CN114154429A - Digital twin body construction method and device of energy storage system and storage medium - Google Patents
Digital twin body construction method and device of energy storage system and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device and a storage medium for constructing a digital twin body of an energy storage system, wherein the method comprises the following steps: establishing an electrochemical mechanism model according to the cell data of the energy storage system; building information models corresponding to the energy storage systems are established based on the data of the energy storage systems; constructing a digital twin scene according to the relation between the building information models; based on data monitored and collected by the energy storage system, establishing a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model; and establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene. By implementing the method, an electrochemical mechanism model and a BIM model are established, and meanwhile, an energy storage system is fully considered to establish a multi-physical-field simulation calculation model which needs to be integrated with a digital twin body, so that static and dynamic data fusion analysis is realized and the method is closer to an electrochemical energy storage power station entity. The practical use of the digital twins is essentially expanded.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method and a device for constructing a digital twin body of an energy storage system and a storage medium.
Background
The establishment of the digital twin body of the electrochemical energy storage system is an advanced technical means for mastering the actual operation state of the electrochemical energy storage system, most of the existing establishment methods of the digital twin body of the electrochemical energy storage system stay in the establishment of an apparent model of each level unit of the electrochemical energy storage system, various dynamic monitoring information is integrated, and on the basis, monitoring data are analyzed and calculated by adopting some algorithms to obtain corresponding analysis and calculation results so as to judge whether abnormity exists or not or predict the data by using historical monitoring data, so that the aim of safety early warning is fulfilled.
Therefore, the existing construction method of the digital twin body aiming at the electrochemical energy storage system is more focused on the visual display effect seen by a user on the three-dimensional model level of the entity object, only the simple rendering display is carried out, the analysis and calculation function is not provided, and the core effect of the simulation analysis of the digital twin body is difficult to embody.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, and a storage medium for constructing a digital twin of an energy storage system, so as to solve a technical problem in the prior art that a core effect of a digital twin simulation analysis is difficult to be embodied for a digital twin constructed for an energy storage system.
The technical scheme provided by the invention is as follows:
the first aspect of the embodiments of the present invention provides a method for constructing a digital twin body of an energy storage system, including: establishing an electrochemical mechanism model according to the cell data of the energy storage system; building information models corresponding to the energy storage systems are established based on the data of the energy storage systems; constructing a digital twin scene according to the relation between the building information models; based on data monitored and collected by the energy storage system, establishing a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model; and establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene.
Optionally, the digital twin construction method of the energy storage system further includes: determining abnormal alarm information of the digital twin body according to the state of the entity energy storage system simulated by the digital twin body; establishing an abnormality prediction machine learning model according to the abnormality alarm information of the digital twin body and the entity energy storage system; and performing optimized regulation and control on the entity energy storage system according to the prediction result of the anomaly prediction machine learning model on the current monitoring data.
Optionally, the digital twin construction method of the energy storage system further includes: adjusting parameter values in the digital twin body, simulating energy storage systems in different states, taking historical parameter values of the digital twin body associated with the corresponding states, carrying out inversion, and determining the state of an entity energy storage system; and regulating and controlling the energy storage system according to the state of the entity energy storage system.
Optionally, the establishing an electrochemical mechanism model according to the cell data of the energy storage system includes: determining the current state parameters of the battery cell according to the battery cell data of the energy storage system; and establishing an electrochemical mechanism model according to the current state parameters of the battery cell, wherein the electrochemical mechanism model is used for dynamically simulating the state parameter change of the battery cell.
Optionally, the building information model corresponding to the energy storage system is established based on the energy storage system data, and the building information model includes: correspondingly establishing a corresponding three-dimensional building information model based on each entity in the energy storage system; and binding various types of static information and the corresponding three-dimensional building information models to obtain a plurality of building information models corresponding to the energy storage system.
Optionally, constructing a digital twin scene according to the relationship between the building information models, including: carrying out format preprocessing on the building information model; adjusting the position state of each building information model based on the actual topological relation and the spatial layout relation of each hierarchical unit in the energy storage system; establishing an incidence relation and a constitutive model of each building information model based on operation and control logic of the energy storage system; and constructing a digital twin scene based on the adjusted building information model, the incidence relation of each building information model and the constitutive model.
