New energy model data processing method, related device and storage medium

Abstract

The invention discloses a new energy model data processing method, a related device and a storage medium, and the method comprises the steps: obtaining multi-source heterogeneous data of each stage of equipment unit of an energy storage power station, and constructing a digital twin simulation model corresponding to each equipment unit through the multi-source heterogeneous data; associating the digital twinborn simulation models, corresponding equipment entities in the energy storage power station and data acquisition equipment on the equipment entities, and performing scene construction by using the digital twinborn simulation models based on layout information of the equipment entities to obtain a digital twinborn scene of the energy storage power station; performing data association on each digital twinborn simulation model in the digital twinborn scene of the energy storage power station and corresponding data acquisition equipment, and establishing a data transmission channel; and updating the digital twinborn scene of the energy storage power station in real time and monitoring and managing each equipment entity according to an equipment management method by using the data of each equipment entity acquired by each data acquisition equipment in real time.

Description

Technical Field

[0001] The present application relates to the field of energy equipment operation and maintenance technology, and in particular to a new energy model data processing method and related devices and storage media. Background Art

[0002] With the rapid development of digital twin technology, it has been widely used in various industries. Especially in the energy storage industry, it plays an important role in the development of the energy storage industry. Specifically, it is mainly through building a digital twin simulation model of the energy storage power station and using it to carry out the maintenance work of the energy storage power station.

[0003] The current method of using digital twin technology to create energy storage power stations is mainly for front-end personnel to directly customize the digital twin simulation model of the energy storage power station through 3D modeling software, or to obtain digital twin simulation models of some existing equipment from external databases and use these digital twin simulation models to build a digital twin simulation model of the energy storage power station.

[0004] However, the relevant data of energy storage power station equipment will change with development. At this time, customized construction or construction using existing digital twin simulation models requires tedious code modification and maintenance. In addition, the interaction between the model constructed by the existing method and the operation and maintenance data is less effective, and it is impossible to effectively operate and manage the energy storage power station. Summary of the invention

[0005] Based on the above-mentioned deficiencies of the prior art, the present application provides a new energy model data processing method and related devices and storage media to solve the problem that the prior art is cumbersome to maintain and cannot effectively operate and maintain energy storage power stations.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] The first aspect of the present application provides a new energy model data processing method, comprising:

[0008] Obtain multi-source heterogeneous data of equipment units at all levels of energy storage power stations;

[0009] Using multi-source heterogeneous data of each of the equipment units to construct a digital twin simulation model corresponding to each of the equipment units;

[0010] Associating each of the digital twin simulation models with the corresponding equipment entities in the energy storage power station and the data acquisition devices on the equipment entities, and based on the layout information of each of the equipment entities in the energy storage power station, using the digital twin simulation models corresponding to each of the equipment units to construct a scene, to obtain a digital twin scene of the energy storage power station;

[0011] Associating data between each digital twin simulation model in the digital twin scene of the energy storage power station and the associated data acquisition device, and establishing a data transmission channel;

[0012] Utilizing the data of each of the device entities collected in real time by each of the data acquisition devices, the digital twin scene of the energy storage power station is updated in real time and each of the device entities is monitored and managed according to the device management method.

[0013] Optionally, in the above-mentioned new energy model data processing method, constructing a digital twin simulation model corresponding to each of the equipment units using multi-source heterogeneous data of each of the equipment units includes:

[0014] Setting the model level corresponding to each of the equipment units based on the scenario model requirements;

[0015] Utilizing the multi-source heterogeneous data of each of the equipment units, three-dimensional modeling is performed according to the model level corresponding to the equipment unit, and the digital twin simulation model corresponding to each of the equipment units is obtained and stored.

[0016] Optionally, in the above-mentioned new energy model data processing method, setting the model level corresponding to each of the equipment units based on the scenario model requirements includes:

[0017] The model level corresponding to each first-level device unit that does not include the device unit is set to the first model level, and the model level corresponding to each first-level device unit that includes the device unit and each of the device units included is set to the second model level; wherein the model accuracy of the second model level is higher than the model accuracy of the first model level.

[0018] Optionally, in the above-mentioned new energy model data processing method, each of the digital twin simulation models is associated with the corresponding equipment entity in the energy storage power station, and the data acquisition device on the equipment entity, and based on the layout information of each of the equipment entities in the energy storage power station, the digital twin simulation model corresponding to each of the equipment units is used to construct a scene to obtain a digital twin scene of the energy storage power station, including:

[0019] Creating a unique code corresponding to the device entity in the energy storage power station;

[0020] Associating the unique code corresponding to the device entity with the device entity, the corresponding digital twin simulation model, and the data acquisition device deployed on the device entity;

[0021] According to the layout information of each of the equipment entities in the drawings of the energy storage power station, on the digital twin base corresponding to each of the equipment units, the digital twin simulation model corresponding to the equipment unit is positioned and set; wherein the digital twin base corresponding to the equipment unit of the first level is the digital twin base of the energy storage power station; the digital twin base corresponding to the equipment unit of the next level is the digital twin simulation model corresponding to the equipment unit of the previous level;

[0022] Through the unique code associated with each digital twin simulation model, the basic information, location and associated scene of the corresponding device entity are associated with the device entity and the data acquisition device thereon.

