AC system transient stability optimization method and system with grid-following ice melting device

Abstract

The present invention relates to the technical field of transient stability optimization and provides a method and system for optimizing the transient stability of an AC system including a grid-following de-icing device. The method involves analyzing the correlation between bandwidth parameters and system oscillation modes based on a system operation dataset acquired for a voltage sag fault scenario, obtaining a bandwidth parameter oscillation damping relationship. Based on this relationship, a power system simulation model is constructed to simulate the power system's fault operation under different phase-locked loop (PLL) bandwidth parameters. After obtaining the bandwidth parameter transient response relationship and the bandwidth parameter stability boundary relationship, a bandwidth parameter optimization model is constructed based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, with the optimization objective of balancing transient response efficiency and transient stability margin. The model is used to determine the optimal bandwidth parameter and adjust the de-icing device's PLL. The present invention can ensure de-icing device synchronization in voltage sag scenarios and effectively improve the power system's transient stability, fault response efficiency, and operational robustness.

Description

Technical Field

[0001] The present invention relates to the technical field of transient stability optimization, and in particular to a method and system for optimizing transient stability of an AC system including a grid-following ice melting device. Background Art

[0002] In freezing weather, rain, snow, and freezing temperatures, transmission lines are prone to ice buildup, potentially paralyzing the grid and causing serious consequences such as tower collapse and line breakage. Grid-mounted de-icing devices efficiently remove ice by heating conductors, ensuring safe grid operation and playing a key role in de-icing power grids in cold and high-altitude regions.

[0003] However, the phase-locked loop (PLL) of a grid-following de-icing device is a negative feedback control system that uses the voltage generated by phase synchronization to tune a voltage-controlled oscillator to produce the target frequency. In the event of a sudden voltage sag caused by a short-circuit fault in the power system, the output phase can fluctuate rapidly. Phase tracking errors can even cause the de-icing device to lose synchronization with the grid, significantly reducing the damping characteristics of the system's oscillation mode and increasing the risk of low-frequency or subsynchronous oscillations, significantly hindering the smooth operation of de-icing services. Therefore, it is of great practical significance to ensure the synchronization of the de-icing device in voltage sag scenarios while avoiding the risks of improper phase adjustment affecting the system's power angle stability limits and weakening system robustness. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for optimizing the transient stability of an AC system containing a grid-following ice-melting device. By extracting and analyzing the output phase fluctuation characteristics of the ice-melting device's phase-locked loop under different phase-locked loop bandwidth parameters under fault scenarios, a power system simulation model is constructed, and the bandwidth parameter oscillation damping relationship obtained is obtained. Based on this, the relationship between the phase-locked loop bandwidth parameter and the transient response rate and transient stability boundary under real fault scenarios is studied, and a bandwidth parameter optimization model is constructed to achieve reliable adjustment of the phase-locked loop bandwidth parameter. While ensuring the synchronization of the ice-melting device under voltage sag scenarios, the transient stability, fault response efficiency and operational robustness of the power system can be effectively improved.

[0005] In order to achieve the above objectives, a method and system for optimizing the transient stability of an AC system including a grid-following ice melting device are provided.

[0006] In a first aspect, an embodiment of the present invention provides a method for optimizing transient stability of an AC system including a grid-following ice melting device, the method comprising the following steps:

[0007] Acquire a system operation data set for a voltage sag fault scenario; the system operation data set includes power grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters;

[0008] performing a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship, and constructing a power system simulation model based on the bandwidth parameter oscillation damping relationship;

[0009] Perform fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship;

[0010] According to the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a bandwidth parameter optimization model is constructed with balanced transient response efficiency and transient stability margin as optimization goals;

[0011] The bandwidth parameter optimization model is solved to obtain the optimal bandwidth parameter, and the phase-locked loop of the ice melting device is adjusted according to the optimal bandwidth parameter.

[0012] Furthermore, the grid operation data includes voltage fluctuation data, current fluctuation data, and frequency deviation data; the de-icing device operation parameters include a DC de-icing current value and an operation duration; and the step of performing correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain an oscillation damping relationship of bandwidth parameters includes:

[0013] The correlation between phase fluctuation and oscillation mode is analyzed based on the grid operation data, ice melting device operation parameters and phase-locked loop output signal under different ice melting device phase-locked loop bandwidth parameters, and the correlation degree of phase fluctuation and oscillation mode is obtained.

[0014] When the correlation degree of the phase fluctuation oscillation mode reaches a preset correlation level, correlation analysis between bandwidth parameters and oscillation mode damping is performed according to bandwidth parameters of different ice melting devices phase-locked loops to obtain a bandwidth parameter oscillation damping relationship.

[0015] Furthermore, the step of performing correlation analysis between phase fluctuation and oscillation mode based on grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters to obtain the correlation degree of phase fluctuation oscillation mode includes:

[0016] According to the phase-locked loop output signal under different phase-locked loop bandwidth parameters of the ice melting device, the corresponding output phase sequence is obtained;

[0017] Generate a corresponding phase fluctuation characteristic spectrum according to the output phase sequence and fast Fourier transform, and obtain a corresponding key frequency component according to the phase fluctuation characteristic spectrum;

[0018] Matching and analyzing the key frequency component with a preset system oscillation mode frequency range to obtain a main oscillation component;

[0019] Obtaining a correlation index based on a deviation between the main oscillation component and an average value of the preset system oscillation mode frequency range, and determining whether the correlation index is less than a preset index threshold;

[0020] If not, the phase fluctuation oscillation mode correlation is set to a preset correlation value; otherwise, the output phase sequence is decomposed by wavelet transform to obtain a corresponding low-frequency oscillation component;

[0021] Calculating a corresponding low-frequency component energy according to the low-frequency oscillation component, and obtaining a key influencing factor according to the low-frequency component energy, the grid operation data, and the ice melting device operation parameters;

[0022] According to the key influencing factors under different de-icing device phase-locked loop bandwidth parameters, oscillation mode classification and prediction are performed based on support vector machine, and the correlation degree of the phase fluctuation oscillation mode is obtained based on SHAP attribution analysis.

[0023] Furthermore, the step of analyzing the correlation between bandwidth parameters and oscillation mode damping according to bandwidth parameters of phase-locked loops of different ice melting devices to obtain the oscillation damping relationship of bandwidth parameters includes:

[0024] The phase fluctuation sequence and voltage amplitude sequence corresponding to the phase-locked loop output signal under different phase-locked loop bandwidth parameters of the ice melting device are obtained respectively;

[0025] According to the phase-locked loop bandwidth parameters of different ice melting devices and the corresponding phase fluctuation sequence and voltage amplitude sequence, the corresponding small signal stability analytical model is constructed based on the state space method.

[0026] Calculating characteristic root trajectories corresponding to different phase-locked loop bandwidth parameters according to the small-signal stability analytical model, and obtaining corresponding oscillation mode damping ratio sequences and oscillation frequency sequences according to the characteristic root trajectories corresponding to the different phase-locked loop bandwidth parameters;

[0027] Generating multiple sets of stability characteristic data according to different phase-locked loop bandwidth parameters and corresponding oscillation mode damping ratio sequences and oscillation frequency sequences; the stability characteristic data including the bandwidth parameters and the corresponding oscillation mode damping ratio and oscillation frequency;

[0028] Based on the support vector machine, multiple groups of stability feature data are classified and predicted to obtain corresponding stability prediction results; the stability prediction results include stable, critically stable and unstable;

[0029] Fitting and analyzing the stability characteristic data of different result types in the stability prediction results are performed respectively to obtain the bandwidth parameter oscillation and damping relationship; the bandwidth parameter oscillation and damping relationship includes bandwidth parameter oscillation and damping relationships corresponding to different result types.

