Oscillation stability analysis method and system of photo-thermal generator set grid-connected system

Abstract

The invention discloses an oscillation stability analysis method and system for a photo-thermal generator set grid-connected system, and the method comprises the steps: constructing a small signal model of the photo-thermal generator set grid-connected system, the small-signal model of the photo-thermal generator set grid-connected system comprises a light condensation and heat collection subsystem small-signal model, an excitation subsystem small-signal model, a synchronous machine subsystem small-signal model and a steam turbine speed regulator subsystem small-signal model. Calculating a characteristic value of a grid-connected system state matrix according to the small signal model of the photo-thermal generator set grid-connected system, and calculating an oscillation mode and a damping rate of the grid-connected system based on the characteristic value of the grid-connected system state matrix; calculating a left feature vector and a right feature vector of the state matrix to obtain a participation factor; and according to the participation factors, evaluating the influence degree of different parameters in the system on the oscillation mode, and obtaining potential factors influencing the oscillation mode of the system. And guidance is provided for system oscillation control and stability improvement.

Description

Technical Field

[0001] This invention relates to the field of stability analysis of new energy grid-connected systems, and specifically to a method and system for analyzing the oscillation stability of a solar thermal power generator grid-connected system. Background Technology

[0002] Among all new energy power generation methods, concentrated solar power (CSP) can reliably provide inertia support and spinning reserve services for the power system. Its internal thermal storage system enables continuous and stable power generation throughout the day, with rapid start-up and shutdown capabilities, exhibiting excellent peak-shaving performance. However, its large land area requirement makes it suitable for large-scale development in desert and Gobi regions. Currently, CSP demonstration projects have been built in Delingha, Qinghai, and Dunhuang, Gansu, among other places.

[0003] However, compared to traditional large-capacity thermal power units, concentrated solar power (CSP) units have smaller unit capacities and lower moments of inertia, and are often located in arid regions at the end of the power grid, making their grid-connected systems more prone to oscillations and instability. The mechanism lies in the fact that system disturbances cause larger fluctuations in speed and power angle. This forms a negative feedback loop through the unit's own excitation system, and the interaction between the collection lines and new energy units significantly amplifies electromagnetic power disturbances, thus triggering low-frequency oscillations. Existing modeling methods use the original motor parameters when constructing the CSP unit's power generation system. However, it is generally difficult to accurately obtain these original parameter values ​​through analysis or calculation, making it difficult to obtain an accurate model of the unit. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for analyzing the oscillation stability of a solar thermal power generator grid-connected system, so as to solve the above-mentioned problems.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for analyzing the oscillation stability of a solar thermal power generator grid-connected system, comprising: A small-signal model of a solar thermal power generator grid-connected system is constructed, which includes: a small-signal model of a concentrating solar collector subsystem, a small-signal model of an excitation subsystem, a small-signal model of a synchronizing machine subsystem, and a small-signal model of a turbine governor subsystem. Based on the small-signal model of the solar thermal power generator grid-connected system, the eigenvalues ​​of the grid-connected system state matrix are calculated, and the oscillation mode and damping rate of the grid-connected system are calculated based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor is obtained by calculating the left and right eigenvectors of the state matrix; Based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode, the potential factors affecting the system's oscillation mode are obtained.

[0006] Furthermore, the small-signal model for constructing the solar thermal power generator grid-connected system includes: Based on the dynamic models of each subsystem, the corresponding small-signal models are obtained by linearization at the stable operating point. Based on the small-signal models of each subsystem, the overall small-signal model of the system is further obtained.

[0007] Furthermore, the specific construction is as follows: A dynamic model of the concentrated solar thermal collection subsystem was constructed, and its small-signal model was obtained through linearization. A dynamic model of the excitation subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the synchronous generator subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the turbine governor subsystem is constructed, and its small-signal model is obtained through linearization.