[0023] Optionally, in the above-mentioned new energy model data processing method, the data of each of the device entities collected in real time by each of the data acquisition devices is used to update the digital twin scene of the energy storage power station in real time and monitor and manage each of the device entities according to the device management method, including:

[0024] Using the data of each of the device entities collected in real time by each of the data acquisition devices, update the data of the digital twin simulation model in the digital twin scene of the energy storage power station according to the refresh rule;

[0025] Based on the data of each of the device entities collected in real time by each of the data collection devices, and in accordance with the corresponding alarm rules, the digital twin simulation model that currently generates the alarm event is analyzed;

[0026] The operation and maintenance are performed using the management method corresponding to the analyzed digital twin simulation model.

[0027] A second aspect of the present application provides a new energy model data processing device, comprising:

[0028] A data acquisition unit, used to acquire multi-source heterogeneous data of equipment units at all levels of the energy storage power station;

[0029] A model building unit, used to build a digital twin simulation model corresponding to each of the equipment units using multi-source heterogeneous data of each of the equipment units;

[0030] A scenario construction unit, used to associate each of the digital twin simulation models with the corresponding equipment entities in the energy storage power station and the data acquisition devices on the equipment entities, and based on the layout information of each of the equipment entities in the energy storage power station, use the digital twin simulation models corresponding to each of the equipment units to construct a scenario, so as to obtain a digital twin scenario of the energy storage power station;

[0031] A data association unit, used to associate data between each digital twin simulation model in the digital twin scene of the energy storage power station and the data acquisition device associated therewith, and establish a data transmission channel;

[0032] A management unit is used to utilize the data of each of the device entities collected in real time by each of the data acquisition devices, to update the digital twin scene of the energy storage power station in real time and to monitor and manage each of the device entities according to the device management method.

[0033] Optionally, in the above-mentioned new energy model data processing device, the model building unit includes:

[0034] A level setting unit, used for setting the model level corresponding to each of the equipment units based on the scenario model requirements;

[0035] The modeling unit is used to utilize the multi-source heterogeneous data of each of the equipment units to perform three-dimensional modeling according to the model level corresponding to the equipment unit, obtain the digital twin simulation model corresponding to each of the equipment units and store it.

[0036] Optionally, in the above-mentioned new energy model data processing device, the level setting unit includes:

[0037] A level setting subunit is used to set the model level corresponding to each first-level device unit that does not include the device unit to the first model level, and to set the model level corresponding to each first-level device unit that includes the device unit and each of the device units included therein to the second model level; wherein the model accuracy of the second model level is higher than the model accuracy of the first model level.

[0038] Optionally, in the above-mentioned new energy model data processing device, the scenario construction unit includes:

[0039] A code creation unit, used to create a unique code corresponding to the device entity in the energy storage power station;

[0040] A first associating unit, used to associate the unique code corresponding to the device entity with the device entity, the corresponding digital twin simulation model, and the data acquisition device deployed on the device entity;

[0041] A model layout unit is used to locate and set the digital twin simulation model corresponding to the equipment unit on the digital twin base corresponding to each equipment unit according to the layout information of each equipment entity in the drawing of the energy storage power station; wherein the digital twin base corresponding to the equipment unit of the first level is the digital twin base of the energy storage power station; the digital twin base corresponding to the equipment unit of the next level is the digital twin simulation model corresponding to the equipment unit of the previous level that contains it;

[0042] The second association unit is used to associate the basic information, location and associated scene of the corresponding device entity with the device entity and the data acquisition device thereon through the unique code associated with each digital twin simulation model.

[0043] Optionally, in the above-mentioned new energy model data processing device, the management unit includes:

[0044] A data updating unit, configured to update the data of the digital twin simulation model in the digital twin scene of the energy storage power station according to a refresh rule by using the data of each of the device entities collected in real time by each of the data collection devices;

[0045] A data analysis unit, configured to analyze the digital twin simulation model that currently generates an alarm event based on the data of each of the device entities collected in real time by each of the data collection devices and in accordance with the corresponding alarm rules;

[0046] An operation and maintenance management unit is used to perform operation and maintenance operations using the management method corresponding to the analyzed digital twin simulation model.

[0047] A third aspect of the present application provides an electronic device, including:

[0048] Memory and processor;

[0049] Wherein, the memory is used to store programs;

[0050] The processor is used to execute the program, and when the program is executed, it is specifically used to implement the new energy model data processing method as described in any one of the above.

[0051] A fourth aspect of the present application provides a computer storage medium for storing a computer program, which, when executed by a processor, is used to implement a new energy model data processing method as described in any one of the above.

