CN114912490A - Characteristic current identification and verification method and device based on Fourier transform algorithm - Google Patents

Characteristic current identification and verification method and device based on Fourier transform algorithm Download PDF

Info

Publication number
CN114912490A
CN114912490A CN202210536353.8A CN202210536353A CN114912490A CN 114912490 A CN114912490 A CN 114912490A CN 202210536353 A CN202210536353 A CN 202210536353A CN 114912490 A CN114912490 A CN 114912490A
Authority
CN
China
Prior art keywords
current
fourier transform
characteristic
signal
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210536353.8A
Other languages
Chinese (zh)
Inventor
徐韬
袁健
杨依睿
杨思洁
周佑
胡瑛俊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Marketing Service Center of State Grid Zhejiang Electric Power Co Ltd
Original Assignee
Marketing Service Center of State Grid Zhejiang Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Marketing Service Center of State Grid Zhejiang Electric Power Co Ltd filed Critical Marketing Service Center of State Grid Zhejiang Electric Power Co Ltd
Priority to CN202210536353.8A priority Critical patent/CN114912490A/en
Publication of CN114912490A publication Critical patent/CN114912490A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08—Feature extraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G06F17/141—Discrete Fourier transforms
    • G06F17/142—Fast Fourier transforms, e.g. using a Cooley-Tukey type algorithm
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52—Outage or fault management, e.g. fault detection or location

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Analysis (AREA)
  • Discrete Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Algebra (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Measurement Of Resistance Or Impedance (AREA)

Abstract

The invention discloses a characteristic current identification and verification method and device based on a Fourier transform algorithm. The method adopts the technical scheme that: firstly, recording current data by using a wave recording plate, uploading the current data through a network cable, and converting the received data by using an analysis module; then, Fourier transform is carried out on the converted current data to obtain a frequency domain curve, a starting point of a signal is obtained according to the frequency domain curve, and the current data are segmented and sliced according to current characteristic code bits sent by a carrier module; and finally, performing signal quality analysis and power quality analysis on the sliced current data to obtain signal quality and power quality results. The invention combines the characteristic current identification function to simulate the operation condition of the field distribution area, thereby realizing the topology identification function of the distribution area.

