A building thermal process simulation method based on Lagrange interpolation integration method

Abstract

The present invention relates to the field of building environment technology, and discloses a building thermal process simulation method based on the Lagrange interpolation integral method. The method comprises the following steps: obtaining building physical parameters and building boundary conditions of a target building, constructing a thermal process state space model of the target building, performing model analysis and eigenvalue decomposition, and determining an eigenvalue matrix and an eigenvector matrix; constructing an integral coefficient matrix according to a first moment and a second moment; and calculating a temperature vector according to the eigenvalue matrix, the eigenvector matrix, and the integral coefficient matrix, which is used as a building thermal process simulation output of the target building. The method can solve the problem that a thermal process simulation program lacks a high-precision matrix calculation format, ensure the prediction accuracy of temperature changes of a building under different environmental conditions, provide data support for building thermal distribution simulation and optimization of building heating system design, reduce energy waste, and provide a scientific basis and technical support for the creation of energy-saving buildings and comfortable environments.

Description

Technical Field

[0001] The present invention relates to the technical field of building environment, and in particular to a building thermal process simulation method based on Lagrange interpolation integral method. Background Art

[0002] Building thermal simulation is a method for evaluating thermal performance by simulating changes in the building's internal thermal environment. Its fundamental principle is based on the physical principles of heat exchange processes such as conduction, convection, and radiation. By modeling the building's structure, materials, and environmental characteristics in detail, simulation software can calculate the building's temperature changes under different environmental conditions. This can then be used to assess the building's thermal performance and energy consumption. It is commonly used in areas such as optimizing building performance design, evaluating energy consumption and energy-saving solutions, and analyzing building environmental adaptability.

[0003] Currently, common building temperature change simulation software includes DeST, which is based on state-space models, and EnergyPlus and eQuest, which are derived from DOE series software. These models are generally based on energy balance methods and weight coefficient methods, among others. However, these methods have the following problems: 1. Separate equations are calculated for each node, making it difficult to utilize tools such as high-performance linear algebra libraries such as Blas. 2. Thermal disturbances per unit time period are usually only linearly interpolated between two time points, which cannot guarantee accuracy while being compatible with the thermal inertia of the building. This results in a generally short simulation time step and slow simulation calculation speed. Therefore, traditional methods cannot accurately predict temperature changes in buildings under different environmental conditions. Summary of the Invention

[0004] In view of this, the present invention proposes a building thermal process simulation method based on the Lagrange interpolation integral method, which can solve the problem of the lack of high-precision matrix calculation format in thermal process simulation programs, ensure the prediction accuracy of temperature changes in buildings under different environmental conditions, and provide data support for building thermal distribution simulation and optimization of building heating system design, thereby improving energy efficiency, reducing energy waste, and providing a scientific basis and technical support for the creation of energy-saving buildings and comfortable environments.

[0005] The present invention proposes a building thermal process simulation method based on Lagrange interpolation integral method, comprising:

[0006] Acquiring building physical parameters and building boundary conditions of a target building, and constructing a thermal process state space model of the target building based on the building physical parameters and building boundary conditions;

[0007] Performing model analysis and eigenvalue decomposition on the thermal process state space model to determine an eigenvalue matrix and an eigenvector matrix;

[0008] Obtaining a first moment and a second moment, and constructing an integral coefficient matrix according to the first moment and the second moment;

[0009] The temperature vector of the target building is calculated according to the eigenvalue matrix, the eigenvector matrix and the integral coefficient matrix, and the temperature vector is output as a building thermal process simulation output of the target building.

[0010] Furthermore, when obtaining the building physical parameters and building boundary conditions of the target building and constructing the thermal process state space model of the target building based on the building physical parameters and building boundary conditions, it includes:

[0011] constructing a first building parameter matrix C and a second building parameter matrix A based on the building physical parameters, wherein the building physical parameters include building density, building specific heat capacity, building volume and building temperature;

[0012] ;

[0013] ;

[0014] Among them, i and j represent the nodes of the target building after spatial discretization. is the building density of the i-th node, is the building specific heat capacity of the i-th node, is the building volume of the i-th node, is the second-order symmetric tensor between the i-th node and the j-th node;

[0015] ;

[0016] in, is the heat exchange coefficient between the i-th node and the j-th node, is the heat exchange coefficient between the i-th node and the external disturbance of the building, k is the external disturbance of the building;

[0017] Constructing a building condition matrix B based on the building boundary conditions;

[0018] ;

[0019] in, is the influence coefficient of building external disturbance k on the i-th node;

[0020] A thermal process state space model of the target building is constructed according to the first building parameter matrix C, the second building parameter matrix A and the building condition matrix B.

