Intelligent configuration method and system for power grid overcurrent protection device

Abstract

The invention relates to the technical field of power grid overcurrent protection, and discloses an intelligent configuration method and system for a power grid overcurrent protection device. The method comprises the steps of collecting power grid data, and performing cleaning conversion to obtain a standardized topology database; setting a virtual fault point, and calculating short-circuit current characteristics to generate a fault feature library; extracting a protection pairing relationship, and constructing a constraint condition set; optimizing parameters of the protection device to form a configuration scheme; performing simulation verification to generate an action sequence diagram and a coordination report; and converting the parameters into a device format, and safely issuing the parameters to implement configuration. By establishing the intelligent configuration method based on the real-time data of the power grid and combining an advanced optimization algorithm and a comprehensive simulation verification mechanism, the scheme can significantly improve the accuracy, adaptability and reliability of protection configuration, reduce manual intervention and adapt to the development requirements of the modern intelligent power grid.

Description

Technical Field

[0001] This application relates to the technical field of power grid overcurrent protection, and particularly to an intelligent configuration method and system for power grid overcurrent protection devices. Background Art

[0002] Power grid overcurrent protection is the most basic and widely used protection form in the power system, mainly used to detect overcurrent faults in power lines and equipment and timely disconnect the fault area to prevent the expansion of faults. The traditional configuration method of power grid overcurrent protection devices mainly relies on engineers to manually calculate and set protection parameters according to experience, including action current thresholds and time delay parameters, etc. This configuration method usually adopts fixed calculation formulas and empirical values, and at the same time considers factors such as power grid topology structure, equipment parameters, and fault current distribution characteristics, and combines protection coordination principles for parameter setting. With the development of smart grid technology, some computer-aided protection configuration methods have been gradually applied, such as setting software using simple optimization algorithms, protection configuration tools based on expert systems, etc. These methods have improved the efficiency and accuracy of protection configuration to a certain extent.

[0003] However, the existing configuration methods of power grid overcurrent protection devices still have many deficiencies. First, the traditional manual configuration method highly depends on the experience and judgment of engineers, and it is difficult to cope with the multi-variable optimization problem under complex power grid structures, often resulting in conservative or sub-optimal protection configurations. Second, the existing computer-aided methods usually only optimize for specific network structures or simplified models, lacking the adaptability to the changing conditions of the actual power grid, especially performing poorly in cases such as dynamic changes in power grid topology and increasing penetration of renewable energy. In addition, most of the existing methods lack a comprehensive simulation verification mechanism, making it difficult to evaluate the coordination reliability of protection parameters under extreme conditions, increasing the risk of protection misoperation or refusal to operate. Finally, the traditional configuration method is usually a one-time static process, lacking an adaptive adjustment mechanism and unable to dynamically optimize protection parameters according to changes in the power grid operation state, restricting the intelligent level of the protection system. Summary of the Invention

[0004] This application provides an intelligent configuration method and system for power grid overcurrent protection devices. By establishing an intelligent configuration method based on real-time power grid data, combined with advanced optimization algorithms and a comprehensive simulation verification mechanism, this solution can significantly improve the accuracy, adaptability, and reliability of protection configuration, reduce manual intervention, and meet the development needs of modern smart grids.

[0005] In a first aspect, the present application provides an intelligent configuration method for a power grid overcurrent protection device. The intelligent configuration method for the power grid overcurrent protection device includes: collecting the connection relationships and operating parameters of buses, lines, and transformers through a power grid monitoring system, cleaning and unit-converting the collected data to obtain a standardized power grid topology database; setting a plurality of virtual fault points in key protection areas according to the standardized power grid topology database, calculating the short-circuit current values and distribution characteristics under each fault point, and generating a fault feature library; extracting the pairing relationship between the main protection and the backup protection based on the fault feature library, constructing an action time difference table and a protection coverage rate index, and forming a set of protection coordination constraint conditions; combining and optimizing the action current thresholds and time delay parameters of each protection device according to the set of protection coordination constraint conditions, and outputting a protection configuration scheme that meets the coordination requirements; using the protection configuration scheme to simulate the fault responses under normal and extreme conditions through a power grid simulation system, generating a protection action sequence diagram and a coordination time interval report; and converting the optimized protection parameters into a device-specific format according to the protection action sequence diagram and the coordination time interval report, and sending them to each protection device through a secure channel to complete the implementation of the protection configuration.

