Energyplus-based simulation data processing method and device, equipment and medium

Abstract

Embodiments of the present application disclose a kind of based on EnergyPlus's simulation data processing method, device, equipment and medium. Among them, the method comprises: obtaining target simulation configuration file in EnergyPlus and target simulation configuration file corresponding target simulation result file;Determine target static data based on the analysis result of target simulation configuration file;Wherein, target static data includes target object, the attribute of target object and the association between target object;Determine the target running time sequence data of target object based on the analysis result of target simulation result file;According to target static data and the target running time sequence data of target object, determine target data.This technical solution, can be based on the simulation file analysis result of EnergyPlus Construction with static data and object dimension running time sequence data as the architecture target data, to provide direct data support for subsequent use of building field digital platform, help building simulation data fast and convenient application.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, device and medium for analog data processing based on EnergyPlus. Background Technology

[0002] EnergyPlus is a widely used building simulation software worldwide, capable of comprehensively simulating building cooling, heating, lighting, ventilation, equipment operation, and energy consumption. The simulated data can be used to support various business functions within building digitalization platforms, such as building energy consumption analysis, HVAC control strategy development, and AI model training.

[0003] However, EnergyPlus stores simulation data in text file format, focusing primarily on individual indicators. This results in a massive and fragmented dataset, which is not conducive to observing the overall operational status of a building. While EnergyPlus offers some comprehensive data output methods, these are inconsistent with the "physical world" data structure defined in the digital platform, failing to provide direct data support for subsequent use and hindering the rapid and convenient application of building simulation data. Summary of the Invention

[0004] This invention provides a simulation data processing method, apparatus, device, and medium based on EnergyPlus. It can construct target data with a structure of static data and runtime sequence data of object dimensions based on the simulation file parsing results of EnergyPlus, thereby providing direct data support for the subsequent use of digital platforms in the construction field and facilitating the rapid and convenient application of building simulation data.

[0005] According to one aspect of the present invention, a simulation data processing method based on EnergyPlus is provided, the method comprising:

[0006] Obtain the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file from EnergyPlus;

[0007] Target static data is determined based on the parsing results of the target simulation configuration file; wherein, the target static data includes target objects, the attributes of the target objects, and the relationships between the target objects;

[0008] The target runtime sequence data of the target object is determined based on the parsing results of the target simulation result file; wherein, the target runtime sequence data is represented by time slices of the target object's running state;

[0009] The target data is determined based on the target static data and the target runtime sequence data of the target object.

[0010] According to another aspect of the present invention, an analog data processing apparatus based on EnergyPlus is provided, the apparatus comprising:

[0011] The target simulation file acquisition module is used to acquire the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus.

[0012] The target static data determination module is used to determine target static data based on the parsing results of the target simulation configuration file; wherein, the target static data includes target objects, the attributes of the target objects, and the association relationships between the target objects;

[0013] The target runtime sequence data determination module is used to determine the target runtime sequence data of the target object based on the parsing results of the target simulation result file; wherein, the target runtime sequence data is characterized by time slices of the target object's running state;

[0014] The target data determination module is used to determine target data based on the target static data and the target runtime sequence data of the target object.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and,

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the EnergyPlus-based simulation data processing method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the EnergyPlus-based analog data processing method according to any embodiment of the present invention.

[0020] The technical solution of this invention involves obtaining the target simulation configuration file and the corresponding target simulation result file in EnergyPlus; determining the target static data based on the parsing results of the target simulation configuration file; wherein the target static data includes the target object, the attributes of the target object, and the relationships between the target objects; determining the target runtime sequence data of the target object based on the parsing results of the target simulation result file; wherein the target runtime sequence data is represented by time slices of the target object's running state; and determining the target data based on the target static data and the target runtime sequence data of the target object. This technical solution can construct target data with a framework of static data and object-dimensional runtime sequence data based on the simulation file parsing results of EnergyPlus, thereby providing direct data support for the subsequent use of digital platforms in the construction field and facilitating the rapid and convenient application of building simulation data.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a simulation data processing method based on EnergyPlus according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a schematic diagram of the class library structure of EnergyPlus according to Embodiment 1 of the present invention;

[0025] Figure 3 This is a schematic diagram of an IDF model of EnergyPlus according to Embodiment 1 of the present invention;

[0026] Figure 4 This is a schematic diagram of the composition of an EnergyPlus eso file according to Embodiment 1 of the present invention;

[0027] Figure 5 This is a schematic diagram of a building structure data conversion method according to Embodiment 1 of the present invention;