[0021] Furthermore, when constructing the thermal process state space model of the target building according to the first building parameter matrix C, the second building parameter matrix A and the building condition matrix B, it includes:

[0022] ;

[0023] in, is the state space model of the thermal process of the target building, , is the building temperature of the i-th node, Q is the internal and external disturbance input of the building, , is the value of the building external disturbance k.

[0024] Furthermore, when performing model analysis and eigenvalue decomposition on the thermal process state space model to determine the eigenvalue matrix and the eigenvector matrix, the following steps are included:

[0025] Perform model analysis on the thermal process state space model to construct the first coefficient matrix and the second coefficient matrix ;

[0026] For the first coefficient matrix and the second coefficient matrix Perform eigenvalue decomposition to obtain the eigenvalue matrix and the eigenvector matrix P, where the eigenvalue matrix is a diagonal matrix, and the eigenvector matrix satisfies , the eigenvalue decomposition satisfies .

[0027] Furthermore, when obtaining the first moment and the second moment, and constructing an integral coefficient matrix according to the first moment and the second moment, the method includes:

[0028] Get the first moment , get the second moment ;

[0029]

[0030] in, is the integral coefficient matrix, is the eigenvalue matrix The i-th eigenvalue of is the allowable error coefficient, e is a constant, x is the integral variable, ∏ is the multiplication symbol, 0≤m≤N, 0≤N≤4, 0≤n≤N.

[0031] Furthermore, when calculating the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix and the integral coefficient matrix, it includes:

[0032] ;

[0033] in, For the target building at the second moment The temperature vector, is the temperature vector corresponding to the first moment, It is the internal and external disturbance input of the building from the first moment to the second moment.

[0034] Furthermore, before the temperature vector is used as the building thermal process simulation output of the target building, the method further includes:

[0035] Obtaining a preset time setting value, determining whether the second time is greater than the time setting value, and if so, using the temperature vector as a building thermal process simulation output of the target building;

[0036] If not, determining whether the thermal process state space model is a time-invariant model; if so, reacquiring a new first moment and a new second moment, and constructing a new integral coefficient matrix according to the new first moment and the new second moment;

[0037] If not, new building physical parameters and new building boundary conditions of the target building are re-acquired, and a new thermal process state space model of the target building is constructed based on the new building physical parameters and new building boundary conditions.

[0038] Furthermore, after the temperature vector is used as the building thermal process simulation output of the target building, the method further includes:

[0039] Collecting temperature vectors corresponding to the target building at multiple moments;

[0040] Sort all temperature vectors by numerical value and determine the maximum temperature vector and the minimum temperature vector;

[0041] Calculate the mean of the temperature vectors corresponding to all temperature vectors;

[0042] Selecting the first ΔR1 temperature vectors between the maximum temperature vector and the mean of the temperature vectors, and selecting the first ΔR2 temperature vectors between the minimum temperature vector and the mean of the temperature vectors;

[0043] Constructing a first temperature vector sequence based on the first ΔR1 temperature vectors and the first ΔR2 temperature vectors;

[0044] Constructing a second temperature vector sequence based on all remaining temperature vectors;

[0045] A temperature change factor of the target building is calculated based on the first temperature vector sequence and the second temperature vector sequence.

[0046] Furthermore, when calculating the temperature change factor of the target building based on the first temperature vector sequence and the second temperature vector sequence, the method includes:

[0047] sorting the first temperature vector sequence by numerical value, and extracting a first maximum temperature vector and a first minimum temperature vector corresponding to the first temperature vector sequence;

[0048] sorting the second temperature vector sequence by numerical value, and extracting the second maximum temperature vector and the second minimum temperature vector corresponding to the second temperature vector sequence;

[0049] Calculating a first temperature vector mean corresponding to the first temperature vector sequence, and marking the first temperature vector mean in the first temperature vector sequence as a first temperature vector marking point;

[0050] Calculating a second temperature vector mean corresponding to the second temperature vector sequence, and marking the second temperature vector mean in the second temperature vector sequence as a second temperature vector marking point;