Description

Characteristic current identification and verification method and device based on Fourier transform algorithm
Technical Field
The invention belongs to the field of distribution room topology identification, and particularly relates to a characteristic current identification and verification method and device based on a Fourier transform algorithm.
Background
At present, a complete and accurate device is not provided in the verification of the district topology identification function in China, and the situations of district chaos and district identification error exist on site, so that the field district management is disordered, and the operation monitoring, fault positioning, early warning and the like of the electric energy meter are influenced.
The existing power frequency voltage distortion technology realizes the topology identification of a transformer area by sending power frequency voltage signals which do not interfere with carrier communication, and the technology is greatly influenced by line distance, power supply quality and equipment on a line, so that the accuracy rate of identification effect is low.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a characteristic current identification and verification method and device based on a Fourier transform algorithm to simulate the operation condition of a field transformer area and realize the topological identification of the transformer area.
Therefore, the invention adopts a technical scheme that: the characteristic current identification and verification method based on the Fourier transform algorithm comprises the following steps:
firstly, recording current data by using a wave recording plate, uploading the current data through a network cable, and converting the received data by using an analysis module;
then, Fourier transform is carried out on the converted current data to obtain a frequency domain curve, a starting point of a signal is obtained according to the frequency domain curve, and the current data are segmented and sliced according to current characteristic code bits sent by a carrier module;
and finally, performing signal quality analysis and power quality analysis on the sliced current data to obtain signal quality and power quality results.
Further, the flow of signal quality analysis is as follows:
firstly, judging whether the current is greater than a set threshold, if the current is less than or equal to the set threshold, considering the current as a low level, judging the next point without a signal; if the signal is larger than the set threshold value, recording the number n1 of the points larger than the set threshold value, then finding the low level, recording the number of the low level points as n2, and calculating the signal quality parameter according to the number of the high level points and the low level points.
Further, the power quality analysis means: and analyzing the harmonic voltage content, the total harmonic distortion rate of the voltage, the inter-harmonic voltage content of 0-800Hz and the maximum allowable harmonic current according to Fourier transform.
Further, the frequency spectrum information of the characteristic current signal is obtained by discrete Fourier transform on the converted current data, and the calculation formula is as follows:
Figure BDA0003643803140000021
Figure BDA0003643803140000022
wherein, a k Representing the real part of the k-th harmonic, b k The imaginary part of the kth harmonic wave is represented, N represents the number of data points of the power frequency cycle wave, and k represents the harmonic frequency; t is 0 Represents a signal period of 100 ms; t represents a signal transmission time;
the attenuation state of the signal amplitude is calculated by quantizing the amplitude of the sinusoidal signal by utilizing a cross-correlation function, and the calculation process is as follows:
x(t i )＝s(t i )+G(t i ) I is 1, 2, … …, N, where x (t) i ) To observe the signal, s (t) i ) Being sinusoidal signals, G (t) i ) Representing additive white gaussian noise with variance σ, the simulation parameters are as follows:
frequency f 0 10Hz, initial phase
Figure BDA0003643803140000023
The amplitude a is 1;
furthermore, the line state monitoring circuit of the wave recording plate collects characteristic current signals by using a 14-bit high-speed AD sampling chip, uses the FPGA XC7Z020 as a data processing unit, and uses a carrier channel as an uplink channel to realize the collection and report of the transmitted current signals.
The invention also provides another technical scheme: the characteristic current identification and calibration device based on the Fourier transform algorithm comprises a concentrator, a modular terminal, a fusion terminal, a circuit breaker, a two-type concentrator, an electric energy meter and a carrier module;
when the carrier module sends the characteristic current signals, the corresponding characteristic current signals are sent to a circuit breaker or a two-type concentrator through an electric energy meter, the circuit breaker or the two-type concentrator is connected with a wave recording plate, the wave recording plate analyzes and quantizes the characteristic currents through high-speed AD sampling, the analysis results and the normal state values acquired by the carrier module in the normal communication process are analyzed and compared, data analysis is carried out through a Fourier transform algorithm based on time domains and frequency domains, the characteristic current information is sent to the concentrator, a modularized terminal or a fusion terminal, the concentrator, the modularized terminal or the fusion terminal are combed, the results are reported to a main station, and the platform area topology identification function is achieved.
The invention combines the characteristic current identification function to simulate the operation condition of the field distribution area, thereby realizing the distribution area topology identification function.
Drawings
FIG. 1 is a flow chart of a characteristic current identification verification method of the present invention;
FIG. 2 is a flow chart of signal quality analysis according to the present invention;
fig. 3 is a block diagram of a characteristic current identification verification device of the present invention.
Detailed Description
The technical scheme of the invention is more clearly and completely described below by combining the embodiment and the attached drawings of the specification.
Example 1
The embodiment provides a characteristic current identification and verification method based on a fourier transform algorithm, as shown in fig. 1, the steps are as follows:
firstly, a characteristic current identification and verification method based on a Fourier transform algorithm comprises the following steps:
firstly, recording current data by using a wave recording plate, uploading the current data through a network cable, and converting the received data by using an analysis module;
then, Fourier transform is carried out on the converted current data to obtain a frequency domain curve, a starting point of a signal is obtained according to the frequency domain curve, and the current data are segmented and sliced according to current characteristic code bits sent by a carrier module;
and finally, performing signal quality analysis and power quality analysis on the sliced current data to obtain signal quality and power quality results.
Specifically, the flow of signal quality analysis is as follows:
firstly, judging whether the current is greater than a set threshold, if the current is less than or equal to the set threshold, considering the current as a low level, judging the next point without a signal; if the signal is larger than the set threshold value, recording the number n1 of the points larger than the set threshold value, then finding the low level, recording the number of the low level points as n2, and calculating the signal quality parameter according to the number of the high level points and the low level points.
Specifically, the power quality analysis means: and analyzing the harmonic voltage content, the total harmonic distortion rate of the voltage, the inter-harmonic voltage content of 0-800Hz and the maximum allowable harmonic current according to Fourier transform.
Specifically, the frequency spectrum information of the characteristic current signal is obtained by discrete fourier transform on the converted current data, and the calculation formula is as follows:
Figure BDA0003643803140000031
Figure BDA0003643803140000032
wherein, a k Representing the real part of the k-th harmonic, b k The imaginary part of the kth harmonic wave is represented, N represents the number of data points of the power frequency cycle wave, and k represents the harmonic frequency; t is a unit of 0 Represents a signal period of 100 ms; t represents a signal transmission time;
the attenuation state of the signal amplitude is calculated by quantizing the amplitude of the sinusoidal signal by utilizing a cross-correlation function, and the calculation process is as follows:
x(t i )＝s(t i )+G(t i ) I is 1, 2, … …, N, wherein x (t) i ) To observe the signal, s (t) i ) Being sinusoidal signals, G (t) i ) Representing additive white gaussian noise with variance σ, the simulation parameters are as follows:
frequency f 0 10Hz, initial phase
Figure BDA0003643803140000041
The amplitude a is 1;
specifically, the line state monitoring circuit of the wave recording plate collects characteristic current signals by using a 14-bit high-speed AD sampling chip, uses an FPGA XC7Z020 as a data processing unit, and uses a carrier channel as an uplink channel to realize collection and report of transmitted current signals.
Example 2
The embodiment provides a characteristic current identification calibrating device based on a Fourier transform algorithm, which comprises a concentrator, a modular terminal, a fusion terminal, a circuit breaker, a two-type concentrator, an electric energy meter and a carrier module, as shown in FIG. 3.
When the carrier module sends the characteristic current signals, the corresponding characteristic current signals are sent to a circuit breaker or a two-type concentrator through an electric energy meter, the circuit breaker or the two-type concentrator is connected with a wave recording plate, the wave recording plate analyzes and quantizes the characteristic currents through high-speed AD sampling, the analysis results and the normal state values acquired by the carrier module in the normal communication process are analyzed and compared, data analysis is carried out through a Fourier transform algorithm based on time domains and frequency domains, the characteristic current information is sent to the concentrator, a modularized terminal or a fusion terminal, the concentrator, the modularized terminal or the fusion terminal are combed, the results are reported to a main station, and the platform area topology identification function is achieved.
The line state monitoring circuit of the wave recording plate collects characteristic current signals by using a 14-bit high-speed AD sampling chip, uses an FPGA XC7Z020 as a data processing unit and uses a carrier channel as an uplink channel to realize the collection and report of transmitted current signals.
The above embodiments are merely preferred embodiments of the present invention. Any simple modification, equivalent change and modification of the above embodiments according to the technical spirit of the present invention fall within the scope of the present invention.