[0006] In a second aspect, the present application provides an intelligent configuration system for a power grid overcurrent protection device. The intelligent configuration system for the power grid overcurrent protection device includes: A collection module for collecting the connection relationships and operating parameters of buses, lines, and transformers through a power grid monitoring system, cleaning and unit-converting the collected data to obtain a standardized power grid topology database; A setting module for setting a plurality of virtual fault points in key protection areas according to the standardized power grid topology database, calculating the short-circuit current values and distribution characteristics under each fault point, and generating a fault feature library; An extraction module for extracting the pairing relationship between the main protection and the backup protection based on the fault feature library, constructing an action time difference table and a protection coverage rate index, and forming a set of protection coordination constraint conditions; An optimization module for combining and optimizing the action current thresholds and time delay parameters of each protection device according to the set of protection coordination constraint conditions, and outputting a protection configuration scheme that meets the coordination requirements; A simulation module for using the protection configuration scheme to simulate the fault responses under normal and extreme conditions through a power grid simulation system, generating a protection action sequence diagram and a coordination time interval report; A sending module for converting the optimized protection parameters into a device-specific format according to the protection action sequence diagram and the coordination time interval report, and sending them to each protection device through a secure channel to complete the implementation of the protection configuration.

[0007] In a third aspect, there is provided an intelligent configuration device for a power grid overcurrent protection device, including: a memory and at least one processor, wherein instructions are stored in the memory; the at least one processor calls the instructions in the memory to enable the intelligent configuration device for the power grid overcurrent protection device to execute the above-mentioned intelligent configuration method for the power grid overcurrent protection device.

[0008] In a fourth aspect, there is provided a computer-readable storage medium, in which instructions are stored, and when it runs on a computer, it enables the computer to execute the above-mentioned intelligent configuration method for the power grid overcurrent protection device.

[0009] In the technical solution provided by this application, real-time data of buses, lines, and transformers are collected through a power grid monitoring system, and are subjected to cleaning and unit conversion processing to establish a standardized power grid topology database, effectively solving the problem of data inconsistency and providing a high-quality data basis for subsequent analysis. Secondly, virtual fault points are set in key protection areas and short-circuit current characteristics under various fault conditions are calculated to form a comprehensive fault feature library, greatly improving the comprehensiveness and accuracy of fault analysis. Based on the fault feature library, the pairing relationship between the main protection and the backup protection is extracted, a time difference table and a coverage rate index are constructed, forming a complete set of protection coordination constraint conditions. This data-driven constraint modeling method significantly reduces the dependence on manual experience and ensures the scientific nature of protection configuration. On this basis, the operating current threshold and time delay parameters of the protection device are combined and optimized through a hybrid genetic algorithm. The characteristics of this algorithm can effectively handle multi-variable non-linear optimization problems and avoid falling into local optimal solutions. The combination of its global search ability and local fine-tuning mechanism enables the solution to find the optimal protection parameter combination in a complex power grid environment, improving the sensitivity, selectivity, and coordination of the protection system. The power grid simulation system is used to simulate the fault response under normal and extreme conditions to verify the reliability of the solution under various conditions. In particular, the robustness of the solution is improved through extreme condition tests. And the parameters are sent to each protection device through a secure channel, ensuring the security and reliability of data transmission. Overall, this method realizes the full-process automation from data collection, feature extraction, constraint modeling to parameter optimization, simulation verification, and implementation configuration, significantly improving the intelligent level of power grid overcurrent protection configuration. Especially in the application of the hybrid genetic algorithm, the self-adaptive characteristics of the algorithm are fully considered. By dynamically adjusting the crossover and mutation probabilities and the parameter search step size, it effectively adapts to the complexity and variability of the specific application field of power grid protection, enabling the algorithm to fine-tune the parameters of key protection devices while maintaining the global search ability, so as to find the optimal protection solution under multiple constraint conditions, greatly reducing the risks of protection malfunction and refusal to operate, and improving the security and reliability of power grid operation. Description of the Drawings

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0011] Figure 1 It is a schematic diagram of an embodiment of the intelligent configuration method for the power grid overcurrent protection device in the embodiments of the present application; Figure 2 It is a schematic diagram of an embodiment of the intelligent configuration system for the power grid overcurrent protection device in the embodiments of the present application; Figure 3 It is a structural schematic block diagram of the intelligent configuration device for the power grid overcurrent protection device in the embodiments of the present invention. Detailed implementation manners

[0012] The embodiments of the present application provide an intelligent configuration method and system for a power grid overcurrent protection device. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and the above accompanying drawings of the present application are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "include" or "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0013] For ease of understanding, the following describes the specific process of the embodiments of the present application. Please refer to Figure 1 , an embodiment of the intelligent configuration method for the power grid overcurrent protection device in the embodiments of the present application includes: Step S101: Collect the connection relationships and operating parameters of buses, lines, and transformers through the power grid monitoring system, clean and perform unit conversion on the collected data to obtain a standardized power grid topology database; Step S102: According to the standardized power grid topology database, set multiple virtual fault points in key protection areas, calculate the short-circuit current values and distribution characteristics under each fault point, and generate a fault feature library; Step S103: Based on the fault feature library, extract the pairing relationships between the main protection and the backup protection, construct an action time difference table and a protection coverage rate index, and form a set of protection coordination constraint conditions; Step S104: According to the protection coordination constraint set, combine and optimize the operating current thresholds and time delay parameters of each protection device, and output a protection configuration scheme that meets the coordination requirements; Step S105: Utilize the protection configuration scheme to simulate the fault responses under normal and extreme conditions through the power grid simulation system, and generate a protection action sequence diagram and a coordination time interval report; Step S106: Based on the protection action sequence diagram and the coordination time interval report, convert the optimized protection parameters into a device-specific format, and send them to each protection device through a secure channel to complete the implementation of the protection configuration.

