Building multi-working-condition batch simulation data generation method, device and medium

Abstract

Embodiments of the present application disclose a kind of building multi-working condition batch simulation data generation method, equipment and medium. Among them, the method comprises: determining the target configuration file corresponding to target batch simulation task;Wherein, the target configuration file is used to describe at least two target parameter adjustment modes for reference source file;According to the at least two target parameter adjustment modes, the reference source file is adjusted to obtain at least two target source files;Based on target building simulation software, the at least two target source files are run to generate target batch simulation data.This technical solution can quickly adjust the source file based on the configuration file to quickly and conveniently generate building multi-working condition batch simulation data, which can ensure the effective coverage of simulation data for various scenarios, improve the applicability, flexibility and generation efficiency of simulation data.

Description

Technical Field

[0001] This invention relates to the field of data generation technology, and in particular to a method, equipment and medium for generating batch simulation data of multiple building conditions. Background Technology

[0002] Building simulation software (such as EnergyPlus) can be used to comprehensively simulate a building's cooling, heating, lighting, ventilation, equipment operation, and energy consumption. In scenarios where there is insufficient actual data, such as during the training and learning of large-scale building AI models, using EnergyPlus to quickly generate large amounts of data through batch simulations of multiple operating conditions is an excellent way to supplement data.

[0003] EnergyPlus itself does not support multi-condition simulation. While some third-party software offers similar functionality, it has limitations. It can only perform simple parameter adjustments, not complex object-level adjustments, and does not support batch simulation. These limitations significantly restrict the use of the generated simulation data, making it unsuitable for different scenarios and resulting in poor applicability and flexibility. Summary of the Invention

[0004] This invention provides a method, device, and medium for generating batch simulation data of multiple building conditions. It enables quick adjustments to source files based on configuration files, thereby facilitating the rapid and convenient generation of batch simulation data of multiple building conditions and improving the applicability, flexibility, and generation efficiency of the simulation data.

[0005] According to one aspect of the present invention, a method for generating batch simulation data of multiple building conditions is provided, the method comprising:

[0006] Determine the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file;

[0007] The reference source file is adjusted according to the at least two target parameter tuning methods to obtain at least two target source files;

[0008] Based on the target building simulation software, run the at least two target source files to generate target batch simulation data.

[0009] According to another aspect of the present invention, a device for generating batch simulation data of multiple working conditions in buildings is provided, the device comprising:

[0010] The configuration file determination module is used to determine the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file;

[0011] The source file parameter adjustment module is used to adjust the parameters of the reference source file according to the at least two target parameter adjustment methods to obtain at least two target source files;

[0012] The batch simulation data generation module is used to generate target batch simulation data by running the at least two target source files based on the target building simulation software.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the building multi-condition batch simulation data generation method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the method for generating batch simulation data of building multi-conditions according to any embodiment of the present invention.

[0018] The technical solution of this invention first determines the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file; then, the parameters of the reference source file are adjusted according to the at least two target parameter tuning methods to obtain at least two target source files; finally, the at least two target source files are run based on the target building simulation software to generate target batch simulation data. This technical solution can quickly adjust the source files based on the configuration file, so as to quickly and conveniently generate batch simulation data for multiple building conditions, ensuring effective coverage of various scenarios by the simulation data, and improving the applicability, flexibility and generation efficiency of the simulation data.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a method for generating batch simulation data of multiple building conditions according to Embodiment 1 of the present invention;

[0022] Figure 2A This is a schematic diagram of a method for determining target parameter tuning according to Embodiment 1 of the present invention;

[0023] Figure 2B This is a schematic diagram of another method for determining target parameter tuning according to Embodiment 1 of the present invention;

[0024] Figure 3 This is a schematic diagram illustrating the traversal of candidate parameter values ​​for a target parameter item according to Embodiment 1 of the present invention;

[0025] Figure 4 This is a schematic diagram of a target batch simulation task processing provided in Embodiment 1 of the present invention;