Optionally, the establishing a data relationship model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on the data collected by monitoring the energy storage system includes: acquiring data monitored and acquired by an energy storage system; associating the data with a corresponding building information model; based on the types of the data, establishing a relation model among the data types of each hierarchy according to the operation logic and mechanism of the energy storage system; and performing combined association according to the parameters of the electrochemical mechanism model, the parameters of the building information model and the data to establish a simulation calculation analysis model of the energy storage system.
A second aspect of an embodiment of the present invention provides a digital twin body construction device for an energy storage system, including: the first model building model is used for building an electrochemical mechanism model according to the battery cell data of the energy storage system; the second model building model is used for building a building information model corresponding to the energy storage system based on the data of the energy storage system; the scene building module is used for building a digital twin scene according to the relation between the building information models; the third and fourth model building module is used for building a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on the data monitored and collected by the energy storage system; and the digital twin body establishing module is used for establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene.
A third aspect of the embodiments of the present invention provides a computer-readable storage medium, where computer instructions are stored, and the computer instructions are configured to cause a computer to execute the method for constructing a digital twin of an energy storage system according to any one of the first aspect and the first aspect of the embodiments of the present invention.
A fourth aspect of an embodiment of the present invention provides an electronic device, including: the digital twin construction method of the energy storage system comprises a memory and a processor, wherein the memory and the processor are connected in a communication mode, the memory stores computer instructions, and the processor executes the computer instructions to execute the digital twin construction method of the energy storage system according to any one of the first aspect and the first aspect of the embodiments of the invention.
The technical scheme provided by the invention has the following effects:
according to the digital twin construction method, device and storage medium of the energy storage system, provided by the embodiment of the invention, the influence of the electrochemical mechanism of the battery cell on the subsequent operation of the electrochemical energy storage system is considered by establishing the electrochemical mechanism model; meanwhile, a BIM model is constructed, and a BIM technology is combined, so that the three-dimensional model of the electrochemical energy storage system is not only a carrier for displaying monitoring data, but also a refined BIM model with simulation calculation capability for integrating various attribute parameters is formed; in addition, the energy storage system is fully considered to establish a multi-physical-field simulation calculation model which needs integration of digital twin, and static and dynamic data fusion analysis is achieved and is closer to an electrochemical energy storage power station entity. And an intelligent mutual feed optimization mode of the virtual digital twin body and the electrochemical energy storage system driven by data and various mathematical calculation models is also better established. The method has simple steps and strong operability, improves the simulation precision of the energy storage system to a certain extent, essentially expands the actual application of the digital twin body, and better applies the digital twin technology to the field of energy storage.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a digital twin construction method of an energy storage system according to an embodiment of the invention;
fig. 2 is a schematic structural diagram of a digital twin body constructed by the digital twin body construction method of the energy storage system according to the embodiment of the invention;
FIG. 3 is a flow chart of a digital twin construction method of an energy storage system according to another embodiment of the invention;
FIG. 4 is a flow chart of a digital twin construction method of an energy storage system according to another embodiment of the invention;
FIG. 5 is a block diagram of a digital twin construction apparatus of an energy storage system according to an embodiment of the invention;
FIG. 6 is a schematic structural diagram of a computer-readable storage medium provided according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As described in the background art, in the prior art, the construction of the digital twin for the energy storage system is only a pure rendering display, and does not have an analysis and calculation function. Meanwhile, the collection and integration of the monitoring data are realized by simply binding the monitoring data with the corresponding three-dimensional model, the relation between various types of monitoring data, including the monitoring data of the battery, state quantity, environmental information and the like, is not represented, and the correlation between the monitoring data and original attribute parameters of an actual entity model is not established, so that the final analysis and calculation work is changed into simple data processing and analysis work according to various monitored data. In fact, in such a method, the model object, the monitoring data and the entity object are split, in other words, the digital twin body constructed by the method can realize the functions of analysis, calculation, feedback, early warning and the like which are to be realized only through the acquired monitoring data, and does not embody the core value of the digital twin technology.
