Power grid lightning stroke fault risk assessment method and system

Abstract

The invention discloses a power grid lightning stroke fault risk assessment method and system, and relates to the technical field of risk assessment, and the method comprises the following steps: obtaining the operation parameters of a power grid region with dense lightning activities, and constructing a dynamic power grid electrical model considering the load level and reactive compensation influence; obtaining thunder and lightning data and power grid fault data of the current thunder and lightning activity dense power grid area; constructing a lightning stroke fault risk assessment model based on a bp neural network according to the lightning related data and the power grid fault related data; and combining output results of the lightning stroke fault risk assessment model and the dynamic power grid electrical model, simulating power grid operation states and fault risks under different lightning protection strategies, and obtaining a lightning stroke fault risk level. According to the invention, the dynamic power grid electrical model and the lightning stroke fault risk assessment model are constructed to predict and assess the future operation state and the lightning stroke fault risk of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of risk assessment, and more specifically, to a method and system for assessing the risk of lightning faults in a power grid. Background Art

[0002] In today's power system operating environment, the safe and stable operation of the power grid is of vital importance. With the continuous expansion of the scale of the power grid and the increasingly wide coverage area, the risk of lightning strikes on the power grid is also increasing. As a natural phenomenon, lightning strikes have a strong destructive power and can cause serious damage to power grid equipment, thereby causing power grid failures and affecting the reliable supply of electricity.

[0003] In recent years, extreme weather has occurred frequently, and the intensity and frequency of lightning activities have increased. Transmission lines, substations and other facilities in the power grid are often exposed in open areas and are easily targeted by lightning. Once struck by lightning, it may cause line tripping, insulator flashover, equipment damage and other problems, which will not only cause power outages, affect industrial production and residents' lives, but may also trigger a series of chain reactions, posing a threat to the stability of the entire power grid.

[0004] Traditional lightning protection measures for power grids mainly focus on hardware protection, such as installing lightning rods and lightning conductors, but these measures cannot completely prevent the occurrence of lightning faults. Moreover, in the planning, construction and operation of power grids, the assessment of lightning fault risks often lacks systematicity and accuracy. Previous assessment methods may only consider some simple factors, such as lightning density in geographical areas, while ignoring many other key factors that affect the risk of lightning faults, such as the insulation level of the line, the grounding resistance of the tower, the surrounding topography and changes in meteorological conditions. This incomplete assessment method makes it difficult to accurately determine the potential risk of lightning faults in various parts of the power grid, and thus it is impossible to take targeted and effective protection and improvement measures to reduce the damage caused by lightning strikes to the power grid and ensure the safe and stable operation of the power grid.

[0005] The above disclosed technical solutions have at least the following technical problems: the traditional evaluation method is usually based on the static parameters of the power grid, and does not fully consider the dynamic changes in the power grid operation status. The load level, reactive power compensation and other operating conditions of the power grid will affect the voltage distribution and current size of the line, thereby changing the lightning resistance level of the line. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for assessing the risk of lightning faults in a power grid, which solves the problems raised in the above-mentioned background technology by constructing a dynamic power grid electrical model that takes into account the influence of load level and reactive power compensation.

[0007] To achieve the above object, the present invention provides the following technical solutions: A method and system for assessing the risk of lightning faults in power grids, comprising the following steps: obtaining operating parameters of power grid areas with dense lightning activities, and constructing a dynamic power grid electrical model that takes into account the influence of load level and reactive power compensation; obtaining lightning data and power grid fault data in the current power grid areas with dense lightning activities; constructing a lightning fault risk assessment model based on a BP neural network according to lightning-related data and power grid fault-related data; combining the output results of the lightning fault risk assessment model and the dynamic power grid electrical model, simulating the power grid operating status and fault risks under different lightning protection strategies, and obtaining the lightning fault risk level.

[0008] In a preferred embodiment, the method of obtaining operating parameters of a power grid area with dense lightning activity and constructing a dynamic power grid electrical model that takes into account the influence of load level and reactive power compensation is as follows: installing sensors at key nodes of the power grid to obtain operating parameters, wherein the operating parameters include load level, voltage amplitude, and line current; preprocessing the collected power grid operating parameters to remove abnormal values ​​and erroneous data; analyzing the load level data, using cluster analysis and spectrum analysis to identify the characteristics of different types of loads, wherein the characteristics of the load include the size of the load and the power factor; real-time monitoring of the operating status of reactive power compensation equipment in the power grid, wherein the operating status includes the switching status, reactive output, and operating parameters of the equipment, wherein the operating parameters include the capacitance value of the capacitor and the reactance value of the reactor; obtaining the power grid topology in the area with dense lightning activity, and abstracting the power grid into a node-branch model, wherein the node represents the substation bus and the line connection point, and the branch represents the transmission line and the transformer; according to the collected power grid operating parameters, setting the initial voltage amplitude and phase angle and classifying the node types, wherein the node types include PQ nodes, PV nodes and balance nodes; establish a transmission line model based on the resistance, inductance, capacitance and conductance per unit length of the transmission line; construct a load model based on an exponential model based on load data and load power factor; for capacitor banks, establish a reactive compensation device model that shows the relationship between its capacitance value and reactive power output; connect and integrate the transmission line model, load model and reactive compensation device model according to the actual topological structure of the power grid to form a complete dynamic power grid electrical model.

[0009] In a preferred embodiment, the lightning data includes a lightning energy density coefficient and a lightning activity frequency coefficient; the power grid fault data includes a line tripping action coefficient; the specific method for obtaining the lightning energy density coefficient is as follows: a voltage signal proportional to the lightning current change rate is measured by a Rogowski coil sensor, and the voltage signal is converted into an output signal proportional to the lightning current by an integrating circuit to obtain a lightning current change curve over time; according to the lightning current change curve, the amplitude, wavefront time and half-peak time of the lightning current are analyzed and obtained; the lightning channel resistance is calculated based on the air humidity, temperature, and amplitude of the lightning current in the lightning activity-intensive power grid area combined with the basic resistance; the total amount of lightning energy is calculated based on the lightning current change curve over time and the lightning channel resistance; the spatial range of lightning action is obtained according to the type of lightning strike and the lightning strike object, the type of lightning strike includes direct lightning or induction lightning, and the lightning strike object includes transmission lines and substations; the total amount of lightning energy and the spatial range of lightning action are combined with the wavefront time and the half-peak time into the lightning energy density coefficient calculation formula to obtain the lightning energy density coefficient.

[0010] In a preferred embodiment, the specific method for obtaining the lightning activity frequency coefficient is as follows: obtaining the area data and thunderstorm hour data of the power grid area with dense lightning activity; using a lightning positioning system to receive the electromagnetic signal generated by lightning return strokes, and obtaining the location, time information and number of thunderstorm days of the lightning strike point by a signal arrival time difference method; counting the total number of lightning occurrences in the target area within a selected time range, and removing misjudgment data; calculating the lightning frequency index based on the time information of each lightning strike and the thunderstorm hour data; calculating the lightning activity frequency coefficient based on a preset lightning activity frequency coefficient calculation formula by combining the total number of lightning occurrences, area data, and number of thunderstorm days with the lightning frequency index.

[0011] In a preferred embodiment, the specific method for obtaining the line tripping action coefficient is as follows: Obtain historical tripping records of lines in a power grid area with dense lightning activity, wherein the historical tripping records include the specific time of each tripping and the duration of the tripping; calculate the line tripping action frequency according to the total operation time of the line and the number of tripping caused by lightning strikes; obtain and obtain the line aging influence factor based on regression analysis according to the insulation condition and maintenance record of the line; obtain the line tripping action coefficient based on the line aging influence factor, the line tripping action frequency and the tripping duration, and the load before the line fault based on the line tripping action coefficient calculation formula.

[0012] In a preferred embodiment, the output results of the lightning fault risk assessment model and the dynamic power grid electrical model are combined to simulate the power grid operation status and fault risk under different lightning protection strategies to obtain the lightning fault risk level, specifically: obtaining the lightning fault risk assessment coefficient from the lightning fault risk assessment model, and obtaining the voltage, current, power, power factor operation parameters of the power grid, as well as the load level and reactive power compensation status from the dynamic power grid electrical model; establishing an associated database according to the sorted data based on the topological structure and equipment number of the power grid; selecting a lightning protection strategy combination for different power grid areas and equipment based on the lightning fault history data and the actual operating environment, the lightning protection strategy includes installing a lightning protection system. Lightning wires, lightning arresters, reducing the grounding resistance of poles and towers, and optimizing line insulation configuration; using the power system simulation software ATP-EMTP to integrate the lightning fault risk assessment model and the dynamic power grid electrical model; based on the lightning fault risk assessment coefficient provided by the lightning fault risk assessment model, randomly generate lightning events in the simulation platform, and combine the electromagnetic coupling theory of lightning and power grid to calculate the overvoltage and overcurrent distribution generated in the power grid at the moment of lightning strike; determine whether a lightning fault occurs based on the insulation tolerance level of the power grid equipment and the overvoltage and overcurrent data obtained by simulation; if a lightning strike occurs, use the risk matrix method, combined with the fault statistical results and power grid operation status data, to obtain the lightning fault risk level.