Claims (7)

1. The characteristic current identification and verification method based on the Fourier transform algorithm is characterized in that,
firstly, recording current data by using a wave recording plate, uploading the current data through a network cable, and converting the received data by using an analysis module;
then, Fourier transform is carried out on the converted current data to obtain a frequency domain curve, a starting point of a signal is obtained according to the frequency domain curve, and the current data are segmented and sliced according to current characteristic code bits sent by a carrier module;
and finally, performing signal quality analysis and power quality analysis on the sliced current data to obtain signal quality and power quality results.
2. The signature current identification verification method based on the Fourier transform algorithm as claimed in claim 1, wherein the signal quality analysis flow is as follows:
firstly, judging whether the current is greater than a set threshold, if the current is less than or equal to the set threshold, considering the current as a low level, judging the next point without a signal; if the signal is larger than the set threshold value, recording the number n1 of the points larger than the set threshold value, then finding the low level, recording the number of the low level points as n2, and calculating the signal quality parameter according to the number of the high level points and the low level points.
3. The characteristic current identification and verification method based on the Fourier transform algorithm according to claim 1, wherein the power quality analysis means that: and analyzing the harmonic voltage content, the total harmonic distortion rate of the voltage, the inter-harmonic voltage content of 0-800Hz and the maximum allowable harmonic current according to Fourier transform.
4. The characteristic current identification and verification method based on the Fourier transform algorithm according to claim 1, wherein the frequency spectrum information of the characteristic current signal is obtained by discrete Fourier transform on the converted current data, and the calculation formula is as follows:
Figure FDA0003643803130000011
Figure FDA0003643803130000012
wherein, a k Representing the real part of the k-th harmonic, b k The imaginary part represents the kth harmonic, N represents the number of data points of power frequency cycle, and k represents the number of harmonic times; t is 0 Represents a signal period of 100 ms; t represents a signal transmission time;
the attenuation state of the signal amplitude is calculated by quantizing the amplitude of the sinusoidal signal by utilizing a cross-correlation function, and the calculation process is as follows:
x(t i )＝s(t i )+G(t i ) I is 1, 2, … …, N, where x (t) i ) To observe the signal, s (t) i ) Being sinusoidal signals, G (t) i ) Representing additive white gaussian noise with variance σ, the simulation parameters are as follows:
frequency f 0 10Hz, initial phase
Figure FDA0003643803130000021
The amplitude a is 1.
5. The characteristic current identification and verification method based on the Fourier transform algorithm as claimed in claim 1, wherein a line state monitoring circuit of the wave recording plate collects characteristic current signals by using a 14-bit high-speed AD sampling chip, and collects and reports transmission current signals by using an FPGA XC7Z020 as a data processing unit and a carrier channel as an uplink channel.
6. The characteristic current identification and calibration device based on the Fourier transform algorithm is characterized by comprising a concentrator, a modularized terminal, a fusion terminal, a circuit breaker, a two-type concentrator, an electric energy meter and a carrier module;
when the carrier module sends the characteristic current signals, the corresponding characteristic current signals are sent to a circuit breaker or a two-type concentrator through an electric energy meter, the circuit breaker or the two-type concentrator is connected with a wave recording plate, the wave recording plate analyzes and quantizes the characteristic currents through high-speed AD sampling, the analysis results and the normal state values acquired by the carrier module in the normal communication process are analyzed and compared, data analysis is carried out through a Fourier transform algorithm based on time domains and frequency domains, the characteristic current information is sent to the concentrator, a modularized terminal or a fusion terminal, the concentrator, the modularized terminal or the fusion terminal are combed, the results are reported to a main station, and the platform area topology identification function is achieved.
7. The characteristic current identification and verification device based on the Fourier transform algorithm according to claim 6, wherein a line state monitoring circuit of the wave recording plate collects characteristic current signals by using a 14-bit high-speed AD sampling chip, and the FPGA XC7Z020 is used as a data processing unit and a carrier channel is used as an uplink channel to collect and report transmitted current signals.
CN202210536353.8A 2022-05-13 2022-05-13 Characteristic current identification and verification method and device based on Fourier transform algorithm Pending CN114912490A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210536353.8A CN114912490A (en) 2022-05-13 2022-05-13 Characteristic current identification and verification method and device based on Fourier transform algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210536353.8A CN114912490A (en) 2022-05-13 2022-05-13 Characteristic current identification and verification method and device based on Fourier transform algorithm

