43 results about "Power system oscillations" patented technology

The invention discloses a wind power grid-connected oscillation suppression method and system based on a self-adaptive damping controller, and relates to the technical field of oscillation suppression of a power system. According to the method, a self-adaptive damping controller structure is designed, and parameter setting is completed; then building a wind power grid-connected system simulation model; after voltage signals are collected, an FFT processing method is used for identifying oscillation frequency, and whether an unstable oscillation mode exists in the system or not is judged; if unstable oscillation exists, a self-adaptive damping controller is connected between the wind power plant side and the power grid side; the self-adaptive damping controller filters out signal components causing system oscillation and performs phase modulation; a signal component generated by the self-adaptive damping controller is injected into the power grid and counteracts with an original signal, and oscillation suppression is achieved. According to the self-adaptive damping controller designed by the invention, the oscillation frequency identification module and the phase shift parameter calculation module are introduced, so that measured data can be fully utilized, control link parameters are adjusted according to vibration frequency changes, and oscillation is effectively suppressed.

The invention discloses a harbor shore power system oscillation damping suppression method based on heuristic probability optimization. According to the method, sliding window preprocessing is carried out on an alternating current bus side current time domain oscillation signal, modal decomposition is carried out based on a Prony algorithm, and modal energy is calculated to judge an oscillation mode; the discriminated oscillation modes are aggregated and mapped into equivalent circuit elements, a corresponding three-order circuit state matrix is constructed, and the damping ratio of each mode is determined according to the characteristic value of the matrix; taking a damping ratio as an evaluation index, introducing an influence factor to construct a multi-objective optimization function, parameterizing the parallel adjustable impedance, and limiting an adjustable range; and searching the control parameters by adopting a heuristic probability optimization strategy to obtain final damping control parameters, and downloading the final damping control parameters to the parallel adjustable impedance device to realize online dynamic adjustment. According to the method, multi-modal identification, physical magnitude mapping and online adaptive optimization can be realized, and the suppression capability and the operation stability of the shore power system on sub / super synchronous oscillation are improved.

The invention discloses a power system oscillation parameter identification method based on improved TVF-EMD, and the method comprises the steps: carrying out the preprocessing of an original PMU data stream, calculating a local cut-off frequency LCF through B-spline approximation, solving a signal local mean value through B-spline approximation, completing the time-varying filtering empirical mode decomposition, namely TVF-EMD decomposition, screening an effective IMF based on a correlation coefficient after the verification of a stop criterion, and carrying out the recognition of the oscillation parameter of a power system. Extracting an instantaneous frequency and a damping ratio through the TKEO; the method combines TVF-EMD with TKEO, can accurately estimate the modal parameters of the power system under the normal operation condition, including frequency and damping ratio, has robustness for the instantaneous mode characteristics in the power system under the condition of low calculation complexity, reduces the problems of modal aliasing and discontinuity easily occurring in the traditional EMD method, and improves the reliability of the power system. The method provides better performance in the aspects of predefined parameters and time-varying cut-off frequency, and is suitable for analysis of non-stationary signals.

The invention belongs to the field of oscillation suppression of a power system, and particularly discloses a method and a device for cooperatively suppressing multi-band oscillation through three channels of a synchronous unit, and the method comprises the steps: employing a reactive damping controller, a PSS damping controller and a speed regulation side damping controller based on a flexible excitation system and a speed regulator; the damping components respectively act on the first channel, the second channel and the third channel to generate damping so as to suppress multi-band oscillation; the problems of time-varying characteristics and diversity of the system and complex and changeable oscillation modes under the double-high characteristic are considered, and parameters of the damping controller are dynamically optimized on line in real time based on reinforcement learning; key frequency bands suppressed by different channels are dynamically and flexibly adjusted according to the monitored change condition of the oscillation mode of the system; the optimal damping configuration can be realized, wider frequency band and stronger damping are provided, the conditions of complex and changeable oscillation modes and frequency band widening brought by a high-proportion new energy power grid are dealt with more efficiently and flexibly, and the safe and stable operation capability of the system is improved.

