CN113688519B - Digital twin model precision online verification method for multi-energy system - Google Patents
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Abstract
The application discloses a digital twin model precision online verification method of a multi-energy system, which comprises a model precision verification triggering method and a model precision online verification method, wherein the model precision online verification method comprises model reconstruction, recording data introduction, recording section selection, simulation data solving and difference value two-norm calculation, and according to the comparison result of the reconstructed model precision obtained by calculation and a precision threshold value set in advance, the model precision is judged whether to reach the standard or not, and the beneficial effects of the application are that: the method ensures that the digital twin model can be always kept in a high-precision range, and achieves the purposes of judging the model precision and guiding the model correction.
Description
Technical Field
The application relates to the technical field of model accuracy verification, in particular to a digital twin model accuracy online verification method of a multi-energy system.
Background
The multi-energy system aims at improving the energy utilization performance, namely the safety, efficiency, sustainability, flexibility and self-healing capability of an energy supply system, and is a comprehensive system which tightly connects an electric power system, a natural gas system, a cooling and heating system, a distributed energy source, energy storage, energy conversion and an intelligent information physical system with an end user.
At present, the operation control of the multi-energy system is limited by a specific control strategy and massive fragment information, the safety and economy of the multi-energy system are reduced, in addition, the limited access authority of the topological structure change and operation data can influence the effectiveness of the traditional planning structure, a new way is provided for realizing the panoramic perception and continuous control of the multi-energy system, the digital twin technology is different from the traditional knowledge-driven modeling method for describing the motion mechanism by adopting a physical field coupling dynamics equation, the concept that knowledge and data are adopted for combined driving is needed for constructing the digital twin model, the digital twin model not only represents various algebraic mathematical equations in differential or partial differential modes, but also comprises a massive system measurement state data for realizing the synchronization between a physical system and a virtual model, and a correlation model for describing the motion rule by utilizing the historical state data through statistics and machine learning, so that the digital twin model is not a group of constant mathematical equations, but a parameter time-varying and continuous updating evolution model is realized, and although a great quantity of research is carried out on the accuracy verification of the traditional simulation model, the digital twin model is basically carried out on the basis, and the accuracy of the digital twin model is not verified by the real-time, and the real-time accuracy is required to be verified, and the accuracy is not verified, and the accuracy is continuously verified on the model is verified on the real-time by the digital model.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
In view of the existing problems, the application provides an online verification method for the precision of the digital twin model of the multi-energy system.
Therefore, the technical problems solved by the application are as follows: the existing technology is mainly focused on the aspect of carrying out accuracy verification on a traditional simulation model by comparing the numerical simulation result with the error of measured data, and is difficult to combine the real-time change condition of measured data, and the accuracy of a nonlinear time-varying model such as a digital twin model cannot be monitored in real time and continuously and automatically verified, so that the model and parameter correction work can be carried out.
In order to solve the technical problems, the application provides the following technical scheme: an online verification method for digital twin model precision of a multi-energy system comprises the following steps:
judging whether the digital twin model parameters of the multi-energy system change, and selecting whether to perform online verification of model accuracy according to the model parameter change condition;
if the model parameters change, triggering on-line verification of the model precision, reconstructing a digital twin model of the multi-energy system, and importing all the wave recording waveforms of state quantity, input quantity and output quantity in a certain period of time before the triggering moment to obtain a wave recording data matrix;
selecting a section of any moment of a wave recording waveform as an initial state of a reconstructed digital twin model of the multi-energy system, starting an electromagnetic transient simulation program at the section of the moment, setting simulation time length, executing simulation calculation on the reconstructed digital twin model of the multi-energy system, solving a state space equation, and obtaining simulation waveforms of all state quantities, input quantities and output quantities in a certain time period after the moment to obtain a simulation data matrix;
the section of any moment of the selective wave recording waveform comprises the following steps:
for a certain period of time t R ～t s Internal selective wave recording waveform at a certain time t 0 And acquires the recording data R (t 0 )，
R(t 0 )＝[x R (t 0 )u R (t 0 )y R (t 0 )]，
Wherein,
x R (t 0 )＝[x 1 (t 0 ),x 2 (t 0 ),x 3 (t 0 ),...] T
u R (t 0 )＝[u 1 (t 0 ),u 2 (t 0 ),u 3 (t 0 ),...] T
y R (t 0 )＝[y 1 (t 0 ),y 2 (t 0 ),y 3 (t 0 ),...] T
taking the model as an initial state of a reconstructed digital twin model of the multi-energy system;
the reconstructed digital twin model of the multi-energy system executes simulation calculation, and the solving of the state space equation comprises the following steps:
acquiring a reconstructed digital twin model of the multi-energy system at t 0 State quantity, input quantity, output quantity at time instant, at t 0 Starting an electromagnetic transient simulation program at a section at moment, wherein the simulation time is set as t s -t 0 Executing simulation calculation on the reconstructed digital twin model of the multi-energy system, and solving a state space equation of the reconstructed digital twin model of the multi-energy system;
the obtained simulation data matrix comprises the following steps:
based on the simulation result, a simulation data matrix S (t 0 ,t s ) Wherein the simulation result is t 0 Time t is a period of time 0 ～t s All state vectors x in s (t 0 ,t s ) Input vector u s (t 0 ,t s ) And output vector y s (t 0 ,t s ) Is a simulation waveform of (a) a simulation data matrix S (t 0 ,t s )＝[x s (t 0 ,t s )u s (t 0 ,t s )y s (t 0 ,t s )]Wherein, the method comprises the steps of, wherein,
Δt s to simulate step length, Δt s ＝Δt R ；
Checking the precision of the digital twin model by calculating the two norms of the difference matrix of the recording data matrix and the simulation data matrix;
the checking of the accuracy of the digital twin model by calculating the difference matrix two norms of the recording data matrix and the simulation data matrix comprises the following steps:
according to the recording data matrix R (t 0 ，t s ) And a simulation data matrix S (t 0 ,t s ) The accuracy of the reconstructed digital twin model of the multi-energy system is verified by calculating the distance between the wave recording data and the simulation data, and the calculation formula of the reconstructed model accuracy mu is as follows:
by comparing mu with a previously set precision threshold mu 0 To check whether the model accuracy meets the standard,
when mu is greater than or equal to mu 0 Outputting a conclusion that the mu value and the model precision reach standards;
when mu<μ 0 And outputting a conclusion that the mu value and the model precision are not up to standard.
As a preferable scheme of the digital twin model precision on-line verification method of the multi-energy system, the application comprises the following steps: the step of judging whether the model parameters change comprises the following steps:
model selection: describing a digital twin model of the multi-energy system by using a state space equation, and taking the digital twin model as the digital twin model of the multi-energy system to be verified;
event monitoring: each coefficient matrix A, B, C, D in the state space equation is stored in a database, the change condition of the coefficient matrix is monitored in real time, and the change of the data content is regarded as an event, so that the online verification of the model accuracy is triggered.
As a preferable scheme of the digital twin model precision on-line verification method of the multi-energy system, the application comprises the following steps: a first order differential equation set of the state space equation is as follows:
wherein x is a state vector, x= [ x ] 1 ,x 2 ,x 3 ,...] T U is the input vector, u= [ u ] 1 ,u 2 ,u 3 ,...] T Y outputs a vector, y= [ y ] 1 ,y 2 ,y 3 ,...] T Where each coefficient matrix A, B, C, D is determined by the element parameters of the system, each coefficient matrix A, B, C, D is constant if it is a linear time-invariant system, and each coefficient matrix A, B, C, D is a function of time if it is a linear time-variant system.
As a preferable scheme of the digital twin model precision on-line verification method of the multi-energy system, the application comprises the following steps: the reconstruction of the digital twin model of the multi-energy system comprises the following steps:
and if the online verification command of the digital twin model of the multi-energy system is triggered, acquiring each coefficient matrix of the triggering moment of the online verification command, and modifying the digital twin model of the multi-energy system.
As a preferable scheme of the digital twin model precision on-line verification method of the multi-energy system, the application comprises the following steps: the modifying the digital twin model of the multi-energy system further comprises: if the trigger time of the online verification command is t s The modified digital twin model of the multi-energy system is expressed as
Wherein A is s 、B s 、C s 、D s Is the coefficient matrix after the model parameter is changed.
As a preferable scheme of the digital twin model precision on-line verification method of the multi-energy system, the application comprises the following steps: the wave recording waveform matrix comprises the following steps:
acquiring wave recording waveform files of all state quantities, input quantities and output quantities of the multi-energy system, and at t s After the check command is triggered at the moment, t is imported s A certain time before the momentSection t R ～t s All state vectors x in R (t R ,t s ) Input vector y R (t R ,t s ) And output vector u R (t R ,t s ) To obtain recording waveform data matrix R (t R ,t s )，
R(t R ,t s )＝[x R (t R ,t s )u R (t R ,t s )y R (t R ,t s )]，
Wherein,
wherein Δt is R Is the recording sampling time interval.
