Abstract: The high-voltage power grid structure in coal mines is complex, making it difficult to locate fault points once a failure occurs. To address this issue, we propose a power grid fault location system based on a wireless sensor network. Practice has shown that this system provides a reliable guarantee for safe production in coal mines and offers significant economic and social benefits. This project has broad applicability in coal mines and demonstrates considerable application value.
Keywords: Graph theory; Wireless sensor networks; High-voltage power grid
Abstract: The structure of coal mine high voltage grid is complex, once a failure happens, it will be difficult to find out where the failure point is. To solve this problem, we propose a positioning system of grid failure points based on wireless sensor network. The practical result shows that this kind of positioning system provides a reliable guarantee for the coal mine production safety and has a great economic and social benefit. The project has widespread applicability in the coal mine and a good application value.
Key words: graph theory; wireless sensor network; High voltage grid
1. Introduction
Currently, the method for locating faults in power distribution lines involves first identifying the faulty line and then tracing the fault point along the worker's path. With the strengthening of power distribution networks, these lines have become particularly complex, making it extremely difficult to pinpoint the exact location of the fault using traditional methods. This wastes considerable time and severely impacts normal coal mine production. Therefore, research on fault location methods for power distribution lines is of great significance. This paper aims to study a suitable method for high-voltage fault location systems in coal mines. Based on domestic and international research on distributed fault location technologies and considering the actual conditions of 6kV high-voltage grids in coal mines, we have developed a fault location system for high-voltage power grids in coal mines.
This paper first constructs the mathematical model of the system, and then studies and formulates a graph theory-based intelligent location algorithm by analyzing the structure of the coal mine distribution network and fault location algorithms. The use of Wireless Sensor Network (WSN) technology based on a high-speed data acquisition system on the ground makes it easy to obtain fault information. By combining MCGS configuration software, Matlab, databases, and other PC software, the system successfully achieves precise fault location, real-time display of the coal mine distribution network, alarm functions, and other operational capabilities.
2. Localization Algorithm
Based on the fundamental principles of graph theory, the feeders in a distributed network are treated as edges, and the feedback switches as vertices. Therefore, we can use graph theory to establish the mathematical model and corresponding algorithms for distributed networks. There are many ways to describe a matrix based on the relationship between vertices and edges. Here, we just introduce the methods for describing adjacency matrices and correlation matrices.
2.1 Adjacency Matrix
For the distribution network of N nodes in graph G(V,E), such as v1 , v2 , ..., vn , we can determine the connection relationship between the nodes and the adjacency matrix An × n of the distribution network. If there are edge nodes, Aij = Aji = 1; otherwise, Aij = Aji = 0.
2.2 Correlation Matrix
The description method of the correlation matrix is determined by the topological structure of the relationships between network nodes and edges. A graph G(V, E) has n nodes: V = { v1 , v2 , ..., vn } and m edges E = { e1 , e2 , ..., em }. If a node is connected to an edge, then A <sub>ij</sub> = A <sub>ji</sub> = 1; otherwise, A <sub>ij</sub> = A<sub> ji</sub> = 0.
2.3 Regional Correlation Matrix
Because the number of feedback lines in a power distribution network is very large and the structure is complex, the network topology often has a high dimension. Directly using adjacency matrix and correlation matrix description methods would be computationally difficult. Therefore, we need a simplified topology description matrix, and thus propose the concept of a regional topology description matrix. Using this matrix for analysis and information processing greatly simplifies the process. Based on the characteristics of node failures, we use a new node to represent the information of the entire region; if one node in a region fails, it means that all nodes in that region are also faulty. Regions Zi ( vi , vj , ..., vm ) are the parent nodes of the child nodes of vi . Assuming the distribution network can be decomposed into m regions, we can establish a regional correlation matrix Q( qij ) M × M. All diagonal elements of the matrix are equal to zero, such as qij = 0. Analyze two connected regions Z <sub>i </sub>(v <sub>i </sub> , v<sub>j</sub>, ..., v<sub>n </sub> ) and Z<sub> j</sub> (v <sub> i</sub>, v<sub> j </sub>, ..., v<sub>n</sub>). If the v <sub>li</sub> of parent node Z<sub> i</sub> is connected to the v <sub>mj</sub> of another parent node Z<sub> j </sub>, then q <sub>ij </sub> = 1; otherwise, q <sub>ij </sub> = 0.
Through the above introduction, we use the regional topology matrix to divide regions. Through analysis, if a child node within a region is faulty, its parent node must also be faulty. For example, if nodes within the sub-region Zi (v<sub>i </sub> , v<sub> j </sub>, ..., v<sub> n</sub> ) are faulty, we consider Zi to be a faulty region. If there are no faults, we consider the region to be normal. Determine the fault information matrix G<sub> D</sub> :
We can identify P- faults using the regional fault information matrix and the region's correlation matrix.