[0026] Figure 5 This is a schematic diagram illustrating the parallel execution of multiple target configuration files according to Embodiment 1 of the present invention;

[0027] Figure 6 This is a flowchart of a method for generating batch simulation data of multiple building conditions according to Embodiment 2 of the present invention;

[0028] Figure 7 This is a schematic diagram of a building multi-condition batch simulation data generation device provided in Embodiment 3 of the present invention;

[0029] Figure 8 This is a schematic diagram of the structure of an electronic device that implements a method for generating batch simulation data of multiple building conditions according to an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a method for generating batch simulation data of multiple building conditions according to Embodiment 1 of the present invention. This embodiment is applicable to the rapid generation of batch simulation data of multiple building conditions. This method can be executed by a batch simulation data generation device for multiple building conditions, which can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes:

[0034] S110, determine the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file.

[0035] The target batch simulation task can refer to a batch simulation task under multiple operating conditions determined in advance based on the actual building simulation requirements. For example, the target batch simulation task can be set up to simulate the operation of commercial centers in different regions (such as Beijing and Shanghai) under different building orientations (such as 0°, 90°), different external wall thermal conductivity coefficients (such as 0.8, 1.0), and different chiller outlet water temperatures (such as 6℃, 7℃). The reference source file can refer to the input source file of the target building simulation software. This software can be used to comprehensively simulate the building's cooling, heating, lighting, ventilation, equipment operation, and energy consumption. For example, when EnergyPlus is used as the target building simulation software, the reference source file is an idf file. The target parameter tuning method can refer to the method of adjusting the parameters of the reference source file in advance based on the actual building simulation requirements, and can be described by assigning specific parameter values ​​to which parameters.

[0036] In this embodiment, when performing batch simulations of multiple building conditions based on the target building simulation software, it is first necessary to determine the target configuration file (such as a YAML file) corresponding to the target batch simulation task. This target configuration file can be used to describe at least two target parameter tuning methods for the reference source file, that is, it describes which reference source file to use which target parameter tuning method for parameter adjustment. It should be noted that conventional simulation methods involve manually modifying the parameter values ​​in the reference source file directly. With several target parameter tuning methods, the reference source file needs to be modified manually several times. In this case, when there are many target parameter tuning methods, a lot of time needs to be spent modifying the reference source file, resulting in low simulation efficiency, and repeated work can easily lead to human fatigue and modification errors. Therefore, in order to quickly and conveniently set multi-condition parameters for the target batch simulation task, this solution adopts a YAML file configuration method. A YAML configuration file is written for each target batch simulation task, defining the IDF file and parameter configuration, thereby determining the target configuration file corresponding to the target batch simulation task.

[0037] In this embodiment, optionally, determining the target configuration file corresponding to the target batch simulation task includes: determining a target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item based on the target batch simulation task; determining a target parameter tuning method based on the traversal results of at least two candidate parameter values ​​for each target parameter item; determining a reference source file corresponding to the target building object; and determining the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

[0038] The target building object refers to the building object that needs to be simulated. For example, the target building object can be different types of buildings such as office buildings, commercial centers, and computer rooms. Each target building object corresponds to one reference source file. Target parameter items refer to parameters that need to be set. For example, target parameter items can include building orientation, external wall thermal conductivity coefficient, chiller outlet water temperature, and geographic information. Furthermore, target parameter items can also include weather files associated with geographic information. These weather files are generally on an annual basis, describing typical weather conditions in a region over a year, such as temperature, humidity, and wind direction. Candidate parameter values ​​refer to the possible values ​​for the target parameter items.

