Electromechanical-electromagnetic simulation time domain data resampling method and system capable of retaining time-frequency domain characteristics

Abstract

The invention discloses an electromechanical-electromagnetic simulation time domain data resampling method and an electromechanical-electromagnetic simulation time domain data resampling system capable of reserving time-frequency domain characteristics. Comprising the following steps: constructing electromechanical and electromagnetic transient time sequence track samples of a new energy power grid system; respectively processing the trajectory samples by using an improved Proni method to obtain frequency domain response features; based on frequency domain response characteristics, reconstructing electromechanical and electromagnetic transient time sequence tracks by using linear interpolation and an adaptive resampling technology; and fusing the time domain features and the frequency domain features in the reconstructed time sequence trajectory data to form a comprehensive feature vector, and obtaining electromechanical-electromagnetic simulation time domain data with the time domain features and the frequency domain features reserved. The asynchronous sampling problem of electromechanical-electromagnetic time domain simulation data is solved, the method can be used for supporting characteristic analysis of a system on non-consistent data under different electromechanical and electromagnetic time scales, and the method has wide application prospects and important practical significance in the fields of scheduling and control of a new energy power grid and the like.

Description

Technical Field

[0001] The present invention belongs to the field of energy technology, and relates to a method and system for resampling time-domain data of electromechanical-electromagnetic simulation, and in particular to a method and system for resampling time-domain data of electromechanical-electromagnetic simulation that retains time-frequency domain characteristics. Background Art

[0002] The time domain simulation of the power system with a high proportion of new energy access (hereinafter referred to as the new energy system) includes electromechanical transient simulation and electromagnetic transient simulation. Electromechanical transient simulation supports rapid simulation of power grids with tens of thousands of nodes, with a step size of milliseconds, which is suitable for stable analysis of the fundamental frequency characteristics of the power grid, but it is difficult to reflect the high-frequency characteristics of new energy and power electronic equipment; while electromagnetic transient simulation supports accurate characterization of the high-frequency characteristics of power electronic equipment, with a step size of microseconds, but its high-order nature makes it difficult to adapt to the full-grid simulation of a certain scale system. Combining the respective advantages of electromechanical and electromagnetic simulation data, the scope of application of existing advanced applications based on the electromechanical transient platform can be improved, and a more refined safety and stability assessment of power grids with a high proportion of new energy can be achieved.

[0003] In practice, due to differences in time scales and iterative solution algorithms, even with the same simulation duration, the resolution and sampling window of the time series data generated by electromagnetic and electromechanical simulations are quite different, which makes it impossible to directly compare the time series trajectories of electromagnetic and electromechanical simulations, affecting subsequent modeling and research work. In addition, the current resampling technology based on the difference algorithm is prone to losing important information and cannot reflect the key time-frequency domain characteristics of the data, which has certain limitations. Summary of the invention

[0004] To solve the above problems, the present invention proposes a method and system for resampling time-domain data of electromechanical-electromagnetic simulation that retains time-frequency domain characteristics, which can effectively unify the sampling of electromagnetic and electromechanical simulation time series, and at the same time retain the time-frequency domain characteristics of the time series trajectories generated by the two simulations. The present invention can be used to support the system's preprocessing and feature analysis of low-consistency data at different time scales of electromechanical and electromagnetic, and also has broad application prospects and important practical significance in the fields of dispatching and control of new energy power grids.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for resampling time domain data of electromechanical-electromagnetic simulation that retains time-frequency domain characteristics comprises the following steps:

[0007] S1. Based on the electromagnetic simulation platform and the electromechanical simulation platform, construct electromechanical and electromagnetic transient time series trajectory samples of the new energy power grid system;

[0008] S2. Use the improved Proni method to process the electromechanical and electromagnetic transient time series trajectory samples respectively to obtain the frequency domain response characteristics of the electromechanical and electromagnetic transient time series trajectory samples;

[0009] S3. Based on the frequency domain response characteristics, the electromechanical and electromagnetic transient time series trajectories are reconstructed using linear interpolation and adaptive resampling techniques to obtain electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain characteristics;

[0010] S4. The time domain features and frequency domain features in the electromechanical and electromagnetic transient reconstruction time series trajectory data are integrated to form a comprehensive feature vector, and the electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features is obtained.

