CN113205672A - Pilot protection measurement data recovery method and pilot communication system - Google Patents
Pilot protection measurement data recovery method and pilot communication system Download PDFInfo
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- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
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Abstract
The invention discloses a pilot protection measurement data recovery method and a pilot communication system, belonging to the field of power communication, wherein the method comprises the following steps: s1: receiving a plurality of messages sent by a protection device; checking the error of each message and sequentially putting the original measurement signals x in the correct message into a buffer queue y according to the message number; s2: setting buffer array phi corresponding to each correct messageiAll buffer arrays are formed byiArranging the observation matrixes phi according to rows to form an observation matrix phi; s3: setting a sparse basis matrix psi, and constructing an underdetermined equation set of an observation matrix phi, an observation value, the sparse basis matrix psi and a sparse coefficient s based on a compressed sensing principle; s4: and solving the underdetermined equation set by using a reconstruction algorithm to obtain a sparse coefficient s, and performing inverse transformation on s by combining the sparse basis matrix psi to obtain an original measurement signal x. The invention is based on compressed sensingThe algorithm corrects the error and missing data in the transmission process, and solves the technical problem of poor transmission reliability in the communication process.
Description
Technical Field
The invention belongs to the field of power communication, and particularly relates to a pilot protection measurement data recovery method and a pilot communication system.
Background
With the development of wireless communication technology, the application of low-delay and high-reliability 5G communication technology in the power industry is scheduled, and the communication reliability and real-time performance of each device in a power system are greatly improved. Especially in a power distribution network, the circuit topology is complex, the optical fiber construction difficulty is high, the optical fiber communication circuit is not suitable for laying, the construction period of the optical fiber network is long, the construction cost is high, the construction of the power distribution network communication circuit is restricted, and the existing power distribution network has low automation degree and low power supply reliability. Therefore, wireless communication has a high application potential in power systems.
Wireless communication channels in the power system are usually in dense power transmission and distribution lines and in a strong electromagnetic interference environment, so that the situations of packet loss, packet error and the like are difficult to avoid in the transmission process, the reliability of communication is affected, and the normal operation of equipment such as protection control and the like is affected.
At present, researches on the aspect of electric power data transmission reliability mainly improve the performance of electric power data transmission in a strong electromagnetic interference environment from the aspects of interference sources, transmission path protection and transmission algorithm performance enhancement, but the problems of packet loss, packet error and the like cannot be fundamentally solved.
Disclosure of Invention
In view of the above defects or improvement requirements of the prior art, the present invention provides a pilot protection measured data recovery method and a pilot communication system, and aims to correct erroneous and missing data in a transmission process based on a compressive sensing algorithm, and solve the technical problem of poor transmission reliability in a communication process.
To achieve the above object, according to an aspect of the present invention, there is provided a method for recovering pilot protection measured data, including:
s1: receiving a plurality of messages sent by a protection device, wherein each message carries a message number and an original measurement signal x; checking the error of each message and sequentially putting the original measurement signals x in the correct message into a buffer queue y according to the message number;
s2: setting a buffer array phi corresponding to each correct messageiAnd i represents the serial number of the correct message; the buffer array phiiSetting the state values of the positions corresponding to the Chinese message codes as 1 and setting the state values of the other positions as 0; all the buffer arrays phiiArranging the observation matrixes phi according to rows to form an observation matrix phi;
s3: setting a sparse basis matrix psi, and constructing an underdetermined equation set of the observation matrix phi, an observation value, the sparse basis matrix psi and a sparse coefficient s based on a compressed sensing principle, wherein the buffer queue y is the observation value;
s4: and solving the underdetermined equation set by using a reconstruction algorithm to obtain the sparse coefficient s, and performing inverse transformation on s by combining the sparse basis matrix psi to obtain the original measurement signal x.
In one embodiment, before S1, the method for recovering the pilot protection measurement data further includes: the protection device continuously collects the original measurement signal x according to a time interval T and sends the original measurement signal x collected each time to a receiving device in the form of a message; so that the receiving device performs the S1 to S4 to recover the original measurement signal x.
In one embodiment, the S1 includes:
s11: receiving a plurality of messages sent by the protection device;
s11: checking each message, discarding error messages and sequentially placing original measurement signals x in the correct message into the buffer queue y according to the message number;
the buffer queue y is a variable-length time sequence, and the length of the variable-length time sequence is determined according to the number of the received correct messages.