[0039] Optionally, the target parameter item may include a single parameter object or multiple parameter objects, where multiple parameter objects are used to describe the same target parameter item. For example, taking geographic information as the target parameter item, geographic information is typically described using longitude, latitude, altitude, and other information to ensure its accuracy. In this case, geographic information can be considered as one target parameter item, and longitude, latitude, altitude, and other information can be considered as multiple parameter objects of the geographic information. Furthermore, if the target parameter item includes a single parameter object, then one value of that single parameter object is used as a candidate parameter value for the target parameter item; if the target parameter item includes multiple parameter objects, then a set of values ​​from the multiple parameter objects is used as a candidate parameter value for the target parameter item. For example, when the target parameter is building orientation, building orientation = 0° is one candidate parameter value for building orientation, and building orientation = 90° is another candidate parameter value for building orientation; when the target parameter is geographic information, longitude = 39.80 and latitude = 116.47 (corresponding to Beijing area) is one candidate parameter value for geographic information, and longitude = 31.40 and latitude = 121.45 (corresponding to Shanghai area) is another candidate parameter value for geographic information.

[0040] Specifically, when determining the target configuration file for the target batch simulation task, it is first necessary to determine the target building object, all target parameter items of the target building object, and all candidate parameter values ​​for each target parameter item based on the target batch simulation task. Then, for each target parameter item, at least two candidate parameter values ​​are iterated sequentially, and a Cartesian product is performed on each candidate parameter value for each target parameter item to determine all target parameter tuning methods. Next, a corresponding reference source file is determined based on the target building object (one reference source file corresponds to one target building object). Then, a YAML file is written based on the reference source file and the target parameter tuning methods, serving as the target configuration file for the target batch simulation task. Using a YAML configuration file for parameter tuning settings balances convenience and flexibility, while also supporting complex operations such as object deletion and addition in EnergyPlus.

[0041] Figure 2A This is a schematic diagram illustrating a method for determining target parameter adjustments according to Embodiment 1 of the present invention. The diagram uses building orientation, external wall heat transfer coefficient, and chiller outlet water temperature as examples of target parameters. Each of these three target parameters includes a single parameter object. Specifically, in the idf file input by EnergyPlus, the building orientation is 0°, the external wall heat transfer coefficient is 1.0, and the chiller outlet water temperature is 6°C. Furthermore, the candidate parameter values ​​for the building orientation are 0° and 90°, the candidate parameter values ​​for the external wall heat transfer coefficient are 0.8 and 1.0, and the candidate parameter values ​​for the chiller outlet water temperature are 6°C and 7°C. Figure 2AAs shown, by iterating through and combining the various candidate parameter values ​​of building orientation, external wall heat transfer coefficient, and chiller outlet water temperature, eight target parameter tuning methods can be obtained, corresponding to eight target source files with modified parameters (i.e., Figure 2A (idf_1-idf_8 in the original text).

[0042] Figure 2B This is a schematic diagram illustrating another method for determining target parameter tuning provided in Embodiment 1 of the present invention. It uses building orientation, external wall heat transfer coefficient, and geographical information as target parameter items for illustration. The geographical information includes multiple parameter objects (i.e., city, longitude, and latitude), and different geographical information is associated with different weather files (EPW). Specifically, the candidate parameter values ​​for building orientation are 0° and 90°, the candidate parameter values ​​for external wall heat transfer coefficient are 0.8 and 1.0, and the candidate parameter values ​​for geographical information are [Beijing, 39.80, 116.47] and [Shanghai, 31.40, 121.45]. Figure 2B As shown, by iterating through and combining the various candidate parameter values ​​of building orientation, exterior wall heat transfer coefficient, and geographical information (treating longitude and latitude as a whole), eight target parameter tuning methods can be obtained. Furthermore, weather files associated with the geographical information can be obtained and incorporated into the target parameter items, supporting batch simulations of multiple climate zones and operating conditions. It should be noted that when using multiple weather files for multi-condition simulations, the geographical information in the IDF file should be automatically modified according to the region of the weather file to ensure consistency with the weather data. Simultaneously, since the IDF file itself is not associated with weather files, but the geographical information in the IDF file needs to be consistent with the applied weather file during simulation, the correspondence between a transformed IDF file and a specific weather file needs to be recorded during parameter transformation to support the correct execution of subsequent simulations.