[0011] Furthermore, step S1 is specifically as follows:

[0012] On the electromechanical transient simulation platform, the electromechanical transient modeling of the new energy power grid system is established, the simulation step size and the total simulation time are set, the basic wave vector is used to describe the calculation element model, and the differential algebraic equations are obtained. The differential algebraic equations are solved simultaneously to obtain the time domain solutions of various physical quantities; various typical operating conditions and typical faults of the new energy power grid system are traversed to obtain electromechanical transient timing trajectory samples;

[0013] The electromagnetic transient modeling of the new energy power grid system is carried out on the electromagnetic transient simulation platform. The simulation step size and the total simulation time are set. The abc three-phase instantaneous value is used to describe the calculation element model to obtain a group of differential equations. The implicit integration method is used to solve the group of differential equations to obtain the time domain solutions of various physical quantities. Various typical operating conditions and typical faults of the new energy power grid system are traversed to obtain the electromagnetic transient time series trajectory samples.

[0014] Furthermore, step S2 is specifically as follows:

[0015] For the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample, the following steps are performed:

[0016] S2.1. According to the fault occurrence and duration set during the simulation, data from the fault occurrence to the steady state in the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample is intercepted to obtain a fault timing trajectory sample, and the plurality of fault timing trajectory samples form a fault timing trajectory sample set;

[0017] S2.2. Initialize the time window and Prony order of the Prony method based on the fault time scale and oscillation frequency band;

[0018] S2.3. Divide the waveform data of the fault timing trajectory sample in each time window into two sections, wherein the first section of waveform data is data from the occurrence of the fault to the fault recovery, and the second section of waveform data is data after the fault returns to a steady state;

[0019] S2.4. Analyze the second waveform data using the Prony method, identify the linear oscillation mode without resonance in the second waveform data, and obtain its frequency as the initial value of the frequency domain result;

[0020] S2.5. Fit the initial value of the frequency domain result to the first segment of waveform data, use the Prony method to analyze the fitted first segment of waveform data, identify the second-order resonance mode caused by the nonlinear model after the fault occurs, and obtain the frequency domain response characteristics of each fault timing trajectory sample.

[0021] Furthermore, step S3 is specifically as follows:

[0022] S3.1. Determine the resampling frequency of each time window according to the frequency domain response characteristics using the Nyquist sampling theorem;

[0023] S3.2. Calculate the complete sampling length K of the electromagnetic transient time series trajectory according to the resampling frequency of each time window;

[0024] S3.3. Linearly interpolate the electromechanical transient time series trajectory according to the sampling step of each time window in the electromagnetic transient time series trajectory to obtain an electromechanical transient time series trajectory corresponding to the sampling points of the electromagnetic transient time series trajectory;

[0025] S3.4. Using the adaptive resampling technology, the electromagnetic transient timing trajectory and the electromechanical transient timing trajectory are resampled according to the resampling frequency and the complete sampling length to obtain an electromechanical transient sequence and an electromagnetic transient sequence with a length of K.

[0026] Furthermore, step S4 is specifically as follows:

[0027] S4.1. Deleting redundant samples and abnormal data in the electromechanical transient sequence or the electromagnetic transient sequence;

[0028] S4.2 performing Z-score normalization processing on the time domain characteristics and frequency domain characteristics of the electrical transient sequence or the electromagnetic transient sequence;

[0029] S4.3 performs weighted fusion on the time domain features and the frequency domain features to form a time comprehensive feature vector, and obtains electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features.

[0030] Furthermore, the time domain features and the frequency domain features are weightedly fused as follows: the time domain feature weights are calculated according to the oscillation energy, the frequency domain feature weights are calculated according to the spectrum energy, and the time domain features and the frequency domain features are weightedly summed to form a comprehensive feature vector.