Therefore, in the prior art, the construction 1 of the digital twin body for the energy storage system does not consider the influence of the electrochemical mechanism model of the battery cell on the subsequent operation; the three-dimensional model only has a rendering display effect, does not have associated attribute parameters and does not have analysis and calculation capacity; the three-dimensional model object, the monitoring data, the environmental information and the like are relatively split, the coupling relation between all the elements and between different types of parameters of all the elements is not considered, and a reasonable and vivid simulation model cannot be formed.
In view of this, the embodiment of the present invention provides a method for constructing a digital twin body of an energy storage system, which is used for constructing a current electrochemical energy storage digital twin body without considering a battery cell electrochemical mechanism model; the method is characterized in that models contained in a digital twin are incomplete, the correlation degree among all elements is insufficient, the defect of the core effect of simulation analysis of the digital twin is difficult to embody, various mathematical analysis models needing integrated correlation of the digital twin are fully considered by introducing a Building Information Modeling (BIM) technology and from the essence of an electrochemical energy storage system, and the digital twin of the electrochemical energy storage system which is closer to the actual scene needs and can dynamically update simulation calculation is established.
In accordance with an embodiment of the present invention, there is provided a method for digital twin construction of an energy storage system, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions and that, although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that presented herein.
In this embodiment, a method for constructing a digital twin of an energy storage system is provided, where the method may be implemented in a cloud, and fig. 1 is a flowchart of the method for constructing a digital twin of an energy storage system according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S101: and establishing an electrochemical mechanism model according to the cell data of the energy storage system. The energy storage system may be an electrochemical energy storage system, or may be other types of energy storage systems. Specifically, the electrochemical mechanism models of different cells are different, and therefore, when the electrochemical mechanism models are established, cell data in the energy storage system needs to be determined so as to obtain the state parameters of the current cell. The cell data may be obtained from battery test data obtained by a corresponding cell manufacturer. Specifically, the electrochemical mechanism model is constructed by fitting the state parameters of the current battery cell, and the state parameter change of the battery cell can be dynamically simulated for the electrochemical mechanism model.
When a digital twin body is constructed at the cloud end, the established electrochemical mechanism model is uploaded to the cloud end, a dynamically adjusted parameter interface is reserved at the cloud end, and the state parameters of the current battery cell and the algorithm corresponding to the electrochemical mechanism model are uploaded to the cloud end, so that the electrochemical mechanism model is continuously calculated and updated along with time.
Step S102: and establishing a building information model corresponding to the energy storage system based on the energy storage system data. Before building the building information model, data such as the size of each entity object in the energy storage system are obtained in advance, the obtained data are input into BIM software, and the three-dimensional BIM model of each entity object is built. Meanwhile, various kinds of static information such as material, mechanical property and thermal property of the entity object are obtained, and the static information is bound with the corresponding three-dimensional building information model, so that the building information model corresponding to each entity object in the energy storage system is obtained.
Step S103: and constructing a digital twin scene according to the relation between the building information models. After the BIM model of each entity object is obtained, in order to enable the subsequently constructed digital twin body to have universality, each BIM model containing complete attribute information is converted into an international universal IFC (interactive file transfer) format before the BIM model is uploaded to the cloud, and then the converted BIM model is imported into the cloud. In addition, because the built BIM model is an independent model of each entity object, the position state of each building information model is adjusted based on the actual topological relation and the spatial layout relation of each hierarchical unit in the energy storage system; meanwhile, based on the operation and control logic of the energy storage system, the incidence relation and the constitutive model of each building information model are established; thereby enabling correlation between the various BIM models.
The constitutive model is a model which needs to be established by simulation calculation on a single object or a whole scene system, such as an electrochemical thermal simulation model of the whole system, a stress-strain model of a battery module shell and other calculation models. After the model construction is completed, a digital twin scene can be built based on the adjusted building information model, the incidence relation of each building information model and the constitutive model. Therefore, the entity BIM model, the relevant static attribute information and the relation models among different models, such as the spatial relation, the physical connection relation and the like (represented by a common formula or an algorithm) are embedded in the built digital twin scene, namely the digital twin scene realizes the reduction of the objects in the real scene and the relations among the objects by the digital model, the data and the formula.
Step S104: and establishing a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on the data monitored and collected by the energy storage system. And after the scene building is completed, acquiring data monitored and collected by the energy storage system, and butting the monitored data. For the data collected by monitoring, the categories of different data are firstly combed, the data are classified and preprocessed, the data collected by different collectors are subjected to protocol conversion, and the converted data are pushed into the built digital twin scene through a preset protocol such as an MQTT (Message Queuing Telemetry Transport) protocol. Meanwhile, the data can be stored in a database in the digital twin scene, the database realizes the storage function of all data in the digital twin scene, the database comprises all static information, monitoring data and the like, and meanwhile, the data can be called externally.
Because each entity model is embedded in the built digital twin scene, after the data is pushed to the digital twin scene, the corresponding data is associated with the corresponding BIM model according to the actual situation. And meanwhile, based on the types of the data, establishing a relational model among the data types of each hierarchy according to the operation logic and mechanism of the energy storage system.
And coupling simulation of multiple models and multiple physical fields can be realized by combining the pushed data, the constructed electrochemical mechanism model and the BIM model of each entity object. Specifically, from a demand side, the main parameters of the electrochemical mechanism model of the cell unit, the attribute parameters of each BIM model, various monitoring data parameters, environmental variables and other elements are combined and associated according to the characteristics of the electrochemical energy storage system, and a simulation calculation analysis model of the electrochemical energy storage system such as a temperature field, an electromagnetic field, a stress strain field and the like is established.
Step S105: and establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene. After the scene building and the model building are completed, the construction of the digital twin is completed. And for the constructed digital twin body, massive dynamic monitoring data can be used for driving dynamic update of various simulation calculation BIM models, and the actual state information of the current digital twin body, including size change, stress strain, temperature, internal resistance, SOC, SOH and the like, can be continuously and dynamically updated by combining the previously established incidence relation and mathematical model relation between each entity object, each parameter type, parameter and simulation field.
According to the digital twin body construction method of the energy storage system, an electrochemical mechanism model is established, and the influence of the electrochemical mechanism of the battery cell on the operation of the subsequent electrochemical energy storage system is considered; meanwhile, a BIM model is constructed, and a BIM technology is combined, so that the three-dimensional model of the electrochemical energy storage system is not only a carrier for displaying monitoring data, but also a refined BIM model with simulation calculation capability for integrating various attribute parameters is formed; in addition, the energy storage system is fully considered to establish a multi-physical-field simulation calculation model which needs integration of digital twin, and static and dynamic data fusion analysis is achieved and is closer to an electrochemical energy storage power station entity. And an intelligent mutual feed optimization mode of the virtual digital twin body and the electrochemical energy storage system driven by data and various mathematical calculation models is also better established. The method has simple steps and strong operability, improves the simulation precision of the energy storage system to a certain extent, essentially expands the actual application of the digital twin body, and better applies the digital twin technology to the field of energy storage.
In an embodiment, the method for constructing a digital twin of an energy storage system further comprises: determining abnormal alarm information of the digital twin body according to the state of the entity energy storage system simulated by the digital twin body; establishing an abnormality prediction machine learning model according to the abnormality alarm information of the digital twin body and the entity energy storage system; and performing optimized regulation and control on the entity energy storage system according to the prediction result of the anomaly prediction machine learning model on the current monitoring data.
Specifically, when the anomaly prediction machine learning model is established, not only the anomaly alarm information of the digital twin body is input, but also the anomaly alarm information of the entity energy storage system is input, and the anomaly alarm information of the entity energy storage system is input into the model to help the model to judge which conditions are abnormal under the actual conditions, so that the anomaly prediction machine learning model is used for correcting the model. The abnormal alarm information of the entity energy storage system is used as a training sample, so that the actual abnormal condition can be determined. And the abnormal alarm information of the digital twin body is input into the model, and whether the digital twin body is abnormal or not, namely whether the real system is abnormal or not is judged by using the current actual dynamic data.
After the abnormity prediction machine learning model is established, the current monitoring data is input into the model, and possible subsequent operation abnormity and risks can be predicted based on the output result, so that the operation abnormity and risks can be fed back to the entity energy storage system for optimal regulation and control.
