Data inspection method and device based on EnergyPlus simulation result and medium

Abstract

The invention discloses a data checking method and device based on an EnergyPlus simulation result and a medium. The method comprises the following steps: determining target static data based on an analysis result of a target simulation configuration file in EnergyPlus; wherein the target static data comprises a target object and an attribute of the target object; determining target time sequence operation data of the target object based on an analysis result of a target simulation result file corresponding to the target simulation configuration file; determining a target data item according to the target data inspection task, and determining a target inspection mode of the target data item; determining a to-be-tested object and a to-be-tested attribute of the to-be-tested object from the target static data according to the target data item, and determining to-be-tested time sequence operation data associated with the to-be-tested attribute of the to-be-tested object from the target time sequence operation data; and performing data inspection on the to-be-detected time sequence operation data according to the target inspection mode to obtain a data inspection result. According to the technical scheme, the checking efficiency and applicability of the EnergyPlus simulation data can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data checking method, device and medium based on EnergyPlus simulation results. Background Art

[0002] EnergyPlus is a building simulation software widely used around the world. It can simulate the cooling, heating, lighting, ventilation, equipment operation and energy consumption of buildings. In some scenarios where the actual data volume is insufficient, using EnergyPlus to quickly produce a large amount of data is a good way to supplement the data.

[0003] Since EnergyPlus modeling is extremely complex and various parameter settings rely on the experience of designers, it is common for simulation results to not conform to physical cognition or engineering experience in some aspects. This requires a convenient way to check the simulation result data to guide the modification of the EnergyPlus model or directly screen the result data to ensure that the quality of the simulation data can meet the needs of subsequent use.

[0004] There is a software called xEsoView on the market that can view the simulation results of EnergyPlus in the form of a line graph. However, it only supports viewing one indicator at a time and has poor performance. It is not capable of multi-scenario inspections of large amounts of data. Summary of the invention

[0005] The present invention provides a data inspection method, device and medium based on EnergyPlus simulation results, which can quickly and effectively inspect the EnergyPlus simulation results through an inspection method determined based on a data inspection task, thereby greatly improving the efficiency and applicability of data inspection.

[0006] According to one aspect of the present invention, a data checking method based on EnergyPlus simulation results is provided, the method comprising:

[0007] Determine target static data based on the parsing result of the target simulation configuration file in EnergyPlus; wherein the target static data includes target object data and association relationship data between the target object data, and the target object data includes a target object, an object type to which the target object belongs, and attributes of the target object;

[0008] Determine the target time series operation data of the target object based on the parsing result of the target simulation result file corresponding to the target simulation configuration file; wherein the target time series operation data is represented in the form of operation state time slices of the target object;

[0009] Determine a target data item according to the target data inspection task, and determine a target inspection method for the target data item; wherein the target data item includes a target object type and a target attribute type of the target object type;

[0010] Determine the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item, and determine the time series operation data to be tested associated with the property to be tested of the object to be tested from the target time series operation data;

[0011] A data check is performed on the timing operation data to be tested according to the target check method to obtain a data check result.

[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0013] at least one processor; and,

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] 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 data checking method based on EnergyPlus simulation results described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the data inspection method based on EnergyPlus simulation results described in any embodiment of the present invention when executed.

[0017] The technical solution of the embodiment of the present invention determines the target static data based on the parsing result of the target simulation configuration file in EnergyPlus; wherein the target static data includes the target object data and the association relationship data between the target object data, and the target object data includes the target object, the object type to which the target object belongs, and the attributes of the target object; based on the parsing result of the target simulation result file corresponding to the target simulation configuration file, the target timing operation data of the target object is determined; wherein the target timing operation data is characterized in the form of a time slice of the operation state of the target object; according to the target data inspection task, the target data item is determined, and the target inspection method of the target data item is determined; wherein the target data item includes the target object type and the target attribute type of the target object type; according to the target data item, the object to be tested and the attribute to be tested of the object to be tested are determined from the target static data, and the timing operation data to be tested associated with the attribute to be tested of the object to be tested is determined from the target timing operation data; according to the target inspection method, the timing operation data to be tested is inspected to obtain the data inspection result. This technical solution can quickly and effectively inspect the EnergyPlus simulation results through the inspection method determined based on the data inspection task, which greatly improves the efficiency and applicability of data inspection.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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.

