Power transmission line icing risk assessment system and assessment method

Abstract

The invention relates to the technical field of circuit operation and maintenance, in particular to a power transmission line icing risk assessment system and method, and the system comprises a data acquisition module, a data collection module, a spectrum analysis module, a data analysis module and a risk assessment module. Wherein the data analysis module determines an icing trend of each characteristic time period according to historical icing data and determines an icing characterization tendency in combination with a real-time temperature so as to determine whether to perform icing risk assessment; the risk assessment module controls the data acquisition module to start data acquisition, determines whether a preset distribution condition is met or not according to the frequency distribution condition, and determines a risk assessment state according to a judgment result whether the preset distribution condition is met or not and the power transmission efficiency so as to determine a subsequent deicing method; according to the method, the icing risk is effectively monitored and evaluated, the corresponding deicing method is provided, safe and stable operation of the power transmission line under the icing condition is guaranteed, the stability of a power system is improved, and adverse effects caused by icing disasters are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit operation and maintenance, and in particular to a transmission line icing risk assessment system and assessment method. Background Art

[0002] With the continuous development of the power system and the widespread laying of transmission lines, the safe and stable operation of transmission lines is of vital importance; however, in many areas, especially under specific climatic conditions such as high altitude, cold and humid, transmission lines face the serious threat of icing. Icing will not only greatly increase the weight of the conductors, causing the towers to bear huge vertical and unbalanced loads, causing structural damage such as tower tilting and collapse, but also change the electrical properties of the conductors, such as reducing the insulation performance of the insulator strings and aggravating the corona discharge phenomenon, thereby generating electromagnetic interference, affecting the transmission efficiency and the normal operation of surrounding communication equipment.

[0003] Traditional transmission line operation and maintenance methods often lack effective early warning and accurate risk assessment methods when facing icing problems, and it is difficult to scientifically select appropriate deicing methods based on actual icing conditions. This may not only lead to untimely and incomplete deicing, increase the probability of power outages and the operation risk of the power system, but also cause unnecessary waste of manpower, material resources and time. Therefore, there is an urgent need for a technical system that can comprehensively and accurately assess the risk of icing on transmission lines and reasonably guide deicing operations.

[0004] The prior art discloses a method for assessing the risk of icing of transmission lines (Chinese patent application number is 202410411473.4), which includes: Step 1: Set a time period, collect temperature data of the area where the target transmission line is located at each time point in the time period, and form a temperature data set; Step 2: Based on the temperature data set, calculate the probability of ice crystal formation at each time point; Step 3: Based on the precipitation data set, calculate the ice coverage thickness at each time point; Step 4: Based on the wind speed data set, calculate the wind speed influence factor at each time point; Step 5: Calculate the ice coverage risk index at each time point based on the wind speed influence factor at each time point; Step 6: Calculate the overall risk assessment for the entire time period based on the ice coverage risk index at each time point. The invention improves the accuracy of ice coverage risk assessment and intelligentizes decision support. It can be seen that the invention has the following problems:

[0005] The invention fails to effectively assess the risk of icing by combining historical icing data and current actual temperature, nor does it consider the issue of determining an effective de-icing method based on the risk of icing. Summary of the invention

[0006] To this end, the present invention provides a transmission line icing risk assessment system and assessment method, which are used to overcome the problem that the prior art fails to effectively assess the icing risk by combining historical icing data and the current actual temperature, and also fails to consider the problem of determining an effective de-icing method based on the icing risk. The system effectively ensures the safe and stable operation of the transmission line under icing conditions, improves the reliability and stability of the power system, and reduces the adverse effects of icing disasters.

[0007] To achieve the above objectives, on the one hand, the present invention provides a transmission line icing risk assessment system, comprising:

[0008] A data acquisition module, comprising a data search unit for acquiring historical ice coverage data of the power transmission line and a data networking unit for acquiring the real-time temperature of the location of the power transmission line, wherein the historical ice coverage data includes a historical ice coverage time period and a corresponding historical ice coverage thickness;

[0009] A data acquisition module, comprising a spectrum acquisition unit for receiving electromagnetic signals generated by corona discharge and an electric meter monitoring unit for collecting power transmission efficiency;

[0010] A spectrum analysis module, connected to the spectrum acquisition unit, for performing spectrum analysis on the electromagnetic signal to determine the frequency distribution of the electromagnetic interference generated by the corona discharge;

[0011] Wherein, the frequency distribution is the intensity distribution of electromagnetic waves at different frequencies;

[0012] A data analysis module, which is connected to the data acquisition module, is used to determine the icing trend of each characteristic time period based on the historical icing data, and determine the icing characterization tendency in combination with the real-time temperature to determine whether to perform icing risk assessment;

[0013] The icing trend includes a heavy icing trend and a light icing trend, and the icing characterization tendency includes an explicit icing tendency and a latent icing tendency;

[0014] a risk assessment module, which is respectively connected to the data acquisition module, the spectrum analysis module and the data analysis module, and is used to control the data acquisition module to start data acquisition according to whether icing risk assessment is performed, determine whether a preset distribution condition is met according to the frequency distribution, and determine a risk assessment state according to a determination result of whether the preset distribution condition is met and the power transmission efficiency to determine a subsequent deicing method;

[0015] Among them, the deicing methods include natural deicing, thermal deicing and mechanical deicing.

[0016] As a preferred technical solution for the transmission line icing risk assessment system, the spectrum analysis module performs spectrum analysis on the electromagnetic signal, and the spectrum analysis includes windowing and filtering processing, power spectrum and unit conversion, peak detection and frequency estimation.