[0052] The present application provides a new energy model data processing method, which obtains multi-source heterogeneous data of equipment units at all levels of an energy storage power station, and uses the multi-source heterogeneous data of each of the equipment units to construct a digital twin simulation model corresponding to each of the equipment units. Then, each of the digital twin simulation models is associated with the corresponding equipment entity in the energy storage power station, and the data acquisition device on the equipment entity, and based on the layout information of each of the equipment entities in the energy storage power station, the digital twin simulation model corresponding to each of the equipment units is used to construct a scene to obtain a digital twin scene of the energy storage power station, thereby realizing the construction of the digital twin scene of the corresponding energy storage power station based on the multi-source heterogeneous data of the equipment units, and no longer using the existing model for construction, which can improve the authenticity and accuracy of the digital twin scene. The digital twin simulation models in the digital twin scene of the energy storage power station are associated with the data acquisition devices associated with them, and a data transmission channel is established. The data of each device entity collected in real time by each data acquisition device is used to update the digital twin scene of the energy storage power station in real time and monitor and manage each device entity in accordance with the device management method, so that the scene data in the digital twin scene of the energy storage power station can be automatically updated in real time without manual tedious code modification and maintenance. In addition, effective interaction between the model and operation and maintenance data is also achieved, so that effective detection and operation and maintenance management of the device entity can be effectively performed. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0054] Figure 1 A flowchart of a new energy model data processing method is provided for an embodiment of the present application;

[0055] Figure 2 A flowchart of a method for constructing a digital twin simulation model corresponding to each equipment unit provided in an embodiment of the present application;

[0056] Figure 3 A flowchart of a method for constructing a digital twin scene of an energy storage power station provided in an embodiment of the present application;

[0057] Figure 4 A flowchart of a method for model data updating and equipment operation and maintenance provided in an embodiment of the present application;

[0058] Figure 5A flowchart of an example of temperature monitoring operation and maintenance provided in an embodiment of the present application;

[0059] Figure 6 A schematic diagram of the architecture of a new energy model data processing device provided in an embodiment of the present application;

[0060] Figure 7 A schematic diagram of the architecture of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0063] The first aspect of the present application provides a new energy model data processing method, such as Figure 1 As shown, including:

[0064] S101. Acquire multi-source heterogeneous data of equipment units at various levels of an energy storage power station.

[0065] It should be noted that since the energy storage power station involves multiple devices, that is, it is composed of multiple device entities, and there will be nesting between the devices, in order to realize the refined model construction of the energy storage power station, the equipment units are divided according to the type of equipment, and the levels of the equipment units of the energy storage power station are divided according to the hierarchical relationship of different devices, and then the multi-source heterogeneous data is obtained. For example, for the current energy storage power station, its equipment units can include a first-level equipment unit. Among them, the first-level equipment unit can include the power system of the power station, the main transformer, the GIS room, the 35KV distribution room, the SVG room, the 10KV station distribution room and the core equipment sub-unit of the energy storage power station. The core equipment sub-unit of the energy storage power station can be further divided into a second-level equipment unit: battery compartment, booster integrated machine. For the booster integrated machine, it can be divided into three-level equipment units: PCS and IO module. The battery compartment can be divided into three-level equipment units: battery stack and peripherals. And the battery pair can be further expanded to: battery cluster-PACK-single cell.

[0066] Multi-source heterogeneous data may specifically include, but are not limited to, equipment images, CAD drawings, and manual models.

[0067] S102. Use multi-source heterogeneous data of each equipment unit to build a digital twin simulation model corresponding to each equipment unit.

[0068] Since the multi-source heterogeneous data of each equipment unit reflects the specific structure of each equipment unit, the multi-source heterogeneous data of each equipment unit can be directly used for three-dimensional modeling to obtain the digital twin simulation model corresponding to each equipment unit.

[0069] Optionally, in another embodiment of the present application, a specific implementation of step S102 is as follows: Figure 2 As shown, including:

[0070] S201. Setting the model level corresponding to each device unit based on the scenario model requirement.

[0071] Since different equipment units have different importance, in order to improve efficiency, etc., in the embodiment of the present application, the model level corresponding to each equipment unit is pre-set based on the scene model requirements. Different model levels correspond to different model accuracies.

[0072] Optionally, in another embodiment of the present application, a specific implementation of step S201 includes:

[0073] The model level corresponding to each first-level equipment unit excluding the equipment unit is set as the first model level, and the model level corresponding to each first-level equipment unit containing the equipment unit and each equipment unit contained therein is set as the second model level.

[0074] Among them, the model accuracy of the second model level is higher than the model accuracy of the first model level. The first model level specifically refers to the L3 model level, and the second model level can be known as the L4 model level. So for example, as shown in the above example, other first-level equipment units except the core equipment subunits of the energy storage power station can be set as L3 level models, and the equipment involved in the core equipment subunits of the energy storage power station can be set as L4 level models.

[0075] S202. Utilize the multi-source heterogeneous data of each equipment unit, perform three-dimensional modeling according to the model level corresponding to the equipment unit, obtain the digital twin simulation model corresponding to each equipment unit, and store it.

[0076] Specifically, the equipment pictures, CAD drawings, and manual models of each equipment unit are processed, and the processed information is used to perform three-dimensional modeling according to the corresponding model level, so as to obtain and store the digital twin simulation model corresponding to each equipment unit. For example, the power system, main transformer, GIS room, 35KV distribution room, SVG room, and 10KV station distribution room of the power station are modeled at the L3 level, and the surface reduction processing is performed on them during modeling, that is, unnecessary surfaces are reduced. The core equipment subunits of the energy storage power station are modeled at the L4 level, such as the energy storage cabin-battery stack-battery cluster-PACK-battery cell, and L4 digital twin simulation models are generated respectively, and they are finely modeled during modeling.