[0020] Figure 1 is a flow chart of a data checking method based on EnergyPlus simulation results provided according to Embodiment 1 of the present invention;

[0021] Figure 2 is a schematic diagram of the structure of target object data provided according to the first embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of the structure of target static data provided according to the first embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of a process for determining target runtime data provided by Embodiment 1 of the present invention;

[0024] Figure 5 is a flow chart of a data checking method based on EnergyPlus simulation results provided according to Embodiment 2 of the present invention;

[0025] Figure 6 is a structural schematic diagram of a data inspection device based on EnergyPlus simulation results provided according to Embodiment 3 of the present invention;

[0026] Figure 7 It is a structural schematic diagram of an electronic device for implementing a data checking method based on EnergyPlus simulation results according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", "target", etc. 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 sequence. It should be understood that the data used in this way can be interchanged 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, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] Figure 1 The flowchart of a data checking method based on EnergyPlus simulation results provided in the first embodiment of the present invention is applicable to the case of performing data checking on EnergyPlus simulation results. The method can be performed by a data checking device based on EnergyPlus simulation results. The data checking device based on EnergyPlus simulation results can be implemented in the form of hardware and / or software. The data checking device based on EnergyPlus simulation results can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes:

[0031] S110, determining target static data based on the parsing result of the target simulation configuration file in EnergyPlus.

[0032] Among them, the simulation configuration file (i.e., idf file) can be used as an input item for EnergyPlus simulation operation, and can be used to describe the simulation object (i.e., the object defined in EnergyPlus, such as a building structure or electromechanical equipment), simulation operation control logic and simulation configuration parameters (including simulation data items and corresponding parameter values). The target simulation configuration file may refer to the idf file that needs to be simulated. The target static data includes the target object data and the association relationship data between the target object data. The target object data includes the target object, the object type to which the target object belongs, and the attributes of the target object. Among them, the target object may refer to an object defined in the building physical world, and the attributes of the target object may include static attributes and dynamic attributes. Figure 2 Schematic diagram of the structure of target object data provided by the first embodiment of the present invention. The information point represents an attribute, and the object ID can be used to uniquely identify the target object. Figure 2 As shown, the target object is room 1 (and the object ID is SP01), the object type to which room 1 belongs is room, the static attributes of room 1 include area and orientation, etc., and the dynamic (time sequence state) attributes of room 1 include set temperature, temperature and relative humidity, etc. The association relationship data between target object data can be characterized by the association relationship between target objects. Among them, the association relationship between target objects can include affiliation, connection relationship and service relationship, etc.

[0033] In this embodiment, the target simulation configuration file in EnergyPlus is first obtained, and the target simulation configuration file is parsed, and then the parsing result is converted into target static data. The specific process is as follows:

[0034] 1. Get the data dictionary definition file in EnergyPlus, and parse the data dictionary definition file to get the class library structure. The data dictionary definition file (i.e., idd file) can be used to describe the EnergyPlus class structure definition, i.e., the data dictionary parsing specification. The class library structure includes object types and attribute types corresponding to object types, which can serve as the basis for subsequent simulation file parsing and data conversion. For example, taking room as an object type, its corresponding attribute types may include area, height, and orientation, etc.

[0035] 2. Based on the class library structure of EnergyPlus, the target simulation configuration file is parsed through the EnergyPlus input model parser, the types and attributes of each definition in the idf file are identified, the corresponding object instances (including simulation objects and the attributes of simulation objects) are constructed, and the dependent reference associations between object instances (i.e. the reference relationships between simulation objects) are calculated.

[0036] 3. From the hierarchical perspective of "building -> floor -> space" and "mechanical system -> mechanical and electrical equipment", convert the simulation objects and their properties in EnergyPlus to the target objects and their properties in the building physics world. It should be noted that there is no concept of floor and mechanical and electrical system in EnergyPlus, and an mechanical and electrical equipment in the building physics world may correspond to one or more mechanical and electrical equipment in EnergyPlus, and an mechanical and electrical system in the building physics world may correspond to one or more circuits in EnergyPlus.

