A power distribution network fault locating method considering low-voltage user power-off information

Abstract

The application discloses a power distribution network fault positioning method considering low-voltage user power-off information, comprising the following steps: S1, constructing a switch function and a target function according to the relationship between each section and each device in the power distribution network; S2, obtaining the detected fault information and the power-off information of the low-voltage user side in the power distribution network, and encoding the fault information; S3, generating a predetermined number of initial populations; S4, calculating the target function value of each individual in the population, performing genetic operation on the population, generating a new generation of population, judging whether the optimization iteration termination condition is reached, if the termination condition is met, continuing to perform step S5, if the termination condition is not met, continuing to perform step S4; S5, decoding the individual with the highest fitness in the population, and outputting the decoded power distribution network fault positioning result. Through the application, the fault position in the power distribution network can be rapidly and accurately determined through real-time global optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of fault location of distribution networks, and in particular to a distribution network fault location method taking into account power outage information of low-voltage users. Background Art

[0002] As the terminal of the power system, the distribution network directly determines the reliability of power supply to users. Accurately locating the fault section in the distribution network is crucial for quickly isolating the fault, restoring power, and improving user power supply reliability.

[0003] Current distribution network fault location methods primarily fall into two categories: matrix-based methods and artificial intelligence optimization algorithms. Matrix algorithms generally construct a network matrix and a fault information matrix based on graph theory analysis, then determine the faulty segment based on matrix operations. While this method is simple and easy to implement, it requires accurate uploaded fault information and suffers from limited fault tolerance. Artificial intelligence optimization algorithms first use 0-1 variables to represent whether each distribution network segment or device has a fault, using the binary encoding of each segment's status as the decision variable for the optimization problem. They also construct several switching functions to reflect the relationship between fault signals detected by devices like circuit breakers or section switches in the distribution network and the fault status of each segment or device, serving as constraints for the optimization problem. The deviation between the measured fault signal and the switching function is then used as the objective function for the optimization problem. By minimizing the objective function, the algorithm seeks the fault type and faulty device combination that best explains the measured fault information, thereby locating the fault in the distribution network. Commonly used algorithms for this optimization problem include genetic algorithms and ant colony algorithms.

[0004] Fault location methods based on artificial intelligence (AI) optimization algorithms have been widely used due to their high fault tolerance. However, while these methods improve the fault tolerance and efficiency of distribution network fault location, they also have certain limitations. In practice, fault signals from certain switches may be erroneous due to signal distortion, communication errors, and other factors. When signals from switches adjacent to the faulty section are distorted, these methods are likely to misjudge and produce erroneous final location results. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for locating distribution network faults taking into account power outage information of low-voltage users, comprising the following steps:

[0006] S1: Construct the switching function and the objective function according to the relationship between each section and each device in the distribution network;

[0007] S2: Obtain fault information detected in the distribution network and power outage information on the low-voltage user side, and encode the fault information;

[0008] S3: Generate a predetermined number of initial populations;

[0009] S4: Calculate the objective function value of each individual in the population, perform genetic operations on the population, generate a new generation of population, and determine whether the optimization iteration termination condition has been met. If the termination condition has been met, proceed to step S5; if the termination condition has not been met, proceed to step S4;

[0010] S5: Decode the individual with the highest fitness in the population and output the decoded distribution network fault location result.

[0011] Furthermore, the construction of the switching function and the objective function according to the relationship between each section and each device in the distribution network includes the following process:

[0012] For a radial distribution line with m users, the switching function is:

[0013]

[0014] Where, F CB is the switching function value of the circuit breaker, F i1 and F i2 are the switching function values ​​of the section switch between Zi and Zi-1 and the section switch between Zi and the i-th low-voltage user, G d,i is the switching function value of the i-th load point; F CB Indicates whether the circuit breaker detects a fault signal, F i1 and F i2 Indicates whether the corresponding section switch detects a fault signal; G d,i Indicates whether there is power outage information at the i-th load point; x i Indicates the fault status of the segment Zi, x i =1 represents the failure of the section Zi, x i =0 means that there is no fault in the section Zi; the symbol ∨ represents the “OR” operation;

[0015] For a radial distribution line with m users, the objective function E(x) is:

[0016]

[0017] Where, Indicates whether the circuit breaker actually sends a fault signal. and Indicates whether the corresponding section switch actually sends a fault signal; Indicates whether the i-th load point actually has power outage information.

[0018] Furthermore, the method of obtaining the fault information detected in the distribution network and the power outage information on the low-voltage user side and encoding the fault information includes the following process: obtaining the fault information detected in each circuit breaker, section switch and other equipment in the distribution network and the power outage information on the low-voltage user side, and representing the fault information in binary code.