[0030] Furthermore, the step of performing a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship includes:

[0031] generating an initial operating environment according to the power system simulation model and preset operating conditions; wherein the initial operating environment includes a stable voltage distribution and a stable current distribution;

[0032] A voltage sag fault is introduced in the initial operating environment, and post-fault electrical change data and system stable state data under different phase-locked loop bandwidth parameters are obtained by adjusting the bandwidth parameters of the phase-locked loop of the ice melting device; the post-fault electrical change data includes voltage amplitude time series data and system frequency time series data; the system stable state data includes a power angle curve, voltage amplitude, and frequency deviation;

[0033] Based on the post-fault electrical change data under different PLL bandwidth parameters, the corresponding oscillation decay time, voltage recovery time and frequency recovery time are calculated;

[0034] The oscillation decay time, voltage recovery time and frequency recovery time under different phase-locked loop bandwidth parameters are weightedly analyzed to obtain the corresponding transient response speed;

[0035] Performing a correlation analysis between bandwidth parameters and transient response speeds according to transient response speeds of different phase-locked loop bandwidth parameters to obtain the bandwidth parameter transient response relationship;

[0036] According to the system stable state data under different phase-locked loop bandwidth parameters, transient power angle stability analysis is carried out based on the energy function method, and the stable boundary relationship of the bandwidth parameter is obtained.

[0037] Furthermore, the step of performing transient power angle stability analysis based on the energy function method according to the system stable state data under different phase-locked loop bandwidth parameters to obtain the bandwidth parameter stability boundary relationship includes:

[0038] According to the preset system potential energy function and the preset system kinetic energy function, energy analysis is performed on the system steady state data with different phase-locked loop bandwidth parameters to obtain the corresponding critical power angle value;

[0039] Data fitting analysis is performed based on critical power angle values ​​corresponding to different phase-locked loop bandwidth parameters to obtain the stable boundary relationship of the bandwidth parameters.

[0040] Furthermore, the step of performing energy analysis on system steady-state data of different phase-locked loop bandwidth parameters according to a preset system potential energy function and a preset system kinetic energy function to obtain corresponding critical power angle values ​​includes:

[0041] According to the preset system potential energy function and the preset system kinetic energy function, energy calculation is performed on the system steady state data under different phase-locked loop bandwidth parameters to obtain the corresponding critical energy threshold and system total energy;

[0042] According to the critical energy threshold and system total energy of different phase-locked loop bandwidth parameters, data fitting analysis is performed respectively to obtain the corresponding bandwidth parameter critical energy threshold expression and bandwidth parameter system total energy expression;

[0043] According to the bandwidth parameter critical energy threshold expression and the bandwidth parameter system total energy expression, critical power angle values ​​of different phase-locked loop bandwidth parameters are obtained based on the Newton iteration method.

[0044] Furthermore, the bandwidth parameter optimization model is expressed as:

[0045]

[0046] Where, and They represent the bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship respectively; Indicates the stable power angle value; Indicates the bandwidth parameter of the phase-locked loop of the ice melting device; and Respectively represent the minimum and maximum values ​​of the bandwidth parameter; represents the system damping ratio; and Represents the weight coefficient.

[0047] Furthermore, the method further comprises:

[0048] After the phase-locked loop of the ice-melting device is adjusted according to the optimal bandwidth parameters, real-time power grid operation status data is obtained, and response speed and robustness simulation verification is performed based on the real-time power grid operation status data. When the corresponding simulation verification results do not meet the preset targets, the optimal bandwidth parameters are adjusted.

[0049] In a second aspect, an embodiment of the present invention provides an AC system transient stability optimization system including a grid-following ice melting device, the system comprising:

[0050] A data acquisition module is used to obtain a system operation data set for a voltage sag fault scenario; the system operation data set includes power grid operation data under different de-icing device phase-locked loop bandwidth parameters, de-icing device operation parameters, and phase-locked loop output signals;

[0051] a simulation model construction module, configured to perform a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set, obtain a bandwidth parameter oscillation damping relationship, and construct a power system simulation model based on the bandwidth parameter oscillation damping relationship;

[0052] A simulation analysis module is used to perform fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model, and obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship;

[0053] An optimization model construction module is used to construct a bandwidth parameter optimization model based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, with the balanced transient response efficiency and transient stability margin as the optimization goal;

[0054] The bandwidth parameter optimization module is used to solve the bandwidth parameter optimization model to obtain the optimal bandwidth parameter and adjust the phase-locked loop of the ice melting device according to the optimal bandwidth parameter.

[0055] The present invention provides a method and system for optimizing the transient stability of an AC system including a grid-following ice-melting device. The method achieves the goal of obtaining a system operation data set for a voltage sag fault scenario, including grid operation data, ice-melting device operation parameters, and a phase-locked loop output signal under different ice-melting device phase-locked loop bandwidth parameters. A correlation analysis between the bandwidth parameter and the system oscillation mode is performed based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship. A power system simulation model is constructed based on the bandwidth parameter oscillation damping relationship. A fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters is then performed based on the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship. Based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a bandwidth parameter optimization model is constructed with balancing transient response efficiency and transient stability margin as optimization goals. The bandwidth parameter optimization model is solved to obtain an optimal bandwidth parameter, and the ice-melting device phase-locked loop is adjusted based on the optimal bandwidth parameter. Compared with the existing technology, the transient stability optimization method of the AC system containing the grid-following ice-melting device constructs a fault scenario simulation mechanism of the power system simulation model based on the bandwidth parameter oscillation damping relationship obtained by extracting and analyzing the output phase fluctuation characteristics of the ice-melting device phase-locked loop under different phase-locked loop bandwidth parameters under fault scenarios. Combined with the multi-objective bandwidth parameter optimization design of balanced transient response efficiency and transient stability margin, it realizes reliable and efficient adjustment of the phase-locked loop bandwidth parameters. It can not only ensure the synchronization of the ice-melting device under voltage sag scenarios, but also effectively improve the transient stability, fault response efficiency and operational robustness of the power system, ensure the safe and stable operation of the power grid, and thus provide reliable technical support for the development of ice-melting business in power grids in high-altitude and cold areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 1 is a flow chart of a method for optimizing transient stability of an AC system including a grid-type ice melting device according to an embodiment of the present invention;

[0057] Figure 2 1 is a structural diagram of an AC system transient stability optimization system including a grid-type ice melting device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and beneficial effects of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. Obviously, the embodiments described below are part of the embodiments of the present invention and are only used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0059] The proposed method for optimizing the transient stability of an AC system with a grid-following ice-melting device can be understood as taking into account that a grid-following ice-melting device must not only cope with dynamic grid voltage drops but also adapt to possible frequency drift after a fault. The magnitude of the phase-locked loop (PLL) bandwidth parameter in the ice-melting device directly affects its response speed to sudden grid phase changes and the system's transient stability margin. The existing fixed setting of the PLL bandwidth parameter is difficult to simultaneously meet the requirements of fast response and disturbance resistance. Therefore, a method for dynamically adjusting the PLL bandwidth parameter is proposed, which ensures the synchronization of the ice-melting device while avoiding the weakening of system robustness due to excessively fast or slow phase adjustments. The following examples will detail the proposed method for optimizing the transient stability of an AC system with a grid-following ice-melting device.