[0008] Furthermore, the specific expression is as follows:

[0009] In the formula, The subscripts fp and fm represent the physical quantities of the conduit and working fluid at the front end of the receiver, respectively; the subscripts tp and tm represent the physical quantities of the conduit and working fluid at the end of the receiver, respectively; the subscripts cm and hm represent the physical quantities of the working fluid in the cold tank and the hot tank, respectively; and the subscript m represents the physical quantity of the working fluid flowing per unit time. T For temperature; m c is the mass; c is the specific heat capacity. U The convective heat transfer coefficient between the duct and the heat transfer medium; S This refers to the contact area between the conduit and the heat transfer medium. Q l The energy change of the receiver due to the flow of the heat transfer medium; T 4 represents the temperature of the working fluid flowing into the cold tank; T 5 represents the temperature of the working fluid flowing out of the cold tank; T 2 represents the temperature of the working fluid flowing into the hot tank; T 3 represents the temperature of the working fluid flowing out of the hot tank; R l Heat loss through the conduit is expressed as a percentage. V T , V f , V F These are the voltage regulator output voltage, generator excitation voltage, and excitation negative feedback voltage, respectively. V t This refers to the generator terminal voltage;K A , T A These are the amplification factor and time constant of the inertial amplification stage of the voltage regulator, respectively. K E , T E , S E These are the amplification factor, time constant, and saturation coefficient of the exciter's inertial element, respectively. K F , T F These are the amplification factor and time constant of the excitation negative feedback loop, respectively. e ' d , e '' d , e ' q and e '' q express d , q Transient and subtransient potentials on the axis; X d and X q They are respectively d , q Synchronous reactance on the shaft; d , q The transient reactance on the axis is expressed as X ' d and X ' q The subtransient reactance is expressed as X '' d and X '' q ; T ' d0 and T ' q0 yes d , q The open-circuit transient time constant of the shaft. T '' d0 and T '' q0 This is the open-circuit subtransient time constant; i d andi q They represent d shaft and q Current on the shaft; E fq This represents the stator voltage of a synchronous motor under steady-state no-load conditions, and its magnitude is related to the excitation voltage. u f Proportional; δ The power angle represents the synchronous motor. ω This indicates the actual speed of the synchronous motor. ω 0 represents synchronous speed. M Indicates the rotor inertia coefficient. P m Represents mechanical power. P e Represents electromagnetic power; H p This refers to the steam pressure in the first stage of the high-pressure cylinder. T 4 represents the time constant of the high-pressure cylinder in the first time step. T sm The time constant of the speed controller, K p The speed controller amplification factor. P ref This is a reference value for generator power. R p This is the generator droop coefficient. ω ref This is a reference value for rotational speed. μ This refers to the steam valve opening of the steam turbine.

[0010] Furthermore, the step of calculating the eigenvalues ​​of the grid-connected system state matrix based on the small-signal model of the solar thermal power generator grid-connected system, and calculating the oscillation modes and damping rates of the grid-connected system based on the eigenvalues ​​of the grid-connected system state matrix, includes:

[0011] In the formula, I is a 17th-order identity matrix, and λ is the eigenvalue of matrix A, where the k-th eigenvalue is denoted as λ. k =σ k +j ωk In the system, each eigenvalue corresponds to a mode; f k and ζ k These are the oscillation frequency and damping rate of the k-th mode of the system, respectively.

[0012] Furthermore, the participation factor is obtained by calculating the left and right eigenvectors of the state matrix, including: The left eigenvector of the state matrix Ψ k Right eigenvector Φ k Participation Matrix P The calculation formula is as follows:

[0013] In the formula, p k,l =Φ k,l Ψ k,l The participation factor represents the degree of correlation between the l-th mode and the k-th state variable; the participation matrix... P The l List p l For the first l The participation vector of a mode, the state variable corresponding to the larger value in the vector is the variable that has a greater impact on this oscillation mode.