[0051] Counting the number of first temperature vectors Δa1 between the first temperature vector marking point and the first minimum temperature vector;

[0052] Counting the number of second temperature vectors Δa2 between the second temperature vector marking point and the second maximum temperature vector;

[0053] A first temperature vector calculation coefficient a3 is calculated according to the first temperature vector quantity Δa1 and the second temperature vector quantity Δa2, wherein: , is the total number of all temperature vectors;

[0054] Counting the number of third temperature vectors Δw1 between the first temperature vector marking point and the first maximum temperature vector;

[0055] Counting the number of fourth temperature vectors Δw2 between the second temperature vector marking point and the second minimum temperature vector;

[0056] The second temperature vector calculation coefficient w3 is calculated according to the third temperature vector quantity Δw1 and the fourth temperature vector quantity Δw2, wherein: ;

[0057] Calculating an absolute value of a coefficient difference between the first temperature vector calculation coefficient and the second temperature vector calculation coefficient, and calculating a coefficient sum of the first temperature vector calculation coefficient and the second temperature vector calculation coefficient;

[0058] The ratio of the absolute value of the coefficient difference to the coefficient sum is calculated and used as the temperature change factor of the target building.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] The present invention discloses a building thermal process simulation method based on the Lagrange interpolation integral method, which obtains building physical parameters and building boundary conditions of a target building, constructs a thermal process state space model of the target building; performs model analysis and eigenvalue decomposition on the thermal process state space model, determines an eigenvalue matrix and an eigenvector matrix; constructs an integral coefficient matrix according to a first moment and a second moment; calculates the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix and the integral coefficient matrix, and uses the temperature vector as the building thermal process simulation output of the target building. The method can solve the problem that a thermal process simulation program lacks a high-precision matrix calculation format, ensures the prediction accuracy of temperature changes of a building under different environmental conditions, provides data support for building thermal distribution simulation and optimization of building heating system design, reduces energy waste, and provides a scientific basis and technical support for the creation of energy-saving buildings and comfortable environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0062] Figure 1 A schematic flow chart of a method for simulating building thermal processes based on the Lagrange interpolation integral method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0064] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides a building thermal process simulation method based on the Lagrange interpolation integral method, including:

[0065] S110: Acquire building physical parameters and building boundary conditions of a target building, and construct a thermal process state space model of the target building based on the building physical parameters and building boundary conditions;

[0066] In some embodiments of the present application, when obtaining building physical parameters and building boundary conditions of a target building and constructing a thermal process state space model of the target building based on the building physical parameters and building boundary conditions, the process includes:

[0067] constructing a first building parameter matrix C and a second building parameter matrix A based on the building physical parameters, wherein the building physical parameters include building density, building specific heat capacity, building volume and building temperature;

[0068] ;

[0069] ;

[0070] Among them, i and j represent the nodes of the target building after spatial discretization. is the building density of the i-th node, is the building specific heat capacity of the i-th node, is the building volume of the i-th node, is the second-order symmetric tensor between the i-th node and the j-th node;

[0071] ;

[0072] in, is the heat exchange coefficient between the i-th node and the j-th node, is the heat exchange coefficient between the i-th node and the external disturbance of the building, k is the external disturbance of the building;

[0073] Constructing a building condition matrix B based on the building boundary conditions;

[0074] ;

[0075] in, is the influence coefficient of building external disturbance k on the i-th node;

[0076] A thermal process state space model of the target building is constructed according to the first building parameter matrix C, the second building parameter matrix A and the building condition matrix B.

[0077] In this embodiment, the building physical parameters include building density, building specific heat capacity, building volume and building temperature.

[0078] In this embodiment, the building boundary conditions include outdoor temperature, solar radiation, heat dissipation of personnel and equipment, etc.

[0079] In this embodiment, the enclosing structures such as walls, ceilings, and floors are divided into 3-5 nodes along the thickness, and the entire volume area of ​​the room is divided into one node.

[0080] In this embodiment, is the heat exchange coefficient between the i-th node and the j-th node. The heat exchange coefficient quantifies the rate of energy exchange between two nodes through various forms of heat transfer. Heat exchange relationships include heat conduction, convection heat transfer on the inner wall, air infiltration through interior doors and windows, and radiation from the inner wall.

