the conservation of different forms of energy during transmission and conversion. For example, the constructed thermodynamic model of the air conditioning load can be described in equation (1) in S201 above.

[0098] In this embodiment, the process of performing Euler transformation on the thermodynamic model is relatively simple. Therefore, the thermodynamic model can be transformed simply and effectively into a differential equation, so that a linear thermal parameter equation of the air-conditioning load can be established based on the differential equation obtained by the transformation, and the thermodynamic parameters of the air-conditioning load can be effectively estimated using the linear thermal parameter equation.

[0099] The following describes an embodiment of the present disclosure in conjunction with a specific thermodynamic parameter determination scenario. Figure 5 As shown, the method includes the following steps:

[0100] S1, based on the first law of thermodynamics, uses indoor temperature parameters, outdoor temperature parameters, and thermal power parameters of air conditioning load to construct a thermodynamic model; wherein the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature.

[0101] S2, perform Euler transformation on the thermodynamic model to obtain Figure 5 The linear thermal parameter equation is shown.

[0102] S3, using the linear thermal parameter equation to obtain the current indoor air temperature value.

[0103] S4, obtaining the difference between the current indoor air temperature value and the actual indoor air temperature value.

[0104] S5, based on the sum of the squares of the difference between the current indoor air temperature and the actual indoor air temperature and the square integral of the error of the thermodynamic parameters, construct the objective function, and according to the characteristic roots of the linear thermal parameter equation to meet the preset stability conditions and the linear thermal parameter equation, construct the constraint conditions, that is, construct Figure 5 The optimization model shown in .

[0105] S6, based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0106] It should be noted that for the descriptions in S1-S6 above, reference can be made to the relevant descriptions in the above embodiments, and the effects are similar, so this embodiment will not be repeated here.

[0107] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0108] Based on the same inventive concept, embodiments of the present application also provide a thermodynamic parameter determination device for implementing the aforementioned thermodynamic parameter determination method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the thermodynamic parameter determination device provided below can be found in the above-described limitations of the thermodynamic parameter determination method and are not further elaborated here.

[0109] In one embodiment, Figure 6 As shown, a thermodynamic parameter determination device is provided, comprising: a first building module 10, a second building module 11 and an acquisition module 12, wherein:

[0110] The first construction module 10 is used to construct a linear thermal parameter equation of the air-conditioning load according to a preset thermodynamic model of the air-conditioning load; the thermodynamic model is used to characterize the corresponding relationship between the air-conditioning thermal power and the indoor temperature.

[0111] The second building module 11 is used to build the objective function and constraint conditions of the linear thermal parameter equation using preset optimization conditions.

[0112] The acquisition module 12 is used to solve the linear thermal parameter equation based on the objective function and the constraint conditions to obtain the thermodynamic parameters of the air conditioning load.

[0113] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0114] In one embodiment, Figure 7 As shown, the above-mentioned optimization conditions include a first optimization condition and a second optimization condition; the above-mentioned second building block 11 includes a first building unit 111 and a second building unit 112; wherein:

[0115] The first construction unit 111 is used to construct an objective function based on a first optimization condition, an error square integral of a thermodynamic parameter, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold.

[0116] The second constructing unit 112 is used to construct a constraint condition according to the second optimization condition and the linear thermal parameter equation; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0117] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0118] In one embodiment, the first construction unit 111 is specifically used to obtain the current indoor air temperature value using a linear thermal parameter equation; obtain the difference between the current indoor air temperature value and the actual indoor air temperature value; and construct an objective function based on the sum of the squares of the differences and the square integral of the errors of the thermodynamic parameters.

[0119] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0120] In one embodiment, Figure 8 As shown, the acquisition module 12 includes an acquisition unit 121, wherein:

[0121] The acquisition unit 121 is used to solve the linear thermal parameter equation based on the objective function and the constraint conditions using the monkey colony algorithm to obtain the thermodynamic parameters.

[0122] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0123] In one embodiment, Figure 9 As shown, the first building block 10 includes a third building unit 101, wherein:

[0124] The third construction unit 101 is used to perform Euler transformation on the thermodynamic model to obtain a linear thermal parameter equation.

[0125] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0126] In one embodiment, Figure 10 As shown, the above device further includes: a third building module 13; wherein:

[0127] The third construction module 13 is used to construct a thermodynamic model based on the first law of thermodynamics using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of the air-conditioning load.

[0128] The thermodynamic parameter determination device provided in this embodiment can execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0129] Each module in the above-mentioned thermodynamic parameter determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0130] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0131] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0132] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0133] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0134] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0135] Constructing an objective function based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold;

[0136] According to the second optimization condition and the linear thermal parameter equation, a constraint condition is constructed; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0137] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0138] Use the linear thermal parameter equation to obtain the current indoor air temperature value;

[0139] Get the difference between the current indoor air temperature and the actual indoor air temperature;

[0140] The objective function is constructed based on the sum of squares of the differences and the integral of squared errors of the thermodynamic parameters.

[0141] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0142] Based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0143] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0144] Perform Euler transformation on the thermodynamic model to obtain the linear thermal parameter equation.

[0145] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0146] Based on the first law of thermodynamics, a thermodynamic model is constructed using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of air-conditioning load.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0148] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0149] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0150] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0151] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0152] Constructing an objective function based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold;

[0153] According to the second optimization condition and the linear thermal parameter equation, a constraint condition is constructed; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0154] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0155] Use the linear thermal parameter equation to obtain the current indoor air temperature value;

[0156] Get the difference between the current indoor air temperature and the actual indoor air temperature;

[0157] The objective function is constructed based on the sum of squares of the differences and the integral of squared errors of the thermodynamic parameters.

