CN-122026315-A - Low-voltage area impedance calculation method based on synchronous measurement data

CN122026315ACN 122026315 ACN122026315 ACN 122026315ACN-122026315-A

Abstract

The application provides a low-voltage area impedance calculation method based on synchronous measurement data, which comprises the steps of obtaining a time sequence data set containing voltage fluctuation by obtaining synchronous measurement data and an upstream node voltage sequence from a low-voltage area acquisition device, extracting a voltage consistency index from a preliminary impedance parameter estimation value, fusing the synchronous measurement data through a Kalman filtering algorithm to obtain updated voltage fluctuation capturing precision of the low-voltage area acquisition device, adjusting input parameters of an optimization model established based on the Kalman filtering algorithm according to the updated voltage fluctuation capturing precision, outputting an impedance parameter iteration sequence for obtaining a target voltage difference value, detecting the synchronous measurement data of the low-voltage area acquisition device by adopting a final line impedance identification result to verify the filling effect of a parameter missing part, and obtaining the overall voltage consistency index of the low-voltage area.

Inventors

LIU DANHUA
QIU DEGUI
HAN LEI
FANG WEN
FENG LINLIN
MA SIYUAN
FENG XIN
ZHANG WENQI
LI SHUANGSHUANG
DUAN YUQING
WANG KAI
DING JIANSHUN
SHU QIQI
REN MIN
HUANG XIN
ZHAO LU
KANG YU

Assignees

国网安徽省电力有限公司营销服务中心
国网安徽省电力有限公司蚌埠供电公司

Dates

Publication Date: 20260512
Application Date: 20251231

Claims (7)

1. The low-voltage area impedance calculation method based on the synchronous measurement data is characterized by comprising the following steps of: acquiring synchronous measurement data and an upstream node voltage sequence from a low-voltage station area acquisition device, and generating a time sequence data set containing voltage fluctuation; Calculating a difference sequence of each moment value of an upstream node voltage sequence and each moment value of the synchronous measurement data voltage according to the time sequence data set, extracting statistical distribution characteristics of the difference sequence, wherein the statistical distribution characteristics comprise a mean value, a standard deviation and kurtosis, and when the statistical distribution characteristics exceed a preset voltage deviation threshold value, adopting a least square method to process a linear equation set constructed by voltage drop values in the difference sequence and load current data at corresponding moments to generate a preliminary impedance parameter estimation value; Extracting a voltage consistency index from the preliminary impedance parameter estimation value, wherein the voltage consistency index comprises a consistency coefficient and a deviation range, and generating updated voltage fluctuation capturing precision by fusing synchronous measurement data through a Kalman filtering algorithm; According to the updated voltage fluctuation capturing precision, adjusting input parameters of a Kalman filtering algorithm optimization model, wherein the input parameters comprise the synchronous measurement data and the voltage consistency index, and generating an impedance parameter iteration sequence of a target voltage difference value; Generating a dynamic feedback factor through deviation analysis of the voltage consistency index and the impedance parameter iteration sequence, and optimizing the dynamic feedback factor through a gradient descent algorithm when the convergence speed of the impedance parameter iteration sequence is lower than a preset speed threshold value to generate a line impedance identification result comprising resistance and reactance parameter values; And detecting the missing value of the synchronous measurement data, identifying a parameter missing part, filling the parameter missing part by adopting an interpolation algorithm, verifying the filling effect based on the line impedance identification result, and generating a low-voltage area integral voltage consistency index comprising a consistency coefficient, a deviation range and a fluctuation range.
2. The method for calculating impedance of a low-voltage station based on synchronous measurement data according to claim 1, wherein the step of acquiring the synchronous measurement data and the upstream node voltage sequence from the low-voltage station acquisition device to generate a time-series data set including voltage fluctuations comprises: reading voltage sampling data uploaded by an intelligent ammeter from a data interface of a low-voltage station area acquisition device, and performing time stamp calibration on the voltage sampling data based on a preset sampling period to generate synchronous measurement data; Reading an upstream node voltage value corresponding to the time stamp calibration from a transformer monitoring terminal, and generating an upstream node voltage sequence in a time sequence arrangement; And performing difference calculation on the synchronous measurement data and the upstream node voltage sequence, marking as a voltage fluctuation point when the absolute value of the difference exceeds a preset voltage deviation threshold value, determining a fluctuation period based on continuous voltage fluctuation points, extracting voltage data in the fluctuation period, and generating the time sequence data set containing voltage fluctuation.
3. The method for calculating impedance of a low-voltage transformer area based on synchronous measurement data according to claim 1, wherein the calculating a difference sequence between each time value of an upstream node voltage sequence and each time value of the synchronous measurement data voltage according to the time series data set, extracting a statistical distribution feature of the difference sequence, comprises: extracting an upstream node voltage sequence from the time sequence data set, calculating the deviation square sum of the voltage value at each moment and the sequence mean value, dividing the deviation square sum by the total number of data points, and generating the upstream node voltage variance; Subtracting the voltage value at each moment in the synchronous measurement data in the time sequence data set from the voltage value of the upstream node at the corresponding moment to generate the difference sequence; Calculating arithmetic mean values of all data points from the difference sequence to serve as mean values, calculating square roots of square sums of deviation of all data points and the mean values to serve as standard deviations, calculating fourth-order central moment of normalized data to serve as kurtosis, and generating the statistical distribution characteristics.
4. The method for calculating the impedance of the low-voltage transformer area based on the synchronous measurement data according to claim 1, wherein the step of extracting the voltage consistency index from the preliminary impedance parameter estimation value, and fusing the synchronous measurement data by a kalman filter algorithm to generate updated voltage fluctuation capturing precision comprises the steps of: Calculating theoretical voltage drop of each measuring point according to the estimated value of the preliminary impedance parameter and combining load current data at corresponding time, comparing the theoretical voltage drop with actual measured voltage drop, calculating a pearson correlation coefficient as the consistency coefficient, and counting the maximum value and the minimum value of the difference value between the theoretical voltage drop and the actual measured voltage drop to generate the deviation range; And constructing a Kalman filtering state space equation based on the voltage consistency index, setting a voltage fluctuation value as a state variable, generating a posterior estimated value sequence by using the synchronous measurement data as an observation variable through a state transfer equation and an observation equation, calculating a root mean square value of deviation between the posterior estimated value sequence and the synchronous measurement data sequence, and normalizing to generate the updated voltage fluctuation capturing precision.
5. The method for calculating the impedance of the low-voltage transformer area based on the synchronous measurement data according to claim 1, wherein the step of adjusting the input parameters of the kalman filter algorithm optimization model according to the updated voltage fluctuation capturing precision to generate the iterative sequence of the impedance parameters of the target voltage difference value comprises the steps of: Calculating an accuracy weight coefficient based on the updated voltage fluctuation capturing accuracy, and adjusting the synchronous measurement data and the voltage consistency index to generate a calibration parameter set; And constructing a Kalman filtering state space equation based on the calibration parameter set, setting an impedance value as a state variable, predicting the impedance parameter value through a state transfer equation, adjusting Kalman gain based on the predicted value and an actual measured voltage drop difference value, generating a corrected impedance parameter sequence, and arranging to generate the impedance parameter iteration sequence.
6. The method for calculating impedance of a low-voltage transformer area based on synchronous measurement data according to claim 1, wherein the generating a dynamic feedback factor by the deviation analysis of the voltage consistency index and the impedance parameter iteration sequence, when the convergence speed of the impedance parameter iteration sequence is lower than a preset speed threshold, optimizing the dynamic feedback factor by a gradient descent algorithm, generating a line impedance identification result including resistance and reactance parameter values, includes: calculating a deviation sequence from the voltage consistency index and the impedance parameter iteration sequence, generating a deviation mean value and a deviation change rate based on the deviation sequence, and calculating the deviation mean value divided by the deviation change rate to generate the dynamic feedback factor; Calculating Euclidean distance of two adjacent iterations of the impedance parameter iteration sequence divided by time interval to generate a convergence speed value; When the convergence speed value is lower than a preset speed threshold value, adjusting the deviation weight and the convergence speed adjustment coefficient of the dynamic feedback factor based on a gradient descent algorithm, and correcting the last impedance parameter value of the impedance parameter iteration sequence based on the optimized dynamic feedback factor to generate the line impedance identification result, wherein the line impedance identification result comprises a resistor and a reactance parameter value.
7. The method for calculating impedance of a low-voltage transformer area based on synchronous measurement data according to claim 1, wherein the step of detecting the missing value of the synchronous measurement data, identifying a missing parameter part, and filling the missing parameter part by using an interpolation algorithm comprises: scanning the synchronous measurement data point by point, marking blank values or data points exceeding a preset voltage range as the parameter missing parts, and recording time stamps and position indexes; And calculating average change rate based on the effective data points before and after the parameter missing part, generating an interpolation result by adopting a linear interpolation algorithm, replacing the parameter missing part, and generating a complement sequence.

