Method, device and equipment for constructing building simulation models in batches and medium

Abstract

The invention discloses a method, device and equipment for constructing building simulation models in batches and a medium. The method comprises the following steps: acquiring at least one preset basic building model, and generating each thermal load model matched with each basic building model by setting at least one thermal load related parameter type and an optional value matched with the thermal load related parameter type; responding to the operation related parameter types of the user and the setting operation of optional values of the operation related parameter types, and generating building simulation models matched with the thermal load models respectively; and performing aggregation operation on each building simulation model to obtain a simulation model set matched with each basic building model, and meanwhile, generating a building model construction result matched with the simulation model set and sending the building model construction result to display equipment for display. Through the technical scheme of the invention, batch construction of the building simulation models can be realized, the construction efficiency of the building simulation models is improved, and the reasonability of construction results of the building simulation models is ensured.

Description

Technical Field

[0001] The present invention relates to the field of model construction, and in particular to a method, device, equipment and medium for batch construction of architectural simulation models. Background Art

[0002] With the continuous development of the construction industry and the advancement of information technology, the application of large-scale AI-powered building operation and maintenance models in the construction field has attracted increasing attention. However, during the training process, sufficient and effective data supply has become a key issue that needs to be addressed.

[0003] Traditional methods of collecting and accumulating real-world data from real-world projects face numerous challenges. First, the amount of data available from real-world projects is relatively limited in magnitude, making it difficult to achieve the massive scale required for training large AI models. Second, in terms of data coverage, real-world data often only covers buildings of specific types, sizes, or geographic regions, lacking comprehensiveness and diversity, and thus failing to meet the broad range of data features required for large-scale model learning. To address this lack of real-world data, building simulation software has emerged. Software such as EnergyPlus, Dest, and DOE-2 have been widely used within the industry. While these software programs offer some solutions for generating building data, they also have significant limitations. Modeling using these software programs typically requires significant human, material, and time resources. Creating each building model requires complex steps such as parameter setting and geometric modeling, which not only requires high expertise and skills from the modeler but also makes the process cumbersome and error-prone. Furthermore, manually creating building models one by one is extremely inefficient and nearly impractical when faced with the large number of models required to train large AI models.

[0004] In summary, the existing methods for constructing building simulation models have the problems of being unable to achieve batch construction, low building efficiency of building simulation models, and poor rationality of building simulation model construction results. Summary of the Invention

[0005] The present invention provides a method, device, equipment and medium for batch construction of building simulation models, which can solve the problems of existing methods for constructing building simulation models, such as the inability to achieve batch construction, low construction efficiency of building simulation models, and poor rationality of building simulation model construction results.

[0006] In a first aspect, an embodiment of the present invention provides a method for batch constructing building simulation models, the method comprising:

[0007] Acquire at least one preset basic building model, and generate heat load models matching each basic building model by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type;

[0008] In response to the user's setting operation of the operation-related parameter type and its optional value, generating each building simulation model that matches each heat load model;

[0009] The building simulation models are aggregated to obtain a simulation model set that matches the basic building models. At the same time, a building model construction result that matches the simulation model set is generated and sent to a display device for display.

[0010] In a second aspect, an embodiment of the present invention provides a device for batch building simulation models, the device comprising:

[0011] a heat load parameter setting module, configured to obtain at least one pre-set basic building model, and generate heat load models matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type;

[0012] An operation parameter setting module, configured to generate respective building simulation models that match respective heat load models in response to a user's operation of setting operation-related parameter types and their optional values;

[0013] The result display model is used to aggregate the various building simulation models to obtain a simulation model set that matches each basic building model, and at the same time generate a building model construction result that matches the simulation model set and send it to a display device for display.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device, comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for batch constructing building simulation models described in any embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a method for batch constructing building simulation models as described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention first obtains at least one pre-set basic building model, generates each heat load model matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type, then generates each building simulation model matching each heat load model in response to the user's setting operation of the operation-related parameter type and its optional value, and finally aggregates each building simulation model to obtain a simulation model set matching each basic building model, and at the same time generates a building model construction result matching the simulation model set and sends it to a display device for display, thereby solving the problems of the existing method for constructing building simulation models, such as the inability to realize batch construction, low construction efficiency of building simulation models, and poor rationality of building simulation model construction results, realizing batch construction of building simulation models, improving the construction efficiency of building simulation models, and ensuring the rationality of building simulation model construction results.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 This is a flow chart of a method for batch building simulation models provided according to the first embodiment of the present invention;