[0081] Specific explanation:

[0082] Conduction: The direct transfer of heat through solid materials (such as walls and floors), described by Fourier's law.

[0083] Convection heat transfer on the inner wall: The heat exchange between the air and the wall is described by the convection heat transfer coefficient, which depends on the air flow rate, temperature difference and surface roughness.

[0084] Air infiltration through indoor doors and windows: Heat exchange caused by air infiltration through gaps, which is related to air flow and density.

[0085] Internal wall radiation: Radiation heat transfer between surfaces, described by the Stefan-Boltzmann law.

[0086] It should be noted that the above specific descriptions and corresponding mathematical formulas are already public and mature in traditional methods and will not be repeated here.

[0087] In this embodiment, the heat exchange coefficient between the node i and the external disturbance k is a comprehensive parameter used to quantify the heat exchange rate between the node i and the external disturbance k.

[0088] Specific explanation:

[0089] External Convection: The convective heat transfer between outdoor air and the exterior surface of a building (such as exterior walls and roofs), which is determined by wind speed, surface roughness, etc.

[0090] Air Infiltration through Doors and Windows: Cold air seeps into the room through gaps in doors and windows and directly mixes with node i (indoor air), resulting in heat loss.

[0091] It should be noted that the above specific descriptions and corresponding mathematical formulas are already public and mature in traditional methods and will not be repeated here.

[0092] In this embodiment, the influence coefficient is usually represented by a heat exchange coefficient.

[0093] In some embodiments of the present application, when constructing the thermal process state space model of the target building according to the first building parameter matrix C, the second building parameter matrix A, and the building condition matrix B, the process includes:

[0094] ;

[0095] in, is the state space model of the thermal process of the target building, , is the building temperature of the i-th node, Q is the internal and external disturbance input of the building, , is the value of the building external disturbance k.

[0096] The beneficial effect of the above technical solution is that the present invention can accurately determine the thermal process state space model of the target building, lay the foundation for the thermal process simulation of the target building, and significantly improve the computational efficiency of the thermal process simulation of the target building.

[0097] S120: performing model analysis and eigenvalue decomposition on the thermal process state space model to determine an eigenvalue matrix and an eigenvector matrix;

[0098] In some embodiments of the present application, when performing model analysis and eigenvalue decomposition on the thermal process state space model to determine the eigenvalue matrix and the eigenvector matrix, the following steps are included:

[0099] Perform model analysis on the thermal process state space model to construct the first coefficient matrix and the second coefficient matrix ;

[0100] For the first coefficient matrix and the second coefficient matrix Perform eigenvalue decomposition to obtain the eigenvalue matrix and the eigenvector matrix P, where the eigenvalue matrix is a diagonal matrix, and the eigenvector matrix satisfies , the eigenvalue decomposition satisfies .

[0101] In this embodiment, the eigenvalue decomposition method is relatively mature and will not be repeated here. That's it.

[0102] The beneficial effect of the above technical solution is that the present invention has the following advantages: and the second coefficient matrix Perform eigenvalue decomposition to obtain the eigenvalue matrix And the eigenvector matrix P, which provides data support for calculating the temperature vector of the target building and ensures the simulation accuracy of the temperature vector of the target building.

[0103] S130: Obtain a first moment and a second moment, and construct an integral coefficient matrix according to the first moment and the second moment;

[0104] In some embodiments of the present application, when obtaining the first moment and the second moment, and constructing an integral coefficient matrix according to the first moment and the second moment, the method includes:

[0105] Get the first moment , get the second moment ;

[0106]

[0107] in, is the integral coefficient matrix, is the eigenvalue matrix The i-th eigenvalue of is the allowable error coefficient, e is a constant, x is the integral variable, ∏ is the multiplication symbol, 0≤m≤N, 0≤N≤4, 0≤n≤N.

[0108] In this embodiment, Preferably 10 -5 .

[0109] In this embodiment, the number of eigenvalues ​​is consistent with the number of nodes, and therefore, is also represented by i.

[0110] In this embodiment, the consecutive multiplication refers to the consecutive multiplication of the result when m is 0 and the result when m is 1, 2, 3, ..., N, wherein the result when m is n is ignored.

[0111] The beneficial effect of the above technical solution is that the present invention constructs an integral coefficient matrix according to the first moment and the second moment, thereby ensuring the accuracy of the subsequent solution format and thus ensuring the accuracy of the temperature change calculation of the target building.