[0017] As a preferred technical solution of the transmission line icing risk assessment system, the data analysis module determines the historical icing time period as a characteristic time period, and determines whether to merge the corresponding two characteristic time periods according to the time interval between two adjacent characteristic time periods, including:

[0018] If the time interval between two adjacent characteristic time periods is less than or equal to the preset time interval, it is determined that the corresponding two characteristic time periods are merged into one characteristic time period;

[0019] If the time interval between two adjacent characteristic time periods is greater than the preset time interval, it is determined not to merge the corresponding two characteristic time periods.

[0020] As a preferred technical solution for the transmission line icing risk assessment system, the data analysis module determines the icing trend of the corresponding characteristic time period according to the average icing thickness of each characteristic time period, including:

[0021] If the average ice thickness in the characteristic time period is greater than the preset ice thickness, the ice trend in the corresponding characteristic time period is determined to be a heavy ice trend;

[0022] If the average ice thickness in the characteristic time period is less than or equal to the preset ice thickness, it is determined that the ice trend in the corresponding characteristic time period is a light ice trend.

[0023] As a preferred technical solution of the transmission line icing risk assessment system, the data analysis module determines the icing characterization tendency according to the determination result of the icing trend at the current time and the real-time temperature, including:

[0024] If the time period corresponding to the current time is not a characteristic time period, the ice coverage tendency is no ice coverage tendency;

[0025] If the time period corresponding to the current time is a characteristic time period, the ice coverage tendency is determined according to the corresponding ice coverage trend, where:

[0026] If the icing tendency is a severe icing tendency, determining the icing characteristic tendency is a dominant icing tendency;

[0027] If the icing trend is a slight icing trend, the icing characterization tendency is determined in combination with the real-time temperature, wherein:

[0028] If the real-time temperature is lower than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a dominant ice-covering tendency;

[0029] If the real-time temperature is higher than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a latent ice-covering tendency;

[0030] The ice-covering temperature is determined according to the freezing point of water and the pressure at the location of the power transmission line.

[0031] As a preferred technical solution for the transmission line icing risk assessment system, the data analysis module determines to perform icing risk assessment based on the judgment result that the icing characterization tendency is a dominant icing tendency, so that the risk assessment module controls the data acquisition module to start data acquisition.

[0032] As a preferred technical solution of the transmission line icing risk assessment system, the risk assessment module determines whether the frequency distribution meets the preset distribution conditions according to the machine learning model;

[0033] The preset distribution condition includes that the frequency center value of the electromagnetic interference is within a preset range and the intensity on both sides of the frequency center value gradually decreases.

[0034] As a preferred technical solution for the transmission line icing risk assessment system, the risk assessment module determines the frequency at which the maximum frequency intensity is located as the frequency center value.

[0035] As a preferred technical solution of the transmission line icing risk assessment system, the risk assessment module determines the risk assessment state according to whether the preset distribution condition determination result and the transmission efficiency are met to determine the subsequent deicing method, including:

[0036] If the preset distribution condition is not met and the power transmission efficiency is greater than or equal to the preset power transmission efficiency, the risk assessment state is determined to be a low risk state, and the subsequent deicing method is determined to be a natural deicing method;

[0037] If the preset distribution condition is met or the power transmission efficiency is less than the preset power transmission efficiency, the risk assessment state is determined to be a medium risk state, and the subsequent deicing method is determined to be a mechanical deicing method;

[0038] If the preset distribution condition is met and the power transmission efficiency is less than the preset power transmission efficiency, the risk assessment state is determined to be a high-risk state, and the subsequent deicing method is determined to be a thermal deicing method and a mechanical deicing method.

[0039] On the other hand, the present invention also provides a method for assessing the risk of icing of a power transmission line, comprising:

[0040] Acquire historical icing data of the transmission line, and determine characteristic time periods and icing trends in each characteristic time period based on the historical icing data;

[0041] Determine the icing trend at the current time, and determine the icing characterization tendency in combination with the real-time temperature to determine whether to conduct an icing risk assessment;

[0042] Controlling the data acquisition module to start data acquisition according to the determination result of the icing risk assessment;

[0043] Performing spectrum analysis on the collected electromagnetic signals to determine the frequency distribution of the electromagnetic interference generated by the corona discharge to determine whether the preset distribution conditions are met;

[0044] Determining a risk assessment state according to a determination result of whether the preset distribution condition is met and the power transmission efficiency;

[0045] A subsequent de-icing method is determined according to the risk assessment status.

[0046] Compared with the prior art, the beneficial effects of the present invention are that the power transmission line icing risk assessment system provided by the present invention collects historical icing data and real-time temperature through a comprehensive and accurate data acquisition module, providing a solid foundation for subsequent analysis; uses a spectrum acquisition and analysis module to effectively monitor corona discharge electromagnetic interference to ensure the stability of the electromagnetic environment of the transmission line; relies on the data analysis module to accurately judge the icing trend and characterization tendency, and scientifically decides whether to conduct risk assessment; uses the risk assessment module to integrate various aspects of information, reasonably determines the risk assessment status and subsequent de-icing methods, thereby playing an important role in improving the accuracy of icing risk judgment, enhancing the operational stability of transmission lines, reducing the probability of failures, reducing de-icing costs and risks, and ensuring the continuity of power supply, and provides strong support for the safe and reliable operation of transmission lines in an environment prone to icing;

