CN-121978465-A - Power distribution network fault accurate positioning method and system based on multi-source data fusion

CN121978465ACN 121978465 ACN121978465 ACN 121978465ACN-121978465-A

Abstract

The application relates to the technical field of fault positioning, in particular to a method and a system for accurately positioning faults of a power distribution network based on multi-source data fusion, wherein the method comprises the steps of collecting corona current data of lines in each section of the power distribution network in a preset period of time, and current data and voltage data of two ends of the lines in each section in real time; the method comprises the steps of obtaining pulse decreasing coefficients of all section lines according to decreasing conditions of pulse amplitudes in corona current data of all section lines, obtaining the width of each section line according to rising time and duration of pulses in the corona current data of all section lines, obtaining corona discharge coefficients of all section lines, obtaining electric distortion characteristic values of all section lines, adjusting control parameters of chaotic mapping, and carrying out fault location on a power distribution network by means of chaotic mapping after the control parameters are adjusted and a gray wolf optimization algorithm. The application aims to improve the accuracy of fault location.

Inventors

LI WEI
WU LINLIN
LIU BAIYUAN
WANG LEXING
SONG XIAOBO
FENG WENCHENG
HU ZHIWEI
Du tianqi
HUANG MENGYAO

Assignees

国网河南省电力公司商丘供电公司

Dates

Publication Date: 20260505
Application Date: 20260316

Claims (10)

1. A power distribution network fault accurate positioning method based on multi-source data fusion is characterized by comprising the following steps: Acquiring corona current data of each section of lines in the power distribution network within a preset period of time, and current data and voltage data of two ends of each section of lines in real time; Acquiring pulse decreasing coefficients of all section lines according to decreasing conditions of pulse amplitudes in corona current data of all section lines, acquiring width kurtosis of all section lines according to rising time and duration of pulses in the corona current data of all section lines, and acquiring corona discharge coefficients of all section lines according to distribution conditions of rising time of all pulses in the corona current data of all section lines, the pulse decreasing coefficients and the width kurtosis; the method comprises the steps of respectively comparing current data and voltage data at two ends of each section line, and acquiring an electric distortion characteristic value of each section line by combining distortion conditions of the voltage data and the distortion conditions of the current data at two ends of each section line; adjusting control parameters of chaotic mapping through the corona discharge coefficient and the electric distortion characteristic value; and performing fault location on the power distribution network by using the chaotic mapping after adjusting the control parameters and combining with a gray wolf optimization algorithm.
2. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 1, wherein the pulse decreasing coefficient obtaining process is as follows: Calculating a first-order differential result of all pulse peaks in corona current data of each section line in time sequence; the pulse decrement coefficient is the number duty ratio of the negative numbers in the first-order difference result.
3. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 1, wherein the obtaining process of the kurtosis is as follows: and acquiring the pulse with the maximum peak value in the corona current data of each section line, calculating the product of the rising time and half-wave time of the acquired pulse, and comparing the product with the square ratio of the peak width of the acquired pulse to obtain the width kurtosis of each section line.
4. The precise positioning method for power distribution network faults based on multi-source data fusion as claimed in claim 1, wherein the process for obtaining the corona discharge coefficient is as follows: Performing normal fitting on the rising time and probability density of all pulse peaks in corona current data of each section line to obtain a normal curve, and calculating the fitting goodness of the normal curve; the corona discharge coefficient is inversely proportional to the kurtosis and the goodness of fit respectively and is directly proportional to the pulse decreasing coefficient.
5. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 1, wherein the obtaining process of the electric distortion characteristic value is as follows: Acquiring an electric difference coefficient of each section line according to the difference degree of the current data at the two ends of each section line and the difference degree of the current data at the two ends of each section line; Synthesizing the distortion condition of voltage data and the distortion condition of current data at two ends of each section to obtain the harmonic correction coefficient of each section line; The electric distortion characteristic value is positively correlated with the electric difference coefficient and the harmonic correction coefficient respectively.
6. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 5, wherein the method for acquiring the electric difference coefficient is as follows: calculating the difference of voltage data at two ends of each section line, and calculating the difference of current data at two ends of each section line; the electrical difference coefficient is the average of the difference and the difference amount.
7. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 5, wherein the method for acquiring the harmonic correction coefficients is as follows: calculating the arithmetic average of the total distortion rate of the current harmonic waves of the current data at the two ends of each section of the circuit; The harmonic correction coefficient is a weighted sum of the average value and the arithmetic average value.
8. The method for accurately positioning faults of a power distribution network based on multi-source data fusion as claimed in claim 1, wherein the process of adjusting control parameters of chaotic mapping is as follows: And obtaining segmentation threshold values of corona discharge coefficients of all section lines, and adjusting control parameters of the chaotic mapping through average levels of electric distortion characteristic values of all section lines with the corona discharge coefficients larger than the segmentation threshold values.
9. The method for accurately positioning the faults of the power distribution network based on multi-source data fusion as claimed in claim 8, wherein the method for adjusting the control parameters of the chaotic map is as follows: the average value of the electric distortion characteristic values of all section lines with the corona discharge coefficient larger than the segmentation threshold value is recorded as a distortion average value; Calculating the product value of the length of the preset value interval of the control parameter and the distortion mean value, and taking the sum of the product value and the preset minimum value of the control parameter as the adjusted control parameter.
10. A power distribution network fault accurate positioning system based on multi-source data fusion, comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor realizes the steps of a power distribution network fault accurate positioning method based on multi-source data fusion according to any one of claims 1-9 when executing the computer program.