[0060] In one embodiment, Figure 1 As shown, a method for optimizing the transient stability of an AC system including a grid-following ice melting device is provided, comprising the following steps:

[0061] S11. Obtain a system operation data set for a voltage sag fault scenario; wherein the system operation data set can be understood as collecting relevant historical data on voltage sag fault scenarios occurring in an AC system containing a grid-following ice-melting device. In order to facilitate accurate analysis of the correlation between the phase-locked loop bandwidth parameter and the system oscillation mode damping, this embodiment preferably configures the system operation data set to include grid operation data, ice-melting device operation parameters, and phase-locked loop output signals under different ice-melting device phase-locked loop bandwidth parameters, and the grid operation data preferably includes voltage fluctuation data, current fluctuation data, and frequency deviation data, etc., and the ice-melting device operation parameters include DC ice-melting current value and operation duration, etc. It should be noted that the collection of various data in the system operation data set can be achieved using existing relevant technologies and will not be described in detail here.

[0062] S12. Performing a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship, and constructing a power system simulation model based on the bandwidth parameter oscillation damping relationship. The bandwidth parameter oscillation damping relationship can be understood as the relationship between the influence of different bandwidth parameters on the damping of the system oscillation mode. Specifically, the step of performing a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain the bandwidth parameter oscillation damping relationship includes:

[0063] A correlation analysis is performed between phase fluctuation and oscillation mode based on grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters to obtain a phase fluctuation oscillation mode correlation degree; wherein the phase fluctuation oscillation mode correlation degree can be understood as the degree of correlation between the phase fluctuation of the phase-locked loop output signal of the ice melting device and the system oscillation mode. Specifically, the step of performing a correlation analysis between phase fluctuation and oscillation mode based on grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters to obtain the phase fluctuation oscillation mode correlation degree includes:

[0064] According to the phase-locked loop output signal under different phase-locked loop bandwidth parameters of the ice melting device, a corresponding output phase sequence is obtained; wherein, the calculation process of the output phase sequence may include first performing discrete time signal sampling on the phase-locked loop output signal, converting the real signal of each sampling point into a corresponding complex signal through Hilbert transform, and then calculating the corresponding phase value based on the real part and imaginary part of the complex signal using the inverse tangent function; an output phase sequence including phase values ​​corresponding to different sampling points can be obtained; it should be noted that the acquisition process of the output phase sequence here can be implemented with reference to relevant existing technologies and will not be described in detail here.

[0065] According to the output phase sequence and fast Fourier transform, a corresponding phase fluctuation characteristic spectrum is generated, and according to the phase fluctuation characteristic spectrum, the corresponding key frequency components are obtained; wherein, the process of obtaining the phase fluctuation characteristic spectrum may include first performing phase unwrapping processing on the output phase sequence to eliminate the periodic jumps of the phase sequence, then calculating the phase difference to extract the change of the phase over time, and then converting the phase change to the frequency domain to obtain the corresponding frequency components, and generating the fluctuation characteristic spectrum based on the obtained frequency components. After obtaining the phase fluctuation characteristic spectrum, the key frequency components can be obtained by the frequency position where the main frequency components displayed by the spectrum are concentrated; for example, if the phase fluctuation characteristic spectrum shows that its main frequency components are concentrated at 5Hz and 10Hz, then 5Hz and 10Hz are the corresponding key frequency components.

[0066] The key frequency components are matched and analyzed with a preset system oscillation mode frequency range to obtain the primary oscillation component. The preset system oscillation mode frequency range can be understood as the typical low-frequency oscillation mode frequency range of the power system, selected to account for the potential low-frequency disturbances introduced by connecting an ice-melting device to the power system. For example, if the preset system low-frequency oscillation mode frequency range is 4-7 Hz, and the key frequency components obtained in actual application are 5 Hz and 10 Hz, then the two key frequency components are compared with the preset system oscillation mode frequency range. The frequency component that matches the preset system low-frequency oscillation mode frequency range can be used as the primary oscillation component. This matching reveals the potential connection between phase fluctuations and system oscillations.

[0067] Based on the deviation between the main oscillation component and the average value of the preset system oscillation mode frequency range, a correlation index is obtained, and it is determined whether the correlation index is less than a preset index threshold; wherein, the correlation index can be understood as the deviation value between the main oscillation component and the average value of the preset system oscillation mode frequency range; the corresponding preset index threshold can be set according to actual application requirements and is not specifically limited here. For example, if the preset index threshold is 0.1Hz, and the average value of the preset system oscillation mode frequency range of 4~7Hz is 5.5Hz, then the deviation of the main oscillation component 5Hz from the preset system oscillation mode frequency range is 0.5Hz, then it is considered that the correlation index is less than the preset index threshold, and the corresponding high-frequency component and low-frequency component can be further obtained through wavelet transform decomposition for further analysis.

[0068] If not, the correlation of the phase fluctuation oscillation mode is set to a preset correlation value. Otherwise, the output phase sequence is subjected to wavelet transform decomposition to obtain the corresponding low-frequency oscillation component. The preset correlation value can be set to 0 or a value indicating a lower correlation level according to actual application requirements, and is not specifically limited here. It should be noted that the process of performing wavelet transform decomposition on the main oscillation component can be referenced by existing wavelet transform technology to obtain high-frequency and low-frequency components. Considering that the high-frequency component reflects rapid disturbances and the low-frequency component is associated with the inherent oscillation of the system, only the low-frequency oscillation component is retained here for subsequent analysis.

[0069] Based on the low-frequency oscillation component, the corresponding low-frequency component energy is calculated, and key influencing factors are obtained based on the low-frequency component energy, the power grid operating data, and the ice-melting device operating parameters. The low-frequency component energy can be understood as the energy value obtained by calculating the energy of the low-frequency oscillation component based on an energy function. To further accurately analyze the correlation between phase fluctuations and system oscillation modes, this embodiment preferably uses the low-frequency component energy, power grid operating data, and ice-melting device operating parameters as influencing factors of the system oscillation mode to generate key influencing factors, which serve as input data for the oscillation mode classification prediction described below.

[0070] Based on the key influencing factors under different de-icing device phase-locked loop bandwidth parameters, a support vector machine is used to classify and predict oscillation modes, and the phase fluctuation oscillation mode correlation is obtained based on SHAP attribution analysis. The phase fluctuation oscillation mode correlation can be understood as the model contribution weight corresponding to the low-frequency component energy obtained through SHAP attribution analysis after the support vector machine is trained for oscillation mode classification and prediction based on the key influencing factors under different de-icing device phase-locked loop bandwidth parameters. It should be noted that both the support vector machine for oscillation mode classification and prediction and the SHAP attribution analysis can be implemented by referring to relevant existing technologies and will not be described in detail here.