The invention discloses a power system oscillation traceability analysis method and system based on multi-method probability fusion, which can effectively solve the problem of oscillation source positioning error caused by sparse measurement data and compressed sensing. Firstly, the oscillation source probability of each node is calculated through an oscillation energy method, a frequency spectrum characteristic method, a correlation analysis method, a voltage fluctuation method and a phase angle gradient method; secondly, calculating the adaptive weight of each method based on an information entropy theory, and completing multi-method probability fusion; the fusion probability is optimized in combination with a power grid topological structure, and an oscillation source candidate sequence is determined; and finally, a comprehensive probability distribution diagram and a detailed analysis report are output through a visual module, and reliable technical support is provided for safe and stable operation of a power system.

The invention discloses an online evaluation method and system for an oscillation monitoring algorithm, and the method comprises the steps: obtaining diversified oscillation test cases, and marking the oscillation characteristics of each case; the method comprises the following steps: configuring a test plant station in an actually running power system, adopting a high-precision sending mechanism by the test plant station, generating an analog data message consistent with a time mark and a format of an actual PMU message according to an oscillation test case, and sending the analog data message to a message bus; and performing oscillation detection on the analog data message received by the message bus by applying an oscillation monitoring algorithm, and comparing an oscillation detection result with the oscillation characteristics of the corresponding oscillation test case to obtain an evaluation result of the oscillation monitoring algorithm. The method can truly reflect the performance of the oscillation monitoring algorithm in an actual environment without influencing the actual operation of a power grid, improves the accuracy and reliability of the algorithm, has the advantages of high authenticity, high reliability and comprehensive coverage, and is suitable for online evaluation and optimization of the oscillation monitoring algorithm of the power system.

The invention relates to a subsynchronous oscillation identification detection method and system based on multiple compression improved spline chirp transformation, and belongs to the field of power system oscillation detection. The method comprises the following steps: firstly, collecting a current signal and a voltage signal output from a power system, then converting the time-domain current signal and the voltage signal into a time-frequency domain by utilizing improved spline chirp transformation, and extracting and mapping an improved spline chirp transformation result to a new time-frequency spectrum by adopting multiple compression transformation; and reconstructing the obtained time-frequency spectrum information, and carrying out identification estimation on oscillation parameters in a new time-frequency spectrum by adopting a matrix pencil algorithm so as to obtain parameters of the next synchronous oscillation signal in different modals. According to the method, subsynchronous oscillation signal modal extraction and parameter estimation can be realized in a high-noise environment, subsynchronous oscillation occurring in a system can be automatically detected, and efficient and accurate time-frequency feature extraction requirements can be comprehensively met.

The application relates to the technical field of power system oscillation analysis, and discloses a method for identifying an ultra-high voltage direct current sending-out system oscillation source based on wavelet analysis. The method comprises the following steps: collecting electrical quantities of measuring points, pre-processing the electrical quantities to construct an input tensor, inputting the input tensor into four wavelet branches to perform five-layer convolution pooling to obtain feature maps, adaptively weighting and fusing the feature maps through a scale channel joint attention network, inputting the feature maps into a bidirectional long short-term memory network to calculate an oscillation source probability, an energy flow direction and a frequency energy in combination with historical states, and determining an oscillation source position according to a comprehensive criterion. The application solves the problems that wavelet basis selection depends on experience, multiple oscillation sources are difficult to separate, and dynamic tracking capability is lacking, and improves the accuracy and real-time performance of ultra-high voltage system oscillation source identification.