[0028] Figure 6This is a schematic diagram illustrating the construction of an association relationship between target objects according to Embodiment 1 of the present invention;

[0029] Figure 7 This is a schematic diagram of electromechanical equipment data conversion according to Embodiment 1 of the present invention;

[0030] Figure 8 This is a schematic diagram illustrating the relationship between physical world objects and ESO file parsing results according to Embodiment 1 of the present invention;

[0031] Figure 9 This is a schematic diagram of target runtime sequence data provided in Embodiment 1 of the present invention;

[0032] Figure 10 This is a schematic diagram of a target data determination process provided in Embodiment 1 of the present invention;

[0033] Figure 11 This is a flowchart of a simulation data processing method based on EnergyPlus according to Embodiment 2 of the present invention;

[0034] Figure 12 This is a schematic diagram of a file parser design pattern provided in Embodiment 2 of the present invention;

[0035] Figure 13 This is a schematic diagram of the structure of an analog data processing device based on EnergyPlus according to Embodiment 3 of the present invention;

[0036] Figure 14 This is a schematic diagram of the structure of an electronic device that implements an analog data processing method based on EnergyPlus according to an embodiment of the present invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] Example 1

[0040] Figure 1 This is a flowchart of a simulation data processing method based on EnergyPlus provided in Embodiment 1 of the present invention. This embodiment is applicable to the construction of target data with a structure of static data and runtime sequence data of object dimensions. The method can be executed by an EnergyPlus-based simulation data processing device, which can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes:

[0041] S110, retrieve the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus.

[0042] The simulation configuration file (i.e., the *.idf file) serves as the input for the EnergyPlus simulation, while the simulation result file (i.e., the *.eso file) serves as the output. Specifically, the simulation configuration file describes the simulation object (such as a building structure or electromechanical equipment), the simulation control logic, and the simulation configuration parameters (including simulation indicators and their corresponding parameter values). The simulation object can refer to an object defined in EnergyPlus. The simulation result file describes the simulation indicators and their corresponding simulation runtime sequence data. The simulation runtime sequence data can refer to the runtime sequence data directly output by EnergyPlus. The target simulation configuration file can be the IDF file to be simulated, and the target simulation result file can be the corresponding ESO file.

[0043] In this embodiment, optionally, after obtaining the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus, the following steps A1-A3 are also included:

[0044] A1. Obtain the data dictionary definition file in EnergyPlus, and parse the data dictionary definition file to obtain the class library structure of EnergyPlus.

[0045] The data dictionary definition file (Energy+.idd) describes the EnergyPlus class structure definition, i.e., the data dictionary parsing specification. The class library structure includes object types and their corresponding attribute types. For example, taking "room" as the object type, its corresponding attribute types could include area, height, and orientation.

[0046] In this embodiment, the EnergyPlus class library structure can be obtained by parsing the data dictionary definition file Energy+.idd using the EnergyPlus data dictionary parser (IddParser). This class library structure forms the basis for subsequent simulation file parsing and data conversion. Specifically, the class library structure mainly contains two concepts: EpClass and EpLib. EpClass corresponds to each EnergyPlus class defined in idd (including object types and their corresponding attribute types), while EpLib provides access and lookup interfaces for EnergyPlus classes to support subsequent IDF and ESO file parsing. Figure 2 This is a schematic diagram of the class library structure of EnergyPlus provided in Embodiment 1 of the present invention. EpClass_1-EpClass_4 represent different object types, while Field_1-Field_3 represent different attribute types corresponding to the object types.

[0047] A2. Based on the class library structure, the target simulation configuration file is parsed to obtain the first parsing result.

[0048] The first parsing result includes simulated objects, their attributes, and the reference relationships between them. In this embodiment, the EnergyPlus input model parser (IdfParser) can be used to parse the IDF file based on the EnergyPlus class library structure, identifying the type and attribute defined in each section of the IDF file, constructing corresponding object instances (including simulated objects and their attributes), and calculating the dependency reference associations between object instances (i.e., the reference relationships between simulated objects). Specifically, IdfParser can parse a specific IDF file to obtain an IDF model (IdfModel). The content of the IDF model file consists of a set of instance definitions of EnergyPlus classes, so the IDF model (IdfModel) is essentially a collection of instance objects (IdfObjects) contained in the file. IdfModel provides a series of operation interfaces, allowing access to instance objects in the IDF model through various means such as type and name, while IdfObject is an instantiated object of a certain EpClass.