Fault DP criteria: (1) d <sub>ii</sub> = 1 (2) If d <sub>ji</sub> = 1 and d<sub> jj</sub> = 0, then we can see that the fault occurs in the Zi region or between the feedback lines Zi and Z<sub> j </sub>. If v <sub>1 </sub> = v <sub>2 </sub> = ... = v <sub>n</sub> = 0, the fault occurs on the feedback line. If one of them equals 1, the fault occurs in the Zi region.
2.4 Algorithm
The central substation is located 255 meters underground, with three power lines originating from the surface and equipped with explosion-proof high-voltage switches. We have installed 21 wireless sensors, which will receive information from base stations connected to the industrial control computer in the event of a fault. Figure 1 shows the numbers for the central substation. "20" and "21" are two contact switches. Using IPC software, we can locate the faulty line using the methods described above.
Figure 1 Central Substation
3. System Design
The components of a coal mine high-voltage power line fault location system are shown in Figure 2. This system employs a state-of-the-art Wireless Sensor Network (WSN) fault condition monitoring system. Wireless sensor network nodes acquire information about the entire line. When a short circuit occurs, the fault information is sent to the base station. The base station encodes the signal and transmits it to the master station on the ground. The diagnostic software installed on the master station's computer determines the location of the fault.
3.1 Wireless Sensor Networks
Wireless sensor networks are suitable for deployment in coal mines, which are characterized by harsh environments and high risks. Figure 2 shows the working principle diagram.
Figure 2 System schematic diagram
The wireless sensor network nodes are equipped with cables that monitor the line's operation. If a short circuit occurs, the wireless sensor network node quickly detects the fault signal and transmits it to a base station installed near the node.
The node mainly consists of two parts: a detection section and a wireless communication section. The node uses the MSP430 MCU F2132 microcontroller core. The MSP430 microcontroller uses a 16-bit RISC processor as its core, and can execute instructions in a single cycle. Compared with other types of microcontrollers, it has stronger processing power and faster operating speed. Some types of MSP430 microcontrollers also have an internal hardware multiplier, DMA, and other functions, enabling them to perform tasks that would normally be handled by a DSP.
The design of the mine wireless fault indicator is shown in Figure 3. The main components of the sensor are: MCU (microcontroller), wireless communication module, and power supply module.
Figure 3. Wireless fault indicator in the mine
3.2 High-speed data acquisition equipment
The high-speed data acquisition system is shown in Figure 4. It adopts a plug-in box structure and modular design, consisting of three parts: a high-speed data acquisition hardware system, data storage and transmission, and data analysis and processing.
Figure 4 High-speed data acquisition system
High-speed data acquisition system hardware: The device accesses a current transformer (CT). The traveling wave component is extracted by a filter circuit and converted into a digital signal by an A/D converter. The FPGA control module controls the data storage in a buffer. Once the start-up conditions are met, the fault trigger point is recorded, and the data stored in the buffer is transferred to the fault record data dump module. Data dump module: Saves data to CF and SD cards, minimizing power loss in the data acquisition section, ensuring data is not lost even during power outages. Data analysis and processing: The ETX embedded computer module automatically analyzes the file, performing data display, printing, keyboard control, etc.
3.3 Main features of ground monitoring stations
Based on the above analysis and calculations, the implementation of the 6KV high-voltage power supply fault location system in the mine requires the establishment of an accurate mathematical model of the distributed network and fault identification matrix, incorporating a wide range of information. Due to the complexity of the system, software design becomes crucial for success. Therefore, we designed software for fault information processing and precise location, and the system structure is shown in Figure 5.
While the configured software boasts a powerful human-computer interface and communication capabilities, it seems insufficient for numerical computation and analysis. MATLAB is an excellent numerical computation, algorithm development, and system simulation software, facilitating easy computation and programming, but its user interface design is inconvenient; it lacks a computer hardware interface, and its ports are inaccessible. We combine their advantages.
When the program runs, the fault data collected by MCGS through the DDE method is processed by Visual Basic. The fault data obtained by the wireless sensor network and high-speed data acquisition device is then sent to the MATLAB function for calculation. Finally, Visual Basic obtains the results from the MATLAB software and displays them in MCGS.
Figure 5 Software Structure
4. Summary
The investment in a 6kV high-voltage fault location system for coal mines enables comprehensive monitoring of the underground high-voltage power grid, preventing accidents and ensuring safety during coal mine production. This system significantly reduces personnel involvement, saves labor costs, improves labor efficiency, and guarantees coal mine safety. The project has broad applicability in coal mines and demonstrates significant application value.
References
References
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