[0013] In a preferred embodiment, the risk matrix method is used to combine the fault statistics and the power grid operation status data to obtain the risk level of the lightning fault, specifically: create a two-dimensional table, the horizontal axis represents the possibility level of the fault, the vertical axis represents the severity level of the fault consequences, and the entire table is divided into different areas, each area corresponds to a different risk level; if the lightning fault risk assessment coefficient is less than the first threshold, the possibility level of the fault is set to a low level; if the lightning fault risk assessment coefficient is greater than the first threshold and less than the second threshold, the possibility level of the fault is set to a medium level; if the lightning fault risk assessment coefficient is greater than the second threshold, the possibility level of the fault is set to a high level; combined with the power outage scope caused by past lightning faults in the fault statistics, the type of users affected, the maintenance cost, etc., the level corresponding to the severity of the consequences of the lightning fault is obtained; through the possibility level of the fault and the severity level of the fault consequences, the corresponding intersection area is found in the constructed risk matrix table to obtain the lightning fault risk level.

[0014] The technical effects and advantages of a power grid lightning fault risk assessment method and system of the present invention are as follows: 1. The present invention not only takes into account the current grid operation status and lightning activity, but also predicts and evaluates the future grid operation status and lightning fault risk by constructing a dynamic grid electrical model and a lightning fault risk assessment model. This foresight enables grid managers to understand the potential risks of the grid in advance and take corresponding measures to prevent them. At the same time, the method also takes into account the insulation tolerance level of grid equipment and the overvoltage and overcurrent data obtained by simulation, as well as fault statistics and grid operation status data, providing strong support for the sustainable development of the grid.

[0015] 2. The present invention can simulate the operation status and failure risk of the power grid under different circumstances according to different lightning protection strategies, and has strong dynamic adaptability. This helps power grid managers to timely understand the weak links of the power grid, formulate effective lightning protection measures, and improve the safety and stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a schematic structural diagram of a method for assessing the risk of lightning faults in a power grid.

[0017] Figure 2 The present invention is a schematic diagram of the structure of a power grid lightning fault risk assessment system. DETAILED DESCRIPTION

[0018] 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.

[0019] Embodiment 1, Figure 1 The present invention provides a method for assessing the risk of lightning faults in a power grid, comprising the following steps: S1, obtain the operating parameters of the power grid area with intensive lightning activities, and build a dynamic power grid electrical model considering the load level and the influence of reactive power compensation; Based on high-resolution weather radar data and satellite cloud images, combined with geographic information systems, we can find power grid areas with dense lightning activity; Meteorological radar can provide high-precision weather information, including precipitation, wind field, turbulence, etc. In lightning monitoring, meteorological radar can detect the scattered signals of precipitation particles generated by lightning activity, thereby indirectly reflecting the location and intensity of lightning activity.

[0020] Satellite cloud images can display the distribution and evolution of clouds in the atmosphere. By analyzing parameters such as cloud top height, brightness, and temperature on satellite cloud images, thunderstorm clouds can be identified and the possible location and intensity of lightning activity can be determined.

[0021] GIS can store, manage and analyze spatial data. By importing meteorological radar data and satellite cloud map data into GIS, data visualization and comprehensive analysis can be achieved.

[0022] The obtaining of the power grid area with dense lightning activities is specifically: Divide the power grid into different areas according to its geographical distribution and topological structure; The location and intensity of lightning activity can be obtained by detecting the scattered signals of precipitation particles generated by lightning activity through weather radar; By analyzing the cloud top height, brightness, and temperature parameters on satellite cloud images, thunderstorm clouds can be identified and the location and intensity of lightning activities can be determined; By importing weather radar data and satellite cloud image data into GIS, the number and intensity of lightning activities in each power grid area are counted, and the density of lightning activities is obtained through weighted calculation; Based on the calculation results of lightning activity density, areas with dense lightning activity are marked out.

[0023] The acquisition of operating parameters of a power grid area with dense lightning activity and the construction of a dynamic power grid electrical model taking into account the influence of load level and reactive power compensation are specifically as follows: Install sensors at key nodes of the power grid to obtain operating parameters, including load level, voltage amplitude, and line current; Preprocess the collected power grid operation parameters to remove abnormal values ​​and erroneous data; Analyze the load level data and use cluster analysis and spectrum analysis to identify the characteristics of different types of loads, wherein the characteristics of the loads include the size of the loads and the power factor; Real-time monitoring of the operating status of reactive power compensation equipment in the power grid, the operating status including switching status, reactive power output, and operating parameters of the equipment, the operating parameters including the capacitance value of the capacitor and the reactance value of the reactor; Obtain the topological structure of the power grid in the area with dense lightning activity, and abstract the power grid into a node-branch model, where nodes represent substation buses and line connection points, and branches represent transmission lines and transformers; According to the collected grid operation parameters, the initial voltage amplitude and phase angle are set and the node types are classified, including PQ nodes (known active and reactive power), PV nodes (known active power and voltage amplitude) and balancing nodes (usually large-capacity substation buses in the grid, whose voltage amplitude and phase angle are known); Establish a transmission line model based on the resistance, inductance, capacitance and conductance per unit length of the transmission line; Construct a load model based on an exponential model according to load data combined with load power factor; For capacitor banks, a reactive power compensation equipment model is established to show the relationship between the capacitance value and reactive power output; The models of the above components are connected and integrated according to the actual topological structure of the power grid to form a complete dynamic power grid electrical model.

[0024] The specific calculation formula of the transmission line model is:

[0025] The specific calculation formula of the load model is:

[0026] The specific calculation formula of the reactive power compensation equipment model is:

[0027] Among them, R is resistance, L is inductance, A is capacitance, G is conductance, P is active power, Q is reactive power, and Rated voltage The active and reactive power under is the actual voltage, and is the load characteristic index, is the angular frequency, It is reactive output.

[0028] S3, obtaining lightning-related data and power grid fault-related data in the power grid area with dense lightning activity; The lightning data includes lightning energy density coefficient and lightning activity frequency coefficient; the power grid fault data includes line tripping action coefficient; The lightning energy density coefficient is a key indicator to measure the density of lightning energy distribution in a certain space. It indicates the amount of energy contained in lightning per unit volume or unit area, and is usually closely related to factors such as lightning intensity, duration, and scope of action.

[0029] The specific method for obtaining the lightning energy density coefficient is as follows: The voltage signal proportional to the rate of change of the lightning current is measured by the Rogowski coil sensor, and the voltage signal is converted into an output signal proportional to the lightning current by the integration circuit to obtain the curve of the change of the lightning current over time; According to the lightning current change curve, the lightning current amplitude, wavefront time (the time for the lightning current to rise from 0 to the peak value) and half-peak time (the time for the lightning current to drop from the peak value to half the peak value) are analyzed and obtained; The lightning channel resistance is calculated based on the air humidity, temperature, and lightning current amplitude in the lightning-intensive power grid area combined with the basic resistance; The total amount of lightning energy is calculated based on the curve of lightning current changing with time and the resistance of the lightning strike channel; The spatial range of the lightning action is obtained according to the type of lightning strike and the lightning strike object, wherein the type of lightning strike includes direct lightning strike or induction lightning strike, and the lightning strike object includes a power transmission line and a substation; The total amount of lightning energy, the spatial range of lightning action, the wavefront time and the half-peak time are input into the lightning energy density coefficient calculation formula to obtain the lightning energy density coefficient.

[0030] The specific calculation formula of the lightning channel resistance is:

[0031] The specific calculation formula for the total amount of lightning energy is:

[0032] The specific calculation formula of the lightning energy density coefficient is:

[0033] in, is the lightning channel resistance, is the basic resistor, is the amplitude of lightning current, is the ambient humidity, is the ambient temperature, is the magnitude of the i-th lightning current, is the total number of measurements, is the change time of lightning current, is the lightning energy density coefficient, is the total amount of lightning energy, is the maximum lightning current, The radius of action is, is the length of the transmission line affected by lightning, is the wavefront time, is the half peak time.

[0034] The benefits of lightning energy density coefficient for power grid lightning fault risk assessment are mainly reflected in the following aspects: Accurately assess the risk level of lightning strikes: The lightning energy density coefficient provides the distribution of lightning energy in the area where power grid equipment is in action. This indicator can be used to estimate the intensity and range of lightning strikes in a certain area, thereby helping power grid operators assess the lightning strike risks faced by different areas. For example, in areas with frequent lightning activity or high energy density, power grid equipment (such as transmission lines, substations, etc.) is more likely to be struck by lightning. The lightning energy density coefficient can reveal such high-risk areas and provide data support for power grid companies to take protective measures in advance.

[0035] Optimizing the lightning protection design of power grids: The lightning energy density coefficient is closely related to the lightning protection design of power grids. When designing a power grid, it is necessary to consider possible lightning currents and their energy distribution to ensure that the equipment can withstand possible lightning strikes. Accurate calculation and analysis of the lightning energy density coefficient can help designers optimize the lightning protection capabilities of power grid equipment, reasonably configure lightning arresters, protective grounding systems and other facilities, and reduce the damage caused by lightning strikes. For example, areas with higher lightning energy density coefficients may require more dense lightning arresters and stronger grounding system designs.

[0036] Determine the probability of failure and preventive maintenance strategy: The lightning energy density coefficient can help predict the probability and severity of lightning-induced power grid failures. By combining information such as the amplitude and wavefront time of the lightning current, we can understand the impact that lightning events may have on power grid equipment, thereby formulating a more accurate preventive maintenance plan.

[0037] Lightning fault simulation and emergency response: The data provided by the lightning energy density coefficient is helpful for conducting lightning fault simulation and simulating the impact that lightning attacks may have on the power grid (such as line tripping, equipment damage, etc.). Based on such simulation results, power grid operators can develop detailed emergency response plans to ensure timely restoration of power supply in lightning weather and reduce the impact of system failures on users.

[0038] Improved power grid monitoring and lightning warning: The lightning energy density coefficient can be combined with real-time meteorological data (such as lightning frequency, lightning current intensity, etc.) to improve the monitoring and lightning warning capabilities of the power grid. By continuously monitoring the energy density changes in lightning activity areas, power grid companies can issue lightning warnings in a timely manner, take effective protective measures, and reduce the risks of lightning disasters.

[0039] The lightning activity frequency coefficient usually refers to the ratio of the number of lightning occurrences within a certain time and space range to the area of ​​the region or other relevant parameters. It can intuitively reflect the frequency of lightning activity in a specific area and provide an important basis for lightning protection, power system design and operation, meteorological research, etc.

[0040] The specific method for obtaining the lightning activity frequency coefficient is as follows: Obtain area data and thunderstorm hour data of power grid areas with dense lightning activity; The lightning location system is used to receive the electromagnetic signal generated by lightning return stroke, and the location, time information and number of thunderstorm days of the lightning strike point are obtained by using the signal arrival time difference method; Count the total number of lightning occurrences in the target area within the selected time range and remove misjudged data; Calculate the lightning frequency index based on the time information of each lightning strike and thunderstorm hour data; The total number of lightning occurrences, area data, and number of thunderstorm days are combined with the lightning frequency index to calculate the lightning activity frequency coefficient based on the preset lightning activity frequency coefficient calculation formula.

[0041] The specific calculation formula of the lightning activity frequency coefficient is:

[0042] in, is the lightning activity frequency coefficient, is the influence coefficient of thunderstorm hour, is the total number of lightning occurrences, is the area data of the power grid area, is the number of thunderstorm days, For thunderstorm hours, is the duration of the ith thunderstorm.

[0043] The benefits of lightning activity frequency coefficient for power grid lightning fault risk assessment are mainly reflected in the following aspects: Lightning risk assessment and protection planning: The lightning activity frequency coefficient can quantify the frequency of lightning in a specific area and provide data support for lightning risk assessment in the power grid. When designing lightning protection measures for the power grid, the possibility of lightning strikes in the area where the power grid is located can be assessed based on the lightning activity frequency coefficient, and lightning protection devices such as lightning arresters and grounding systems can be reasonably arranged. Areas with high-frequency lightning activity require enhanced protection design to avoid equipment damage and shutdown caused by lightning strikes.

[0044] Optimize power system design: During the design phase of the power system, the lightning activity frequency coefficient can help determine the design standards for power grid facilities in different regions. For example, for areas with frequent lightning activity, more lightning protection design elements and redundant measures need to be considered to improve the system's ability to resist lightning strikes. By counting the frequency and spatial distribution of lightning, power designers can reasonably select the type, quantity and layout of lightning protection equipment to ensure the safety and reliability of the system.

[0045] Auxiliary operation and maintenance management: Through dynamic monitoring of the lightning activity frequency coefficient, the operation and maintenance personnel can timely grasp the changes in lightning activity in the area where the power grid is located. Once lightning activity is frequent, the operation and maintenance department can give early warnings and strengthen the inspection and maintenance of power equipment to reduce failures caused by lightning strikes. For example, when the monitoring detects that the frequency of lightning activity in a certain area has increased significantly, the operation and maintenance personnel can increase the frequency of inspections of substations, transmission lines and other equipment in the area to prevent equipment failures or shutdowns caused by lightning strikes.

[0046] Lightning fault prediction and emergency response: The lightning activity frequency coefficient can also help power grid companies to predict faults and prepare for emergency response. In periods when lightning strikes frequently occur, the coefficient can be used to predict which areas may experience more lightning strike faults and formulate emergency response plans in advance. In this way, when a lightning strike occurs, the power grid company can respond quickly to avoid large-scale power outages or long-term damage to equipment.

[0047] Improve the reliability and stability of the power grid: By calculating the lightning activity frequency coefficient, the power system can make a more accurate risk assessment of lightning faults, so as to take corresponding protection and reinforcement measures. This can not only effectively reduce the impact of lightning on the power grid system, but also improve the reliability and stability of the power grid under extreme weather conditions, and ensure the continuity of power supply, especially in the high-incidence season of lightning and in areas with high lightning activity.

[0048] The line tripping action coefficient is an indicator used to evaluate the frequency of tripping actions of transmission lines in the face of lightning strikes. It is of great significance in line operation and maintenance and power grid security assessment. The higher the coefficient, the more frequent the line trips, which may indicate that the line has many problems such as insulation aging, insufficient lightning protection measures, and large interference from the external environment. A lower coefficient means that the line can maintain good stability when facing lightning strikes, and the reliability of normal power supply is higher.

[0049] The specific method for obtaining the line tripping action coefficient is as follows: Obtaining historical tripping records of lines in a power grid area with dense lightning activity, wherein the historical tripping records include the specific time and duration of each tripping; Calculate the line tripping frequency based on the total operation time of the line and the number of tripping caused by lightning strikes; Obtain and obtain the line aging influencing factors based on the insulation condition and maintenance records of the line through regression analysis; According to the line aging influencing factor, line tripping action frequency and tripping duration, the line load before the fault is combined and the line tripping action coefficient is calculated based on the line tripping action coefficient calculation formula to obtain the line tripping action coefficient.

[0050] The specific calculation formula of the line aging influencing factor is:

[0051] The specific calculation formula of the line tripping action coefficient is:

[0052] in, is the line aging influencing factor, Insulation condition indicator. is the number of line maintenance times, is the operating life of the line, The designed operating life of the line, is the line tripping action coefficient, is the number of trips caused by lightning strikes, is the total running time of the statistical line, is the duration of the ith trip, is the load before the line fault, The maximum permissible load on the line.

[0053] S3, constructing a lightning fault risk assessment model based on the BP neural network according to lightning related data and power grid fault related data; The lightning fault risk assessment model is specifically:

[0054] in is the lightning fault risk assessment coefficient, is the lightning energy density coefficient, is the lightning activity frequency coefficient, is the line tripping action coefficient, is the preset lightning energy density coefficient weight factor, is the preset lightning activity frequency coefficient weight factor, It is the preset line tripping action coefficient weight factor.

[0055] S4, combining the output results of the lightning fault risk assessment model and the dynamic power grid electrical model, simulating the power grid operation status and fault risk under different lightning protection strategies, and obtaining the lightning fault risk level; The output results of the lightning fault risk assessment model and the dynamic power grid electrical model are combined to simulate the power grid operation status and fault risk under different lightning protection strategies to obtain the lightning fault risk level, which is specifically: Obtain the lightning fault risk assessment coefficient from the lightning fault risk assessment model, and obtain the voltage, current, power, power factor operating parameters of the power grid, as well as the load level and reactive power compensation status from the dynamic power grid electrical model; Establish a related database based on the organized data according to the topological structure of the power grid and the equipment number; For different power grid areas and equipment, according to the historical data of lightning faults and the actual operating environment, a combination of lightning protection strategies is selected, which includes installing lightning conductors, lightning arresters, reducing the grounding resistance of towers, and optimizing the line insulation configuration; Using the power system simulation software ATP-EMTP, the lightning fault risk assessment model and the dynamic power grid electrical model are integrated; According to the lightning fault risk assessment coefficient provided by the lightning fault risk assessment model, lightning events are randomly generated in the simulation platform, and the overvoltage and overcurrent distribution generated in the power grid at the moment of lightning strike are calculated by combining the electromagnetic coupling theory of lightning and power grid; Determine whether a lightning fault has occurred based on the insulation tolerance level of the power grid equipment and the overvoltage and overcurrent data obtained through simulation; If a lightning strike occurs, the risk matrix method is used to combine the fault statistics results and the power grid operation status data to obtain the lightning strike fault risk level.

[0056] The risk matrix method is used to combine the fault statistics and the grid operation status data to obtain the lightning fault risk level, which is specifically: Create a two-dimensional table, with the horizontal axis representing the probability of failure and the vertical axis representing the severity of the consequences of the failure. Divide the entire table into different areas, each corresponding to a different risk level; If the lightning fault risk assessment coefficient is less than the first threshold, the possibility level of the fault occurrence is set to a low level; If the lightning fault risk assessment coefficient is greater than the first threshold and less than the second threshold, the probability level of the fault occurrence is determined to be medium; If the lightning fault risk assessment coefficient is greater than the second threshold, the possibility level of the fault occurrence is set to a high level; Combined with the power outage scope, affected user types, and repair costs caused by past lightning faults in the fault statistics, the severity level of the consequences of a lightning fault is obtained; According to the fault probability level and fault consequence severity level, the corresponding intersection area is found in the constructed risk matrix table to obtain the lightning fault risk level.

[0057] It should be noted that if either the fault occurrence possibility level or the fault consequence severity level is high, the final lightning fault risk level is also high; if both the fault occurrence possibility level and the fault consequence severity level are low, the final lightning fault risk level is low; otherwise, the final lightning fault risk level is medium.

[0058] Embodiment 2, Figure 2 The present invention provides a power grid lightning fault risk assessment system, which includes the following modules: a dynamic model construction module, a lightning grid data acquisition module, a lightning fault risk assessment model construction module and a lightning fault risk level determination module; Dynamic model building module: obtains the operating parameters of the power grid area with intensive lightning activities, and builds a dynamic power grid electrical model that takes into account the impact of load level and reactive power compensation; Lightning grid data acquisition module: obtains lightning data and grid fault data in the grid area with dense lightning activity; Lightning fault risk assessment model construction module: constructs a lightning fault risk assessment model based on BP neural network according to lightning related data and power grid fault related data; Lightning fault risk level determination module: Combines the output results of the lightning fault risk assessment model and the dynamic power grid electrical model, simulates the power grid operation status and fault risk under different lightning protection strategies, and obtains the lightning fault risk level.

[0059] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0060] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0061] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0062] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0063] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0064] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for assessing the risk of lightning failure in a power grid, characterized in that: The following steps are involved: Obtain the operating parameters of power grid areas with intensive lightning activity, and build a dynamic power grid electrical model that takes into account the impact of load level and reactive power compensation; Obtain lightning data and power grid fault data in power grid areas with dense lightning activity; According to lightning related data and power grid fault related data, a lightning fault risk assessment model is constructed based on BP neural network; The output results of the lightning fault risk assessment model and the dynamic power grid electrical model are combined to simulate the power grid operation status and fault risk under different lightning protection strategies to obtain the lightning fault risk level.

2. A method for assessing the risk of lightning failure in a power grid according to claim 1, characterized in that: The acquisition of operating parameters of a power grid area with dense lightning activity and the construction of a dynamic power grid electrical model taking into account the influence of load level and reactive power compensation are specifically as follows: Install sensors at key nodes of the power grid to obtain operating parameters, including load level, voltage amplitude, and line current; Preprocess the collected power grid operation parameters to remove abnormal values ​​and erroneous data; Analyze the load level data and use cluster analysis and spectrum analysis to identify the characteristics of different types of loads, wherein the characteristics of the loads include the size of the loads and the power factor; Real-time monitoring of the operating status of reactive power compensation equipment in the power grid, the operating status including switching status, reactive power output, and operating parameters of the equipment, the operating parameters including the capacitance value of the capacitor and the reactance value of the reactor; Obtain the topological structure of the power grid in the area with dense lightning activity, and abstract the power grid into a node-branch model, where nodes represent substation buses and line connection points, and branches represent transmission lines and transformers; According to the collected grid operation parameters, the initial voltage amplitude and phase angle are set and the node types are classified, wherein the node types include PQ nodes, PV nodes and balancing nodes; Establish a transmission line model based on the resistance, inductance, capacitance and conductance per unit length of the transmission line; Construct a load model based on an exponential model according to load data combined with load power factor; For capacitor banks, a reactive power compensation equipment model is established to show the relationship between the capacitance value and reactive power output; The transmission line model, load model and reactive power compensation equipment model are connected and integrated according to the actual topological structure of the power grid to form a complete dynamic power grid electrical model.

3. A method for assessing the risk of lightning failure in a power grid according to claim 2, characterized in that: The lightning data includes lightning energy density coefficient and lightning activity frequency coefficient; the power grid fault data includes line tripping action coefficient; The specific method for obtaining the lightning energy density coefficient is as follows: The voltage signal proportional to the rate of change of the lightning current is measured by the Rogowski coil sensor, and the voltage signal is converted into an output signal proportional to the lightning current by the integration circuit to obtain the curve of the change of the lightning current over time; According to the lightning current variation curve, the amplitude, wavefront time and half-peak time of lightning current are analyzed and obtained; The lightning channel resistance is calculated based on the air humidity, temperature, and lightning current amplitude in the lightning-intensive power grid area combined with the basic resistance; The total amount of lightning energy is calculated based on the curve of lightning current changing with time and the resistance of the lightning strike channel; The spatial range of the lightning action is obtained according to the type of lightning strike and the lightning strike object, wherein the type of lightning strike includes direct lightning strike or induction lightning strike, and the lightning strike object includes a power transmission line and a substation; The total amount of lightning energy, the spatial range of lightning action, the wavefront time and the half-peak time are input into the lightning energy density coefficient calculation formula to obtain the lightning energy density coefficient.

4. A method for assessing the risk of lightning failure in a power grid according to claim 3, characterized in that: The specific method for obtaining the lightning activity frequency coefficient is as follows: Obtain area data and thunderstorm hour data of power grid areas with dense lightning activity; The lightning location system is used to receive the electromagnetic signal generated by lightning return stroke, and the location, time information and number of thunderstorm days of the lightning strike point are obtained by using the signal arrival time difference method; Count the total number of lightning occurrences in the target area within the selected time range and remove misjudged data; Calculate the lightning frequency index based on the time information of each lightning strike and thunderstorm hour data; The total number of lightning occurrences, area data, and number of thunderstorm days are combined with the lightning frequency index to calculate the lightning activity frequency coefficient based on the preset lightning activity frequency coefficient calculation formula.

5. A method for assessing the risk of lightning failure in a power grid according to claim 4, characterized in that: The specific method for obtaining the line tripping action coefficient is as follows: Obtaining historical tripping records of lines in a power grid area with dense lightning activity, wherein the historical tripping records include the specific time and duration of each tripping; Calculate the line tripping frequency based on the total operation time of the line and the number of tripping caused by lightning strikes; Obtain and obtain the line aging influencing factors based on the insulation condition and maintenance records of the line through regression analysis; According to the line aging influencing factor, line tripping action frequency and tripping duration, the line load before the fault is combined and the line tripping action coefficient is calculated based on the line tripping action coefficient calculation formula to obtain the line tripping action coefficient.

6. A method for assessing the risk of lightning failure in a power grid according to claim 5, characterized in that: The output results of the lightning fault risk assessment model and the dynamic power grid electrical model are combined to simulate the power grid operation status and fault risk under different lightning protection strategies to obtain the lightning fault risk level, which is specifically: Obtain the lightning fault risk assessment coefficient from the lightning fault risk assessment model, and obtain the voltage, current, power, power factor operating parameters of the power grid, as well as the load level and reactive power compensation status from the dynamic power grid electrical model; Establish a related database based on the organized data according to the topological structure of the power grid and the equipment number; For different power grid areas and equipment, according to the historical data of lightning faults and the actual operating environment, a combination of lightning protection strategies is selected, which includes installing lightning conductors, lightning arresters, reducing the grounding resistance of towers, and optimizing the line insulation configuration; Using the power system simulation software ATP-EMTP, the lightning fault risk assessment model and the dynamic power grid electrical model are integrated; According to the lightning fault risk assessment coefficient provided by the lightning fault risk assessment model, lightning events are randomly generated in the simulation platform, and the overvoltage and overcurrent distribution generated in the power grid at the moment of lightning strike are calculated by combining the electromagnetic coupling theory of lightning and power grid; Determine whether a lightning fault has occurred based on the insulation tolerance level of the power grid equipment and the overvoltage and overcurrent data obtained through simulation; If a lightning strike occurs, the risk matrix method is used to combine the fault statistics results and the power grid operation status data to obtain the lightning strike fault risk level.

7. A method for assessing the risk of lightning failure in a power grid according to claim 6, characterized in that: The risk matrix method is used to combine the fault statistics and the grid operation status data to obtain the lightning fault risk level, which is specifically: Create a two-dimensional table, with the horizontal axis representing the probability of failure and the vertical axis representing the severity of the consequences of the failure. Divide the entire table into different areas, each corresponding to a different risk level; If the lightning fault risk assessment coefficient is less than the first threshold, the possibility level of the fault occurrence is set to a low level; If the lightning fault risk assessment coefficient is greater than the first threshold and less than the second threshold, the probability level of the fault occurrence is determined to be medium; If the lightning fault risk assessment coefficient is greater than the second threshold, the possibility level of the fault occurrence is set to a high level; Combined with the power outage scope, affected user types, and repair costs caused by past lightning faults in the fault statistics, the severity level of the consequences of a lightning fault is obtained; According to the fault probability level and fault consequence severity level, the corresponding intersection area is found in the constructed risk matrix table to obtain the lightning fault risk level.

8. A method for assessing the risk of lightning failure in a power grid according to claim 7, characterized in that: The specific calculation formula of the lightning channel resistance is: The specific calculation formula for the total amount of lightning energy is: The specific calculation formula of the lightning energy density coefficient is: in, is the lightning channel resistance, is the basic resistor, is the amplitude of lightning current, is the ambient humidity, is the ambient temperature, is the magnitude of the i-th lightning current, is the total number of measurements, is the change time of lightning current, is the lightning energy density coefficient, is the total amount of lightning energy, is the maximum lightning current, The radius of action is, is the length of the transmission line affected by lightning, is the wavefront time, is the half peak time.

9. A method for assessing the risk of lightning failure in a power grid according to claim 8, characterized in that: The specific calculation formula of the line aging influencing factor is: The specific calculation formula of the line tripping action coefficient is: in, is the line aging influencing factor, Insulation condition indicator. is the number of line maintenance times, is the operating life of the line, The designed operating life of the line, is the line tripping action coefficient, is the number of trips caused by lightning strikes, is the total running time of the statistical line, is the duration of the ith trip, is the load before the line fault, The maximum permissible load on the line.

10. A system using a power grid lightning fault risk assessment method according to any one of claims 1 to 9, characterized in that: It includes the following modules: dynamic model building module, lightning power grid data acquisition module, lightning fault risk assessment model building module and lightning fault risk level determination module; Dynamic model building module: obtains the operating parameters of the power grid area with intensive lightning activities, and builds a dynamic power grid electrical model that takes into account the impact of load level and reactive power compensation; Lightning grid data acquisition module: obtains lightning data and grid fault data in the grid area with dense lightning activity; Lightning fault risk assessment model construction module: builds a lightning fault risk assessment model based on BP neural network according to lightning related data and power grid fault related data; Lightning fault risk level determination module: Combines the output results of the lightning fault risk assessment model and the dynamic power grid electrical model, simulates the power grid operation status and fault risk under different lightning protection strategies, and obtains the lightning fault risk level.

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