The invention relates to the technical field of power systems, and discloses a power system oscillation source judgment method. The method comprises the following steps: S1, acquiring apparent power data of each unit in a power system, and calculating the relationship between the apparent power of each unit and active power and reactive power; s2, the apparent power is converted into a per unit value, and the comparability of data between different units is ensured; and S3, setting an upper limit threshold value and a lower limit threshold value of the voltage of the power generation element by adopting per unit value data, and displaying a voltage threshold value boundary on a monitoring interface. By adopting the technical scheme of combining apparent power per unit and oscillation energy calculation, the technical effect of accurately identifying the oscillation source in the power system is achieved. Compared with a method for judging the oscillation source only depending on power fluctuation or a single parameter in the prior art, the problems that the oscillation source recognition misjudgment rate is high and the applicability is insufficient are solved, data of different units have higher comparability, and the judgment accuracy is improved.

The present invention discloses a method and system for identifying power system oscillation parameters based on synchronized phasor data, which relates to the technical field of power system oscillation analysis. It solves the problem that the traditional MPM directly obtains the eigenvalues of the matrix pencil, resulting in large errors. The key points of its technical solution are as follows: By constructing a real Hankel matrix and solving the eigenvalues of this matrix, the fundamental wave component angular frequency that satisfies the angular frequency conjugate constraint of two modes of the fundamental frequency component and the oscillation component angular frequency that satisfies the angular frequency conjugate constraint of two modes of the oscillation component can be directly obtained. The solution is simple and the computational amount is small. Moreover, by combining the real part and the imaginary part of the synchronized phasor to construct a real Hankel matrix, the information of the synchronized phasor can be completely retained, and thus the subsynchronous oscillation parameters can be accurately identified under an ultra-short data window.

The invention relates to the technical field of power system oscillation analysis and control, and provides a multi-scale modeling-based broadband oscillation feature extraction and suppression method for a new energy high-proportion access system, and the method comprises the steps: building a multi-scale model which is used for describing a power system and comprises an electromagnetic transient model, an electromechanical transient model and a dynamic feature model; based on the multi-scale model, constructing a digital twinborn model which operates synchronously with the physical power system, and updating the state of the digital twinborn model in real time by adopting a data assimilation algorithm; utilizing a digital twinborn model to extract broadband oscillation characteristics of the power system; and generating a suppression strategy according to the broadband oscillation characteristics, and regulating and controlling the physical power system through the suppression strategy verified in the digital twinborn model. Furthermore, accurate extraction and effective suppression of broadband oscillation in the new energy high-proportion access system are realized.

The invention discloses a power system oscillation mechanism identification method and a model construction method, and relates to the field of power system low-frequency oscillation, and the method comprises the steps: collecting the active power data of a generator and the active power data of a tie line; performing linear normalization and principal component analysis dimension reduction processing on the data, and constructing a multi-dimensional time sequence to-be-tested sample; a sample is input into a pre-trained deep belief network (DBN) model, the model is formed by stacking a plurality of restricted Boltzmann machines (RBM), data deep features are extracted through unsupervised layer-by-layer greedy pre-training, and parameter optimization is performed in combination with supervised fine tuning. According to the method, negative damping oscillation and forced power oscillation can be automatically identified, the uncertainty of manual feature selection is avoided, the influence of noise and amplitude difference on the identification precision is effectively suppressed, and the adaptability of the model to an actual power grid complex disturbance condition is improved.

The invention discloses an automatic intelligent voltage regulation method for improving the electrical performance of an LNG ship, and the method comprises the steps: carrying out the preprocessing of real-time data after a power system enters a working state, transmitting the preprocessed data to a control system PID module, converting the data into a voltage regulation signal after the data is processed by the control system PID module, and transmitting the voltage regulation signal to an AVR system module, an algorithm model is preset in a PID module of a control system, the algorithm model is obtained by collecting historical data from an LNG ship power system, preprocessing the collected historical data, building the algorithm model through a long-short term memory neural network and a convolutional neural network and training the algorithm model, and the algorithm model is obtained through the algorithm model. The algorithm model feeds back and adjusts the voltage through intelligent prediction and multiple iteration processing, so that the output voltage reaches or approaches the standard voltage to realize stable balance. According to the method, the deep learning optimization algorithm is adopted, automatic adjustment of the LNG ship power system is achieved, oscillation and faults of the power system are reduced, and the overall performance of the ship is improved.