Publications (1)

Publication Number Publication Date
CN114912490A true CN114912490A (en) 2022-08-16

Family

ID=82768980

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210536353.8A Pending CN114912490A (en) 2022-05-13 2022-05-13 Characteristic current identification and verification method and device based on Fourier transform algorithm

Country Status (1)

Country Link
CN (1) CN114912490A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115343564A (en) * 2022-10-18 2022-11-15 青岛鼎信通讯股份有限公司 Signal detection method applied to electric power field
CN115951114A (en) * 2023-01-17 2023-04-11 上海山源电子科技股份有限公司 Current signal identification method in power supply monitoring system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115343564A (en) * 2022-10-18 2022-11-15 青岛鼎信通讯股份有限公司 Signal detection method applied to electric power field
CN115951114A (en) * 2023-01-17 2023-04-11 上海山源电子科技股份有限公司 Current signal identification method in power supply monitoring system
CN115951114B (en) * 2023-01-17 2023-06-23 上海山源电子科技股份有限公司 Current signal identification method in power supply monitoring system

Similar Documents

Publication Publication Date Title
CN114912490A (en) Characteristic current identification and verification method and device based on Fourier transform algorithm
CN110658397B (en) Method and system for identifying user variable relationship based on resistance switching and frequency domain analysis
CN102841296B (en) Online monitoring system and method for partial discharge of intelligent switch cabinet based on ultra-high frequency detection
CN103916207A (en) Active device and method for interfering multi-frequency-band power line communication
CN114002501A (en) Acquisition terminal topology identification method with digital filtering
CN109752607A (en) A kind of method and system of traction converter failure diagnosis
CN104635109A (en) High-accuracy method for directly calculating and extracting amplitude value and time constant of transient aperiodic component of power grid from fault recording data
CN111103498B (en) Low-voltage transformer area line-change user relationship identification system and method
CN202794359U (en) Zinc oxide lightning arrester on-line monitoring device
CN113660009B (en) Testing system and testing method for power distribution and utilization communication
CN211860117U (en) Communication test experiment platform for electric energy metering equipment
CN116127163B (en) Anti-interference power transformer short circuit impact analysis system and method
CN103532233B (en) Based on the power information acquisition abnormity Precise Position System of GPRS technology
CN103901261A (en) System and method for conducting wireless measurement on overvoltage of electrical power system
CN113992238A (en) Quantitative test analysis method, device and system for carrier communication performance
CN116961821B (en) Method, system, equipment and readable storage medium for shielding mobile communication signal
CN117061039B (en) Broadcast signal monitoring device, method, system, equipment and medium
CN109375139A (en) A kind of device and method of automatic testing light fiber current mutual inductor
CN113709784B (en) Self-adaptive analysis test system and test method for wireless 6G
CN113783633B (en) Simulation device and method for multiband noise
KR102676754B1 (en) Real-time data transmission system using iot measuring devices for power measuremnet and data transmission using the same
Mujcic et al. Power line noise model appropriate for investigation if channel coding methods
CN210015512U (en) Line loss statistical analysis device and system
CN113315658B (en) Topology identification optimization method and system for low-voltage distribution network
Wang et al. Analysis on Anti-Jamming Performance Test Method of Communication System in New Energy Power Plant

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination