CN115980513A - Power distribution network single-phase earth fault distinguishing method and device based on particle swarm optimization - Google Patents
Power distribution network single-phase earth fault distinguishing method and device based on particle swarm optimization Download PDFInfo
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Abstract
A power distribution network single-phase earth fault distinguishing method and device based on particle swarm optimization are characterized in that a functional relation between zero sequence and negative sequence steady-state current on a fault path of a power distribution network system and a fault distance is established by analyzing distribution characteristics of negative sequence and zero sequence current in the power distribution network system and combining line parameters; and taking the functional relation as a target function, and iteratively obtaining the accurate fault distance according to a particle swarm algorithm. According to the invention, fault discrimination and distance measurement are completed by using the negative sequence and zero sequence steady-state current, so that the influence of noise and the like on transient signals is avoided, auxiliary judgment of voltage signals is not needed, and the algorithm reliability and the engineering practicability are improved; the distance measurement technology fully utilizes the global search capability of the particle swarm algorithm, the algorithm is simple and easy to implement, the convergence speed is high, and the running speed and the accuracy of the method are guaranteed.
Description
Field of the patent
The invention belongs to the technical field of electric power automation, relates to the field of single-phase ground faults in a power distribution network, and particularly relates to a method and a device for judging single-phase ground faults of the power distribution network based on a particle swarm algorithm.
Background
With the continuous development of economic society, the connection between people's production and life and electric energy is increasingly close. As the last kilometer of a power transmission system, after a fault occurs in a power distribution network, the living standard and the production quality of products of people are seriously influenced. And the single-phase earth fault has small current and unclear characteristics, and is difficult to complete fault positioning as soon as possible. In order to ensure the power supply reliability of the power distribution network, a technology for accurately positioning the single-phase earth fault of the power distribution network needs to be provided urgently.
In recent years, a large number of research experiments are carried out on single-phase earth fault positioning of a power distribution network by domestic and foreign experts, and abundant results are obtained. The positioning accuracy degree can be divided into fault line selection, section positioning and fault distance measurement according to the technology. The fault line selection technology is a technology for judging the outgoing line of the single-phase earth fault by analyzing the current or voltage characteristics of each outgoing line of a station. The common fault line selection technology comprises the following steps: a test-pull method, a zero sequence current amplitude comparison method, a first half-wave method, a power method and the like. However, the fault line selection technology can only complete the positioning of the outgoing line where the fault is located, and the outgoing line is directly broken, so that the electricity utilization of the user connected to the outgoing line is influenced; in order to further confirm the fault location simultaneously, the staff often need carry out complicated inspection task, will greatly increase personnel's work load. In order to further refine the location of the fault, experts have proposed fault zone location techniques. According to the technology, the distribution network system is divided into all sections by using devices such as FTUs and switches, fault location is completed according to current or voltage characteristics among the sections in a distinguishing mode, and fault isolation can be achieved only by disconnecting the section where the fault is located. The common section positioning technology can be divided into an active positioning technology and a passive positioning technology, the section positioning technology avoids the power supply influence on most users, the workload of line patrol personnel is reduced to a certain extent, and the fault removal and power supply recovery as soon as possible cannot be guaranteed. In order to further determine the position of the fault, realize fault isolation and removal as soon as possible and recover the line power supply, experts provide a fault location technology. The fault distance measuring technology can judge the fault distance, can quickly position and eliminate the fault, and greatly reduces the power failure time. Common fault location techniques can be divided into traveling wave methods and impedance methods. The traveling wave method is to judge the fault distance by the circulation path of the wave head of the reflected wave in the monitoring system and the time of reaching each monitoring point. However, the transient wave head is seriously interfered by harmonic waves, noise and the like, so that the reliability cannot be ensured; in order to accurately capture the wave head, the signal monitoring device needs to have a high-frequency sampling project, the requirement on the device is high, the engineering economy is poor, and an impedance method is often adopted on site. The impedance method is to obtain the line impedance of the fault point from the signal monitoring point by analyzing the current and voltage relationship in the system, and judge the fault distance by using the direct ratio relationship between the line impedance and the fault point distance. However, because a large number of inductance and capacitance elements exist in the power distribution network, the current and the voltage are in a nonlinear relation, and the traditional method cannot obtain an accurate fault distance.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a power distribution network single-phase earth fault distinguishing method and device based on a particle swarm algorithm. The technology establishes the functional relation between the zero sequence, negative sequence steady-state current and fault distance on the fault path of the power distribution network system by analyzing the distribution characteristics of the negative sequence and zero sequence current in the power distribution network system and combining line parameters; the distance measurement technology takes the functional relation as a target function and iteratively obtains the accurate fault distance according to a particle swarm algorithm.