The present invention belongs to the field of power system stability and control, and relates to a control method for suppressing power system oscillations based on energy storage VSG. The steps are: detecting the difference between the virtual angular frequency of the energy storage VSG system and the reference angular frequency of the power grid, and obtaining a damping power signal through an additional damping controller based on bandpass filtering; designing the bandpass filter parameters according to the low-frequency oscillation characteristics of the new power system; introducing the damping power signal output by the additional damping controller into the active control loop of the energy storage VSG system, and constructing a model of the energy storage VSG system connected to a single-machine infinite system; based on linearization analysis, deriving the damping torque provided by the energy storage VSG system for the single-machine infinite system; and using the damping torque method to analyze the main parameters of the additional damping controller. The present invention constructs an additional damping control based on a bandpass filter according to the characteristics of low-frequency oscillations, increases the damping during the low-frequency oscillation process, and thus suppresses the low-frequency oscillations of the power system.

This application discloses a method and apparatus for tracing the source of power system oscillations, including converters and synchronous machines. Belonging to the field of power system transmission and distribution technology, the method involves: reducing the order of the power network and constructing its linearized admittance matrix; establishing port admittance matrices for all power supply equipment, including converters and synchronous machines, under small disturbances; establishing the port external admittance matrix of the synchronous machines, taking into account the impedance embedding of the converters, based on the port admittance models of the power supply equipment and the power network; sequentially calculating the port impedance of each synchronous machine and establishing its damping torque model; and identifying the synchronous machine providing negative damping torque based on the phase characteristics of the damping torque model, which is the low-frequency oscillation source of the system. This application does not require internal converter information, can achieve information isolation between different power sources, is applicable to converters with different control strategies, has clear physical meaning, can provide theoretical guidance for oscillation suppression in large-scale multi-machine power systems, and can be embedded in power system analysis software, making it of significant engineering importance.

The invention provides a novel power system oscillation early warning method and device, electronic equipment and a storage medium, and the method comprises the steps: setting an initial early warning threshold value, and periodically storing a plurality of oscillation-related characteristic values in a power system; selecting a target value from the characteristic values at an updating time point as a candidate early warning threshold value, wherein a preset time point is related to a storage period of the oscillation related characteristic values; comparing a candidate early warning threshold value with a current early warning threshold value to determine whether to update the early warning threshold value according to the candidate early warning threshold value; and carrying out oscillation early warning according to the oscillation related characteristic value and the early warning threshold value. By periodically storing various oscillation related characteristic values and dynamically adjusting the early warning threshold value, the early warning threshold value is adjusted in real time according to different working conditions of the power system and changes of the characteristic values, the actual operation state of the power system can be accurately determined, potential oscillation risks can be captured in time, and the accuracy of oscillation early warning is improved.

The invention provides a novel power system key electrical quantity oscillation monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a monitoring electrical quantity collected by an electrical measurement point; according to the monitored electrical quantity and the periodic time parameter, calculating an oscillation characteristic value, the oscillation characteristic values comprise a single-cycle rolling characteristic value based on the reciprocating motion mileage, a long-cycle nested characteristic value based on the reciprocating motion mileage, a single-cycle rolling characteristic value based on the oscillation waveform area and a long-cycle nested characteristic value based on the oscillation waveform area; setting an oscillation alarm threshold value according to the oscillation characteristic value; and determining whether abnormal oscillation occurs or not according to the oscillation characteristic value and the oscillation alarm threshold value, and performing oscillation early warning. Through multi-dimensional and multi-time-scale feature extraction, the oscillation feature value is extracted from the monitored electrical quantity, and adaptive threshold setting is carried out, so that the accuracy, sensitivity and adaptability of oscillation monitoring of the power system are remarkably improved.

