Dynamic response simulation method and device of thermal power generating unit network-related model

Abstract

The invention provides a dynamic response simulation method and device for a thermal power generating unit network-related model, and the method comprises the steps: obtaining a target thermal power generating unit parameter and a network-related parameter, and collecting the operation data of a corresponding sub-model in an operation process according to the thermal power generating unit parameter and the network-related parameter; generating model construction data through feature extraction according to the operation data, and reconstructing a subsystem model through the model construction data according to the influence condition of each subsystem on network-related parameters; utilizing a forward and reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining a forward model and a reverse model; and substituting the hybrid parallel simulation model into an excitation type simulation system for simulation processing to obtain a simulation result.

Description

Technical Field

[0001] The present application relates to the field of power generation units, and in particular to a method and device for simulating the dynamic response of a grid-related model of a thermal power unit. Background Art

[0002] The simulation of the grid-related model of thermal power units is a complex and critical process, which involves the dynamic interaction between the power system and the thermal power units, as well as the response characteristics of the thermal power units under various operating conditions in the power grid. This simulation is of great significance for the planning, design, operation, control and optimization of the power system. In the simulation software, it is necessary to set the simulation parameters and initial conditions according to actual needs, such as unit output, load demand, grid structure, etc.; then, run the simulation model to observe the response characteristics of the thermal power units under different conditions, such as power output, frequency fluctuation, voltage stability, etc., and analyze the operating performance of the thermal power units and the stability of the power grid based on the simulation results; if problems are found, it is necessary to adjust the control strategy of the unit or the power grid, optimize the model parameters, and then re-simulate and verify. The simulation of the grid-related model of thermal power units is a complex but crucial process, which helps to deeply understand the interaction between thermal power units and the power grid, and provide strong support for the planning, design, operation, control and optimization of the power system.

[0003] Existing power system simulation technology focuses more on the grid side, because the grid-side system equipment is more suitable for simulation through mathematical methods. Since the physical process of the thermal system of thermal power units is too complex, nonlinear and highly coupled, its response process is usually simplified in the simulation. However, the simulation accuracy of the thermal power unit model is important for the simulation and analysis of the electromechanical transient and medium- and long-term dynamic stability of the power system, especially for the early warning and analysis of cascading failures in the power system. Summary of the invention

[0004] The purpose of this application is to provide a method and device for simulating the dynamic response of a grid-related model of a thermal power unit, so as to solve the defects existing in the existing power system simulation and effectively improve the simulation accuracy.

[0005] To achieve the above-mentioned purpose, the dynamic response simulation method of the grid-related model of a thermal power unit provided in the present application specifically includes: obtaining target thermal power unit parameters and grid-related parameters, and collecting operating data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters; generating model construction data through feature extraction according to the operating data, and reconstructing the subsystem model through the model construction data according to the influence of each subsystem on the grid-related parameters; using the forward and reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining a forward model and a reverse model; and bringing the hybrid parallel simulation model into an incentive simulation system for simulation processing to obtain simulation results.

[0006] In the above-mentioned dynamic response simulation method of the grid-related model of a thermal power unit, optionally, generating model construction data through feature extraction according to the operating data also includes: generating feature information through data cleaning and dimensionality reduction processing according to the operating data, and analyzing the feature information through a cluster analysis algorithm to obtain generated model construction data.

[0007] In the above-mentioned dynamic response simulation method of the grid-related model of a thermal power unit, optionally, the data cleaning includes missing value filling processing and outlier detection and removal processing; the dimensionality reduction processing includes principal component analysis processing and t-SNE processing.

[0008] In the above-mentioned dynamic response simulation method of the grid-related model of the thermal power unit, optionally, reconstructing the subsystem model through the model construction data according to the influence of each subsystem on the grid-related parameters includes: performing data screening and feature extraction on the model construction data to obtain influence data according to the influence of each subsystem on the grid-related parameters; and reconstructing the subsystem model according to the influence data.