[0023] Figure 2 This is a flow chart of a method for batch building simulation models provided according to a second embodiment of the present invention;

[0024] Figure 3 2 is a schematic structural diagram of a device for batch building simulation models according to a third embodiment of the present invention;

[0025] Figure 4 The present invention is a schematic structural diagram of an electronic device for implementing a method for batch constructing building simulation models according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," and the like in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, any variations of the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1 A flowchart of a method for batch building simulation models provided in Example 1 of the present invention is provided. This embodiment is applicable to the situation where building simulation models are batch built. The method can be executed by a device for batch building simulation models. The device for batch building simulation models can be implemented in the form of hardware and / or software. The device for batch building simulation models can be configured in a terminal or server with the function of batch building simulation models.

[0030] like Figure 1 As shown, the method includes:

[0031] S110 , obtaining at least one preset basic building model, and generating heat load models matching the basic building models by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type.

[0032] The heat load related parameter types include at least one of regional information, building orientation information, wall heat transfer coefficient, glass heat transfer coefficient, business hours and customer flow information.

[0033] Among them, the basic building model is a pre-built building model that contains basic information such as the basic structure, layout, and electromechanical equipment configuration of the building. It is the cornerstone for subsequent various simulation calculations and parameter adjustments. For example, in a project simulating the energy consumption of an urban commercial complex, the pre-built basic building model may cover the floor distribution of the shopping mall, the functional division of each area (such as shopping area, dining area, office area, etc.), and the preliminary settings of major electromechanical equipment (such as air-conditioning system, lighting system, etc.). These basic building models can be constructed based on the measurement data of real buildings, or they can be representative models created based on common building types and design specifications. This embodiment does not limit this.

[0034] Furthermore, the heat load related parameter types are categories of various factors that affect the heat load of the building, mainly including regional information, building orientation information, wall heat transfer coefficient, glass heat transfer coefficient, business hours and passenger flow information. Regional information refers to the geographical location of the building, which has a significant impact on the heat load of the building. Regional information is an important parameter in the simulation, and its optional values ​​are usually representative cities or regions. For example, in this solution, the optional values ​​are Harbin, Beijing, Chengdu, and Shenzhen. Building orientation information refers to the orientation of the building. Different orientations will cause the building to receive different amounts of solar radiation, which in turn affects the heat load. Taking the east and south directions as examples, buildings facing south can obtain more solar radiation heat in winter, and relatively speaking, the heat load may be lower than buildings facing east. Setting optional values ​​for building orientation information during the simulation helps study the impact of different orientations on building heat loads and provides a reference for building design. The wall heat transfer coefficient reflects the wall's ability to transfer heat and is an important indicator of wall insulation performance. The glass heat transfer coefficient, similar to the wall heat transfer coefficient, is a parameter that measures the heat transfer capacity of glass. Business hours have a significant impact on the heat load of commercial buildings and other types of buildings. Standardizing business hours for the entire building versus different business areas can lead to differences in personnel activity and equipment operation within the building, which in turn affects the heat load. For example, in a large shopping mall, if standardizing business hours for the entire building, all areas will turn on and off air conditioning, lighting, and other equipment simultaneously. However, if different business areas have different business hours, the dining area may have different operating hours than the shopping area, resulting in different temporal distributions of heat loads in different areas. Setting different optional values ​​for this parameter in the simulation can more accurately simulate the building heat load under actual operating conditions. Customer flow information also affects the building heat load. Standardizing customer flow throughout the day versus differentiating between weekdays and weekends can lead to differences in the amount of heat and moisture dissipated by people, which in turn affects the building's heat load.

[0035] Specifically, by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type, each heat load model matching each basic building model is generated, including: obtaining at least one optional value of each heat load related parameter type, performing orthogonal combination of each optional value of each heat load related parameter type through an orthogonal test method, and obtaining each heat load parameter combination result matching each heat load related parameter type, wherein the heat load parameter combination result includes one optional value of each heat load related parameter type, and the number of the optional values ​​is consistent with the number of heat load related parameter types; applying each heat load parameter combination result to the basic building model respectively, and simulating and calculating each electromechanical equipment parameter in the basic building model based on the currently applied heat load parameter combination result, and obtaining a heat load model matching the current heat load parameter combination result.