[0037] 4. Determine the association relationship between target objects based on the reference relationship between simulation objects. It should be noted that the simulation configuration file in EnergyPlus contains a wealth of attribute definitions, and there are mutual references between instance objects. Therefore, through the calculation and judgment of some attributes, and referring to the reference logic between instance objects, various types of "association relationships between objects" required in the physical world can be constructed. Through the above data parsing and conversion process, the target static data can be obtained.

[0038] Figure 3 A schematic diagram of the structure of target static data provided in the first embodiment of the present invention. The EnergyPlus model represents the target simulation configuration file, and the static object data represents the target object data, which specifically includes the space enclosure structure and equipment (simplified here, the specific structure can be seen in Figure 2 ); the object association relationship data is the association relationship data between the target object data. Figure 3 As shown, by parsing and converting the EnergyPlus model, target static data including static object data and relationship data between objects can be obtained.

[0039] S120, determining target timing operation data of the target object based on the parsing result of the target simulation result file corresponding to the target simulation configuration file.

[0040] Among them, the simulation result file (ie, eso file) can be used as an output item of the EnergyPlus simulation operation, and can be used to describe the simulation data items and their corresponding simulation runtime data. Among them, the simulation runtime data can be understood as the runtime data directly output by EnergyPlus. The target simulation result file can refer to the eso file corresponding to the target simulation configuration file. The target timing operation data is characterized by the operating state time slice form of the target object.

[0041] In this embodiment, it is also necessary to obtain the target simulation result file corresponding to the target simulation configuration file in EnergyPlus, parse the target simulation result file, and then perform data conversion on the parsed result to obtain the target timing operation data of the target object. The specific process is as follows: 1. Obtain the data dictionary definition file in EnergyPlus, and parse the data dictionary definition file to obtain the class library structure. 2. Based on the class library structure of EnergyPlus, parse the target simulation result file through the EnergyPlus output data parser to obtain simulation data items and their corresponding simulation operation timing data. Among them, the simulation timing operation data is recorded one by one based on a single indicator item. 3. Aggregate the simulation operation timing data in the object dimension to construct the timing data in the real-time state slice format of the object (that is, the target operation timing data corresponding to the target object). Figure 4 A schematic diagram of a process for determining target runtime data provided by the first embodiment of the present invention. Figure 4 As shown, by performing data analysis and conversion on the EnergyPlus simulation results, the target runtime data of the target object can be obtained.

[0042] S130, determining a target data item according to the target data inspection task, and determining a target inspection method for the target data item.

[0043] Among them, the target data inspection task can be used to describe the main object that needs to be inspected and the inspection content. The target data item includes the target object type and the target attribute type of the target object type. It should be noted that the target data item mainly focuses on which data needs to be inspected, and the target inspection method mainly focuses on the execution logic and output results of the data inspection. Exemplarily, taking the target data item as the room environment as an example, its typical configuration is as follows: target data item: room environment, target object type: room, target attribute type: [temperature, humidity, set temperature].

[0044] In this embodiment, optionally, determining the target data item according to the target data inspection task includes: determining the data item to be tested according to the target data inspection task; determining the reference data item associated with the data item to be tested according to the association relationship data between the target object data; and determining the target data item according to the data item to be tested and the reference data item.

[0045] It should be noted that, since a certain data item has an association relationship with other data items, in order to improve the accuracy and comprehensiveness of data inspection, a comparison inspection method of multiple associated data items can be used to perform data inspection. Exemplarily, assuming that the data item to be tested is the room environment, it is determined that the fan coil unit is associated with the room through a service relationship based on the association relationship data between the target object data. At this time, the fan coil unit operation status can be used as a reference data item of the room environment, thereby taking the room environment and the fan coil unit operation status associated therewith as the target data item. Exemplarily, a typical configuration of a target data item using a comparison inspection method is as follows: data item to be tested: room environment, object type to be tested: room, attribute type to be tested: [temperature, humidity, set temperature]; reference data item: fan coil unit operation status, reference object type: fan coil unit, reference attribute type: [operating power, supply air temperature]; associated data item: room environment, relationship type: service relationship.