The invention discloses an L1 regularization and neural network-based power system sub / super synchronous oscillation parameter identification method and device applied to a synchronous phasor measurement device, and a storage medium, and belongs to the technical field of power system oscillation analysis. Recombining the non-missing parts into a continuous synchronous phasor sequence in sequence; 2, setting a neural network and a Fourier transform matrix as input, and setting a continuous synchronous phasor sequence as target output; 3, initializing weight parameters of the neural network; 4, adding L1 regularization as a penalty term of a target output error; 5, optimizing the network weight by using an RMSProp optimizer to obtain a solution of an equation set; and 6, calculating sub / super synchronous oscillation parameters according to a synchronous phasor algorithm in combination with the solution of the equation set. The method can be applied to a synchronous phasor measurement device, synchronous phasor data collected by the device serve as input of the method, and oscillation parameters of signals can be measured online.

The invention provides a power system oscillation source positioning method and device, electronic equipment and a storage medium, and relates to the technical field of power system oscillation analysis, and the method comprises the steps: obtaining a three-phase voltage instantaneous sampling value and a three-phase current instantaneous sampling value of each port in a plurality of ports of a power system; based on the three-phase voltage instantaneous sampling value and the three-phase current instantaneous sampling value, calculating to obtain instantaneous total power and a steady-state direct-current power component of each port; calculating a difference value between the instantaneous total power and the steady-state direct-current power component to obtain a net power component of each port; and analyzing the net supply energy change trend of the plurality of ports based on the net power component of each port, and determining an oscillation source in the plurality of ports based on the net supply energy change trend. According to the method provided by the invention, the oscillation source criterion based on the net supply energy is more reliable, and misjudgment caused by improper removal of the direct current component is reduced.

The present invention discloses a method and system for suppressing wind power grid connection oscillations based on an adaptive damping controller, which relates to the technical field of power system oscillation suppression. The present invention designs the structure of the adaptive damping controller and completes parameter tuning; then builds a simulation model of the wind power grid connection system; after collecting voltage signals, uses the FFT processing method to identify the oscillation frequency and determine whether there is an unstable oscillation mode in the system; if there is an unstable oscillation, an adaptive damping controller is connected between the wind farm side and the grid side; the adaptive damping controller filters out the signal components causing system oscillations and performs phase modulation; the signal components generated by the adaptive damping controller are injected into the grid to cancel the original signals, achieving oscillation suppression. The adaptive damping controller designed by the present invention can make full use of measurement data by introducing an oscillation frequency identification module and a phase shift parameter calculation module, adjust the parameters of the control link according to the change of the vibration frequency, and effectively suppress oscillations.

This invention discloses a method, system, and device for identifying subsynchronous oscillation modes under environmental excitation, belonging to the field of power system oscillation detection. Kalman filtering (KF) is used to estimate the coefficients of an autoregressive (AR) model to fit measured environmental data. The damping factor and frequency of the subsynchronous oscillation (SSO) mode can be directly obtained by solving for the roots of the characteristic polynomial corresponding to the AR model. Furthermore, multi-model segmentation filtering (MMPF) is applied to KF to select the correct AR model order. This invention combines the KF algorithm with MMPF, enabling the algorithm to directly identify weak SSO mode parameters from environmental data. The method has simple operation steps and short response time, thus possessing good application prospects.

The present application belongs to the technical field of power system oscillation suppression, and specifically discloses an oscillation suppression method and system based on high-inertia energy storage type phase modifier impedance remodeling, which comprises the following steps: identifying a target suppression frequency band; obtaining the active power signal of a grid-connected new energy unit or new energy station, and performing band-pass filtering to obtain the subsynchronous and / or supersynchronous oscillation component of the target suppression frequency band; performing asymmetric complex number lead correction on the oscillation component; after amplitude shaping and safety limiting of the phase-compensated signal, the signal is injected into the rotor-side converter power outer ring of the high-inertia energy storage type phase modifier as an additional control signal to form an additional power deviation; the deviation is output as a rotor-side current reference value after PI regulation, and then a damping power opposite to the oscillation component is formed on the stator side to remodel the equivalent output impedance of the point of common coupling. The present application can suppress the subsynchronous and / or supersynchronous oscillation of the new energy station.