The positioning technology acquires phase current signals and synthesizes zero-sequence current to monitor fault occurrence; when the amplitude of the zero sequence current is larger than the threshold value, the single-phase earth fault is judged to occur, the distance measurement algorithm is started, the outgoing line where the fault is located is judged, relevant parameter information is obtained, a target function is established according to the distribution characteristics of the negative sequence current and the zero sequence current of the system in the system, and particle swarm algorithm operation is started. The algorithm firstly sets parameters such as particle size, iteration times and the like, randomly generates particle positions and speeds, calculates the adaptive value of each particle according to an objective function, and sets an initial individual extreme value and an initial global optimum value. After one iteration, the algorithm judges whether the iteration result meets the convergence condition or reaches the maximum iteration times, if so, the iteration is ended, the optimal solution of the iteration is output, otherwise, the position and the speed of the particle are updated, and the next iteration is carried out.
Specifically, the invention provides a power distribution network single-phase earth fault discrimination method based on a particle swarm algorithm, which comprises the following steps:
step 1: acquiring phase current signals, synthesizing zero-sequence current, and monitoring fault occurrence;
and 2, step: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault exists, acquiring related parameter information, and returning to the step 1 to continuously monitor the zero sequence current amplitude change if the amplitude is not larger than the threshold value;
and step 3: establishing a target function according to the distribution characteristics of the negative sequence current and the zero sequence current of the system, and constructing a particle swarm algorithm model; randomly generating the position and the speed of the particles according to preset parameters;
and 4, step 4: performing particle swarm algorithm iteration according to a set target function and power distribution network system parameters, and seeking a global optimum value;
and 5: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration, outputting an optimal iteration solution, and acquiring an accurate fault distance, otherwise, updating the position and the speed of the particle, and returning to the step 4 for the next iteration.
Further, the particle swarm algorithm objective function is:
wherein the content of the first and second substances,
in order to calculate the theoretical value of the negative sequence current at the upstream of the fault line according to the zero sequence current at the fault point,
the negative sequence current measurement value of the first section of the fault line is obtained; lambda is a weight coefficient set according to a 'minimum set' in the fault diagnosis theory, and the value range is (0, 1); s (j) represents the equipment fault state, the value of 1 represents the equipment fault, the value of 0 represents the equipment normal, n represents the total quantity of the equipment, and j represents the equipment serial number; f (l) represents a particle swarm algorithm target function, the adaptive value of the target function takes a minimum value, and the particle swarm algorithm is used for solving the fault distance in the target function.
Further, in the step S3,
when the system comprises two outgoing lines, a single-phase earth fault occurs in the second outgoing line, and the single-phase earth fault occurs, the zero sequence current obtained by the head end of the fault line
And zero sequence current at fault point>
The relationship is as follows:
wherein L is an arc suppression coil inductance; c Σ Is system equivalent capacitance to ground, C' 2 The capacitance to ground of the upstream and downstream lines of the fault point of the fault line; l is the inductance of the system arc suppression coil;
negative sequence current drawn upstream of a faulted line
And the negative sequence current at the fault point->
The relationship is as follows:/>
wherein Z 1 A negative sequence impedance for the first outgoing line, including line and load impedances; z' 2 Negative sequence impedance at the downstream of the fault point of the fault line, which comprises line and load negative sequence impedance connected with the line; z T Equivalent negative sequence impedance of the transformer line and the high-voltage side; z 20 Positive and negative sequence impedance for a unit length of the line.