[0014] It can be understood that the execution entity of this application can be an intelligent configuration system for power grid overcurrent protection devices, or a terminal or a server. Specifically, it is not limited here. In the embodiment of this application, the server is used as the execution entity for illustration.

[0015] In the embodiment of this application, the connection relationships and operating parameters of buses, lines, and transformers are collected through the power grid monitoring system. This process involves obtaining the voltage levels and rated load data of each bus from intelligent electronic devices, and extracting the line impedance parameters and transformer rated capacity information from the power system equipment management database. The collected data is cleaned, including linearly interpolating the missing values in the initial network connection map, and removing abnormal data points using the median rule to form a normalized network parameter table. After data cleaning, the physical quantities in the normalized network parameter table are converted into the standard unit system, and the impedance parameters are converted into per-unit values to generate a standard parameter set with a unified reference benchmark, and finally integrated into a topological description matrix with a node-branch structure to construct a complete standardized power grid topology database. According to the standardized power grid topology database, the line intersection points, transformer connection points, and load-intensive areas are identified through a network criticality evaluation algorithm to determine the scope of the key protection areas. Virtual fault points are set in these key protection areas according to the principle of uniform distribution of electrical distances, and the density of virtual fault points is increased in areas with significant changes in current gradients to form a fault point distribution grid. For each fault point, single-phase grounding, two-phase short circuit, two-phase grounding, and three-phase symmetrical short circuit types are respectively simulated to generate a multi-type fault scenario set. The improved node voltage method is used to calculate the short-circuit current amplitude, phase angle, and distribution characteristics under each fault scenario, and a current distribution matrix is constructed. The current distribution matrix is associated with the fault type and location information, and the boundary values of the bearing capacity of power grid components are added as marks to generate a fault feature library containing fault types, locations, and current characteristics.

[0016] Based on the fault feature library, analyze the power grid structure, identify the connection relationships between protection regions, and determine the pairing table of main protection and backup protection according to the protection cascade principle. For each pair of protection devices, extract the action response times under corresponding fault scenarios, calculate the time difference between them, and form a time-ladder coordination matrix. Screen out the pairing combinations with time differences less than the preset safety limit from the time-ladder coordination matrix, mark them as coordination risk points, and generate a time-difference constraint table. Scan the protection scopes of each protection device through the current overlap analysis method, calculate the protection coverage times of network nodes, generate a heat map of coverage rate, and convert it into a numerical coverage rate index to determine protection dead zones and overlapping protection regions, and establish coverage rate constraint conditions. Integrate the time-difference constraint table and the coverage rate constraint conditions, and add the sensitivity limit values and selectivity requirements of protection devices to form a complete set of protection coordination constraint conditions.

[0017] According to the set of protection coordination constraint conditions, perform normalization processing on the set of protection coordination constraint conditions, convert the time-difference constraint and the coverage rate constraint into standard weight coefficients, and construct an optimization objective function for protection parameters. Taking the action current threshold and time delay parameters of each protection device as variables, establish a parameter search space, set the parameter change step size and boundary conditions, and generate an initial set of parameter combinations. Perform crossover and mutation operations on the initial set of parameter combinations through a hybrid genetic algorithm to generate multiple sets of candidate protection parameter solutions, and calculate the constraint violation degrees of each solution. Sort and screen the candidate protection parameter solutions according to the constraint violation degrees, retain the parameter combinations that meet the coordination constraints and have better objective function values, and form a pool of preferred solutions. For the parameter combinations in the pool of preferred solutions, perform local fine-tuning, use a smaller change step size for the parameters of key protection devices, and obtain a finely tuned set of parameters. Select the combination with the optimal objective function value from the finely tuned set of parameters and integrate it into a protection configuration plan that includes the action current threshold and time delay parameters of each protection device.

[0018] Using the protection configuration plan, convert the protection configuration plan into a parameter format recognizable by the simulation system, load it onto the real-time digital simulation platform, and construct a power grid fault simulation environment. Set a group of normal operating conditions in the power grid fault simulation environment, including basic load, peak load, and light load operating states, and trigger the fault events at each virtual fault point in sequence. For each fault event in the group of normal operating conditions, record the action times and tripping sequences of each protection device, and draw a time-sequence distribution diagram of the protection device actions. Set a group of extreme operating conditions in the power grid fault simulation environment, including large load fluctuations, multi-point simultaneous faults, and power output mutations, and trigger faults at key nodes. Extract the time difference between the main protection and the backup protection action times from the fault response data of the group of extreme operating conditions to form a protection coordination margin statistical table. Integrate the time-sequence distribution diagram of the protection device actions and the protection coordination margin statistical table into a protection action sequence diagram and a coordination time interval report.