[0077] Finally, after the modeling of each equipment unit is completed, the digital twin simulation model corresponding to each equipment unit is saved. Specifically, it can be saved to the server or remote end, so that when the equipment of the energy storage power station is added or the layout is adjusted, it can be directly dragged and used for scene construction.

[0078] S103. Associate each digital twin simulation model with the corresponding equipment entity in the energy storage power station and the data acquisition device on the equipment entity, and based on the layout information of each equipment entity in the energy storage power station, use the digital twin simulation model corresponding to each equipment unit to construct a scene to obtain a digital twin scene of the energy storage power station.

[0079] It should be noted that the digital twin simulation models corresponding to the equipment units of various equipment entities involved in the energy storage power station are constructed through the above steps. In order to obtain an overall digital twin model that is completely consistent with the energy storage power station, it is also necessary to use the digital twin simulation models of each equipment unit that have been constructed to construct the scene for the specific scene of the energy storage power station, that is, for the specific conditions of each equipment entity of the energy storage power station.

[0080] Since the energy storage power station is monitored and maintained through the digital twin simulation model, that is, the various equipment entities of the energy storage power station are monitored and maintained through the digital twin simulation model, and the corresponding data needs to be collected for monitoring and maintenance. Therefore, in order to monitor and maintain the energy storage power station through the digital twin simulation model, each digital twin simulation model needs to be associated with the corresponding equipment entity to determine the management relationship between the digital twin simulation model and the equipment unit, and also associated with the data acquisition device on the equipment entity to determine which data acquisition device provides the collected data to which digital twin simulation model.

[0081] The digital twin simulation model corresponding to a device entity is the digital twin simulation model corresponding to the device unit of the device entity. For example, multiple energy storage compartment entities in an energy storage power station each correspond to a digital twin simulation model corresponding to a device unit.

[0082] Then, according to the layout information of each equipment entity in the energy storage power station, which may specifically include the number, area, location, etc. of each equipment entity, the scene is built using the digital twin simulation model corresponding to the corresponding equipment unit. That is, according to the number of various equipment units in the energy storage power station, the digital twin simulation models of the equipment units of various equipment entities are combined to form a digital twin scene of the energy storage power station.

[0083] Optionally, in another embodiment of the present application, a specific implementation of step S103 is as follows: Figure 3 As shown, the following steps are included:

[0084] S301. Create a unique code corresponding to a device entity in an energy storage power station.

[0085] Since a certain device unit may correspond to multiple device entities, a unique code can be set according to the number of device entities covered by each device unit, thereby generating a corresponding unique code for each device entity. The unique code can be the SN device code or a unique code generated by the blockchain.

[0086] Optionally, in order to identify the inclusion relationship of device entities at different levels, unique codes may be generated level by level, so that the unique code corresponding to the next level device entity consists of the position code corresponding to the previous level device entity and its own code.

[0087] S302. Associate the unique code corresponding to the device entity with the device entity, the corresponding digital twin simulation model, and the data acquisition device deployed on the device entity.

[0088] It should be noted that the digital twin simulation model corresponding to the device entity is the digital twin simulation model of the device unit corresponding to the device entity.

[0089] Optionally, the unique code corresponding to the device entity may also be associated with basic information such as the name of the corresponding device entity, device location and other information, so as to facilitate management and use of the information of the device entity.

[0090] S303: According to the layout information of each equipment entity in the drawings of the energy storage power station, the digital twin simulation model corresponding to each equipment unit is positioned and set on the digital twin base corresponding to each equipment unit.

[0091] Among them, the digital twin base corresponding to the first-level equipment unit is the digital twin base of the energy storage power station. The digital twin base corresponding to the next-level equipment unit is the digital twin simulation model corresponding to the upper-level equipment unit that contains it. That is, for the energy storage power station, a most basic base will be set up, namely the digital twin base of the energy storage power station, and the digital twin simulation model corresponding to the first-level equipment unit will be directly set on the base. The digital twin simulation models corresponding to the equipment units of other levels will be set on the digital twin simulation models corresponding to the equipment units of the upper level.

[0092] Therefore, when constructing the scene, it can be constructed step by step. Specifically, the digital twin simulation model of the first-level equipment unit can be set on the digital twin base of the energy storage power station according to the energy storage power station drawings that are consistent with the equipment position layout in the real scene, which can be the layout of each equipment entity of the first-level equipment unit of the energy storage power station in the CAD drawings. Specifically, based on the layout information such as the area, quantity, placement position, direction, etc. of the corresponding equipment entity in the drawings, the digital twin simulation model of the first-level equipment unit, such as the digital twin simulation model of the power system of the power station, the main transformer, the GIS room, the 35KV distribution room, the SVG room, and the 10KV station distribution room, can be accurately positioned according to the three axes (XYZ axes) and 9 values ​​(coordinate parameters, translation parameters, and scaling parameters), that is, the setting position of the digital twin simulation model of the first-level equipment unit on the base is determined. Then, according to the positioning information, the digital twin simulation model is uniformly translated, rotated, and scaled to achieve the setting of the digital twin simulation model of the equipment entity of each first-level equipment unit, so that it can be integrated with the digital twin three-dimensional scene of the energy storage power station.

