CN-121983980-A - New energy broadband oscillation online monitoring and analyzing method and system for cloud edge end architecture

CN121983980ACN 121983980 ACN121983980 ACN 121983980ACN-121983980-A

Abstract

The invention belongs to the technical field of new energy access and control, and relates to a new energy broadband oscillation on-line monitoring and analyzing method and system of a cloud edge end architecture. The method aims at solving the contradiction between the transmission of a large amount of high-frequency transient data and the real-time processing requirement. The method comprises the steps of acquiring temporary steady state data of a new energy unit and grid connection points in real time by an intelligent terminal at an end side, calculating full-wave active power, carrying out integral FFT, carrying out sliding window FFT on the active power to obtain a time-frequency matrix, screening potential oscillation frequency points based on a preset threshold value, calculating an oscillation component damping ratio, clustering similar oscillation frequency points, sending an analysis result and partial data to a cloud side server by the cloud side server, and gathering data from a plurality of the cloud side servers to carry out centralized display and multi-station comparison analysis. Through cloud edge end collaborative architecture, data transmission pressure is remarkably reduced, and analysis efficiency and instantaneity are improved.

Inventors

QIAN CHENFEI
ZHANG JIN
QIN SHIYAO
LI SHAOLIN
LI CHUNYAN
CHEN YUSHAN
HE JING
ZHANG MEI
ZHANG SONGTAO
LI PENGKUN

Assignees

中国电力科学研究院有限公司
国家电网有限公司

Dates

Publication Date: 20260505
Application Date: 20260115

Claims (10)

1. A new energy broadband oscillation online monitoring and analyzing method of a cloud end architecture is characterized by comprising the following steps: the intelligent terminal at the end side acquires temporary steady state data of a new energy unit and a grid-connected point and transmits the temporary steady state data to the side server, wherein the temporary steady state data comprises three-phase voltage and current instantaneous values; The method comprises the steps of operating a broadband oscillation on-line analysis algorithm by an edge server to analyze transient steady-state data to obtain an analysis result, wherein the analysis result comprises the steps of calculating full-wave active power P based on three-phase voltage and current instantaneous values, carrying out integral FFT on the full-wave active power P to obtain active amplitude values of a frequency domain, carrying out sliding window FFT processing on the full-wave active power P to obtain active amplitude values PFreqMov of a plurality of groups of frequency domains, extracting maximum values Pmax of each frequency in all time from the active amplitude values PFreqMov according to frequency groups, screening out frequency points f which are possibly subjected to oscillation based on a preset threshold value Plim, judging whether damping ratio calculation conditions are met or not based on a preset threshold value PDCalLim on frequency points except direct current components in the frequency points f, if so, calculating damping ratios of corresponding frequency points, carrying out clustering processing on the frequency points f, dividing the frequency points with the frequency difference not exceeding the preset threshold value CLim into identical oscillation frequency clusters, and transmitting the analysis result and at least part of real-time data to a cloud side server; And the cloud side server performs centralized display and comparative analysis on the multi-station data corresponding to the at least one side server.
2. The method according to claim 1, wherein the full wave active power P is calculated by the formula: )/1000 Wherein, the For the instantaneous value of the three-phase voltage, Is a three-phase current instantaneous value.
3. The method of claim 1, wherein the sliding window FFT processing comprises: setting a sliding window size FFTWin, a wave recording sampling rate fs and a sliding window interval time T; the number of data points in each sliding window is N= FFTWin ×fs, and the number of interval data points delta=T×fs of adjacent sliding windows; Segmenting the full wave active power P to obtain N sets of data temP 1 to temP n , wherein temP k =p [ (k-1) x delta+1:n+ (k-1) x delta ], k=1, 2,..n, and n= (ds-N)/delta+1, ds is the total data set number; And carrying out FFT on each group of data temP k to obtain an active amplitude value PFreqMov k corresponding to each group of data, wherein the active amplitude values PFreqMov of a plurality of groups of frequency domains are formed by PFreqMov 1 to PFreqMov n .
4. The method according to claim 1, wherein the screening out the frequency points f at which the oscillation is likely to occur based on the preset threshold Plim comprises: The maximum value Pmax comprises a maximum value Pmax 1 corresponding to the direct current component and a maximum value Pmax x corresponding to other frequencies, wherein x is more than or equal to 2; Sequentially judging whether each Pmax x is larger than Pmax 1 xPlim, if so, the corresponding frequency point fre (x) is a frequency point which is possible to oscillate; and all the frequency points meeting the conditions form the frequency point f.
5. The method of claim 1, wherein the damping ratio The calculation formula of (2) is as follows: Wherein, the For the attenuation coefficient, A j is the active amplitude ratio of two continuous times corresponding to one frequency point in the frequency point f, the time Deltat= [ FFTWin:delta/fs: FFTWin + (n-1): delta/fs ], f is the oscillation frequency, For damping ratio, j is a data index.
6. The method according to claim 1, wherein the clustering the frequency bin f comprises: If the frequency difference value of any two adjacent frequency points in the frequency point f is less than or equal to a threshold value CLim, dividing the two adjacent frequency points into the same oscillation frequency cluster.
7. The method of claim 1, wherein the intelligent terminal on the end side and the side server transmit data through ModbusTCP, FTP, IEC60870-5-104 or IEC61850 protocol, and/or, And the side server and the cloud side server transmit data through IEC60870-5-104 protocol or FTP protocol.
8. The method of claim 1, wherein the side server stores data in a time series database InfluxDB, and/or, The cloud side server stores the data in a time sequence database TDengine, a distributed file storage database MongoDB or a relational database MySQL.
9. The method of claim 1, further comprising triggering the recording step: And setting an oscillation power monitoring threshold value at a unit or a grid-connected point, and triggering the terminal side intelligent terminal or the side intelligent terminal to start wave recording when the monitored active power oscillation amplitude exceeds the threshold value and lasts for a preset time, and recording three-phase voltage instantaneous value and three-phase current instantaneous value data of a set sampling rate fs and wave recording time ts.
10. A new energy broadband oscillation online monitoring and analyzing system of a cloud end architecture is characterized by comprising: the intelligent terminal at the end side collects temporary steady state data of the new energy unit and the grid-connected point and transmits the temporary steady state data to the side server, wherein the temporary steady state data comprises three-phase voltage and current instantaneous values; The side server is used for analyzing the transient steady state data by running a broadband oscillation on-line analysis algorithm to obtain an analysis result, and comprises the steps of calculating full-wave active power P based on the three-phase voltage and current instantaneous values, carrying out integral FFT on the full-wave active power P to obtain active amplitude values of a frequency domain, carrying out sliding window FFT processing on the full-wave active power P to obtain active amplitude values PFreqMov of a plurality of groups of frequency domains, extracting maximum values Pmax of each frequency in all time from the active amplitude values PFreqMov according to frequency groups, screening out frequency points f which are likely to generate oscillation based on a preset threshold value Plim, judging whether damping ratio calculation conditions are met or not for frequency points except for direct current components in the frequency points f based on a preset threshold value PDCalLim, if so, calculating damping ratios of corresponding frequency points, carrying out clustering processing on the frequency points f, dividing the frequency points with frequency difference not exceeding the preset threshold value CLim into identical oscillation frequency clusters, and transmitting the analysis result and at least part of real-time data to the cloud side server; And the cloud side server performs centralized display and comparative analysis on the multi-station data corresponding to the at least one side server.