[0019] According to the protection action sequence diagram and the coordination time interval report, the protection action sequence diagram is re-verified for safety, and all protection action sequences are checked to see if they meet the coordination requirements, and the protection parameter sets that meet the standards are screened out. According to the margin data in the coordination time interval report, the protection parameter sets are prioritized and the parameter distribution sequence table for key protection devices is determined. According to the communication protocol specifications of each protection device manufacturer, the protection parameter set is formatted and a device-specific parameter file that complies with the IEC61850 standard is generated. An encrypted secure communication channel is established, connected to the communication interface of each protection device, and a parameter distribution session is created. The device-specific parameter files are grouped and transmitted to the corresponding protection device according to the distribution sequence table to implement parameter configuration. The configured protection device is read back and compared and verified through the remote verification mechanism to confirm that the protection configuration has been implemented.

[0020] Taking the outgoing line of a 220kV substation as an example, among the 10 line parameters collected by the power grid monitoring system, the impedance value of line 1 is 0.32+j0.85Ω / km and the length is 15km. Through data cleaning, it is found that there are abnormal values, which are converted to the per-unit value 0.026+j0.068 after cleaning. 20 virtual fault points are set in the key protection area. It is calculated that when a three-phase short circuit fault occurs in line 1 5km away from the substation, the short-circuit current is 8.7kA. Based on the fault feature library, it is determined that the time difference between the main protection of line 1 and the backup protection of the adjacent line should be no less than 0.3s, and an action time difference table is constructed. Through combined optimization, the protection configuration scheme with an action current threshold of 5kA and a time delay of 0.1s for the overcurrent protection of line 1 is obtained. In the simulation verification, the protection coordination margin of the line under extreme conditions is 0.35s, which meets the coordination requirements. Finally, the optimized parameters are sent to the line protection device through the IEC 61850 communication protocol to complete the configuration implementation.

[0021] In a specific embodiment, the process of executing step S101 may specifically include the following steps: The voltage level and rated load data of each bus are obtained through intelligent electronic devices, and the line impedance parameters and transformer rated capacity information are extracted from the power system equipment management database to build an initial network connection map; Perform linear interpolation on the missing values ​​in the initial network connection map, use the median rule to eliminate abnormal data points, and form a standardized network parameter table; Convert the physical quantities in the normalized network parameter table into standard units, convert the impedance parameters into per-unit values, and generate a standard parameter set with a unified reference benchmark; The standard parameter set is integrated into a topological description matrix of the node-branch structure, and the equipment operation status identifier and connection relationship weight are added to construct a standardized power grid topology database.

[0022] Specifically, the voltage levels of each bus and the rated load data are obtained through intelligent electronic devices (IEDs). Intelligent electronic devices are data acquisition terminals installed in substations and key power grid nodes, which can monitor and upload power grid operation parameters in real time through the IEC 61850 communication protocol. These devices continuously collect the voltage data of the bus, including the rated voltage values of each bus (such as 110 kV, 220 kV, 500 kV) and the real-time operating voltage, and at the same time record the load data connected to the bus, including the rated power, power factor, and load type. When extracting the line impedance parameters and transformer rated capacity information from the power system equipment management database, it is necessary to query the equipment parameter table stored in the power system asset management system to obtain the resistance value, reactance value, length information of each transmission line, and technical parameters such as the rated capacity, short-circuit impedance percentage, and connection group of each transformer. After obtaining the above data, an initial network connection map is constructed through the node-branch modeling method. This map represents the power grid using a directed graph structure, where the bus is used as a node, and the line and transformer are used as branches connecting the nodes. Each node records its voltage level and load information, and each branch records its impedance parameters and rated capacity. During the construction of the initial map, the physical connection relationship between devices is recorded, and the breaker status is marked to form a data structure reflecting the real-time topological state of the power grid.

[0023] There are often missing data and outliers in the initial network connection map, and data cleaning needs to be carried out. Linear interpolation is performed on the missing values, that is, the estimated value of the missing point is calculated based on the known adjacent data points. The specific processing method is to determine the known data points before and after the missing data point, calculate the interpolation coefficient, and then fill in the missing value according to the linear relationship. For example, for a line segment with missing impedance parameters, it can be estimated by multiplying the unit length impedance value of the same type and cross-sectional area wire by the length of this line segment. For the processing of outlier data points, the median rule is used for screening and elimination. This method first calculates the median of the data set, and then sets a threshold that deviates from the median by a certain multiple. The data points exceeding this threshold are marked as outliers and replaced with reasonable values. Through these processing steps, a standardized network parameter table with good data consistency and high reliability is formed. The physical quantities in the standardized network parameter table need to be converted to the standard unit system. This process includes unifying the voltage unit to kilovolts (kV), the current unit to amperes (A), the impedance unit to ohms (Ω), the power unit to megawatts (MW), etc. It is particularly important to perform per-unit conversion on the impedance parameters, converting the actual physical impedance value to a relative value based on the system base value. The per-unit conversion selects the system base voltage and base capacity, calculates the base impedance, and divides the actual impedance by the base impedance to obtain the per-unit value. This conversion makes the component parameters of different voltage levels comparable and facilitates subsequent power grid calculation and analysis. After unit conversion and per-unit conversion, a standard parameter set with a unified reference benchmark is generated.