[0043] In this embodiment, optionally, determining the target parameter tuning method based on the traversal results of at least two candidate parameter values ​​for each target parameter item includes: determining the target parameter node corresponding to each target parameter item; wherein, the target parameter node includes a parameter value list, which is used to store at least two candidate parameter values ​​for the target parameter item; for each target parameter node, determining the candidate position information of each candidate parameter value in the parameter value list, traversing the candidate position information to obtain target position information; assigning a value to the target parameter node according to the target parameter value corresponding to the target position information, and determining the target parameter tuning method based on the target parameter value of each target parameter node.

[0044] Specifically, each configurable target parameter item corresponds to a target parameter node (ParamNode). This node contains parameter information (representing what the target parameter item is) and a list of possible parameter values ​​(i.e., the parameter value list). Multiple target parameter nodes constitute a parameter setting scheme (i.e., a target parameter tuning method), and these nodes are sequentially connected using a doubly linked list data structure. During parameter setting, the target parameter node also records and updates the position index (target position information) of the currently set parameter value (i.e., the target parameter value) in the list of possible values, enabling traversal and Cartesian product combinations of the possible values.

[0045] Figure 3 This is a schematic diagram illustrating the traversal of candidate parameter values ​​for a target parameter item according to Embodiment 1 of the present invention, using building orientation, external wall heat transfer coefficient, and chiller outlet water temperature as examples. For instance, as shown... Figure 3 As shown, when iterating through at least two candidate parameter values ​​for each target parameter item, the following operations can be used: 1. Set parameter operations sequentially from front to back, assigning the parameter value corresponding to the target position number for each target parameter node in turn. After all nodes have been assigned values, a new IDF file can be created; 2. Update position number operations sequentially from back to front. When the position number of a target parameter node exceeds the length of the selectable value, it needs to be set to 0 to restart the traversal and update the position number of the previous node. This operation will propagate forward sequentially until the first target parameter item has completed the assignment traversal, and the entire parameter setting scheme is completed.

[0046] In this embodiment, optionally, determining the target configuration file corresponding to the target batch simulation task includes: determining a target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item based on the target batch simulation task; determining at least two target parameter groups based on the target parameter items; wherein each target parameter group includes different target parameter items; determining at least two sets of preset parameter values ​​for each target parameter group, and determining a target parameter tuning method based on the traversal results of the at least two sets of preset parameter values ​​for each target parameter group; determining a reference source file corresponding to the target building object, and determining the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

[0047] In this embodiment, when determining the target configuration file corresponding to the target batch simulation task, in addition to using the Cartesian product mode, the parameter group mode can also be used. Specifically, after determining the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item based on the target batch simulation task, at least two target parameter groups are first determined based on the target parameter items, and each target parameter group includes different target parameter items. Then, several sets of typical parameter values ​​are manually set as at least two sets of preset parameter values ​​for each target parameter group. Then, referring to the above traversal method, the preset parameter values ​​of each target parameter group are combined by Cartesian product to obtain the target parameter tuning method, so that the target configuration file corresponding to the target batch simulation task can be determined subsequently based on the reference source file and the target parameter tuning method.

[0048] S120, adjust the parameters of the reference source file according to at least two target parameter tuning methods to obtain at least two target source files.

[0049] In this embodiment, after determining the target configuration file corresponding to the target batch simulation task, the target configuration file can be parsed using a configuration file parser to obtain the reference source file and the target parameter tuning method. Then, the reference source file is loaded, and the parameters of the reference source file are adjusted according to each target parameter tuning method to obtain the target source file. The number of target source files is consistent with the number of target parameter tuning methods.

[0050] S130: Based on the target building simulation software, run at least two target source files to generate target batch simulation data.

[0051] In this embodiment, after obtaining the target source files, each target source file can be run based on the target building simulation software, and the generated simulation results can be used as the target batch simulation data corresponding to the target source files. It should be noted that the construction and running process of the target source files can be executed continuously (i.e., running begins once the target source files are built) or separately (i.e., running is performed at a suitable time after the target source files are built). Because EnergyPlus simulations take a relatively long time, and batch running takes even longer, to reduce the impact of anomalies during operation and to support batch scheduling of planned tasks, the task of building the IDF file and the simulation running task can be separated. For example, since the server typically experiences lower operating pressure at night, after the target source files are built, they can be scheduled to run at night, which helps improve simulation efficiency.

