New energy grid-connected line fault section positioning system based on ant colony algorithm

Abstract

The invention discloses a new energy grid-connected line fault section positioning system based on an ant colony algorithm, and relates to the technical field of power grid fault diagnosis, and the system comprises a wire signal collection module and a fog end intelligent analysis module. According to a distributed architecture, an optimal section where a fault occurs in a grid-connected line is analyzed. The method has the advantages that real-time positioning is high, the network pressure of data centralized transmission and the complexity of centralized calculation are reduced, the fault analysis precision is improved, and the criterion reliability is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid fault diagnosis, and in particular to a new energy grid-connected line fault section positioning system based on ant colony algorithm. Background Art

[0002] With the development of the power system, the number of new energy grid-connected is increasing, and the types of distributed power sources are gradually enriched, highlighting the advantages of economy, environmental protection, safety, and flexibility. However, it also makes the network topology of the power system more complex, which has a certain impact on the stability of the power grid. At present, the amount of monitoring and operation data of new energy grid-connected lines is large, and the signal is weak and difficult to identify when a fault occurs. At the same time, due to the slow calculation speed and poor effect of the current fault section location algorithm, it brings certain difficulties to the fault section location. Summary of the invention

[0003] In order to solve the above problems, the purpose of the present invention is to provide a new energy grid-connected line fault section positioning system based on ant colony algorithm, which aims to analyze the transient fault waveform characteristics collected and extracted by the terminal through an intelligent ant colony algorithm, and transmit, process, store and analyze the ant colony data according to the distributed power supply network topology, so as to achieve fast, dynamic and accurate fault section positioning.

[0004] In order to achieve the above technical objectives, the present application provides a new energy grid-connected line fault section positioning system based on ant colony algorithm, comprising: Conductor signal acquisition module, used to collect transient signals of the power grid; The fog terminal intelligent analysis module is used to process transient voltage and transient current, perform fault feature analysis using wavelet packets, and calculate the fault section path based on the ant colony algorithm.

[0005] Preferably, the fog terminal intelligent analysis module transmits, processes, stores and analyzes ant colony data according to the distributed power supply network topology.

[0006] Preferably, the fog terminal intelligent analysis module is also used to denoise the transient signal to improve the signal-to-noise ratio; capture the characteristics of the signal mutation point through multi-layer wavelet packet decomposition, and adaptively determine the number of wavelet packet decomposition layers according to the degree of performance of different fault voltage or current mutation points; and determine the fault characteristic points by analyzing the energy changes of the high-frequency components of the voltage and current signals.

[0007] Preferably, the fog-end intelligent analysis module is also used to initialize the number of ants, the number of iterations, the node topology matrix, the pheromone matrix, the pheromone volatility rate, and the heuristic factor to execute the ant colony algorithm for fault location.

[0008] Preferably, the fog terminal intelligent analysis module is also used to create a group of ants with phase current fault characteristic values ​​in time sequence when a fault is triggered, and use the occupancy rate of the phase current fault characteristic value as the pheromone concentration.

[0009] Preferably, the fog terminal intelligent analysis module is also used to release ants from the first fault trigger point, detect the electrical signal characteristics of adjacent monitoring points, update the pheromone matrix, and select the final path. When each ant passes through the power line collection point, the pheromone concentration is updated according to the fault characteristics. If the information concentration increases, it moves to the next node in the direction of the current and records the path information.

[0010] Preferably, the fog terminal intelligent analysis module, when performing fault location, includes the following steps: Step 3.1, the ant calculates the transfer probability based on the pheromone concentration and fitness value of the current node. The transfer probability formula is as follows: in, represents the probability of ant k transferring from node i to node j at time t; represents the pheromone concentration between node i and node j; represents heuristic information, the detailedness of the fault characteristics between node i and node j; ɑ represents the pheromone importance factor, which controls the influence of pheromone concentration on the transfer probability; represents the importance factor of heuristic information, which controls the impact of heuristic information on the transition probability; d represents the set of nodes that ant k can access at the current node i; N, N is the number of sensors collecting wire signals, representing the number of nodes in the high-voltage line; Step 3.2, calculate the pheromone concentration of the node, the formula is as follows: ; in, Represents the updated node To Node The pheromone concentration is initially ; Indicates the pheromone volatilization rate, with a value between 0 and 1; Indicates that the ant is at a path node To Node Increased pheromone release; Step 3.3, update the node access status matrix: Ant k triggers the fog terminal intelligent computing function, arrives at the node to obtain the pheromone concentration of the adjacent nodes, and updates the pheromone concentration matrix of the adjacent nodes.