[0024] The standard parameter set needs to be further integrated into a topological description matrix with a node-branch structure. This matrix mainly includes two parts: the node incidence matrix and the branch parameter matrix. The node incidence matrix describes the connection relationship between nodes and branches, and the matrix elements represent the relevance between nodes and branches. The branch parameter matrix records the electrical parameters of each branch, including components such as resistance, reactance, and conductance. In the topological description matrix, add device operation status identifiers, using 0 / 1 to represent the disconnected / connected state of the device, and at the same time add connection relationship weights to represent the connection strength or importance. Through these processing steps, a complete standardized power grid topology database is finally constructed, providing a data basis for the intelligent configuration of subsequent overcurrent protection devices.

[0025] In a specific embodiment, the process of executing step S102 may specifically include the following steps: Scan the standardized power grid topology database through a network criticality evaluation algorithm to identify line intersection points, transformer connection points, and load-dense areas, and determine the scope of the critical protection area; Set virtual fault points in the critical protection area according to the principle of uniform distribution of electrical distances, and increase the density of virtual fault points in areas with significant changes in current gradient to form a fault point distribution grid; For each fault point in the fault point distribution grid, simulate single-phase grounding, two-phase short circuit, two-phase grounding, and three-phase symmetrical short circuit types respectively to generate a multi-type fault scenario set; Use the improved node voltage method to calculate the short-circuit current amplitude, phase angle, and distribution characteristics for each fault scenario in the multi-type fault scenario set, and construct a current distribution matrix; Associate the current distribution matrix with the fault type and location information, and add the boundary value marks of the withstand capacity of power grid components to generate a fault feature library containing fault types, locations, and current characteristics.

[0026] Specifically, the standardized power grid topology database is scanned through a network criticality assessment algorithm to identify critical protection areas. The network criticality assessment algorithm is a graph theory-based analysis method that calculates the importance indicators of each node and branch for the power grid topology structure. The algorithm first calculates the node connectivity, that is, the number of branches directly connected to each node. Nodes with high connectivity are often line intersections. Secondly, the node electrical centrality is calculated, considering the position of the node in the network and the electrical distance from other nodes. The electrical distance refers to the network distance considering impedance factors, rather than simply the topological distance. The algorithm also calculates the load weight coefficient, normalizes the load capacity connected to each node, and forms an indicator reflecting the load density. By comprehensively considering the node connectivity, electrical centrality, and load weight coefficient, a criticality score is assigned to each node and branch, and the area with a score exceeding the preset threshold is marked as a critical protection area. Virtual fault points are set in the determined critical protection area according to the principle of uniform distribution of electrical distance. The electrical distance is the actual electrical transmission distance considering line impedance, different from the physical distance. According to the principle of uniform distribution, a virtual fault point is set at a certain electrical distance interval on the lines within the critical protection area. The initial interval is usually set to about 10% of the total electrical distance of the line. For areas with significant current gradient changes, the density of virtual fault points needs to be increased. Areas with significant current gradient changes refer to areas where the short-circuit current changes significantly with the fault location, such as line segments near the power source point or load concentration areas. In these areas, the fault point interval can be reduced to half or less of the initial interval, so as to more accurately capture the changes in the current distribution characteristics. Through the above processing, a fault point distribution grid covering the critical area is formed, which constitutes the basis for fault simulation.

[0027] For each fault point in the fault point distribution grid, four basic fault types are respectively simulated: single-phase grounding, two-phase short circuit, two-phase grounding, and three-phase symmetrical short circuit. A single-phase grounding fault refers to a short circuit between one phase conductor and the ground, which is the most common fault type in the power system. A two-phase short circuit fault refers to a short circuit between two phase conductors without grounding. A two-phase grounding fault refers to a short circuit between two phase conductors and grounding at the same time. A three-phase symmetrical short circuit refers to a short circuit of three phase conductors at the same time, which belongs to the most serious fault type. Each virtual fault point is modeled according to these four fault types respectively to generate a multi-type fault scenario set including the fault point location and fault type. The improved nodal voltage method is used to calculate the short-circuit current for each fault scenario in the multi-type fault scenario set. The improved nodal voltage method is a short-circuit calculation method optimized according to the characteristics of the power system based on the traditional nodal voltage method. This method first establishes a nodal admittance matrix to describe the electrical connection relationship between nodes. Then, according to the fault type and location, the nodal admittance matrix is modified, and a fault current source is injected at the fault point. Next, the nodal voltage equation is solved to calculate the voltage of each node under fault conditions. Finally, the short-circuit current of each branch is calculated according to the nodal voltage and branch impedance. For asymmetric faults (such as single-phase grounding, two-phase short circuit, two-phase grounding), the symmetrical component method is used for calculation, and the three-phase system is decomposed into three symmetrical component networks of positive sequence, negative sequence, and zero sequence for analysis. The short-circuit current amplitude, phase angle, and distribution characteristics of each fault scenario are obtained through calculation, and a current distribution matrix is constructed.