[0047] In particular, the data analysis module determines the historical icing time period as the characteristic time period, and compares the time interval of adjacent characteristic time periods with the preset time interval to decide whether to merge the characteristic time periods; on the one hand, it can accurately and effectively integrate the icing time periods to avoid the waste of resources and ineffective occupation of computing resources caused by frequent icing cycles in a short period of time, thereby improving the operating efficiency of the system; on the other hand, the reasonable setting of the preset time interval can not only enable the system to standby at the right time to save resources, but also reduce the number of power on and off times to protect the assessment system, thereby significantly optimizing the resource utilization, operating cost control and system stability maintenance of the entire transmission line icing risk assessment system, providing strong support for more efficient and accurate assessment of the icing risk of transmission lines, ensuring the safe and stable operation of transmission lines, reducing the risk of power failures caused by icing, and improving the reliability and sustainability of power supply. At the same time, it also provides a more scientific and reasonable basis for subsequent de-icing decisions.

[0048] In particular, the data analysis module accurately determines the icing trend based on the comparison between the average icing thickness in each characteristic time period and the preset icing thickness, and combines the real-time temperature and various environmental factors to clarify the icing characterization tendency, providing a key and accurate basis for the icing risk assessment of transmission lines;

[0049] In particular, the risk assessment module scientifically and accurately determines the risk assessment status through a comprehensive analysis of the preset distribution condition judgment results and transmission efficiency, and rationally selects the subsequent de-icing method based on this, providing an efficient and targeted solution to the problem of icing on transmission lines, effectively ensuring the safe and stable operation of transmission lines and the electromagnetic compatibility of the surrounding environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A connection diagram of a transmission line icing risk assessment system according to an embodiment of the present invention;

[0051] Figure 2 The following is a flowchart of the data analysis module according to an embodiment of the present invention;

[0052] Figure 3 is a workflow diagram of a risk assessment module according to an embodiment of the present invention;

[0053] Figure 4 This is a step diagram of a method for assessing icing risk of a power transmission line according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0056] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0057] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0058] See also Figure 1 As shown, it is a connection diagram of a transmission line icing risk assessment system according to an embodiment of the present invention. An embodiment of the present invention provides a transmission line icing risk assessment system, comprising:

[0059] A data acquisition module, comprising a data search unit for acquiring historical ice coverage data of the power transmission line and a data networking unit for acquiring the real-time temperature of the location of the power transmission line, wherein the historical ice coverage data includes a historical ice coverage time period and a corresponding historical ice coverage thickness;

[0060] A data acquisition module, comprising a spectrum acquisition unit for receiving electromagnetic signals generated by corona discharge and an electric meter monitoring unit for collecting power transmission efficiency;

[0061] A spectrum analysis module, connected to the spectrum acquisition unit, for performing spectrum analysis on the electromagnetic signal to determine the frequency distribution of the electromagnetic interference generated by the corona discharge;

[0062] In detail, based on the above embodiments, the spectrum analysis module and the spectrum acquisition unit can be a spectrum analyzer in the prior art: the spectrum acquisition unit is the receiving antenna of the spectrum analyzer, and the spectrum analysis module is the other parts of the spectrum analyzer except the receiving antenna; it can be understood that the spectrum of the electromagnetic wave generated by the corona discharge is analyzed by the spectrum analyzer, and the receiving antenna of the spectrum analyzer is placed at a suitable position around the transmission line to receive the electromagnetic signal generated by the corona discharge. The spectrum analyzer can display the frequency component and amplitude of the signal, so as to understand the frequency distribution of the electromagnetic interference generated by the corona discharge;

[0063] In practice, (1) the spectrum acquisition unit (receiving antenna) is placed at a certain horizontal distance from the edge of the line, generally at a certain distance from the outside of the projection of the edge conductor of the transmission line, and this distance is determined according to the transmission lines of different voltage levels: ① For 110kV transmission lines, it may be placed 10m to 20m outside the projection of the edge conductor; for ultra-high voltage transmission lines of 500kV and above, this distance may reach about 30m to 50m; this is because the intensity of electromagnetic interference generated by corona discharge weakens with increasing distance, and safety factors and avoidance of other interference sources must be considered; (2) The height of the spectrum acquisition unit (receiving antenna) is usually matched with the height of the transmission line conductor. If the antenna is placed too low, factors such as ground reflection will interfere with the reception of electromagnetic signals; if If the antenna is placed too high, it may be interfered by other high-altitude electromagnetic sources (such as communication base station antennas, aviation navigation signals, etc.); the antenna is generally placed at a height of about 2m to 5m from the ground (on flat ground) so that it is in a relatively pure electromagnetic environment to receive the signal generated by the corona discharge of the transmission line; (3) Since wind direction will affect the distribution of corona discharge products (such as ions), the wind direction should be considered when placing the antenna; in one implementation, placing the antenna on the leeward side of the prevailing wind may receive a stronger electromagnetic signal. At the same time, for areas with complex terrain, such as mountainous areas or near large buildings, avoid placing the antenna in a position that may cause signal reflection or obstruction; therefore, choose an open and flat location so that the antenna can receive the electromagnetic signal generated by corona discharge in all directions and reduce the distortion effect of terrain on the signal;

[0064] Wherein, the frequency distribution is the intensity distribution of electromagnetic waves at different frequencies;

[0065] A data analysis module, which is connected to the data acquisition module, is used to determine the icing trend of each characteristic time period based on the historical icing data, and determine the icing characterization tendency in combination with the real-time temperature to determine whether to perform icing risk assessment;

[0066] The icing trend includes a heavy icing trend and a light icing trend, and the icing characterization tendency includes an explicit icing tendency and a latent icing tendency;

[0067] a risk assessment module, which is respectively connected to the data acquisition module, the spectrum analysis module and the data analysis module, and is used to control the data acquisition module to start data acquisition according to whether icing risk assessment is performed, determine whether a preset distribution condition is met according to the frequency distribution, and determine a risk assessment state according to a determination result of whether the preset distribution condition is met and the power transmission efficiency to determine a subsequent deicing method;

[0068] Among them, the deicing methods include natural deicing, thermal deicing and mechanical deicing.