[0071] When the correlation between the phase fluctuation oscillation mode reaches a preset correlation level, a correlation analysis between the bandwidth parameter and the oscillation mode damping is performed based on different de-icing device phase-locked loop bandwidth parameters to obtain a bandwidth parameter oscillation damping relationship. The preset correlation level can be understood as being set based on actual application requirements and indicating that the correlation between the phase fluctuation and the system oscillation mode reaches a correlation level that indirectly affects the oscillation mode damping change through bandwidth parameter adjustment. Specifically, the steps of performing a correlation analysis between the bandwidth parameter and the oscillation mode damping based on different de-icing device phase-locked loop bandwidth parameters to obtain a bandwidth parameter oscillation damping relationship include:

[0072] The phase fluctuation sequence and voltage amplitude sequence corresponding to the phase-locked loop output signal under different de-icing device phase-locked loop bandwidth parameters are obtained respectively; wherein, the phase fluctuation sequence and voltage amplitude sequence can be obtained by processing the phase-locked loop output signal based on the working principle of the de-icing device phase-locked loop, which will not be described in detail here.

[0073] Based on the bandwidth parameters of the phase-locked loops of different de-icing devices and the corresponding phase fluctuation sequences and voltage amplitude sequences, a corresponding small-signal stability analytical model is constructed based on the state-space method. The small-signal stability analytical model can be understood as treating the power system as a multi-input and multi-output dynamic system. By coupling the dynamics of the de-icing device phase-locked loop with the dynamics of the main power grid, a model is constructed based on the state-space method to quantify the impact of the bandwidth parameters of the de-icing device phase-locked loop on the small-signal stability of the power grid. The specific construction process may include:

[0074] The grid dynamic modeling is performed based on the following dynamic equations for the synchronous generator (generator rotor motion equation), the excitation system (excitation voltage dynamic equation), and the load (voltage-frequency sensitive load equation):

[0075] 1) Generator rotor motion equation:

[0076]

[0077] Where, represents the inertia time constant; Indicates the generator speed deviation; and represent the mechanical input power and electromagnetic output power respectively; Represents the damping coefficient.

[0078] 2) Dynamic equation of excitation voltage:

[0079]

[0080] Where, Indicates the time constant of the excitation system, reflecting the response speed of the excitation system; Indicates the excitation voltage, which directly determines the magnetic field strength of the generator; Indicates the excitation reference voltage, which is set by the automatic voltage regulator; Indicates the generator terminal voltage, the actual measured value affected by load changes, It represents the gain of the excitation system, which characterizes the amplification factor of the input voltage deviation on the excitation voltage.

[0081] 3) Voltage-frequency sensitive load equation:

[0082]

[0083] Where, and Respectively represent the active power and reactive power absorbed by the load from the power grid; and represents the time constant; and Represents the voltage sensitivity coefficient; and represents the frequency sensitivity coefficient; Indicates the actual voltage amplitude of the node where the load is located; Indicates the system frequency; and Represent the rated voltage and rated frequency respectively.

[0084] Based on the working principles of the phase detector, loop filter, and voltage-controlled oscillator, the phase detector output model, loop filter first-order RC model, and voltage-controlled oscillator model are used to dynamically model the phase-locked loop of the ice melting device:

[0085] Phase detector output model:

[0086]

[0087] Where,

[0088]

[0089] in, Indicates the phase detector output voltage; represents the phase detector gain; Indicates the real-time phase error; and Represent the reference phase (grid phase) and the phase-locked loop output phase respectively.

[0090] The first-order RC time domain equation of the loop filter is:

[0091]

[0092] Where, represents the filter time constant; Represents the control voltage output by the loop filter; Indicates the phase detector output voltage.

[0093] Voltage Controlled Oscillator Model:

[0094]

[0095] Where, Indicates the phase of the phase-locked loop output; Represents the control voltage output by the loop filter; Represents VCO gain, the rate of phase change corresponding to unit control voltage; Indicates the VCO free-running frequency.

[0096] It should be noted that based on the operating principle of the phase-locked loop of the ice melting device, it is easy to know that the phase-locked loop bandwidth parameter satisfies the following formula:

[0097]

[0098] Where B represents the phase-locked loop bandwidth parameter; and They represent the phase detector gain and VCO gain respectively.

[0099] By coupling the above-mentioned grid dynamic model with the phase-locked loop dynamic model of the ice melting device (grid voltage , system frequency and grid output phase The output active power and reactive power of the ice melting device phase-locked loop are fed back to the grid. The state variables in the above grid dynamic model and the ice melting device phase-locked loop dynamic model are summarized to obtain the complete state variables of the grid dynamic model and the ice melting device phase-locked loop dynamic model. , which may include generator power angle deviation (affecting electromagnetic output power), generator speed deviation, excitation voltage deviation, generator terminal voltage deviation, phase-locked loop output voltage deviation, grid node voltage deviation, grid voltage amplitude deviation and system frequency deviation, etc.; the corresponding input variables This can include phase-locked loop bandwidth parameter disturbances (phase detector gain deviation and VCO gain deviation) and external disturbances (including mechanical power deviation, active power deviation, and reactive power deviation). On this basis, the above-mentioned power grid dynamic model and the de-icing device phase-locked loop dynamic model are linearized and then integrated to obtain the complete state space equation:

[0100]

[0101] Where, and denote the state variable vector and input variable vector respectively; and Represents the state matrix and the input matrix; it should be noted that the above process of linearizing the power grid dynamic model and the de-icing device phase-locked loop dynamic model and integrating them to obtain the complete state space equation can be obtained by referring to the existing related technologies for linearizing nonlinear equations and merging linearized state equations in the small signal stability analytical model based on the state space method, which will not be described in detail here.

[0102] Based on the small-signal stability analytical model, the characteristic root loci corresponding to different phase-locked loop bandwidth parameters are calculated, and the corresponding oscillation mode damping ratio sequence and oscillation frequency sequence are obtained based on the characteristic root loci corresponding to different phase-locked loop bandwidth parameters. The characteristic root loci are the changing trajectories of the characteristic roots of the state matrix A corresponding to different phase-locked loop bandwidth parameters. The specific method for solving the characteristic roots of the state matrix can be implemented by referring to the relevant existing technologies. Assume that the characteristic root of the state matrix corresponding to a certain phase-locked loop bandwidth parameter is expressed as: ,and represents the characteristic root, and Represent the real and imaginary parts of the characteristic roots respectively; the corresponding damping ratio It can be expressed as: , oscillation frequency Expressed as: The oscillation mode damping ratio sequence and oscillation frequency sequence obtained in this embodiment can be understood as corresponding sequences obtained by arranging the damping ratios and oscillation frequencies obtained by solving for different phase-locked loop bandwidth parameters in ascending order according to the bandwidth parameters.

[0103] Multiple sets of stability characteristic data are generated based on different phase-locked loop bandwidth parameters and corresponding oscillation mode damping ratio sequences and oscillation frequency sequences; wherein the stability characteristic data can be understood as a feature vector that can be used for subsequent prediction and classification after splicing each phase-locked loop bandwidth parameter and the corresponding oscillation mode damping ratio and oscillation frequency, that is, the stability characteristic data includes the bandwidth parameter and the corresponding oscillation mode damping ratio and oscillation frequency.

[0104] Based on the support vector machine, multiple groups of stability characteristic data are classified and predicted to obtain corresponding stability prediction results; wherein, the support vector machine can be understood as a model that is pre-trained and constructed based on historically collected stability characteristic data and can be used for stability area classification and identification. The specific training process can refer to relevant existing technologies; different stability characteristic data are classified and predicted by the support vector machine to obtain different stability area classification results, that is, the stability prediction results include stable, critically stable and unstable.