[0093] Then, the digital twin simulation model of the device entity with sub-device units is used as the next-level scene base to build the next-level scene. For example, after the energy storage cabin is built on the digital twin base of the energy storage power station, the battery stack and peripherals are precisely positioned according to the three axes (XYZ axes) and 9 values ​​(coordinate parameters, translation parameters, and scaling parameters) based on the area, quantity, placement, and direction of the corresponding equipment in the CAD drawings. The digital twin simulation model is also uniformly translated, rotated, scaled, and other setting operations are performed on the model to complete the second-level scene construction.

[0094] Of course, in addition to the step-by-step construction method, you can also directly define the equipment unit of the previous level and its sub-location as an overall digital twin simulation model, so that you can directly set the model on the digital twin base of the energy storage power station and complete the setting in one go.

[0095] S304. Through the unique code associated with each digital twin simulation model, the basic information, location and associated scene of the corresponding device entity are associated with the device entity and the data acquisition device thereon.

[0096] It should be noted that after the scene is constructed, the digital twin simulation model of a device unit may construct a digital twin simulation model of the device entity. Therefore, in order to facilitate the monitoring and management of each device entity through the digital twin simulation model of each device entity, it is necessary to associate the basic information, location and associated scene of the corresponding device entity with the device entity and the data acquisition device on it through its associated unique code for each digital twin simulation model in the scene.

[0097] S104: Associating data between each digital twin simulation model in the digital twin scene of the energy storage power station and its associated data acquisition device, and establishing a data transmission channel.

[0098] Specifically, in order to monitor the data of the data acquisition device, each digital twin simulation model is associated with its associated data acquisition device, and a data transmission channel is established. In addition, the data acquisition device can be connected to the Internet of Things platform, so that the Internet of Things platform can be used to set the data acquisition frequency, the conversion format of the collected data, etc. based on the data acquisition requirements or the data update frequency requirements in the digital twin scene of the energy storage power station, and obtain the operation data of the relevant equipment entities of the energy storage power station collected by the data acquisition device, such as current, voltage, temperature, humidity, etc.

[0099] S105. Using the data of each device entity collected in real time by each data collection device, the digital twin scene of the energy storage power station is updated in real time according to the device management method, and each device entity is monitored and managed.

[0100] Specifically, the data of each device entity collected in real time by each data collection device is obtained, and then the digital twin model of the associated device entity in the digital twin scene of the energy storage power station is updated using the collected data. In addition, the collected data can be processed, and then the corresponding methods can be used to perform operation and maintenance operations based on the processed data, such as displaying or generating charts, or analyzing to determine whether there are any abnormalities. When there are abnormalities, a preset method can be used to issue an alarm and take other corresponding operation and maintenance operations to handle them, thereby realizing the monitoring and management of the device entity.

[0101] Optionally, in another embodiment of the present application, a specific implementation of step S105 is as follows: Figure 4 As shown, the following steps are included:

[0102] S401. Using the data of each device entity collected in real time by each data collection device, update the data of the digital twin simulation model in the digital twin scene of the energy storage power station according to the refresh rules.

[0103] Specifically, when the state data of each device entity collected in real time by the data acquisition device changes, the data of the digital twin simulation model corresponding to the corresponding device entity in the digital twin scene of the energy storage power station is updated according to the refresh rules corresponding to the device entity.

[0104] S402: Based on the data of each device entity collected in real time by each data collection device, and in accordance with the corresponding alarm rules, a digital twin simulation model of the current alarm event is analyzed.

[0105] Optionally, different alarm rules are set for different types of status data, and the alarm levels and alarm methods in different alarm rules may be the same.

[0106] S403. Use the management method corresponding to the analyzed digital twin simulation model to perform operation and maintenance.

[0107] Optionally, different alarm methods can be adopted for monitoring data of different ranges. For example, the operation and maintenance management method for the digital twin simulation model that generates the alarm event can be a model rendering and coloring method: the equipment units of different levels can be specifically divided and confirmed by the equipment alarm level. For example, the energy storage cabin and the booster integrated machine model that currently have an alarm event are colored according to the highest level of the alarm event, that is, the corresponding model is displayed in a different color. When there is no alarm, it is the original model style. The specific color can be red for the third-level alarm, orange for the second-level alarm, and yellow for the first-level alarm. For equipment units with sub-devices, they can be colored according to the highest level of the alarm level in the sub-device. For example, for a battery compartment of a third-level equipment unit, there will be multiple alarms in one battery compartment at the same time, that is, the alarm information of different levels of subordinate battery stacks, battery clusters, and battery cells included in it needs to be attributed to the battery compartment, so at this time, the model can be colored according to the highest level of the alarm level among each subordinate. For example, for a three-level device unit, a booster unit has multiple alarms. That is, the alarm information of different levels of the PCS and IO modules needs to be attributed to the booster unit. At this time, the model is colored according to the highest alarm level of the PCS and IO modules.