[0052] Figure 4 This is a schematic diagram illustrating a target batch simulation task processing method provided in Embodiment 1 of the present invention. Figure 4As shown, a YAML configuration file is pre-configured for each target batch simulation task, defining the original IDF file (i.e., the reference source file), related weather files, and parameter configurations. The configuration file parser parses the YAML configuration file to obtain the simulation task (including the reference source file and target parameter tuning method). This simulation task first performs a build operation, creating multiple IDF files (i.e., target source files) through parameter assignment. Then, it performs a run operation, calling the program interface provided by EnergyPlus for each of these IDF files (i.e., target source files) to obtain the simulation results corresponding to each IDF file (i.e., target source file) as the target batch simulation data, thus completing the simulation work. Furthermore, the simulation executor program can also accept multiple YAML files as input parameters to meet the needs of batch automated simulation, such as... Figure 5 As shown, multiple YAML files (corresponding to models A, B, and C in the diagram) can be executed in parallel to improve the execution efficiency of the YAML files.

[0053] In this embodiment, optionally, generating target batch simulation data based on running at least two target source files based on the target building simulation software includes: generating log records for each target source file during the process of running at least two target source files based on the target building simulation software; wherein, the log records are used to describe the execution status of the target source files; if it is determined from the log records that the target source files have been executed, then the target batch simulation data is determined based on the running data of the target source files.

[0054] The execution status can include completed, incomplete, or interrupted. Specifically, if the log records indicate that the target source file has been completed, then all the running data of the target source file can be used as the target batch simulation data. If the log records indicate that the target source file has not been completed, then it is necessary to wait until the target source file is completed, and then all the running data of the target source file can be used as the target batch simulation data. If the log records indicate that the target source file has been interrupted, it indicates that a task interruption has occurred, and the target source file needs to be executed again until it is completed. When a task interruption occurs and the target source file needs to be executed again, it can be done in two ways: starting from the beginning or continuing from where it was interrupted.

[0055] In this embodiment, optionally, after generating log records for each target source file during the process of running at least two target source files based on the target building simulation software, the method further includes: if it is determined from the log records that the execution of the target source file is interrupted, determining a first part and a second part of the target source file based on the log records; wherein, the first part is used to indicate that it has been executed, and the second part is used to indicate that it has not been executed; running the second part of the target source file until the target source file is completed, and determining the target batch simulation data based on the running data of the first part and the second part of the target source file.

[0056] Specifically, if the interruption of the target source file's execution is determined based on log records, the point of interruption can be identified. The target source file can then be divided into a first part (executed) and a second part (not executed). When the target source file is run again, completed tasks (the first part) can be skipped based on the log records, and only the incomplete tasks (the second part) need to be executed until the target source file is completed. The execution data from the first and second parts of the target source file is then used as the target batch simulation data. This can speed up the execution of the target source file when a task is abnormally interrupted, avoiding the re-execution of completed parts.

[0057] The technical solution of this invention first determines the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file; then, the parameters of the reference source file are adjusted according to the at least two target parameter tuning methods to obtain at least two target source files; finally, the at least two target source files are run based on the target building simulation software to generate target batch simulation data. This technical solution can quickly adjust the source files based on the configuration file, so as to quickly and conveniently generate batch simulation data of building multi-conditions, which can ensure the effective coverage of simulation data for various scenarios, improve the applicability, flexibility and generation efficiency of simulation data, and strongly support the training and learning of large AI models.

[0058] Example 2

[0059] Figure 6 This is a flowchart of a method for generating batch simulation data of multiple building conditions provided in Embodiment 2 of the present invention. This embodiment is an optimization based on the above embodiment.

[0060] like Figure 6 As shown, the method in this embodiment specifically includes the following steps:

[0061] S210, determine the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item based on the target batch simulation task.