[0105] Fitting analysis is performed on the stability characteristic data of different result types in the stability prediction results respectively to obtain the bandwidth parameter oscillation and damping relationship; wherein, the fitting analysis process can be understood as aggregating the stability characteristic data belonging to the same result type in the stability prediction results to perform fitting analysis on the data of a single result type to obtain the bandwidth parameter oscillation and damping relationship of the corresponding result type; the bandwidth parameter oscillation and damping relationship that can be finally obtained includes the bandwidth parameter oscillation and damping relationship corresponding to the stable result type, the critically stable result type and the unstable result type.

[0106] After obtaining the bandwidth parameter oscillation and damping relationship through the above method steps, you can use an existing power grid simulation platform (such as PSCAD or DIgSILENT) to build a system operation framework based on the actual topology and basic parameter settings of the power system. Then, based on the obtained bandwidth parameter oscillation and damping relationship combined with the dynamic characteristics and control theory of the power system, configure the power grid operation-related control parameters in the system operation framework to obtain the required power system simulation model. It should be noted that the specific process of building the power system simulation model can be implemented by referring to relevant existing technologies and will not be described in detail here.

[0107] This embodiment extracts and analyzes the output phase fluctuation characteristics corresponding to different phase-locked loop bandwidth parameters set for the phase-locked loop of the de-icing device under fault scenarios and obtains the correlation of phase fluctuation oscillation modes. Then, based on the state-space method, a small-signal stability analytical model of the dynamic coupling between the de-icing device and the power grid is constructed to perform stability analysis and extract the bandwidth parameter oscillation damping relationship. This can effectively capture the impact of different phase-locked loop bandwidth parameters on the system oscillation mode damping under fault scenarios, and provide reliable data support for the subsequent construction of a power system simulation model that can realistically simulate fault operation scenarios.

[0108] S13. Perform a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters based on the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship; wherein the bandwidth parameter transient response relationship can be understood as the influence of the de-icing device phase-locked loop bandwidth parameter on the system transient response duration under a fault condition of the power system including the de-icing device; and the bandwidth parameter stability boundary relationship can be understood as the influence of the de-icing device phase-locked loop bandwidth parameter on the system critical power angle value under a fault condition of the power system including the de-icing device.

[0109] In order to accurately capture the impact of the transient stability of the fault condition of the power system containing the de-icing device on the bandwidth parameters of the phase-locked loop of the de-icing device, this embodiment preferably studies and analyzes the transient response speed and critical power angle value under different phase-locked loop bandwidth parameters based on the post-fault electrical change data collected by the power system fault operation simulation to obtain a reliable bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship. Specifically, the steps of performing fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model to obtain the bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship include:

[0110] An initial operating environment is generated based on the power system simulation model and preset operating conditions; the preset operating conditions include line impedance and load power; wherein the initial operating environment can be understood as the normal operating environment of the power system obtained by performing relevant power flow calculations based on the power system simulation model and the corresponding preset operating conditions, and may include stable voltage distribution and stable current distribution.

[0111] A voltage sag fault is introduced in the initial operating environment. By adjusting the bandwidth parameter of the de-icing device's phase-locked loop (PLL), post-fault electrical variation data and system stability data are obtained under different PLL bandwidth parameters. A voltage sag fault can be understood as a fault that can cause a voltage sag in an actual power system, including short circuit faults (three-phase short circuit, two-phase short circuit, and single-phase ground fault), reactive power compensation equipment faults, and generator / transformer faults. Simulations can be conducted based on potential voltage sag faults that may occur during the operation of an AC system containing a grid-following de-icing device. For example, a single-phase fault occurrence node and fault duration are set in a simulation model of a normally operating power system. Then, by continuously adjusting the bandwidth parameter of the de-icing device's PLL (e.g., increasing the bandwidth parameter from 10 Hz to 50 Hz), post-fault electrical variation data corresponding to different PLL bandwidth parameters is collected for subsequent bandwidth parameter impact analysis. To ensure the effectiveness of the bandwidth parameter impact analysis, in this embodiment, the post-fault electrical variation data preferably includes voltage amplitude time series data and system frequency time series data.

[0112] Based on the post-fault electrical change data under different phase-locked loop bandwidth parameters, the corresponding oscillation decay time, voltage recovery time and frequency recovery time are calculated; the oscillation decay time can be understood as the time required for the system oscillation amplitude to decay to 1 / e of the initial value, which can reflect the system damping characteristics; the corresponding oscillation decay time can be based on the voltage amplitude time series data, through the voltage amplitude envelope obtained by Hilbert transform or moving average method Fitting analysis is performed to obtain: Indicates the voltage at time t after the fault; Indicates the voltage amplitude (per unit value) at the initial moment (t=0); represents the attenuation coefficient, and the corresponding oscillation decay time can be expressed as . The voltage recovery time can be understood as the time required for the voltage to recover from the lowest point of the fault to the recovery threshold (such as 90% of the voltage rating). The specific acquisition process may include obtaining the voltage minimum moment corresponding to the minimum voltage value after the fault based on the voltage amplitude timing data, and finding the first voltage recovery moment that meets the condition that the voltage value is greater than the recovery threshold, and then subtracting the voltage recovery moment from the voltage minimum moment to obtain the required voltage recovery time. The frequency recovery time can be understood as the time required for the system frequency to recover from the lowest point of the fault to a bit size near the rated frequency. The specific acquisition process may include obtaining the frequency minimum moment corresponding to the minimum frequency value after the fault based on the system frequency timing data, and finding the first frequency recovery moment that meets the condition that the frequency is within the preset threshold range of the normal frequency deviation, and then subtracting the frequency recovery moment from the frequency minimum moment to obtain the required frequency recovery time.

[0113] A weighted analysis is performed on the oscillation decay time, voltage recovery time, and frequency recovery time under different phase-locked loop bandwidth parameters to obtain the corresponding transient response speed. The transient response speed can be understood as a transient response index obtained by comprehensively analyzing the oscillation decay time, voltage recovery time, and frequency recovery time. It can be used to comprehensively and reliably evaluate the transient response efficiency of different phase-locked loop bandwidth parameters and is expressed as:

[0114]

[0115] Where, Indicates transient response speed; 、 and They represent oscillation decay time, voltage recovery time, and frequency recovery time respectively; 、 and Represents the weight coefficient.

[0116] Performing a correlation analysis between bandwidth parameters and transient response speeds according to transient response speeds of different phase-locked loop bandwidth parameters to obtain the bandwidth parameter transient response relationship;

[0117] According to the system stable state data under different phase-locked loop bandwidth parameters, transient power angle stability analysis is carried out based on the energy function method, and the stable boundary relationship of the bandwidth parameter is obtained.

[0118] The system stability data in this embodiment can be understood as system operation stability-related data collected by performing fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters based on the power system simulation model, which is convenient for transient power angle stability analysis, and preferably includes data such as power angle curves, voltage amplitudes, and frequency deviations. Specifically, the step of performing transient power angle stability analysis based on the energy function method according to the system stability data under different phase-locked loop bandwidth parameters to obtain the bandwidth parameter stability boundary relationship includes:

[0119] Energy analysis is performed on system steady-state data of different phase-locked loop bandwidth parameters according to a preset system potential energy function and a preset system kinetic energy function to obtain corresponding critical power angle values. The preset system potential energy function and the preset system kinetic energy function can be set based on the actual analyzed power system conditions and the energy analysis principle:

[0120] 1) The potential energy function of the preset system is expressed as:

[0121]

[0122] Where, express System potential energy at time represents the generator inertia time constant; Indicates the rated angular frequency; and Represent the power angle curve and steady-state power angle respectively.