[0108] Alternatively, a method of displaying an abnormal alarm pop-up window is used: an alarm is issued through an obvious abnormal alarm pop-up window, in which the pop-up window can display the unique code of the alarm device, the device name, the alarm name, the alarm time, the alarm level, the alarm status, etc., so that the operation and maintenance personnel can obtain the alarm status of the relevant equipment units of the energy storage power station in a timely manner.

[0109] Alternatively, the inspection route is set based on the point data of the digital twin simulation model associated with the alarm data. When an alarm occurs, an inspection command is sent to arrange the intelligent robot to conduct an inspection. When the intelligent robot receives the inspection command, it goes directly from the starting point to the nearest point involved in the inspection route and starts the inspection. During the inspection, it detects whether the relevant equipment units of the energy storage power station in the alarm state within the monitoring range of the inspection route are faulty, and relevant operation and maintenance operations can be taken in a timely manner.

[0110] Therefore, through the method provided in the embodiment of the present application, the effective operation and maintenance of the energy storage power station can be realized based on the digital twin scene of the energy storage power station. For example, when monitoring and maintaining the temperature of the energy storage power station, the specific implementation process is as follows: Figure 5 As shown, the following steps are included:

[0111] S501. Acquire temperature data collected by a temperature data collection device arranged in an energy storage power station, and process the temperature data.

[0112] Optionally, the processing of temperature data may specifically include processing its format and abnormal data. Specifically, the data result and data type of the temperature data may be set, and a filter code script for processing mode data conversion rules may be developed, thereby performing data format conversion. Furthermore, the logic and algorithm of data conversion may be defined according to requirements, thereby filtering abnormal values ​​or incomplete data records that appear in the collected data.

[0113] Similarly, for other types of data, such as the voltage of the device entity and the switch status light data, mathematical or statistical methods can be used to convert the data accordingly, such as normalization, unit conversion, etc. In addition, the data set can be enriched by adding additional contextual information or derived data to ensure that the converted data meets the quality standards and business rules of the energy storage scenario.

[0114] S502: Set a temperature threshold based on a temperature control condition of a designated device entity.

[0115] The designated device entity may be a designated device entity for monitoring temperature, such as a battery compartment, a battery stack, a battery cluster, a PACK, or a battery cell of an energy storage power station.

[0116] Specifically, the maximum and maximum values ​​can be set according to the temperature control conditions to determine the temperature range, so as to ensure that all data can be displayed in the subsequent plot. Then, N temperature thresholds can be set for the temperature range to form multiple temperature regions, and different color representations can be associated and mapped for each temperature region.

[0117] S503: Draw a temperature heat map based on the temperature threshold and the collected temperature data.

[0118] A temperature thermodynamic map is drawn based on the collected temperature data and the point data of the temperature sensor on the three-dimensional scene map of the energy storage power station.

[0119] Optionally, a heat map can be drawn on an HTML canvas, and the drawing process can include creating a canvas, clearing the canvas, drawing data points, and applying colors. In addition, when drawing a graph, a global transparency value can be calculated based on the value of each temperature sensor data point (heat level and point data x, y coordinates), and then a corresponding graph can be drawn on the canvas based on the position of the data point and the global transparency value.

[0120] As for the color of the data point, the depth and transparency of the color can be determined according to the value of the data point and the set color gradient effect, so as to form a temperature gradient heat map through gradient colors.

[0121] Among them, the specific method of generating the temperature gradient can be to first generate a color gradient palette, so as to facilitate the selection of the corresponding color according to the value of the data point. Among them, the generation of the color palette includes predefining a color gradient. It is usually a gradient color band from low value to high value, such as from blue to red. Usage scenario: When drawing the corresponding graphics on the canvas according to the position of the data point, when the graphics of different data points overlap, the color gradient calculation is performed on the overlapping area. Then initialize the palette, draw a rectangular color band with a corresponding gradient according to the predefined color gradient, and convert it into image data. Then, through the color selector, select the corresponding color value in the gradient color band according to the value of the data point. Finally, color mixing and superposition are performed. Specifically, a transparency value is calculated according to the value of the data point, and then it is applied to the drawing context to achieve color mixing. That is, the drawn graphics will set the corresponding transparency according to the value of the data point, so as to achieve the color mixing and superposition effect. A larger value will result in a denser color, while a smaller value will make the color more transparent.

[0122] S504: Based on the temperature heat map, obtain the abnormal temperature location and cause of the energy storage power station equipment, and adopt corresponding strategies for operation and maintenance.

[0123] The embodiment of the present application provides a new energy model data processing method, which obtains multi-source heterogeneous data of equipment units at all levels of an energy storage power station, and uses the multi-source heterogeneous data of each equipment unit to construct a digital twin simulation model corresponding to each equipment unit. Then, each digital twin simulation model is associated with the corresponding equipment entity in the energy storage power station, and the data acquisition device on the equipment entity, and based on the layout information of each equipment entity in the energy storage power station, the digital twin simulation model corresponding to each equipment unit is used to construct a scene to obtain a digital twin scene of the energy storage power station, thereby realizing the construction of the digital twin scene of the corresponding energy storage power station based on the multi-source heterogeneous data of the equipment unit, and no longer using the existing model for construction, which can improve the authenticity and accuracy of the digital twin scene. Data association is performed between each digital twin simulation model in the digital twin scene of the energy storage power station and its associated data acquisition device, and a data transmission channel is established, and the data of each equipment entity collected in real time by each data acquisition device is used to update the digital twin scene of the energy storage power station in real time and monitor and manage each equipment entity according to the equipment management method, so that the scene data in the digital twin scene of the energy storage power station can be automatically updated in real time, without the need for manual tedious code modification and maintenance. In addition, effective interaction between the model and operation and maintenance data is achieved, which can effectively detect and manage the operation and maintenance of equipment entities.