[0009] In the above-mentioned dynamic response simulation method of the grid-related model of the thermal power unit, optionally, using the forward-reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining the forward model and the reverse model includes: using the forward-reverse hybrid simulation algorithm and the subsystem model to construct an evolution sub-model and an inverse sub-model in a manner of synchronous simulation of the power supply side and the grid side of the power generation process; obtaining a hybrid parallel simulation model combining the forward model and the reverse model according to the evolution sub-model and the reverse sub-model; wherein the reverse model uses the reverse algorithm to perform feedback correction on the simulation results of the forward model.

[0010] The present application also provides a dynamic response simulation device for a grid-related model of a thermal power unit, the device comprising: an acquisition module, a reconstruction module, a correction module and a simulation module; the acquisition module is used to obtain target thermal power unit parameters and grid-related parameters, and collect operating data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters; the reconstruction module is used to generate model construction data through feature extraction according to the operating data, and reconstruct the subsystem model through the model construction data according to the influence of each subsystem on the grid-related parameters; the correction module is used to use a forward and reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining a forward model and a reverse model; the simulation module is used to bring the hybrid parallel simulation model into an incentive simulation system for simulation processing to obtain simulation results.

[0011] In the above-mentioned dynamic response simulation device of the grid-related model of a thermal power unit, optionally, the reconstruction module includes a preprocessing unit and a reconstruction unit; the preprocessing unit is used to perform data screening and feature extraction on the model construction data to obtain influence data according to the influence of each subsystem on the grid-related parameters; the reconstruction unit is used to reconstruct the subsystem model according to the influence data.

[0012] In the above-mentioned dynamic response simulation device of the grid-related model of the thermal power unit, optionally, the correction module includes a construction unit and a correction unit; the construction unit is used to construct an evolution sub-model and an inverse sub-model by using a forward and reverse hybrid simulation algorithm and the subsystem model in a manner of synchronous simulation of the power supply side and the grid side of the power generation process; the correction unit is used to obtain a hybrid parallel simulation model combining a forward model and a reverse model according to the evolution sub-model and the reverse sub-model; wherein the reverse model uses a reverse algorithm to perform feedback correction on the simulation results of the forward model.

[0013] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0014] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above method.

[0015] The present application also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0016] The beneficial technical effect of the present application is that it can effectively improve the accuracy and application scope of power system stability simulation, especially plays an important role in the early warning and analysis of cascading failures in the power system, has high management benefits for the power grid, and reduces the risk of major accidents in the power grid through simulation analysis, which has high social benefits. At the same time, the model built by the invention is closer to the actual unit. The use of this model to evaluate and optimize the grid-related performance of the speed control system of the thermal power unit can expand the business scope and has high economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute a limitation of the present application. In the drawings:

[0018] Figure 1 A schematic flow chart of a method for simulating the dynamic response of a grid-related model of a thermal power unit provided in one embodiment of the present application;

[0019] Figure 2 A schematic diagram provided for an embodiment of the present application;

[0020] Figure 3 A schematic diagram provided for an embodiment of the present application;

[0021] Figure 4 A schematic diagram of the structure of a dynamic response simulation device for a thermal power unit grid-related model provided in one embodiment of the present application;

[0022] Figure 5 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will describe the implementation methods of the present application in detail in conjunction with the accompanying drawings and embodiments, so that the implementation process of how the present application applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments in the present application and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present application.

[0024] In addition, the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be performed in an order different from that shown here.

[0025] Please refer to Figure 1 As shown, in one embodiment of the present application, a dynamic response simulation method of a thermal power unit grid-related model is provided, which specifically includes:

[0026] S101 obtains target thermal power unit parameters and grid-related parameters, and collects operation data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters;

[0027] S102 generates model building data by feature extraction according to the operation data, and reconstructs the subsystem model by using the model building data according to the influence of each subsystem on the network-related parameters;

[0028] S103 constructs a hybrid parallel simulation model combining a forward model and a reverse model by using a forward-reverse hybrid simulation algorithm and the subsystem model;

[0029] S104 brings the hybrid parallel simulation model into an incentive simulation system for simulation processing to obtain simulation results.