[0123] 2) The preset system kinetic energy function is expressed as:

[0124]

[0125] Where, express System kinetic energy at a given moment; Indicates the speed deviation at time t.

[0126] Specifically, the step of performing energy analysis on system steady-state data of different phase-locked loop bandwidth parameters according to a preset system potential energy function and a preset system kinetic energy function to obtain corresponding critical power angle values ​​includes:

[0127] Based on the preset system potential energy function and the preset system kinetic energy function, the energy of the system stable state data under different phase-locked loop bandwidth parameters is calculated to obtain the corresponding critical energy threshold and system total energy. The critical energy threshold can be understood as the critical value of the total system energy that reaches instability, which is expressed as:

[0128]

[0129] Where, represents the critical energy threshold; represents the system inertia constant; Indicates the deviation of the system frequency from the rated frequency at the critical moment.

[0130] The total energy of the system is expressed as:

[0131]

[0132] Where, Represents the total energy of the system.

[0133] Data fitting analysis is performed on the critical energy thresholds and system total energy of different phase-locked loop bandwidth parameters to obtain the corresponding bandwidth parameter critical energy threshold expressions and bandwidth parameter system total energy expressions; among them, the bandwidth parameter critical energy threshold expression can be understood as the relationship expression between the bandwidth parameter and the critical energy threshold obtained by fitting analysis with the phase-locked loop bandwidth parameter and the system frequency deviation as independent variables and the critical energy threshold as the dependent variable; the bandwidth parameter system total energy expression can be understood as the relationship expression between the bandwidth parameter and the system total energy obtained by fitting analysis with the phase-locked loop bandwidth parameter and the power angle as independent variables and the system total energy as the dependent variable.

[0134] According to the bandwidth parameter critical energy threshold expression and the bandwidth parameter system total energy expression, the critical power angle values ​​of different phase-locked loop bandwidth parameters are obtained based on the Newton iteration method. In practical applications, the solution process of the critical power angle values ​​of different phase-locked loop bandwidth parameters can be understood as first combining the obtained bandwidth parameter critical energy threshold expression and the bandwidth parameter system total energy expression. Then, while fixing the phase-locked loop bandwidth parameter in the equation, the power angle variable value is continuously updated until the preset iteration termination condition is reached, and the obtained power angle variable value is used as the corresponding critical power angle value. The specific solution process can refer to the relevant implementation steps of the existing Newton iteration method, which will not be repeated here.

[0135] Data fitting analysis is performed based on the critical power angle values ​​corresponding to different phase-locked loop bandwidth parameters to obtain the bandwidth parameter stability boundary relationship; wherein the bandwidth parameter stability boundary relationship can be understood as a mathematical expression obtained by fitting with the phase-locked loop bandwidth parameter as the independent variable and the critical power angle value as the dependent variable.

[0136] S14. Based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a bandwidth parameter optimization model is constructed with balanced transient response efficiency and transient stability margin as optimization objectives. Balancing transient response efficiency and transient stability margin as optimization objectives can be understood as minimizing transient response time and maximizing critical power angle. Specifically, the bandwidth parameter optimization model is expressed as:

[0137]

[0138] Where, and They represent the bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship respectively; Indicates the stable power angle value; Indicates the bandwidth parameter of the phase-locked loop of the ice melting device; and Respectively represent the minimum and maximum values ​​of the bandwidth parameter; Represents the system damping ratio, which is related to the bandwidth parameter value as shown in the above analysis; and It represents the weight coefficient, which can be set as a fixed weight according to actual application requirements or as a dynamically adjustable weight according to requirements. There is no specific limitation here.

[0139] This embodiment uses the transient response speed obtained by comprehensively analyzing the oscillation decay time, voltage recovery time, and frequency recovery time as the basis for transient response efficiency analysis. A multi-objective optimization model, established using the critical power angle as a stability margin indicator, is used to select the optimal bandwidth parameter. This effectively improves the transient stability and fault response efficiency of the power system while ensuring the synchronization of the de-icing device in voltage sag scenarios.

[0140] S15. Solve the bandwidth parameter optimization model to obtain the optimal bandwidth parameter, and adjust the phase-locked loop of the ice-melting device according to the optimal bandwidth parameter. The optimal bandwidth parameter can be solved by using an existing multi-objective optimization algorithm to solve the bandwidth parameter optimization model. The selection of a specific target optimization algorithm can be determined based on actual application requirements and is not specifically limited here. After obtaining the corresponding optimal bandwidth parameter, the relevant variables affecting the bandwidth parameter can be adjusted directly based on the operating principle of the phase-locked loop of the ice-melting device according to the optimal bandwidth parameter. and Reasonable adjustments and settings are made so that the adjusted phase-locked loop of the ice melting device can meet the synchronization of the ice melting device under the voltage sag scenario, so as to ensure the smooth implementation of the ice melting service under the voltage sag fault scenario.

[0141] The embodiment of the present invention provides a system operation data set for obtaining a voltage sag fault scenario, including power grid operation data under different de-icing device phase-locked loop bandwidth parameters, de-icing device operation parameters, and phase-locked loop output signals. A correlation analysis between bandwidth parameters and system oscillation modes is performed based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship. After a power system simulation model is constructed based on the bandwidth parameter oscillation damping relationship, a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters is performed based on the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship. Based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a balanced transient response efficiency and transient stability margin are used as the basis. The optimization objective is to construct a bandwidth parameter optimization model, solve the bandwidth parameter optimization model to obtain the optimal bandwidth parameters, and adjust the de-icing device phase-locked loop according to the optimal bandwidth parameters. The technical solution is to construct a fault scenario simulation mechanism of the power system simulation model based on the bandwidth parameter oscillation damping relationship obtained by extracting and analyzing the output phase fluctuation characteristics of the de-icing device phase-locked loop under different phase-locked loop bandwidth parameters under fault scenarios. Combined with the multi-objective bandwidth parameter optimization design of balanced transient response efficiency and transient stability margin, reliable and efficient adjustment of the phase-locked loop bandwidth parameters is achieved, which can not only ensure the synchronization of the de-icing device under voltage sag scenarios, but also effectively improve the transient stability, fault response efficiency and operation robustness of the power system.

[0142] Furthermore, considering that after adjusting the phase-locked loop of the de-icing device based on the optimal bandwidth parameters, the actual power grid operation effect may not meet the expected operation target, in order to ensure that both the de-icing device and the power grid can continue to operate stably and safely in a voltage sag scenario, this embodiment preferably further tracks the adjusted power grid operation effect after adjusting the phase-locked loop of the de-icing device, and fine-tunes the optimal bandwidth parameters based on the actual operation effect. Specifically, the method further includes:

[0143] After the phase-locked loop of the ice-melting device is adjusted according to the optimal bandwidth parameters, real-time grid operation status data is obtained, and response speed and robustness simulation verification is performed based on the real-time grid operation status data. When the corresponding simulation verification results do not meet the preset targets, the optimal bandwidth parameters are adjusted; wherein, the response speed can be evaluated in combination using one or more indicators including voltage recovery time (for example, the time to recover from the lowest point of the disturbance to 95% of the rated value), frequency recovery time (for example, the length of time the frequency deviation enters the range of ±0.1Hz), and power angle recovery time (for example, the time required for the maximum power angle offset to decay to 50% of the steady-state value); robustness can be evaluated using indicators such as the maximum energy accumulation before the system becomes unstable, or the oscillation decay rate, calculated based on the energy function method.