[0019] Furthermore, the generation of a predetermined number of initial populations includes the following process: generating an initial population, wherein an individual in the population is a binary-coded digital string containing a possible operating status information of each section of the distribution network; the length of the coding string is the same as the number of sections in the distribution network; each bit of the coding string represents a fault state of a section of the distribution network, and the value of each bit is randomly selected from 0 or 1, 1 indicates that the section is faulty, and 0 indicates that the section is normal; continuously generating new individuals according to the above method until the number of individuals reaches a predetermined population size; if a newly generated individual is repeated with a previously generated individual during the generation of the initial population, the new individual is modified bit by bit and the modified new individual is compared with the previously generated individual until the generated new individual does not repeat with other individuals.

[0020] Furthermore, the specific process of step S4 is as follows: calculating the objective function E(x) value of each individual in the population according to the switching function; selecting individuals according to the selection mechanism, performing crossover and mutation operations on them, and generating a new generation population, the size of the new generation population being the same as the size of the initial population; wherein the selection mechanism adopts a roulette mechanism for finding the minimum value of the objective function; judging whether the conditions for terminating the optimization iteration have been met according to the individual objective function E(x) value and the number of iterations that have been performed; if the termination conditions have been met, the optimization is terminated; otherwise, step S4 is repeated.

[0021] Furthermore, the decoding of the individual with the highest fitness in the population and the output of the decoded distribution network fault location result include the following process: after the iteration, selecting the individual in the current population that minimizes the objective function value E(x), decoding the binary code of the individual to restore it to information about the fault status of each section in the distribution network, screening out the section where the fault occurs, and providing the fault location result.

[0022] The beneficial effects of the present invention are as follows: the present invention adopts a genetic algorithm taking into account the power outage information on the low-voltage user side to solve the fault location problem in the distribution network, and can quickly and accurately determine the fault location in the distribution network through real-time global optimization;

[0023] Due to the addition of low-voltage user-side power outage information as an information source, it has better fault tolerance than the closest existing technology. The accuracy of the positioning results given in the case of information distortion is higher than that of the existing technology. It can better adapt to situations in actual applications with information distortion, communication errors, etc., and is more suitable for the needs of actual projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of a distribution network fault location method taking into account low-voltage user power outage information;

[0025] Figure 2 1 is a flow chart of a distribution network fault location method taking into account low-voltage user power outage information of the present invention;

[0026] Figure 3 This is a schematic diagram of the general structure of a radial distribution network to which the method of the present invention is applicable. DETAILED DESCRIPTION

[0027] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0028] like Figure 1 As shown, a distribution network fault location method taking into account low-voltage user power outage information includes the following steps:

[0029] S1: Construct the switching function and the objective function according to the relationship between each section and each device in the distribution network;

[0030] S2: Obtain fault information detected in the distribution network and power outage information on the low-voltage user side, and encode the fault information;

[0031] S3: Generate a predetermined number of initial populations;

[0032] S4: Calculate the objective function value of each individual in the population, perform genetic operations on the population, generate a new generation of population, and determine whether the optimization iteration termination condition has been met. If the termination condition has been met, proceed to step S5; if the termination condition has not been met, proceed to step S4;

[0033] S5: Decode the individual with the highest fitness in the population and output the decoded distribution network fault location result.

[0034] The construction of the switching function and the objective function according to the relationship between each section and each device in the distribution network includes the following process:

[0035] For a radial distribution line with m users, the switching function is:

[0036]

[0037] Where, F CB is the switching function value of the circuit breaker, F i1 and F i2 are the switching function values ​​of the section switch between Zi and Zi-1 and the section switch between Zi and the i-th low-voltage user, G d,iis the switch function value of the ith load point; F CB represents whether the circuit breaker detects a fault signal, F i1 and F i2 represents whether the corresponding sectionalizer detects a fault signal; G d,i represents whether the ith load point has power failure information; x i represents the fault state of the section Zi, x i = 1 represents that the section Zi is faulty, x i = 0 represents that the section Zi is not faulty; the symbol ∨ represents "or" operation;

[0038] The radial distribution line with m users, the objective function E(x) is:

[0039]

[0040] In the formula, represents whether the circuit breaker actually sends a fault signal, and represents whether the corresponding sectionalizer actually sends a fault signal; represents whether the ith load point actually has power failure information.

[0041] The fault information detected in the power distribution network and the power failure information on the low-voltage user side are obtained, and the fault information is encoded, including the following process: obtaining the fault information detected in each circuit breaker, sectionalizer and other devices in the power distribution network and the power failure information on the low-voltage user side, and encoding the fault information with a binary code.