In one embodiment, the S2 includes:
s21: determining a one-dimensional array phi with the length of N according to the message number of the received correct messageiIf the message number of the correct message is j, the buffer array phiiThe j-th position 1, the remaining positions 0;
s22: all buffer arrays are numbered phiiArranging and forming an m multiplied by N observation matrix phi according to rows, wherein each row represents a state row vector of a received correct message, and each column represents a number of the message in the transmission process; i is 1,2, and m is the total number of messages transmitted correctly.
In one embodiment, the S3 includes:
constructing an underdetermined equation set y of the observation matrix phi, the observation value y, the sparse basis matrix psi and the sparse coefficient s as phi psi s based on a compressed sensing principle: y is a one-dimensional measurement of length m;
the observation matrix phi is regarded as a sub-sampling process of the original measurement signal x due to the phenomenon that the original measurement signal x is occasionally lost and mistakenly frame in the transmission process;
wherein the expression of the sparse basis matrix ψ is:
in one embodiment, the S4 includes:
and solving the underdetermined equation set y phi psi s by adopting a reconstruction algorithm to obtain the sparse coefficient s, and performing inverse transformation on s by using x phi psi s to obtain the original measurement signal x.
In one embodiment, the reconstruction algorithm is:
taking the observation matrix phi, the observation value y and the sparsity K as input parameters; taking an approximate value theta of the sparse coefficient s as an output parameter;
setting an initial error ε0Y; dividing the observation matrix phi into phi and { phi in columns1,φ2,...,φNAnd calculate εtPhi and phiiTo correspond to the maximum inner product of phijPut into a set A, wherein t is the iteration number, At＝At-1∪φjA is initially an empty set;
using formulas
Finding y as AtθtLeast squares solution of thetat(ii) a Updating the residual εt＝y-AtUntil t is more than or equal to K or epsilontResidual error is 0, and theta is obtainedtAs the sparse coefficient s.
According to another aspect of the present invention, there is provided a pilot communication system including:
the protection device is used for continuously acquiring the original measurement signal x according to a time interval T and sending the original measurement signal x acquired each time to the receiving device in the form of the message;
and the receiving device is in communication connection with the protection device and is used for executing the steps of the method.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
the invention sets the buffer array phi corresponding to each correct messageiSetting a sparse basis matrix psi; constructing an underdetermined equation set of the observation matrix phi, the observation value, the sparse basis matrix psi and the sparse coefficient s based on a compressed sensing principle; and solving the underdetermined equation set by using a reconstruction algorithm to obtain a sparse coefficient s, and performing inverse transformation on s by combining the sparse basis matrix psi to obtain the original measurement signal x. That is, the invention corrects the error and missing data in the transmission process based on the compressed sensing algorithm, and can effectively solve the problemThe original data is recovered through correct transmission data, and the reliability of the transmission of the pilot protection measurement data is improved.
Drawings
FIG. 1 is a flowchart illustrating a method for recovering pilot protection measurement data according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for recovering pilot protection metrology data according to another embodiment of the present invention;
FIG. 3 is a graph of a sampled current waveform and its frequency spectrum according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating compressed sensing-based power data recovery calculations according to an embodiment of the present invention;
fig. 5 is a flow chart of signal reconstruction based on an orthogonal matching pursuit algorithm according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the present invention provides a method for recovering pilot protection measurement data, including:
s1: receiving a plurality of messages sent by a protection device, wherein each message carries a message number and an original measurement signal x; checking the error of each message and sequentially putting the original measurement signals x in the correct message into a buffer queue y according to the message number;
s2: setting buffer array phi corresponding to each correct messageiI represents the serial number of the correct message; will buffer the array phiiSetting the state values of the positions corresponding to the Chinese message codes as 1 and setting the state values of the other positions as 0; all buffer arrays are numbered phiiArranging the observation matrixes phi according to rows to form an observation matrix phi;
s3: setting a sparse basis matrix psi, and constructing an underdetermined equation set of an observation matrix phi, an observation value, the sparse basis matrix psi and a sparse coefficient s based on a compressed sensing principle, wherein a buffer queue y is the observation value;
s4: and solving the underdetermined equation set by using a reconstruction algorithm to obtain a sparse coefficient s, and performing inverse transformation on s by combining the sparse basis matrix psi to obtain an original measurement signal x.
In one embodiment, as shown in fig. 2, before S1, the method for recovering the pilot protection measured data further includes:
the protection device continuously collects original measurement signals x according to a time interval T and sends the collected original measurement signals x to the receiving device in a message form; so that the receiving apparatus performs S1 to S4 to recover the original measurement signal x.