In an embodiment, the method for constructing a digital twin of an energy storage system further comprises: adjusting parameter values in the digital twin body to simulate energy storage systems in different states; calling historical parameter values of the digital twin bodies associated with the corresponding states to perform inversion, and determining the states of the entity energy storage system; and regulating and controlling the energy storage system according to the state of the entity energy storage system.
After the digital twin of the energy storage system is constructed, the inversion optimization of the energy storage system can be realized based on the digital twin. Specifically, parameter values associated with a digital twin body at the cloud are adjusted, the environment and the state of the energy storage system to be simulated are embedded into the digital twin body, historical digital twin body associated parameters associated with the state are adjusted for inversion, the state of the digital twin body simulation reality system under a specific condition can be obtained, the real system is fed back and regulated, and related risks are avoided.
In addition, the static and dynamic parameters of the entity energy storage system and the digital twin body are continuously fed mutually, so that the construction and dynamic update of the digital twin body of the energy storage system can be realized. As can be seen from the above steps, the structure of the digital twin constructed by the digital twin construction method of the energy storage system is specifically shown in fig. 2.
In an embodiment, as shown in fig. 3, when a constructed digital twin body is required to perform temperature field simulation analysis and thermal runaway early warning on an electrochemical energy storage system, the method for constructing the digital twin body of the energy storage system specifically includes the following steps:
step 201: the electrochemical mechanism of the embedded cell is modeled. Firstly, according to different battery cores used by an electrochemical energy storage system, battery test data of corresponding battery core manufacturers are collected, and actual states of the battery cores in the current batch, including actual information such as internal resistance, battery electric quantity and health degree, are accurately acquired. And then establishing an electrochemical mechanism model fitting each battery cell, wherein the model can dynamically simulate the internal parameter change of the battery cell along with time. Meanwhile, an algorithm corresponding to the electrochemical mechanism model, for example, for thermal runaway, a calculation method of heat generated by battery cell charging and discharging and current parameter values of actual health degree, battery cell internal resistance and the like of each battery cell are uploaded to the cloud end to be continuously calculated and updated along with time, and differences among the battery cells in each group can be simulated and monitored. And a dynamically adjustable parameter interface is reserved on the cloud.
Step 202: and establishing a BIM model of the electrochemical energy storage system. And in BIM software, establishing a corresponding three-dimensional BIM model according to the sizes of all entity objects related to the electrochemical energy storage system. And binding various types of static information such as materials, mechanical properties, thermal properties and the like with the corresponding BIM model object.
Step 203: and constructing a digital twin scene. And converting each BIM containing complete attribute information into an international universal IFC format, and importing the IFC format into the cloud. And adjusting the position state of each BIM according to the actual topological relation and the spatial layout relation of each hierarchical unit of the electrochemical energy storage system to form a uniform three-dimensional simulation scene. And establishing an incidence relation and a constitutive model of each BIM model object according to the operation and control logic of the electrochemical energy storage system, the thermal runaway influence range of each object unit and other associated objects.
Step 204: and monitoring data docking. According to the data category monitored and collected by an electrochemical energy storage system, the parameters such as current, voltage, environment temperature, battery hierarchy system temperature and the like related to thermal runaway are classified and preprocessed, and information collected by different collectors is pushed to a database and a digital twin scene through protocol conversion by an MQTT protocol. The monitoring data is associated with the corresponding BIM model object with reference to the actual situation. And establishing a relation model among various types of data of various levels according to the collected various types of monitoring data and starting from the monitoring data related to the occurrence of the thermal runaway event of the electrochemical energy storage system.