[0036] For example, in a specific implementation scenario of this embodiment, when generating a heat load model, at least one optional value for each heat load-related parameter type is first obtained. For example, one optional value is selected from the region information (Harbin, Beijing, Chengdu, Shenzhen), one optional value is selected from the building orientation information (0°, 90°), and so on, to obtain an optional value for each heat load-related parameter type. Then, an orthogonal test method is used to perform orthogonal combinations of the optional values ​​for each heat load-related parameter type. Through the orthogonal test method, each heat load parameter combination result that matches each heat load-related parameter type is obtained. Each heat load parameter combination result contains an optional value for each heat load-related parameter type, and the number of optional values ​​matches the number of heat load-related parameter types. For example, a heat load parameter combination result might include Harbin as the region, 90° as the building orientation, 80% as the wall heat transfer coefficient, 100% as the glass heat transfer coefficient, business hours to distinguish different commercial areas, and customer flow to distinguish between weekdays and weekends. Next, each heat load parameter combination result is applied to the basic building model. The base building model is a pre-built model that contains basic information such as the building's basic structure, layout, and mechanical and electrical equipment configuration. It serves as the foundation for subsequent simulation calculations. Taking the base building model of a commercial complex as an example, the aforementioned heat load parameter combinations are substituted into the model, and the corresponding parameter settings in the model are modified. Then, simulation calculations are performed on the mechanical and electrical equipment parameters in the base building model based on the currently applied heat load parameter combinations. For example, based on the heat load calculation results, classical HVAC theory formulas are used to calculate mechanical and electrical equipment parameters such as chiller capacity, chilled water flow, cooling water flow, pump flow, and fan coil unit water and air flow. Through simulation calculations, a heat load model matching the current heat load parameter combination is generated. By repeatedly applying different heat load parameter combinations to the base building model for simulation calculations, multiple different heat load models matching each base building model can be generated, providing rich data support for subsequent building simulations and data analysis.

[0037] S120 : In response to the user's operation of setting the operation-related parameter type and its optional value, generate each building simulation model that matches each heat load model.

[0038] The operation-related parameter types include at least one of: source-side equipment efficiency, distribution equipment efficiency, terminal equipment efficiency, room air-conditioning set temperature, and air infiltration intensity.

[0039] Among them, the operation-related parameter type refers to a series of parameters that have a significant impact on the building's energy consumption, indoor environmental comfort, etc. during the operation of the building; further, the source-side equipment efficiency is often measured by the efficiency (COP) of the source-side equipment, which is a key indicator for evaluating the source-side equipment (such as cold and heat source equipment, such as chillers, boilers, etc.) to convert energy into effective cooling or heating capabilities; the distribution equipment efficiency involves the efficiency of equipment responsible for transporting energy (such as hot and cold water, air, etc.) in the building, such as water pumps, fans, etc.; the terminal equipment efficiency refers to the efficiency of equipment that directly serves the indoor space and meets the needs of the indoor environment, such as fan coil units, air-conditioning boxes, etc. Taking fan coil units as an example, their efficiency affects the ability to deliver hot and cold air indoors, as well as energy consumption. Setting the terminal unit efficiency to 100%, 80%, and 120% simulates terminal unit performance under different operating conditions, helping to analyze the relationship between terminal unit performance, indoor environmental quality, and energy consumption. The room air conditioning setpoint temperature represents the desired indoor temperature set by the user. By simulating different room air conditioning setpoint temperatures, their combined impact on building energy consumption and indoor comfort can be studied, providing a reference for developing reasonable air conditioning operation strategies. The air infiltration intensity measures the degree to which outdoor air infiltrates the interior through gaps in the building envelope, with selectable values ​​such as 1, 2, and 0.5, providing a quantitative representation of air infiltration. Air infiltration can exchange heat or cooling, affecting indoor temperature stability and building energy consumption.

[0040] S130: Aggregate the building simulation models to obtain a simulation model set that matches the basic building models, and generate a building model construction result that matches the simulation model set and send it to a display device for display.