[0031] A time domain data resampling system for electromechanical-electromagnetic simulation retaining time and frequency domain characteristics, comprising:

[0032] Data acquisition module: used to obtain electromechanical and electromagnetic transient time sequence trajectory samples for building new energy power grid systems based on electromagnetic simulation platforms and electromechanical simulation platforms;

[0033] Feature acquisition module: used to process the electromechanical and electromagnetic transient time series trajectory samples respectively using the improved Proni method to obtain the frequency domain response characteristics of the electromechanical and electromagnetic transient time series trajectory samples;

[0034] Trajectory reconstruction module: It is used to reconstruct the electromechanical and electromagnetic transient time series trajectory respectively based on the frequency domain response characteristics by using linear interpolation and adaptive resampling technology to obtain the electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain characteristics;

[0035] Feature fusion module: used to fuse the time domain features and frequency domain features in the electromechanical and electromagnetic transient reconstruction time series trajectory data to form a comprehensive feature vector, and obtain the electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features.

[0036] A computer device, comprising:

[0037] one or more processors;

[0038] A memory for storing one or more programs;

[0039] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned electromechanical-electromagnetic simulation time domain data resampling method that retains time-frequency domain characteristics.

[0040] A computer-readable storage medium storing computer instructions, when the computer instructions are executed by one or more processors, causes the one or more processors to execute the steps in the above method.

[0041] The beneficial effects of the present invention are:

[0042] The present invention provides a method for resampling electromechanical-electromagnetic simulation time domain data with preserved time and frequency domain features, wherein the frequency domain response features of electromechanical and electromagnetic transient time series trajectory samples are calculated by using an improved Prony method, and based on the frequency domain response features, the electromechanical and electromagnetic transient time series trajectories are respectively reconstructed by using linear interpolation and adaptive resampling techniques to obtain electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain features, and this step focuses on analyzing the occurrence time of the peak points of the electromagnetic transient trajectory, and the electromechanical transient corresponding points are supplemented by adaptive resampling to ensure that the time and frequency domain information of the mutation period after the fault is not lost; the time domain features and the frequency domain features in the electromechanical and electromagnetic transient reconstructed time series trajectory data are fused to form a comprehensive feature vector, and the electromechanical-electromagnetic simulation time domain data with preserved time and frequency domain features is obtained, and the comprehensive feature vector can be directly used for subsequent analysis and processing such as mapping and stability analysis of the electromechanical-electromagnetic trajectory, and can overcome the problem that the electromagnetic and electromechanical simulation time series trajectories cannot be compared due to differences in time scales and iterative solution algorithms. The present invention proposes a time-domain data resampling technology for electromechanical-electromagnetic simulation that retains time-domain characteristics, thereby solving the asynchronous sampling problem and time-domain characteristic analysis problem of electromechanical-electromagnetic time-domain sampling data. This technology can be used to support the system's characteristic analysis of non-consistent data at different time scales of electromechanical and electromagnetic, and has broad application prospects and important practical significance in the fields of stability and control of new energy power grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flow chart of the resampling method in an embodiment of the present invention.

[0044] Figure 2 This is a flow chart of the analysis and calculation of the improved Prony method in an embodiment of the present invention.

[0045] Figure 3 This is a time domain fitting result diagram of the Prony method in an embodiment of the present invention.

[0046] Figure 4 It is a frequency domain characteristic diagram of the Prony method in an embodiment of the present invention.

[0047] Figure 5 This is a diagram of the time domain resampling result based on the Prony method in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] The present invention proposes a method for resampling time domain data of electromechanical-electromagnetic simulation that retains time-frequency domain characteristics, which solves the problem that the new energy grid is difficult to apply to the original electromechanical and electromagnetic simulation under the background of increasing penetration rate of new energy. The flow chart is as follows Figure 1 shown.