[0144] In actual applications, after performing response speed and robustness simulation verification based on the real-time operating status data of the power grid to obtain the corresponding response speed evaluation value and robustness evaluation value, the response speed evaluation value and the robustness evaluation value can be weighted and summed to obtain the final simulation verification result (score value); the corresponding preset target can be set based on the quantification method of the actual simulation verification result. If the simulation verification result is a comprehensive score value, the preset target can be a minimum score threshold set based on the actual application requirements. When the simulation verification result is less than the minimum score threshold, it is considered that the preset target has not been achieved and the optimal bandwidth parameter needs to be fine-tuned. The specific fine-tuning ratio and method can be selected based on the actual application requirements and are not specifically limited here. It should be noted that after fine-tuning the optimal bandwidth parameter, the above method can still be used to simulate and verify the response speed and robustness of the fine-tuned real-time operating status data of the power grid to ensure the operating effect of the fine-tuned power system.

[0145] The embodiment of the present invention obtains a system operation data set including power grid operation data under different de-icing device phase-locked loop bandwidth parameters, de-icing device operation parameters and phase-locked loop output signals in a voltage sag fault scenario, performs a correlation analysis between bandwidth parameters and system oscillation modes according to the system operation data set to obtain a bandwidth parameter oscillation damping relationship, and constructs a power system simulation model according to the bandwidth parameter oscillation damping relationship. Then, a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters is performed according to the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship, and constructs a power system simulation model based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship with a balanced transient response efficiency and a transient stability margin as an optimization target. A bandwidth parameter optimization model is established, and the bandwidth parameter optimization model is solved to obtain the optimal bandwidth parameters. The phase-locked loop of the ice melting device is adjusted according to the optimal bandwidth parameters. After the phase-locked loop of the ice melting device is adjusted according to the optimal bandwidth parameters, the response speed and robustness simulation verification of the real-time operation status data of the power grid is obtained. When the corresponding simulation verification result does not meet the preset target, the optimal bandwidth parameter is adjusted. This technical solution can not only ensure the synchronization of the ice melting device under the voltage sag scenario, but also effectively improve the transient stability, fault response efficiency and operation robustness of the power system, and can also continuously maintain the stable and safe operation of the ice melting device and the power grid after the fault is restored, thereby providing reliable technical support for the development of ice melting business in the power grid in high-altitude and cold areas.

[0146] It should be noted that although the steps in the above flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0147] In one embodiment, Figure 2As shown, a transient stability optimization system for an AC system including a grid-following ice melting device is provided, the system comprising:

[0148] Data acquisition module 1, used to obtain a system operation data set for a voltage sag fault scenario; the system operation data set includes power grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters;

[0149] A simulation model construction module 2 is used to perform a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set, obtain a bandwidth parameter oscillation damping relationship, and construct a power system simulation model based on the bandwidth parameter oscillation damping relationship;

[0150] Simulation analysis module 3, used to perform fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model, and obtain the bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship;

[0151] An optimization model construction module 4 is configured to construct a bandwidth parameter optimization model based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, with the balanced transient response efficiency and transient stability margin as the optimization goal;

[0152] The bandwidth parameter optimization module 5 is used to solve the bandwidth parameter optimization model to obtain the optimal bandwidth parameter and adjust the phase-locked loop of the ice melting device according to the optimal bandwidth parameter.

[0153] Regarding the specific definition of the AC system transient stability optimization system including a grid-type ice melting device, please refer to the definition of the AC system transient stability optimization method including a grid-type ice melting device above. The corresponding technical effects can also be obtained equivalently, and will not be repeated here. Each module in the above-mentioned AC system transient stability optimization system including a grid-type ice melting device can be implemented in whole or in part through software, hardware, and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0154] In summary, an embodiment of the present invention provides an AC system transient stability optimization method and system containing a grid-following ice melting device. The AC system transient stability optimization method containing a grid-following ice melting device realizes obtaining a system operation data set including grid operation data under different ice melting device phase-locked loop bandwidth parameters, ice melting device operation parameters and phase-locked loop output signals in a voltage sag fault scenario, performs correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship, and constructs a power system simulation model based on the bandwidth parameter oscillation damping relationship. Then, a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters is performed based on the power system simulation model to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship. Based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a bandwidth parameter optimization model is constructed with balanced transient response efficiency and transient stability margin as optimization goals, and the bandwidth parameter optimization model is solved to obtain the optimal bandwidth parameter. The optimal bandwidth parameter is adjusted for the phase-locked loop (PLL) of the de-icing device. After the PLL is adjusted according to the optimal bandwidth parameter, the response speed and robustness of the real-time operation status data of the power grid are simulated and verified. When the corresponding simulation verification result does not meet the preset target, the optimal bandwidth parameter is adjusted again. The method constructs a fault scenario simulation mechanism of the power system simulation model based on the bandwidth parameter oscillation damping relationship obtained by extracting and analyzing the output phase fluctuation characteristics of the PLL of the de-icing device under different PLL bandwidth parameters. Combined with the multi-objective bandwidth parameter optimization design that balances transient response efficiency and transient stability margin and the feedback adjustment optimization mechanism after bandwidth parameter adjustment, it can not only ensure the synchronization of the de-icing device under voltage sag scenarios, but also effectively improve the transient stability, fault response efficiency and operation robustness of the power system. It can also continuously maintain the stable and safe operation of the de-icing device and the power grid after fault recovery, thereby providing reliable technical support for the development of de-icing services in power grids in high-altitude and cold areas.

[0155] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the various technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0156] The above-described embodiments merely represent several preferred implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art can make several improvements and substitutions without departing from the technical principles of the present invention, and such improvements and substitutions should also be considered within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be based on the scope of protection of the claims.

Claims

1. A method for optimizing the transient stability of an AC system including a grid-type ice melting device, characterized in that: The method comprises the following steps: Acquire a system operation data set for a voltage sag fault scenario; the system operation data set includes power grid operation data, ice melting device operation parameters, and phase-locked loop output signals under different ice melting device phase-locked loop bandwidth parameters; performing a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain a bandwidth parameter oscillation damping relationship, and constructing a power system simulation model based on the bandwidth parameter oscillation damping relationship; According to the power system simulation model, a fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters is performed to obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship, including: generating an initial operating environment according to the power system simulation model and preset operating conditions; wherein the initial operating environment includes a stable voltage distribution and a stable current distribution; A voltage sag fault is introduced in the initial operating environment, and post-fault electrical change data and system stable state data under different phase-locked loop bandwidth parameters are obtained by adjusting the bandwidth parameters of the phase-locked loop of the ice melting device; the post-fault electrical change data includes voltage amplitude time series data and system frequency time series data; the system stable state data includes a power angle curve, voltage amplitude, and frequency deviation; Based on the post-fault electrical change data under different PLL bandwidth parameters, the corresponding oscillation decay time, voltage recovery time and frequency recovery time are calculated; The oscillation decay time, voltage recovery time and frequency recovery time under different phase-locked loop bandwidth parameters are weightedly analyzed to obtain the corresponding transient response speed; Performing a correlation analysis between bandwidth parameters and transient response speeds according to transient response speeds of different phase-locked loop bandwidth parameters to obtain the bandwidth parameter transient response relationship; Based on the system stable state data under different phase-locked loop bandwidth parameters, transient power angle stability analysis is performed based on the energy function method to obtain the bandwidth parameter stability boundary relationship, including: performing energy analysis on the system stable state data with different phase-locked loop bandwidth parameters according to a preset system potential energy function and a preset system kinetic energy function to obtain corresponding critical power angle values; performing data fitting analysis based on the critical power angle values ​​corresponding to different phase-locked loop bandwidth parameters to obtain the bandwidth parameter stability boundary relationship; According to the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, a bandwidth parameter optimization model is constructed with balanced transient response efficiency and transient stability margin as optimization goals; The bandwidth parameter optimization model is solved to obtain the optimal bandwidth parameter, and the phase-locked loop of the ice melting device is adjusted according to the optimal bandwidth parameter.

2. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 1, wherein: The grid operation data includes voltage fluctuation data, current fluctuation data, and frequency deviation data; the de-icing device operation parameters include DC de-icing current value and operation time; and the step of performing correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set to obtain the bandwidth parameter oscillation damping relationship includes: The correlation between phase fluctuation and oscillation mode is analyzed based on the grid operation data, ice melting device operation parameters and phase-locked loop output signal under different ice melting device phase-locked loop bandwidth parameters, and the correlation degree of phase fluctuation and oscillation mode is obtained. When the correlation degree of the phase fluctuation oscillation mode reaches a preset correlation level, correlation analysis between bandwidth parameters and oscillation mode damping is performed according to bandwidth parameters of different ice melting devices phase-locked loops to obtain a bandwidth parameter oscillation damping relationship.

3. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 2, wherein: The step of analyzing the correlation between phase fluctuation and oscillation mode based on grid operation data, ice melting device operation parameters, and phase locked loop output signals under different ice melting device phase locked loop bandwidth parameters to obtain the correlation between phase fluctuation and oscillation mode includes: According to the phase-locked loop output signal under different phase-locked loop bandwidth parameters of the ice melting device, the corresponding output phase sequence is obtained; Generate a corresponding phase fluctuation characteristic spectrum according to the output phase sequence and fast Fourier transform, and obtain a corresponding key frequency component according to the phase fluctuation characteristic spectrum; Matching and analyzing the key frequency component with a preset system oscillation mode frequency range to obtain a main oscillation component; Obtaining a correlation index based on a deviation between the main oscillation component and an average value of the preset system oscillation mode frequency range, and determining whether the correlation index is less than a preset index threshold; If not, the phase fluctuation oscillation mode correlation is set to a preset correlation value; otherwise, the output phase sequence is decomposed by wavelet transform to obtain a corresponding low-frequency oscillation component; Calculating a corresponding low-frequency component energy according to the low-frequency oscillation component, and obtaining a key influencing factor according to the low-frequency component energy, the grid operation data, and the ice melting device operation parameters; According to the key influencing factors under different de-icing device phase-locked loop bandwidth parameters, oscillation mode classification and prediction are performed based on support vector machine, and the correlation degree of the phase fluctuation oscillation mode is obtained based on SHAP attribution analysis.

4. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 2, wherein: The step of analyzing the correlation between bandwidth parameters and oscillation mode damping according to bandwidth parameters of phase-locked loops of different ice melting devices to obtain the oscillation damping relationship of bandwidth parameters includes: The phase fluctuation sequence and voltage amplitude sequence corresponding to the phase-locked loop output signal under different phase-locked loop bandwidth parameters of the ice melting device are obtained respectively; According to the phase-locked loop bandwidth parameters of different ice melting devices and the corresponding phase fluctuation sequence and voltage amplitude sequence, the corresponding small signal stability analytical model is constructed based on the state space method. Calculating characteristic root trajectories corresponding to different phase-locked loop bandwidth parameters according to the small-signal stability analytical model, and obtaining corresponding oscillation mode damping ratio sequences and oscillation frequency sequences according to the characteristic root trajectories corresponding to the different phase-locked loop bandwidth parameters; Generating multiple sets of stability characteristic data according to different phase-locked loop bandwidth parameters and corresponding oscillation mode damping ratio sequences and oscillation frequency sequences; the stability characteristic data including the bandwidth parameters and the corresponding oscillation mode damping ratio and oscillation frequency; Based on the support vector machine, multiple groups of stability feature data are classified and predicted to obtain corresponding stability prediction results; the stability prediction results include stable, critically stable and unstable; Fitting and analyzing the stability characteristic data of different result types in the stability prediction results are performed respectively to obtain the bandwidth parameter oscillation and damping relationship; the bandwidth parameter oscillation and damping relationship includes bandwidth parameter oscillation and damping relationships corresponding to different result types.

5. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 1, wherein: The step of performing energy analysis on system steady state data of different phase-locked loop bandwidth parameters according to the preset system potential energy function and the preset system kinetic energy function to obtain corresponding critical power angle values ​​includes: According to the preset system potential energy function and the preset system kinetic energy function, energy calculation is performed on the system steady state data under different phase-locked loop bandwidth parameters to obtain the corresponding critical energy threshold and system total energy; According to the critical energy threshold and system total energy of different phase-locked loop bandwidth parameters, data fitting analysis is performed respectively to obtain the corresponding bandwidth parameter critical energy threshold expression and bandwidth parameter system total energy expression; According to the bandwidth parameter critical energy threshold expression and the bandwidth parameter system total energy expression, critical power angle values ​​of different phase-locked loop bandwidth parameters are obtained based on the Newton iteration method.

6. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 1, wherein: The bandwidth parameter optimization model is expressed as: Where, and They represent the bandwidth parameter transient response relationship and bandwidth parameter stability boundary relationship respectively; Indicates the stable power angle value; Indicates the bandwidth parameter of the phase-locked loop of the ice melting device; and Respectively represent the minimum and maximum values ​​of the bandwidth parameter; represents the system damping ratio; and Represents the weight coefficient.

7. The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 1, wherein: The method further comprises: After the phase-locked loop of the ice-melting device is adjusted according to the optimal bandwidth parameters, real-time power grid operation status data is obtained, and response speed and robustness simulation verification is performed based on the real-time power grid operation status data. When the corresponding simulation verification results do not meet the preset targets, the optimal bandwidth parameters are adjusted.

8. An AC system transient stability optimization system including a grid-type ice melting device, characterized in that: The method for optimizing transient stability of an AC system including a grid-type ice melting device according to claim 1 is applied, wherein the system comprises: A data acquisition module is used to obtain a system operation data set for a voltage sag fault scenario; the system operation data set includes power grid operation data under different de-icing device phase-locked loop bandwidth parameters, de-icing device operation parameters, and phase-locked loop output signals; a simulation model construction module, configured to perform a correlation analysis between bandwidth parameters and system oscillation modes based on the system operation data set, obtain a bandwidth parameter oscillation damping relationship, and construct a power system simulation model based on the bandwidth parameter oscillation damping relationship; A simulation analysis module is used to perform fault operation simulation analysis of the power system under different phase-locked loop bandwidth parameters according to the power system simulation model, and obtain a bandwidth parameter transient response relationship and a bandwidth parameter stability boundary relationship; An optimization model construction module is used to construct a bandwidth parameter optimization model based on the bandwidth parameter stability boundary relationship and the bandwidth parameter transient response relationship, with the balanced transient response efficiency and transient stability margin as the optimization goal; The bandwidth parameter optimization module is used to solve the bandwidth parameter optimization model to obtain the optimal bandwidth parameter and adjust the phase-locked loop of the ice melting device according to the optimal bandwidth parameter.

Images