Specifically, the present invention provides a recovery scheme for error and leakage of pilot protection measured data, which takes the current waveform shown in fig. 3 as an example, and the protection device samples the current waveform at N60 points per cycle, where the current waveform includes frequency components of 50Hz and 100 Hz. After the current is sampled by the protection device, sampling data of the current moment is generated to a device on one side, each sampling point is packaged into a message, and 60 messages are sent in total. During the transmission process, only messages No. 10-12, 20-22 and 30-32 are transmitted in error or lost, and other messages are transmitted correctly.
S1: the receiving device puts the sampling value data contained in the correctly transmitted message into a buffer queue y according to the sequence of message numbers (i.e. the sampling sequence), and the length of y is 51 at this time.
S2: the receiving side device receives the sampling value of No. 1 message transmission, after checking that the transmission is correct, a one-dimensional array with the length of 60 is opened up, the 1 st element of the array is set to be 1, and the other elements of the array are set to be 0, so as to obtain a queue phi1. The receiving side device can obtain the queue phi when receiving other messages2-φ51. After the queues are arranged according to rows, a 51-order observation matrix phi can be formed, each row represents a state row vector of a received correct message, and each column represents the number of the message in the transmission process.
S3: as can be known from the compressive sensing principle, y is phi psi s, and x is psi s, where y is a one-dimensional measurement value with a length of 51, and represents a sample value sequence after the missing data is removed, the observation matrix phi represents a sub-sampling process for the signal x, and x is a 60-point sample value in a current cycle in the transmission process.
The compressed sensing principle requires that signals are sparse, as shown in fig. 4, after a proper threshold is selected, only 50Hz and 100Hz have non-zero values, and the requirement of the compressed sensing principle on the sparsity of the signals is met. The discrete fourier transform matrix ψ is as follows:
S4: in this embodiment, an orthogonal matching pursuit algorithm is used as a signal reconstruction algorithm, and the steps are as follows:
inputting: measuring a matrix phi, measuring a vector y, wherein a value K of sparsity is 3;
and (3) outputting: an approximation value θ of s;
(1) initializing an error epsilon as y, and setting a time t as 1;
(2) the measurement matrix is divided by columns, phi ═ phi1,φ2,...,φ60}, calculating εtPhi and phiiFinding the index j with the maximum inner product, and dividing phijThrow into set A, where At＝At-1∪φjA is initially an empty set;
(3) finding y as AtθtThe least-squares solution of (a) is,
(4) updating the residual εt＝y-At；
(5) t is t +1, if t is more than or equal to K or the residual error is 0, stopping, and theta of the last iteration istIs an approximation value. If not, the step returns to the step (2).
The s-approximation value θ is obtained through the above steps, and the flowchart is shown in fig. 5. And recovering the original measurement signal x according to the inverse discrete Fourier transform.
In one embodiment, S1 includes:
s11: receiving a plurality of messages sent by a protection device;
s11: checking each message, discarding error messages and sequentially putting original measurement signals x in correct messages into a buffer queue y according to message numbers;
the buffer queue y is a variable length time sequence, and the length of the variable length time sequence is determined according to the number of received correct messages.
In one embodiment, S2 includes:
s21: determining a one-dimensional array phi with the length of N according to the message number of the received correct messageiIf the message number of the correct message is j, then buffer array phiiThe j-th position 1, the remaining positions 0;
s22: all buffer arrays are numbered phiiArranging and forming an m multiplied by N observation matrix phi according to rows, wherein each row represents a state row vector of a received correct message, and each column represents a number of the message in the transmission process; i is 1,2, and m is the total number of messages transmitted correctly.
In one embodiment, S3 includes:
an underdetermined equation set y of an observation matrix phi, an observation value y, a sparse basis matrix psi and a sparse coefficient s is constructed based on a compressed sensing principle, wherein the underdetermined equation set y is phi psi s: y is a one-dimensional measurement of length m;
the observation matrix phi is regarded as a sub-sampling process of the original measurement signal x due to the phenomenon that the original measurement signal x is occasionally lost and mistakenly frame in the transmission process;
wherein, the expression of the sparse basis matrix psi is:
in one embodiment, S4 includes:
and solving the underdetermined equation set y phi psi s by adopting a reconstruction algorithm to obtain a sparse coefficient s, and performing inverse transformation on s by using x phi psi s to obtain an original measurement signal x.
In one embodiment, the reconstruction algorithm is:
taking an observation matrix phi, an observation value y and sparsity K as input parameters; taking an approximate value theta of the sparse coefficient s as an output parameter;
setting an initial error ε0Y; dividing the observation matrix phi into columns phi ═ phi [ [ phi ] ]1,φ2,...,φNAnd calculate εtPhi and phiiTo correspond to the maximum inner product of phijPut into a set A, wherein t is the iteration number, At＝At-1∪φjA is initially an empty set;
using formulas
Finding y as AtθtLeast squares solution of thetat(ii) a Updating the residual εt＝y-AtUntil t is more than or equal to K or epsilontResidual error is 0, and theta is obtainedtAs the sparse coefficient s.