[0050] The specific steps of this method are:

[0051] like Figure 1 As shown, a method for resampling time domain data of electromechanical-electromagnetic simulation that retains time-frequency domain characteristics includes the following steps:

[0052] S1. Based on the electromagnetic simulation platform and the electromechanical simulation platform, construct the electromechanical and electromagnetic transient time series trajectory samples of the new energy power grid system to form an electromechanical-electromagnetic time domain asynchronous data set that can characterize the dynamic response characteristics of the system at different time scales; specifically:

[0053] On the electromechanical transient simulation platform, the electromechanical transient modeling of the new energy power grid system is established, the simulation step size and the total simulation time are set, the basic wave vector is used to describe the calculation element model, and the differential algebraic equations are obtained. The differential algebraic equations are solved simultaneously to obtain the time domain solutions of various physical quantities; various typical operating conditions and typical faults of the new energy power grid system are traversed to obtain electromechanical transient timing trajectory samples;

[0054] The electromagnetic transient modeling of the new energy power grid system is carried out on the electromagnetic transient simulation platform. The simulation step size and the total simulation time are set. The abc three-phase instantaneous value is used to describe the calculation element model to obtain a group of differential equations. The implicit integration method is used to solve the group of differential equations to obtain the time domain solutions of various physical quantities. Various typical operating conditions and typical faults of the new energy power grid system are traversed to obtain the electromagnetic transient time series trajectory samples.

[0055] Assuming that the effective simulation time of electromechanical transient and electromagnetic transient is T, for the electromagnetic transient model, record the three-phase instantaneous value v of voltage and current at any time of each renewable energy grid connection point sabc 、i abc , effective value of voltage and current V s emt (t) And grid-connected active and reactive power, for the electromechanical transient model, measure the voltage and current amplitude V at each renewable energy grid-connected point at any time s rms (t)

[0056]

[0057]

[0058] In the formula, Δt emt and Δt rms are the simulation steps of electromagnetic transient and electromechanical transient simulation, V s rms (k×Δt emt )and They are the kth sampling values ​​in the electromagnetic transient voltage trajectory and the electromechanical transient current trajectory respectively.

[0059] S2. The electromechanical and electromagnetic transient time series trajectory samples are processed respectively by using the improved Prony method to obtain the frequency domain response characteristics of the electromechanical and electromagnetic transient time series trajectory samples;

[0060] Using complex exponential decay linear combinations to fit equally spaced sampled data, the Prony method assumes that the signal It is a combination of a series of exponential functions with arbitrary amplitude, phase, frequency and attenuation factor:

[0061]

[0062] Where N is the number of attenuated sine and cosine signal components, A i is the amplitude, θ i is the phase (rad), α i is the attenuation factor, f i is the oscillation frequency (HZ). Expand the cosine through Euler's formula, and the discrete function is as follows:

[0063]

[0064] In the formula, is the signal estimation value at the nth sampling time point, p is the number of complex exponential components, is the i-th decaying complex exponential component, b i is the i-th complex linear coefficient. Fit a homogeneous solution of a linear difference equation with constant coefficients and solve for the Prony pole z i , use the following formula to calculate the amplitude A i , phase θ i , attenuation factor α i , frequency f i and damping ratio ξ i :

[0065]

[0066] like Figure 2 As shown, the specific steps are:

[0067] For the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample, the following steps are performed:

[0068] S2.1. According to the fault occurrence and duration set during simulation, the initial time of the electromechanical and electromagnetic timing data is set as the fault time, and the data from the fault occurrence to the steady state in the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample is intercepted to ensure that the key time nodes in the electromechanical and electromagnetic timing trajectories correspond one to one, and the fault timing trajectory samples are obtained. The plurality of fault timing trajectory samples form a fault timing trajectory sample set;

[0069] S2.2. Initialize the time window and Prony order of the Prony method based on the fault time scale and oscillation frequency band;

[0070] S2.3. Divide the waveform data of the fault timing trajectory sample in each time window into two sections, wherein the first section of waveform data is data from the occurrence of the fault to the fault recovery, and the second section of waveform data is data after the fault returns to a steady state;