[0112] S140: Calculating the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix, and the integral coefficient matrix, and outputting the temperature vector as a building thermal process simulation of the target building.

[0113] In some embodiments of the present application, when calculating the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix, and the integral coefficient matrix, the process includes:

[0114] ;

[0115] in, For the target building at the second moment The temperature vector, is the temperature vector corresponding to the first moment, It is the internal and external disturbance input of the building from the first moment to the second moment.

[0116] The beneficial effect of the above technical solution is that it uses an explicit recursive algorithm in a linear matrix format. In computer implementation, it can fully utilize high-performance linear algebra libraries such as Blas to achieve efficient model solving and ensure extremely high integration accuracy. This solves the problem of thermal process simulation programs lacking high-precision matrix calculation formats and ensures accurate prediction of building temperature changes under different environmental conditions.

[0117] In some embodiments of the present application, before using the temperature vector as the building thermal process simulation output of the target building, the method further includes:

[0118] Obtaining a preset time setting value, determining whether the second time is greater than the time setting value, and if so, using the temperature vector as a building thermal process simulation output of the target building;

[0119] If not, determining whether the thermal process state space model is a time-invariant model; if so, reacquiring a new first moment and a new second moment, and constructing a new integral coefficient matrix according to the new first moment and the new second moment;

[0120] If not, new building physical parameters and new building boundary conditions of the target building are re-acquired, and a new thermal process state space model of the target building is constructed based on the new building physical parameters and new building boundary conditions.

[0121] In this embodiment, the time setting value is preferably 24 hours, and can be adjusted according to actual conditions.

[0122] In this embodiment, the time-invariant model refers to a mathematical model whose parameters, input-output relationship, or dynamic characteristics do not change with time.

[0123] In this embodiment, a new integral coefficient matrix is ​​constructed according to the new first moment and the new second moment. The specific steps are the same as those described above, and only adaptive adjustments are required.

[0124] In this embodiment, a new thermal process state space model of the target building is constructed based on the new building physical parameters and new building boundary conditions. The specific steps are the same as those described above and only require adaptive adjustments.

[0125] In some embodiments of the present application, after the temperature vector is used as the building thermal process simulation output of the target building, the method further includes:

[0126] Collecting temperature vectors corresponding to the target building at multiple moments;

[0127] Sort all temperature vectors by numerical value and determine the maximum temperature vector and the minimum temperature vector;

[0128] Calculate the mean of the temperature vectors corresponding to all temperature vectors;

[0129] Selecting the first ΔR1 temperature vectors between the maximum temperature vector and the mean of the temperature vectors, and selecting the first ΔR2 temperature vectors between the minimum temperature vector and the mean of the temperature vectors;

[0130] Constructing a first temperature vector sequence based on the first ΔR1 temperature vectors and the first ΔR2 temperature vectors;

[0131] Constructing a second temperature vector sequence based on all remaining temperature vectors;

[0132] A temperature change factor of the target building is calculated based on the first temperature vector sequence and the second temperature vector sequence.

[0133] In this embodiment, through the above steps, temperature vectors corresponding to multiple moments can be obtained. The number of moments is preferably 20, and can be adjusted according to actual conditions.

[0134] In this embodiment, ΔR1 is preferably 8, and ΔR2 is preferably 4, which can be adjusted according to actual conditions.

[0135] In some embodiments of the present application, when calculating the temperature change factor of the target building based on the first temperature vector sequence and the second temperature vector sequence, the method includes:

[0136] sorting the first temperature vector sequence by numerical value, and extracting a first maximum temperature vector and a first minimum temperature vector corresponding to the first temperature vector sequence;

[0137] sorting the second temperature vector sequence by numerical value, and extracting the second maximum temperature vector and the second minimum temperature vector corresponding to the second temperature vector sequence;

[0138] Calculating a first temperature vector mean corresponding to the first temperature vector sequence, and marking the first temperature vector mean in the first temperature vector sequence as a first temperature vector marking point;

[0139] Calculating a second temperature vector mean corresponding to the second temperature vector sequence, and marking the second temperature vector mean in the second temperature vector sequence as a second temperature vector marking point;

[0140] Counting the number of first temperature vectors Δa1 between the first temperature vector marking point and the first minimum temperature vector;