[0046] Since there are multiple rooms in the building and different fan coil units are installed in each room, an association relationship setting can be added to the reference data item to clarify that the fan coil units need to be associated with the rooms through a service relationship. In this way, multiple groups of data can be obtained for inspection. Each group of data contains the environmental data of a room and the operating status data of the fan coil units in this room.

[0047] Among them, the target inspection method can include qualitative inspection (such as manual analysis inspection) and quantitative inspection (such as formula / function inspection). The specific method can be flexibly set according to actual needs, such as selecting one of the methods or combining the two methods. Optionally, determining the target inspection method of the target data item includes: determining the target inspection function from a preset inspection function library according to the target data item; wherein the preset function inspection library includes inspection functions for multiple building field scenarios, and the inspection function includes calculation logic and judgment rules; determining the target inspection method of the target data item according to the target inspection function.

[0048] Among them, the preset function check library may refer to a pre-set database including check functions in multiple building field scenarios. The check function can be used as the basis for data inspection, specifically including calculation logic and judgment rules. Exemplarily, the preset function check library includes check functions corresponding to the building thermal process, the terminal equipment operation process and the cold source system operation process. Specifically, the check function corresponding to the building thermal process may include a reasonable range of room temperature, the temperature response inside and outside the building, the influence of the air-conditioning terminal on the room temperature, and the relationship between the air-conditioning set temperature and the total load of the building; the check function corresponding to the terminal equipment operation process may include a reasonable range of terminal supply / return air temperature, the relationship between terminal supply / return air temperature, a reasonable range of terminal supply / return water temperature, and a relationship between terminal supply / return water temperature; the check function corresponding to the cold source system operation process may include the relationship between the rated power of the equipment and the actual power, the relationship between the rated water flow of the equipment and the actual water flow, the reasonable range of chiller efficiency, the reasonable range of water pump efficiency, the reasonable range of cooling tower efficiency, the reasonable range of chilled water supply / return water temperature, the relationship between chilled water supply / return water temperature, the reasonable range of cooling water supply / return water temperature, the relationship between cooling water supply / return water temperature, and the consistency of operation of multiple devices.

[0049] In this embodiment, a preset function check library containing a series of check functions is pre-set according to the complexity of the building simulation to cover various scenarios from the heat exchange process to the operation of the equipment. When determining the target check method of the target data item, one or more check functions matching the target data item can be searched from the preset check function library as the target check function, and the target check function is determined as the target check method of the target data item. Among them, each target check function can be set with one or more parameters, which come from the target data item configuration.

[0050] Exemplarily, taking the typical configuration of a target data item using the above-mentioned comparative inspection method as an example, the target inspection function corresponding to the target data item can be set as: Inspection function 1: reasonable range of room temperature, parameters: [room environment. temperature, room environment. set temperature]; Inspection function 2: influence of air-conditioning terminal on room temperature, parameters: [fan coil. operating power, room environment. temperature, room environment. set temperature]. The above two inspection functions can be used to respectively perform rationality inspections on the room temperature and the relationship between the room temperature change trend and the fan coil.

[0051] Through such a setting, this solution can use function checking to perform rapid and quantitative checking on simulation data, which can be applied to massive data checking in multiple scenarios, effectively improving data checking efficiency.

[0052] S140, determining the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item, and determining the time series operation data to be tested associated with the property to be tested of the object to be tested from the target time series operation data.

[0053] In this embodiment, after determining the target data item, the object to be tested and the property to be tested of the object to be tested can be determined from the target static data according to the target data item, and then the time series operation data to be tested associated with the property to be tested of the object to be tested can be determined from the target time series operation data. Optionally, determining the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item includes: determining the object to be tested from the target object according to the target object type; determining the property to be tested from the property of the object to be tested according to the target property type of the target object type.

[0054] Exemplarily, assuming that the target object type is a room, and the target attribute type includes temperature, humidity, and set temperature, all room instantiations (such as room 1, room 2...room n) or some room instantiations in the target object can be determined as the object to be tested, and the temperature, humidity, and set temperature in the attributes of the object to be tested can be determined as the attributes to be tested. After determining the object to be tested and the attributes to be tested of the object to be tested, all or part of the data associated with the attributes to be tested of the object to be tested can be screened from the target time series operation data as the time series operation data to be tested.