[0041] Among them, generating a building model construction result that matches the simulation model set and sending it to a display device for display, including: respectively counting the total number of basic building models, the total number of heat load parameter combination results, the total number of operating parameter combination results and the total number of building simulation models in the simulation model set; calculating the total number of basic building models × the total number of heat load parameter combination results × the total number of operating parameter combination results, and judging whether the calculation result is equal to the total number of building simulation models in the simulation model set; if equal, generating a building model construction success result based on the total number of building simulation models in the simulation model set and sending it to the display device; if not equal, generating an error prompt message and sending it to the display device to prompt the user.

[0042] In a specific implementation scenario of this embodiment, when generating building model construction results that match a simulation model set and sending them to a display device for display, the specific operations are as follows: 1) Counting: Counting the total number of basic building models, the total number of heat load parameter combination results, the total number of operating parameter combination results, and the total number of building simulation models in the simulation model set. Assume that in a building simulation project, three basic building models are established. Through orthogonal combination, 16 heat load parameter combination results and 27 operating parameter combination results are obtained. The resulting simulation model set contains 1296 building simulation models. 2) Calculation and Judgment: Calculate the total number of basic building models × the total number of heat load parameter combination results × the total number of operating parameter combination results (i.e., 3 × 16 × 27 = 1296). This calculated result is then compared with the total number of building simulation models in the simulation model set for evaluation. The principle behind this calculation and judgment process is based on the theoretical model construction logic of building simulation. Ideally, the number of simulation models generated by applying different parameter combinations to the basic models should equal the theoretical number calculated according to combinatorial mathematics principles. If the two are equal, it means that the entire simulation process is accurate in the number of models built, and there is no omission or incorrect generation of models; if they are not equal, it means that there may be problems such as data errors, abnormal simulation process or parameter combination calculation errors. 3) Result generation and transmission: If the calculation result is equal to the total number of building simulation models in the simulation model set, the building model construction success result is generated based on the total number of building simulation models in the simulation model set and sent to the display device. For example, in the above example, since the calculation result 1296 is equal to the total number of building simulation models in the simulation model set, the display device will display the message "The building model was successfully built, and a total of 1296 building simulation models were generated", allowing the user to intuitively understand that the simulation process was successfully completed and the number of models is correct. If the calculation result is not equal to the total number of building simulation models in the simulation model set, the system will generate an error prompt message and send it to the display device to prompt the user. For example, if the calculated result is 1000, but the simulation model set contains 1200 models, the display device may display "An exception occurred in the building model construction. The calculated number of models does not match the actual number of generated models. Please check the simulation process and parameter settings." This reminds the user to promptly troubleshoot the problem and ensure the reliability of the simulation results. Through this rigorous process, users can clearly understand the status of the building model construction and promptly identify and resolve any problems, ensuring the smooth progress of building simulation work.

[0043] Optionally, after aggregating the building simulation models to obtain a simulation model set that matches the basic building models, the method further includes: generating a training sample set based on the basic building models, the heat load parameter combination results, the operation parameter combination results, and the building simulation models, wherein the building simulation models serve as labeled data in the training sample set; using the training sample set to train the building AI operation and maintenance large model to obtain a building simulation working condition generation model, wherein the building simulation working condition generation model is used to generate a target simulation working condition model based on the user-set basic building model, at least one heat load-related parameter type and its value, and at least one operation-related parameter type and its value.

[0044] For example, in a specific implementation scenario of this embodiment, after obtaining the simulation model set, a training sample set is generated based on each basic building model, each heat load parameter combination result, each operating parameter combination result, and each building simulation model, and the building simulation model is used as the labeled data in the training sample set. Next, this training sample set is used to train the building AI operation and maintenance large model. The building AI operation and maintenance large model is a model based on artificial intelligence technology, which has powerful data learning and pattern recognition capabilities. By learning a large amount of data in the training sample set, the model can gradually grasp the relationship between different basic building models, heat load parameters and operating parameters and the actual operating status of the building. For example, the model can learn what kind of changing trend the building's energy consumption will show when it is in the northern region (specific regional parameters), the building faces south (specific building orientation parameters), and the source side equipment efficiency is low (specific operating parameters). After training with a large amount of data, a building simulation working condition generation model is obtained. This building simulation working condition generation model is a tool specifically used to generate a target simulation working condition model. After the user sets the basic building model, at least one heat load-related parameter type and its value, and at least one operation-related parameter type and its value, the building simulation working condition generation model can generate the corresponding target simulation working condition model based on the previously learned knowledge. For example, the user is given a basic building model of a new shopping mall, sets the heat load-related parameters (such as the region is Chengdu, the wall heat transfer coefficient is 100%) and operation-related parameters (such as the terminal equipment efficiency is 80%, and the room air conditioning set temperature is 27.5°C). The building simulation working condition generation model will use the rules it has learned to generate a target simulation working condition model that simulates the mall's operation under these conditions. This target simulation working condition model can predict key indicators such as the mall's energy consumption and indoor comfort, providing valuable reference for architectural designers and operation managers, helping them to evaluate the performance of the building under different design and operation conditions in advance, so as to make more reasonable decisions.

[0045] The technical solution of the embodiment of the present invention first obtains at least one pre-set basic building model, and generates each heat load model matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type. Then, in response to the user's setting operation of the operation-related parameter type and its optional value, each building simulation model matching each heat load model is generated. Finally, each building simulation model is aggregated to obtain a simulation model set matching each basic building model. At the same time, a building model construction result matching the simulation model set is generated and sent to a display device for display, thereby realizing batch construction of building simulation models, improving the construction efficiency of building simulation models, and ensuring the rationality of the building simulation model construction results.

[0046] Example 2

[0047] Figure 2 This is a flowchart of a method for batch building simulation models provided in Example 2 of the present invention. This embodiment is refined based on the above embodiment. In this embodiment, the method of generating each building simulation model that matches each heat load model in response to the user's operation-related parameter type and its optional value setting operation is specifically refined.

[0048] like Figure 2 As shown, the method includes:

[0049] S210: Acquire at least one pre-set basic building model, and generate heat load models matching each basic building model by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type.

[0050] S220: Obtain at least one optional value of each operation-related parameter type, perform orthogonal combinations on the optional values ​​of the operation-related parameter types through an orthogonal test method, and obtain operation parameter combination results that match each operation-related parameter type.

[0051] The operation parameter combination includes an optional value for each operation-related parameter type, and the number of the optional values ​​is consistent with the number of operation-related parameter types.

[0052] Specifically, after obtaining at least one optional value for each operation-related parameter type, orthogonal combinations of these optional values ​​are performed using the orthogonal experiment method. The orthogonal experiment method is a scientific and rational experimental design method that selects representative combinations from a large number of experimental combinations for testing. This method not only reduces the number of experiments but also ensures the reliability and validity of the test results. For example, for five operation-related parameter types—source-side equipment efficiency (COP), transmission and distribution equipment efficiency, terminal equipment efficiency, room air conditioning set temperature, and air infiltration intensity—each parameter type has three optional values. Using the traditional Cartesian product combination method, a total of 3 × 3 × 3 × 3 × 3 = 243 combinations would be generated. However, using the orthogonal experiment method, some representative combinations can be selected from these 243 combinations for testing. Through the orthogonal experiment method, the results of each operation parameter combination matching each operation-related parameter type are obtained. Each operation parameter combination result contains one optional value for each operation-related parameter type, and the number of optional values ​​matches the number of operation-related parameter types. For example, an operating parameter combination might result in a source-side equipment efficiency (COP) of 5, a transmission and distribution equipment efficiency of 80%, a terminal equipment efficiency of 120%, a room air conditioning setpoint temperature of 26°C, and an air infiltration intensity of 1. These operating parameter combinations provide key parameter basis for the subsequent construction of building models for different operating conditions, helping to more efficiently and accurately simulate building performance under various operating conditions.

[0053] S230. Apply each operating parameter combination result to each heat load model respectively, and simulate and calculate each electromechanical equipment parameter in the heat load model based on the currently applied operating parameter combination result to obtain a building simulation model that matches the current operating parameter combination result.

[0054] Based on the above steps, for example, a heat load model has been constructed. This model is generated based on factors such as the building structure and location of an office building, reflecting the changes in the building's heat load across different seasons and time periods. When the aforementioned operating parameter combination (source-side equipment efficiency of 5, distribution equipment efficiency of 80%, terminal equipment efficiency of 100%, room air conditioning set temperature of 26°C, and air infiltration intensity of 1) is applied to this heat load model, it is equivalent to setting a simulation scenario for the office building under these specific operating conditions. Then, based on the results of the currently applied operating parameter combination, the parameters of each electromechanical device in the heat load model are simulated and calculated. This process requires the use of professional building simulation software such as EnergyPlus, Dest, and DOE-2. Taking the chiller as an example, in the heat load model, the chiller capacity is determined based on the heat load and factors such as the source-side equipment efficiency in the operating parameters. Based on classic HVAC theory formulas, combined with the heat load data from the heat load model and the set source-side equipment efficiency (e.g., 5), the cooling capacity required by the chiller under these operating conditions can be calculated, thereby determining the chiller's capacity. For example, for a water pump, its flow rate parameters need to take into account factors such as the efficiency of the distribution equipment and the chiller's cooling capacity. If the distribution equipment efficiency is 80%, this means there will be a certain amount of energy loss during the transportation of hot and cold water. Based on these conditions, the required flow rate of the water pump is calculated to meet the operating requirements of the chiller and terminal equipment. For fan coil units, the water and air flow rates are calculated based on factors such as the terminal equipment efficiency, the room air conditioning set temperature, and the heat load. When the terminal equipment efficiency is 100% and the room air conditioning set temperature is 26°C, simulation calculations can determine the appropriate water and air flow rates required by the fan coil unit to maintain a stable indoor temperature. Through these simulations, a building simulation model is ultimately generated that matches the current operating parameter combination. This building simulation model comprehensively reflects various aspects of the building's energy consumption, indoor temperature distribution, and equipment operating status under specific heat load conditions and operating parameter settings. For example, a building simulation model calculated through calculation may show that, under a certain combination of operating parameters, the total power consumption of an office building on a certain summer day is X degrees, and the indoor temperature of each floor can be stably maintained at around 26 degrees Celsius. The operating hours and load conditions of electromechanical equipment such as chillers, water pumps, and fan coil units also have corresponding simulation data. This data provides valuable reference for architectural designers, energy managers, etc., helping them evaluate the performance of buildings under different operating conditions, and then optimize building design and operation strategies to improve the building's energy utilization efficiency and indoor environmental comfort.

[0055] S240: Aggregate the building simulation models to obtain a simulation model set that matches the basic building models, and generate a building model construction result that matches the simulation model set and send it to a display device for display.

[0056] The technical solution of the embodiment of the present invention first obtains at least one pre-set basic building model, sets at least one heat load-related parameter type and an optional value matching the heat load-related parameter type, generates each heat load model matching each basic building model, then obtains at least one optional value of each operation-related parameter type, performs orthogonal combination of each optional value of the operation-related parameter type through an orthogonal test method, obtains each operation parameter combination result matching each operation-related parameter type, then applies each operation parameter combination result to each heat load model, and simulates and calculates each electromechanical equipment parameter in the heat load model based on the currently applied operation parameter combination result to obtain a building simulation model matching the current operation parameter combination result, finally aggregates each building simulation model to obtain a simulation model set matching each basic building model, and simultaneously generates a building model construction result matching the simulation model set and sends it to a display device for display, thereby realizing batch construction of building simulation models, improving the construction efficiency of building simulation models, and ensuring the rationality of building simulation model construction results.

[0057] Example 3

[0058] Figure 3 This is a structural diagram of a device for batch building simulation models provided by Example 3 of the present invention.

[0059] like Figure 3 As shown, the device includes:

[0060] The heat load parameter setting module 310 is configured to obtain at least one pre-set basic building model and generate heat load models matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type.

[0061] An operation parameter setting module 320 is configured to generate respective building simulation models that match respective heat load models in response to a user's setting operation of the operation-related parameter type and its optional value;

[0062] The result display model 330 is used to aggregate the various building simulation models to obtain a simulation model set that matches each basic building model, and at the same time generate a building model construction result that matches the simulation model set and send it to a display device for display.

[0063] The technical solution of the embodiment of the present invention first obtains at least one pre-set basic building model, and generates each heat load model matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type. Then, in response to the user's setting operation of the operation-related parameter type and its optional value, each building simulation model matching each heat load model is generated. Finally, each building simulation model is aggregated to obtain a simulation model set matching each basic building model. At the same time, a building model construction result matching the simulation model set is generated and sent to a display device for display, thereby realizing batch construction of building simulation models, improving the construction efficiency of building simulation models, and ensuring the rationality of the building simulation model construction results.