[0141] Counting the number of second temperature vectors Δa2 between the second temperature vector marking point and the second maximum temperature vector;

[0142] A first temperature vector calculation coefficient a3 is calculated according to the first temperature vector quantity Δa1 and the second temperature vector quantity Δa2, wherein: , is the total number of all temperature vectors;

[0143] Counting the number of third temperature vectors Δw1 between the first temperature vector marking point and the first maximum temperature vector;

[0144] Counting the number of fourth temperature vectors Δw2 between the second temperature vector marking point and the second minimum temperature vector;

[0145] The second temperature vector calculation coefficient w3 is calculated according to the third temperature vector quantity Δw1 and the fourth temperature vector quantity Δw2, wherein: ;

[0146] Calculating an absolute value of a coefficient difference between the first temperature vector calculation coefficient and the second temperature vector calculation coefficient, and calculating a coefficient sum of the first temperature vector calculation coefficient and the second temperature vector calculation coefficient;

[0147] The ratio of the absolute value of the coefficient difference to the coefficient sum is calculated and used as the temperature change factor of the target building.

[0148] In this embodiment, when counting the number of temperature vectors, temperature vectors equal to the mean value of the temperature vectors are not counted.

[0149] The beneficial effects of the above technical solution are: the present invention calculates the temperature change factor of the target building based on the first temperature vector sequence and the second temperature vector sequence, thereby ensuring the calculation accuracy of the temperature change factor. The temperature change factor can reflect the temperature change of the target building, provide data support for building thermal distribution simulation and optimization of building heating system design, reduce energy waste, and provide a scientific basis and technical support for the creation of energy-saving buildings and comfortable environments.

[0150] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0151] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0152] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of protection of the present invention.

Claims

1. A building thermal process simulation method based on Lagrange interpolation integral method, characterized in that: include: Acquiring building physical parameters and building boundary conditions of a target building, and constructing a thermal process state space model of the target building based on the building physical parameters and building boundary conditions; Performing model analysis and eigenvalue decomposition on the thermal process state space model to determine an eigenvalue matrix and an eigenvector matrix; Obtaining a first moment and a second moment, and constructing an integral coefficient matrix according to the first moment and the second moment; Calculating the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix, and the integral coefficient matrix, and outputting the temperature vector as a building thermal process simulation output of the target building; When obtaining building physical parameters and building boundary conditions of a target building and constructing a thermal process state space model of the target building based on the building physical parameters and building boundary conditions, the method includes: constructing a first building parameter matrix C and a second building parameter matrix A based on the building physical parameters, wherein the building physical parameters include building density, building specific heat capacity, building volume and building temperature; ； ； Among them, i and j represent the nodes of the target building after spatial discretization. is the building density of the i-th node, is the building specific heat capacity of the i-th node, is the building volume of the i-th node, is the second-order symmetric tensor between the i-th node and the j-th node; ； in, is the heat exchange coefficient between the i-th node and the j-th node, is the heat exchange coefficient between the i-th node and the external disturbance of the building, k is the external disturbance of the building; Constructing a building condition matrix B based on the building boundary conditions; ； in, is the influence coefficient of building external disturbance k on the i-th node; Constructing a thermal process state space model of the target building according to the first building parameter matrix C, the second building parameter matrix A and the building condition matrix B; When constructing the thermal process state space model of the target building according to the first building parameter matrix C, the second building parameter matrix A and the building condition matrix B, it includes: ； in, is the state space model of the thermal process of the target building, , is the building temperature of the i-th node, Q is the internal and external disturbance input of the building, , is the value of the building external disturbance k.

2. The building thermal process simulation method based on the Lagrange interpolation integral method according to claim 1 is characterized in that: When performing model analysis and eigenvalue decomposition on the thermal process state space model to determine the eigenvalue matrix and the eigenvector matrix, the following steps are included: Perform model analysis on the thermal process state space model to construct the first coefficient matrix and the second coefficient matrix ; For the first coefficient matrix and the second coefficient matrix Perform eigenvalue decomposition to obtain the eigenvalue matrix and the eigenvector matrix P, where the eigenvalue matrix is a diagonal matrix, and the eigenvector matrix satisfies , the eigenvalue decomposition satisfies .