[0055] S150, performing data inspection on the timing operation data to be tested according to the target inspection method to obtain a data inspection result.

[0056] In this embodiment, a function check method can be used to perform quantitative data check on the timing operation data to be tested. Optionally, the data check is performed on the timing operation data to be tested according to the target check method to obtain the data check result, including: performing data verification on each timing operation data to be tested according to the target check method to obtain the verification result of the timing operation data to be tested; wherein the verification result is passed or failed; based on the verification result, the verification pass rate of the timing operation data to be tested is determined, and the data inspection result of the timing operation data to be tested is determined according to the verification pass rate.

[0057] Specifically, firstly, the corresponding target check function is executed for each time series operation data to be tested, and the target check function is used to determine whether each time series operation data to be tested passes the data check, and the check result of each time series operation data to be tested is obtained. Then, the ratio of the amount of data of the time series operation data to be tested that passes the check to the total amount of data of the time series operation data to be tested is calculated, and the ratio is used as the check pass rate of the time series operation data to be tested. For example, there are 100 rooms in a building, and 10 "reasonable range of room temperature" checks are performed for each room, totaling 1000 function checks. Assuming that 5 times fail to pass the check, that is, 995 times pass the check, then the check pass rate is 99.5%. Further, the pass rate threshold (such as 90%) can be pre-set according to actual needs. When the check pass rate of the time series operation data to be tested is greater than the pass rate threshold, it can be considered that the data quality of the time series operation data to be tested is high. During the execution of the target check function, the error information that fails to pass the check can be recorded in the log, and the check pass rate of the check is counted and recorded in the log. By consulting the log, the data check result can be quickly and intuitively obtained. It should be noted that, in this embodiment, for multiple target data items, a parallel execution method can be used to perform data checks on the time series operation data to be tested corresponding to the target data items, thereby effectively improving the data check efficiency.

[0058] The technical solution of the embodiment of the present invention determines the target static data based on the parsing result of the target simulation configuration file in EnergyPlus; wherein the target static data includes the target object data and the association relationship data between the target object data, and the target object data includes the target object, the object type to which the target object belongs, and the attributes of the target object; based on the parsing result of the target simulation result file corresponding to the target simulation configuration file, the target timing operation data of the target object is determined; wherein the target timing operation data is characterized in the form of a time slice of the operation state of the target object; according to the target data inspection task, the target data item is determined, and the target inspection method of the target data item is determined; wherein the target data item includes the target object type and the target attribute type of the target object type; according to the target data item, the object to be tested and the attribute to be tested of the object to be tested are determined from the target static data, and the timing operation data to be tested associated with the attribute to be tested of the object to be tested is determined from the target timing operation data; according to the target inspection method, the timing operation data to be tested is inspected to obtain the data inspection result. This technical solution can quickly and effectively inspect the EnergyPlus simulation results through the inspection method determined based on the data inspection task, which greatly improves the efficiency and applicability of data inspection.

[0059] In this embodiment, optionally, after determining the data inspection result of the timing operation data to be tested according to the verification pass rate, it also includes: analyzing the change trend of the timing operation data to be tested to obtain the analysis result; and supplementing the data inspection result of the timing operation data to be tested according to the analysis result.

[0060] It should be noted that the quantitative inspection method may be subject to certain limitations in actual use. For example, the inspection function can only be set for certain inspection contents of certain scenarios, and may not cover all inspection contents. Therefore, in order to ensure the comprehensiveness and completeness of the data inspection, on the basis of the quantitative inspection method, a comprehensive data inspection can also be performed in combination with the qualitative inspection method. Specifically, after determining the timing operation data to be tested, the timing operation data to be tested can be plotted according to the time series to obtain a visual chart (such as a line chart). Then, through manual inspection or automated methods, the changing trend of the timing operation data to be tested is analyzed based on the visual chart to obtain the analysis results, and then the data inspection results of the timing operation data to be tested are supplemented according to the analysis results to obtain a more comprehensive data inspection result.