Description

Power distribution network fault accurate positioning method and system based on multi-source data fusion Technical Field The application relates to the technical field of fault positioning, in particular to a power distribution network fault accurate positioning method and system based on multi-source data fusion. Background The power distribution network is an important link for distributing electric energy of the power system, along with economic development, the scale of the power distribution network is rapidly enlarged, nodes are increased, a network topology structure is complicated, and the difficulty in positioning faults of the power distribution network is increased. In order to improve the accuracy and the anti-interference capability of fault location, a multi-source data fusion method is generally adopted, and the fault tolerance of data is improved by integrating multiple data sources. The gray wolf optimization algorithm is one of the current commonly used power distribution network fault positioning algorithms, but the optimization effect is easily influenced by an initial population, the initial population of the gray wolf optimization algorithm is initialized through Tent mapping at present, control parameters in Tent mapping usually take a fixed value, however, in rainy weather, voltage and current are easily influenced by rainwater to generate distortion, the fault positioning difficulty is increased, if the control parameters are too small, the population searching range is smaller, the fault interval is concentrated in a certain range and cannot cover all candidate intervals, if the control parameters are too large, the stability of a chaotic sequence is damaged, the randomness of the fault interval is increased, and the fault positioning accuracy is further influenced. Disclosure of Invention In view of the above, it is necessary to provide a method and a system for accurately positioning faults of a power distribution network based on multi-source data fusion, which improve the accuracy of fault positioning compared with the traditional method for accurately positioning faults of the power distribution network based on multi-source data fusion: In a first aspect, an embodiment of the present application provides a method for accurately positioning a fault of a power distribution network based on multi-source data fusion, where the method includes the following steps: Acquiring corona current data of each section of lines in the power distribution network within a preset period of time, and current data and voltage data of two ends of each section of lines in real time; Acquiring pulse decreasing coefficients of all section lines according to decreasing conditions of pulse amplitudes in corona current data of all section lines, acquiring width kurtosis of all section lines according to rising time and duration of pulses in the corona current data of all section lines, and acquiring corona discharge coefficients of all section lines according to distribution conditions of rising time of all pulses in the corona current data of all section lines, the pulse decreasing coefficients and the width kurtosis; the method comprises the steps of respectively comparing current data and voltage data at two ends of each section line, and acquiring an electric distortion characteristic value of each section line by combining distortion conditions of the voltage data and the distortion conditions of the current data at two ends of each section line; adjusting control parameters of chaotic mapping through the corona discharge coefficient and the electric distortion characteristic value; and performing fault location on the power distribution network by using the chaotic mapping after adjusting the control parameters and combining with a gray wolf optimization algorithm. In one embodiment, the pulse decreasing coefficient is obtained by: Calculating a first-order differential result of all pulse peaks in corona current data of each section line in time sequence; the pulse decrement coefficient is the number duty ratio of the negative numbers in the first-order difference result. In one embodiment, the obtaining of the kurtosis is: and acquiring the pulse with the maximum peak value in the corona current data of each section line, calculating the product of the rising time and half-wave time of the acquired pulse, and comparing the product with the square ratio of the peak width of the acquired pulse to obtain the width kurtosis of each section line. In one embodiment, the process of obtaining the corona discharge coefficient is: Performing normal fitting on the rising time and probability density of all pulse peaks in corona current data of each section line to obtain a normal curve, and calculating the fitting goodness of the normal curve; the corona discharge coefficient is inversely proportional to the kurtosis and the goodness of fit respectively and is directly proportional to the pulse decreasin