[0030] Specifically, in actual work, the above process can be divided into three parts: target unit definition and data preprocessing, key subsystem model reconstruction and optimization, and forward and reverse hybrid parallel simulation strategy implementation; at the same time, on this basis, it can also include model verification and other links. The specific implementation methods will be explained one by one in the subsequent embodiments, and will not be described in detail here.

[0031] In one embodiment of the present application, generating model building data through feature extraction according to the operating data further includes: generating feature information through data cleaning and dimensionality reduction processing according to the operating data, and analyzing the feature information through a cluster analysis algorithm to obtain generated model building data. Wherein, the data cleaning includes missing value filling processing and outlier detection and elimination processing; the dimensionality reduction processing includes principal component analysis processing and t-SNE processing.

[0032] Specifically, in actual work, the above embodiment mainly executes the target unit definition and data preprocessing steps. In this process, the target thermal power unit and its key grid-related parameters need to be clarified, and then the detailed data of the sub-model operation process closely related to these parameters are comprehensively collected (through the analysis of the operation mechanism of the unit, the subsystems that affect the grid-related parameters are found. For example, the subsystems that can temporarily improve the working capacity parameters of the turbine include the extraction system, the condensate system model, the circulating water system, etc.). Through the preprocessing and dimensionality reduction technology of the data, the data scale is effectively reduced while retaining the key information. The clustering analysis algorithm is further used to deeply explore the intrinsic structure of the data and accurately extract the data features, so as to provide a data basis for the subsequent construction of a high-precision simulation model. The data preprocessing includes missing value filling, outlier detection and elimination, and the dimensionality reduction technology includes principal component analysis and t-SNE.

[0033] Please refer to Figure 2 As shown, in one embodiment of the present application, constructing data through the model to reconstruct the subsystem model according to the influence of each subsystem on the network-related parameters includes:

[0034] S201 performs data screening and feature extraction on the model building data to obtain impact data according to the impact of each subsystem on the network-related parameters;

[0035] S202 reconstructs a subsystem model according to the impact data.

[0036] Specifically, in actual work, the above embodiment mainly executes the key subsystem model reconstruction and optimization steps. In this process, for the key subsystems closely related to the network-related parameters, the historical data is thoroughly preprocessed, including data cleaning, refined screening and feature extraction. By combing the operating mechanism of the unit and combining the data correlation analysis between the operating parameters, the modeling scope and objectives are defined, and the subsystem model is reconstructed to ensure that the model can accurately reflect the actual operating characteristics and improve the accuracy and credibility of the simulation results.

[0037] Please refer to Figure 3 As shown, in one embodiment of the present application, using the forward-reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining a forward model and a reverse model includes:

[0038] S301 constructs an evolution sub-model and an inverse sub-model by using a forward and reverse hybrid simulation algorithm and the subsystem model in a synchronous simulation mode of the power supply side and the grid side of the power generation process;

[0039] S302 obtains a hybrid parallel simulation model combining a forward model and a reverse model according to the evolution sub-model and the reverse sub-model; wherein the reverse model uses a reverse algorithm to perform feedback correction on the simulation result of the forward model.

[0040] Specifically, in actual work, the above-mentioned embodiment mainly executes the implementation steps of the forward and reverse hybrid parallel simulation strategy. In this process, the synchronous simulation technology of the power supply side and the grid side of the power generation process can be implemented with reference to the existing technology, and the present application does not make further limitations on this. In order to cope with the simulation challenges under complex working conditions such as successive grid failures, a hybrid parallel simulation system combining forward and reverse models is established. The system uses a reverse algorithm to perform online and real-time feedback correction on the forward simulation results, which effectively improves the response speed and accuracy of the model in a dynamically changing environment. The implementation of this strategy provides strong technical support for the stable operation of the power grid and rapid response to faults.