[0049] Figure 3 This is a schematic diagram of an EnergyPlus IDF model provided in Embodiment 1 of the present invention. IdfObject_1-IdfObject_4 represent different simulated objects, and IdfObject_1 and IdfObject_2 belong to the same object type EpClass_1 (i.e., IdfObject_1 and IdfObject_2 are different instantiations of EpClass_1). IdfObject_3 and IdfObject_4 belong to the same object type EpClass_2 (i.e., IdfObject_3 and IdfObject_4 are different instantiations of EpClass_2). Field_1:xxx-Field_3:xxx represent different attributes of the simulated object (i.e., instantiations of Field_1-Field_3).

[0050] A3. The second parsing result is obtained by parsing the target simulation result file according to the class library structure.

[0051] The second parsing result includes the simulation metrics of the simulated objects and the simulation runtime sequence data of the simulation metrics. In this embodiment, the eso file can be parsed using the EnergyPlus output data parser (EsoParser) based on the EnergyPlus library structure. The eso file consists of two parts: the first part is the output dictionary definition, which associates each simulation metric with all simulated objects in the model that support that metric, based on the simulation metrics defined in the idf, defining a series of output IDs; the second part is the output time series data obtained from the simulation run. This output time series data contains multiple entries, and the primary key of each data entry (i.e., the unique identifier of each output time series data entry) is composed of the time point and the output ID defined in the first part. The data item represents the data value of the output item of a certain simulated object at that time point. Therefore, when parsing the eso file, the first part of the eso file (i.e., the output dictionary definition) is parsed first to obtain the output simulation metrics, and then the output time series data in the second part is parsed to obtain the simulation runtime sequence data corresponding to the simulation metrics.

[0052] Figure 4 This is a schematic diagram of the composition of an EnergyPlus eso file provided in Embodiment 1 of the present invention.

[0053] EsoParser primarily comprises two concepts: Meta, which corresponds to the output ID in the output dictionary definition and includes fields such as ID value, output item, and object name in the model; and Record, which corresponds to each output time-series data entry and includes fields such as output ID, time point, and data value. Meta and Record are linked through the ID field, with one Meta corresponding to multiple Records.

[0054] S120, determine the target static data based on the parsing results of the target simulation configuration file.

[0055] The target static data includes the target object, the target object's attributes, and the relationships between target objects. The target object can refer to an object defined in the building physics world. It should be noted that both simulated objects and target objects typically include building structures and electromechanical equipment, but their specific representations differ. For example, EnergyPlus does not have the concept of floors, so the building structure corresponding to a simulated object does not include floors; the equipment granularity in EnergyPlus is finer, and in reality, one electromechanical device in the building physics world may correspond to multiple devices in EnergyPlus.

[0056] In this embodiment, optionally, the simulated object includes a simulated building structure, and the simulated building structure includes a simulated space; correspondingly, the target static data is determined based on the parsing results of the target simulation configuration file, including the following steps B1-B3:

[0057] B1. Determine the target space based on the surface attribute information of the simulated space.

[0058] It's important to note that the building structures in EnergyPlus primarily focus on thermal equilibrium, which differs from the building structures defined in the physical world of architecture. Typically, EnergyPlus lacks the concept of floors. Therefore, these inconsistencies need to be mapped during simulation data processing. Specifically, a space in EnergyPlus is a polyhedron containing multiple surfaces, each potentially containing several fenestration surfaces. Data processing requires mapping these surfaces to entities such as walls, doors, windows, roofs, and floors based on their specific properties, such as type and material. Surfaces with special materials, such as air boundaries, are mapped to virtual walls. This allows the simulated space to be converted into a target space. The simulated space and target space can refer to the spaces in EnergyPlus and the physical world of architecture, respectively. For example, assuming the simulated space is a square room with six surfaces, its top surface can be mapped to the roof, the bottom surface to the floor, the four sides to the walls, and the fenestration surfaces on the walls to doors and windows.

[0059] Figure 5 This is a schematic diagram illustrating a building structure data conversion method provided in Embodiment 1 of the present invention. In this diagram, the E+ building model represents the building structure in EnergyPlus, and the physical world building represents the building structure in the physical world. Figure 5 As shown, the E+ building model can include building structures such as buildings, thermal zones, spaces, surfaces, and window surfaces. Through data conversion, it can obtain building structures such as buildings, floors, property spaces, walls, doors, windows, and virtual walls in the physical world of buildings.

[0060] B2. Determine the target floor based on the geometric location information of the target space.