[0011] Preferably, the fog terminal intelligent analysis module is also used to determine whether the kth ant has completed path finding, and when path finding is completed, calculate the optimal path: ,in, Represents the node combination of all paths of the k-th ant.

[0012] The present invention discloses the following technical effects: (1) Reduce the time of locating the fault section and enhance real-time positioning; (2) A decentralized fault analysis architecture that reduces the network pressure of centralized data transmission and the complexity of centralized computing; (3) Optimize the noise removal method of fault judgment criteria, improve the accuracy of fault analysis, and enhance the reliability of judgment criteria; (4) Signal acquisition technology, communication technology, and edge computing technology are mature and have good adaptability and robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0015] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0016] like Figure 1 As shown, the present invention provides a fault section positioning system for new energy grid-connected lines based on ant colony algorithm, which uses the fog terminal distributed computing module to integrate the intelligent ant colony algorithm to analyze the transient fault waveform characteristics collected and extracted by the terminal, and transmits, processes, stores and analyzes the ant colony data according to the distributed power network topology. In this way, fast, dynamic and accurate fault section positioning is achieved; The data source of this technology comes from the conductor signal acquisition module. The fog terminal intelligent analysis module is used to make a preliminary judgment on the collected transient signals such as voltage and current, and the ant colony algorithm and the fog terminal intelligent body are integrated to distribute and analyze the optimal section where the fault occurs in the grid-connected line. Among them, the fog terminal intelligent analysis module is based on the decentralized conductor electrical signal abnormal state data preprocessing analysis and computing resources and communication resource status analysis. It mainly completes the transient voltage and current preprocessing and wavelet packet-based fault feature analysis, and ant colony-based calculation of the fault section path; terminal CPU, memory, power and other resource status monitoring and analysis. When any of the CPU, memory, power and other resources is close to the threshold range, the calculation process data or results are transmitted to another node.

[0017] The method for locating a fault section of a new energy grid-connected line based on an ant colony algorithm mentioned in the present invention comprises the following steps: Step 1: Monitor and analyze the phase voltage or phase current state, triggering the fault section location mechanism based on the ant colony algorithm. First, when the zero-sequence voltage amplitude exceeds a certain threshold, the fault feature analysis and extraction is started. The present invention uses wavelet packet transform to extract fault features, and the extraction process is as follows: Step 1.1, denoising the collected voltage and current information to improve the signal-to-noise ratio.

[0018] Step 1.2, capture the characteristics of the voltage and current signal mutation points after denoising through multi-layer wavelet packet decomposition, and adaptively determine the number of wavelet packet decomposition layers according to the degree of performance of different fault voltage or current mutation points.

[0019] Step 1.3: Analyze the energy changes of the high-frequency components of the voltage and current signals to determine the fault characteristic points.

[0020] Step 2: Start ant colony analysis and initialize relevant data. Initialize the number of ants, number of iterations, node topology matrix, pheromone matrix, pheromone volatility, heuristic factor and other data. When a fault is triggered, create a group of ants with phase current fault characteristic values ​​in time sequence, and use the occupancy rate of phase current fault characteristic values ​​as the pheromone concentration.

[0021] Step 3: Release ants from the first fault trigger point to detect the electrical signal characteristics of adjacent monitoring points, update the pheromone matrix, and select the final path. When each ant passes through the power line collection point, the pheromone concentration is updated according to the fault characteristics. If the information concentration increases, it moves to the next node in the direction of the current and records the path information. The specific steps include the following: Step 3.1, the ant calculates the transfer probability based on the pheromone concentration and fitness value of the current node. The transfer probability formula is as follows: in, represents the probability that ant k moves from node i to node j at time t.

[0022] Represents the pheromone concentration between node i and node j.

[0023] Represents heuristic information, detailed fault characteristics between node i and node j.

[0024] ɑ represents the pheromone importance factor, which controls the effect of pheromone concentration on the transfer probability; It represents the importance factor of heuristic information, which controls the impact of heuristic information on the transition probability.

[0025] d represents the set of nodes that ant k can access at the current node i.

[0026] N, N is the number of sensors collecting wire signals, representing the number of nodes in the high-voltage line.

[0027] Step 3.2, calculate the pheromone concentration of the node, the formula is as follows. .

[0028] in, Represents the updated node To Node The pheromone concentration is initially .

[0029] Indicates the pheromone volatilization rate, with a value between 0 and 1.

[0030] Indicates that the ant is at a path node To Node The increment of pheromone released is determined by the similarity of fault characteristics between nodes on the path.

[0031] Step 3.3, update the node access state matrix. Ant k triggers the fog terminal intelligent computing function, arrives at the node to obtain the pheromone concentration of the adjacent nodes, and updates the pheromone concentration matrix of the adjacent nodes.