[0069] It can be understood that through the data search unit and data networking unit in the data acquisition module, the historical icing data of the transmission line and the real-time temperature of the location can be fully collected to provide detailed information for subsequent analysis. Real-time temperature monitoring helps to judge the current icing tendency in combination with historical icing data. This accurate and comprehensive data acquisition method lays a solid foundation for the system to accurately assess icing risks, and can make predictions in advance about possible icing situations, thereby reducing the probability of transmission failures caused by icing. The data analysis module determines the icing trends (severe icing trends and light icing trends) in each characteristic time period based on historical icing data, and clarifies the icing characterization tendency (explicit icing tendency and implicit icing tendency) in combination with real-time temperature. This accurate judgment makes it more scientific and targeted to conduct icing risk assessment, and can be used in the early or potential stages of icing. Accurate judgment can be made at the icing risk stage to buy time for the subsequent timely and effective de-icing measures, reduce the possibility of severe damage to transmission lines caused by icing, and ensure the normal operation of transmission lines in winter and other periods prone to icing; the risk assessment module integrates the information of the data acquisition module, spectrum analysis module and data analysis module, determines the risk assessment status according to whether the preset distribution conditions and transmission efficiency are met, and then reasonably selects the subsequent de-icing method (natural de-icing method, thermal de-icing method and mechanical de-icing method); this decision-making process can select the most suitable de-icing method for different icing conditions and transmission line conditions, improve de-icing efficiency, reduce unnecessary manpower, material and time costs, and at the same time reduce the potential damage risk to transmission lines during the de-icing process, so as to ensure the safe and stable operation of transmission lines and the continuity of power supply.

[0070] Specifically, the spectrum analysis module performs spectrum analysis on the electromagnetic signal, and the spectrum analysis includes windowing and filtering processing, power spectrum and unit conversion, peak detection and frequency estimation.

[0071] In detail, spectrum analysis includes: (1) The electromagnetic signal generated by the corona discharge is an analog signal. The signal may be relatively weak and will be amplified by a preamplifier first; (2) The amplified analog signal is converted into a digital signal through an analog-to-digital converter. In this process, the analog signal is discretized according to a certain sampling frequency to obtain a series of digital samples; (3) The digital signal enters the digital signal processor (DSP) and uses the fast Fourier transform (FFT) algorithm to convert the time domain signal into a frequency domain signal. FFT is an efficient algorithm that can quickly calculate the signal's spectrum, that is, the distribution of the signal at different frequencies; (4) In order to reduce problems such as spectrum leakage, the signal can be windowed. The actual sampled signal window may not be an integer multiple of the signal period. The windowing function (such as Hanning window, Hanning window, etc.) (5) Filter the signal to remove some known background noise or other interference signals, leaving only the electromagnetic interference signal generated by corona discharge. Low-pass, high-pass, band-pass or band-stop filters can be used to achieve this goal. (6) Convert the signal spectrum data into power spectrum form and convert the units according to specific requirements, such as converting to effective value, peak-to-peak value and other power spectrum units, so that the distribution of signal power at different frequencies can be more intuitively understood. (7) Determine the peak frequency in the spectrum and its corresponding power estimate through peak detection and frequency estimation operations, which helps to quickly locate the main frequency components and their intensity of the electromagnetic interference generated by corona discharge, thereby understanding its frequency distribution.

[0072] See also Figure 2 Specifically, the data analysis module determines the historical ice-covered time period as a characteristic time period, and determines whether to merge the corresponding two characteristic time periods according to the time interval between two adjacent characteristic time periods, including:

[0073] If the time interval between two adjacent characteristic time periods is less than or equal to the preset time interval, it is determined that the corresponding two characteristic time periods are merged into one characteristic time period;

[0074] If the time interval between two adjacent characteristic time periods is greater than the preset time interval, it is determined not to merge the corresponding two characteristic time periods.

[0075] It is understandable that the ice-covering time is definitely a period of time. Therefore, the historical ice-covering time period in the past two to three years can be determined through the data search unit, and the corresponding time period can be determined as the characteristic time period. In one implementation, the historical ice-covering time period is from 21:21 on December 25th two years ago to 9:00 on December 26th, then the corresponding 21:21 on December 25th this year to 9:00 on December 26th is recorded as the characteristic time period.

[0076] It is understandable that in some areas of winter, the transmission lines may be covered with ice at night, thaw during the day, and then be covered with ice again at night in a cycle. At this time, if the interval between two characteristic time periods is too close, a new judgment and adjustment must be restarted, which will result in large resource usage and waste of computing resources. Therefore, in implementation, a preset time interval is set, and whether to merge two adjacent characteristic time periods is determined based on this. If the time interval is less than the preset time interval, the two characteristic time periods are merged and then the standby / icing trend is selected according to the real-time temperature and subsequent judgments are made. If the time interval is greater than / equal to the preset time interval, the two characteristic time periods are not merged, and it is necessary to directly end all subsequent judgments after the end of the previous characteristic time period until the next characteristic time period begins to restart the transmission line icing risk assessment. Generally, the preset time interval is 3h to 6h. If the preset time is too long, the original intention of saving resources and reducing the number of power on and off times to protect the assessment system by putting the assessment system on standby is lost. It is preferably set to 5h.

[0077] Specifically, the data analysis module determines the ice coverage trend of the corresponding characteristic time period according to the average ice coverage thickness of each characteristic time period, including:

[0078] If the average ice thickness in the characteristic time period is greater than the preset ice thickness, the ice trend in the corresponding characteristic time period is determined to be a heavy ice trend;

[0079] If the average ice thickness in the characteristic time period is less than or equal to the preset ice thickness, it is determined that the ice trend in the corresponding characteristic time period is a light ice trend.

[0080] In practice, the preset ice thickness is usually set to 10mm. It is understandable that (1) when the average ice thickness is ≤10mm, the impact of ice on the transmission line is relatively small. For general transmission lines, 2mm to 5mm of ice may only slightly increase the weight of the conductor and increase the vertical load on the tower to a certain extent, but generally will not cause obvious deformation or tilt of the tower, and the tension change of the line is also within the safe range. Moreover, at this ice thickness, the insulation performance of the insulator string decreases slightly, and the reduction of the corona starting voltage is also limited. The line can usually be maintained. (2) When the ice thickness exceeds 10 mm, the degree of damage to the transmission line will increase significantly. When the ice thickness reaches 15 mm to 20 mm, the weight of the conductor will increase significantly, causing the conductor tension to rise sharply, which may cause the conductor to stretch or even break. At the same time, the vertical and unbalanced loads on the tower may exceed the design limit, which may easily cause the tower foundation to sink and the cross arm to twist. For the insulator string, the insulation performance will be significantly reduced and the leakage current will increase, which can easily cause flashover accidents, and the corona phenomenon will be aggravated, resulting in more energy loss and electromagnetic interference.

[0081] In practice, for transmission lines located in harsh environments such as wind outlets and high altitudes, serious consequences may occur due to the superposition of other unfavorable factors. Therefore, the preset ice thickness will be lower than 10mm, usually set to 5mm~8mm.

[0082] It is understandable that the data analysis module uses the preset ice thickness as the boundary to accurately divide the trends of light and heavy icing, so that there is a clear judgment on the severity of icing on the transmission lines; for example, when the average ice thickness exceeds 10mm (the preset value is adjusted according to the actual situation under special harsh environments), it is judged as a heavy icing trend. This precise definition helps to promptly detect icing conditions that may cause serious damage to the line, such as conductor breakage, tower deformation, etc., so as to take effective countermeasures in advance to ensure the physical structural integrity and mechanical stability of the transmission line.

[0083] Specifically, the data analysis module determines the ice accumulation tendency according to the determination result of the ice accumulation tendency at the current time and in combination with the real-time temperature, including:

[0084] If the time period corresponding to the current time is not a characteristic time period, the ice coverage tendency is no ice coverage tendency;

[0085] If the time period corresponding to the current time is a characteristic time period, the ice coverage tendency is determined according to the corresponding ice coverage trend, where:

[0086] If the icing tendency is a severe icing tendency, determining the icing characteristic tendency is a dominant icing tendency;

[0087] If the icing trend is a slight icing trend, the icing characterization tendency is determined in combination with the real-time temperature, wherein:

[0088] If the real-time temperature is lower than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a dominant ice-covering tendency;

[0089] If the real-time temperature is higher than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a latent ice-covering tendency;

[0090] The ice-covering temperature is determined according to the freezing point of water and the pressure at the location of the power transmission line.

[0091] It is understandable that the freezing point of water under standard atmospheric pressure is 0°C, which is the critical temperature for water to change from liquid to solid (ice); when the ambient temperature drops to 0°C or below, water will release heat, its molecular movement will gradually slow down, and the distance between molecules will be relatively fixed, thus forming a regular crystal structure, that is, ice. In addition, pressure will affect the freezing point of water. When the pressure increases, the freezing point of water will decrease. In practice, the air pressure on high mountains is lower than the standard atmospheric pressure, and the freezing point of water will be slightly higher than 0°C, but this change is relatively small. In some special high-pressure environments, the freezing point of water may be significantly reduced.

[0092] In implementation, the freezing point of water under each pressure is known in the prior art, so the ice-covering temperature is determined according to the freezing point of water under each pressure; at the same time, considering the influence of dissolved substances in water and / or strong winds on the freezing point, it is necessary to add a temperature correction value, usually the temperature correction value ∈ [2°C, 5°C], preferably set to 3°C; therefore, the ice-covering temperature in the present invention = the freezing point of water under each pressure + the temperature correction value. It can be understood that when determining the ice-covering temperature, not only the freezing point of water under standard atmospheric pressure is considered, but also the pressure of the location of the transmission line and the influence of dissolved substances in water and strong winds on the freezing point are combined to increase the temperature correction value, so that the determination of the ice-covering temperature is more in line with the actual situation, and can more accurately reflect the real ice-covering conditions of the environment in which the transmission line is located, further optimize the judgment of ice-covering trends and characterization tendencies, and provide more scientific and practical data support for the entire transmission line ice-covering risk assessment system, which effectively guarantees the safe and stable operation of the transmission line in a complex environment.

[0093] It is understandable that the data analysis module combines the real-time temperature and icing trend to comprehensively judge the icing tendency, avoiding the limitations of single factor judgment; for cases of mild icing trends, the real-time temperature is further referred to. When the temperature is lower than the icing temperature (the temperature corrected for factors such as pressure, dissolved substances and strong winds), it is judged as an explicit icing tendency; when the temperature is higher than the icing temperature, it is judged as an implicit icing tendency. This scientific judgment method can more accurately reflect the potential risks and actual development trends of icing, provide a reasonable basis for whether to initiate icing risk assessment, effectively reduce the possibility of misjudgment and missed judgment, and improve the accuracy and reliability of risk assessment.

[0094] Specifically, the data analysis module determines to perform icing risk assessment according to the determination result that the icing characterization tendency is a dominant icing tendency, so that the risk assessment module controls the data acquisition module to start data acquisition.

[0095] It is understandable that if the icing tendency is latent icing tendency or no icing tendency, it is determined that there is no possibility of icing at the moment, so no icing risk assessment is performed; this time period may be the time interval before the two adjacent time periods are merged, or it may be caused by the difference between this year's temperature and historical temperature.

[0096] See also Figure 3 As shown, it is a workflow diagram of the risk assessment module of an embodiment of the present invention. Specifically, the risk assessment module determines whether the frequency distribution meets the preset distribution condition according to the machine learning model;

[0097] The preset distribution condition includes that the frequency center value of the electromagnetic interference is within a preset range and the intensity on both sides of the frequency center value gradually decreases.

[0098] It can be understood that the frequency distribution of electromagnetic interference generated by corona discharge refers to the intensity distribution of electromagnetic waves generated by corona discharge at different frequencies: (1) Corona discharge will generate broadband noise, and its frequency range is generally from kHz to hundreds of MHz. Within this range, the electromagnetic interference intensity at different frequencies is different, showing a certain continuity as a whole, and the intensity usually gradually weakens with the increase of frequency; (2) Corona discharge also generates pulse noise, and its frequency range is concentrated in tens of kHz to several MHz. The electromagnetic interference intensity in this frequency band is relatively high, while at frequencies outside this range, the interference intensity decreases rapidly; (3) Corona discharge will also generate flicker noise, and its frequency is relatively fixed, usually between 200Hz and 400Hz. The electromagnetic interference at this frequency has a certain regularity and may interfere with radio navigation and radar signals; In summary, the high-frequency waves generated by corona discharge often take 0.5MHz as the center value, and the electromagnetic interference intensity in the frequency range near it is relatively large, and gradually weakens towards the frequencies on both sides. The interference in this frequency band will affect communication systems such as wired telephones, radio reception and television.

[0099] Therefore, a pre-trained machine learning model can be used to determine whether the frequency distribution meets the preset distribution conditions to determine the subsequent de-icing method in combination with the bookstore efficiency.

[0100] Specifically, the risk assessment module determines the frequency at which the maximum frequency intensity is located as the frequency center value.

[0101] Specifically, the risk assessment module determines the risk assessment state according to whether the preset distribution condition determination result and the power transmission efficiency are met to determine the subsequent deicing method, including:

[0102] If the preset distribution condition is not met and the power transmission efficiency is greater than or equal to the preset power transmission efficiency, the risk assessment state is determined to be a low risk state, and the subsequent deicing method is determined to be a natural deicing method; it can be understood that if the preset distribution condition is not met and the power transmission efficiency is greater than or equal to the preset power transmission efficiency, it means that the corona phenomenon is not obvious and the power transmission process is normal, so it does not affect the normal operation of the power transmission line and does not affect the surrounding communication system. At this time, there is no need to use external force to remove the ice on the power transmission line, and it can be left to melt naturally;

[0103] If the preset distribution condition is met or the transmission efficiency is less than the preset transmission efficiency, the risk assessment state is determined to be a medium risk state, and the subsequent deicing method is determined to be a mechanical deicing method; it can be understood that the preset distribution condition is met or the transmission efficiency is less than the preset transmission efficiency, indicating that the corona phenomenon or one aspect of the transmission process is abnormal, thereby affecting the normal operation of the transmission line or affecting the surrounding communication system, indicating that the influence of icing already exists and external force (mechanical deicing) is needed to remove the ice on the transmission line;

[0104] If the preset distribution conditions are met and the transmission efficiency is less than the preset transmission efficiency, the risk assessment state is determined to be a high-risk state, and the subsequent deicing method is determined to be a thermal deicing method and a mechanical deicing method; it can be understood that the preset distribution conditions are met and the transmission efficiency is less than the preset transmission efficiency, indicating that the corona phenomenon and the transmission process are abnormal, and at the same time affect the normal operation of the transmission line and the surrounding communication system, indicating that the impact of icing is very serious. At this time, only mechanical deicing cannot achieve a good deicing effect, so it is necessary to combine thermal deicing and mechanical deicing to remove ice on the transmission line;

[0105] It is understandable that (1) a high risk assessment status means that the ice is thick and covers a wide area. At this time, mechanical de-icing methods will face huge challenges, while short-circuit current melting and direct current melting in thermal de-icing methods can quickly generate a large amount of heat, causing the thick ice layer to melt in a short time; short-circuit current melting is achieved by short-circuiting the three-phase conductors at the end of the transmission line and applying a certain voltage at the head end to generate a strong short-circuit current in the line, using the conductor's own resistance to heat to melt the ice; direct current melting can also provide sufficient heat, and its advantage is that it can more accurately control the melting current and heat. For long-distance, large-area, severely ice-covered transmission lines, this efficient de-icing method can quickly reduce the line burden; (2) Secondly, severe ice may This results in the formation of various irregular ice ridges and ice hangings on the line, and even complex structures such as insulators are wrapped around them. Thermal deicing can gradually melt these complex ice shapes through heat transfer, avoiding the problem of damage to the line or incomplete deicing that may occur when mechanical deicing is used to deal with these complex structures; (3) In addition, in the case of severe icing, the on-site environment is often more severe, such as strong winds, heavy snow, low temperatures and other weather conditions. The use of mechanical deicing is very dangerous, while some thermal deicing equipment (such as DC deicing devices and laser deicing systems) can be remotely operated. Workers can remotely start and control the deicing process in a relatively safe control room based on real-time monitoring data of line icing (such as ice thickness, line temperature, etc.), greatly reducing the risk to personnel safety. Therefore, when the risk assessment status is high, mechanical deicing can be used as an auxiliary means.

[0106] It is understandable that (1) mechanical deicing tools (such as insulating rods for manual deicing, pulley scraping tools, deicing robots, etc.) can act directly on the ice-covered areas and can accurately de-ice areas with severe local icing; however, mechanical deicing methods may not be able to remove the tiny ice crystals on the surface of the line and the impurities inside the ice layer. These residual ice may cause icing problems again when the environment changes later; (2) Thermal deicing methods (such as short-circuit current deicing, DC deicing, laser deicing) can quickly melt large areas of ice. Once the deicing program is started, the ice layer can melt and fall off in a short time. It is very effective for long-distance transmission lines with thick ice cover. Some thermal deicing equipment (such as DC ice melting devices and laser ice melting systems) can be remotely operated. Workers can remotely start and control the ice melting process in the control room based on the real-time monitoring of line ice cover, avoiding the risk of on-site operations in harsh environments. Thermal deicing can de-ice line components such as conductors and insulators of various shapes. Whether it is a curved conductor or a complex-shaped hardware, as long as the heat can be transferred to the ice-covered part, the ice can be melted. Compared with the limitations of mechanical deicing on complex structures, it has obvious advantages.

[0107] It is understandable that each transmission line is established with a corresponding transmission efficiency range, and the preset transmission efficiency is determined based on its maximum transmission efficiency and minimum transmission efficiency. Usually, the preset transmission efficiency = minimum transmission efficiency + 0.3 × (maximum transmission efficiency - minimum transmission efficiency).

[0108] It is understandable that the risk assessment module divides the risk assessment status into low, medium and high risk states according to whether the preset distribution conditions are met and the level of transmission efficiency. This assessment method can comprehensively and accurately reflect the potential impact of icing on transmission lines, avoid the ambiguity and uncertainty of risk assessment, make the understanding of icing risks clearer and clearer, and provide a reliable basis for subsequent decision-making; according to different risk assessment states, the subsequent de-icing methods are determined in a targeted manner to ensure that the transmission lines resume normal operation as soon as possible and reduce the probability of power outages caused by icing; for low-risk states, the natural de-icing method is selected to make full use of natural conditions and avoid unnecessary manpower and material resources; for medium-risk states, the mechanical de-icing method is used to deal with the icing problem in a timely and effective manner to prevent it from further deteriorating; for high-risk states, the thermal de-icing method and the mechanical de-icing method are combined to give play to the advantages of efficient and fast thermal de-icing and adaptability to complex icing structures, as well as the characteristics of precise local treatment and emergency repair of mechanical de-icing, which can quickly and thoroughly solve serious icing problems.

[0109] See also Figure 4 As shown, it is a step diagram of a method for assessing the risk of icing on a transmission line according to an embodiment of the present invention. The embodiment of the present invention also provides a method for assessing the risk of icing on a transmission line, comprising:

[0110] Step S1, obtaining historical icing data of the transmission line, and determining characteristic time periods and icing trends in each characteristic time period according to the historical icing data;

[0111] Step S2, determining the icing trend at the current time, and determining the icing characterization tendency in combination with the real-time temperature to determine whether to perform an icing risk assessment;

[0112] Step S3, controlling the data acquisition module to start data acquisition according to the determination result of the icing risk assessment;

[0113] Step S4, performing spectrum analysis on the collected electromagnetic signal to determine the frequency distribution of the electromagnetic interference generated by the corona discharge to determine whether a preset distribution condition is met;

[0114] Step S5, determining a risk assessment state according to a result of determining whether the preset distribution condition is met and the power transmission efficiency;

[0115] Step S6: determining a subsequent deicing method according to the risk assessment status.