[0061] For example, geometric location information can include the coordinates of the starting point (such as the lower left corner), height, and location. For instance, target spaces at the same height belong to the same floor. Based on this, related object instances can be constructed into a clear and easily understood static physical world model from a hierarchical perspective of "building -> floor -> space." During the construction process, the EnergyPlus object is extracted and transformed, converting the EnergyPlus object and its properties into objects and properties within the physical world model.

[0062] B3. Based on the reference relationships between simulated building structures, determine the first association relationship between the target building structures.

[0063] The first type of association includes the correspondence between floors and spaces, as well as the association between different spaces. For example, the association between different spaces can include adjacency and connectivity relationships. It should be noted that inter-object relationships are an important concept in the physical world of buildings, describing the mutual influence and association between various types of objects such as building structures and electromechanical equipment. Although EnergyPlus does not have this concept, the IDF model contains rich attribute definitions and mutual references between instance objects. Therefore, by calculating some attributes and referring to the reference logic between instance objects, the various types of inter-object relationships required in the physical world can be constructed. Figure 6 This is a schematic diagram illustrating the construction of an association relationship between target objects according to Embodiment 1 of the present invention. Figure 6 As shown, the correspondence between floors and spaces can be constructed through geometric calculations of spatial coordinates, and the adjacency or connectivity between spaces can be constructed based on the surface material and external properties.

[0064] In this embodiment, optionally, the simulated object includes simulated electromechanical equipment, which is described in the form of a loop. The loop includes branches and collection / distribution connection points, and the branches include simulated electromechanical equipment and input / output nodes. Correspondingly, the target static data is determined based on the parsing results of the target simulation configuration file, including the following steps C1-C3:

[0065] C1. Traverse each candidate circuit in the first analysis result, and extract the analog electromechanical equipment in the candidate circuit as candidate electromechanical equipment in turn during the traversal process.

[0066] Candidate loops can refer to any loop involved in the first analysis result. It's important to note that in EnergyPlus, equipment operates and provides services to the building in the form of loops. Therefore, when extracting equipment data, loops should also be the starting point. There are two main types of loops: plant loops, including typical water circulation loops such as cooling, heating, and so on; and air loops, including air conditioning loops and fresh air loops. Loops can be further broken down into branches, collection / distribution connection points, equipment, and input / output nodes. Data processing can be done by traversing the loops, extracting equipment information segment by segment and point by point until returning to the starting point, completing the extraction process of equipment within the loop and obtaining candidate electromechanical equipment.

[0067] C2. Based on the mapping relationship between simulated electromechanical equipment and physical electromechanical equipment, as well as the connection relationship between simulated electromechanical equipment in candidate loops, the candidate electromechanical equipment is merged to obtain the target electromechanical equipment.

[0068] In this context, "physical electromechanical equipment" refers to the electromechanical equipment defined in the building's physical world. Specifically, the mapping relationship between simulated electromechanical equipment and physical electromechanical equipment can be one-to-one or many-to-one. For example, an air conditioning unit in the building's physical world actually corresponds to multiple device objects in EnergyPlus, such as OutdoorAir:Mixer, Fan, and Cooling / Heating Coil. In this case, the mapping relationship between simulated and physical electromechanical equipment is many-to-one. It should be noted that because the device granularity in EnergyPlus is finer, some device integration work is required during data conversion to better align with the perspective of concern in the business scenario.

[0069] Specifically, when performing data conversion, it is necessary to first divide the main / branch range in the loop, and then combine multiple EnergyPlus devices into a physical world device (i.e., target electromechanical device) based on the connection relationship between the devices within the local range. Figure 7 This is a schematic diagram of electromechanical equipment data conversion according to Embodiment 1 of the present invention. In this diagram, simple devices in the physical world satisfy a one-to-one device mapping relationship (i.e., no device merging is required), while composite devices in the physical world satisfy a many-to-one device mapping relationship (i.e., device merging is required).

[0070] C3. Based on the reference relationships between candidate circuits, determine the second association relationship corresponding to the target electromechanical equipment.

[0071] The second association includes the connection relationship between electromechanical equipment and the association relationship between electromechanical equipment and space. For example, the association relationship between electromechanical equipment and space can include locational relationships and service relationships, etc. Figure 6 As shown, the connection relationship between devices can be constructed based on the traversal results of the loop, and the service relationship between devices and space can be constructed based on the terminal devices of the hot zone.

[0072] S130, Determine the target runtime sequence data of the target object based on the parsing results of the target simulation result file.