Further, wherein the line negative sequence impedance Z upstream of the fault point of the faulty line 2 ＝Z 20 l；
When the neutral point of the power distribution network is grounded through the arc suppression coil:
when the neutral point of the power distribution network is not grounded:
further, in the step S3,
in a non-grounded system with a neutral point, an arc suppression coil loop in a zero sequence network diagram is opened, and zero sequence current obtained at the head end of a line
And zero sequence current at fault point->
The relationship is
Further, in step S3, the particle velocity and position iterative formula of the particle algorithm is as follows:
x i ＝x i +v i
in the formula: n, N being the total number of particles in the population; v. of i Is the particle velocity; x is a radical of a fluorine atom i Is the particle position; rand () is a random number, the random number range being (0, 1); c. C 0 The inertial weight factor can realize the adjustment of the global and local optimization capability of the algorithm by changing the numerical value of the inertial weight factor; c. C 1 And c 2 Respectively an individual and a global learning factor,
the individual extreme values of the particles are represented,
representing a global optimum.
Further, in the step S4, the adaptive value of each particle is calculated according to the objective function set in the algorithm and the parameters of the power distribution network system, the initial individual extreme value is updated according to the adaptive value during the first iteration, and the minimum value of all the individual extreme values is used as the initial global optimum value; in the iterative process, when the adaptive value is smaller than the individual extreme value or the global optimal value, the corresponding value is updated.
Further, the invention also provides a device for judging the single-phase earth fault of the power distribution network based on the particle swarm optimization, and the device comprises:
a fault monitoring module: acquiring phase current signals, synthesizing zero-sequence current, and monitoring fault occurrence;
a fault determination module: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault is positioned, acquiring related parameter information, and if the amplitude is not larger than the threshold value, continuously monitoring the amplitude change of the zero sequence current;
a model construction module: establishing a target function according to the distribution characteristics of the negative sequence current and the zero sequence current of the system, and constructing a particle swarm algorithm model; randomly generating the position and the speed of the particles according to preset parameters;
a solving module: performing particle swarm algorithm iteration according to a set target function and power distribution network system parameters, and seeking a global optimum value;
an output module: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration, outputting an optimal iteration solution, and obtaining an accurate fault distance, otherwise, updating the position and the speed of the particle, and returning to perform the next iteration.
Further, the present invention also proposes a computer readable storage medium storing one or more programs, characterized in that the one or more programs comprise instructions, which when executed by a computing device, cause the computing device to execute the method according to the present invention.
Further, the present invention also proposes a computing device comprising: one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods according to the invention.
The beneficial technical effects of the invention are as follows:
(1) According to the invention, through comprehensive analysis of the distribution characteristics of the negative sequence current and the zero sequence current, fault judgment and accurate distance measurement can be realized after a single-phase earth fault occurs in the power distribution network, and the operation reliability of the power distribution network is ensured;
(2) According to the invention, fault discrimination and distance measurement are completed by using the negative sequence and zero sequence steady-state currents, so that the influence of noise on transient signals is avoided, auxiliary judgment of voltage signals is not needed, and the practicability of algorithm engineering is improved;
(3) The invention fully utilizes the global search capability of the particle swarm algorithm, the algorithm is simple and easy to implement, the convergence speed is high, and the operation speed and the accuracy of the technology are ensured.
Drawings
Fig. 1 is a diagram showing a system configuration in which a neutral point is grounded via an arc suppression coil.
Fig. 2 is a schematic diagram of a zero sequence network.
FIG. 3 is a schematic negative sequence net.
Fig. 4 is a flowchart of a fault determination method according to the present invention.