The present invention also provides a pilot communication system, comprising: a protection device and a receiving device; the protection device is used for continuously acquiring original measurement signals x according to a time interval T and sending the acquired original measurement signals x to the receiving device in a message form; and the receiving device is in communication connection with the protection device and is used for executing the steps of the method.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A method for recovering pilot protection measurement data is characterized by comprising the following steps:
s1: receiving a plurality of messages sent by a protection device, wherein each message carries a message number and an original measurement signal x; checking the error of each message and sequentially putting the original measurement signals x in the correct message into a buffer queue y according to the message number;
s2: setting a buffer array phi corresponding to each correct messageiAnd i represents the serial number of the correct message; the buffer array phiiSetting the state values of the positions corresponding to the Chinese message codes as 1 and setting the state values of the other positions as 0; all the buffer arrays phiiArranging the observation matrixes phi according to rows to form an observation matrix phi;
s3: setting a sparse basis matrix psi, and constructing an underdetermined equation set of the observation matrix phi, an observation value, the sparse basis matrix psi and a sparse coefficient s based on a compressed sensing principle, wherein the buffer queue y is the observation value;
s4: and solving the underdetermined equation set by using a reconstruction algorithm to obtain the sparse coefficient s, and performing inverse transformation on s by combining the sparse basis matrix psi to obtain the original measurement signal x.
2. The method for recovering pilot protection metrology data as claimed in claim 1, wherein before S1, the method further comprises:
the protection device continuously collects the original measurement signal x according to a time interval T and sends the original measurement signal x collected each time to a receiving device in the form of a message; so that the receiving device performs the S1 to S4 to recover the original measurement signal x.
3. The method for recovering pilot protection metrology data as claimed in claim 1, wherein said S1 comprises:
s11: receiving a plurality of messages sent by the protection device;
s11: checking each message, discarding error messages and sequentially placing original measurement signals x in the correct message into the buffer queue y according to the message number;
the buffer queue y is a variable-length time sequence, and the length of the variable-length time sequence is determined according to the number of the received correct messages.
4. The method for recovering pilot protection metrology data as claimed in claim 1, wherein said S2 comprises:
s21: determining a one-dimensional array phi with the length of N according to the message number of the received correct messageiIf the message number of the correct message is j, the buffer array phiiThe j-th position 1, the remaining positions 0;
s22: all buffer arrays are numbered phiiArranging and forming an m multiplied by N observation matrix phi according to rows, wherein each row represents a state row vector of a received correct message, and each column represents a number of the message in the transmission process; i is 1,2, and m is the total number of messages transmitted correctly.
5. The method for recovering pilot protection metrology data as claimed in claim 1, wherein said S3 comprises:
constructing an underdetermined equation set y of the observation matrix phi, the observation value y, the sparse basis matrix psi and the sparse coefficient s as phi psi s based on a compressed sensing principle: y is a one-dimensional measurement of length m;
the observation matrix phi is regarded as a sub-sampling process of the original measurement signal x due to the phenomenon that the original measurement signal x is occasionally lost and mistakenly frame in the transmission process;
wherein the expression of the sparse basis matrix ψ is:
6. the method for recovering pilot protection measurement data according to claim 5, wherein the step S4 includes:
and solving the underdetermined equation set y phi psi s by adopting a reconstruction algorithm to obtain the sparse coefficient s, and performing inverse transformation on s by using x phi psi s to obtain the original measurement signal x.
7. The method for recovering pilot protection measurement data according to claim 6, wherein the reconstruction algorithm is:
taking the observation matrix phi, the observation value y and the sparsity K as input parameters; taking an approximate value theta of the sparse coefficient s as an output parameter;
setting an initial error ε0Y; dividing the observation matrix phi into phi and { phi in columns1,φ2,...,φNAnd calculate εtPhi and phiiTo correspond to the maximum inner product of phijPut into a set A, wherein t is the iteration number, At＝At-1∪φjA is initially an empty set;
using formulas
Finding y as AtθtLeast squares solution of thetat(ii) a Updating the residual εt＝y-AtUntil t is more than or equal to K or epsilontResidual error is 0, and theta is obtainedtAs the sparse coefficient s.
8. A pilot communication system, comprising:
the protection device is used for continuously acquiring the original measurement signal x according to a time interval T and sending the original measurement signal x acquired each time to the receiving device in the form of the message;
receiving means, communicatively connected to the protection means, for performing the steps of the method of any one of claims 1 to 7.
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