[0042] The initial population of a predetermined number is generated, including the following process: generating an initial population, each individual in the population is a binary code digital string containing a possible operating state information of each section of the power distribution network; the length of the code string is the same as the number of sections in the power distribution network; each bit of the code string represents the fault state of a section of the power distribution network, and each bit is randomly selected between 0 and 1, taking 1 to represent that the section is faulty, and taking 0 to represent that the section is normal; continuously generate new individuals according to the above method until the number of individuals reaches the predetermined population size; if the newly generated individual is repeated with the previously generated individual during the generation of the initial population, modify the new individual bit by bit and compare the modified new individual with the previously generated individual until the generated new individual is not repeated with other individuals.

[0043] The specific process of step S4 is as follows: the objective function E(x) value of each individual in the population is calculated according to the switching function; individuals with smaller adaptive objective function E(x) values ​​are selected according to the selection mechanism, and crossover and mutation operations are performed on them to generate a new generation population, the size of the new generation population is the same as the size of the initial population; wherein the selection mechanism adopts a roulette mechanism for finding the minimum value of the objective function; and whether the conditions for terminating the optimization iteration have been met according to the individual objective function E(x) value and the number of iterations that have been performed. If the termination conditions have been met, the optimization is terminated; otherwise, step S4 is repeated.

[0044] The decoding of the individual with the highest fitness in the population and outputting the decoded distribution network fault location result includes the following process: after the iteration, selecting the individual in the current population that minimizes the objective function value E(x), decoding the binary code of the individual to restore it to information about the fault status of each section in the distribution network, screening out the section where the fault occurs, and providing the fault location result.

[0045] Specifically, the distribution network fault location method proposed in the present invention taking into account low-voltage user power outage information includes the following process:

[0046] Construct a switching function based on the relationship between each section and each device in the distribution network. Figure 3 For the radial distribution line with m users shown in the figure, the switching function is defined as:

[0047]

[0048] Where, F CB is the switching function value of the circuit breaker, F i1 and F i2 are the switching function values ​​of the section switch between Zi and Zi-1 and the section switch between Zi and the i-th low-voltage user, G d,i is the switching function value of the i-th load point (i.e. the i-th low-voltage user). CB Indicates whether the circuit breaker detects a fault signal, F i1 and F i2 Indicates whether the corresponding section switch is detected, 1 represents a fault signal, 0 represents no fault signal; G d,i Indicates whether there is power outage information at the i-th load point, 1 represents power outage information, and 0 represents no power outage information. i Indicates the fault status of the segment Zi, x i =1 represents the failure of the section Zi, x i =0 means that there is no fault in the section Zi. The symbol ∨ represents an “OR” operation.

[0049] For Figure 3 For the radial distribution line with m users shown in the figure, the objective function E(x) is defined as:

[0050]

[0051] Where, Indicates whether the circuit breaker actually sends a fault signal. and Indicates whether the corresponding section switch actually sends out a fault signal, 1 means a fault signal is sent out, 0 means no fault signal; Indicates whether the i-th load point actually has power outage information, 1 represents power outage information, and 0 represents no power outage information.

[0052] This function obtains fault information detected in devices such as circuit breakers and section switches in the distribution network, as well as power outage information for low-voltage users. This information is represented by a binary code. A value of 1 indicates a fault signal has been detected in a device such as a circuit breaker or section switch, or a power outage has occurred for a low-voltage user. A value of 0 indicates no fault signal has been detected in a device such as a circuit breaker or section switch, or no power outage has occurred for a low-voltage user.

[0053] Generate an initial population. The population size is between 50 and 150, meaning the initial population can contain 50-150 unique individuals. The population size can be adjusted within the above range based on the number of sections in the distribution network to be tested. If the number of sections is small, a smaller population size can be selected; if the number is large, a larger population size can be selected. Each individual in the population is a binary-coded string containing information about a possible operating state for each section of the distribution network. The length of the string is the same as the number of sections in the distribution network. Each bit in the string represents the fault state of a distribution network section. The value of each bit is randomly selected between 0 and 1, with 1 indicating a faulty section and 0 indicating normal operation. New individuals are continuously generated using the above method until the number of individuals reaches the predetermined population size. If a newly generated individual duplicates a previously generated individual during the initial population generation process, the new individual is modified bit by bit and compared with the previously generated individual until no new individuals are duplicated.

[0054] The switch function constructed in the previous step calculates the objective function E(x) value of each individual in the population. Based on the individual objective function E(x) value and the number of iterations that have been performed, it is determined whether the conditions for terminating the optimization iteration have been met. That is, if there is an individual that meets the set fitness function value requirement or the number of iterations that have been performed has reached the set upper limit of the number of iterations, then the optimization is terminated.