[0014] Furthermore, based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode, the potential factors affecting the system's oscillation mode are obtained, including: By comparing the participation matrix P The magnitude of the median value is used to assess the influence of different parameters on the oscillation mode in the system and to identify potential factors affecting the key oscillation modes of the system.

[0015] Secondly, the present invention provides an oscillation stability analysis system for a solar thermal power generator grid-connected system, comprising: The model building module is used to build a small-signal model of the solar thermal power generator grid-connected system. The small-signal model of the solar thermal power generator grid-connected system includes: a small-signal model of the concentrating solar collector subsystem, a small-signal model of the excitation subsystem, a small-signal model of the synchronizing machine subsystem, and a small-signal model of the turbine governor subsystem. The oscillation mode acquisition module is used to calculate the eigenvalues ​​of the grid-connected system state matrix based on the small-signal model of the solar thermal generator grid-connected system, and to calculate the oscillation mode and damping rate of the grid-connected system based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor acquisition module is used to obtain the participation factor by calculating the left and right eigenvectors of the state matrix; The output module is used to obtain the potential factors affecting the oscillation mode of the system based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode.

[0016] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for analyzing the oscillation stability of a solar thermal generator grid-connected system.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for analyzing the oscillation stability of a solar thermal generator grid-connected system.

[0018] Compared with the prior art, the present invention has the following technical effects: This invention first establishes a small-signal model of a grid-connected solar thermal power plant system. The model uses motor parameters, rather than raw parameters, to describe the dynamic characteristics of the solar thermal generator unit. These motor parameters include steady-state, transient, and subtransient parameters. Accurate parameters in the established model can be easily obtained through motor experiments, improving the model's accuracy. Then, modal analysis is used to analyze the model's stability, revealing the system's inherent oscillation characteristics under different operating parameters. Furthermore, by employing participation factor analysis, the influence of different parameters on key oscillation modes is evaluated, identifying potential factors affecting these modes and providing guidance for system oscillation control and stability improvement. Attached Figure Description

[0019] Figure 1 This is a flowchart of a method for analyzing the oscillation stability of a solar thermal generator grid-connected system provided by the present invention.

[0020] Figure 2 This is a flowchart of a method for constructing a small-signal model for a solar thermal power generator grid-connected system provided by the present invention.

[0021] Figure 3 This is a structural diagram of the solar thermal power generator set provided in this invention.

[0022] Figure 4 This is a schematic diagram of a solar thermal power generator grid connection system provided by an embodiment of the present invention. Detailed Implementation

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Example 1: This invention provides a method for analyzing the oscillation stability of a solar thermal power generator grid-connected system, comprising: A small-signal model of a solar thermal power generator grid-connected system is constructed, which includes: a small-signal model of a concentrating solar collector subsystem, a small-signal model of an excitation subsystem, a small-signal model of a synchronizing machine subsystem, and a small-signal model of a turbine governor subsystem. Based on the small-signal model of the solar thermal power generator grid-connected system, the eigenvalues ​​of the grid-connected system state matrix are calculated, and the oscillation mode and damping rate of the grid-connected system are calculated based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor is obtained by calculating the left and right eigenvectors of the state matrix; Based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode, the potential factors affecting the system's oscillation mode are obtained.

[0025] By comparing the values ​​in the participation matrix, we can assess the influence of different parameters on the oscillation modes in the system, identify potential factors affecting the key oscillation modes of the system, and provide guidance for the oscillation control and stability improvement of the system.

[0026] Example 2: This invention provides a method for analyzing the oscillation stability of a solar thermal power generator grid-connected system, comprising: A small-signal model of a solar thermal power generator grid-connected system is constructed. This system comprises four subsystems: a concentrating solar collector subsystem, an excitation subsystem, a synchronizing machine subsystem, and a turbine governor subsystem. Its structural block diagram is shown below. Figure 3 As shown, first, dynamic models of each subsystem are established, and then the small-signal model of the system is obtained by linearization at the stable operating point.