[0062] S220, determine the number of candidate parameter values ​​for each target parameter item, and determine the number of parameter tuning methods based on the product of the number of candidate parameter values ​​for each target parameter item.

[0063] The preset threshold can refer to a reference value for the number of parameter tuning methods pre-set according to actual simulation requirements. Specifically, the number of parameter tuning methods can be obtained by multiplying the number of candidate parameter values ​​for each target parameter item.

[0064] S230: Determine if the number of parameter tuning methods exceeds the preset threshold. If yes, execute S240-S250; otherwise, execute S260.

[0065] S240, determine at least two target parameter groups based on the target parameter items; wherein each target parameter group includes different target parameter items.

[0066] It should be noted that due to the excessive number of simulation schemes (i.e., parameter tuning methods) generated by the Cartesian product mode parameter setting combinations, an orthogonal testing method can be used to construct simulation schemes to save time and computational costs, while also making the simulation schemes more representative. This scheme introduces a parameter group node pattern. A parameter group contains a set of parameter items (potentially from multiple parameter objects) for setting adjustments. Each parameter item corresponds to a list of optional values, and these lists are of equal length and consistent with the sequence of orthogonal test schemes. During each parameter setting operation, all parameters within the group are adjusted synchronously as a whole, thus achieving an orthogonal simulation scheme.

[0067] S250, determine at least two preset parameter values ​​for each target parameter group, and determine the target parameter tuning method based on the traversal results of at least two preset parameter values ​​for each target parameter group.

[0068] Specifically, firstly, at least two target parameter groups are determined based on the target parameter items, and each target parameter group includes different target parameter items. Then, several sets of typical parameter values ​​are manually set as at least two preset parameter values ​​for each target parameter group. Next, referring to the traversal method in Embodiment 1 above, the preset parameter values ​​of each target parameter group are combined using a Cartesian product to obtain the target parameter tuning method. By combining the parameter group mode with the Cartesian product mode, a more flexible simulation data generation scheme can be formulated, while effectively improving the efficiency of simulation data generation.

[0069] S260, determine the target parameter tuning method based on the traversal results of at least two candidate parameter values ​​for each target parameter item.

[0070] S270, determine the reference source file corresponding to the target building object, and determine the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

[0071] S280, adjust the parameters of the reference source file according to at least two target parameter tuning methods to obtain at least two target source files.

[0072] S290, based on the target building simulation software, runs at least two target source files to generate target batch simulation data.

[0073] The specific implementation of S260-S290 can be referred to the relevant description in Embodiment 1 above, and will not be repeated here.

[0074] The technical solution of this invention, after determining the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item according to the target batch simulation task, determines the number of candidate parameter values ​​for each target parameter item, and determines the number of parameter tuning methods based on the product of the number of candidate parameter values ​​for each target parameter item; if the number of parameter tuning methods is greater than a preset threshold, at least two target parameter groups are determined according to the target parameter item; wherein, each target parameter group includes different target parameter items; and at least two preset parameter values ​​for each target parameter group are determined, and the target parameter tuning method is determined based on the traversal result of the at least two preset parameter values ​​for each target parameter group; otherwise, the target parameter tuning method is determined based on the traversal result of the at least two candidate parameter values ​​for each target parameter item; then, the reference source file corresponding to the target building object is determined, and the target configuration file corresponding to the target batch simulation task is determined according to the reference source file and the target parameter tuning method; then, the parameters of the reference source file are adjusted according to at least two target parameter tuning methods respectively to obtain at least two target source files; finally, the target building simulation software runs at least two target source files to generate target batch simulation data. This technical solution adds a parameter group mode to the parameter tuning combination scheme, which can support orthogonal test schemes. By combining the parameter group mode with the Cartesian product mode, the simulation data generation scheme can be formulated more flexibly, while effectively improving the generation efficiency of simulation data.

[0075] Example 3

[0076] Figure 7 This is a schematic diagram of a building multi-condition batch simulation data generation device provided in Embodiment 3 of the present invention. This device can execute the building multi-condition batch simulation data generation method provided in any embodiment of the present invention, and possesses the corresponding functional modules and beneficial effects of the method. Figure 7 As shown, the device includes:

[0077] The configuration file determination module 310 is used to determine the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file;

[0078] The source file parameter adjustment module 320 is used to adjust the parameters of the reference source file according to the at least two target parameter adjustment methods to obtain at least two target source files;

[0079] The batch simulation data generation module 330 is used to generate target batch simulation data by running the at least two target source files based on the target building simulation software.

[0080] Optionally, the configuration file determination module 310 includes:

[0081] The target object and parameter determination unit is used to determine a target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item according to the target batch simulation task.

[0082] The first parameter tuning method determination unit is used to determine the target parameter tuning method based on the traversal results of at least two candidate parameter values ​​for each target parameter item;

[0083] The configuration file determination unit is used to determine the reference source file corresponding to the target building object, and to determine the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

[0084] Optionally, the first parameter tuning method determination unit is specifically used for:

[0085] Determine the target parameter node corresponding to each target parameter item; wherein, the target parameter node includes a parameter value list, which is used to store at least two candidate parameter values ​​for the target parameter item;

[0086] For each target parameter node, determine the candidate position information of each candidate parameter value in the parameter value list, and traverse the candidate position information to obtain the target position information;

[0087] The target parameter nodes are assigned values ​​based on the target parameter values ​​corresponding to the target location information, and the target parameter tuning method is determined based on the target parameter values ​​of each target parameter node.

[0088] Optionally, the configuration file determination module 310 further includes:

[0089] The parameter tuning method quantity determination unit is used to determine the number of candidate parameter values ​​for each target parameter item after determining the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item according to the target batch simulation task, and to determine the number of parameter tuning methods according to the product of the number of candidate parameter values ​​of each target parameter item.

[0090] The target parameter group determination unit is used to determine at least two target parameter groups based on the target parameter items if the number of parameter tuning methods is greater than a preset number threshold; wherein each target parameter group includes different target parameter items;

[0091] The second parameter tuning method determination unit is used to determine at least two sets of preset parameter values ​​for each target parameter group, and to determine the target parameter tuning method based on the traversal results of at least two sets of preset parameter values ​​for each target parameter group.

[0092] Optionally, the configuration file determination module 310 is further configured to:

[0093] Based on the target batch simulation task, determine the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item;

[0094] At least two target parameter groups are determined based on the target parameter items; wherein each target parameter group includes different target parameter items;

[0095] Determine at least two sets of preset parameter values ​​for each target parameter group, and determine the target parameter tuning method based on the traversal results of at least two sets of preset parameter values ​​for each target parameter group;

[0096] Determine the reference source file corresponding to the target building object, and determine the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

[0097] Optionally, the batch simulation data generation module 330 is used for:

[0098] During the execution of the at least two target source files based on the target building simulation software, a log record is generated for each target source file; wherein the log record is used to describe the execution status of the target source file;

[0099] If it is determined from the log records that the target source file has been executed, then the target batch simulation data is determined based on the running data of the target source file.

[0100] Optionally, the batch simulation data generation module 330 is further configured to:

[0101] During the process of running the at least two target source files based on the target building simulation software, after generating a log record for each target source file, if it is determined from the log record that the execution of the target source file is interrupted, a first part and a second part of the target source file are determined according to the log record; wherein, the first part is used to indicate that it has been executed, and the second part is used to indicate that it has not been executed;

[0102] Run the second part of the target source file until the target source file is completed, and determine the target batch simulation data based on the running data of the first and second parts of the target source file.

[0103] Optionally, the target parameter item may include a single parameter object or multiple parameter objects, wherein the multiple parameter objects are used to describe the same target parameter item.

[0104] The building multi-condition batch simulation data generation device provided in the embodiments of the present invention can execute the building multi-condition batch simulation data generation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0105] Example 4

[0106] Figure 8 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0107] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0108] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0109] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the method for generating batch simulation data for multi-condition building construction.