The application has the beneficial effects that: the method ensures that the digital twin model can be always kept in a high-precision range, and achieves the purposes of judging the model precision and guiding the model correction.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a flow chart of steps of a method for verifying the accuracy of a digital twin model of a multi-energy system on line;
FIG. 2 is a waveform chart of a wave record of the method for checking the accuracy of a digital twin model of a multi-energy system on line;
FIG. 3 is a schematic view of a recording section selection of a method for checking the accuracy of a digital twin model of a multi-energy system on line according to the present application;
fig. 4 is a simulation waveform diagram of a digital twin model precision on-line verification method of a multi-energy system.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1, the embodiment provides a method for checking the accuracy of a digital twin model of a multi-energy system on line, which comprises a triggering method for checking the accuracy of the model and a method for checking the accuracy of the model on line, and can realize the real-time checking of the reconstructed digital twin model after the random change of system parameters based on an event triggering mechanism by monitoring the variation condition of a coefficient matrix in a database in real time.
The method refines the digital twin model precision verification method into 5 steps: under the premise of complete recording data, an electromagnetic transient simulation program is started at the section of the moment by selecting the initial state of the reconstructed digital twin model, a state space equation is solved to obtain a simulation data matrix, the difference two norms of the recording data matrix and the simulation data matrix are calculated to further carry out on-line verification on the precision of the model, and therefore the purpose of judging whether the precision of the model meets the standard in real time is achieved.
The method comprises the following steps:
judging whether the digital twin model parameters of the multi-energy system change, and selecting whether to perform online verification of model accuracy according to the model parameter change condition;
if the model parameters change, triggering on-line verification of the model precision, reconstructing a digital twin model of the multi-energy system, and importing all the wave recording waveforms of state quantity, input quantity and output quantity in a certain period of time before the triggering moment to obtain a wave recording data matrix;
selecting a section of any moment of a wave recording waveform as an initial state of a reconstructed digital twin model of the multi-energy system, starting an electromagnetic transient simulation program at the section of the moment, setting simulation time length, executing simulation calculation on the reconstructed digital twin model of the multi-energy system, solving a state space equation, and obtaining simulation waveforms of all state quantities, input quantities and output quantities in a certain time period after the moment to obtain a simulation data matrix;
and checking the precision of the digital twin model by calculating the two norms of the difference matrix of the recording data matrix and the simulation data matrix.
Wherein the method comprises a multi-energy system digital twin model precision verification triggering method and a multi-energy system digital twin model precision online verification method,
1. model precision verification triggering method
S1: model selection, namely describing digital twin of the multi-energy system by using a state space equation, taking the digital twin as a digital twin model of the multi-energy system to be verified, and considering that the multi-energy system is a continuous time system, wherein the state space equation of the continuous time system is represented by a first-order differential equation set of state variables;
s2: the method comprises the steps of event monitoring, namely, because of interaction between a digital twin model of a multi-energy system and an actual physical system, system parameters can be continuously changed, the system parameters can be regarded as a linear time-varying system, random change of the system parameters can cause corresponding change of a coefficient matrix, the coefficient matrix is stored in a database, the change condition of the coefficient matrix is monitored in real time, and the change of data content is regarded as an event, so that the online verification of model accuracy is started.
2. Model precision online verification method
And (3) model reconstruction: acquiring the moment of triggering a model precision online verification command, further acquiring the variation condition of a coefficient matrix at the moment, and correspondingly modifying a digital twin model of the multi-energy system;
importing recording data: acquiring all state quantity, input quantity and output quantity wave recording waveform files (COMTRADE format, including start and stop time) of the multi-energy system, and after a verification command is triggered, importing wave recording waveforms of all state vectors, input vectors and output vectors in a period of time before the moment;
selecting a wave recording section: selecting a section of a wave recording waveform at a certain moment in a period of time before the moment, obtaining wave recording data at the certain moment, and taking the wave recording data as an initial value of a state space equation of the modified digital twin model, namely an initial state of the reconstructed digital twin model of the multi-energy system;
and (3) solving simulation data: after the state quantity, input quantity and output quantity of the reconstructed digital twin model of the multi-energy system at a certain moment are obtained, an electromagnetic transient simulation program can be started at the section of the moment, simulation time length is set, simulation calculation is executed on the reconstructed digital twin model of the multi-energy system, a state space equation of the modified digital twin model is solved, and a simulation data matrix is obtained according to a simulation waveform diagram of a simulation result;
calculating a difference value two norms: the method comprises the steps of obtaining a recording data matrix and a simulation data matrix, calculating the distance between waveform data and simulation data to verify the accuracy of a reconstructed digital twin model of the multi-energy system, wherein the distance between the data can be represented by using the characteristics of vectors, and the common difference vector double norms, hausdorff distance and the like.