3. The building thermal process simulation method based on Lagrange interpolation integral method according to claim 2 is characterized in that: When obtaining the first moment and the second moment, and constructing an integral coefficient matrix according to the first moment and the second moment, the method includes: Get the first moment , get the second moment ; in, is the integral coefficient matrix, is the eigenvalue matrix The i-th eigenvalue of is the allowable error coefficient, e is a constant, x is the integral variable, ∏ is the multiplication symbol, 0≤m≤N, 0≤N≤4, 0≤n≤N.

4. The building thermal process simulation method based on Lagrange interpolation integral method according to claim 3 is characterized in that: When calculating the temperature vector of the target building according to the eigenvalue matrix, the eigenvector matrix and the integral coefficient matrix, it includes: ； in, For the target building at the second moment The temperature vector, is the temperature vector corresponding to the first moment, It is the internal and external disturbance input of the building from the first moment to the second moment.

5. The building thermal process simulation method based on Lagrange interpolation integral method according to claim 1, characterized in that: Before using the temperature vector as the building thermal process simulation output of the target building, the method further includes: Obtaining a preset time setting value, determining whether the second time is greater than the time setting value, and if so, using the temperature vector as a building thermal process simulation output of the target building; If not, determining whether the thermal process state space model is a time-invariant model; if so, reacquiring a new first moment and a new second moment, and constructing a new integral coefficient matrix according to the new first moment and the new second moment; If not, new building physical parameters and new building boundary conditions of the target building are re-acquired, and a new thermal process state space model of the target building is constructed based on the new building physical parameters and new building boundary conditions.

6. The building thermal process simulation method based on Lagrange interpolation integral method according to claim 1, characterized in that: After the temperature vector is used as the building thermal process simulation output of the target building, the method further includes: Collecting temperature vectors corresponding to the target building at multiple moments; Sort all temperature vectors by numerical value and determine the maximum temperature vector and the minimum temperature vector; Calculate the mean of the temperature vectors corresponding to all temperature vectors; Selecting the first ΔR1 temperature vectors between the maximum temperature vector and the mean of the temperature vectors, and selecting the first ΔR2 temperature vectors between the minimum temperature vector and the mean of the temperature vectors; Constructing a first temperature vector sequence based on the first ΔR1 temperature vectors and the first ΔR2 temperature vectors; Constructing a second temperature vector sequence based on all remaining temperature vectors; A temperature change factor of the target building is calculated based on the first temperature vector sequence and the second temperature vector sequence.

7. The building thermal process simulation method based on the Lagrange interpolation integral method according to claim 6 is characterized in that: When calculating the temperature change factor of the target building based on the first temperature vector sequence and the second temperature vector sequence, the method includes: sorting the first temperature vector sequence by numerical value, and extracting a first maximum temperature vector and a first minimum temperature vector corresponding to the first temperature vector sequence; sorting the second temperature vector sequence by numerical value, and extracting the second maximum temperature vector and the second minimum temperature vector corresponding to the second temperature vector sequence; Calculating a first temperature vector mean corresponding to the first temperature vector sequence, and marking the first temperature vector mean in the first temperature vector sequence as a first temperature vector marking point; Calculating a second temperature vector mean corresponding to the second temperature vector sequence, and marking the second temperature vector mean in the second temperature vector sequence as a second temperature vector marking point; Counting the number of first temperature vectors Δa1 between the first temperature vector marking point and the first minimum temperature vector; Counting the number of second temperature vectors Δa2 between the second temperature vector marking point and the second maximum temperature vector; A first temperature vector calculation coefficient a3 is calculated according to the first temperature vector quantity Δa1 and the second temperature vector quantity Δa2, wherein: , is the total number of all temperature vectors; Counting the number of third temperature vectors Δw1 between the first temperature vector marking point and the first maximum temperature vector; Counting the number of fourth temperature vectors Δw2 between the second temperature vector marking point and the second minimum temperature vector; The second temperature vector calculation coefficient w3 is calculated according to the third temperature vector quantity Δw1 and the fourth temperature vector quantity Δw2, wherein: ; Calculating an absolute value of a coefficient difference between the first temperature vector calculation coefficient and the second temperature vector calculation coefficient, and calculating a coefficient sum of the first temperature vector calculation coefficient and the second temperature vector calculation coefficient; The ratio of the absolute value of the coefficient difference to the coefficient sum is calculated and used as the temperature change factor of the target building.

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