The invention discloses a power system low-frequency oscillation monitoring and analysis method, system, equipment and medium, and relates to the technical field of power system analysis, and the method comprises the steps: reading PMU data, and extracting oscillation features according to fluctuation changes; if an oscillation sign occurs, rapidly determining the oscillation frequency by using fast Fourier transform (FFT), and if the adjacent stations of the regional power grid detect oscillation at the same frequency, determining that the power grid oscillates; based on the oscillation characteristic data, weak damping oscillation monitoring analysis is carried out, and an online grouping result of a synchronous power grid unit and a node injection active power oscillation mode is output; and performing forced oscillation monitoring analysis, and outputting an oscillation source positioning result of the synchronous power grid based on transient energy integration. The method can quickly confirm the oscillation mode and the oscillation source when the power system oscillates, assists a dispatcher in quickly and accurately understanding the situation of the oscillation source of the power grid, takes effective measures to eliminate the influence of low-frequency oscillation on the operation of the power grid, and improves the safety and stability of the power system.

The invention discloses a broadband oscillation traceability method for a power system driven by measurement data, and relates to the technical field of power system oscillation analysis. According to the invention, based on port voltage and current instantaneous measurement data of a power generation unit or a grid-connected node, a target broadband oscillation frequency is identified through frequency domain analysis, and corresponding voltage and current oscillation mode components are extracted; then constructing modal power under the modal to represent oscillation energy exchange characteristics; and finally, according to the sign and the change characteristic of the modal power, determining that the unit or the node which continuously injects oscillation energy into the system is a broadband oscillation source. The method is low in model dependency, visual in positioning and suitable for a new energy high-proportion power system, and provides a basis for oscillation suppression.

The invention relates to a power supply oscillation suppression system and a power supply oscillation suppression method, the power supply oscillation suppression system comprises an oscillation detection module and an oscillation suppression module, and the oscillation detection module is connected with a wave trap; the wave trap is used for acquiring oscillation information from the oscillation detection module and updating parameters of the wave trap according to the oscillation information to suppress oscillation, the synchronous generator is used for remodeling power supply impedance from a current source type to a voltage source type, and the additional damping controller is used for injecting an inversion signal into a current loop to offset the oscillation. Oscillation is rapidly detected through an oscillation detection module, oscillation is suppressed through a wave trap in an oscillation suppression module, power supply impedance is remodeled from a current source type to a voltage source type through a synchronous generator, damping resistance of a power system is improved from the source, and an anti-phase signal is injected into a current loop through an additional damping controller to offset an oscillation component. The oscillation energy attenuation is accelerated, the oscillation suppression capability of the power system is improved, and the stability of the power system is improved.

The invention provides an oscillation identification method and device, equipment, a storage medium and a product. The method comprises the following steps: dividing waveform data of a power system into a plurality of sub-data according to a preset time window and a preset sliding step length; based on a margin index algorithm, separately determining margin indexes corresponding to the sub-data; the margin index represents the fluctuation degree of the current in the time window corresponding to the sub-data; determining an oscillation starting moment based on a difference value between each margin index; fourier transform is carried out on waveform data corresponding to the oscillation starting moment to obtain corresponding frequency domain data, and the waveform data and the frequency domain data are combined into a time-frequency domain data set; and inputting the time-frequency domain data set into a preset deep learning model, and determining the oscillation type of the power system. The time-frequency domain data is input into the preset deep learning model for classification, so that the complexity and subjectivity of manual feature extraction are avoided, the accuracy and efficiency of power system oscillation type recognition are improved, and oscillation in the power system can be quickly and accurately recognized.