[0028] The current distribution matrix is associated with the fault type and location information, and the boundary value mark of the grid component bearing capacity is added to generate a fault feature library. The current distribution matrix records the current values measured at the locations of each protection device under each fault scenario. These current values are associated with the specific type and location information of the fault occurrence to establish a fault-current response mapping relationship. The boundary value of the grid component bearing capacity refers to the maximum short-circuit current value that each device can withstand. Exceeding this value may cause device damage. By adding these boundary value marks, potential device overload risk points can be identified. The finally formed fault feature library contains multi-dimensional information such as fault type, location, and current characteristics.

[0029] In a specific embodiment, the process of executing step S103 may specifically include the following steps: Conduct a power grid structure analysis on the fault feature library, identify the connection relationship between each protection area, and determine the pairing table of the main protection and the backup protection according to the protection cascade principle; For each pair of protection devices in the pairing table of the main protection and the backup protection, extract the action response time under the corresponding fault scenario, calculate the time difference between the two, and form a time ladder coordination matrix; Select the paired combinations with time differences less than the preset safety limit from the time ladder coordination matrix, mark them as coordination risk points, and generate a time difference constraint table; Scan the protection scopes of each protection device through the current overlap analysis method, calculate the protection coverage times of network nodes, and generate a coverage heat map; Convert the coverage heat map into a numerical coverage rate index, determine the protection dead zone and the overlapping protection area, and establish coverage rate constraint conditions; Integrate the time difference constraint table and the coverage rate constraint conditions, add the sensitivity limit value and selectivity requirements of the protection device, and generate a protection coordination constraint condition set.

[0030] Specifically, perform a power grid structure analysis on the fault feature library to identify the connection relationships between each protection area. This process processes the data in the fault feature library through a topology analysis algorithm to identify the physical boundaries and electrical connection relationships of each protection area in the power grid. A protection area refers to the network section responsible for being protected by a specific protection device, including the main protection area and the backup protection area. Determine the pairing table of the main protection and the backup protection according to the protection cascading principle. The protection cascading principle means that when the main protection fails, there should be a reliable backup protection to take over the action configuration principle. The generation process of the pairing table includes: first, analyze the power grid structure to determine the upstream and downstream relationships of each area; then, for each protection area, set the directly adjacent downstream protection device as the main protection and the upstream protection device as the backup protection; finally, for the protection devices that are not directly adjacent but have an electrical connection path, determine the remote backup protection relationship according to the electrical distance. For each pair of protection devices in the pairing table of the main protection and the backup protection, extract the action response time under the corresponding fault scenario. The action response time refers to the time interval from the occurrence of the fault to the action tripping of the protection device, which is determined by the characteristics of the protection device. Extract the short-circuit current values of each pair of main and backup protections in each fault scenario from the fault feature library, and calculate their respective action times according to the current-time characteristic curve of the protection device. The current-time characteristic curve describes the action time of the protection device under different current values, usually adopting the inverse time limit characteristic, that is, the larger the current, the shorter the action time. Calculate the time difference between the two, that is, the action time of the backup protection minus the action time of the main protection, to form a time ladder coordination matrix. This matrix records the action time differences of all main and backup protection pairs in various fault scenarios.

[0031] Select paired combinations with time differences less than the preset safety limit from the time ladder coordination matrix. The safety limit is usually set to 0.3 - 0.5 seconds, which is the minimum time interval to ensure the coordination of protection actions. A paired combination with a time difference less than the safety limit means that the action time interval between the main protection and the backup protection is insufficient, and there is a risk that the backup protection may act prematurely or act simultaneously with the main protection. Therefore, it is marked as a coordination risk point, and a time difference constraint table is generated. This constraint table records the protection pairing relationships that need special attention and adjustment and their time difference requirements.

[0032] Scan the protection ranges of each protection device through the current overlap analysis method. The current overlap analysis method is an effective tool for evaluating the protection coverage, and its mathematical expression can be represented by the Protection Coverage Index (PCI):

[0033] where, represents the protection coverage index of network node n, P is the total number of protection devices in the system, is the coverage indication factor, which takes the value of 1 when protection device p can detect a fault at node n and act correctly, otherwise 0. is the weight coefficient of protection device p, reflecting the importance and reliability of this protection device.