[0073] Target runtime sequence data refers to runtime sequence data categorized by the target object. This data can be represented by time slices of the target object's runtime state. Specifically, after parsing the eso file using EsoParser, a list of Meta elements and a list of Record elements are obtained. The Meta element contains the object name and output fields. Each output field is essentially a runtime information point of a physical world object. Therefore, multiple Meta elements associated with the same physical world object represent all runtime information points of that object. Record elements are linked to Meta elements through a many-to-one relationship via output IDs. A Record element is essentially the runtime data value of a Meta element at different points in time. See also... Figure 8 This demonstrates the relationship between physical world objects and the results of eso file parsing.

[0074] In this embodiment, optionally, determining the target runtime sequence data of the target object based on the parsing results of the target simulation result file includes: taking the simulation index items belonging to the same simulation object in the second parsing result as target index items, and taking the same simulation object as the target object; and determining the target runtime sequence data corresponding to the target object based on the simulation runtime sequence data corresponding to the target index item.

[0075] For example, based on Figure 8 The association between physical world objects and ESO file parsing results, as shown in the example, allows for the aggregation of data recorded line by line in the ESO file according to individual indicator items at the object level. This enables the association of time-series data based on observed indicators with objects such as building structures or electromechanical equipment in the physical world of the building, thereby constructing time-series data in a real-time state slice format (i.e., target runtime time-series data corresponding to the target object), such as... Figure 9 As shown in the diagram. The object ID serves as a unique identifier for each object; that is, each object has a unique object ID.

[0076] S140, Determine the target data based on the target static data and the target runtime sequence data of the target object.

[0077] In this embodiment, after obtaining the target static data and the target runtime sequence data of the target object, the two can be combined to obtain the target data required for the physical world of the building. This allows the EnergyPlus simulation data to be transformed into a clearer structure, facilitating the observation of building operations from multiple perspectives, both macroscopic and microscopic. Furthermore, the data structure of the obtained target data conforms to the physical world structure definition in the digital platform for the building field, and therefore can be directly used within the digital platform. This effectively utilizes the simulation capabilities of EnergyPlus to supplement the data source of the digital platform, facilitating the rapid and convenient application of simulation data.

[0078] The technical solution of this invention involves obtaining the target simulation configuration file and the corresponding target simulation result file in EnergyPlus; determining the target static data based on the parsing results of the target simulation configuration file; wherein the target static data includes the target object, the attributes of the target object, and the relationships between the target objects; determining the target runtime sequence data of the target object based on the parsing results of the target simulation result file; wherein the target runtime sequence data is represented by time slices of the target object's running state; and determining the target data based on the target static data and the target runtime sequence data of the target object. This technical solution can construct target data with a framework of static data and object-dimensional runtime sequence data based on the simulation file parsing results of EnergyPlus, thereby providing direct data support for the subsequent use of digital platforms in the construction field and facilitating the rapid and convenient application of building simulation data.

[0079] In this embodiment, optionally, determining the target static data based on the parsing result of the target simulation configuration file further includes: taking candidate circuits with the same simulated electromechanical equipment in the first parsing result as target circuits; if the target circuits belong to the same preset system type, then integrating the target circuits to obtain the target electromechanical system.

[0080] The preset system type refers to a system type pre-defined based on actual engineering needs. For example, preset system types may include cold source systems and air conditioning terminal systems. Specifically, the cold source system corresponds to the cold source loop and cooling loop in EnergyPlus. It should be noted that the concept of a loop in EnergyPlus is basically consistent with the concept of an electromechanical system in the building physics world; however, some electromechanical systems may contain multiple loops. In such cases, it is necessary to integrate loops with the same simulated electromechanical equipment based on the preset system type to which the loop belongs to obtain the target electromechanical system. For example... Figure 7 As shown, systems in physical world devices can include systems with a single loop (i.e., no loop integration is required) and systems consisting of multiple loops (i.e., loop integration is required).

[0081] This solution, through this setup, enables the system to be constructed based on actual engineering needs and the circuit, allowing the equipment simulation data to be better applied to actual engineering projects.

[0082] In this embodiment, optionally, the second association relationship also includes: the connection relationship between electromechanical equipment and electromechanical system, and the association relationship between different electromechanical systems.

[0083] For example, the relationships between different electromechanical systems can include service relationships. For instance... Figure 6 As shown, the connection relationship between the system and the device can also be constructed based on the traversal result of the loop, and then the service relationship between the system and the system can be constructed.

