21 results about "Power system oscillations" patented technology

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 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 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 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.

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.

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 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 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 invention discloses a method and system suitable for preventing oscillation misjudgment of a power system. Abnormal data are removed from monitoring data to obtain to-be-identified data; based on repetitive oscillation characteristics, zero value points and fixed value points extracted from data to be identified, eliminating system oscillation when periodic fluctuation is judged to exist through prior detection and posterior detection; when the system oscillation is not eliminated, if the to-be-identified data passes node power balance verification and voltage and current phase verification and meets a power supply constraint condition, eliminating the system oscillation; otherwise, determining that the to-be-identified data is oscillation abnormal data; calculating the similarity between the oscillation abnormal data of each device, and taking the oscillation abnormal data of which the similarity is not less than a set similarity as to-be-verified data; screening out misjudgment data from the to-be-verified data, recovering the misjudgment data, and merging the misjudgment data into the oscillation abnormal data; iterative convergence is based on the installation positions of the devices with the similarity smaller than the set similarity, the system oscillation area is determined in combination with the power grid topology, and the accuracy and reliability of oscillation judgment are guaranteed.

The invention discloses an online oscillation suppression method and device of a doubly-fed wind turbine generator and the doubly-fed wind turbine generator, and relates to the technical field of wind power generation. According to the method, monitoring voltage representing the voltage state of a power grid is obtained, frequency domain analysis is carried out on the monitoring voltage, the characteristics of inter-harmonic voltage in the voltage of the power grid are recognized in real time, and therefore whether the doubly-fed wind turbine generator oscillates or not is judged. And when oscillation is detected, an oscillation suppression mechanism is triggered to perform control intervention on the unit. The method does not need to depend on an accurate system model, can carry out the online detection and quick response of the oscillation of the power system under the condition of a weak power grid, overcomes the problems that the oscillation recognition is lagged and the suppression capability is insufficient in a high-proportion new energy access scene in an existing network tracking type and network constructing type control mode, and improves the reliability of the system. And the operation stability and the grid-connected reliability of the doubly-fed wind turbine generator in a weak power grid environment are improved.

The invention discloses a flexible direct current power transmission system oscillation risk assessment method based on phase-space reconstruction, and belongs to the technical field of power system oscillation risk assessment, and the method comprises the steps: collecting an oscillation output signal comprising an oscillation component when a flexible direct current power transmission system is unstable, and carrying out the preprocessing of the oscillation output signal; performing phase-space trajectory reconstruction on the preprocessed oscillation output signal by adopting a time delay embedding method; on the basis of the reconstructed phase space trajectory, predicting the phase space trajectory of the oscillation output signal of the power transmission system at the next time by using a linear autoregression model as a prediction model or a prediction model representing the geometrical characteristics of the phase space trajectory on polar coordinates; and analyzing the evolution trajectory of the predicted phase space trajectory, and evaluating the oscillation risk of the power transmission system. According to the method, oscillation risk assessment and early warning are realized based on real-time measurement data, the method does not depend on accurate modeling of the system, the complexity is low, the operation cost is low, and the method has relatively high adaptability under different working conditions.

The application provides a power system oscillation source detection method and device, and relates to the technical field of power operation and maintenance.The method comprises the following steps: determining a first phase difference of generator power data and rotating speed data based on an oscillation period, and determining whether the power system oscillation source is from a prime mover side of the generator based on the first phase difference; if yes, an alarm is given that the prime mover side has an oscillation source; if no, determining a second phase difference of calculated excitation voltage data and measured excitation voltage data based on the oscillation period, and determining an amplitude difference of the calculated excitation voltage data and the measured excitation voltage data; determining whether the power system oscillation source is from a generator excitation system side based on the second phase difference and the amplitude difference; if yes, an alarm is given that the excitation system side has an oscillation source; if no, an alarm is given that the power grid side has an oscillation source.The application can improve the accuracy, speed and applicability of power system oscillation source detection.

This invention relates to the field of power system condition monitoring technology, and is a method and system for identifying source-load parameter combinations for suppressing low-frequency oscillations based on damping ratio sensitivity. The system includes a simulation model establishment unit, a new energy unit selection unit, a motor load selection unit, and a source-load parameter combination identification unit. It establishes a power system simulation model containing multiple new energy units and multiple motor loads and calculates the initial system damping ratio. By calculating the damping ratio sensitivity, this invention identifies the new energy units, motor loads, and source-load parameter combinations that are most sensitive to power system oscillations, providing a reference for improving the damping ratio and suppressing oscillations. This method can simultaneously identify parameter combinations of new energy units and motor loads, reflecting the synergistic effect of both the source and load sides on the system damping ratio and oscillations. Compared with the identification of single power source or load parameters, this method has guiding significance for locating and suppressing low-frequency system oscillations.

The invention relates to the technical field of power system oscillation analysis, and discloses an extra-high voltage direct current transmission system oscillation source identification method based on wavelet analysis. The method comprises the steps of collecting electrical quantity of a measuring point, constructing an input tensor through preprocessing, respectively inputting four wavelet branches to execute five-layer convolution pooling to obtain a feature map, performing adaptive weighted fusion through a scale channel combined attention network, inputting a bidirectional long-short-term memory network, and calculating oscillation source probability, energy flow direction and frequency domain energy in combination with a historical state, and determining the position of the oscillation source by integrating criteria. According to the method, the problems that wavelet basis selection depends on experience, coupling of multiple oscillation sources is difficult to separate, and dynamic tracking capability lacks are solved, and the accuracy and real-time performance of oscillation source identification of the extra-high voltage system are improved.