[0071] S2.4. Analyze the second waveform data using the Prony method, identify the linear oscillation mode without resonance in the second waveform data, and obtain its frequency as the initial value of the frequency domain result;

[0072] S2.5. Fit the initial value of the frequency domain result to the first segment of waveform data, and use the Prony method to analyze the fitted first segment of waveform data to identify the second-order resonance mode caused by the nonlinear model after the fault occurs, that is, the frequency domain response result to the large signal, thereby improving the fitting accuracy of the signal extreme point in the initial stage of the fault, and obtaining the frequency domain response characteristics of each of the fault timing trajectory samples.

[0073] S3. Based on the frequency domain response characteristics, the electromechanical and electromagnetic transient time series trajectories are reconstructed using linear interpolation and adaptive resampling techniques, and the key fault nodes and extreme points are supplemented and corrected to obtain the electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain characteristics; specifically:

[0074] S3.1. Determine the resampling frequency of each time window according to the frequency domain response characteristics using the Nyquist sampling theorem; for simulation steps Δt emt and Δt rms The electromagnetic and electromechanical transient time series data can be regarded as two discrete signals sampled at equal intervals. The above-mentioned Prony algorithm is used to solve the complex exponential decay linear combination that can fit its corresponding continuous signal, and the resampling frequency of the electromechanical-electromagnetic time series data is determined according to the complex exponential frequency.

[0075] Since electromechanical transient time series data often does not contain high-frequency components, the maximum frequency component of the key oscillation mode of the electromagnetic simulation time series trajectory in the Prony window is assumed to be f m According to the Nyquist sampling theorem, the minimum sampling frequency f is obtained by retaining the complete frequency domain information of the original signal. s Need to meet:

[0076] f s =2*f m

[0077] S3.2. Calculate the complete sampling length K of the electromagnetic transient time series trajectory according to the resampling frequency of each time window; the complete sampling length K of the electromagnetic simulation time series trajectory is calculated using the following formula:

[0078]

[0079] Among them, T prony is the time window for Prony calculation of electromagnetic and electromechanical sequences, f s (i) is the sampling frequency of the i-th Prony sampling window. S3.3. Linearly interpolate the electromechanical transient time series trajectory according to the sampling step size of each time window in the electromagnetic transient time series trajectory to obtain an electromechanical transient time series trajectory that corresponds one-to-one to the sampling points of the electromagnetic transient time series trajectory;

[0080] S3.4. Using the adaptive resampling technology, the electromagnetic transient time sequence trajectory and the electromechanical transient time sequence trajectory are resampled according to the resampling frequency and the complete sampling length to obtain an electromechanical transient sequence X and an electromagnetic transient sequence Y both of length K:

[0081] X=[x (1) ,…,x (K) ]

[0082] Y=[y (1) ,…,y (K) ].

[0083] S4. Fuse the time domain features and frequency domain features in the electromechanical and electromagnetic transient reconstruction time series trajectory data to form a comprehensive feature vector, and obtain electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features. Specifically:

[0084] S4.1. Deleting redundant samples and abnormal data in the electromechanical transient sequence or the electromagnetic transient sequence;

[0085] S4.2 performing Z-score normalization processing on the time domain features and frequency domain features of the electrical transient sequence or the electromagnetic transient sequence to eliminate differences between different feature dimensions;

[0086] S4.3 weightedly fuse the time domain features and the frequency domain features to form a time comprehensive feature vector, and obtain electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features. The weighted fusion of the time domain features and the frequency domain features is specifically as follows: the time domain feature weight is calculated according to the oscillation energy, the frequency domain feature weight is calculated according to the spectrum energy, and the time domain features and the frequency domain features are weightedly summed to form a comprehensive feature vector.