[0084] Figure 10 This is a schematic diagram illustrating a target data determination process provided in Embodiment 1 of the present invention. Figure 10 As shown, the EnergyPlus library structure is first obtained by parsing the idd file using IddParser. Then, based on this library structure, the idf and eso files are parsed using IdfParser and EsoParser respectively, yielding the corresponding parsing results. Subsequently, the data conversion and adaptation module transforms the data in the parsing results to obtain a static model (i.e., target static data) and a slice of the building's operational state on the timeline (i.e., target runtime sequence data of the target object), thereby constructing a data structure that conforms to the definition of the physical world of buildings. Specifically, the building space converter can be used to convert simulated building structures into target building structures; the electromechanical system and equipment converter can be used to convert simulated electromechanical equipment into target electromechanical equipment and simulated loops into target electromechanical systems; the relational data converter can be used to convert the reference relationships between simulated objects into the association relationships between target objects; and the time-series data converter can be used to convert the simulated runtime sequence data of simulated indicators into the target runtime sequence data of the target object.

[0085] Example 2

[0086] Figure 11 This is a flowchart of a simulation data processing method based on EnergyPlus provided in Embodiment 2 of the present invention. This embodiment is an optimization based on the above embodiment.

[0087] like Figure 11 As shown, the method in this embodiment specifically includes the following steps:

[0088] S210, retrieve the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus.

[0089] S220: Obtain the data dictionary definition file in EnergyPlus, and parse the data dictionary definition file to obtain the class library structure of EnergyPlus.

[0090] The class library structure includes object types and the corresponding attribute types.

[0091] S230: Parse the target simulation configuration file according to the class library structure to obtain the first parsing result, and determine the target static data based on the first parsing result.

[0092] The first parsing result includes the simulated object, the attributes of the simulated object, and the reference relationships between the simulated objects. The target static data includes the target object, the attributes of the target object, and the association relationships between the target objects.

[0093] S240, parse the target simulation result file according to the class library structure to obtain the second parsing result, and determine the target runtime sequence data of the target object based on the second parsing result.

[0094] The second analysis result includes the simulation index items of the simulation object and the simulation runtime sequence data of the simulation index items. The target runtime sequence data is represented by the runtime state time slice of the target object.

[0095] It should be noted that since idd, idf, and eso files have similar basic structures—all being text files delimited by characters such as commas and semicolons—the parser implementation can use a common base class (BaseEpParser) to provide general text parsing capabilities. Parsers for each file type inherit from this common base class design pattern. Figure 12 As shown. Compared with the traditional file parsing method in EnergyPlus, this solution can effectively improve file parsing efficiency and make the parsing results more in line with the needs of actual applications.

[0096] S250, determine the target data based on the target static data and the target runtime sequence data of the target object.

[0097] The technical solution of this invention is based on the general text parsing capability provided by the common base class. It adopts multiple parsers inherited from the common base class to be responsible for parsing various types of files, which can effectively improve the file parsing efficiency and make the parsing results more in line with the actual application requirements.

[0098] Example 3

[0099] Figure 13This is a schematic diagram of a simulation data processing device based on EnergyPlus provided in Embodiment 3 of the present invention. This device can execute the simulation data processing method based on EnergyPlus provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. For example... Figure 13 As shown, the device includes:

[0100] The target simulation file acquisition module 310 is used to acquire the target simulation configuration file in EnergyPlus and the target simulation result file corresponding to the target simulation configuration file.

[0101] The target static data determination module 320 is used to determine target static data based on the parsing results of the target simulation configuration file; wherein, the target static data includes target objects, the attributes of the target objects, and the association relationships between the target objects;

[0102] The target runtime sequence data determination module 330 is used to determine the target runtime sequence data of the target object based on the parsing results of the target simulation result file; wherein, the target runtime sequence data is characterized by time slices of the running state of the target object;

[0103] The target data determination module 340 is used to determine target data based on the target static data and the target runtime sequence data of the target object.

[0104] Optionally, the device further includes:

[0105] The data dictionary definition file parsing module is used to obtain the data dictionary definition file in EnergyPlus after obtaining the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus, and to parse the data dictionary definition file to obtain the class library structure of EnergyPlus; wherein, the class library structure includes object types and the attribute types corresponding to the object types;

[0106] The target simulation configuration file parsing module is used to parse the target simulation configuration file according to the class library structure to obtain a first parsing result; wherein, the first parsing result includes simulation objects, the attributes of the simulation objects, and the reference relationships between the simulation objects;

[0107] The target simulation result file parsing module is used to parse the target simulation result file according to the class library structure to obtain a second parsing result; wherein, the second parsing result includes the simulation index items of the simulation object and the simulation runtime sequence data of the simulation index items.

[0108] Optionally, the simulated object includes a simulated building structure, and the simulated building structure includes a simulated space;

[0109] The target static data determination module 320 is used for:

[0110] The target space is determined based on the surface property information of the simulated space;

[0111] The target floor is determined based on the geometric location information of the target space;

[0112] Based on the reference relationships between the simulated building structures, a first association relationship between the target building structures is determined; wherein, the first association relationship includes the correspondence between floors and spaces and the association relationship between different spaces.

[0113] Optionally, the simulated object includes simulated electromechanical equipment, which is described in the form of a loop. The loop includes branches and collection / distribution connection points, and the branches include the simulated electromechanical equipment and input / output nodes.

[0114] The target static data determination module 320 is used for:

[0115] Each candidate circuit in the first analysis result is traversed, and the simulated electromechanical equipment in the candidate circuit is extracted as candidate electromechanical equipment in turn during the traversal process.

[0116] Based on the mapping relationship between simulated electromechanical equipment and physical electromechanical equipment, and the connection relationship between the simulated electromechanical equipment in the candidate circuit, the candidate electromechanical equipment is merged to obtain the target electromechanical equipment.

[0117] Based on the reference relationships between the candidate loops, a second association relationship corresponding to the target electromechanical equipment is determined; wherein, the second association relationship includes the connection relationship between electromechanical equipment and the association relationship between electromechanical equipment and space.

[0118] Optionally, the target static data determination module 320 is further configured to:

[0119] The candidate circuits that contain the same simulated electromechanical equipment in the first analysis result are taken as the target circuits;

[0120] If the target circuits belong to the same preset system type, the target circuits are integrated to obtain the target electromechanical system.

[0121] Optionally, the second association relationship also includes: the connection relationship between electromechanical equipment and electromechanical systems, and the association relationship between different electromechanical systems.

[0122] Optionally, the target runtime sequence data determination module 330 is used for:

[0123] The simulation index items belonging to the same simulation object in the second analysis result are taken as target index items, and the same simulation object is taken as target object;

[0124] Based on the simulated runtime sequence data corresponding to the target indicator item, determine the target runtime sequence data corresponding to the target object.

[0125] The simulation data processing device based on EnergyPlus provided in this embodiment of the invention can execute the simulation data processing method based on EnergyPlus provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0126] Example 4

[0127] Figure 14 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0128] like Figure 14 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0129] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0130] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the analog data processing method based on EnergyPlus.

[0131] In some embodiments, the EnergyPlus-based analog data processing method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the EnergyPlus-based analog data processing method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the EnergyPlus-based analog data processing method by any other suitable means (e.g., by means of firmware).

[0132] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0133] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0134] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0135] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0136] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0137] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0138] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0139] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A simulation data processing method based on EnergyPlus, characterized in that, The method includes: Obtain the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file from EnergyPlus; Target static data is determined based on the parsing results of the target simulation configuration file; wherein, the target static data includes target objects, the attributes of the target objects, and the relationships between the target objects; The target runtime sequence data of the target object is determined based on the parsing results of the target simulation result file; wherein, the target runtime sequence data is represented by time slices of the target object's running state; The target data is determined based on the target static data and the target runtime sequence data of the target object; The method further includes, after obtaining the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus: Obtain the data dictionary definition file in EnergyPlus, and parse the data dictionary definition file to obtain the class library structure of EnergyPlus; wherein, the class library structure includes object types and the attribute types corresponding to the object types; The target simulation configuration file is parsed according to the class library structure to obtain a first parsing result; wherein, the first parsing result includes simulation objects, the attributes of the simulation objects, and the reference relationships between the simulation objects; the simulation objects refer to objects defined in EnergyPlus, and the target objects refer to objects defined in the building physics world, and the simulation objects and the target objects have different forms of representation; The target simulation result file is parsed according to the class library structure to obtain a second parsing result; wherein, the second parsing result includes the simulation index items of the simulation object and the simulation runtime sequence data of the simulation index items; The simulated object includes simulated electromechanical equipment, which is described in the form of a loop. The loop includes branches and collection / distribution connection points. The branches include the simulated electromechanical equipment and input / output nodes. The determination of target static data based on the parsing results of the target simulation configuration file includes: Each candidate circuit in the first analysis result is traversed, and the simulated electromechanical equipment in the candidate circuit is extracted as candidate electromechanical equipment in turn during the traversal process. Based on the mapping relationship between the simulated electromechanical equipment and the physical electromechanical equipment, and the connection relationship between the simulated electromechanical equipment in the candidate circuit, the candidate electromechanical equipment is merged to obtain the target electromechanical equipment. Based on the reference relationships between the candidate loops, a second association relationship corresponding to the target electromechanical equipment is determined; wherein, the second association relationship includes the connection relationship between electromechanical equipment and the association relationship between electromechanical equipment and space; The step of determining the target runtime sequence data of the target object based on the parsing results of the target simulation result file includes: The simulation index items belonging to the same simulation object in the second analysis result are taken as target index items, and the same simulation object is taken as target object; Based on the simulated runtime sequence data corresponding to the target indicator item, determine the target runtime sequence data corresponding to the target object.