Example 2
Referring to fig. 1-3, the embodiment provides an online inspection method for digital twin model precision of a multi-energy system, which comprises the following steps,
and (one) model selection: describing a digital twin model of the multi-energy system by using a state space equation, and taking the digital twin model as the digital twin model of the multi-energy system to be verified, wherein the state space equation is a first-order differential equation set of state variables and is expressed as follows:
wherein x is a state vector, x= [ x ] 1 ,x 2 ,x 3 ,...] T U is the input vector, u= [ u ] 1 ,u 2 ,u 3 ,...] T Y outputs a vector, y= [ y ] 1 ,y 2 ,y 3 ,...] T Wherein each coefficient matrix A, B, C, D is determined by element parameters of the system, and each coefficient matrix A, B, C, D is constant if the system is a linear time-invariant system, and each coefficient matrix A, B, C, D is a time function if the system is a linear time-variant system;
(II) event monitoring: each coefficient matrix A, B, C, D in the state space equation is stored in a database, the change condition of the coefficient matrix is monitored in real time, and the change of the data content is regarded as an event, so that the online verification of the model accuracy is triggered.
And (III) model reconstruction: if the online verification command of the digital twin model of the multi-energy system is triggered, acquiring each coefficient matrix of the triggering moment of the online verification command, modifying the digital twin model of the multi-energy system, and if the triggering moment of the online verification command is t s The modified digital twin model of the multi-energy system is expressed as
Wherein A is s 、B s 、C s 、D s Is the coefficient matrix after the model parameter is changed.
And (IV) importing recording data: the digital twin model of the multi-energy system is constructed by a large number of measuring devices to completely measure, transmit and store the state quantity, input quantity and output quantity of the multi-energy system, so that the wave recording waveform file of all the state quantity, input quantity and output quantity of the multi-energy system can be obtained at t s After the check command is triggered at the moment, t is imported s A certain period of time t before the moment R ～t s All state vectors x in R (t R ,t s ) Input vector y R (t R ,t s ) And output vector u R (t R ,t s ) As shown in FIG. 2, to obtain a recording data matrix R (t R ,t s )，
R(t R ,t s )＝[x R (t R ,t s ) u R (t R ,t s ) y R (t R ,t s )]，
Wherein,
wherein Δt is R Is the recording sampling time interval.
And (V) selecting a recording section: for a certain period of time t R ～t s Internal selective wave recording waveform at a certain time t 0 As shown in FIG. 3, and acquires the recording data R (t 0 )，
R(t 0 )＝[x R (t 0 ) u R (t 0 ) y R (t 0 )]，
Wherein,
x R (t 0 )＝[x 1 (t 0 ),x 2 (t 0 ),x 3 (t 0 ),...] T
u R (t 0 )＝[u 1 (t 0 ),u 2 (t 0 ),u 3 (t 0 ),...] T
y R (t 0 )＝[y 1 (t 0 ),y 2 (t 0 ),y 3 (t 0 ),...] T
and taking the model as an initial state of the reconstructed digital twin model of the multi-energy system.