FIG. 5 is a diagram of a simulation experiment system.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
The invention provides a power distribution network single-phase earth fault distinguishing method based on a particle swarm algorithm, which is used as an evolutionary computing technology. Compared with a simulated annealing algorithm and a genetic algorithm, the particle swarm algorithm is simple in rule and easy to operate, iteration is performed by adopting a mode of pursuing the current optimal solution from a random solution, and the method has the characteristics of simplicity in realization, quickness in convergence and high precision.
In the PSO algorithm, the random solution of each problem is a particle in space, the particle has both velocity and position properties, and the fitness value (fitness value) of the particle at the current position and the individual extreme value P of the particle up to this point can be determined according to the objective function best And a global optimum G known for each particle best And G is best The moving direction of each particle can be determined as the reference experience of the whole particles, namely, iteration is carried out. The particle velocity and position iterative formula is as follows:
x i ＝x i +v i
in the formula: n, N being the total number of particles in the population;v i is the particle velocity; x is a radical of a fluorine atom i Is the particle position; rand () is a random number, the range of which is (0, 1); c. C 0 The inertial weight factor can realize the adjustment of the global and local optimization capability of the algorithm by changing the numerical value of the inertial weight factor; c. C 1 And c 2 Individual and global learning factors, respectively.
In the particle velocity expression, a first term is a memory term and represents the velocity and the position of the particle after the last iteration; the second item is an individual cognitive item and is an optimal action judged according to the extreme value of the second item; the third item is a global recognition item, and the optimal action is judged for the particle according to the global optimal value. The particles are iterated in space for the individual extrema and the global optimum until they meet a specified error or until the number of iterations is reached.
In order to better obtain the numerical iteration and convergence effect, the invention sets the parameters as follows: c. C 0 ＝0.729，c 1 ＝c 2 =1.4962, particle maximum velocity is 1.
In order to reasonably construct an objective function of the particle swarm optimization, a system with a neutral point grounded through an arc suppression coil is adopted for analysis, and the structure diagram of the system is shown in the attached drawing 1.
The system comprises two outgoing lines, and the single-phase earth fault occurs in the second outgoing line. L is an arc suppression coil inductor; r is the resistance value of the grounding resistor; l is the distance from the ground fault point to the bus.
After a single-phase earth fault occurs, the fault current can be divided into positive, negative and zero sequence currents according to a symmetrical component method, and the three sequence currents are the same at the fault point according to boundary conditions:
the distribution characteristics of the negative sequence current and the zero sequence current in the system are different. The zero sequence current flows to a fault point through the pair capacitor in the normal line, and flows to the fault point upstream line and the fault point downstream line respectively after being shunted at the fault point, and the current flowing to the fault point upstream line flows back to the respective lines through the bus to form a loop. Taking fig. 1 as an example, the zero sequence current sequence diagram is shown in fig. 2.
Wherein the content of the first and second substances,
is zero sequence equivalent voltage; c 1 Is the line 1 capacitance to ground; c 2 And C' 2 The line-to-ground capacitance of the upstream and downstream line 2 fault points; l is the inductance of the system arc suppression coil; and R is the grounding resistance at the fault point.
Therefore, the zero sequence current obtained from the head end of the fault line 2 can be obtained
And zero sequence current at fault point->
The relationship is as follows:
wherein, C Σ Is the equivalent capacitance to ground of the system.
In the non-grounded neutral point system, the arc suppression coil loop in the zero sequence network diagram is open, so that the relationship between the zero sequence current at the fault point and the zero sequence current obtained from the head end of the line 2 is as follows:
the negative sequence current flows to the upstream line and the downstream line of the fault point after being shunted by the fault point, the negative sequence current flowing through the upstream line of the fault point flows to the normal line and the transformer line through the bus, and the negative sequence network diagram of the neutral point ungrounded system is the same as that of the system grounded through the arc suppression coil because the circuit of the arc suppression coil does not influence the distribution of the negative sequence current. The negative sequence equivalent diagram is shown in the attached figure 3:
in the figure, the position of the upper end of the main shaft,
is a negative sequence equivalent voltage; z is a linear or branched member 1 Is the negative sequence impedance of the line 1, including the line and load impedance; z 2 Negative sequence impedance of the line upstream of the fault point of the fault line 2; z' 2 The negative sequence impedance at the downstream of the fault point of the fault line 2 comprises line and connected load negative sequence impedance; z T The equivalent negative sequence impedance of the transformer line and the high-voltage side.
