A method and system for evaluating power line status based on artificial intelligence

Abstract

The present invention relates to a method and system for evaluating the state of a power line based on artificial intelligence. The method comprises the following steps: acquiring power monitoring data of a base station; performing power transportation path analysis on the power monitoring data of the base station to generate the power transportation path of the base station; performing power line network topology through the power transportation path of the base station to generate a power line topology network of the base station; screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; using a voltage sensor to perform real-time voltage collection of the power line transportation on the key nodes of the power line of the base station, thereby generating real-time voltage data of the power line of the base station. The present invention improves the accuracy and comprehensiveness of the power line state evaluation by performing comprehensive data collection, multi-dimensional analysis, key node management and intelligent evaluation on the power line.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power evaluation, and in particular to an artificial intelligence-based power line status evaluation method and system. Background Art

[0002] Early power line status assessment mainly relied on sensor technology and data acquisition equipment, which can monitor the voltage, current, temperature and other parameters of power lines and transmit data to the monitoring center through wireless communication technology. However, the analysis of these data still relies on manual processing, making it difficult to quickly and accurately detect potential faults. Entering the 21st century, machine learning and big data technologies have been gradually applied to power systems. By analyzing a large amount of historical data, machine learning algorithms can identify abnormal patterns in the operation of power lines. For example, algorithms such as support vector machines (SVM), decision trees, and neural networks are widely used in fault detection and prediction. In recent years, the development of deep learning technology has provided more powerful tools for power line status assessment. Deep learning models such as convolutional neural networks (CNN) and long short-term memory networks (LSTM) can process more complex data, such as images and time series data, to achieve higher fault detection accuracy. For example, by taking power line images with drones and analyzing them with CNN, defects and damage on the lines can be automatically identified. However, traditional methods are usually unable to effectively identify and manage key nodes of power lines, and ignore the impact of environmental factors on the operation of power lines, which leads to low accuracy and comprehensiveness of power line status assessment. Summary of the invention

[0003] Based on this, it is necessary to provide an artificial intelligence-based power line status assessment method and system to solve at least one of the above technical problems.

[0004] To achieve the above object, a power line status assessment method based on artificial intelligence is provided, the method comprising the following steps:

[0005] Step S1: acquiring base station power monitoring data; performing power transmission path analysis on the base station power monitoring data to generate the base station power transmission path; performing power line network topology through the base station power transmission path to generate the base station power line topology network;

[0006] Step S2: Screen the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data;

[0007] Step S3: Perform power line quality monitoring using power quality monitoring equipment according to key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data;

[0008] Step S4: Acquire power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

[0009] The present invention can monitor the operation status of the power line in real time by collecting voltage data and power quality data of key nodes of the base station power line in real time. This real-time monitoring capability ensures that it can respond quickly when an abnormality occurs, take repair measures in time, reduce power outages and failure time, and improve the stability and reliability of the power system. Through comprehensive analysis of data such as power line transmission voltage stability, harmonic distortion, waveform distortion, etc., potential fault nodes can be predicted in advance. This fault prediction and prevention capability helps power companies to carry out maintenance and repair in advance to avoid large-scale power outages and economic losses caused by sudden failures. Based on the power line state evaluation index generated by comprehensive evaluation, a scientific and efficient power line maintenance plan can be formulated. This maintenance plan can not only accurately repair specific problems and reduce unnecessary maintenance work and costs, but also ensure the continuous stability of power transportation. Through multi-dimensional data collection and analysis, a comprehensive comprehensive evaluation of power quality is carried out. Compared with the single indicator evaluation of traditional methods, this comprehensive evaluation method can more accurately reflect the actual operation status of the power line and provide more reliable data support for subsequent decision-making and optimization. The use of artificial intelligence algorithms to automatically analyze and process massive monitoring data reduces manual intervention and human errors, and improves the accuracy and efficiency of data processing. This improvement in the level of intelligence not only optimizes the process of power line status assessment, but also improves the operating efficiency of the entire power system. By acquiring power line environmental perception data, the impact of the external environment on the operation of the power line can be considered. This comprehensive environmental perception capability helps to more accurately assess the line status and formulate maintenance strategies, further improving the adaptability and reliability of the power system. Through real-time monitoring and evaluation of key nodes of power lines, the power transportation path can be optimized, power loss can be reduced, and power transmission efficiency can be improved. Therefore, the present invention improves the accuracy and comprehensiveness of power line status assessment by performing comprehensive data collection, multi-dimensional analysis, key node management and intelligent evaluation of power lines.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: Obtaining base station power monitoring data;

[0012] Step S12: Analyze the power transmission path of the base station power monitoring data to generate the base station power transmission path;

[0013] Step S13: confirming the power transmission line through the base station power transmission path to obtain the base station power transmission line;

[0014] Step S14: Perform power line network topology according to the base station power transmission line, thereby generating a base station power line topology network.

[0015] The present invention can obtain the operating status of the power line in real time and accurately by acquiring the base station power monitoring data, which provides a reliable data basis for subsequent path analysis and topology generation, and ensures the accuracy of the entire evaluation process. The power transportation path analysis of the base station power monitoring data is performed to generate the base station power transportation path. This step can identify the best power transportation path, reduce power loss and transportation costs, and improve the efficiency and reliability of power transportation. The power transportation line is confirmed through the base station power transportation path to ensure the specific path of each power line. This process can accurately locate the actual direction of each line, and provide an accurate basis for the subsequent topological network generation. By confirming the power transportation line, the potential weak links in the line can be identified, and maintenance and reinforcement can be carried out in advance to prevent the occurrence of potential faults. According to the confirmed power transportation line, the power line network topology is performed to generate the base station power line topology network. This step can construct the topological structure of the entire power system and fully display the connection relationship and layout of the power line. The generated topological network can be used to comprehensively monitor the entire power system, identify key nodes and important lines, and ensure the stable operation of the system.

[0016] Preferably, step S2 comprises the following steps:

[0017] Step S21: Screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station;

[0018] Step S22: using voltage sensors to collect real-time voltage data of power line transportation at key nodes of the base station power line, thereby generating real-time voltage data of the base station power line;

[0019] Step S23: performing power transmission fluctuation detection on the real-time voltage data of the power line to generate power line transmission voltage fluctuation data; performing waveform conversion on the power line transmission voltage fluctuation data to generate a power line transmission voltage fluctuation curve;

[0020] Step S24: Performing a line transmission voltage stability assessment based on the power line transmission voltage fluctuation curve to generate power line transmission voltage stability data.

[0021] The present invention can identify and locate nodes that are critical to power transmission by screening the key nodes of the power line topology network of the base station power line. These key nodes are important links in the power transportation system. Accurate monitoring of these nodes can more effectively manage and maintain the entire power system. The identified key nodes can obtain priority monitoring and maintenance resources to ensure the operational stability of these nodes, thereby ensuring the reliability of the entire power system. The voltage sensor is used to collect the real-time voltage of the power line transportation of the key nodes, and the voltage data of the power line can be obtained with high precision and in real time. This real-time monitoring capability ensures the dynamic grasp of the operating status of the power line, which helps to discover and solve problems in a timely manner. The acquisition of real-time voltage data enables the system to respond quickly when the voltage is abnormal, take measures in time, and reduce potential losses and risks. The real-time voltage data of the power line is detected for power transportation fluctuations, and the power line transportation voltage fluctuation data is generated, and the waveform conversion is performed to generate the power line transportation voltage fluctuation curve. These data and curves can provide detailed voltage fluctuations and help technicians to conduct in-depth analysis. Voltage fluctuation detection can timely detect abnormal fluctuations in the power transportation process, and provide an accurate basis for subsequent voltage stability evaluation. Based on the power line transportation voltage fluctuation curve, the line transmission voltage stability assessment can generate detailed power line transmission voltage stability data. These assessment data can accurately reflect the operational stability of the power line and help decision makers formulate corresponding maintenance and optimization measures. Through the assessment of voltage stability, potential voltage fluctuation problems can be identified, preventive measures can be taken in advance, the probability of failure can be reduced, and the continuous and stable operation of the power system can be guaranteed.

[0022] Preferably, step S21 includes the following steps:

[0023] Step S221: using a power flow calculation method to perform power load flow analysis on the base station power line topology network to generate power line load flow data;

[0024] Step S222: comparing the power line load flow data with a preset power line load flow threshold, and when the power line load flow data is greater than or equal to the preset power line load flow threshold, dividing the corresponding power line into a high load area;

[0025] Step S223: Performing power initial node deployment on the base station power line topology network according to the high-load area to generate power line initial deployment nodes; performing node criticality index evaluation on the power line initial deployment nodes to generate power line critical node evaluation index data, wherein the node criticality index evaluation includes node degree centrality evaluation, betweenness centrality evaluation, and eigenvector centrality evaluation;

[0026] Step S224: Screen the power line key nodes of the initial deployment nodes of the power line through the power line key node evaluation index data to obtain the base station power line key nodes.

[0027] The present invention uses a power flow calculation method to analyze the power load flow of the base station power line topology network and generate power line load flow data. This process can fully understand the load flow in the power line and provide data support for the subsequent high-load area identification. The load flow data obtained by the power flow calculation has high accuracy and provides a reliable data basis for the subsequent load threshold comparison and key node screening. The power line load flow data is compared with the preset load flow threshold. When the data is greater than or equal to the threshold, it is divided into a high-load area. This process can effectively identify the high-load area in the power system and ensure that these key areas are more carefully monitored and managed. Identifying high-load areas helps prevent the risk of line overload, take corresponding measures in advance to balance and optimize the load, and reduce the probability of failure. According to the high-load area, the base station power line topology network is initially deployed, and the power line initial deployment node is generated. This step ensures the rationality of the node deployment and optimizes the monitoring and control strategy. The node key index evaluation is performed on the initial deployment node, including node degree centrality evaluation, betweenness centrality evaluation, and eigenvector centrality evaluation. These multi-dimensional evaluation indicators fully reflect the importance and influence of the node in the network, and provide a scientific basis for the key node screening. The initial deployment nodes are screened through key indicator data to obtain the key nodes of the base station power line. The screening process is based on multi-dimensional evaluation data to ensure the scientificity and accuracy of the screening results. The identified key nodes are the most important nodes in the power system. These nodes will be monitored and maintained to ensure the stable operation of the system.

[0028] Preferably, step S3 comprises the following steps:

[0029] Step S31: monitoring the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data;

[0030] Step S32: performing time series data cleaning on the power line power quality data to generate standard power quality data, wherein the standard power quality data includes power line transmission voltage waveform data and power line transmission current waveform data;

[0031] Step S33: performing spectrum signal conversion on the power line transmission voltage waveform data and the power line transmission current waveform data to generate power line spectrum data; performing harmonic distortion calculation on the power line spectrum data to obtain power line harmonic analysis data;

[0032] Step S34: performing waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; performing voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data;

[0033] Step S35: Use the comprehensive power quality assessment formula to conduct a comprehensive power quality assessment on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality assessment data.

[0034] The present invention can monitor the power quality of power lines in real time by monitoring the quality of power lines in real time, including the cleaning and standardization of transmission voltage and current waveform data, so as to timely discover potential problems. By converting the power line spectrum data and calculating the harmonic distortion, the harmonic situation in the power line can be comprehensively analyzed to help identify power quality problems. The standard power quality data is detected by using the power transmission waveform distortion rate, and the voltage event is detected by using the power transmission waveform distortion rate, which helps to accurately judge abnormal conditions in the power line. The comprehensive power quality evaluation formula is used to comprehensively evaluate various data, thereby generating power line transmission quality evaluation data, providing comprehensive evaluation and guidance for power line operation.

[0035] Preferably, detecting voltage events through power line harmonic analysis data and power transmission waveform distortion rate includes:

[0036] The voltage drop is identified on the power line transmission voltage waveform data by the power transmission waveform distortion rate to obtain the power line transmission voltage drop value; the power line transmission voltage drop value is calculated based on the preset rated drop voltage to obtain the power line voltage drop excess value;

[0037] According to the power line voltage drop excess value, the power line transmission voltage waveform data is analyzed for drop duration, and the power line transmission voltage drop time period data is generated; the power line voltage drop excess value and the power line transmission voltage drop time period data are used to determine the voltage sag time, and the voltage sag event data is generated;

[0038] Based on the IEC61000-4-15 standard flicker measurement method, the standard power quality data is used to calculate the flicker value using the power transmission waveform distortion rate to obtain the voltage short-time flicker value and the voltage long-time flicker value; the voltage flicker event analysis is performed based on the voltage short-time flicker value and the voltage long-time flicker value to generate voltage flicker event data;

[0039] The voltage sag event data and the voltage flicker event data are integrated to generate power line transmission event data.

[0040] By analyzing the power line transmission voltage waveform data and the power transmission waveform distortion rate, the system can accurately detect the voltage drop and calculate the voltage drop excess value of the power line, which is helpful to timely discover the voltage drop problem and provide guarantee for the stable power supply of the power line. By analyzing the power line voltage drop excess value and drop duration cycle data, the system can identify the voltage sag event and generate corresponding event data, which is helpful for operators to understand the sag situation in the power line and take timely measures to avoid power interruption or damage to equipment. Based on the flicker measurement method of the IEC61000-4-15 standard, the system can calculate the short-term flicker value and long-term flicker value of the voltage, and perform corresponding event analysis, which is helpful to evaluate the voltage fluctuation situation in the power line and improve the power supply quality. The voltage sag event data and the voltage flicker event data are integrated to generate the power line transmission event data. Such integration can clearly understand the various event situations of the power line and help timely adjustment and maintenance.

[0041] Preferably, the comprehensive power quality evaluation formula in step S35 is as follows:

[0042] ;

[0043] In the formula, Expressed as a comprehensive quality assessment score, Represented as the power line at a point in time The voltage change value, Represented as the power line at a point in time The current change value, is the time point of the evaluation, is the length of the evaluation period, Expressed as The harmonic frequency, Expressed as The amplitude of the harmonics, Expressed as a comprehensive weight coefficient, Denotes the threshold value for quality assessment, Expressed as a correction factor for quality assessment.

[0044] The present invention constructs a comprehensive power quality evaluation formula, in which the harmonic analysis term By calculating the square root of the sum of the squares of the amplitudes of all harmonics and dividing it by the threshold , which is done to measure the degree of impact of harmonics on power quality. The presence of harmonics will cause waveform distortion of voltage and current, thus affecting the effective transmission of power. By incorporating harmonic analysis data into the evaluation, the problem of power quality can be considered more comprehensively. The waveform distortion rate term in the formula It measures the difference between the voltage and current waveforms, i.e. the waveform distortion rate. It is calculated by integrating the square of the difference between the voltage and current and dividing it by the correction factor , the stability of the voltage and current waveforms can be evaluated, helping to identify mismatches between voltage and current, as well as existing power quality issues. The transmission event data term in the formula The instantaneous rate of change of voltage, i.e. the slope of voltage, is taken into account to capture transmission events on the power line, such as sudden voltage fluctuations or interruptions. The voltage slope is integrated and divided by the correction factor , the stability and reliability of power lines can be evaluated. The comprehensive weight coefficient in the formula Used to adjust the relative importance of each item. The value of can be used to weight the harmonic analysis, waveform distortion rate, and transmission event data according to specific circumstances and needs, which allows the formula to be customized according to actual conditions to more accurately evaluate the quality of electric energy. When using the conventional electric energy comprehensive quality evaluation formula in the art, a comprehensive quality evaluation score can be obtained. By applying the electric energy comprehensive quality evaluation formula provided by the present invention, the comprehensive quality evaluation score can be calculated more accurately. By comprehensively considering the harmonic analysis data, waveform distortion rate, and transmission event data, this formula can provide a comprehensive electric energy quality assessment. The interaction between different parameters enables the evaluation to more comprehensively capture the quality problems of power lines, which helps to promptly discover and resolve potential power quality anomalies, thereby improving the stability and reliability of the power system.

[0045] Preferably, step S4 comprises the following steps:

[0046] Step S41: Acquire power line environment perception data;

[0047] Step S42: marking the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generating the initial abnormal node data of the base station power line;

[0048] Step S43: using the power line environment perception data to analyze the external environment impact on the initial abnormal node data of the base station power line, and generate power line abnormal external impact data; checking the operation status of the internal equipment of the power line on the initial abnormal node data of the base station power line, and generate power line abnormal internal impact data;

[0049] Step S44: Performing power line status evaluation on the power line abnormality external impact data and the power line abnormality internal impact data to generate a power line status evaluation index;

[0050] Step S45: constructing a power line maintenance plan according to the power line status evaluation index to obtain a power line maintenance plan to perform normal power transportation operations on the power line.

[0051] The present invention uses power line transmission voltage stability data and quality assessment data to mark initial abnormal nodes of base station power lines, which helps to quickly identify nodes with problems and provide direction for subsequent analysis and processing. By analyzing power line environmental perception data, the abnormal nodes of the base station power line are analyzed for external environmental impacts and internal equipment operating status, which helps to fully understand the causes of the formation of abnormal nodes, so as to take targeted measures. Comprehensively considering the external and internal impact data of abnormal nodes, the state of the power line is evaluated, and a power line state assessment index is generated, which helps to quantify the degree of abnormality of the power line and provide a basis for subsequent maintenance plans. According to the power line state assessment index, a corresponding maintenance plan is formulated to perform normal power transportation operations of the power line. Such a plan can efficiently solve the abnormal situation of the power line and ensure the stability and reliability of power transmission.

[0052] Preferably, performing power line status assessment on the power line abnormality external impact data and the power line abnormality internal impact data comprises:

[0053] Integrate the data sets of external impact data of power line anomalies and internal impact data of power line anomalies to generate power line anomaly impact data; divide the data sets of power line anomaly impact data to obtain model training sets and model test sets;

[0054] The model training set is trained through the convolutional neural network algorithm to generate a power line state training model; the power line state training model is iterated based on the model test set to generate a power line state assessment model; the power line abnormal impact data is imported into the power line state assessment model to perform a comprehensive power line state assessment and generate a power line state assessment index.

[0055] The present invention ensures full utilization of data and verification of model validity by integrating abnormal external and internal impact data into a data set and dividing it into a model training set and a test set. The model training set is trained using a convolutional neural network algorithm to generate a power line state training model, and the model test set is iteratively tested to generate an evaluation model. This method can fully mine the features in the data, and the model can be continuously optimized through test iterations to improve the accuracy and stability of the evaluation. The abnormal impact data of the power line is imported into the evaluation model, a comprehensive evaluation is performed, and a power line state evaluation index is generated. Such a comprehensive evaluation can comprehensively consider the abnormal external and internal influencing factors and provide accurate evaluation indicators for the state of the power line. The use of the CNN algorithm for state evaluation can realize an automated evaluation process, and the process from data input to result output can achieve rapid response, which helps to timely discover abnormal conditions of the power line and take corresponding countermeasures.

[0056] In this specification, a power line state assessment system based on artificial intelligence is provided, which is used to execute the power line state assessment method based on artificial intelligence described above, and the power line state assessment system based on artificial intelligence includes:

[0057] The power grid topology module is used to obtain the power monitoring data of the base station; analyze the power transmission path of the base station power monitoring data to generate the power transmission path of the base station; perform the power line network topology through the power transmission path of the base station, thereby generating the power line topology network of the base station;

[0058] The voltage stability assessment module is used to screen the key nodes of the power line topology network of the base station power line to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data;

[0059] The power quality assessment module is used to monitor the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate the power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data;

[0060] The power line status assessment module is used to obtain power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

[0061] The beneficial effect of the present invention is that by acquiring base station power monitoring data and conducting power transportation path analysis, the transportation path and topological structure of the power line can be fully understood, providing a basis for subsequent monitoring and analysis. By using voltage sensors to collect real-time voltage at key nodes and combining line transmission voltage stability assessment, the operating status of the power line can be monitored in a timely manner to ensure voltage stability. Power line quality monitoring equipment is used to monitor key nodes to generate power quality data, and a comprehensive evaluation of power quality is performed by comprehensively considering harmonic analysis, waveform distortion rate and transmission event data to provide a comprehensive evaluation of the quality of the power line. Obtaining power line environmental perception data and constructing a power line maintenance plan based on the power line status assessment index helps to accurately assess the status of the power line on the basis of considering environmental factors, and formulate corresponding maintenance plans to ensure the normal operation of the power line. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of the steps of a power line condition assessment method based on artificial intelligence;

[0063] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0064] Figure 3 for Figure 2 Detailed implementation steps of step S21;

[0065] Figure 4 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0066] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0067] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0068] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0069] It should be understood that although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, and the term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0070] To achieve this, please refer to Figures 1 to 4 , a power line status assessment method based on artificial intelligence, the method comprising the following steps:

[0071] Step S1: acquiring base station power monitoring data; performing power transmission path analysis on the base station power monitoring data to generate the base station power transmission path; performing power line network topology through the base station power transmission path to generate the base station power line topology network;

[0072] Step S2: Screen the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data;

[0073] Step S3: Perform power line quality monitoring using power quality monitoring equipment according to key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data;

[0074] Step S4: Acquire power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

[0075] The present invention can monitor the operation status of the power line in real time by collecting voltage data and power quality data of key nodes of the base station power line in real time. This real-time monitoring capability ensures that it can respond quickly when an abnormality occurs, take repair measures in time, reduce power outages and failure time, and improve the stability and reliability of the power system. Through comprehensive analysis of data such as power line transmission voltage stability, harmonic distortion, waveform distortion, etc., potential fault nodes can be predicted in advance. This fault prediction and prevention capability helps power companies to carry out maintenance and repair in advance to avoid large-scale power outages and economic losses caused by sudden failures. Based on the power line state evaluation index generated by comprehensive evaluation, a scientific and efficient power line maintenance plan can be formulated. This maintenance plan can not only accurately repair specific problems and reduce unnecessary maintenance work and costs, but also ensure the continuous stability of power transportation. Through multi-dimensional data collection and analysis, a comprehensive comprehensive evaluation of power quality is carried out. Compared with the single indicator evaluation of traditional methods, this comprehensive evaluation method can more accurately reflect the actual operation status of the power line and provide more reliable data support for subsequent decision-making and optimization. The use of artificial intelligence algorithms to automatically analyze and process massive monitoring data reduces manual intervention and human errors, and improves the accuracy and efficiency of data processing. This improvement in the level of intelligence not only optimizes the process of power line status assessment, but also improves the operating efficiency of the entire power system. By acquiring power line environmental perception data, the impact of the external environment on the operation of the power line can be considered. This comprehensive environmental perception capability helps to more accurately assess the line status and formulate maintenance strategies, further improving the adaptability and reliability of the power system. Through real-time monitoring and evaluation of key nodes of power lines, the power transportation path can be optimized, power loss can be reduced, and power transmission efficiency can be improved. Therefore, the present invention improves the accuracy and comprehensiveness of power line status assessment by performing comprehensive data collection, multi-dimensional analysis, key node management and intelligent evaluation of power lines.

[0076] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of a power line status assessment method based on artificial intelligence of the present invention. In this example, the power line status assessment method based on artificial intelligence includes the following steps:

[0077] Step S1: acquiring base station power monitoring data; performing power transmission path analysis on the base station power monitoring data to generate the base station power transmission path; performing power line network topology through the base station power transmission path to generate the base station power line topology network;

[0078] In an embodiment of the present invention, power monitoring data is collected in real time through sensors and monitoring equipment installed on the base station, and these data include voltage, current, power, power consumption, etc. The collected data is transmitted to the data center for processing through a wireless communication network or a wired network. The collected raw data is cleaned to remove noise and outliers to ensure the accuracy and integrity of the data. According to the power consumption data of the base station, the power demand of each base station is analyzed to determine the priority and importance of power transportation. According to the geographic information system (GIS) and the existing power infrastructure, the power transportation path between the base stations is preliminarily set. The initial path is optimized by applying an optimization algorithm (such as the Dijkstra algorithm, etc.) to ensure the efficiency and reliability of power transportation. Using the results of path planning, a power transportation path map between base stations is drawn. The drawn path is verified to ensure the feasibility and safety of the path. Each base station and power substation is used as a network node. According to the power transportation path, the power lines between the nodes are connected to form a preliminary topological structure. Redundant lines are introduced to ensure that when a line fails, power can still be transported through other lines to improve the reliability of the network. By adjusting the network structure, the power load is evenly distributed on each line to avoid overloading of some lines. Use the network topology drawing tool to generate a complete power line topology network diagram.

[0079] Step S2: Screen the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data;

[0080] In the embodiment of the present invention, by calculating the degree of each node (the number of lines connected to the node), the node with high degree is a key node. The betweenness centrality of each node in the network (the number of shortest paths through the node) is calculated, and the node with high betweenness centrality is usually a key node. The impact of node removal on network connectivity is evaluated, and the node with a large impact on the network after removal is a key node. The results of node degree, betweenness centrality and connectivity analysis are integrated to screen out key nodes that are critical to network power transmission. The key nodes initially screened out are verified and adjusted through expert opinions and practical operation experience. The key nodes initially screened out are verified and adjusted through expert opinions and practical operation experience. The voltage data of the key nodes is collected in real time and transmitted to the data center through the network for storage and processing. Ensure the stability and reliability of the sensor and data transmission system to prevent data loss and transmission delay. Analyze the fluctuation of voltage data and calculate statistical indicators such as the mean, variance, and standard deviation of voltage. According to the power industry standards, calculate relevant indicators of voltage stability, such as voltage deviation and frequency deviation. Through time series analysis, the trend and periodicity of voltage changes are evaluated, and future voltage changes are predicted. Based on the results of various analyses, a data report on the stability of power line transmission voltage is generated. Improvement suggestions are made for unstable lines and nodes, such as adding redundant lines and replacing aging equipment.

[0081] Step S3: Perform power line quality monitoring using power quality monitoring equipment according to key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data;

[0082] In the embodiment of the present invention, by installing power quality monitoring equipment at key nodes (such as base stations A and B), it is ensured that the equipment can monitor the power quality parameters of the power line in real time, including voltage, current, frequency, power factor, etc. Configure the monitoring equipment, set the sampling frequency and data transmission mechanism, and collect power quality data in real time. Ensure the stable operation of the equipment and the reliable transmission of data, and transmit the collected data to the data center for storage and processing. Preprocess the collected power quality data to remove noise and abnormal values ​​to ensure the accuracy of the data. Use Fourier transform and other methods to perform harmonic analysis on the power quality data and calculate the amplitude and phase of each harmonic. Calculate the total harmonic distortion (THD) to evaluate the harmonic distortion of the power line. Define the standard power quality waveform according to the power system standard. Compare the actual collected power quality data with the standard waveform to detect the waveform distortion. Calculate the waveform distortion rate to evaluate the waveform distortion degree of the power quality. Define voltage events (such as voltage sag, voltage swell, short-term interruption, etc.) and corresponding detection thresholds. The waveform distortion rate and actual voltage data are used to detect the occurrence of voltage events. The detected voltage events are recorded and classified to generate power line transmission event data. The harmonic analysis data of the power line, the power transmission waveform distortion rate and the power line transmission event data are comprehensively analyzed. Based on the various data, the comprehensive evaluation indicators of power quality, such as the Power Quality Index (PQI), are calculated. For example, power quality monitoring equipment is installed at nodes A and B to collect power quality data once a second. The collected data include voltage, current, frequency, harmonic components, etc. The power quality data of nodes A and B are Fourier transformed to calculate the amplitude and phase of each harmonic. The total harmonic distortion (THD) of A and B is calculated. For example, the THD of A is 5% and the THD of B is 7%. The actual voltage waveforms of A and B are compared with the standard waveform to calculate the waveform distortion rate. For example, the waveform distortion rate of A is 3% and the waveform distortion rate of B is 4%. Detect voltage events at nodes A and B, such as voltage sags and swells. Record voltage event data, such as 3 voltage sags at node A and 5 voltage swells at node B. Comprehensively analyze the harmonic distortion, waveform distortion rate, and voltage event data of A and B. Calculate the power quality index (PQI), such as 85 for A and 80 for B. Generate a power quality assessment report and make improvement suggestions, such as adding a filter at node B to reduce harmonic distortion.

[0083] Step S4: Acquire power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

[0084] In an embodiment of the present invention, environmental parameters such as ambient temperature, humidity, wind speed, and rainfall are monitored by installing environmental perception sensors at key nodes of power lines and key locations along the lines. Environmental perception data is collected in real time and transmitted to a data center through a wireless or wired network for storage and processing. Power line transmission voltage stability data, power line transmission quality assessment data, and environmental perception data are integrated. Based on the integrated data, data analysis and machine learning algorithms (such as anomaly detection algorithms) are applied to perform anomaly detection on nodes in the power line. The detected initial abnormal nodes are marked to generate initial abnormal node data of the base station power line. A power line status assessment model is constructed, comprehensively considering voltage stability, quality assessment, environmental factors, and historical fault data. Based on the initial abnormal node data, the status assessment index (such as health index or risk index) of each node is calculated to quantify the health status of the node. An overall status assessment report of the power line is generated, indicating high-risk areas and nodes that need to be focused on. A detailed power line maintenance plan is formulated based on the status assessment index and report. It includes priority nodes for maintenance, required maintenance measures (such as equipment replacement, line maintenance, obstacle removal, etc.), required resources, and time arrangements. Apply optimization algorithms (such as genetic algorithms, simulated annealing algorithms, etc.) to optimize maintenance plans to ensure efficient use of maintenance resources and minimize system downtime. Implement maintenance plans, monitor the maintenance process in real time and record data to ensure maintenance quality and progress. After the maintenance is completed, re-evaluate the power line status, verify the maintenance effect, and update the status assessment data and model.

[0085] Preferably, step S1 comprises the following steps:

[0086] Step S11: Obtaining base station power monitoring data;

[0087] Step S12: Analyze the power transmission path of the base station power monitoring data to generate the base station power transmission path;

[0088] Step S13: confirming the power transmission line through the base station power transmission path to obtain the base station power transmission line;

[0089] Step S14: Perform power line network topology according to the base station power transmission line, thereby generating a base station power line topology network.

[0090] In an embodiment of the present invention, by installing power monitoring equipment (such as electric energy meters, voltmeters, ammeters, etc.) at the base station, power parameters including voltage, current, power and power consumption are monitored in real time. The equipment should have data storage and transmission functions to transmit the collected data to the data center. The collected data is transmitted to the data center through a wireless network or a wired network to ensure the timeliness and integrity of data transmission. A database is established in the data center to store and manage the collected power monitoring data to ensure the security and accessibility of the data. The collected raw data is cleaned to remove noise and outliers to ensure the accuracy of the data. According to the power consumption data of the base station, the power demand of each base station is analyzed to determine the priority and importance of power transportation. The power transportation path between base stations is preliminarily set using the geographic information system (GIS) and the existing power infrastructure data. The initial path is optimized by applying an optimization algorithm (such as the Dijkstra algorithm, etc.) to ensure the efficiency and reliability of the power transportation path. According to the path planning results, a base station power transportation path map is generated, and the path is verified to ensure feasibility and safety. According to the power transportation path, the power transportation line between base stations is confirmed. The line is surveyed and confirmed on site to ensure the actual feasibility of the path. According to the results of the on-site survey, the power transmission lines are optimized and adjusted to ensure the stability and efficiency of the lines. The final confirmed power transmission lines are recorded as the basis for the subsequent topological network generation. Base stations, power substations and other important equipment are used as network nodes. According to the confirmed power transmission lines, the power lines between the nodes are connected to form a preliminary topological structure. Redundant lines are introduced to ensure that when a line fails, power can still be transported through other lines to improve the reliability of the network. Through load balancing, the network structure is adjusted to evenly distribute the power load on each line to avoid overloading of some lines. Use the network topology drawing tool to generate a complete power line topological network diagram. Verify and optimize the topological diagram to ensure its accuracy and practicality. More specifically, power monitoring equipment is installed at base stations A, B and C to collect voltage, current and power data every minute, and transmit the data to the data center through the wireless network. A database is established in the data center to store the power monitoring data of A, B and C. Analyze the power demand of A, B and C, and determine the power transportation priority of S to A, S to B, and S to C. Use GIS data and optimization algorithms to plan the power transportation path from S to A, B, and C and generate a path map. Confirm the power transportation line from S to A, B, and C. After the on-site survey, optimize and adjust the line from S to A to ensure practical feasibility. Define S, A, B, and C as network nodes. Connect S to A, S to B, and S to C, and add redundant lines A to B and B to C to generate a power line topology network diagram and verify it.

[0091] Preferably, step S2 comprises the following steps:

[0092] Step S21: Screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station;

[0093] Step S22: using voltage sensors to collect real-time voltage data of power line transportation at key nodes of the base station power line, thereby generating real-time voltage data of the base station power line;

[0094] Step S23: performing power transmission fluctuation detection on the real-time voltage data of the power line to generate power line transmission voltage fluctuation data; performing waveform conversion on the power line transmission voltage fluctuation data to generate a power line transmission voltage fluctuation curve;

[0095] Step S24: Performing a line transmission voltage stability assessment based on the power line transmission voltage fluctuation curve to generate power line transmission voltage stability data.

[0096] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0097] Step S21: Screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station;

[0098] In an embodiment of the present invention, the base station power line topology network diagram generated by step S14 includes all base station nodes, power substation nodes and their connecting lines. Collect relevant data of the node, including the power load (power consumption) of the node, the number of connected lines, the distance and importance to other nodes, etc. Calculate the degree of each node, that is, the number of lines directly connected to the node. The higher the degree, the more important the node is in the network. Calculate the betweenness centrality of each node, that is, the number of shortest paths passing through the node. Nodes with higher betweenness centrality usually have a more important intermediary role in the network. Evaluate the connectivity of the node, that is, the impact of the existence of the node on the overall connectivity of the network. After the removal of nodes with high connectivity, it will cause network segmentation or seriously affect the connectivity of the network. Evaluate the power load of the node, that is, the power consumption or power supply demand of the node. Nodes with important loads are generally key nodes. Calculate the degree of each node and sort them according to the degree. Use network analysis tools (such as NetworkX, etc.) to calculate the betweenness centrality of each node and sort them. Conduct a connectivity assessment, simulate the impact of node removal on network connectivity, and identify key nodes with high connectivity. Consider degree, betweenness centrality, connectivity, and power load importance, score each node, and assess its criticality. Set a threshold for key nodes based on the comprehensive assessment score. Nodes that exceed the threshold are identified as key nodes. Verify the key nodes that have been initially screened to ensure their importance and feasibility in actual operation. Combine expert opinions and actual operation experience to make final confirmation and adjustments to the key node list. Generate a final list of key nodes for base station power lines, and record the relevant information and evaluation results of each key node.

[0099] Step S22: using voltage sensors to collect real-time voltage data of power line transportation at key nodes of the base station power line, thereby generating real-time voltage data of the base station power line;

[0100] In an embodiment of the present invention, the installation position of the voltage sensor is determined by the key nodes (such as S, A, and C) selected according to step S21. A high-precision voltage sensor suitable for base station power line monitoring is selected to ensure that it can meet the real-time monitoring requirements and has a data transmission function. The voltage sensor is installed on the power line of the key node to ensure good contact and stable installation between the sensor and the line. The installed sensor is debugged to ensure its normal operation and accurate data collection. The sampling frequency and data recording interval of the voltage sensor are set. For example, it is set to collect voltage data once per second to ensure the real-time nature of the data. The collected voltage data is transmitted to the data center in real time through a wireless network (such as Wi-Fi, LoRa, NB-IoT, etc.) or a wired network (such as optical fiber, Ethernet, etc.). Ensure that the data transmission of the sensor is stable to avoid data loss and transmission delay. Establish a special database in the data center for storing and managing real-time voltage data. Back up data regularly to ensure the security and integrity of the data. Preprocess the voltage data transmitted to the data center in real time to remove noise and outliers to ensure the accuracy of the data. According to the processed voltage data, a real-time voltage curve of each key node is generated to display the voltage change.

[0101] Step S23: performing power transmission fluctuation detection on the real-time voltage data of the power line to generate power line transmission voltage fluctuation data; performing waveform conversion on the power line transmission voltage fluctuation data to generate a power line transmission voltage fluctuation curve;

[0102] In an embodiment of the present invention, by selecting a suitable fluctuation detection algorithm, such as fast Fourier transform (FFT), wavelet transform, sliding window statistical analysis, etc., the real-time voltage data is converted to the frequency domain, the high-frequency components therein are identified, and the frequency and amplitude of the voltage fluctuation are detected. The voltage data is multi-scaled decomposed using wavelet transform to detect the voltage fluctuation at different time scales. A sliding window is set, and the mean, variance and standard deviation of the voltage are calculated in each window to detect the amplitude and frequency of the voltage fluctuation. According to the fluctuation detection result, the power line transportation voltage fluctuation data is generated, including information such as the amplitude, frequency and duration of the fluctuation. The fluctuation detection data is converted to generate standard voltage fluctuation waveform data. For example, the FFT result is inversely transformed to restore the time domain waveform; the wavelet transform result is inversely transformed to reconstruct the original waveform. The fluctuation waveform data is used to generate the power line transportation voltage fluctuation curve to show the change of voltage over time. A graphical tool (such as Matplotlib, etc.) is used to draw the fluctuation curve to display information such as the amplitude, frequency and phase of the fluctuation. The generated voltage fluctuation data and fluctuation curves are analyzed in detail to identify potential power transportation problems, such as instantaneous voltage drops and excessive voltage fluctuations.

[0103] Step S24: Performing a line transmission voltage stability assessment based on the power line transmission voltage fluctuation curve to generate power line transmission voltage stability data.

[0104] In the embodiment of the present invention, by calculating the deviation between the actual voltage value and the rated value, the smaller the deviation, the more stable the voltage. Evaluate the rate of change of voltage over time, the smaller the fluctuation rate, the more stable the voltage. Determine the range between the maximum and minimum values ​​of voltage fluctuation, the smaller the range, the more stable the voltage. Monitor the instantaneous changes of voltage, such as the frequency and amplitude of voltage sag or swell. Combined with the above indicators, calculate a comprehensive voltage stability index to quantify the overall stability of the voltage. Further process the voltage fluctuation curve data generated in step S23 to remove outliers and noise to ensure the accuracy of the data. Calculate the voltage deviation at each time point, the formula is: voltage deviation = | actual voltage - rated voltage | / rated voltage × 100%; use sliding window technology to calculate the voltage fluctuation rate in each window, the formula is: voltage fluctuation rate = max (voltage in window) - min (voltage in window) / average voltage in window × 100%; count the maximum and minimum values ​​of voltage fluctuations, and calculate the range of variation. Use high-frequency sampling data to monitor the instantaneous changes of voltage and record sudden drops or swells. Based on the above indicators, the comprehensive voltage stability index is calculated by weighted average or other methods. A voltage stability assessment model is constructed to conduct a comprehensive assessment of voltage stability by combining voltage deviation, voltage fluctuation rate, voltage change range and instantaneous voltage change. Based on the assessment model, power line transmission voltage stability data is generated, including voltage stability scores for each time period and overall stability assessment results.

[0105] Preferably, step S21 includes the following steps:

[0106] Step S221: using a power flow calculation method to perform power load flow analysis on the base station power line topology network to generate power line load flow data;

[0107] Step S222: comparing the power line load flow data with a preset power line load flow threshold, and when the power line load flow data is greater than or equal to the preset power line load flow threshold, dividing the corresponding power line into a high load area;

[0108] Step S223: Performing power initial node deployment on the base station power line topology network according to the high-load area to generate power line initial deployment nodes; performing node criticality index evaluation on the power line initial deployment nodes to generate power line critical node evaluation index data, wherein the node criticality index evaluation includes node degree centrality evaluation, betweenness centrality evaluation, and eigenvector centrality evaluation;

[0109] Step S224: Screen the power line key nodes of the initial deployment nodes of the power line through the power line key node evaluation index data to obtain the base station power line key nodes.

[0110] As an example of the present invention, refer to Figure 3 As shown, in this example, step S21 includes:

[0111] Step S221: using a power flow calculation method to perform power load flow analysis on the base station power line topology network to generate power line load flow data;

[0112] In the embodiment of the present invention, the voltage level, power demand and power generation capacity of each node are obtained through the base station power line topology network data generated in step S14, including node information, line connection information, transformer location, load location, etc.

[0113] Obtain the impedance parameters (resistance, reactance, etc.) of each line. Select a suitable power flow calculation method (such as the Newton-Raphson method), solve the power flow equation, obtain the voltage amplitude and phase angle of each node, and the active power and reactive power of each line. The power flow calculation method can use, for example, the DC power flow method, the AC power flow method, the Newton-Raphson method, and the Gauss-Seidel method to set the initial voltage amplitude and phase angle. Perform iterative solution according to the power flow equation, update the voltage amplitude and phase angle until the convergence condition is met. Verify the rationality of the calculation results and check whether the power balance and voltage deviation are within the allowable range. Based on the power flow calculation results, generate the load flow data of the power line, including the voltage amplitude and phase angle of each node, and the active power and reactive power flow of each line.

[0114] Step S222: comparing the power line load flow data with a preset power line load flow threshold, and when the power line load flow data is greater than or equal to the preset power line load flow threshold, dividing the corresponding power line into a high load area;

[0115] In an embodiment of the present invention, the load flow data of the power line generated by using step S221 includes the voltage amplitude and phase angle of each node, and the active power and reactive power flow of each line. According to the design capacity and safety index of the power line, a preset load flow threshold is set. For example, the maximum allowable value of the active power or reactive power of the line is set. Each power line is traversed and its load flow data is compared with the preset threshold. If the active power or reactive power flow exceeds the threshold, the power line is marked as a high-load area. The power line exceeding the threshold is marked as a high-load area, and its node and line information is recorded. The information of the high-load area is output to a report or a data table, including the node and line names, and the specific parameters of the overload.

[0116] Step S223: Performing power initial node deployment on the base station power line topology network according to the high-load area to generate power line initial deployment nodes; performing node criticality index evaluation on the power line initial deployment nodes to generate power line critical node evaluation index data, wherein the node criticality index evaluation includes node degree centrality evaluation, betweenness centrality evaluation, and eigenvector centrality evaluation;

[0117] In an embodiment of the present invention, the high-load area information identified in step S222 is used. A node deployment strategy is formulated according to the location and power demand of the high-load area. It is preferred to deploy the initial power node near the high-load area or in the potential load growth area. The initial power node is deployed at a suitable location near the high-load area to relieve load pressure and improve power transmission efficiency. The key indicators of the node reflect its importance and influence in the power system. Common indicators include node degree centrality, betweenness centrality and eigenvector centrality. Calculate the degree centrality of each node, that is, the number of direct connections to other nodes. Calculate the betweenness centrality of each node, that is, the number of shortest paths passing through the node. Calculate the eigenvector centrality of each node, that is, the importance of the node in the power network. The calculated indicators are normalized to ensure the comparability and weight consistency between different indicators. Integrate the key indicator data of each node to generate the evaluation indicator data of the key nodes of the power line.

[0118] Step S224: Screen the power line key nodes of the initial deployment nodes of the power line through the power line key node evaluation index data to obtain the base station power line key nodes.

[0119] In the embodiment of the present invention, by determining the criteria for screening key nodes, screening is performed specifically according to the absolute value or relative value of the indicator data. According to the preset screening criteria, nodes with higher indicators such as degree centrality, betweenness centrality, and eigenvector centrality are selected as key nodes of the power line. The screened node set is used as the key node set of the base station power line. More specifically, for example, the nodes ranked in the top 20% of degree centrality, betweenness centrality, and eigenvector centrality are selected as key nodes.

[0120] Preferably, step S3 comprises the following steps:

[0121] Step S31: monitoring the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data;

[0122] Step S32: performing time series data cleaning on the power line power quality data to generate standard power quality data, wherein the standard power quality data includes power line transmission voltage waveform data and power line transmission current waveform data;

[0123] Step S33: performing spectrum signal conversion on the power line transmission voltage waveform data and the power line transmission current waveform data to generate power line spectrum data; performing harmonic distortion calculation on the power line spectrum data to obtain power line harmonic analysis data;

[0124] Step S34: performing waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; performing voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data;

[0125] Step S35: Use the comprehensive power quality assessment formula to conduct a comprehensive power quality assessment on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality assessment data.

[0126] As an example of the present invention, refer to Figure 4 As shown, in this example, step S3 includes:

[0127] Step S31: monitoring the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data;

[0128] In an embodiment of the present invention, appropriate power quality monitoring equipment is selected according to the characteristics of the power line and the monitoring requirements. Including voltage / current recorders, power quality analyzers, power quality analyzers, etc. The power quality monitoring equipment is installed near the key nodes of the base station power line to ensure that the power quality of the power line can be effectively monitored. The power line is monitored in real time using the power quality monitoring equipment to collect relevant data such as voltage, current, and power. The data collection cycle is set according to actual needs, usually from a few seconds to a few minutes. The collected power quality data is stored in a database or data center to ensure the security and reliability of the data. The collected power quality data is analyzed, including analysis of harmonics, flicker, instantaneous voltage changes, etc. The data is processed using power quality analysis software or tools to extract relevant features and indicators. Identify abnormal conditions in the power line, such as excessive harmonics, voltage fluctuations, flicker, etc., as well as faults or abnormal events related to power quality.

[0129] Step S32: performing time series data cleaning on the power line power quality data to generate standard power quality data, wherein the standard power quality data includes power line transmission voltage waveform data and power line transmission current waveform data;

[0130] In an embodiment of the present invention, the power line power quality data obtained by monitoring in step S31 is used, including voltage waveform data and current waveform data. The original data is preprocessed, including missing value processing, outlier detection and denoising operations to ensure data quality. For missing data points, interpolation processing is performed to fill the missing values ​​to ensure the integrity of the data. The data is filtered to remove noise and interference to improve the accuracy and stability of the data. The voltage waveform data is extracted, including features such as amplitude, frequency, and phase, and standardized. The current waveform data is extracted, including features such as amplitude, frequency, and phase, and standardized. The voltage waveform data and the current waveform data after time series data cleaning and processing are merged to generate standard power quality data.

[0131] Step S33: performing spectrum signal conversion on the power line transmission voltage waveform data and the power line transmission current waveform data to generate power line spectrum data; performing harmonic distortion calculation on the power line spectrum data to obtain power line harmonic analysis data;

[0132] In an embodiment of the present invention, the power line transmission voltage waveform data and the power line transmission current waveform data are converted from the time domain to the frequency domain by using Fourier transform or fast Fourier transform (FFT). The frequency domain signal is subjected to spectrum analysis to obtain the amplitude and phase information of the frequency component for subsequent harmonic distortion calculation. Harmonic components in the spectrum data are identified and extracted, including higher-order harmonic components such as the second harmonic and the third harmonic. Indicators such as the amplitude, phase and distortion rate of each harmonic component are calculated as the result of the power line harmonic analysis data. The calculated power line harmonic analysis data is stored in a database or a data file for subsequent analysis and application.

[0133] Step S34: performing waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; performing voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data;

[0134] In the embodiment of the present invention, the distortion components in the voltage and current waveforms are identified by using the power line harmonic analysis data calculated in step S33. The distortion rates of the voltage and current waveforms are calculated. Commonly used indicators include total harmonic distortion (THD) and odd harmonic distortion. A threshold value of the distortion rate is set. When the distortion rate of the voltage or current waveform exceeds the threshold, it is considered that a voltage event has occurred. According to the duration of the voltage event, amplitude change and other characteristics, the event is classified into short-term flicker, long-term flicker, instantaneous overvoltage, etc.

[0135] Step S35: Use the comprehensive power quality assessment formula to conduct a comprehensive power quality assessment on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality assessment data.

[0136] In the embodiment of the present invention, an index system for comprehensive power quality assessment is designed, including indicators such as harmonic distortion, voltage events, and current waveform distortion rate. According to the index system, a mathematical model and formula for comprehensive power quality assessment are formulated, and specifically methods such as weighted summation or multivariate linear regression are adopted. Each indicator is normalized so that each indicator can be compared at the same level. According to the established comprehensive power quality assessment formula, the weight and score of each indicator are calculated to obtain a comprehensive assessment result of the power line.

[0137] Preferably, detecting voltage events through power line harmonic analysis data and power transmission waveform distortion rate includes:

[0138] The voltage drop is identified on the power line transmission voltage waveform data by the power transmission waveform distortion rate to obtain the power line transmission voltage drop value; the power line transmission voltage drop value is calculated based on the preset rated drop voltage to obtain the power line voltage drop excess value;

[0139] According to the power line voltage drop excess value, the power line transmission voltage waveform data is analyzed for drop duration, and the power line transmission voltage drop time period data is generated; the power line voltage drop excess value and the power line transmission voltage drop time period data are used to determine the voltage sag time, and the voltage sag event data is generated;

[0140] Based on the IEC61000-4-15 standard flicker measurement method, the standard power quality data is used to calculate the flicker value using the power transmission waveform distortion rate to obtain the voltage short-time flicker value and the voltage long-time flicker value; the voltage flicker event analysis is performed based on the voltage short-time flicker value and the voltage long-time flicker value to generate voltage flicker event data;

[0141] The voltage sag event data and the voltage flicker event data are integrated to generate power line transmission event data.

[0142] In an embodiment of the present invention, a voltage drop event is identified by analyzing the power line transmission voltage waveform data using the power transmission waveform distortion rate. According to the identified voltage drop event, the drop value of the power line transmission voltage is calculated. Based on the preset rated drop voltage, a drop voltage threshold is set. The calculated voltage drop value is compared with the rated drop voltage to determine whether a voltage drop over-value event occurs. The duration of the identified voltage drop event is analyzed to determine the duration period of the drop event. The voltage drop over-value event and the drop duration data are used to determine whether a voltage sag event occurs. The flicker measurement method in the IEC61000-4-15 standard is used to calculate the flicker value of the standard power quality data using the power transmission waveform distortion rate. The voltage short-time flicker value and the voltage long-time flicker value are calculated. According to the calculated voltage short-time flicker value and the voltage long-time flicker value, it is determined whether a voltage flicker event occurs. The identified voltage sag event data and the voltage flicker event data are integrated to generate power line transmission event data.

[0143] Preferably, the comprehensive power quality evaluation formula in step S35 is as follows:

[0144] ;

[0145] In the formula, Expressed as a comprehensive quality assessment score, Represented as the power line at a point in time The voltage change value, Represented as the power line at a point in time The current change value, is the time point of the evaluation, is the length of the evaluation period, Expressed as The harmonic frequency, Expressed as The amplitude of the harmonics, Expressed as a comprehensive weight coefficient, Denotes the threshold value for quality assessment, Expressed as a correction factor for quality assessment.

[0146] The present invention constructs a comprehensive power quality evaluation formula, in which the harmonic analysis term By calculating the square root of the sum of the squares of the amplitudes of all harmonics and dividing it by the threshold , which is done to measure the degree of impact of harmonics on power quality. The presence of harmonics will cause waveform distortion of voltage and current, thus affecting the effective transmission of power. By incorporating harmonic analysis data into the evaluation, the problem of power quality can be considered more comprehensively. The waveform distortion rate term in the formula It measures the difference between the voltage and current waveforms, i.e. the waveform distortion rate. It is calculated by integrating the square of the difference between the voltage and current and dividing it by the correction factor , the stability of the voltage and current waveforms can be evaluated, helping to identify mismatches between voltage and current, as well as existing power quality issues. The transmission event data term in the formula The instantaneous rate of change of voltage, i.e. the slope of voltage, is taken into account to capture transmission events on the power line, such as sudden voltage fluctuations or interruptions. The voltage slope is integrated and divided by the correction factor , the stability and reliability of power lines can be evaluated. The comprehensive weight coefficient in the formula Used to adjust the relative importance of each item. The value of can be used to weight the harmonic analysis, waveform distortion rate, and transmission event data according to specific circumstances and needs, which allows the formula to be customized according to actual conditions to more accurately evaluate the quality of electric energy. When using the conventional electric energy comprehensive quality evaluation formula in the art, a comprehensive quality evaluation score can be obtained. By applying the electric energy comprehensive quality evaluation formula provided by the present invention, the comprehensive quality evaluation score can be calculated more accurately. By comprehensively considering the harmonic analysis data, waveform distortion rate, and transmission event data, this formula can provide a comprehensive electric energy quality assessment. The interaction between different parameters enables the evaluation to more comprehensively capture the quality problems of power lines, which helps to promptly discover and resolve potential power quality anomalies, thereby improving the stability and reliability of the power system.

[0147] Preferably, step S4 comprises the following steps:

[0148] Step S41: Acquire power line environment perception data;

[0149] Step S42: marking the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generating the initial abnormal node data of the base station power line;

[0150] Step S43: using the power line environment perception data to analyze the external environment impact on the initial abnormal node data of the base station power line, and generate power line abnormal external impact data; checking the operation status of the internal equipment of the power line on the initial abnormal node data of the base station power line, and generate power line abnormal internal impact data;

[0151] Step S44: Performing power line status evaluation on the power line abnormality external impact data and the power line abnormality internal impact data to generate a power line status evaluation index;

[0152] Step S45: constructing a power line maintenance plan according to the power line status evaluation index to obtain a power line maintenance plan to perform normal power transportation operations on the power line.

[0153] In the embodiment of the present invention, various sensors or monitoring devices are used to collect perception data of the environment around the power line, including meteorological data, temperature, humidity, wind speed, etc. The initial abnormal nodes in the power line topology network are marked according to the power line transmission voltage stability data and the power line transmission quality assessment data. The power line environment perception data is used to analyze the impact of the external environment on the power line abnormality, and abnormal external impact data is generated. The marked abnormal nodes are checked for internal equipment operation status, internal equipment failures or abnormal conditions are identified, and abnormal internal impact data is generated. Combined with the external impact data and the internal impact data, the power line is evaluated for status, and a power line status assessment index is generated. According to the power line status assessment index, a maintenance plan for the power line is formulated, including repairing abnormal nodes, replacing faulty equipment, etc., to ensure the normal transportation of the power line, and more specifically, the meteorological data is used to analyze the impact of the external environment on the power line, such as strong winds, rainfall, etc. The marked abnormal nodes are inspected, the internal equipment operation status is checked, and equipment failures or abnormal conditions are discovered and recorded.

[0154] Preferably, performing power line status assessment on the power line abnormality external impact data and the power line abnormality internal impact data comprises:

[0155] Integrate the data sets of external impact data of power line anomalies and internal impact data of power line anomalies to generate power line anomaly impact data; divide the data sets of power line anomaly impact data to obtain model training sets and model test sets;

[0156] The model training set is trained through the convolutional neural network algorithm to generate a power line state training model; the power line state training model is iterated based on the model test set to generate a power line state assessment model; the power line abnormal impact data is imported into the power line state assessment model to perform a comprehensive power line state assessment and generate a power line state assessment index.

[0157] In an embodiment of the present invention, the data on the external impact of power line anomalies and the data on the internal impact of power line anomalies are integrated into a complete data set, which includes the external and internal impact factors of the anomalies. The integrated data set is divided into a model training set and a model test set, usually divided in a certain proportion to ensure the effectiveness and generalization ability of the training model. The model training set is trained using a convolutional neural network (CNN) algorithm to learn the characteristics and patterns of the power line anomaly impact data. Based on the trained model, the model is tested and iterated using the model test set, and the model parameters are adjusted to improve the performance and generalization ability of the model. The power line anomaly impact data is imported into the trained power line status assessment model. The model is used to analyze and process the anomaly impact data to generate a power line status assessment index that reflects the overall status and health of the power line.

[0158] In this specification, a power line state assessment system based on artificial intelligence is provided, which is used to execute the power line state assessment method based on artificial intelligence described above, and the power line state assessment system based on artificial intelligence includes:

[0159] The power grid topology module is used to obtain the power monitoring data of the base station; analyze the power transmission path of the base station power monitoring data to generate the power transmission path of the base station; perform the power line network topology through the power transmission path of the base station, thereby generating the power line topology network of the base station;

[0160] The voltage stability assessment module is used to screen the key nodes of the power line topology network of the base station power line to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data;

[0161] The power quality assessment module is used to monitor the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate the power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data;

[0162] The power line status assessment module is used to obtain power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

[0163] The beneficial effect of the present invention is that by acquiring base station power monitoring data and conducting power transportation path analysis, the transportation path and topological structure of the power line can be fully understood, providing a basis for subsequent monitoring and analysis. By using voltage sensors to collect real-time voltage at key nodes and combining line transmission voltage stability assessment, the operating status of the power line can be monitored in a timely manner to ensure voltage stability. Power line quality monitoring equipment is used to monitor key nodes to generate power quality data, and a comprehensive evaluation of power quality is performed by comprehensively considering harmonic analysis, waveform distortion rate and transmission event data to provide a comprehensive evaluation of the quality of the power line. Obtaining power line environmental perception data and constructing a power line maintenance plan based on the power line status assessment index helps to accurately assess the status of the power line on the basis of considering environmental factors, and formulate corresponding maintenance plans to ensure the normal operation of the power line.

[0164] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0165] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A power line status assessment method based on artificial intelligence, characterized in that: The following steps are involved: Step S1: Obtain base station power monitoring data; Perform power transmission path analysis on base station power monitoring data to generate base station power transmission path; The power line network topology is performed through the base station power transportation path, thereby generating a base station power line topology network; Step S2: Screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; Use voltage sensors to collect real-time voltage data of power lines at key nodes of base station power lines, thereby generating real-time voltage data of base station power lines; Conduct line transmission voltage stability assessment on real-time voltage data of power lines to generate power line transmission voltage stability data; Step S3: monitoring the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data; Calculate the harmonic distortion of the power line power quality data to obtain the power line harmonic analysis data; Perform waveform distortion detection on standard power quality data based on power line harmonic analysis data to generate power transmission waveform distortion rate; perform voltage event detection on standard power quality data based on power transmission waveform distortion rate to generate power line transmission event data; Conduct comprehensive power quality assessment on power line harmonic analysis data, power transmission waveform distortion rate and power line transmission event data, thereby generating power line transmission quality assessment data; Step S4: Acquire power line environment perception data; Marking the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generating the initial abnormal node data of the base station power line; Based on the initial abnormal node data of the base station power line, the power line status is evaluated to generate a power line status evaluation index; Constructing a power line maintenance plan according to the power line status evaluation index to obtain a power line maintenance plan to perform normal power transportation operations on the power line; Step S3 includes the following steps: Step S31: monitoring the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data; Step S32: performing time series data cleaning on the power line power quality data to generate standard power quality data, wherein the standard power quality data includes power line transmission voltage waveform data and power line transmission current waveform data; Step S33: performing spectrum signal conversion on the power line transmission voltage waveform data and the power line transmission current waveform data to generate power line spectrum data; performing harmonic distortion calculation on the power line spectrum data to obtain power line harmonic analysis data; Step S34: performing waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate a power transmission waveform distortion rate; performing voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; Step S35: using a comprehensive power quality evaluation formula to perform a comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate, and the power line transmission event data, thereby generating power line transmission quality evaluation data; Voltage event detection using power line harmonic analysis data and power transmission waveform distortion rate includes: The voltage drop is identified on the power line transmission voltage waveform data by the power transmission waveform distortion rate to obtain the power line transmission voltage drop value; the power line transmission voltage drop value is calculated based on the preset rated drop voltage to obtain the power line voltage drop excess value; According to the power line voltage drop excess value, the power line transmission voltage waveform data is analyzed for drop duration, and the power line transmission voltage drop time period data is generated; the power line voltage drop excess value and the power line transmission voltage drop time period data are used to determine the voltage sag time, and the voltage sag event data is generated; Based on the IEC61000-4-15 standard flicker measurement method, the standard power quality data is used to calculate the flicker value using the power transmission waveform distortion rate to obtain the voltage short-time flicker value and the voltage long-time flicker value; the voltage flicker event analysis is performed based on the voltage short-time flicker value and the voltage long-time flicker value to generate voltage flicker event data; Integrate the voltage sag event data and the voltage flicker event data to generate power line transmission event data; The comprehensive power quality evaluation formula in step S35 is as follows: ； In the formula, Expressed as a comprehensive quality assessment score, Represented as the power line at a point in time The voltage change value, Represented as the power line at a point in time The current change value, is the time point of the evaluation, is the length of the evaluation period, Expressed as The harmonic frequency, Expressed as The amplitude of the harmonics, Expressed as a comprehensive weight coefficient, Denotes the threshold value for quality assessment, Expressed as a correction factor for quality assessment.

2. The power line status assessment method based on artificial intelligence according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Acquire base station power monitoring data; Step S12: Analyze the power transmission path of the base station power monitoring data to generate the base station power transmission path; Step S13: confirming the power transmission line through the base station power transmission path to obtain the base station power transmission line; Step S14: Perform power line network topology according to the base station power transmission line, thereby generating a base station power line topology network.

3. The power line status assessment method based on artificial intelligence according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: Screening the key nodes of the power line of the base station power line topology network to obtain the key nodes of the power line of the base station; Step S22: using voltage sensors to collect real-time voltage data of power line transportation at key nodes of the base station power line, thereby generating real-time voltage data of the base station power line; Step S23: performing power transmission fluctuation detection on the real-time voltage data of the power line to generate power line transmission voltage fluctuation data; performing waveform conversion on the power line transmission voltage fluctuation data to generate a power line transmission voltage fluctuation curve; Step S24: Performing a line transmission voltage stability assessment based on the power line transmission voltage fluctuation curve to generate power line transmission voltage stability data.

4. The power line status assessment method based on artificial intelligence according to claim 3 is characterized in that: Step S21 includes the following steps: Step S221: using a power flow calculation method to perform power load flow analysis on the base station power line topology network to generate power line load flow data; Step S222: comparing the power line load flow data with a preset power line load flow threshold, and when the power line load flow data is greater than or equal to the preset power line load flow threshold, dividing the corresponding power line into a high load area; Step S223: Performing power initial node deployment on the base station power line topology network according to the high-load area to generate power line initial deployment nodes; performing node criticality index evaluation on the power line initial deployment nodes to generate power line critical node evaluation index data, wherein the node criticality index evaluation includes node degree centrality evaluation, betweenness centrality evaluation, and eigenvector centrality evaluation; Step S224: Screen the power line key nodes of the initial deployment nodes of the power line through the power line key node evaluation index data to obtain the base station power line key nodes.

5. The power line status assessment method based on artificial intelligence according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: Acquire power line environment perception data; Step S42: marking the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generating the initial abnormal node data of the base station power line; Step S43: using the power line environment perception data to analyze the external environment impact on the initial abnormal node data of the base station power line, and generate power line abnormal external impact data; checking the operation status of the internal equipment of the power line on the initial abnormal node data of the base station power line, and generate power line abnormal internal impact data; Step S44: Performing power line status evaluation on the power line abnormality external impact data and the power line abnormality internal impact data to generate a power line status evaluation index; Step S45: constructing a power line maintenance plan according to the power line status evaluation index to obtain a power line maintenance plan to perform normal power transportation operations on the power line.

6. The power line status assessment method based on artificial intelligence according to claim 5 is characterized in that: The power line status assessment based on the power line abnormal external impact data and the power line abnormal internal impact data includes: Integrate the data sets of external impact data of power line anomalies and internal impact data of power line anomalies to generate power line anomaly impact data; divide the data sets of power line anomaly impact data to obtain model training sets and model test sets; The model training set is trained through the convolutional neural network algorithm to generate a power line state training model; the power line state training model is iterated based on the model test set to generate a power line state assessment model; the power line abnormal impact data is imported into the power line state assessment model to perform a comprehensive power line state assessment and generate a power line state assessment index.

7. An artificial intelligence-based power line status assessment system, characterized in that: Used to execute the power line status assessment method based on artificial intelligence as claimed in claim 1, the power line status assessment system based on artificial intelligence comprises: The power grid topology module is used to obtain the power monitoring data of the base station; analyze the power transmission path of the base station power monitoring data to generate the power transmission path of the base station; perform the power line network topology through the power transmission path of the base station, thereby generating the power line topology network of the base station; The voltage stability assessment module is used to screen the key nodes of the power line topology network of the base station power line to obtain the key nodes of the power line of the base station; use the voltage sensor to collect the real-time voltage of the power line transportation of the key nodes of the power line of the base station, so as to generate the real-time voltage data of the power line of the base station; evaluate the line transmission voltage stability of the real-time voltage data of the power line, and generate the power line transmission voltage stability data; The power quality assessment module is used to monitor the power line quality using power quality monitoring equipment according to the key nodes of the base station power line to generate power line power quality data; perform harmonic distortion calculation on the power line power quality data to obtain power line harmonic analysis data; perform waveform distortion detection on the standard power quality data according to the power line harmonic analysis data to generate the power transmission waveform distortion rate; perform voltage event detection on the standard power quality data through the power transmission waveform distortion rate to generate power line transmission event data; perform comprehensive power quality evaluation on the power line harmonic analysis data, the power transmission waveform distortion rate and the power line transmission event data, thereby generating power line transmission quality evaluation data; The power line status assessment module is used to obtain power line environmental perception data; mark the initial abnormal nodes of the power line of the base station power line topology network according to the power line transmission voltage stability data and the power line transmission quality assessment data, and generate the initial abnormal node data of the base station power line; evaluate the power line status based on the initial abnormal node data of the base station power line, and generate a power line status assessment index; construct a power line maintenance plan according to the power line status assessment index, and obtain a power line maintenance plan to perform normal power transportation operations of the power line.

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