[0041] In view of the significant differences in time scale, scope and objectives between transient simulation of thermal power units on the power supply side and grid side, the traditional single evaluation index can no longer meet the comprehensive evaluation needs of hybrid simulation. Therefore, a comprehensive evaluation system is constructed, which integrates multi-dimensional and multi-level evaluation indicators, can comprehensively reflect the performance and advantages and disadvantages of the simulation model, provide strong guidance for the continuous optimization of the model, and help improve the simulation accuracy of the model from the perspective of feedback. At this stage, in-depth model disturbance response tests are carried out for single grid transient faults (such as steady-state error and dynamic error, using the error measurement of data points, comprehensive evaluation, and considering more indicators on the basis of a single evaluation indicator, such as calculation efficiency, synchronization of calculations, etc.), and the accuracy and reliability of the model are verified by simulating the system state changes before and after the fault occurs. At the same time, based on the mechanism analysis of a single fault, a combination of successive faults is further designed to simulate the fault disturbance response of different types of generator sets. This process not only deepens the understanding of the interaction mechanism between generator sets and grids, but also provides a reference for fault prevention and emergency response of grids.

[0042] Please refer to Figure 4As shown, the present application also provides a dynamic response simulation device for a grid-related model of a thermal power unit, the device comprising: an acquisition module, a reconstruction module, a correction module and a simulation module; the acquisition module is used to obtain target thermal power unit parameters and grid-related parameters, and collect operating data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters; the reconstruction module is used to generate model construction data through feature extraction according to the operating data, and reconstruct the subsystem model through the model construction data according to the influence of each subsystem on the grid-related parameters; the correction module is used to use the forward and reverse hybrid simulation algorithm and the subsystem model to construct a hybrid parallel simulation model combining a forward model and a reverse model; the simulation module is used to bring the hybrid parallel simulation model into an incentive simulation system for simulation processing to obtain simulation results.

[0043] In the above embodiment, the reconstruction module includes a preprocessing unit and a reconstruction unit; the preprocessing unit is used to perform data screening and feature extraction on the model construction data according to the influence of each subsystem on the network-related parameters to obtain influence data; the reconstruction unit is used to reconstruct the subsystem model according to the influence data. The correction module includes a construction unit and a correction unit; the construction unit is used to construct an evolution submodel and an inverse submodel using a forward and reverse hybrid simulation algorithm and the subsystem model in a synchronous simulation mode of the power supply side and the grid side of the power generation process; the correction unit is used to obtain a hybrid parallel simulation model combining a forward model and a reverse model according to the evolution submodel and the reverse submodel; wherein the reverse model uses a reverse algorithm to perform feedback correction on the simulation results of the forward model.

[0044] In view of the fact that the process implemented by the above-mentioned dynamic response simulation device of the grid-related model of a thermal power unit is similar to the dynamic response simulation method of the grid-related model of a thermal power unit, its specific implementation principle and method will not be described in detail here.

[0045] The beneficial technical effect of the present application is that it can effectively improve the accuracy and application scope of power system stability simulation, especially plays an important role in the early warning and analysis of cascading failures in the power system, has high management benefits for the power grid, and reduces the risk of major accidents in the power grid through simulation analysis, which has high social benefits. At the same time, the model built by the invention is closer to the actual unit. The use of this model to evaluate and optimize the grid-related performance of the speed control system of the thermal power unit can expand the business scope and has high economic benefits.

[0046] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0047] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above method.

[0048] The present application also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0049] like Figure 5 As shown, the electronic device 600 may further include: a communication module 110, an input unit 120, an audio processing unit 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily have to include Figure 5 In addition, the electronic device 600 may also include Figure 5 For components not shown, reference may be made to the prior art.

[0050] like Figure 5 As shown, the central processor 100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processor 100 receives inputs and controls the operations of various components of the electronic device 600.

[0051] The memory 140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 100 may execute the program stored in the memory 140 to implement information storage or processing.

[0052] The input unit 120 provides input to the CPU 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0053] The memory 140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 140 may also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 600 through the central processor 100.

[0054] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0055] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processor 100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0056] Based on different communication technologies, multiple communication modules 110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide an audio output via the speaker 131 and receive an audio input from the microphone 132, thereby realizing a common telecommunication function. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 130 is also coupled to the central processor 100, so that the sound can be recorded on the local machine through the microphone 132, and the sound stored on the local machine can be played through the speaker 131.