[0064] Based on the above embodiment, the heat load parameter setting module 310 includes:

[0065] a first orthogonal combination unit, configured to obtain at least one optional value for each heat load related parameter type, and perform orthogonal combination of the optional values ​​for each heat load related parameter type through an orthogonal test method to obtain heat load parameter combination results that match each heat load related parameter type, wherein the heat load parameter combination results include one optional value for each heat load related parameter type, and the number of the optional values ​​is consistent with the number of heat load related parameter types;

[0066] The first equipment parameter calculation unit is used to apply the results of each heat load parameter combination to the basic building model, and simulate and calculate the parameters of each electromechanical equipment in the basic building model based on the currently applied heat load parameter combination result to obtain a heat load model that matches the current heat load parameter combination result.

[0067] Based on the above embodiment, the operation parameter setting module 320 includes:

[0068] a second orthogonal combination unit, configured to obtain at least one optional value for each operation-related parameter type, and perform orthogonal combination of the optional values ​​of the operation-related parameter type through an orthogonal test method to obtain operation parameter combination results that match the operation-related parameter type, wherein the operation parameter combination includes one optional value for each operation-related parameter type, and the number of the optional values ​​is consistent with the number of the operation-related parameter types;

[0069] The second equipment parameter calculation unit is used to apply the results of each operating parameter combination to each heat load model respectively, and simulate and calculate the parameters of each electromechanical equipment in the heat load model based on the currently applied operating parameter combination result to obtain a building simulation model that matches the current operating parameter combination result.

[0070] Based on the above embodiment, the result display model 330 includes:

[0071] A quantity statistics unit is used to respectively count the total number of basic building models, the total number of heat load parameter combination results, the total number of operation parameter combination results, and the total number of building simulation models in the simulation model set;

[0072] a quantity judgment unit, configured to calculate the total number of basic building models × the total number of heat load parameter combination results × the total number of operation parameter combination results, and to judge whether the calculation result is equal to the total number of building simulation models in the simulation model set;

[0073] A first result generating unit is configured to generate a building model construction success result based on the total number of building simulation models in the simulation model set and send the result to a display device if the result is equal to the total number of building simulation models in the simulation model set;

[0074] The second result generating unit is used to generate an error prompt message and send it to the display device if it is not equal to, so as to prompt the user.

[0075] On the basis of the above embodiment, the result display model 330 is also used to: aggregate the building simulation models to obtain a simulation model set that matches the basic building models, and then generate a training sample set based on the basic building models, the heat load parameter combination results, the operation parameter combination results and the building simulation models, wherein the building simulation model serves as the labeled data in the training sample set; use the training sample set to train the building AI operation and maintenance large model to obtain a building simulation working condition generation model, wherein the building simulation working condition generation model is used to generate a target simulation working condition model based on the basic building model set by the user, at least one heat load related parameter type and its value, and at least one operation related parameter type and its value.

[0076] An apparatus for batch building simulation models provided by an embodiment of the present invention can execute a method for batch building simulation models provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0077] Example 4

[0078] Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment 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 processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0079] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12 and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0080] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0081] Processor 11 can be any general-purpose and / or specialized processing component 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 specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as a method for batch building simulation models.

[0082] Accordingly, the method includes:

[0083] Acquire at least one preset basic building model, and generate heat load models matching each basic building model by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type;

[0084] In response to the user's setting operation of the operation-related parameter type and its optional value, generating each building simulation model that matches each heat load model;

[0085] The building simulation models are aggregated to obtain a simulation model set that matches the basic building models. At the same time, a building model construction result that matches the simulation model set is generated and sent to a display device for display.

[0086] In some embodiments, a method for batch building simulation models can be implemented as a computer program tangibly embodied 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 batch building simulation models described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the method for batch building simulation models in any other appropriate manner (e.g., by means of firmware).

[0087] Various embodiments of the systems and techniques described 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), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0088] Computer programs for implementing 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 the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0089] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0090] 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 can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the 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 acoustic input, voice input, or tactile input).