Description

New energy broadband oscillation online monitoring and analyzing method and system for cloud edge end architecture Technical Field The invention belongs to the field of new energy access and control, and particularly relates to a new energy broadband oscillation online monitoring and analyzing method and system of a cloud edge end architecture. Background The new energy power generation development is rapid, the new energy unit is connected to the power grid by adopting power electronic equipment, a large number of new energy power generation equipment is connected to the power grid, and then interacts with the power grid and other new energy power generation equipment, so that complex oscillation phenomena in a wide frequency band range such as a plurality of oscillation modes, time variation of the oscillation modes and the like can occur in the power grid, and in order to ensure the running stability of the power system, the wide frequency oscillation modes of the power grid need to be monitored in real time. However, achieving this objective faces a significant technical bottleneck in the contradiction between the massive high frequency transient data transfer and the real-time processing requirements. In order to realize effective broadband oscillation monitoring, intelligent terminals are deployed at the new energy unit end and the station grid-connected point to acquire data with high sampling rate, and original transient state recording data such as three-phase voltage and current instantaneous values are acquired. For a large-scale new energy station comprising a large number of units and grid-connected points, if continuously generated massive raw data are directly uploaded to a central cloud platform for analysis and processing, huge transmission pressure is brought to a communication network, bandwidth consumption is huge, and transmission delay is remarkably increased. Meanwhile, the huge high-frequency data is processed in a centralized way in the cloud, complex broadband oscillation analysis and calculation are carried out, extremely high requirements are put on calculation resources of a cloud server, strict requirements of broadband oscillation on-line monitoring on real-time performance and high efficiency are difficult to meet, and the contradiction is more remarkable particularly in a large-scale new energy station access scene. The existing centralized data processing architecture is difficult to effectively support the efficient and real-time online monitoring and analysis of the new energy broadband oscillation based on the original measurement data. Disclosure of Invention The invention aims to provide a new energy broadband oscillation online monitoring analysis method and system of a cloud edge end architecture, which at least solve or improve the problem that the existing centralized data processing architecture in the prior art is difficult to effectively support the new energy broadband oscillation efficient and real-time online monitoring analysis based on original measurement data In order to achieve the above purpose, the present invention adopts the following technical scheme: the first aspect of the invention provides a new energy broadband oscillation online monitoring and analyzing method of a cloud edge end architecture, which comprises the following steps: the intelligent terminal at the end side acquires temporary steady state data of a new energy unit and a grid-connected point and transmits the temporary steady state data to the side server, wherein the temporary steady state data comprises three-phase voltage and current instantaneous values; The method comprises the steps of operating a broadband oscillation on-line analysis algorithm by an edge server to analyze transient steady-state data to obtain an analysis result, wherein the analysis result comprises the steps of calculating full-wave active power P based on three-phase voltage and current instantaneous values, carrying out integral FFT on the full-wave active power P to obtain active amplitude values of a frequency domain, carrying out sliding window FFT processing on the full-wave active power P to obtain active amplitude values PFreqMov of a plurality of groups of frequency domains, extracting maximum values Pmax of each frequency in all time from the active amplitude values PFreqMov according to frequency groups, screening out frequency points f which are possibly subjected to oscillation based on a preset threshold value Plim, judging whether damping ratio calculation conditions are met or not based on a preset threshold value PDCalLim on frequency points except direct current components in the frequency points f, if so, calculating damping ratios of corresponding frequency points, carrying out clustering processing on the frequency points f, dividing the frequency points with the frequency difference not exceeding the preset threshold value CLim into identical oscillation frequency clusters, and transm