The negative-sequence current drawn upstream of the fault line 2 from fig. 3 can be derived
And the negative sequence current at the fault point->
The relationship is as follows:
and wherein the negative sequence impedance Z of the line upstream of the point of failure of the faulty line 2 2 ＝Z 20 l，Z 20 The positive and negative sequence impedances of the line in unit length can be obtained by combining the fault point and the zero sequence current relation and the boundary condition at the head end of the line 2:
when the neutral point of the power distribution network is grounded through the arc suppression coil:
when the neutral point of the power distribution network is not grounded:
according to the negative sequence current measured value and the theoretical calculated value obtained from the head end of the fault line 2 and the running state of the equipment in the system, a particle swarm algorithm objective function is obtained as follows:
wherein the content of the first and second substances,
is the line 2 head end negative sequence current measurement; λ is a weight coefficient set according to a "minimum set" in the fault diagnosis theory, the value range is (0, 1), and the value range is set to 0.45; and S (j) represents the equipment fault state, the value of 1 represents the equipment fault, and the value of 0 represents the equipment normal. For the objective function, the smaller the value of the objective function is, the more accurate the fault distance is, so the adaptive value of the objective function should be a minimum value. In the above formula, F (l) represents a particle swarm algorithm target function, and for the target function, the smaller the value of the target function is, the more accurate the fault distance is, so that the target function adaptive value should be a minimum value. n denotes the total number of devices, and j denotes the serial number of the device. The method is characterized in that the method comprises the following steps that a fault line initial end negative sequence current formula is obtained, the magnitude of the negative sequence current is related to a fault distance, a particle swarm algorithm is used for solving the fault distance l in a target function, and the speed and the position of the fault distance l are random generation numbers of the particle swarm algorithm.
And finally, obtaining a final result which is the distance length l between the fault point and the bus through iteration of the particle swarm optimization.
In order to verify the reliability of the algorithm, an ATP simulation model is built according to the structure diagram of the power distribution network shown in the attached figure 1 and is shown in the attached figure 5. The figure comprises two outgoing lines, and the single-phase grounding fault occurs in the middle section of the second outgoing line.
The power distribution network single-phase earth fault distinguishing technology based on the particle swarm optimization can be adopted for a single-phase earth fault of a neutral point grounded system or a neutral point ungrounded system, after a positioning device is installed at each wire outlet end of the power distribution network system, the particle swarm optimization iteration is carried out by obtaining negative sequence, zero sequence current and line parameters on a line, and finally fault distance measurement can be completed. The specific implementation steps are shown in figure 4.
Step 1: acquiring phase current signals, synthesizing zero-sequence current, and monitoring fault occurrence;
and setting a zero-sequence current threshold value according to a large amount of field data and simulation verification, wherein the zero-sequence current threshold value is used for distinguishing the fault state and the non-fault state of the line.
Step 2: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault is located, acquiring related parameter information, and returning to the step 1 to continuously monitor the zero sequence current amplitude change if the amplitude is not larger than the threshold value;
and step 3: randomly generating particle positions and speeds according to parameters such as preset particle scale, iteration times and the like, and starting algorithm iteration;
and 4, step 4: and calculating the adaptive value of each particle according to the objective function set in the algorithm and the parameters of the power distribution network system, updating the initial individual extreme value according to the adaptive value during first iteration, and taking the minimum value in all the individual extreme values as the initial global optimum value as the set objective function is smaller and more accurate. In the iteration process, when the adaptive value is smaller than the individual extreme value or the global optimal value, updating the corresponding value;
and 5: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration and outputting an optimal iteration solution, otherwise, updating the position and the speed of the particles and returning to the step 4 to carry out the next iteration.