[0061] Through such a setting, the present solution can simultaneously realize quantitative and qualitative inspection of data through a fully automated method or a combination of automated inspection method and manual inspection method, thereby improving the comprehensiveness and completeness of data inspection and helping to improve the accuracy of data inspection.

[0062] Embodiment 2

[0063] Figure 5 A flowchart of a data checking method based on EnergyPlus simulation results provided in the second embodiment of the present invention is provided. This embodiment is optimized based on the above embodiment.

[0064] like Figure 5 As shown, the method of this embodiment specifically includes the following steps:

[0065] S210 , determining target static data based on the parsing result of the target simulation configuration file in EnergyPlus.

[0066] The target static data includes target object data and association relationship data between target object data, and the target object data includes the target object, the object type to which the target object belongs, and the attributes of the target object.

[0067] S220, determining target timing operation data of the target object based on the parsing result of the target simulation result file corresponding to the target simulation configuration file.

[0068] The target time series operation data is represented in the form of time slices of the operation status of the target object.

[0069] S230, determining a target data item according to the target data inspection task, and determining a target inspection method for the target data item.

[0070] The target data item includes a target object type and a target attribute type of the target object type. In addition, the specific implementation of S210-S230 can refer to the relevant description in the first embodiment, which will not be repeated here.

[0071] S240: Determine the target object corresponding to the target object type as a candidate object.

[0072] It should be noted that since simulation data is often in units of years and usually contains a large number of rooms and equipment, if a full data check is performed, it will take up too much time and computing resources, and in the scenario of manual qualitative analysis, too much data will also cause the inspectors to be unable to effectively view and analyze. Therefore, the strategy of data sampling inspection is adopted in this embodiment. Through the data sampling configuration, several time points and some objects can be extracted in a specified time period to perform inspection operations and obtain representative data inspection results. In addition to reducing the amount of data, data sampling can also provide a more focused perspective for data inspection tasks, and improve the pertinence and effectiveness of inspection rules (including target data items and target inspection functions). For example, assuming that the target object type is room, all room instantiations (such as room 1, room 2, ..., room n) can be determined as candidate objects.

[0073] S250: Determine a preset number of candidate objects as objects to be tested in a random manner.

[0074] The preset number may refer to the number of candidate objects preset according to actual needs, such as 15. In this embodiment, after the candidate objects are determined, a preset number of objects may be selected from the candidate objects as the objects to be tested by random sampling.

[0075] S260: Determine a property to be tested from the properties of the object to be tested according to the target property type of the target object type.

[0076] S270: Determine the target time series operation data associated with the property to be tested of the object to be tested as the candidate time series operation data.

[0077] In this embodiment, after the object to be tested and the property to be tested of the object to be tested are determined, data associated with the property to be tested of the object to be tested may be screened out from the target time series operation data as candidate time series operation data.

[0078] S280: Determine the timing operation data to be tested from the candidate timing operation data based on a preset sampling period and a preset sampling quantity.

[0079] The preset sampling period and the preset sampling number may refer to the sampling period and the number of sampling points preset according to actual needs, respectively. In this embodiment, after determining the candidate timing operation data, data can be extracted at equal intervals from the candidate timing operation data according to the preset sampling period and the preset sampling number, thereby obtaining the timing operation data to be tested.

[0080] Exemplarily, a typical configuration of a data inspection task is as follows: simulation data directory to be inspected: / sim_data_001, inspection rules: room environment inspection through inspection function, preset sampling period: cooling season, preset number of samples: 5, number of days included in each sampling point: 3, daily time period: air conditioning operation time, number of object samples of room environment (i.e. preset number): 15.

[0081] Specifically, in the above example, the location of the time series operation data to be tested (i.e., the simulation data directory to be checked) and the check rules to be used (including target data items and target check functions) are first specified. Then comes the sampling configuration of the time part, setting the preset sampling period to the air conditioning cooling season; the preset number of samples and the number of days included in each sampling point mean that 5 samples are taken during the entire cooling season, each containing 3 days, and the date intervals between multiple samples are the same, and only the data of the air conditioning on time is selected on each day. Finally, there is the sampling setting of the data object. You can set the screening conditions of the object to be tested for the target data item in the check rule, such as selecting up to 15 rooms for inspection.