[0027] Modal analysis was used to perform stability analysis on a small-signal model of a generator grid-connected system. The three main indicators of modal analysis are eigenvalues, mode shapes, and participation factors. First, the state matrix of the grid-connected system can be obtained from the small-signal model. Calculating the eigenvalues ​​of the state matrix allows for further analysis of the system's oscillation modes and damping ratio. By calculating the left and right eigenvectors of the state matrix, the participation factors can be obtained, thereby assessing the influence of different parameters on key oscillation modes and identifying potential factors affecting these modes.

[0028] Furthermore, step 11) includes the following specific steps: A dynamic model of the concentrating solar collector subsystem of a solar thermal power generator grid-connected system is constructed, and its small-signal model is further obtained by linearization at the steady operating point as follows: ; In the formula, The subscripts fp and fm represent the physical quantities of the conduit and working fluid at the front end of the receiver, respectively; the subscripts tp and tm represent the physical quantities of the conduit and working fluid at the end of the receiver, respectively; the subscripts cm and hm represent the physical quantities of the working fluid in the cold tank and the hot tank, respectively; and the subscript m represents the physical quantity of the working fluid flowing per unit time. T For temperature; m c is the mass; c is the specific heat capacity. U The convective heat transfer coefficient between the duct and the heat transfer medium; S This refers to the contact area between the conduit and the heat transfer medium.Q l The energy change of the receiver due to the flow of the heat transfer medium; T 4 represents the temperature of the working fluid flowing into the cold tank; T 5 represents the temperature of the working fluid flowing out of the cold tank; T 2 represents the temperature of the working fluid flowing into the hot tank; T 3 represents the temperature of the working fluid flowing out of the hot tank. R l Heat loss in the conduit is expressed as a percentage.

[0029] A dynamic model of the excitation subsystem is constructed, and its small-signal model is further obtained by linearization at the steady operating point as follows: ; In the formula, V T , V f , V F These are the voltage regulator output voltage, generator excitation voltage, and excitation negative feedback voltage, respectively. V t This refers to the generator terminal voltage; K A , T A These are the amplification factor and time constant of the inertial amplification stage of the voltage regulator, respectively. K E , T E , S E These are the amplification factor, time constant, and saturation coefficient of the exciter's inertial element, respectively. K F , T F These are the amplification factor and time constant of the excitation negative feedback loop, respectively.

[0030] A dynamic model of the synchronous machine subsystem is constructed, and its small-signal model is further obtained by linearization at the stable operating point as follows: ; In the formula, e ' d , e '' d , e ' q and e '' q express d , q Transient and subtransient potentials on the axis.X d and X q They are respectively d , q Synchronous reactance on the shaft. d , q The transient reactance on the axis is expressed as X ' d and X ' q The subtransient reactance is expressed as X '' d and X '' q . T ' d0 and T ' q0 yes d , q The open-circuit transient time constant of the shaft. T '' d0 and T '' q0 This is the open-circuit subtransient time constant; i d and i q They represent d shaft and q Current on the shaft; E fq This represents the stator voltage of a synchronous motor under steady-state no-load conditions, and its magnitude is related to the excitation voltage. u f Proportional; δ The power angle represents the synchronous motor. ω This indicates the actual speed of the synchronous motor. ω 0 represents synchronous speed. M Indicates the rotor inertia coefficient. P m Represents mechanical power. P e Represents electromagnetic power.

[0031] A dynamic model of the turbine governor subsystem is constructed, and its small-signal model is further obtained by linearization at the steady operating point as follows: ; In the formula, H p This refers to the steam pressure in the first stage of the high-pressure cylinder.T 4 represents the time constant of the high-pressure cylinder in the first time step. T sm The time constant of the speed controller, K p The speed controller amplification factor. P ref This is a reference value for generator power. R p This is the generator droop coefficient. ω ref This is a reference value for rotational speed. μ This refers to the steam valve opening of the steam turbine.