[0032] Step 4: Determine whether the kth ant has completed pathfinding. If pathfinding is completed, calculate the optimal path: ,in, The nodes representing all the paths of the k-th ant are combined, and the process jumps to step 3 for the next round of pathfinding.

[0033] Step 5: Output the optimal solution finally found.

[0034] Compared with traditional technical designs, the system designed in the present invention has the advantages of reducing the time of locating the fault section and having strong real-time positioning capabilities. At the same time, the system design of the present invention belongs to a decentralized fault analysis architecture, which reduces the network pressure of centralized data transmission and the complexity of centralized calculation; by optimizing the noise removal method of fault judgment criteria, the accuracy of fault analysis is improved and the reliability of the judgment criteria is enhanced; the present invention has good adaptability and robustness through the maturity of signal acquisition technology, communication technology, and edge computing technology.

[0035] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0036] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0037] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A fault section location system for new energy grid-connected lines based on ant colony algorithm, characterized in that: include: Conductor signal acquisition module, used to collect transient signals of the power grid; The fog terminal intelligent analysis module is used to process transient voltage and transient current, perform fault feature analysis using wavelet packets, and calculate the fault section path based on the ant colony algorithm.

2. According to claim 1, a new energy grid-connected line fault section positioning system based on ant colony algorithm is characterized by: The fog terminal intelligent analysis module transmits, processes, stores and analyzes ant colony data based on the distributed power network topology.

3. According to claim 2, a new energy grid-connected line fault section positioning system based on ant colony algorithm is characterized by: The fog terminal intelligent analysis module is also used to denoise the transient signal to improve the signal-to-noise ratio; capture the signal mutation point characteristics through multi-layer wavelet packet decomposition, and adaptively determine the number of wavelet packet decomposition layers according to the degree of performance of different fault voltage or current mutation points; and determine the fault feature points by analyzing the energy changes of the high-frequency components of the voltage and current signals.

4. According to claim 3, a new energy grid-connected line fault section positioning system based on ant colony algorithm is characterized by: The fog terminal intelligent analysis module is also used to initialize the number of ants, the number of iterations, the node topology matrix, the pheromone matrix, the pheromone volatility rate, and the heuristic factor to execute the ant colony algorithm for fault location.

5. According to claim 4, a new energy grid-connected line fault section positioning system based on ant colony algorithm is characterized by: The fog terminal intelligent analysis module is also used to create a group of ants with phase current fault characteristic values ​​in time sequence when a fault is triggered, and use the occupancy rate of the phase current fault characteristic value as the pheromone concentration.

6. According to claim 5, a new energy grid-connected line fault section positioning system based on ant colony algorithm is characterized by: The fog terminal intelligent analysis module is also used to release ants from the first fault trigger point, detect the electrical signal characteristics of adjacent monitoring points, update the pheromone matrix, and select the final path. When each ant passes through the power line collection point, the pheromone concentration is updated according to the fault characteristics. If the information concentration increases, it moves to the next node in the direction of the current and records the path information.

7. A fault section positioning system for new energy grid-connected lines based on ant colony algorithm according to claim 6, characterized in that: The fog terminal intelligent analysis module, when performing fault location, includes the following steps: Step 3.1, the ant calculates the transfer probability based on the pheromone concentration and fitness value of the current node. The transfer probability formula is as follows: in, represents the probability of ant k transferring from node i to node j at time t; represents the pheromone concentration between node i and node j; represents heuristic information, the detailedness of the fault characteristics between node i and node j; ɑ represents the pheromone importance factor, which controls the influence of pheromone concentration on the transfer probability; represents the importance factor of heuristic information, which controls the impact of heuristic information on the transition probability; d represents the set of nodes that ant k can access at the current node i; N, N is the number of sensors collecting wire signals, representing the number of nodes in the high-voltage line; Step 3.2, calculate the pheromone concentration of the node, the formula is as follows: ； in, Represents the updated node To Node The pheromone concentration is initially ; Indicates the pheromone volatilization rate, with a value between 0 and 1; Indicates that the ant is at a path node To Node Increased pheromone release; Step 3.3, update the node access status matrix: Ant k triggers the fog terminal intelligent computing function, arrives at the node to obtain the pheromone concentration of the adjacent nodes, and updates the pheromone concentration matrix of the adjacent nodes.

8. The fault section positioning system for new energy grid-connected lines based on ant colony algorithm according to claim 7 is characterized by: The fog terminal intelligent analysis module is also used to determine whether the kth ant has completed path finding, and when path finding is completed, calculate the optimal path: ,in, Represents the node combination of all paths of the k-th ant.

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