[0082] S290, performing data inspection on the timing operation data to be tested according to the target inspection method to obtain a data inspection result.

[0083] The technical solution of the embodiment of the present invention adopts a data sampling inspection (including time sampling and object sampling) strategy. Through data sampling configuration, several time points and some objects can be extracted in a specified time period to perform inspection operations and obtain representative data inspection results. The above settings can effectively reduce the amount of data, improve the efficiency of data inspection, and provide a more focused perspective for data inspection tasks, thereby improving the pertinence and effectiveness of inspection rules (including target data items and target inspection functions).

[0084] Embodiment 3

[0085] Figure 6 This is a schematic diagram of the structure of a data inspection device based on EnergyPlus simulation results provided in Embodiment 3 of the present invention. The device can execute the data inspection method based on EnergyPlus simulation results provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. Figure 6 As shown, the device comprises:

[0086] A target static data determination module 310 is used to determine target static data based on the parsing result of the target simulation configuration file in EnergyPlus; wherein the target static data includes target object data and association relationship data between the target object data, and the target object data includes a target object, an object type to which the target object belongs, and attributes of the target object;

[0087] A target timing operation data determination module 320 is used to determine the target timing operation data of the target object based on the parsing result of the target simulation result file corresponding to the target simulation configuration file; wherein the target timing operation data is represented in the form of a time slice of the operation state of the target object;

[0088] A target inspection parameter determination module 330 is used to determine a target data item according to a target data inspection task, and determine a target inspection method for the target data item; wherein the target data item includes a target object type and a target attribute type of the target object type;

[0089] The module 340 for determining the time series operation data to be tested is used to determine the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item, and to determine the time series operation data to be tested associated with the property to be tested of the object to be tested from the target time series operation data;

[0090] The data inspection result determination module 350 is used to perform data inspection on the timing operation data to be tested according to the target inspection method to obtain a data inspection result.

[0091] Optionally, the target inspection parameter determination module 330 is used to:

[0092] Determine the data items to be tested according to the target data inspection task;

[0093] Determining a reference data item associated with the data item to be tested according to the association relationship data between the target object data;

[0094] The target data item is determined according to the data item to be tested and the reference data item.

[0095] Optionally, the to-be-tested timing operation data determination module 340 includes:

[0096] a to-be-tested object determining unit, configured to determine the to-be-tested object from the target objects according to the target object type;

[0097] The attribute to be measured determining unit is used to determine the attribute to be measured from the attributes of the object to be measured according to the target attribute type of the target object type.

[0098] Optionally, the object to be detected determining unit is used to:

[0099] Determine a target object corresponding to the target object type as a candidate object;

[0100] A preset number of candidate objects are determined randomly as the objects to be tested.

[0101] Optionally, the to-be-tested timing operation data determination module 340 is configured to:

[0102] Determine the target time series operation data associated with the property to be tested of the object to be tested as the candidate time series operation data;

[0103] The timing operation data to be tested is determined from the candidate timing operation data based on a preset sampling period and a preset sampling quantity.

[0104] Optionally, the target inspection parameter determination module 330 is further configured to:

[0105] Determine a target inspection function from a preset inspection function library according to the target data item; wherein the preset function inspection library includes inspection functions for multiple building field scenarios, and the inspection function includes calculation logic and judgment rules;

[0106] A target checking method for the target data item is determined according to the target checking function.

[0107] Optionally, the data inspection result determination module 350 is used to:

[0108] According to the target inspection method, data verification is performed on each of the time sequence operation data to be tested to obtain a verification result of the time sequence operation data to be tested; wherein the verification result is passed or failed;

[0109] A verification pass rate of the time sequence operation data to be tested is determined based on the verification result, and a data inspection result of the time sequence operation data to be tested is determined according to the verification pass rate.

[0110] Optionally, the device further comprises: a data inspection result supplement module, configured to:

[0111] After determining the data inspection result of the time series operation data to be tested according to the verification pass rate, analyzing the change trend of the time series operation data to be tested to obtain an analysis result;

[0112] The data inspection result of the timing operation data to be tested is supplemented according to the analysis result.