[0057] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0058] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for simulating the dynamic response of a thermal power unit grid-related model, characterized in that: The method comprises: Obtaining target thermal power unit parameters and grid-related parameters, and collecting operating data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters; Generate model building data through feature extraction according to the operation data, and reconstruct the subsystem model through the model building data according to the influence of each subsystem on the network-related parameters; A hybrid parallel simulation model combining a forward model and a reverse model is constructed by using a forward-reverse hybrid simulation algorithm and the subsystem model; The hybrid parallel simulation model is brought into an incentive simulation system for simulation processing to obtain simulation results.

2. The method for simulating the dynamic response of a thermal power unit grid-related model according to claim 1, characterized in that: Generating model construction data by feature extraction according to the operation data also includes: Characteristic information is generated according to the operating data through data cleaning and dimensionality reduction processing, and the characteristic information is analyzed through a cluster analysis algorithm to obtain generation model construction data.

3. The dynamic response simulation method of the grid-related model of a thermal power unit according to claim 2 is characterized in that: The data cleaning includes missing value filling processing and outlier detection and elimination processing; the dimensionality reduction processing includes principal component analysis processing and t-SNE processing.

4. The method for simulating the dynamic response of a thermal power unit grid-related model according to claim 1, characterized in that: According to the influence of each subsystem on the network-related parameters, the subsystem model is constructed by building data through the model, including: According to the influence of each subsystem on the network-related parameters, the model construction data is screened and features are extracted to obtain the influence data; The subsystem model is reconstructed according to the impact data.

5. The method for simulating the dynamic response of a thermal power unit grid-related model according to claim 1, characterized in that: The hybrid parallel simulation model combining the forward model and the reverse model is constructed by using the forward and reverse hybrid simulation algorithm and the subsystem model, including: The evolution sub-model and the inverse sub-model are constructed by using a forward and reverse hybrid simulation algorithm and the subsystem model in a synchronous simulation mode of the power supply side and the grid side of the power generation process; Obtaining a hybrid parallel simulation model combining a forward model and a reverse model according to the evolution sub-model and the reverse sub-model; The reverse model uses a reverse algorithm to perform feedback correction on the simulation results of the forward model.

6. A dynamic response simulation device for a thermal power unit grid-related model, characterized in that: The device comprises: an acquisition module, a reconstruction module, a correction module and a simulation module; The acquisition module is used to obtain the target thermal power unit parameters and grid-related parameters, and to collect the operation data of the corresponding sub-model during operation according to the thermal power unit parameters and grid-related parameters; The reconstruction module is used to generate model construction data through feature extraction according to the operation data, and reconstruct the subsystem model through the model construction data according to the influence of each subsystem on the network-related parameters; The correction module is used to construct a hybrid parallel simulation model combining a forward model and a reverse model by using a forward and reverse hybrid simulation algorithm and the subsystem model; The simulation module is used to bring the hybrid parallel simulation model into the incentive simulation system for simulation processing to obtain simulation results.

7. The dynamic response simulation device of the grid-related model of a thermal power unit according to claim 6, characterized in that: The reconstruction module comprises a preprocessing unit and a reconstruction unit; The preprocessing unit is used to perform data screening and feature extraction on the model building data to obtain impact data according to the impact of each subsystem on the network-related parameters; The reconstruction unit is used to reconstruct the subsystem model according to the impact data.

8. The dynamic response simulation device of the grid-related model of a thermal power unit according to claim 6, characterized in that: The correction module comprises a construction unit and a correction unit; The construction unit is used to construct an evolution sub-model and an inverse sub-model by using a forward and reverse hybrid simulation algorithm and the subsystem model in a synchronous simulation mode of the power supply side and the grid side of the power generation process; The correction unit is used to obtain a hybrid parallel simulation model combining a forward model and a reverse model according to the evolution sub-model and the reverse sub-model; wherein the reverse model uses a reverse algorithm to perform feedback correction on the simulation result of the forward model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for causing a computer to execute the method according to any one of claims 1 to 5.

11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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