[0091] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0092] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0093] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

Claims

1. A method for batch building simulation models, characterized in that: include: Acquire at least one preset basic building model, and generate heat load models matching each basic building model by setting at least one heat load related parameter type and an optional value matching the heat load related parameter type; In response to the user's setting operation of the operation-related parameter type and its optional value, generating each building simulation model that matches each heat load model; The building simulation models are aggregated to obtain a simulation model set that matches the basic building models. At the same time, a building model construction result that matches the simulation model set is generated and sent to a display device for display.

2. The method according to claim 1, characterized in that The heat load related parameter types include: at least one of regional information, building orientation information, wall heat transfer coefficient, glass heat transfer coefficient, business hours and customer flow information.

3. The method according to claim 1, characterized in that By setting at least one heat load related parameter type and an optional value matching the heat load related parameter type, each heat load model matching each basic building model is generated, including: Obtaining at least one optional value of each heat load related parameter type, performing orthogonal combinations of the optional values ​​of each heat load related parameter type through an orthogonal test method, and obtaining heat load parameter combination results that match each heat load related parameter type, wherein the heat load parameter combination results include one optional value of each heat load related parameter type, and the number of the optional values ​​is consistent with the number of heat load related parameter types; The results of each heat load parameter combination are applied to the basic building model respectively, and the parameters of each electromechanical equipment in the basic building model are simulated and calculated based on the currently applied heat load parameter combination results to obtain a heat load model that matches the current heat load parameter combination results.

4. The method according to claim 1, wherein The operation-related parameter types include: at least one of: source-side equipment efficiency, distribution equipment efficiency, terminal equipment efficiency, room air-conditioning set temperature, and air infiltration intensity.

5. The method according to claim 1, wherein In response to the user's setting of the operation-related parameter type and its optional value, each building simulation model matching each heat load model is generated, including: Obtaining at least one optional value for each operation-related parameter type, performing orthogonal combinations of the optional values ​​of the operation-related parameter types through an orthogonal test method, and obtaining operation parameter combination results that match each operation-related parameter type, wherein the operation parameter combination includes one optional value for each operation-related parameter type, and the number of the optional values ​​is consistent with the number of the operation-related parameter types; The results of each operating parameter combination are applied to each heat load model respectively, and the parameters of each electromechanical equipment in the heat load model are simulated and calculated based on the currently applied operating parameter combination results to obtain a building simulation model that matches the current operating parameter combination results.

6. The method according to claims 1-5, characterized in that Generating a building model construction result that matches the simulation model set and sending it to a display device for display, including: Count the total number of basic building models, the total number of heat load parameter combination results, the total number of operation parameter combination results, and the total number of building simulation models in the simulation model set; Calculate the total number of basic building models × the total number of heat load parameter combination results × the total number of operation parameter combination results, and determine whether the calculation result is equal to the total number of building simulation models in the simulation model set; If they are equal, generating a building model construction success result based on the total number of building simulation models in the simulation model set and sending it to the display device; If not, an error message is generated and sent to the display device to prompt the user.

7. The method according to claim 1, characterized in that After aggregating the building simulation models to obtain a set of simulation models that match the basic building models, the following also applies: Generating a training sample set based on each basic building model, each heat load parameter combination result, each operating parameter combination result, and each building simulation model, wherein the building simulation model serves as labeled data in the training sample set; The building AI operation and maintenance large model is trained using the training sample set to obtain a building simulation working condition generation model, wherein the building simulation working condition generation model is used to generate a target simulation working condition model based on a basic building model set by a user, at least one heat load-related parameter type and its value, and at least one operation-related parameter type and its value.

8. A device for batch building building simulation models, characterized in that: include: a heat load parameter setting module, configured to obtain at least one pre-set basic building model, and generate heat load models matching each basic building model by setting at least one heat load-related parameter type and an optional value matching the heat load-related parameter type; An operation parameter setting module, configured to generate respective building simulation models that match respective heat load models in response to a user's operation of setting operation-related parameter types and their optional values; The result display model is used to aggregate the various building simulation models to obtain a simulation model set that matches each basic building model, and at the same time generate a building model construction result that matches the simulation model set and send it to a display device for display.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform a method for batch constructing building simulation models according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a method for batch constructing building simulation models according to any one of claims 1 to 7 when executed.

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