The invention relates to the technical field of power system stability analysis, in particular to a quantitative analysis method and device for logarithmic derivatives of a dominant oscillation mode of a power system, and the method comprises the steps: determining the frequency step size of the power system, and obtaining the logarithmic derivative of an admittance matrix determinant according to the frequency step size; acquiring a real part extreme point and an adjacent frequency point of the logarithmic derivative, and pre-identifying a dominant oscillation mode of the power system according to the real part extreme point and the adjacent frequency point; and calculating oscillation damping and frequency of the power system according to the dominant oscillation mode. Therefore, the problem that the accuracy of oscillation source identification and system stability evaluation is affected due to inaccurate estimation of key parameters such as the damping ratio and the oscillation frequency in the dominant oscillation mode due to the fact that the influence of the frequency step length on the parameter identification precision is not fully considered in an electric power system oscillation analysis method is solved.

The invention discloses a power system oscillation alarm false alarm prevention method and system based on multi-source data checking. The method comprises the steps that a master station monitors oscillation alarm in real time; when the main station monitors an oscillation alarm, triggering oscillation checking based on the broadband data real-time checking path so as to judge whether the oscillation alarm is caused by spectrum aliasing or not; when the oscillation alarm is judged to be caused by spectrum aliasing based on the broadband data real-time checking path, the master station issues an oscillation false alarm, otherwise, the master station triggers oscillation checking based on the high-sampling wave recording calling checking path; carrying out oscillation checking based on a high-sampling wave recording call checking path so as to check whether the oscillation alarm is caused by spectrum aliasing; and when the oscillation check based on the high-sampling wave recording call check path judges that the oscillation alarm is caused by spectrum aliasing, the master station issues an oscillation false alarm. According to the invention, the problem of oscillation false alarm caused by spectrum aliasing is solved.

The present invention belongs to the field of electric power automation and discloses a power system oscillation risk assessment method, system, computer equipment, and medium. The method includes real-time monitoring of power system measurement data, determining whether subsynchronous / supersynchronous interharmonics exist in the power system based on the measurement data, obtaining the frequency, amplitude, and voltage-current angle difference of the subsynchronous / supersynchronous interharmonics, and combining the torsional vibration frequency, each oscillation risk frequency, and the amplitude threshold of each oscillation risk frequency in historical record data to obtain an oscillation risk assessment result for the subsynchronous / supersynchronous interharmonics; supplementing the frequency and amplitude of the subsynchronous / supersynchronous interharmonics with oscillation risk in the oscillation risk assessment result to the historical record data, and updating the torsional vibration frequency, each oscillation risk frequency, and the amplitude threshold of each oscillation risk frequency in the historical record data. Oscillation risk assessment is performed based on real-time data and historical record data, improving the accuracy of the oscillation risk assessment result and reducing the false alarm rate.

The application discloses a port shore power system oscillation damping suppression method based on heuristic probability optimization. The method carries out sliding window pretreatment on the time domain oscillation signal of the current on the AC bus side and implements modal decomposition based on the Prony algorithm, calculates modal energy to identify the oscillation mode; the identified oscillation mode is aggregated and mapped into equivalent circuit elements, a corresponding third-order circuit state matrix is constructed, and the damping ratio of each mode is determined from the characteristic value; a multi-objective optimization function is constructed with the damping ratio as an evaluation index and an influence factor is introduced, a parallel adjustable impedance is parameterized and limited in a range; a heuristic probability optimization strategy is used to search for control parameters, and the final damping control parameters are obtained and transmitted to the parallel adjustable impedance device to realize online dynamic adjustment. The method can realize multi-modal identification, physical quantity level mapping and online adaptive optimization, and improve the suppression ability of the shore power system to sub- / ultra-synchronous oscillation and the operation stability.