[0034] Calculate the protection coverage times of network nodes, that is, how many different protection devices can respond to the faults of this node. Ideally, each node should be covered by at least one main protection and one backup protection, and the coverage times should be at least 2. By calculating the coverage times of each node and using the heat map visualization technology, a coverage rate heat distribution map is generated. The heat map uses different colors to represent different coverage degrees. Usually, high-coverage areas are displayed as warm colors (red, orange), and low-coverage areas are displayed as cold colors (blue, green).

[0035] Convert the coverage rate heat distribution map into a numerical coverage rate index. This process involves quantitative analysis of the heat map data. For each network node, a coverage rate score is assigned according to its coverage times. For example, a node with a coverage time of 0 gets a score of 0, a node with a coverage time of 1 gets a score of 0.5, a node with a coverage time of 2 gets a score of 0.8, and a node with a coverage time greater than 2 gets a score of 1. In this way, protection dead zones and repeated protection areas are determined. The protection dead zone refers to the area with a coverage rate of 0, indicating that no protection device can respond to the faults in this area; the repeated protection area refers to the area with a coverage rate score of 1, indicating that multiple protection devices cover simultaneously. Based on these analysis results, coverage rate constraint conditions are established, requiring that the coverage rate scores of all nodes should be greater than the preset threshold, usually 0.8.

[0036] Integrate the time difference constraint table and the coverage constraint conditions, and add the sensitivity limit value and selectivity requirements of the protection device. The sensitivity limit value refers to the minimum fault current value that the protection device can reliably detect. Generally, it is required that the sensitivity coefficient is greater than 1.5, that is, the setting current of the protection device should be less than 1.5 times the minimum fault current. The selectivity requirement means that the protection device should only respond to faults within its own protection area and not operate on external faults. Combine these constraint conditions to generate a comprehensive set of protection coordination constraint conditions as the constraint basis for subsequent optimal configuration.

[0037] Take a 35 kV distribution network as an example to illustrate the above process: This network contains 3 feeders, and overcurrent protection devices are installed on each feeder. By analyzing the topological relationship in the fault feature library, it is determined that the protection devices P1 and P2 on line 1 and line 2 form a primary and backup protection relationship, and P2 is the backup protection of P1. Extract relevant data from the fault feature library and calculate that when a three-phase short-circuit fault occurs on line 1, the operating time of P1 is 0.3 seconds, the operating time of P2 is 0.7 seconds, and the time difference between the two is 0.4 seconds. When a single-phase ground fault occurs at the end of line 1, the operating time of P1 is 0.5 seconds, the operating time of P2 is 0.7 seconds, and the time difference is only 0.2 seconds, which is less than the safety limit of 0.3 seconds, so it is marked as a coordination risk point. Through current overlap analysis to calculate the network coverage, it is found that the end node of line 3 is only covered by one protection device, and the coverage score is 0.5, which is lower than the threshold of 0.8, so it is marked as a weak protection area. At the same time, the nodes near the starting point of line 1 are covered by 3 protection devices, which is marked as a redundant protection area. Integrate these analysis results to form a comprehensive set of constraint conditions including time difference constraints, coverage constraints, and sensitivity and selectivity requirements, providing a basis for the next parameter optimization.

[0038] In a specific embodiment, the process of executing step S104 may specifically include the following steps: Normalize the set of protection coordination constraint conditions, convert the time difference constraint and the coverage constraint into standard weight coefficients, and construct an optimization objective function for protection parameters; Taking the operating current threshold and time delay parameters of each protection device as variables, establish a parameter search space, set the parameter change step size and boundary conditions, and generate an initial set of parameter combinations; Perform crossover and mutation operations on the initial set of parameter combinations through a hybrid genetic algorithm to generate multiple sets of candidate protection parameter schemes, and calculate the constraint violation degree of each scheme; Rank and screen the candidate protection parameter schemes according to the constraint violation degree, retain the parameter combinations that meet the coordination constraints and have better objective function values, and form a preferred scheme pool; For the parameter combinations in the preferred solution pool, perform local fine-tuning, adopt a smaller change step for the parameters of the key protection devices, and obtain the fine-tuned parameter set. Select the combination with the optimal objective function value from the fine-tuned parameter set and integrate it into a protection configuration plan that includes the operating current thresholds and time delay parameters of each protection device.