[0032] By aggregating the small-signal models of each component, a total of 17 orders of small-signal model is formed for the overall solar thermal power generator grid-connected system. The corresponding system grid-connection diagram is shown below. Figure 4 As shown, U G ∠ δ This refers to the output voltage of the solar thermal power generator set. U t ∠0 is the grid connection point voltage. X t The line impedance between the generator set output point and the grid connection point; state variable x = [ T fp , T fm , T tp , T tm , T cm , T hm , δ , ω , e ’ d , e ’’ d , e ’ q , e ’’ q , V T , V f , V F , H p , μ ] T .

[0033] Furthermore, step 12) includes the following specific steps: Based on the above small-signal model, the system's state matrix is ​​obtained, and the eigenvalues ​​of the 17th-order state matrix A are calculated as follows: ; In the formula, I is a 17th-order identity matrix. λ These are the eigenvalues ​​of matrix A, where the eigenvalue of matrix A is... k The eigenvalues ​​are denoted as λ. k = σ k + jω k .

[0034] The oscillation modes and damping rates of the system are calculated based on the eigenvalues ​​of the state matrix, as shown in the following equation: ; In the formula, f k and ζ k These are the system's first k The oscillation frequency and damping rate of each mode.

[0035] Calculate the first k The right eigenvector Φ corresponding to each mode k and left eigenvector Ψ k As shown in the following formula: .

[0036] Calculate the participation matrix of the system based on the left and right eigenvectors. P This allows for a better measurement of the correlation between state variables and modes. The formula for calculating the participation matrix is ​​as follows: ; In the formula, p k,l =Φ k,l Ψ k,l As a participation factor, it represents the first l The modality and the first k The degree of correlation of the state variables, matrix P The l List p l For the first l The participation vectors for each mode are used, and the state variables corresponding to the larger values ​​in the vectors are those that have a greater impact on that oscillation mode. This is achieved by comparing the participation matrices. P The magnitude of the median value can be used to assess the degree of influence of different parameters on the oscillation mode in the system, identify potential factors affecting the key oscillation mode of the system, and provide guidance for the oscillation control and stability improvement of the system.

[0037] By comparing the participation matrix PThe magnitude of the median value can be used to assess the degree of influence of different parameters on the oscillation mode in the system, identify potential factors affecting the key oscillation mode of the system, and provide guidance for the oscillation control and stability improvement of the system.

[0038] Methods for constructing small-signal models of grid-connected solar thermal power generation systems, such as... Figure 2 As shown, it includes: A dynamic model of the concentrated solar thermal collection subsystem was constructed, and its small-signal model was obtained through linearization. A dynamic model of the excitation subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the synchronous generator subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the turbine governor subsystem is constructed, and its small-signal model is obtained through linearization.

[0039] This invention establishes a holistic dynamic model of a solar thermal power plant grid-connected system, including the dynamic processes of the concentrating solar collector subsystem and the electron generating system. A small-signal model of the system is constructed based on Taylor series expansion. The system's state matrix is ​​obtained through the small-signal model, and the eigenvalues ​​of the state matrix are calculated to further analyze the system's oscillation modes and damping rate. By calculating the left and right eigenvectors of the state matrix, the system's participation factors are obtained, thereby assessing the influence of different parameters on key oscillation modes and identifying potential factors affecting these modes, providing guidance for system oscillation control and stability improvement.

[0040] In another embodiment of the present invention, an oscillation stability analysis system for a solar thermal power generator grid-connected system is provided, which can be used to implement the above-mentioned oscillation stability analysis method for a solar thermal power generator grid-connected system. Specifically, the system includes: The model building module is used to build a small-signal model of the solar thermal power generator grid-connected system. The small-signal model of the solar thermal power generator grid-connected system includes: a small-signal model of the concentrating solar collector subsystem, a small-signal model of the excitation subsystem, a small-signal model of the synchronizing machine subsystem, and a small-signal model of the turbine governor subsystem. The oscillation mode acquisition module is used to calculate the eigenvalues ​​of the grid-connected system state matrix based on the small-signal model of the solar thermal generator grid-connected system, and to calculate the oscillation mode and damping rate of the grid-connected system based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor acquisition module is used to obtain the participation factor by calculating the left and right eigenvectors of the state matrix; The output module is used to obtain the potential factors affecting the oscillation mode of the system based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode.