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based device that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A transmission line icing risk assessment system, characterized in that: include: A data acquisition module, comprising a data search unit for acquiring historical ice coverage data of the power transmission line and a data networking unit for acquiring the real-time temperature of the location of the power transmission line, wherein the historical ice coverage data includes a historical ice coverage time period and a corresponding historical ice coverage thickness; A data acquisition module, comprising a spectrum acquisition unit for receiving electromagnetic signals generated by corona discharge and an electric meter monitoring unit for collecting power transmission efficiency; A spectrum analysis module, connected to the spectrum acquisition unit, for performing spectrum analysis on the electromagnetic signal to determine the frequency distribution of the electromagnetic interference generated by the corona discharge; Wherein, the frequency distribution is the intensity distribution of electromagnetic waves at different frequencies; A data analysis module, which is connected to the data acquisition module, is used to determine the icing trend of each characteristic time period based on the historical icing data, and determine the icing characterization tendency in combination with the real-time temperature to determine whether to perform icing risk assessment; The icing trend includes a heavy icing trend and a light icing trend, and the icing characterization tendency includes an explicit icing tendency and a latent icing tendency; a risk assessment module, which is respectively connected to the data acquisition module, the spectrum analysis module and the data analysis module, and is used to control the data acquisition module to start data acquisition according to whether icing risk assessment is performed, determine whether a preset distribution condition is met according to the frequency distribution, and determine a risk assessment state according to a determination result of whether the preset distribution condition is met and the power transmission efficiency to determine a subsequent deicing method; Among them, the deicing methods include natural deicing, thermal deicing and mechanical deicing.

2. The transmission line icing risk assessment system according to claim 1, characterized in that: The spectrum analysis module performs spectrum analysis on the electromagnetic signal, and the spectrum analysis includes windowing and filtering processing, power spectrum and unit conversion, peak detection and frequency estimation.

3. The transmission line icing risk assessment system according to claim 1, characterized in that: The data analysis module determines the historical ice-covered time period as a characteristic time period, and determines whether to merge two corresponding characteristic time periods according to the time interval between two adjacent characteristic time periods, including: If the time interval between two adjacent characteristic time periods is less than or equal to the preset time interval, it is determined that the corresponding two characteristic time periods are merged into one characteristic time period; If the time interval between two adjacent characteristic time periods is greater than the preset time interval, it is determined not to merge the corresponding two characteristic time periods.

4. The transmission line icing risk assessment system according to claim 3, characterized in that: The data analysis module determines the ice coverage trend of the corresponding characteristic time period according to the average ice coverage thickness of each characteristic time period, including: If the average ice thickness in the characteristic time period is greater than the preset ice thickness, the ice trend in the corresponding characteristic time period is determined to be a heavy ice trend; If the average ice thickness in the characteristic time period is less than or equal to the preset ice thickness, it is determined that the ice trend in the corresponding characteristic time period is a light ice trend.

5. The transmission line icing risk assessment system according to claim 4, characterized in that: The data analysis module determines the ice accumulation tendency according to the determination result of the ice accumulation tendency at the current time in combination with the real-time temperature, including: If the time period corresponding to the current time is not a characteristic time period, the ice coverage tendency is no ice coverage tendency; If the time period corresponding to the current time is a characteristic time period, the ice coverage tendency is determined according to the corresponding ice coverage trend, where: If the icing tendency is a severe icing tendency, determining the icing characteristic tendency is a dominant icing tendency; If the icing trend is a slight icing trend, the icing characterization tendency is determined in combination with the real-time temperature, wherein: If the real-time temperature is lower than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a dominant ice-covering tendency; If the real-time temperature is higher than the ice-covering temperature, the ice-covering characteristic tendency is determined to be a latent ice-covering tendency; The ice-covering temperature is determined according to the freezing point of water and the pressure at the location of the power transmission line.

6. The transmission line icing risk assessment system according to claim 1, characterized in that: The data analysis module determines to perform icing risk assessment according to the determination result that the icing characterization tendency is a dominant icing tendency, so that the risk assessment module controls the data acquisition module to start data acquisition.

7. The power transmission line icing risk assessment system according to claim 1, characterized in that: The risk assessment module determines whether the frequency distribution meets the preset distribution condition according to the machine learning model; The preset distribution condition includes that the frequency center value of the electromagnetic interference is within a preset range and the intensity on both sides of the frequency center value gradually decreases.

8. The transmission line icing risk assessment system according to claim 7, characterized in that: The risk assessment module determines the frequency at which the maximum frequency intensity is located as the frequency center value.

9. The method for assessing the risk of icing on a power transmission line according to claim 1, characterized in that: The risk assessment module determines the risk assessment state according to the result of whether the preset distribution condition is met and the power transmission efficiency to determine the subsequent deicing method, including: If the preset distribution condition is not met and the power transmission efficiency is greater than or equal to the preset power transmission efficiency, the risk assessment state is determined to be a low risk state, and the subsequent deicing method is determined to be a natural deicing method; If the preset distribution condition is met or the power transmission efficiency is less than the preset power transmission efficiency, the risk assessment state is determined to be a medium risk state, and the subsequent deicing method is determined to be a mechanical deicing method; If the preset distribution condition is met and the power transmission efficiency is less than the preset power transmission efficiency, the risk assessment state is determined to be a high-risk state, and the subsequent deicing method is determined to be a thermal deicing method and a mechanical deicing method.

10. A transmission line icing risk assessment method applied to the transmission line icing risk assessment system according to any one of claims 1 to 9, characterized in that: include, Acquire historical icing data of the transmission line, and determine characteristic time periods and icing trends in each characteristic time period based on the historical icing data; Determine the icing trend at the current time, and determine the icing characterization tendency in combination with the real-time temperature to determine whether to conduct an icing risk assessment; Controlling the data acquisition module to start data acquisition according to the determination result of the icing risk assessment; Performing spectrum analysis on the collected electromagnetic signals to determine the frequency distribution of the electromagnetic interference generated by the corona discharge to determine whether the preset distribution conditions are met; Determining a risk assessment state according to a determination result of whether the preset distribution condition is met and the power transmission efficiency; A subsequent de-icing method is determined according to the risk assessment status.

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