[0055] According to the selection mechanism, individuals with the smallest fitness function value E(x) are selected and subjected to crossover and mutation operations to generate a new generation of populations. The size of the new generation of populations is the same as that of the initial population. The selection operation uses a roulette wheel mechanism to find the minimum value of the objective function; the crossover operation uses a binary single-point crossover mechanism with a crossover probability of 0.6; and the mutation operation uses a binary mutation mechanism with a mutation probability of 0.01.

[0056] After the iteration is completed, the individual with the smallest objective function value E(x) in the current population is selected, and the binary code of the individual is decoded and restored to the information of the fault status of each section in the distribution network. The section where the fault occurs is screened out, and the fault location result is given.

[0057] The foregoing description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein and should not be construed as excluding other embodiments. Rather, the present invention can be used in various other combinations, modifications, and environments and can be modified within the scope of the concept described herein through the above teachings or techniques or knowledge in the relevant field. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention are intended to be protected by the appended claims.

Claims

1. A distribution network fault location method taking into account low-voltage user power outage information, characterized in that: The steps include: S1: Construct the switching function and the objective function according to the relationship between each section and each device in the distribution network; S2: Obtain fault information detected in the distribution network and power outage information on the low-voltage user side, and encode the fault information; S3: Generate a predetermined number of initial populations; S4: Calculate the objective function value of each individual in the population, perform genetic operations on the population, generate a new generation of population, and determine whether the optimization iteration termination condition has been met. If the termination condition has been met, proceed to step S5; if the termination condition has not been met, proceed to step S4; S5: Decode the individual with the highest fitness in the population and output the decoded distribution network fault location result; The construction of the switching function and the objective function according to the relationship between each section and each device in the distribution network includes the following process: For a radial distribution line with m users, the switching function is: Where, F CB is the switching function value of the circuit breaker, F i1 and F i2 are the switching function values ​​of the section switch between Zi and Zi-1 and the section switch between Zi and the i-th low-voltage user, G d,i is the switching function value of the i-th load point; F CB Indicates whether the circuit breaker detects a fault signal, F i1 and F i2 Indicates whether the corresponding section switch detects a fault signal; G d,i Indicates whether there is power outage information at the i-th load point; x i Indicates the fault status of the segment Zi, x i =1 represents the failure of the section Zi, x i =0 means that there is no fault in the section Zi; the symbol ∨ represents the "OR" operation; For a radial distribution line with m users, the objective function E(x) is: Where, Indicates whether the circuit breaker actually sends a fault signal. and Indicates whether the corresponding section switch actually sends a fault signal; Indicates whether the i-th load point actually has power outage information.

2. A distribution network fault location method taking into account low-voltage user power outage information according to claim 1, characterized in that: The method of obtaining the fault information detected in the distribution network and the power outage information on the low-voltage user side and encoding the fault information includes the following process: obtaining the fault information detected in each circuit breaker, section switch and other equipment in the distribution network and the power outage information on the low-voltage user side, and representing the fault information in binary code.

3. A distribution network fault location method taking into account low-voltage user power outage information according to claim 1, characterized in that: The generating of the predetermined number of initial populations comprises the following steps: generating the initial population, wherein an individual in the population is a binary coded digital string containing information about a possible operating state of each section of the distribution network; the length of the coded digital string is the same as the number of sections in the distribution network; each bit of the coded digital string represents a fault state of a section of the distribution network, and the value of each bit is randomly selected as 0 or 1; and continuously generating new individuals according to the above method until the number of individuals reaches the predetermined population size; If the newly generated individuals in the process of generating the initial population are repeated with the previously generated individuals, the new individuals are modified bit by bit and the modified new individuals are compared with the previously generated individuals until the generated new individuals are no longer repeated with other individuals.

4. A distribution network fault location method taking into account low-voltage user power outage information according to claim 1, characterized in that: The specific process of step S4 is as follows: calculating the objective function E(x) value of each individual in the population according to the switching function; selecting individuals according to the selection mechanism, performing crossover and mutation operations on them, and generating a new generation population, the size of the new generation population being the same as the size of the initial population; wherein the selection mechanism adopts a roulette mechanism for finding the minimum value of the objective function; judging whether the conditions for terminating the optimization iteration have been met based on the individual objective function E(x) value and the number of iterations that have been performed; if the termination conditions have been met, the optimization is terminated; otherwise, step S4 is repeated.

5. A distribution network fault location method taking into account low-voltage user power outage information according to claim 1, characterized in that: The decoding of the individual with the highest fitness in the population and outputting the decoded distribution network fault location result includes the following process: after the iteration, selecting the individual in the current population that minimizes the objective function value E(x), decoding the binary code of the individual to restore it to information about the fault status of each section in the distribution network, screening out the section where the fault occurs, and providing the fault location result.

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