Obtaining the negative sequence and zero sequence current of the head end of the line 2 and line parameters to carry out algorithm iteration, wherein the iteration result is shown in table 1:
and 5, obtaining the result in the step 5, constructing a particle swarm algorithm target function by obtaining the negative sequence and zero sequence current of the head end of the fault line and system parameters in the discrimination and ranging technology, and then iterating according to the particle swarm algorithm to accurately obtain the fault distance, wherein the average relative error in the ranging result is 5.7898%, the accuracy of the ranging result is high, and the correctness and the application reliability of the theoretical analysis of the technology are verified.
The invention also provides a power distribution network single-phase earth fault judgment device based on the particle swarm optimization corresponding to the method, and the device comprises:
a fault monitoring module: acquiring phase current signals, synthesizing zero-sequence current, and monitoring fault occurrence;
a fault determination module: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault is positioned, acquiring related parameter information, and if the amplitude is not larger than the threshold value, continuously monitoring the amplitude change of the zero sequence current;
a model construction module: establishing a target function according to the distribution characteristics of the negative sequence current and the zero sequence current of the system, and constructing a particle swarm algorithm model; randomly generating the position and the speed of the particles according to preset parameters;
a solving module: performing particle swarm algorithm iteration according to a set target function and power distribution network system parameters, and seeking a global optimum value;
an output module: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration, outputting an optimal iteration solution, and acquiring an accurate fault distance, otherwise, updating the position and the speed of the particle, and returning to perform the next iteration.
Further, the present invention also proposes a computer-readable storage medium storing one or more programs, characterized in that the one or more programs comprise instructions, which, when executed by a computing device, cause the computing device to perform the method according to the present invention.
Further, the present invention also proposes a computing device comprising: one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods according to the invention.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are only preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for the purpose of limiting the scope of the present invention, and on the contrary, any modifications or modifications based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A power distribution network single-phase earth fault distinguishing method based on a particle swarm algorithm is characterized by comprising the following steps:
step 1: obtaining phase current signals and synthesizing zero-sequence current;
step 2: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault exists, acquiring related parameter information, and returning to the step 1 to continuously monitor the zero sequence current amplitude change if the amplitude is not larger than the threshold value;
and step 3: establishing a target function according to the distribution characteristics of the negative sequence current and the zero sequence current of the system, and constructing a particle swarm algorithm model; randomly generating the position and the speed of the particles according to preset parameters;
and 4, step 4: performing particle swarm algorithm iteration according to a set target function and power distribution network system parameters, and seeking a global optimum value;
and 5: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration, outputting an optimal iteration solution, and obtaining an accurate fault distance, otherwise, updating the position and the speed of the particle, and returning to the step 4 to perform the next iteration.
2. The method according to claim 1, wherein in step 3, the particle swarm algorithm objective function is:
wherein the content of the first and second substances,
is a theoretical value of the negative sequence current of the upstream of the fault line calculated and acquired according to the zero sequence current at the fault point, and is used for judging whether the fault line is normal or not>
The negative sequence current measurement value of the first section of the fault line is obtained; lambda is a weight coefficient set according to a 'minimum set' in the fault diagnosis theory, and the value range is (0, 1); s (j) represents the equipment fault state, the value of 1 represents the equipment fault, the value of 0 represents the equipment normal, n represents the total quantity of the equipment, and j represents the equipment serial number; f (l) represents a particle swarm algorithm target function, the adaptive value of the target function takes a minimum value, and the particle swarm algorithm is used for solving the fault distance in the target function.
3. The method according to claim 2, wherein, in the step 3,
when the system comprises two outgoing lines and the second outgoing line has single-phase earth fault, the zero sequence current obtained from the head end of the fault line
And zero sequence current at fault point->
The relationship is as follows:
wherein L is an arc suppression coil inductance; c Σ Is system equivalent capacitance to ground, C' 2 The capacitance to ground of the upstream and downstream lines of the fault point of the fault line; l is the inductance of the system arc suppression coil;
negative sequence current drawn upstream of a faulted line
And negative at fault pointCurrent-sequential->
The relationship is as follows:
wherein Z 1 Negative sequence impedance of the first outgoing line, including line and load impedance; z' 2 The negative sequence impedance at the downstream of the fault point of the fault line comprises the line and the connected load negative sequence impedance; z T Equivalent negative sequence impedance of the transformer line and the high-voltage side; z 20 Positive and negative sequence impedance for a unit length of the line.
4. A method according to claim 3, wherein the line negative sequence impedance Z upstream of the point of fault of the faulty line 2 ＝Z 20 l；
When the neutral point of the power distribution network is grounded through the arc suppression coil:
when the neutral point of the power distribution network is not grounded:
5. the method according to claim 3, wherein, in step S3,
in a non-grounded system with a neutral point, an arc suppression coil loop in a zero sequence network diagram is opened, and zero sequence current obtained at the head end of a line
And zero sequence current at fault point->
The relationship is
6. The method of claim 5, wherein in step S3, the particle velocity and position iterative formula of the particle algorithm is as follows:
x i ＝x i +v i
in the formula: n, N being the total number of particles in the population; v. of i Is the particle velocity; x is the number of i Is the particle position; rand () is a random number, the range of which is (0, 1); c. C 0 The inertial weight factor can realize the adjustment of the global and local optimization capability of the algorithm by changing the numerical value of the inertial weight factor; c. C 1 And c 2 Respectively an individual and a global learning factor,
represents an individual extremum of a particle, is present>
Representing a global optimum.
7. The method according to claim 6, wherein in step S4, the adaptive value of each particle is calculated according to the objective function set in the algorithm and the parameters of the distribution network system, the initial individual extremum is updated according to the adaptive value during the first iteration, and the minimum value of all the individual extremum is used as the initial global optimum value; in the iterative process, when the adaptive value is smaller than the individual extreme value or the global optimal value, the corresponding value is updated.
8. A power distribution network single-phase earth fault discrimination device based on particle swarm optimization is used for realizing the method of any one of claims 1 to 7, and the device comprises:
a fault monitoring module: acquiring phase current signals, synthesizing zero-sequence current, and monitoring fault occurrence;
a fault determination module: when the zero sequence current amplitude is larger than the threshold value, judging that the single-phase earth fault occurs, starting a distance measurement algorithm, judging an outgoing line where the fault is positioned, acquiring related parameter information, and if the amplitude is not larger than the threshold value, continuously monitoring the amplitude change of the zero sequence current;
a model construction module: establishing a target function according to the distribution characteristics of the negative sequence current and the zero sequence current of the system, and constructing a particle swarm algorithm model; randomly generating the position and the speed of the particles according to preset parameters;
a solution module: performing particle swarm algorithm iteration according to a set target function and power distribution network system parameters, and seeking a global optimum value;
an output module: and judging whether the convergence condition is met or the maximum iteration number is reached, if so, ending the iteration, outputting an optimal iteration solution, and obtaining an accurate fault distance, otherwise, updating the position and the speed of the particle, and returning to perform the next iteration.
9. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-7.
10. A computing device, comprising:
one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-7.
Applications Claiming Priority (2)
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| CN117277230A (en) * | 2023-08-18 | 2023-12-22 | 国家电网有限公司华东分部 | Single-phase grounding distance protection method and device, storage medium and computer equipment |
| CN118011151A (en) * | 2024-04-08 | 2024-05-10 | 山东大学 | Distribution network single-phase earth fault distance measurement method and system based on zero sequence current |
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| CN117277230A (en) * | 2023-08-18 | 2023-12-22 | 国家电网有限公司华东分部 | Single-phase grounding distance protection method and device, storage medium and computer equipment |
| CN118011151A (en) * | 2024-04-08 | 2024-05-10 | 山东大学 | Distribution network single-phase earth fault distance measurement method and system based on zero sequence current |
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