[0087] A specific embodiment of the present invention is as follows:

[0088] The effectiveness of the proposed method is verified in the electromechanical-electromagnetic simulation sampling data of a high-proportion renewable energy power grid. Electromechanical and electromagnetic transient simulations are performed on the system under various working conditions and fault scenarios. The fault is set to a three-phase ground short circuit fault. The circuit breaker is actuated 0.1s after the fault to cut off the fault line. For electromechanical simulation, the maximum power angle difference, the lowest bus voltage and the highest bus frequency of the system are recorded at each moment, and the sampling step is ΔT=10ms. For electromagnetic simulation, the sampling step is ΔT=10ms, and the voltage, current, active and reactive power of each renewable energy grid connection point are recorded. The parameter settings of the Prony algorithm are shown in Table 1.

[0089] Table 1 Prony algorithm parameter settings

[0090]

[0091] The Prony sliding window size is set to 0.5s, the oscillation frequency range of interest is 0-100HZ, and the Prony frequency domain calculation results of the electromagnetic transient time series trajectory are shown in Table 2, where the lowest oscillation frequency is 2.39HZ and the highest oscillation frequency is 77.06HZ.

[0092] Table 2 Prony frequency domain calculation results

[0093]

[0094]

[0095] Figure 3 The fitting effect of frequency domain analysis on time series data is given. Figure 4 The frequency domain Bode diagram and the frequency domain characteristics of the signal are given. The resampled time series data is as follows Figure 5 As shown in the results, it can be seen that the method designed by the present invention can accurately analyze the frequency domain characteristics of the system at different electromechanical and electromagnetic scales.

[0096] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented 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.

[0097] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 Process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0100] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0101] The above specific implementation modes are used to explain the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A method for resampling time-domain data in electromechanical-electromagnetic simulation that retains time-frequency domain characteristics, characterized in that: The following steps are involved: S1. Based on the electromagnetic simulation platform and the electromechanical simulation platform, construct electromechanical and electromagnetic transient time series trajectory samples of the new energy power grid system; S2. Use the improved Proni method to process the electromechanical and electromagnetic transient time series trajectory samples respectively to obtain the frequency domain response characteristics of the electromechanical and electromagnetic transient time series trajectory samples; S3. Based on the frequency domain response characteristics, the electromechanical and electromagnetic transient time series trajectories are reconstructed using linear interpolation and adaptive resampling techniques to obtain electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain characteristics; S4. The time domain features and frequency domain features in the electromechanical and electromagnetic transient reconstruction time series trajectory data are integrated to form a comprehensive feature vector, and the electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features is obtained.

2. The method for resampling time domain data of electromechanical-electromagnetic simulation with time-frequency domain characteristics preserved according to claim 1, characterized in that: Step S1 is specifically as follows: The electromechanical transient modeling of the new energy power grid system is carried out on the electromechanical transient simulation platform, the simulation step size and the total simulation time are set, the basic wave vector is used to describe the calculation element model, the differential algebraic equations are obtained, and the differential algebraic equations are solved simultaneously to obtain the time domain solutions of various physical quantities; Traverse various typical operating conditions and typical faults of the new energy power grid system to obtain electromechanical transient timing trajectory samples; The electromagnetic transient model of the new energy power grid system is built on the electromagnetic transient simulation platform, the simulation step size and the total simulation time are set, the abc three-phase instantaneous value is used to describe the calculation element model, and the differential equation group is obtained. The implicit integration method is used to solve the differential equation group and obtain the time domain solution of each physical quantity; Traverse various typical operating conditions and typical faults of the new energy power grid system to obtain electromagnetic transient time series trajectory samples.

3. The method for resampling time domain data of electromechanical-electromagnetic simulation with time-frequency domain characteristics preserved according to claim 1, characterized in that: Step S2 is specifically as follows: For the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample, the following steps are performed: S2.

1. According to the fault occurrence and duration set during the simulation, data from the fault occurrence to the steady state in the electromechanical transient timing trajectory sample or the electromagnetic transient timing trajectory sample is intercepted to obtain a fault timing trajectory sample, and the plurality of fault timing trajectory samples form a fault timing trajectory sample set; S2.

2. Initialize the time window and Prony order of the Prony method based on the fault time scale and oscillation frequency band; S2.