[0041] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0042] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or 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, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of an oscillation stability analysis method for a solar thermal generator grid-connected system.

[0043] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the terminal. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the oscillation stability analysis method for a solar thermal power generator grid-connected system in the above embodiments.

[0044] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0045] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0046] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0047] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for analyzing the oscillation stability of a solar thermal power generator grid-connected system, characterized in that, include: A small-signal model of a solar thermal power generator grid-connected system is constructed, which includes: a small-signal model of a concentrating solar collector subsystem, a small-signal model of an excitation subsystem, a small-signal model of a synchronizing machine subsystem, and a small-signal model of a turbine governor subsystem. Based on the small-signal model of the solar thermal power generator grid-connected system, the eigenvalues ​​of the grid-connected system state matrix are calculated, and the oscillation mode and damping rate of the grid-connected system are calculated based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor is obtained by calculating the left and right eigenvectors of the state matrix; Based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode, the potential factors affecting the system's oscillation mode are obtained.

2. The method for analyzing the oscillation stability of a solar thermal power generator grid-connected system according to claim 1, characterized in that, The small-signal model for constructing a solar thermal power generator grid-connected system includes: Based on the dynamic models of each subsystem, the corresponding small-signal models are obtained by linearization at the stable operating point. Based on the small-signal models of each subsystem, the overall small-signal model of the system is further obtained.

3. The oscillation stability analysis method for a solar thermal power generator grid-connected system according to claim 2, characterized in that, The specific construction is as follows: A dynamic model of the concentrated solar thermal collection subsystem was constructed, and its small-signal model was obtained through linearization. A dynamic model of the excitation subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the synchronous generator subsystem is constructed, and its small-signal model is obtained through linearization. A dynamic model of the turbine governor subsystem is constructed, and its small-signal model is obtained through linearization.

4. The oscillation stability analysis method for a solar thermal power generator grid-connected system according to claim 3, characterized in that, The specific expression is as follows: In the formula, The subscripts fp and fm represent the physical quantities of the conduit and working fluid at the front end of the receiver, respectively; the subscripts tp and tm represent the physical quantities of the conduit and working fluid at the end of the receiver, respectively; the subscripts cm and hm represent the physical quantities of the working fluid in the cold tank and the hot tank, respectively; and the subscript m represents the physical quantity of the working fluid flowing per unit time. T For temperature; m c is the mass; c is the specific heat capacity. U The convective heat transfer coefficient between the duct and the heat transfer medium; S This refers to the contact area between the conduit and the heat transfer medium. Q l The energy change of the receiver due to the flow of the heat transfer medium; T 4 represents the temperature of the working fluid flowing into the cold tank; T 5 represents the temperature of the working fluid flowing out of the cold tank; T 2 represents the temperature of the working fluid flowing into the hot tank; T 3 represents the temperature of the working fluid flowing out of the hot tank; R l Heat loss through the conduit is expressed as a percentage. V T , V f , V F These are the voltage regulator output voltage, generator excitation voltage, and excitation negative feedback voltage, respectively. V t This refers to the generator terminal voltage; K A , T A These are the amplification factor and time constant of the inertial amplification stage of the voltage regulator, respectively. K E , T E , S E These are the amplification factor, time constant, and saturation coefficient of the exciter's inertial element, respectively. K F , T F These are the amplification factor and time constant of the excitation negative feedback loop, respectively. e ' d , e '' d , e ' q and e '' q express d , q Transient and subtransient potentials on the axis; X d and X q They are respectively d , q Synchronous reactance on the shaft; d , q The transient reactance on the axis is expressed as X ' d and X ' q The subtransient reactance is expressed as X '' d and X '' q ; T ' d0 and T ' q0 yes d , q The open-circuit transient time constant of the shaft, T '' d0 and T '' q0 This is the open-circuit subtransient time constant; i d and i q They represent d shaft and q Current on the shaft; E fq This represents the stator voltage of a synchronous motor under steady-state no-load conditions, and its magnitude is related to the excitation voltage. u f Proportional; δ The power angle represents the synchronous motor. ω This indicates the actual speed of the synchronous motor. ω 0 represents synchronous speed. M Indicates the rotor inertia coefficient. P m Represents mechanical power. P e Represents electromagnetic power; H p This refers to the steam pressure in the first stage of the high-pressure cylinder. T 4 represents the time constant of the high-pressure cylinder in the first time step. T sm The time constant of the speed controller, K p The speed controller amplification factor. P ref This is a reference value for generator power. R p This is the generator droop coefficient. ω ref This is a reference value for rotational speed. μ This refers to the steam valve opening of the steam turbine.

5. The method for analyzing the oscillation stability of a solar thermal power generator grid-connected system according to claim 1, characterized in that, The step of calculating the eigenvalues ​​of the grid-connected system state matrix based on the small-signal model of the solar thermal power generator grid-connected system, and calculating the oscillation modes and damping rate of the grid-connected system based on the eigenvalues ​​of the grid-connected system state matrix includes: In the formula, I is a 17th-order identity matrix, and λ is the eigenvalue of matrix A, where the k-th eigenvalue is denoted as λ. k =σ k +j ωk In the system, each eigenvalue corresponds to a mode; f k and ζ k These are the oscillation frequency and damping rate of the k-th mode of the system, respectively.

6. The method for analyzing the oscillation stability of a solar thermal power generator grid-connected system according to claim 1, characterized in that, The participation factor is obtained by calculating the left and right eigenvectors of the state matrix, including: The left eigenvector of the state matrix Ψ k Right eigenvector Φ k Participation Matrix P The calculation formula is as follows: In the formula, p k,l =Φ k,l Ψ k,l The participation factor represents the degree of correlation between the l-th mode and the k-th state variable; the participation matrix... P The l List p l For the first l The participation vector of a mode, the state variable corresponding to the larger value in the vector is the variable that has a greater impact on this oscillation mode.

7. The method for analyzing the oscillation stability of a solar thermal power generator grid-connected system according to claim 1, characterized in that, The potential factors affecting the system's oscillation modes are obtained based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation modes, including: By comparing the participation matrix P The magnitude of the median value is used to assess the influence of different parameters on the oscillation mode in the system and to identify potential factors affecting the key oscillation modes of the system.

8. An oscillation stability analysis system for a solar thermal power generator grid-connected system, characterized in that, include: The model building module is used to build a small-signal model of the solar thermal power generator grid-connected system. The small-signal model of the solar thermal power generator grid-connected system includes: a small-signal model of the concentrating solar collector subsystem, a small-signal model of the excitation subsystem, a small-signal model of the synchronizing machine subsystem, and a small-signal model of the turbine governor subsystem. The oscillation mode acquisition module is used to calculate the eigenvalues ​​of the grid-connected system state matrix based on the small-signal model of the solar thermal generator grid-connected system, and to calculate the oscillation mode and damping rate of the grid-connected system based on the eigenvalues ​​of the grid-connected system state matrix. The participation factor acquisition module is used to obtain the participation factor by calculating the left and right eigenvectors of the state matrix; The output module is used to obtain the potential factors affecting the oscillation mode of the system based on the degree of influence of different parameters in the participating factor evaluation system on the oscillation mode.

9. A computer 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, it implements the steps of the oscillation stability analysis method for a solar thermal generator grid-connected system as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the oscillation stability analysis method for a solar thermal generator grid-connected system as described in any one of claims 1 to 7.

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