[0158] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0159] Based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0161] Perform Euler transformation on the thermodynamic model to obtain the linear thermal parameter equation.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0163] Based on the first law of thermodynamics, a thermodynamic model is constructed using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of air-conditioning load.

[0164] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0165] Based on the preset thermodynamic model of air conditioning load, a linear thermal parameter equation of air conditioning load is constructed; the thermodynamic model is used to characterize the corresponding relationship between air conditioning thermal power and indoor temperature;

[0166] Using the preset optimization conditions, the objective function and constraints of the linear thermal parameter equation are constructed;

[0167] Based on the objective function and constraints, the linear thermal parameter equation is solved to obtain the thermodynamic parameters of the air conditioning load.

[0168] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0169] Constructing an objective function based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and a linear thermal parameter equation; the first optimization condition includes that the difference between the indoor air temperature value obtained by the thermal linear parameter equation and the actual indoor air temperature value is less than a preset threshold;

[0170] According to the second optimization condition and the linear thermal parameter equation, a constraint condition is constructed; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition.

[0171] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0172] Use the linear thermal parameter equation to obtain the current indoor air temperature value;

[0173] Get the difference between the current indoor air temperature and the actual indoor air temperature;

[0174] The objective function is constructed based on the sum of squares of the differences and the integral of squared errors of the thermodynamic parameters.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0176] Based on the objective function and constraints, the monkey swarm algorithm is used to solve the linear thermal parameter equation to obtain the thermodynamic parameters.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0178] Perform Euler transformation on the thermodynamic model to obtain the linear thermal parameter equation.

[0179] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0180] Based on the first law of thermodynamics, a thermodynamic model is constructed using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of air-conditioning load.

[0181] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0182] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0183] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0184] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining thermodynamic parameters, characterized in that: The method comprises: Constructing a linear thermal parameter equation of the air conditioning load based on a preset thermodynamic model of the air conditioning load; the thermodynamic model is used to characterize the corresponding relationship between the air conditioning thermal power and the indoor temperature; constructing an objective function of the linear thermal parameter equation based on a first optimization condition, an integral of squared errors of thermodynamic parameters, and the linear thermal parameter equation; the first optimization condition including that a difference between an indoor air temperature value obtained by the linear thermal parameter equation and an actual indoor air temperature value is less than a preset threshold; Constructing a constraint condition based on a second optimization condition and the linear thermal parameter equation; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition; Solving the linear thermal parameter equation based on the objective function and the constraint conditions to obtain thermodynamic parameters of the air conditioning load; The step of constructing an objective function of the linear thermal parameter equation based on the first optimization condition, the square integral of the error of the thermodynamic parameter, and the linear thermal parameter equation comprises: The linear thermal parameter equation is used to obtain the current indoor air temperature value; the difference between the current indoor air temperature value and the actual indoor air temperature value is obtained; and the objective function is constructed based on the square sum of the differences and the square integral of the error of the thermodynamic parameters.

2. The method according to claim 1, characterized in that The method of obtaining the current indoor air temperature value by using the linear thermal parameter equation includes: By calculation formula: Obtaining the current indoor air temperature value; Among them, A 11 、A 12 , B1 and B2 represent the thermodynamic parameters, Indicates the current indoor air temperature value, T a (t-1) represents the actual indoor air temperature at the previous moment, T m (t-1) represents the indoor solid temperature value at the previous moment, T o (t-1) represents the outdoor air temperature value at the previous moment, Q(t-1) represents the thermal power of the air conditioning load at the previous moment, and I(t-1) represents the heat generated by other indoor heat sources at the previous moment.

3. The method according to claim 1, characterized in that The objective function is: Others, ISE represents the integrated square of the error, Indicates the difference between the current indoor air temperature and the actual indoor air temperature.

4. The method according to claim 1, wherein Solving the linear thermal parameter equation based on the objective function and the constraint conditions to obtain the thermodynamic parameters of the air conditioning load includes: Based on the objective function and the constraint conditions, the linear thermal parameter equation is solved using the monkey colony algorithm to obtain the thermodynamic parameters.

5. The method according to any one of claims 1 to 4, characterized in that The linear thermal parameter equation of the air conditioning load is constructed based on the preset thermodynamic model of the air conditioning load, including: Performing Euler transformation on the thermodynamic model to obtain the linear thermal parameter equation.

6. The method according to claim 5, characterized in that The method further comprises: Based on the first law of thermodynamics, the thermodynamic model is constructed using indoor temperature parameters, outdoor temperature parameters and thermal power parameters of the air-conditioning load.

7. A device for determining thermodynamic parameters, characterized in that: The device comprises: A first construction module is used to construct a linear thermal parameter equation of the air conditioning load based on a preset thermodynamic model of the air conditioning load; the thermodynamic model is used to characterize the corresponding relationship between the air conditioning thermal power and the indoor temperature; A second construction module is configured to obtain a current indoor air temperature value using the linear thermal parameter equation; obtain a difference between the current indoor air temperature value and the actual indoor air temperature value; construct an objective function based on the sum of squares of the difference and the square integral of the error of the thermodynamic parameter; and construct a constraint condition based on a second optimization condition and the linear thermal parameter equation; the second optimization condition includes that the characteristic root of the linear thermal parameter equation satisfies a preset stability condition; The acquisition module is used to solve the linear thermal parameter equation based on the objective function and the constraint conditions to obtain the thermodynamic parameters of the air-conditioning load.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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