Description

Low-voltage area impedance calculation method based on synchronous measurement data Technical Field The invention relates to the technical field of information, in particular to a low-voltage transformer area impedance calculation method based on synchronous measurement data. Background In the power system, the low-voltage area is used as the last ring for connecting the power grid and the user, and the running stability and the power supply quality of the low-voltage area directly influence the user power consumption experience and the power grid running efficiency. The line parameter data of the low-voltage transformer area is an important basis for guaranteeing voltage stability and power distribution, and particularly, the accurate line parameter data is particularly critical in the present day of rapid change of electricity demand. However, due to frequent extension and reconstruction by users, the actual line parameters of the low-voltage transformer area often do not match the ledger records, resulting in data update lag, thereby affecting the reliability and efficiency of the grid operation. This problem is particularly prominent in urban and rural junctions, which are rapidly developed, and needs to be solved in order to improve the management level and the power supply quality of the low-voltage transformer area. Currently, the acquisition of the line parameters of the low-voltage transformer area mainly depends on manual inspection and periodic updating of the ledger information. However, this method often has difficulty reflecting the actual state of the line in real time when it is frequently extended in the face of the user. For example, users may add electric equipment privately or change the connection mode of the lines, which may cause deviation between the ledger information and the actual line parameters. Some areas attempt to infer line parameters by collecting data from smart meters, but these methods typically only focus on measuring data at a single point in time, ignoring the dynamic correlation between voltage fluctuations and line parameter changes. The static analysis mode cannot adapt to the actual situation that the power load in the low-voltage transformer area is frequently changed, and the dynamic characteristics of the line parameters are difficult to accurately capture. In the low-voltage transformer area, voltage consistency is one of core indexes for ensuring power supply quality, and the voltage consistency refers to that deviation between the voltage of an upstream node (such as a transformer) and the measured voltage of a smart meter is kept within a reasonable range. However, voltage consistency is difficult to maintain due to line parameter data loss. Particularly, when the smart meter captures voltage fluctuation through a precise time setting technology, uncertainty of parameters such as line impedance and the like can cause voltage deviation to be further amplified. There is a dynamic feedback relationship between this uncertainty and the voltage fluctuations, i.e. inaccuracy of the parameters leads to voltage deviations which in turn further interfere with the estimation of the parameters. This dynamic feedback relationship makes it extremely complex to accurately identify the line impedance. Specifically, in the actual service scenario, when a user increases power electric equipment in the low-voltage transformer area, the line impedance may change due to the newly increased load, but the ledger information cannot be updated in time. At this time, the smart meter may detect abnormal voltage fluctuations, but the system cannot determine whether the fluctuations are caused by line impedance changes or other factors due to lack of accurate impedance parameters. This situation may not only lead to an overrun in voltage, affecting the quality of the electricity used by the user, but may also increase the risk of grid operation. Therefore, how to dynamically adjust the impedance parameter estimation based on the synchronous measurement data to ensure the voltage consistency becomes a key problem for accurately identifying the line impedance of the low-voltage transformer area under the condition that the line parameter data is lost due to frequent extension of users Disclosure of Invention The invention provides a low-voltage transformer area impedance calculation method based on synchronous measurement data, which mainly comprises the following steps: acquiring synchronous measurement data and an upstream node voltage sequence from a low-voltage station area acquisition device, and generating a time sequence data set containing voltage fluctuation; Calculating a difference sequence of each moment value of an upstream node voltage sequence and each moment value of the synchronous measurement data voltage according to the time sequence data set, extracting statistical distribution characteristics of the difference sequence, wherein the statistical distribution characte