3. Divide the waveform data of the fault timing trajectory sample in each time window into two sections, wherein the first section of waveform data is data from the occurrence of the fault to the fault recovery, and the second section of waveform data is data after the fault returns to a steady state; S2.

4. Analyze the second waveform data using the Prony method, identify the linear oscillation mode without resonance in the second waveform data, and obtain its frequency as the initial value of the frequency domain result; S2.

5. Fit the initial value of the frequency domain result to the first segment of waveform data, use the Prony method to analyze the fitted first segment of waveform data, identify the second-order resonance mode caused by the nonlinear model after the fault occurs, and obtain the frequency domain response characteristics of each fault timing trajectory sample.

4. The method for resampling time domain data of electromechanical-electromagnetic simulation with time-frequency domain characteristics preserved according to claim 1, characterized in that: Step S3 is specifically as follows: S3.

1. Determine the resampling frequency of each time window according to the frequency domain response characteristics using the Nyquist sampling theorem; S3.

2. Calculate the complete sampling length K of the electromagnetic transient time series trajectory according to the resampling frequency of each time window; S3.

3. Linearly interpolate the electromechanical transient time series trajectory according to the sampling step of each time window in the electromagnetic transient time series trajectory to obtain an electromechanical transient time series trajectory corresponding to the sampling points of the electromagnetic transient time series trajectory; S3.

4. Using the adaptive resampling technology, the electromagnetic transient timing trajectory and the electromechanical transient timing trajectory are resampled according to the resampling frequency and the complete sampling length to obtain an electromechanical transient sequence and an electromagnetic transient sequence with a length of K.

5. The method for resampling time domain data of electromechanical-electromagnetic simulation with time-frequency domain characteristics preserved according to claim 1, characterized in that: Step S4 is specifically as follows: S4.

1. Deleting redundant samples and abnormal data in the electromechanical transient sequence or the electromagnetic transient sequence; S4.2 performing Z-score normalization processing on the time domain characteristics and frequency domain characteristics of the electrical transient sequence or the electromagnetic transient sequence; S4.3 performs weighted fusion on the time domain features and the frequency domain features to form a time comprehensive feature vector, and obtains electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features.

6. The method for resampling time domain data of electromechanical-electromagnetic simulation with time-frequency domain characteristics preserved according to claim 5, characterized in that: The weighted fusion of the time domain features and the frequency domain features is specifically as follows: the weight of the time domain features is calculated according to the oscillation energy, the weight of the frequency domain features is calculated according to the spectrum energy, and the time domain features and the frequency domain features are weightedly summed to form a comprehensive feature vector.

7. A time domain data resampling system for electromechanical-electromagnetic simulation that retains time-frequency domain characteristics, characterized in that: include: Data acquisition module: used to obtain electromechanical and electromagnetic transient time sequence trajectory samples for building new energy power grid systems based on electromagnetic simulation platforms and electromechanical simulation platforms; Feature acquisition module: used to process the electromechanical and electromagnetic transient time series trajectory samples respectively using the improved Proni method to obtain the frequency domain response characteristics of the electromechanical and electromagnetic transient time series trajectory samples; Trajectory reconstruction module: It is used to reconstruct the electromechanical and electromagnetic transient time series trajectory respectively based on the frequency domain response characteristics by using linear interpolation and adaptive resampling technology to obtain the electromechanical and electromagnetic transient reconstructed time series trajectory data containing frequency domain characteristics; Feature fusion module: used to fuse the time domain features and frequency domain features in the electromechanical and electromagnetic transient reconstruction time series trajectory data to form a comprehensive feature vector, and obtain the electromechanical-electromagnetic simulation time domain data that retains the time and frequency domain features.

8. A computer device, characterized in that: The computer device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement a time domain data resampling method for electromechanical-electromagnetic simulation that retains time-frequency domain characteristics as described in any one of claims 1-6.

9. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are executed by one or more processors, the one or more processors are caused to execute the steps in the method according to any one of claims 1 to 6.

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