2. The method according to claim 1, characterized in that, The simulated object includes a simulated building structure, and the simulated building structure includes a simulated space; The target static data is determined based on the parsing results of the target simulation configuration file, including: The target space is determined based on the surface property information of the simulated space; The target floor is determined based on the geometric location information of the target space; Based on the reference relationships between the simulated building structures, a first association relationship between the target building structures is determined; wherein, the first association relationship includes the correspondence between floors and spaces and the association relationship between different spaces.

3. The method according to claim 1, characterized in that, Determining target static data based on the parsing results of the target simulation configuration file also includes: The candidate circuits that contain the same simulated electromechanical equipment in the first analysis result are taken as the target circuits; If the target circuits belong to the same preset system type, the target circuits are integrated to obtain the target electromechanical system.

4. The method according to claim 3, characterized in that, The second association also includes: the connection relationship between electromechanical equipment and electromechanical systems, as well as the association relationship between different electromechanical systems.

5. A simulation data processing device based on EnergyPlus, characterized in that, The device includes: The target simulation file acquisition module is used to acquire the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus. The target static data determination module is used to determine target static data based on the parsing results of the target simulation configuration file; wherein, the target static data includes target objects, the attributes of the target objects, and the association relationships between the target objects; The target runtime sequence data determination module is used to determine the target runtime sequence data of the target object based on the parsing results of the target simulation result file; wherein, the target runtime sequence data is characterized by time slices of the target object's running state; The target data determination module is used to determine target data based on the target static data and the target runtime sequence data of the target object; The device further includes: The data dictionary definition file parsing module is used to obtain the data dictionary definition file in EnergyPlus after obtaining the target simulation configuration file and the target simulation result file corresponding to the target simulation configuration file in EnergyPlus, and to parse the data dictionary definition file to obtain the class library structure of EnergyPlus; wherein, the class library structure includes object types and the attribute types corresponding to the object types; The target simulation configuration file parsing module is used to parse the target simulation configuration file according to the class library structure to obtain a first parsing result; wherein, the first parsing result includes simulation objects, the attributes of the simulation objects, and the reference relationships between the simulation objects; the simulation objects refer to objects defined in EnergyPlus, and the target objects refer to objects defined in the building physics world, and the simulation objects and the target objects have different forms of representation; The target simulation result file parsing module is used to parse the target simulation result file according to the class library structure to obtain a second parsing result; wherein, the second parsing result includes the simulation index items of the simulation object and the simulation runtime sequence data of the simulation index items; The simulated object includes simulated electromechanical equipment, which is described in the form of a loop. Each loop includes branches and set / distribute connection points. Each branch includes the simulated electromechanical equipment and input / output nodes. The target static data determination module is used to traverse each candidate loop in the first analysis result, and sequentially extract the simulated electromechanical equipment in the candidate loops as candidate electromechanical equipment during the traversal. Based on the mapping relationship between the simulated electromechanical equipment and physical electromechanical equipment, and the connection relationship between the simulated electromechanical equipment in the candidate loops, the candidate electromechanical equipment is merged to obtain the target electromechanical equipment. According to the reference relationship between the candidate loops, a second association relationship corresponding to the target electromechanical equipment is determined. The second association relationship includes the connection relationship between electromechanical equipment and the association relationship between the electromechanical equipment and space. The target runtime sequence data determination module is used to take the simulation index items belonging to the same simulation object in the second parsing result as target index items, and take the same simulation object as the target object; and determine the target runtime sequence data corresponding to the target object based on the simulation runtime sequence data corresponding to the target index item.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the EnergyPlus-based analog data processing method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the EnergyPlus-based analog data processing method according to any one of claims 1-4.

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