And (six) solving simulation data: acquiring a reconstructed digital twin model of the multi-energy system at t 0 State quantity, input quantity, output quantity at time instant, at t 0 Starting an electromagnetic transient simulation program at a section at moment, wherein the simulation time is set as t s -t 0 Executing simulation calculation on the reconstructed digital twin model of the multi-energy system, solving a state space equation of the reconstructed digital twin model of the multi-energy system, and obtaining a simulation data matrix S (t 0 ,t s ) Wherein the simulation result is t 0 Time t is a period of time 0 ～t s All state vectors x in s (t 0 ,t s ) Input vector u s (t 0 ,t s ) And output vector y s (t 0 ,t s ) As shown in fig. 4, the simulation data matrix S (t 0 ,t s )＝[x s (t 0 ,t s )u s (t 0 ,t s )y s (t 0 ,t s )]Wherein, the method comprises the steps of, wherein,
Δt s to simulate step length, Δt s ＝Δt R 。
(seventh) difference two-norm calculation: according to the recording data matrix R (t 0 ，t s ) And a simulation data matrix S (t 0 ,t s ) Calculating the distance between the wave recording data and the simulation data to verify the accuracy of the reconstructed digital twin model of the multi-energy system, wherein the two norms of a real matrix A are the square root value of the maximum characteristic root of the product of the transposed matrix of A and the matrix A,
wherein eig (X) represents the eigenvalue function of matrix X, returning vector [ lambda ] 1 、λ 2 、λ 3 、...、λ n-1 、λ n ] T 。
The calculation formula of the reconstructed model precision mu is as follows:
by comparing mu with a previously set precision threshold mu 0 To check whether the model accuracy meets the standard,
when mu is greater than or equal to mu 0 Outputting a conclusion that the mu value and the model precision reach standards;
when mu<μ 0 And outputting a conclusion that the mu value and the model precision are not up to standard.
It should be appreciated that embodiments of the application may be implemented or realized by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer readable storage medium configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, in accordance with the methods and drawings described in the specific embodiments. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes (or variations and/or combinations thereof) described herein may be performed under control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications), by hardware, or combinations thereof, collectively executing on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable computing platform, including, but not limited to, a personal computer, mini-computer, mainframe, workstation, network or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and so forth. Aspects of the application may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optical read and/or write storage medium, RAM, ROM, etc., such that it is readable by a programmable computer, which when read by a computer, is operable to configure and operate the computer to perform the processes described herein. Further, the machine readable code, or portions thereof, may be transmitted over a wired or wireless network. When such media includes instructions or programs that, in conjunction with a microprocessor or other data processor, implement the steps described above, the application described herein includes these and other different types of non-transitory computer-readable storage media. The application also includes the computer itself when programmed according to the methods and techniques of the present application. The computer program can be applied to the input data to perform the functions described herein, thereby converting the input data to generate output data that is stored to the non-volatile memory. The output information may also be applied to one or more output devices such as a display. In a preferred embodiment of the application, the transformed data represents physical and tangible objects, including specific visual depictions of physical and tangible objects produced on a display.
As used in this disclosure, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, the components may be, but are not limited to: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers. Furthermore, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered in the scope of the claims of the present application.
Claims (6)
1. A digital twin model precision on-line verification method of a multi-energy system is characterized in that: the online verification method comprises the following steps:
judging whether the digital twin model parameters of the multi-energy system change, and selecting whether to perform online verification of model accuracy according to the model parameter change condition;
if the model parameters change, triggering on-line verification of the model precision, reconstructing a digital twin model of the multi-energy system, and importing all the wave recording waveforms of state quantity, input quantity and output quantity in a certain period of time before the triggering moment to obtain a wave recording data matrix;
selecting a section of any moment of a wave recording waveform as an initial state of a reconstructed digital twin model of the multi-energy system, starting an electromagnetic transient simulation program at the section of the moment, setting simulation time length, executing simulation calculation on the reconstructed digital twin model of the multi-energy system, solving a state space equation, and obtaining simulation waveforms of all state quantities, input quantities and output quantities in a certain time period after the moment to obtain a simulation data matrix;
the section of any moment of the selective wave recording waveform comprises the following steps:
for a certain period of time t R ～t s Internal selective wave recording waveform at a certain time t 0 And acquires the recording data R (t 0 )，
R(t 0 )＝[x R (t 0 ) u R (t 0 ) y R (t 0 )]，
Wherein,
x R (t 0 )＝[x 1 (t 0 ),x 2 (t 0 ),x 3 (t 0 ),...] T
u R (t 0 )＝[u 1 (t 0 ),u 2 (t 0 ),u 3 (t 0 ),...] T
y R (t 0 )＝[y 1 (t 0 ),y 2 (t 0 ),y 3 (t 0 ),...] T
taking the model as an initial state of a reconstructed digital twin model of the multi-energy system;
the reconstructed digital twin model of the multi-energy system executes simulation calculation, and the solving of the state space equation comprises the following steps:
acquiring a reconstructed digital twin model of the multi-energy system at t 0 State quantity, input quantity, output quantity at time instant, at t 0 Starting an electromagnetic transient simulation program at a section at moment, wherein the simulation time is set as t s -t 0 Executing simulation calculation on the reconstructed digital twin model of the multi-energy system, and solving a state space equation of the reconstructed digital twin model of the multi-energy system;
the obtained simulation data matrix comprises the following steps:
based on the simulation result, a simulation data matrix S (t 0 ,t s ) Wherein the simulation result is t 0 Time t is a period of time 0 ～t s All state vectors x in s (t 0 ,t s ) Input vector u s (t 0 ,t s ) And output vector y s (t 0 ,t s ) Is a simulation waveform of (a) a simulation data matrix S (t 0 ,t s )＝[x s (t 0 ,t s )u s (t 0 ,t s )y s (t 0 ,t s )]Wherein, the method comprises the steps of, wherein,
Δt s to simulate step length, Δt s ＝Δt R ；
Checking the precision of the digital twin model by calculating the two norms of the difference matrix of the recording data matrix and the simulation data matrix;
the checking of the accuracy of the digital twin model by calculating the difference matrix two norms of the recording data matrix and the simulation data matrix comprises the following steps:
according to the recording data matrix R (t 0 ，t s ) And a simulation data matrix S (t 0 ,t s ) The accuracy of the reconstructed digital twin model of the multi-energy system is verified by calculating the distance between the wave recording data and the simulation data, and the calculation formula of the reconstructed model accuracy mu is as follows:
by comparing mu with a previously set precision threshold mu 0 To check whether the model accuracy meets the standard,
when mu is greater than or equal to mu 0 Outputting a conclusion that the mu value and the model precision reach standards;
when mu<μ 0 And outputting a conclusion that the mu value and the model precision are not up to standard.
2. The online verification method for digital twin model precision of a multi-energy system according to claim 1, which is characterized in that: determining whether the model parameters change includes the steps of:
model selection: describing a digital twin model of the multi-energy system by using a state space equation, and taking the digital twin model as the digital twin model of the multi-energy system to be verified;
event monitoring: each coefficient matrix A, B, C, D in the state space equation is stored in a database, the change condition of the coefficient matrix is monitored in real time, and the change of the data content is regarded as an event, so that the online verification of the model accuracy is triggered.
3. The online verification method for digital twin model precision of a multi-energy system according to claim 2, which is characterized in that: a first order differential equation set of the state space equation is as follows:
wherein x is a state vector, x= [ x ] 1 ,x 2 ,x 3 ,...] T U is the input vector, u= [ u ] 1 ,u 2 ,u 3 ,...] T Y outputs a vector, y= [ y ] 1 ,y 2 ,y 3 ,...] T Where each coefficient matrix A, B, C, D is determined by the element parameters of the system, each coefficient matrix A, B, C, D is constant if it is a linear time-invariant system, and each coefficient matrix A, B, C, D is a function of time if it is a linear time-variant system.
4. The online verification method for digital twin model precision of multi-energy system according to claim 3, wherein the method comprises the following steps: the reconstruction of the digital twin model of the multi-energy system comprises the following steps:
and if the online verification command of the digital twin model of the multi-energy system is triggered, acquiring each coefficient matrix of the triggering moment of the online verification command, and modifying the digital twin model of the multi-energy system.
5. The online verification method for digital twin model precision of a multi-energy system according to claim 4, which is characterized in that: the modifying the digital twin model of the multi-energy system further comprises: if the trigger time of the online verification command is t s The modified digital twin model of the multi-energy system is expressed as
Wherein A is s 、B s 、C s 、D s Is the coefficient matrix after the model parameter is changed.
6. The online verification method for digital twin model precision of a multi-energy system according to claim 5, wherein the method comprises the following steps: the method for obtaining the wave-recording waveform matrix comprises the following steps:
acquiring wave recording waveform files of all state quantities, input quantities and output quantities of the multi-energy system, and at t s After the check command is triggered at the moment, t is imported s A certain period of time t before the moment R ～t s All state vectors x in R (t R ,t s ) Input vector y R (t R ,t s ) And output vector u R (t R ,t s ) To obtain recording waveform data matrix R (t R ,t s )，
R(t R ,t s )＝[x R (t R ,t s ) u R (t R ,t s ) y R (t R ,t s )]，
Wherein,
wherein Δt is R Is the recording sampling time interval.
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