Strong wind disaster monitoring equipment for transmission and distribution lines based on smart grid

Abstract

The present invention discloses a wind disaster monitoring device for transmission and distribution lines based on a smart grid, which belongs to the technical field of smart grid transmission and distribution line monitoring, and is used to solve the problems of fixed sensor acquisition frequency, low resource utilization rate, and lack of effective level assessment mechanism when dealing with the impact of wind disasters on conductor tension in wind disaster monitoring equipment; the device comprises a sensor module, a data acquisition module, a data processing module and a disaster detection module; the sensor module arranges a variety of environmental sensors at transmission and distribution line towers and conductors to collect environmental parameters; the data acquisition module divides and assigns environmental parameter risk intervals based on historical data, and intelligently adjusts the acquisition frequency according to the real-time total risk value; the data processing module integrates environmental parameters into detection data packets, determines to send disaster inspection packages according to the total risk value, and verifies their integrity; the disaster detection module analyzes the environmental parameters of the disaster inspection package to obtain the disaster assessment value, compares it with the threshold value, assesses the disaster level, and adjusts the conductor tension.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart grid transmission and distribution line monitoring, and specifically relates to a transmission and distribution line gale disaster monitoring device based on a smart grid. Background Art

[0002] In the operation guarantee of the transmission and distribution lines of the smart grid, wind disaster monitoring is crucial; however, current monitoring equipment has many shortcomings;

[0003] In terms of energy management: existing monitoring equipment lacks intelligence; sensors usually operate at a fixed acquisition frequency without considering the actual working status and environmental requirements of the sensors;

[0004] In terms of dealing with the impact of strong wind disasters on conductor tension: the existing technology has obvious limitations; when strong wind disasters are monitored, there is a lack of an effective strong wind disaster level assessment mechanism, and it is impossible to accurately calculate the strong wind disaster level based on multiple parameters such as wind speed, wind direction, temperature, humidity, air pressure, conductor tension and conductor dancing amplitude, so it is impossible to reasonably adjust the conductor tension based on the level. For this reason, we propose a strong wind disaster monitoring device for transmission and distribution lines based on smart grids. Summary of the invention

[0005] The purpose of the present invention is to provide a transmission and distribution line gale disaster monitoring device based on a smart grid to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a wind disaster monitoring device for transmission and distribution lines based on a smart grid, comprising a sensor module, a data acquisition module, a data processing module, and a disaster detection module;

[0007] Sensor module: Environmental sensors are placed on transmission and distribution line towers and conductors to collect environmental parameters; environmental sensors include temperature sensors, humidity sensors, air pressure sensors, wind speed sensors, wind direction sensors, conductor tension sensors, and conductor dancing sensors. Environmental parameters include wind speed, wind direction, temperature, humidity, air pressure, conductor tension, and conductor dancing amplitude;

[0008] Data acquisition module: controls the environmental sensor to collect environmental parameters, dynamically adjusts the environmental sensor collection frequency, and sends the collected environmental parameters to the data processing module;

[0009] Data processing module: Integrate environmental parameters at the same collection time into detection data packets, analyze the detection data packets to obtain the total risk value of the detection data packets, determine whether to send them to the disaster detection module based on the total risk value of the detection data packets, and record the detection data packets sent to the disaster detection module as disaster detection packets; verify the completeness of the disaster detection packets before and after they are sent;

[0010] Disaster detection module: Analyze the environmental parameter data in the disaster inspection package to obtain the disaster assessment value of the disaster inspection package, compare the disaster assessment value of the disaster inspection package with the preset threshold, and if the disaster assessment value of the disaster inspection package is greater than the preset threshold, it is determined to be a strong wind disaster, and the disaster level is evaluated and the conductor tension is adjusted according to the disaster level.

[0011] Preferably, the specific process of dynamically adjusting the environmental sensor acquisition frequency is:

[0012] For each environmental parameter, it is divided into several risk intervals according to its value range. Each risk interval corresponds to a value range of an environmental parameter. Based on the historical environmental parameter data, the degree of correlation between each risk interval and the strong wind disaster is calculated, and a risk value is assigned to each risk interval, that is, each environmental parameter risk interval corresponds to a risk assignment;

[0013] The preset environmental sensor acquisition frequency is divided into three gears, including: low-frequency acquisition, medium-frequency acquisition and high-frequency acquisition; the working time of the environmental sensor in one day is divided into several detection periods;

[0014] For each group of detection time periods, the medium frequency acquisition is set as the initial acquisition frequency for parameter acquisition; the environmental parameter values ​​collected at the acquisition time are obtained, the environmental parameter values ​​at the acquisition time are matched with the corresponding risk intervals, the risk assignment corresponding to the risk interval is output, and the risk assignments of all environmental parameters at the same acquisition time are assigned different weight coefficients respectively, and then each risk assignment is weighted to obtain the total risk value, and a curve diagram of the change of the total risk value and time is established, with the total risk value as the vertical axis and the time as the horizontal axis. The total risk values ​​corresponding to each acquisition time are connected by curves according to the time sequence to obtain a risk change line, and the preset low-frequency acquisition, medium-frequency acquisition and high-frequency acquisition each correspond to a total risk value interval, which are the low-frequency interval, the medium-frequency interval and the high-frequency interval respectively, and the total risk values ​​corresponding to five consecutive acquisition times centered on the current acquisition time are obtained. If the total risk values ​​corresponding to more than two of the five acquisition times are within the total risk value interval corresponding to the same acquisition frequency, the acquisition frequency corresponding to the total risk value interval is set as the subsequent acquisition frequency. Conversely, if the total risk values ​​corresponding to less than or equal to two of the five acquisition times are within the total risk value interval corresponding to the same acquisition frequency, the acquisition frequency remains unchanged.

[0015] Preferably, the specific process of calculating the correlation between each risk interval and the strong wind disaster is as follows:

[0016] Based on historical environmental parameter data, for each environmental parameter, the environmental parameter value corresponding to the occurrence of strong wind disasters is marked as the wind vane value; then, for each risk interval, each wind vane value is matched with it one by one, and the number of wind vane values ​​falling in each risk interval is counted. The more wind vane values ​​there are in the risk interval, the higher the degree of correlation between the risk interval and strong wind disasters.

[0017] Preferably, the specific working process of the data processing module is:

[0018] Integrate the different environmental parameter data received at the same collection time to form a data packet containing complete environmental information, which is recorded as a detection data packet; obtain the total risk value of the detection data packet, preset the total risk threshold of the detection data packet assessment, and compare the total risk value of the detection data packet with the preset total risk threshold of the detection data packet assessment. If the total risk value of the detection data packet is greater than or equal to the preset total risk threshold of the detection data packet assessment, the detection data packet is sent to the disaster detection module, otherwise it is not sent;

[0019] The detection data packet sent to the disaster detection module is recorded as a disaster detection package. For each disaster detection package, the number of bytes of the disaster detection package is calculated and recorded before it is sent to the disaster detection module. After receiving the package, the disaster detection module recounts the number of bytes and compares it with the number of bytes before sending. If they are the same, it is determined that the disaster detection package data has been sent completely. If they are different, a resending instruction for the disaster detection package is generated.

[0020] Preferably, the specific process of analyzing the environmental parameter data in the disaster inspection package to obtain the disaster assessment value of the disaster inspection package is:

[0021] Extract environmental parameter data from the disaster inspection package;

[0022] For the analysis of wind speed environmental parameters, a normal wind speed threshold is preset, and the wind speed is compared with the preset normal wind speed threshold. If the wind speed is greater than the preset normal wind speed threshold, the deviation between the wind speed and the normal wind speed threshold is obtained and recorded as the wind deviation value FP. The wind deviation risk contribution coefficient kf is preset, and the wind speed contribution value FG is obtained using the formula: FG=FP×kf. If the wind speed is less than or equal to the preset normal wind speed threshold, the wind speed contribution value is zero; the analysis method for obtaining the wind speed contribution value is marked as the first contribution value analysis method for strong wind disasters;

[0023] The first contribution value analysis method of strong wind disaster is used to analyze the conductor galloping amplitude, and the conductor galloping amplitude contribution value WG is obtained;

[0024] For the analysis of temperature environment parameters, a normal temperature value interval is preset, and the temperature is compared with the preset normal temperature value interval. If the temperature is greater than the preset normal temperature value interval, the deviation value between the temperature and the previous value of the preset normal temperature value interval is obtained and recorded as the upper temperature deviation value WSP. The temperature contribution value WG is obtained by using the formula: FG=WSP×kw1; if the temperature is less than the preset normal temperature value interval, the deviation value between the temperature and the next value of the preset normal temperature value interval is obtained and recorded as the lower temperature deviation value WXP. The temperature contribution value WG is obtained by using the formula: WG=WXP×kw2, where kw1 and kw2 are the preset temperature contribution coefficients; if the temperature is within the preset normal temperature value interval, the temperature contribution value is zero; the analysis method for obtaining the temperature contribution value is marked as the second contribution value analysis method for strong wind disasters;

[0025] The second contribution value analysis method of strong wind disaster is used to analyze humidity and conductor tension, and the humidity contribution value SG and the conductor tension contribution value ZG are obtained;

[0026] For the analysis of air pressure environment parameters, a normal air pressure threshold is preset, and the air pressure is compared with the preset normal air pressure threshold. If the air pressure is less than the preset normal wind speed threshold, the deviation between the air pressure and the preset normal air pressure threshold is obtained and recorded as the pressure deviation value YP. The pressure deviation risk contribution coefficient ky is preset, and the air pressure contribution value QG is obtained using the formula: QG=YP×ky. If the air pressure is greater than or equal to the preset normal air pressure threshold, the air pressure contribution value is zero;

[0027] For the analysis of wind direction environmental parameters, a plane rectangular coordinate system is established with the Y axis parallel to the conductor direction and the X axis perpendicular to the conductor direction as the wind direction coordinate system; a wind direction line is drawn in the wind direction coordinate system in the direction parallel to the wind direction, and the angle of the wind direction line deviating from the acute angle of the Y axis is calculated, which is recorded as the deviation angle XG;

[0028] The wind speed contribution value FG, deviation angle XG, temperature contribution value WG, humidity contribution value SG, air pressure contribution value QG, conductor tension contribution value ZG and conductor dancing amplitude contribution value WG of the disaster inspection package are normalized and input into the preset formula model: ZH=FG×a1+XG×a2+WG×a3+SG×a4+QG×a5+ZG×a6+WG×a7 to obtain the disaster assessment value ZH of the disaster inspection package, where a1, a2, a3, a4, a5, a6, and a7 are preset weight coefficients.

[0029] Preferably, the specific process of determining a gale disaster is as follows:

[0030] The disaster assessment value of the disaster inspection package is compared with the preset disaster assessment threshold in the order in which the disaster inspection packages are received. If the disaster assessment value of the disaster inspection package is greater than or equal to the preset disaster assessment threshold, it is determined to be a strong wind disaster, the disaster level is assessed, and the conductor tension is adjusted according to the disaster level. During the period of assessing the disaster level and adjusting the conductor tension according to the disaster level, the subsequent disaster level assessment process of the disaster inspection package is stopped until the disaster level assessment and the conductor tension adjustment operation are completed, and then the strong wind disaster determination and disaster level assessment process are carried out.

[0031] Preferably, the specific process of evaluating the disaster level and adjusting the conductor tension according to the disaster level is:

[0032] Taking the current moment as the starting moment, the evaluation period is preset, and the disaster evaluation values ​​of each disaster detection package sent to the disaster detection module within the evaluation period are summed to obtain the total evaluation value, and an ellipse model is established. The size of the total evaluation value is the length of the major axis of the ellipse, and the time length of the preset evaluation period is the length of the minor axis of the ellipse. The ellipse is drawn and recorded as the evaluation circle, and the area of ​​the evaluation circle is calculated and recorded as the disaster evaluation value; three gale disaster levels are set, which are divided into level 1 gale disaster, level 2 gale disaster, and level 3 gale disaster; each gale disaster level corresponds to a disaster evaluation value interval, and each gale disaster level corresponds to a standard conductor tension value;

[0033] Match the disaster assessment value with the disaster assessment value interval corresponding to the high wind disaster level, and output the corresponding high wind disaster level; find the corresponding standard conductor tension value according to the determined high wind disaster level; and use the conductor tension adjustment device to adjust the conductor tension so that the current conductor tension is consistent with the conductor standard tension value corresponding to the determined high wind disaster level;

[0034] When it is a level 1 gale disaster, a level 1 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to half of the original;

[0035] When it is a level 2 gale disaster, a level 2 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to one third of the original;

[0036] When a level 3 gale disaster occurs, a level 3 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal. The detection personnel terminal immediately dispatches maintenance personnel to conduct on-site inspections, and reports to the superior power dispatching department and emergency management department, and deploys more emergency repair personnel and materials to the level 3 gale disaster line area on standby, ready to carry out line emergency repair and restoration work at any time.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] (1) The wind disaster monitoring equipment for the transmission and distribution lines based on the smart grid divides each environmental parameter into risk intervals based on historical environmental parameter data and assigns values ​​to obtain the total risk value at the time of collection, and establishes a curve diagram of the change of the total risk value and time. The preset low-frequency collection, medium-frequency collection and high-frequency collection each correspond to a total risk value interval. The collection frequency is determined based on the total risk values ​​corresponding to five consecutive collection moments centered on the current collection moment. If the total risk values ​​corresponding to two or more collection frequencies in the five collection moments are all in the low-frequency interval, the collection frequency can be adjusted to the interval length corresponding to the low-frequency collection, thereby reducing unnecessary data collection. If they are all in the high-frequency interval, they are switched to the high-frequency collection interval to ensure that the rapid changes of environmental parameters can be accurately captured, providing more detailed data support for responding to possible wind disasters. This intelligent adjustment mechanism ensures that the system resource utilization efficiency is optimized under the premise of ensuring effective monitoring of wind disasters, avoiding the waste of resources on data collection during invalid or low-risk periods.

[0039] (2) The wind disaster monitoring equipment for transmission and distribution lines based on smart grid, the disaster detection module analyzes the environmental parameters of the disaster detection package, such as wind speed, wind direction, temperature, humidity, air pressure, conductor tension and conductor dancing amplitude, to obtain a disaster assessment value, and judges whether a wind disaster occurs according to the disaster assessment value of the disaster detection package. If a wind disaster occurs, the disaster assessment value is obtained by comprehensively analyzing the total value of the disaster assessment values ​​of all disaster detection packages within the assessment period with the elliptical model, and the wind disaster level is determined according to the disaster assessment value. At the same time, the conductor tension is adjusted according to the wind disaster level. In this way, the disaster level can be analyzed based on multiple environmental parameters, and the conductor tension can be reasonably adjusted according to the disaster level.

[0040] (3) The wind disaster monitoring equipment for transmission and distribution lines based on the smart grid, through the data processing module, only sends high-risk detection data packets whose total risk value reaches the preset assessment risk total threshold to the disaster detection module, reducing unnecessary data transmission and processing and improving processing efficiency; at the same time, by verifying the number of bytes of the disaster detection packet, it ensures the data integrity of the detection data packet sent to the disaster detection module, ensures the accuracy and reliability of data reception, and provides a solid data foundation for the disaster detection module to accurately assess the wind disaster risk, further improving the reliability and effectiveness of the entire monitoring equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flowchart of the present invention;

[0042] Figure 2 It is a curve diagram of the change of the total risk value and time of the present invention;

[0043] Figure 3 It is the ellipse model diagram of the present invention;

[0044] Figure 4 is the wind direction coordinate system of the present invention; DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0046] See also Figure 1 - Figure 4 , the present invention provides a wind disaster monitoring device for transmission and distribution lines based on a smart grid, including a sensor module, a data acquisition module, a data processing module, and a disaster detection module;

[0047] Sensor module: Environmental sensors are arranged on transmission and distribution line towers and conductors, where the environmental sensors include: temperature sensors, humidity sensors, air pressure sensors, wind speed sensors, wind direction sensors, conductor tension sensors, and conductor dancing sensors;

[0048] The environmental sensor is connected to the monitoring device to collect environmental parameters; the environmental parameters include: wind speed, wind direction, temperature, humidity, air pressure, wire tension and wire dancing amplitude;

[0049] Data acquisition module: controls the environmental sensor to collect environmental parameters, dynamically adjusts the collection frequency, and sends the collected environmental parameters to the data processing module. The specific process of dynamically adjusting the collection frequency of the environmental sensor is as follows:

[0050] For each environmental parameter, it is divided into several risk intervals according to its value range. Each risk interval corresponds to a value range of an environmental parameter. Based on the historical environmental parameter data, the degree of correlation between each risk interval and the strong wind disaster is calculated, and a risk value is assigned to each risk interval. The higher the degree of correlation between the risk interval and the strong wind disaster, the greater the corresponding risk value.

[0051] The specific process of calculating the correlation between each risk interval and the strong wind disaster is as follows:

[0052] Based on the historical environmental parameter data, for each environmental parameter, the corresponding environmental parameter value when the strong wind disaster occurs is marked as the wind vane value; then, for each risk interval, each wind vane value is matched with it one by one, and the number of wind vane values ​​falling in each risk interval is counted. The more wind vane values ​​there are in the risk interval, the higher the degree of correlation between the risk interval and the strong wind disaster;

[0053] Because the number of wind vane values ​​can directly reflect the degree of correlation between the risk interval and the strong wind disaster, the more wind vane values ​​there are, the higher the degree of correlation between the risk interval and the strong wind disaster; that is, by counting the number of wind vane values ​​in each risk interval, the correlation between the risk interval and the strong wind disaster can be effectively judged;

[0054] The preset environmental sensor acquisition frequency is divided into three gears, including: low-frequency acquisition, medium-frequency acquisition and high-frequency acquisition; all environmental sensors share a unified acquisition frequency, and the working hours of the environmental sensors in one day are divided into several detection periods;

[0055] For each group of detection periods, set the medium frequency acquisition as the initial acquisition frequency for parameter acquisition; obtain the environmental parameter values ​​collected at the acquisition time, match the environmental parameter values ​​at the acquisition time with the corresponding risk interval, output the risk assignment corresponding to the risk interval, assign different weight coefficients to the risk assignments of all environmental parameters at the same acquisition time, and then perform weighted calculation on each risk assignment to obtain the total risk value, and establish a curve chart of the change of the total risk value and time, such as Figure 2, the total risk value is the vertical axis, and time is the horizontal axis. The total risk values ​​corresponding to each collection moment are connected by curves according to the time sequence to obtain the risk change line. The preset low-frequency collection, medium-frequency collection and high-frequency collection each correspond to a total risk value interval, which are the low-frequency interval, the medium-frequency interval and the high-frequency interval respectively. The total risk values ​​corresponding to the five consecutive collection moments centered on the current collection moment are obtained. If the total risk values ​​corresponding to more than two of the five collection moments are within the total risk value interval corresponding to the same collection frequency (low-frequency interval, medium-frequency interval or high-frequency interval), the collection frequency corresponding to the total risk value interval is set as the subsequent collection frequency. Conversely, if the total risk values ​​corresponding to less than or equal to two of the five collection moments are within the total risk value interval corresponding to the same collection frequency, the collection frequency remains unchanged. For example: among the five total risk values ​​corresponding to the five consecutive collection moments centered on the current collection moment, three or more collection times are If the total risk value corresponding to the moment is in the low-frequency interval, then after the collection of the five collection moments is completed, the collection frequency of the detection period will be adjusted to the interval length corresponding to the low-frequency collection, so as to reduce unnecessary data collection and reduce system resource consumption; if they are all in the high-frequency interval, then switch to the high-frequency collection interval to ensure that the rapid changes of environmental parameters can be accurately captured, so as to provide more detailed data support for responding to possible strong wind disasters; if the number of the five risk total values ​​distributed in the risk total value interval corresponding to the same collection moment does not exceed two, it indicates that the environmental parameters are unstable. At this time, keep the current collection interval unchanged, continue to closely monitor the dynamics of environmental parameters, and wait until the subsequent data shows a clearer trend before deciding whether to adjust the collection frequency; in this way, the data collection frequency can be flexibly and intelligently adjusted according to the real-time changes in environmental parameter risks, while ensuring the effective monitoring of strong wind disasters, optimizing the efficiency of system resource utilization and the rationality of data collection.

[0056] The data processing module integrates the environmental parameters at the time of collection into a detection data packet, and determines whether to send it to the disaster detection module based on the total risk value of the detection data packet. At the same time, it verifies the completeness of the detection data packet before and after it is sent. The specific process is as follows:

[0057] Integrate the different environmental parameter data received at the same collection time to form a data packet containing complete environmental information, which is recorded as a detection data packet; obtain the total risk value of the detection data packet, preset the total risk threshold of the detection data packet assessment, and compare the total risk value of the detection data packet with the preset total risk threshold of the detection data packet assessment. If the total risk value of the detection data packet is greater than or equal to the preset total risk threshold of the detection data packet assessment, the detection data packet is sent to the disaster detection module, otherwise it is not sent;

[0058] The detection data packet sent to the disaster detection module is recorded as a disaster detection package. For each disaster detection package, the number of bytes of the disaster detection package is calculated and recorded before it is sent to the disaster detection module. After receiving the package, the disaster detection module recounts the number of bytes and compares it with the number of bytes before sending. If they are the same, it is determined that the disaster detection package data has been sent completely. If they are different, a resending instruction for the disaster detection package is generated.

[0059] It should be noted that only high-risk detection data packets are sent to the disaster detection module to reduce unnecessary data transmission and processing and improve processing efficiency. At the same time, the data integrity of the detection data packets sent to the disaster detection module is ensured by verifying the number of bytes, ensuring accurate and reliable data reception, which is conducive to the disaster detection module to accurately assess the risk of high wind disasters.

[0060] When receiving the disaster inspection package, the disaster detection module unpacks the received disaster inspection package, extracts and analyzes the environmental parameter data such as wind speed, wind direction, temperature, humidity, air pressure, wire tension and wire dancing amplitude, obtains the disaster assessment value of the disaster inspection package, compares the disaster assessment value of the disaster inspection package with the preset threshold, and if the disaster assessment value of the disaster inspection package is greater than the preset threshold, it is determined to be a strong wind disaster, evaluates the disaster level and adjusts the wire tension according to the disaster level; the specific process is as follows:

[0061] Extract environmental parameter data from the disaster inspection package;

[0062] For the analysis of wind speed environmental parameters, a normal wind speed threshold is preset, and the wind speed is compared with the preset normal wind speed threshold. If the wind speed is greater than the preset normal wind speed threshold, the deviation between the wind speed and the normal wind speed threshold is obtained and recorded as the wind deviation value FP. The wind deviation risk contribution coefficient kf is preset, and the wind speed contribution value FG is obtained using the formula: FG=FP×kf. If the wind speed is less than or equal to the preset normal wind speed threshold, the wind speed contribution value is zero; the analysis method for obtaining the wind speed contribution value is marked as the first contribution value analysis method for strong wind disasters;

[0063] The first contribution value analysis method of strong wind disaster is used to analyze the conductor galloping amplitude, and the conductor galloping amplitude contribution value WG is obtained;

[0064] For the analysis of temperature environment parameters, a normal temperature value interval is preset, and the temperature is compared with the preset normal temperature value interval. If the temperature is greater than the preset normal temperature value interval, the deviation value between the temperature and the previous value of the preset normal temperature value interval is obtained and recorded as the upper temperature deviation value WSP. The temperature contribution value WG is obtained by using the formula: FG=WSP×kw1; if the temperature is less than the preset normal temperature value interval, the deviation value between the temperature and the next value of the preset normal temperature value interval is obtained and recorded as the lower temperature deviation value WXP. The temperature contribution value WG is obtained by using the formula: WG=WXP×kw2, where kw1 and kw2 are the preset temperature contribution coefficients; if the temperature is within the preset normal temperature value interval, the temperature contribution value is zero; the analysis method for obtaining the temperature contribution value is marked as the second contribution value analysis method for strong wind disasters;

[0065] The second contribution value analysis method of strong wind disaster is used to analyze humidity and conductor tension, and the humidity contribution value SG and the conductor tension contribution value ZG are obtained;

[0066] For the analysis of air pressure environment parameters, a normal air pressure threshold is preset, and the air pressure is compared with the preset normal air pressure threshold. If the air pressure is less than the preset normal wind speed threshold, the deviation between the air pressure and the preset normal air pressure threshold is obtained and recorded as the pressure deviation value YP. The pressure deviation risk contribution coefficient ky is preset, and the air pressure contribution value QG is obtained using the formula: QG=YP×ky. If the air pressure is greater than or equal to the preset normal air pressure threshold, the air pressure contribution value is zero;

[0067] For the analysis of wind direction environmental parameters, a plane rectangular coordinate system is established with the Y axis parallel to the wire direction and the X axis perpendicular to the wire direction, which is recorded as the wind direction coordinate system; Figure 4 , draw a wind direction line in the wind direction coordinate system parallel to the wind direction, and calculate the angle at which the wind direction line deviates from the acute angle of the Y axis, recorded as the deviation angle XG;

[0068] The wind speed contribution value FG, deviation angle XG, temperature contribution value WG, humidity contribution value SG, air pressure contribution value QG, wire tension contribution value ZG and wire dancing amplitude contribution value WG of the disaster inspection package are normalized and then input into the preset formula model: ZH=FG×a1+XG×a2+WG×a3+SG×a4+QG×a5+ZG×a6+WG×a7, and the disaster assessment value ZH of the disaster inspection package is obtained, where a1, a2, a3, a4, a5, a6, and a7 are preset weight coefficients;

[0069] Obtain the disaster assessment value of the disaster inspection package, preset a disaster assessment threshold, and compare the disaster assessment value of the disaster inspection package with the preset disaster assessment threshold in the order in which the disaster inspection packages are received. If the disaster assessment value of the disaster inspection package is greater than or equal to the preset disaster assessment threshold, it is determined to be a strong wind disaster, and the disaster level is assessed and the conductor tension is adjusted according to the disaster level. During the period of assessing the disaster level and adjusting the conductor tension according to the disaster level, stop the subsequent disaster level assessment process of the disaster inspection package until the disaster level assessment and the conductor tension adjustment operation are completed, and then the strong wind disaster determination and disaster level assessment process are carried out.

[0070] The specific process of evaluating the disaster level and adjusting the conductor tension according to the disaster level is as follows:

[0071] Taking the current time as the starting time, the evaluation period is preset, and the disaster evaluation values ​​of each disaster detection package sent to the disaster detection module within the evaluation period are summed up to obtain the total evaluation value, and an elliptical model is established, such as Figure 3 , taking the total evaluation value as the length of the major axis of the ellipse and the length of the preset evaluation period as the length of the minor axis of the ellipse, draw an ellipse and record it as the evaluation circle, and calculate the area of ​​the evaluation circle and record it as the disaster evaluation value; set three gale disaster levels, divided into level one gale disaster, level two gale disaster and level three gale disaster; each gale disaster level corresponds to a disaster evaluation value interval, and each gale disaster level corresponds to a standard conductor tension value;

[0072] Match the disaster assessment value with the disaster assessment value interval corresponding to the high wind disaster level, and output the corresponding high wind disaster level; find the corresponding standard conductor tension value according to the determined high wind disaster level; and use the conductor tension adjustment device to adjust the conductor tension so that the current conductor tension is consistent with the conductor standard tension value corresponding to the determined high wind disaster level;

[0073] The higher the gale disaster level, the higher the gale disaster risk;

[0074] When it is a level 1 gale disaster, a level 1 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to half of the original;

[0075] When it is a level 2 gale disaster, a level 2 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to one third of the original;

[0076] When a level 3 gale disaster occurs, a level 3 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal. The detection personnel terminal immediately dispatches maintenance personnel to conduct on-site inspections, and reports to the superior power dispatching department and emergency management department, and deploys more emergency repair personnel and materials to the level 3 gale disaster line area on standby, ready to carry out line emergency repair and restoration work at any time.

[0077] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wind disaster monitoring device for transmission and distribution lines based on smart grid, including a sensor module, a data acquisition module, a data processing module, and a disaster detection module; the characteristics are: Sensor module: Environmental sensors are placed on transmission and distribution line towers and conductors to collect environmental parameters; environmental sensors include temperature sensors, humidity sensors, air pressure sensors, wind speed sensors, wind direction sensors, conductor tension sensors, and conductor dancing sensors. Environmental parameters include wind speed, wind direction, temperature, humidity, air pressure, conductor tension, and conductor dancing amplitude; Data acquisition module: controls the environmental sensor to collect environmental parameters, dynamically adjusts the environmental sensor collection frequency, and sends the collected environmental parameters to the data processing module; Data processing module: Integrate environmental parameters at the same collection time into detection data packets, analyze the detection data packets to obtain the total risk value of the detection data packets, determine whether to send them to the disaster detection module based on the total risk value of the detection data packets, and record the detection data packets sent to the disaster detection module as disaster detection packets; verify the completeness of the disaster detection packets before and after they are sent; Disaster detection module: Analyze the environmental parameter data in the disaster inspection package to obtain the disaster assessment value of the disaster inspection package, compare the disaster assessment value of the disaster inspection package with the preset threshold, and if the disaster assessment value of the disaster inspection package is greater than the preset threshold, it is determined to be a strong wind disaster, and the disaster level is evaluated and the conductor tension is adjusted according to the disaster level; The specific process of dynamically adjusting the environmental sensor acquisition frequency is as follows: For each environmental parameter, it is divided into several risk intervals according to its value range. Each risk interval corresponds to a value range of an environmental parameter. Based on the historical environmental parameter data, the degree of correlation between each risk interval and the strong wind disaster is calculated, and a risk value is preset for each risk interval according to the degree of correlation between each risk interval and the strong wind disaster. The preset environmental sensor acquisition frequency is divided into three gears, including: low-frequency acquisition, medium-frequency acquisition and high-frequency acquisition; the working time of the environmental sensor in one day is divided into several detection periods; For each group of detection time periods, the medium frequency acquisition is set as the initial acquisition frequency for parameter acquisition; the environmental parameter values ​​collected at the acquisition time are obtained, the environmental parameter values ​​at the acquisition time are matched with the corresponding risk intervals, the risk assignment corresponding to the risk interval is output, and the risk assignments of all environmental parameters at the same acquisition time are assigned different weight coefficients respectively, and then each risk assignment is weighted to obtain the total risk value, and a curve diagram of the change of the total risk value and time is established, with the total risk value as the vertical axis and time as the horizontal axis. The total risk values ​​corresponding to each acquisition time are connected by curves according to the time sequence to obtain a risk change line, and the preset low-frequency acquisition, medium-frequency acquisition and high-frequency acquisition each correspond to a total risk value interval, which are the low-frequency interval, the medium-frequency interval and the high-frequency interval respectively, and the total risk values ​​corresponding to five consecutive acquisition times centered on the current acquisition time are obtained. If the total risk values ​​corresponding to two or more of the five acquisition times are within the total risk value interval corresponding to the same acquisition frequency, then the acquisition frequency corresponding to the total risk value interval is set to the subsequent acquisition frequency, otherwise the acquisition frequency remains unchanged.

2. The wind disaster monitoring device for transmission and distribution lines based on smart grid according to claim 1 is characterized in that: The specific process of calculating the correlation between each risk interval and the strong wind disaster is as follows: Based on historical environmental parameter data, for each environmental parameter, the environmental parameter value corresponding to the occurrence of strong wind disasters is marked as the wind vane value; then, for each risk interval, each wind vane value is matched with it one by one, and the number of wind vane values ​​falling in each risk interval is counted. The more wind vane values ​​there are in the risk interval, the higher the degree of correlation between the risk interval and strong wind disasters.

3. The wind disaster monitoring device for transmission and distribution lines based on smart grid according to claim 2 is characterized in that: The specific working process of the data processing module is as follows: Integrate the different environmental parameter data received at the same collection time to form a data packet containing complete environmental information, which is recorded as a detection data packet; obtain the total risk value of the detection data packet, preset the total risk threshold of the detection data packet assessment, and compare the total risk value of the detection data packet with the preset total risk threshold of the detection data packet assessment. If the total risk value of the detection data packet is greater than or equal to the preset total risk threshold of the detection data packet assessment, the detection data packet is sent to the disaster detection module, otherwise it is not sent, and the total risk value of the detection data packet at the subsequent collection time is continuously monitored; The detection data packet sent to the disaster detection module is recorded as a disaster detection package. For each disaster detection package, the number of bytes of the disaster detection package is calculated and recorded before it is sent to the disaster detection module. After receiving the package, the disaster detection module recounts the number of bytes and compares it with the number of bytes before sending. If they are the same, it is determined that the disaster detection package data has been sent completely. If they are different, a resending instruction for the disaster detection package is generated.

4. The wind disaster monitoring device for transmission and distribution lines based on smart grid according to claim 3 is characterized in that: The specific process of analyzing the environmental parameter data in the disaster inspection package and obtaining the disaster assessment value of the disaster inspection package is as follows: Extract environmental parameter data from the disaster inspection package; For the analysis of wind speed environmental parameters, a normal wind speed threshold is preset, and the wind speed is compared with the preset normal wind speed threshold. If the wind speed is greater than the preset normal wind speed threshold, the deviation between the wind speed and the normal wind speed threshold is obtained and recorded as the wind deviation value FP. The wind deviation risk contribution coefficient kf is preset, and the wind speed contribution value FG is obtained using the formula: FG=FP×kf. If the wind speed is less than or equal to the preset normal wind speed threshold, the wind speed contribution value is zero; the analysis method for obtaining the wind speed contribution value is marked as the first contribution value analysis method for strong wind disasters; The first contribution value analysis method of strong wind disaster is used to analyze the conductor galloping amplitude, and the conductor galloping amplitude contribution value WG is obtained; For the analysis of temperature environment parameters, a normal temperature value interval is preset, and the temperature is compared with the preset normal temperature value interval. If the temperature is greater than the preset normal temperature value interval, the deviation between the temperature and the previous value of the preset normal temperature value interval is obtained and recorded as the temperature upper deviation value WSP. The temperature contribution value WG is obtained using the formula: FG=WSP×kw1; If the temperature is lower than the preset normal temperature range, the deviation between the temperature and the next value of the preset normal temperature range is recorded as the temperature deviation WXP. The temperature contribution value WG is obtained by using the formula: WG=WXP×kw2, where kw1 and kw2 are the preset temperature contribution coefficients; if the temperature is within the preset normal temperature range, the temperature contribution value is zero; the analysis method for obtaining the temperature contribution value is marked as the second contribution value analysis method for strong wind disasters; The second contribution value analysis method of strong wind disaster is used to analyze humidity and conductor tension, and the humidity contribution value SG and the conductor tension contribution value ZG are obtained; For the analysis of air pressure environment parameters, a normal air pressure threshold is preset, and the air pressure is compared with the preset normal air pressure threshold. If the air pressure is less than the preset normal wind speed threshold, the deviation between the air pressure and the preset normal air pressure threshold is obtained and recorded as the pressure deviation value YP. The pressure deviation risk contribution coefficient ky is preset, and the air pressure contribution value QG is obtained using the formula: QG=YP×ky. If the air pressure is greater than or equal to the preset normal air pressure threshold, the air pressure contribution value is zero; For the analysis of wind direction environmental parameters, a plane rectangular coordinate system is established with the Y axis parallel to the conductor direction and the X axis perpendicular to the conductor direction, which is recorded as the wind direction coordinate system. Draw a wind direction line in the wind direction coordinate system parallel to the wind direction, and calculate the angle at which the wind direction line deviates from the acute angle of the Y axis, which is recorded as the deviation angle XG; The wind speed contribution value FG, deviation angle XG, temperature contribution value WG, humidity contribution value SG, air pressure contribution value QG, conductor tension contribution value ZG and conductor dancing amplitude contribution value WG of the disaster inspection package are normalized and input into the preset formula model: ZH=FG×a1+XG×a2+WG×a3+SG×a4+QG×a5+ZG×a6+WG×a7 to obtain the disaster assessment value ZH of the disaster inspection package, where a1, a2, a3, a4, a5, a6, and a7 are preset weight coefficients.

5. The wind disaster monitoring device for transmission and distribution lines based on smart grid according to claim 4 is characterized in that: The specific process of determining gale disasters is as follows: The disaster assessment value of the disaster inspection package is compared with the preset disaster assessment threshold in the order in which the disaster inspection packages are received. If the disaster assessment value of the disaster inspection package is greater than or equal to the preset disaster assessment threshold, it is determined to be a strong wind disaster, the disaster level is assessed, and the conductor tension is adjusted according to the disaster level. During the period of assessing the disaster level and adjusting the conductor tension according to the disaster level, the subsequent disaster level assessment process of the disaster inspection package is stopped until the disaster level assessment and the conductor tension adjustment operation are completed, and then the strong wind disaster determination and disaster level assessment process are carried out.

6. The wind disaster monitoring device for transmission and distribution lines based on smart grid according to claim 5 is characterized in that: The specific process of evaluating the disaster level and adjusting the conductor tension according to the disaster level is as follows: Taking the current moment as the starting moment, the evaluation period is preset, and the disaster evaluation values ​​of each disaster detection package sent to the disaster detection module within the evaluation period are summed to obtain the total evaluation value, and an ellipse model is established. The size of the total evaluation value is the length of the major axis of the ellipse, and the time length of the preset evaluation period is the length of the minor axis of the ellipse. The ellipse is drawn and recorded as the evaluation circle, and the area of ​​the evaluation circle is calculated and recorded as the disaster evaluation value; three gale disaster levels are set, which are divided into level 1 gale disaster, level 2 gale disaster, and level 3 gale disaster; each gale disaster level corresponds to a disaster evaluation value interval, and each gale disaster level corresponds to a standard conductor tension value; Match the disaster assessment value with the disaster assessment value interval corresponding to the gale disaster level, and output the corresponding gale disaster level; According to the determined gale disaster level, find the corresponding standard tension value of the conductor; The conductor tension adjustment device is used to adjust the conductor tension so that the current conductor tension is consistent with the conductor standard tension value corresponding to the determined gale disaster level; When it is a level 1 gale disaster, a level 1 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to half of the original; When it is a level 2 gale disaster, a level 2 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal, and the detection personnel terminal shortens the inspection cycle to one third of the original; When a level 3 gale disaster occurs, a level 3 disaster alarm signal is generated while adjusting the conductor tension and sent to the detection personnel terminal. The detection personnel terminal immediately dispatches maintenance personnel to conduct on-site inspections, and reports to the superior power dispatching department and emergency management department, and deploys more emergency repair personnel and materials to the level 3 gale disaster line area on standby, ready to carry out line emergency repair and restoration work at any time.

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