Step 205: and coupling and simulating multiple models and multiple physical fields. Starting from the mechanism of thermal runaway, according to the characteristics of an electrochemical energy storage system, the main parameters of an electrochemical mechanism model of a cell unit, the thermodynamic parameters of materials of each BIM unit, the monitoring data parameters of current, voltage, temperature and the like, the environmental temperature, the concentration of combustible gas in the energy storage system and other factors are combined and associated, and a temperature field simulation calculation analysis model of the electrochemical energy storage system is established. The method comprises the steps of docking multi-physical field simulation calculation software such as COMSOL and the like, utilizing massive dynamic monitoring data to drive dynamic updating of a temperature field simulation calculation BIM model, combining previously established entity objects, parameter types, incidence relations between parameters and simulation fields and mathematical model relations, continuously and dynamically updating actual state information of current digital twin bodies, including size change, stress strain, temperature, internal resistance, SOC, SOH difference and the like, checking whether temperature abnormal points exist in an actual electrochemical energy storage system or not based on a digital twin body temperature field simulation result, and performing targeted processing.
Step 206: and dynamic updating and machine learning model building. According to temperature abnormity alarm information of the digital twin body and the entity energy storage system, a thermal runaway prediction machine learning model of the electrochemical energy storage system is established at the cloud end, dynamic monitoring information such as temperature, voltage and current and actual thermal runaway alarm information are used for driving the machine learning model to train, and parameters of the machine learning model are optimized. The current monitoring data are input into a thermal runaway prediction machine learning model, the possible subsequent temperature abnormity and risks are predicted, and the temperature abnormity and the risks are fed back to the entity energy storage system for optimization regulation and control and prior control, so that the risks can be avoided in advance, and the safe and stable operation of the electrochemical energy storage system is guaranteed.
In an embodiment, as shown in fig. 4, when a dynamic prediction of the remaining life of a battery of an electrochemical energy storage system needs to be performed by using a constructed digital twin, the method for constructing the digital twin of the energy storage system specifically includes the following steps:
and 301, embedding a battery degradation model of the battery core. Firstly, collecting relevant data of battery charging and discharging and service life testing of corresponding battery core manufacturers according to different battery cores used by an electrochemical energy storage system, and accurately acquiring the actual health state of the battery cores of the current batch and the core parameters of a degradation model of the battery. And then, establishing a degradation model fitting each battery cell, and dynamically simulating the internal parameter change of the battery cell along with time. Meanwhile, internal parameter quantities such as Bayesian algorithms corresponding to the battery degradation model, the actual state quantity of each current battery cell, the cell capacity and the like are uploaded to the cloud end to be continuously calculated and updated along with time, and a dynamically adjustable parameter interface is reserved.
And 302, establishing a BIM model of the electrochemical energy storage system. And in BIM software, establishing a corresponding three-dimensional BIM model according to the sizes of all entity objects related to the electrochemical energy storage system. And binding various types of static information such as materials, mechanical properties, thermal properties and the like with the corresponding BIM model object.
And 303, building a digital twin scene. And converting each BIM containing complete attribute information into an international universal IFC format, and importing the IFC format into the cloud. And adjusting the position state of each BIM according to the actual topological relation and the spatial layout relation of each hierarchical unit of the electrochemical energy storage system to form a uniform three-dimensional simulation scene. And establishing the association relation and the constitutive model of each BIM model object on the basis of the mutual association parameters among the cell degradation models in the same group of strings according to the operation and control logic of the electrochemical energy storage system.
And step 304, monitoring data docking. The method comprises the steps of classifying and preprocessing data according to the type of the data monitored and collected by an electrochemical energy storage system, converting the information collected by different collectors through protocols, and pushing the information into a database and a digital twin scene through an MQTT protocol. The monitoring data is associated with the corresponding BIM model object with reference to the actual situation. And establishing a relevant battery cell degradation parameter relation model among various types of data of each hierarchy from the operation logic and mechanism of the electrochemical energy storage system according to the acquired data such as voltage, current and electric quantity.
And 305, coupling simulation of multiple models and multiple physical fields. Starting from key factors influencing the service life of the battery, the main parameters of the cell unit degradation model, the attribute parameters of each BIM unit, various monitoring data parameters, environmental variables and other factors are combined and associated according to the characteristics of the electrochemical energy storage system, and a simulation calculation analysis model of the electrochemical energy storage system such as a temperature field, an electromagnetic field, a stress strain field and the like is established. And (3) docking multi-physical field simulation calculation software, driving dynamic update of various simulation calculation BIM models by using massive dynamic monitoring data, and continuously and dynamically updating the actual state information of each current digital twin body, including size change, stress strain, temperature, internal resistance, SOC, SOH and the like, by combining the previously established entity objects, parameter types, incidence relations between parameters and simulation fields and mathematical model relations.
And step 306, dynamically predicting the residual life of the battery. According to the monitoring data information of the digital twin body and the entity energy storage system, a machine learning model for estimating the residual capacity of the battery of the electrochemical energy storage system is established at the cloud end, the machine learning model is driven to train by massive dynamic monitoring information and charge and discharge amount information, and model parameters are optimized. And tracking the capacity decline of each battery according to the state of the entity energy storage system simulated by the current digital twin body, establishing a capacity decline curve of each battery, and fitting a predicted value of the residual life of each battery in the current electrochemical energy storage system according to the current operation data and the charge-discharge intensity and state. And accessing the current actual monitoring data into a machine learning model, predicting the residual life of each battery which is continuously used according to the current regulation and control strategy, reflecting the difference of the residual life of different batteries, and helping operation and maintenance personnel to find abnormal batteries for processing and replacing. The battery self-characteristic, the electrochemical energy storage system characteristic and the actual operation strategy and other factors are fully coupled, and the residual life of each battery is dynamically predicted in real time. Theoretically, the service life prediction result has higher reliability and actual reference value.
An embodiment of the present invention further provides a digital twin body constructing apparatus of an energy storage system, as shown in fig. 5, the apparatus includes:
the first model building model is used for building an electrochemical mechanism model according to the battery cell data of the energy storage system; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
The second model building model is used for building a building information model corresponding to the energy storage system based on the data of the energy storage system; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
The scene building module is used for building a digital twin scene according to the relation between the building information models; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
The third and fourth model building module is used for building a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on the data monitored and collected by the energy storage system; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
And the digital twin body establishing module is used for establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
According to the digital twin body construction device of the energy storage system, the influence of the electrochemical mechanism of the battery cell on the operation of the subsequent electrochemical energy storage system is considered by establishing the electrochemical mechanism model; meanwhile, a BIM model is constructed, and a BIM technology is combined, so that the three-dimensional model of the electrochemical energy storage system is not only a carrier for displaying monitoring data, but also a refined BIM model with simulation calculation capability for integrating various attribute parameters is formed; in addition, the energy storage system is fully considered to establish a multi-physical-field simulation calculation model which needs integration of digital twin, and static and dynamic data fusion analysis is achieved and is closer to an electrochemical energy storage power station entity. And an intelligent mutual feed optimization mode of the virtual digital twin body and the electrochemical energy storage system driven by data and various mathematical calculation models is also better established. The device has a simple structure and strong operability, improves the simulation precision of the energy storage system to a certain extent, essentially expands the practical application of the digital twin body, and better applies the digital twin technology to the field of energy storage.
The digital twin body construction device of the energy storage system provided by the embodiment of the invention has the function description in detail with reference to the digital twin body construction method of the energy storage system in the above embodiment.
An embodiment of the present invention further provides a storage medium, as shown in fig. 6, on which a computer program 601 is stored, where the instructions, when executed by a processor, implement the steps of the digital twin construction method of the energy storage system in the foregoing embodiment. The storage medium is also stored with audio and video stream data, characteristic frame data, an interactive request signaling, encrypted data, preset data size and the like. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
An embodiment of the present invention further provides an electronic device, as shown in fig. 7, the electronic device may include a processor 51 and a memory 52, where the processor 51 and the memory 52 may be connected by a bus or in another manner, and fig. 7 takes the connection by the bus as an example.
The processor 51 may be a Central Processing Unit (CPU). The Processor 51 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 52, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the corresponding program instructions/modules in the embodiments of the present invention. The processor 51 executes various functional applications and data processing of the processor by executing the non-transitory software programs, instructions and modules stored in the memory 52, namely, implements the digital twin construction method of the energy storage system in the above method embodiment.
The memory 52 may include a storage program area and a storage data area, wherein the storage program area may store an operating device, an application program required for at least one function; the storage data area may store data created by the processor 51, and the like. Further, the memory 52 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 52 may optionally include memory located remotely from the processor 51, and these remote memories may be connected to the processor 51 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 52 and when executed by the processor 51 perform a digital twin construction method of an energy storage system as in the embodiment shown in fig. 1-4.
The details of the electronic device may be understood by referring to the corresponding descriptions and effects in the embodiments shown in fig. 1 to fig. 4, and are not described herein again.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. A digital twin construction method of an energy storage system is characterized by comprising the following steps:
establishing an electrochemical mechanism model according to the cell data of the energy storage system;
building information models corresponding to the energy storage systems are established based on the data of the energy storage systems;
constructing a digital twin scene according to the relation between the building information models;
based on data monitored and collected by the energy storage system, establishing a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model;
and establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene.
2. The digital twin construction method of an energy storage system according to claim 1, further comprising:
determining abnormal alarm information of the digital twin body according to the state of the entity energy storage system simulated by the digital twin body;
establishing an abnormality prediction machine learning model according to the abnormality alarm information of the digital twin body and the entity energy storage system;
and performing optimized regulation and control on the entity energy storage system according to the prediction result of the anomaly prediction machine learning model on the current monitoring data.
3. The digital twin construction method of an energy storage system according to claim 1, further comprising:
adjusting parameter values in the digital twin body to simulate energy storage systems in different states;
calling historical parameter values of the digital twin bodies associated with the corresponding states to perform inversion, and determining the states of the entity energy storage system;
and regulating and controlling the energy storage system according to the state of the entity energy storage system.
4. The method for constructing the digital twin body of the energy storage system according to claim 1, wherein establishing an electrochemical mechanism model according to cell data of the energy storage system comprises:
determining the current state parameters of the battery cell according to the battery cell data of the energy storage system;
and establishing an electrochemical mechanism model according to the current state parameters of the battery cell, wherein the electrochemical mechanism model is used for dynamically simulating the state parameter change of the battery cell.
5. The method for constructing the digital twin body of the energy storage system according to claim 1, wherein the building information model corresponding to the energy storage system is established based on the data of the energy storage system, and the method comprises the following steps:
correspondingly establishing a corresponding three-dimensional building information model based on each entity in the energy storage system;
and binding various types of static information and the corresponding three-dimensional building information models to obtain a plurality of building information models corresponding to the energy storage system.
6. The method for constructing the digital twin of the energy storage system according to claim 1, wherein constructing the digital twin scene according to the relationship between the building information models comprises:
carrying out format preprocessing on the building information model;
adjusting the position state of each building information model based on the actual topological relation and the spatial layout relation of each hierarchical unit in the energy storage system;
establishing an incidence relation and a constitutive model of each building information model based on operation and control logic of the energy storage system;
and constructing a digital twin scene based on the adjusted building information model, the incidence relation of each building information model and the constitutive model.
7. The method for constructing the digital twin body of the energy storage system according to claim 1, wherein the steps of establishing a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on data collected by monitoring the energy storage system comprise:
acquiring data monitored and acquired by an energy storage system;
associating the data with a corresponding building information model;
based on the types of the data, establishing a relation model among the data types of each hierarchy according to the operation logic and mechanism of the energy storage system;
and performing combined association according to the parameters of the electrochemical mechanism model, the parameters of the building information model and the data to establish a simulation calculation analysis model of the energy storage system.
8. A digital twin construction apparatus of an energy storage system, comprising:
the first model building model is used for building an electrochemical mechanism model according to the battery cell data of the energy storage system;
the second model building model is used for building a building information model corresponding to the energy storage system based on the data of the energy storage system;
the scene building module is used for building a digital twin scene according to the relation between the building information models;
the third and fourth model building module is used for building a data relation model and a simulation calculation analysis model of the energy storage system according to the electrochemical mechanism model and the building information model based on the data monitored and collected by the energy storage system;
and the digital twin body establishing module is used for establishing a digital twin body of the energy storage system according to the data relation model and the simulation calculation analysis model based on the digital twin scene.
9. A computer-readable storage medium storing computer instructions for causing a computer to perform the method of digital twin construction of an energy storage system according to any one of claims 1-7.
10. An electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method of digital twinning of an energy storage system according to any of claims 1-7.
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