[0124] Another embodiment of the present application provides a new energy model data processing device, such as Figure 6 As shown, including:

[0125] The data acquisition unit 601 is used to acquire multi-source heterogeneous data of equipment units at various levels of the energy storage power station.

[0126] The model building unit 602 is used to build a digital twin simulation model corresponding to each equipment unit by using multi-source heterogeneous data of each equipment unit.

[0127] The scene construction unit 603 is used to associate each digital twin simulation model with the corresponding equipment entity in the energy storage power station and the data acquisition device on the equipment entity, and based on the layout information of each equipment entity in the energy storage power station, use the digital twin simulation model corresponding to each equipment unit to construct the scene to obtain the digital twin scene of the energy storage power station.

[0128] The data association unit 604 is used to associate data between each digital twin simulation model in the digital twin scene of the energy storage power station and its associated data acquisition device, and establish a data transmission channel.

[0129] The management unit 605 is used to utilize the data of each device entity collected in real time by each data collection device to update the digital twin scene of the energy storage power station in real time and monitor and manage each device entity according to the device management method.

[0130] Optionally, in the new energy model data processing device provided in another embodiment of the present application, the model building unit includes:

[0131] The level setting unit is used to set the model level corresponding to each device unit based on the scene model requirements.

[0132] The modeling unit is used to utilize the multi-source heterogeneous data of each equipment unit, perform three-dimensional modeling according to the model level corresponding to the equipment unit, obtain the digital twin simulation model corresponding to each equipment unit and store it.

[0133] Optionally, in the new energy model data processing device provided in another embodiment of the present application, the level setting unit includes:

[0134] The level setting subunit is used to set the model level corresponding to each first-level equipment unit that does not include the equipment unit to the first model level, and to set the model level corresponding to each first-level equipment unit that includes the equipment unit and each equipment unit included therein to the second model level. The model accuracy of the second model level is higher than the model accuracy of the first model level.

[0135] Optionally, in the new energy model data processing device provided in another embodiment of the present application, the scene construction unit includes:

[0136] The code creation unit is used to create a unique code corresponding to the equipment entity in the energy storage power station.

[0137] The first association unit is used to associate the unique code corresponding to the device entity with the device entity, the corresponding digital twin simulation model, and the data acquisition device deployed on the device entity.

[0138] The model layout unit is used to locate and set the digital twin simulation model corresponding to the equipment unit on the digital twin base corresponding to each equipment unit according to the layout information of each equipment entity in the drawings of the energy storage power station. Among them, the digital twin base corresponding to the first-level equipment unit is the digital twin base of the energy storage power station. The digital twin base corresponding to the equipment unit of the next level is the digital twin simulation model corresponding to the equipment unit of the previous level that contains it.

[0139] The second association unit is used to associate the basic information, location and associated scenes of the corresponding device entity with the device entity and the data acquisition device thereon through the unique code associated with each digital twin simulation model.

[0140] Optionally, in the new energy model data processing device provided in another embodiment of the present application, the management unit includes:

[0141] The data updating unit is used to update the data of the digital twin simulation model in the digital twin scene of the energy storage power station according to the refresh rules using the data of each device entity collected in real time by each data acquisition device.

[0142] The data analysis unit is used to analyze the digital twin simulation model of the current alarm event based on the data of each device entity collected in real time by each data acquisition device and in accordance with the corresponding alarm rules.

[0143] The operation and maintenance management unit is used to perform operation and maintenance operations using the management method corresponding to the analyzed digital twin simulation model.

[0144] It should be noted that the specific working process of each unit provided in the above embodiments of the present application can refer to the implementation process of the corresponding steps in the above method embodiments, and will not be repeated here.

[0145] Another embodiment of the present application provides an electronic device, such as Figure 7 As shown, including:

[0146] Memory 701 and processor 702 .

[0147] The memory 701 is used to store programs.

[0148] The processor 702 is used to execute the program stored in the memory 701. When the program is executed, it is specifically used to implement the new energy model data processing method provided by any one of the above embodiments.

[0149] Another embodiment of the present application provides a computer storage medium for storing a computer program. When the computer program is executed by a processor, it is used to implement the new energy model data processing method provided in any of the above embodiments.

[0150] Computer storage media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0151] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0152] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A new energy model data processing method, characterized in that: include: Obtain multi-source heterogeneous data of equipment units at all levels of energy storage power stations; Using multi-source heterogeneous data of each of the equipment units to construct a digital twin simulation model corresponding to each of the equipment units; Associating each of the digital twin simulation models with the corresponding equipment entities in the energy storage power station and the data acquisition devices on the equipment entities, and based on the layout information of each of the equipment entities in the energy storage power station, using the digital twin simulation models corresponding to each of the equipment units to construct a scene, to obtain a digital twin scene of the energy storage power station; Associating data between each digital twin simulation model in the digital twin scene of the energy storage power station and the associated data acquisition device, and establishing a data transmission channel; Utilizing the data of each of the device entities collected in real time by each of the data acquisition devices, the digital twin scene of the energy storage power station is updated in real time and each of the device entities is monitored and managed according to the device management method.

2. The method according to claim 1, characterized in that The method of using the multi-source heterogeneous data of each of the equipment units to construct a digital twin simulation model corresponding to each of the equipment units includes: Setting the model level corresponding to each of the equipment units based on the scenario model requirements; Utilizing the multi-source heterogeneous data of each of the equipment units, three-dimensional modeling is performed according to the model level corresponding to the equipment unit, and the digital twin simulation model corresponding to each of the equipment units is obtained and stored.

3. The method according to claim 1, characterized in that The setting of the model level corresponding to each of the equipment units based on the scenario model requirement includes: The model level corresponding to each first-level device unit that does not include the device unit is set to the first model level, and the model level corresponding to each first-level device unit that includes the device unit and each of the device units included is set to the second model level; wherein the model accuracy of the second model level is higher than the model accuracy of the first model level.

4. The method according to claim 1, characterized in that: The digital twin simulation model is associated with the corresponding equipment entity in the energy storage power station and the data acquisition device on the equipment entity, and based on the layout information of each equipment entity in the energy storage power station, the digital twin simulation model corresponding to each equipment unit is used to construct a scene to obtain the digital twin scene of the energy storage power station, including: Creating a unique code corresponding to the device entity in the energy storage power station; Associating the unique code corresponding to the device entity with the device entity, the corresponding digital twin simulation model, and the data acquisition device deployed on the device entity; According to the layout information of each of the equipment entities in the drawings of the energy storage power station, on the digital twin base corresponding to each of the equipment units, the digital twin simulation model corresponding to the equipment unit is positioned and set; wherein the digital twin base corresponding to the equipment unit of the first level is the digital twin base of the energy storage power station; the digital twin base corresponding to the equipment unit of the next level is the digital twin simulation model corresponding to the equipment unit of the previous level; Through the unique code associated with each digital twin simulation model, the basic information, location and associated scene of the corresponding device entity are associated with the device entity and the data acquisition device thereon.

5. The method according to claim 1, characterized in that The data of each device entity collected in real time by each data acquisition device is used to update the digital twin scene of the energy storage power station in real time and monitor and manage each device entity according to the device management method, including: Using the data of each of the device entities collected in real time by each of the data acquisition devices, update the data of the digital twin simulation model in the digital twin scene of the energy storage power station according to the refresh rule; Based on the data of each of the device entities collected in real time by each of the data collection devices, and in accordance with the corresponding alarm rules, the digital twin simulation model that currently generates the alarm event is analyzed; The operation and maintenance are performed using the management method corresponding to the analyzed digital twin simulation model.

6. A new energy model data processing device, characterized in that: include: A data acquisition unit, used to acquire multi-source heterogeneous data of equipment units at all levels of the energy storage power station; A model building unit, used to build a digital twin simulation model corresponding to each of the equipment units using multi-source heterogeneous data of each of the equipment units; A scenario construction unit, used to associate each of the digital twin simulation models with the corresponding equipment entities in the energy storage power station and the data acquisition devices on the equipment entities, and based on the layout information of each of the equipment entities in the energy storage power station, use the digital twin simulation models corresponding to each of the equipment units to construct a scenario, so as to obtain a digital twin scenario of the energy storage power station; A data association unit, used to associate data between each digital twin simulation model in the digital twin scene of the energy storage power station and the data acquisition device associated therewith, and establish a data transmission channel; A management unit is used to utilize the data of each of the device entities collected in real time by each of the data acquisition devices, to update the digital twin scene of the energy storage power station in real time and to monitor and manage each of the device entities according to the device management method.

7. The device according to claim 6, characterized in that The model building unit comprises: A level setting unit, used for setting the model level corresponding to each of the equipment units based on the scenario model requirements; The modeling unit is used to utilize the multi-source heterogeneous data of each of the equipment units to perform three-dimensional modeling according to the model level corresponding to the equipment unit, obtain the digital twin simulation model corresponding to each of the equipment units and store it.

8. The device according to claim 6, characterized in that The level setting unit comprises: A level setting subunit is used to set the model level corresponding to each first-level device unit that does not include the device unit to the first model level, and to set the model level corresponding to each first-level device unit that includes the device unit and each of the device units included therein to the second model level; wherein the model accuracy of the second model level is higher than the model accuracy of the first model level.

9. An electronic device, characterized in that: include: Memory and processor; Wherein, the memory is used to store programs; The processor is used to execute the program, and when the program is executed, it is specifically used to implement the new energy model data processing method as described in any one of claims 1 to 5.

10. A computer storage medium, characterized in that: Used to store a computer program, which, when executed by a processor, is used to implement the new energy model data processing method as described in any one of claims 1 to 5.

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