[0113] A data inspection device based on EnergyPlus simulation results provided in an embodiment of the present invention can execute a data inspection method based on EnergyPlus simulation results provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0114] Embodiment 4

[0115] Figure 7 A 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 required herein.

[0116] like Figure 7 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 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. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0117] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.

[0118] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the data checking method based on the EnergyPlus simulation results.

[0119] In some embodiments, the data checking method based on the EnergyPlus simulation results can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the data checking method based on the EnergyPlus simulation results described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the data checking method based on the EnergyPlus simulation results by any other appropriate means (e.g., by means of firmware).

[0120] Various implementations 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 chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including 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.

[0121] 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0122] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0123] To provide interaction with a user, the systems and techniques described herein may 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0124] The systems and techniques described herein may be implemented in a computing system that includes backend 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 frontend components (e.g., a user computer with a graphical user interface or a 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 backend components, middleware components, or frontend components. The components of the system may 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.

[0125] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0126] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0127] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A data checking method based on EnergyPlus simulation results, characterized in that: The method comprises: Determine target static data based on the parsing result of the target simulation configuration file in EnergyPlus; wherein the target static data includes target object data and association relationship data between the target object data, and the target object data includes a target object, an object type to which the target object belongs, and attributes of the target object; Determine the target time series operation data of the target object based on the parsing result of the target simulation result file corresponding to the target simulation configuration file; wherein the target time series operation data is represented in the form of operation state time slices of the target object; Determine a target data item according to the target data inspection task, and determine a target inspection method for the target data item; wherein the target data item includes a target object type and a target attribute type of the target object type; Determine the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item, and determine the time series operation data to be tested associated with the property to be tested of the object to be tested from the target time series operation data; A data check is performed on the timing operation data to be tested according to the target check method to obtain a data check result.

2. The method according to claim 1, characterized in that Determine the target data items according to the target data inspection task, including: Determine the data items to be tested according to the target data inspection task; Determining a reference data item associated with the data item to be tested according to the association relationship data between the target object data; The target data item is determined according to the data item to be tested and the reference data item.

3. The method according to claim 1, characterized in that Determining the object to be tested and the property to be tested of the object to be tested from the target static data according to the target data item includes: Determining an object to be tested from the target objects according to the type of the target object; According to the target attribute type of the target object type, the attribute to be measured is determined from the attributes of the object to be measured.

4. The method according to claim 3, characterized in that Determining an object to be detected from the target object according to the target object type includes: Determine a target object corresponding to the target object type as a candidate object; A preset number of candidate objects are determined randomly as the objects to be tested.

5. The method according to claim 4, characterized in that Determining the time series operation data to be tested associated with the property to be tested of the object to be tested from the target time series operation data includes: Determine the target time series operation data associated with the property to be tested of the object to be tested as the candidate time series operation data; The timing operation data to be tested is determined from the candidate timing operation data based on a preset sampling period and a preset sampling quantity.

6. The method according to any one of claims 1 to 5, characterized in that Determining a target inspection method for the target data item includes: Determine a target inspection function from a preset inspection function library according to the target data item; wherein the preset function inspection library includes inspection functions for multiple building field scenarios, and the inspection function includes calculation logic and judgment rules; A target checking method for the target data item is determined according to the target checking function.

7. The method according to claim 6, characterized in that Performing data inspection on the timing operation data to be tested according to the target inspection method to obtain a data inspection result includes: According to the target inspection method, data verification is performed on each of the time sequence operation data to be tested to obtain a verification result of the time sequence operation data to be tested; wherein the verification result is passed or failed; A verification pass rate of the time sequence operation data to be tested is determined based on the verification result, and a data inspection result of the time sequence operation data to be tested is determined according to the verification pass rate.

8. The method according to claim 7, characterized in that After determining the data inspection result of the timing operation data to be tested according to the verification pass rate, the method further includes: Analyze the change trend of the time series operation data to be tested to obtain analysis results; The data inspection result of the timing operation data to be tested is supplemented according to the analysis result.

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, and the computer program is executed by the at least one processor so that the at least one processor can perform the data checking method based on EnergyPlus simulation results according to any one of claims 1 to 8.

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 the data inspection method based on EnergyPlus simulation results according to any one of claims 1 to 8 when executed.

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