[0110] In some embodiments, the method for generating batch simulation data of multiple building conditions can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for generating batch simulation data of multiple building conditions described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for generating batch simulation data of multiple building conditions by any other suitable means (e.g., by means of firmware).

[0111] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0113] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0114] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0115] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0116] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0117] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0118] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for generating batch simulation data of multiple building conditions, characterized in that, The method includes: Determine the target configuration file corresponding to the target batch simulation task; wherein, the target configuration file is used to describe at least two target parameter tuning methods for the reference source file; The reference source file is adjusted according to the at least two target parameter tuning methods to obtain at least two target source files; Based on the target building simulation software, run the at least two target source files to generate target batch simulation data; Determine the target configuration file corresponding to the target batch simulation task, including: Based on the target batch simulation task, determine the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item; The target parameter tuning method is determined based on the traversal results of at least two candidate parameter values ​​for each of the target parameter items; Determine the reference source file corresponding to the target building object, and determine the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method; After determining the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item based on the target batch simulation task, the method further includes: Determine the number of candidate parameter values ​​for each target parameter item, and determine the number of parameter tuning methods based on the product of the number of candidate parameter values ​​for each target parameter item; If the number of parameter tuning methods is greater than a preset threshold, at least two target parameter groups are determined based on the target parameter items; wherein each target parameter group includes different target parameter items; Determine at least two preset parameter values ​​for each target parameter group, and determine the target parameter tuning method based on the traversal results of at least two preset parameter values ​​for each target parameter group.

2. The method according to claim 1, characterized in that, The target parameter tuning method is determined based on the traversal results of at least two candidate parameter values ​​for each of the target parameter items, including: Determine the target parameter node corresponding to each target parameter item; wherein, the target parameter node includes a parameter value list, which is used to store at least two candidate parameter values ​​for the target parameter item; For each target parameter node, determine the candidate position information of each candidate parameter value in the parameter value list, and traverse the candidate position information to obtain the target position information; The target parameter nodes are assigned values ​​based on the target parameter values ​​corresponding to the target location information, and the target parameter tuning method is determined based on the target parameter values ​​of each target parameter node.

3. The method according to claim 1, characterized in that, Determine the target configuration file corresponding to the target batch simulation task, including: Based on the target batch simulation task, determine the target building object, at least one target parameter item of the target building object, and at least two candidate parameter values ​​of the target parameter item; At least two target parameter groups are determined based on the target parameter items; wherein each target parameter group includes different target parameter items; Determine at least two sets of preset parameter values ​​for each target parameter group, and determine the target parameter tuning method based on the traversal results of at least two sets of preset parameter values ​​for each target parameter group; Determine the reference source file corresponding to the target building object, and determine the target configuration file corresponding to the target batch simulation task based on the reference source file and the target parameter tuning method.

4. The method according to claim 1, characterized in that, Based on the target building simulation software, at least two target source files are run to generate target batch simulation data, including: During the execution of the at least two target source files based on the target building simulation software, a log record is generated for each target source file; wherein the log record is used to describe the execution status of the target source file; If it is determined from the log records that the target source file has been executed, then the target batch simulation data is determined based on the running data of the target source file.

5. The method according to claim 4, characterized in that, During the process of running the at least two target source files based on the target building simulation software, after generating log records for each target source file, the process further includes: If it is determined from the log records that the execution of the target source file was interrupted, a first part and a second part of the target source file are determined according to the log records; wherein, the first part is used to indicate that it has been executed, and the second part is used to indicate that it has not been executed; Run the second part of the target source file until the target source file is completed, and determine the target batch simulation data based on the running data of the first and second parts of the target source file.

6. The method according to any one of claims 1-3, characterized in that, The target parameter item includes a single parameter object or multiple parameter objects, and the multiple parameter objects are used to describe the same target parameter item.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for generating batch simulation data of building multi-conditions as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for generating batch simulation data of building multi-conditions as described in any one of claims 1-6.

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