[0039] Specifically, normalize the protection coordination constraint set to convert the constraints with different dimensions and orders of magnitude into a comparable unified standard. The normalization process includes performing a linear transformation on the time difference constraint and using the ratio of the actual time difference to the safety limit as the normalized index; performing a function mapping on the coverage rate constraint to convert the coverage rate index into a value between 0 and 1. These normalized indexes are multiplied by their respective weight coefficients to form the standard weight coefficients. The weight of the time difference constraint is usually higher because the time coordination relationship directly affects the reliability of protection; the weight of the coverage rate constraint is the second, ensuring that there are no protection blind spots in the network. By linearly combining these weighted indexes, construct an optimization objective function for protection parameters, and the minimum value of this function corresponds to the optimal protection configuration plan. Taking the operating current thresholds and time delay parameters of each protection device as variables, establish a parameter search space. The operating current threshold refers to the minimum current value at which the protection device starts to operate, usually set as several times the rated current; the time delay parameter refers to the set value at which the protection device delays for a certain time after detecting a fault before operating. For each protection device, its parameter search space is two-dimensional, including the current threshold and time delay dimensions. Set the parameter change step. The step of the current threshold is usually 0.1 times the rated current, and the step of the time delay is usually 0.05 seconds. Set the boundary conditions. The lower limit of the current threshold is usually 1.2 times the rated current, and the upper limit is 0.8 times the minimum short-circuit current; the lower limit of the time delay is usually 0.1 seconds, and the upper limit is 2.0 seconds. By uniformly sampling in the parameter search space, generate an initial parameter combination set as the starting point of the optimization algorithm.

[0040] Optimize the initial parameter combination set through a hybrid genetic algorithm. The hybrid genetic algorithm combines the global search ability of the genetic algorithm and the fine-tuning ability of the local search method. First, encode the initial parameter combination set into chromosomes, where each chromosome represents a complete parameter configuration of a set of protection devices. Perform crossover operations on these chromosomes, randomly select crossover points from two parent chromosomes, and exchange the parameter values on both sides of the crossover points to generate new offspring chromosomes. Then perform mutation operations, randomly change some parameter values in the chromosomes with a certain probability to increase the population diversity. For the generated candidate protection parameter schemes, calculate the constraint violation degree of each scheme, that is, the degree of non-satisfaction of each constraint condition. The lower the constraint violation degree, the closer the scheme is to meeting all coordination requirements. Sort and screen the candidate protection parameter schemes according to the constraint violation degree. First, calculate the total constraint violation degree of each scheme, and then sort them from small to large according to the constraint violation degree. Retain the parameter combinations with a constraint violation degree of zero (indicating that all constraint conditions are met) and better objective function values to form an optimal solution pool. If there is no scheme with a constraint violation degree of zero, select several schemes with the smallest constraint violation degree. The solutions in the optimal solution pool all have good coordination performance, but there may still be room for further optimization.

[0041] For the parameter combinations in the optimal solution pool, perform local fine-tuning. First, identify the key protection devices, that is, the devices that play a key role or are in a key position in protection coordination, such as the protection devices at the intersection of multiple lines. For the parameters of these key protection devices, adjust them with a smaller change step. The fine step of the current threshold may be 1 / 5 of the original step, and the fine step of the time delay may be 0.01 seconds. By slightly adjusting the key parameters, further optimize the local performance without destroying the overall coordination to obtain the fine-tuned parameter set.

[0042] Select the combination with the optimal objective function value from the fine-tuned parameter set. Calculate the objective function value of each parameter combination, and select the combination with the smallest (or largest, depending on the optimization direction) value as the final selected scheme. Integrate this scheme into a protection configuration scheme including the operating current threshold and time delay parameters of each protection device, and record the specific configuration parameters of each protection device for subsequent implementation.

[0043] Taking the 110 kV power grid in a certain area as an example to illustrate the above process: This power grid includes 5 lines, and each line is equipped with an overcurrent protection device. First, normalize the protection coordination constraint set, convert the time difference constraint (required to be not less than 0.3 seconds) into a normalized index. For example, the violation degree of the pairing constraint with a time difference of 0.2 seconds is 0.33; also convert the coverage rate constraint (required to be greater than 0.8) into a unified index. Assign weight coefficients, the weight of the time difference constraint is 0.7, and the weight of the coverage rate constraint is 0.3, and construct an optimization objective function. Establish a parameter search space, where the current threshold of each protection device varies between 1.2 times and 5 times the rated current, with a step size of 0.2 times; the time delay varies between 0.1 second and 1.5 seconds, with a step size of 0.1 second. Generate an initial set containing 100 different parameter combinations. Use a hybrid genetic algorithm for optimization, set the population size to 50, the number of evolutionary generations to 100, the crossover probability to 0.8, and the mutation probability to 0.1. Generate new candidate solutions through crossover and mutation operations, calculate the constraint violation degree of each solution. For example, the time difference between the L2 and L3 protection pairings of a certain solution is only 0.25 seconds, violating the minimum difference requirement of 0.3 seconds. Sort and select 10 solutions with a constraint violation degree of zero to form a preferred solution pool. Fine-tune the key protection device L1 (the node protection connecting multiple lines) in these solutions, and reduce the adjustment step size to 0.05 times and 0.02 seconds. Finally, select the solution with the minimum objective function value. The current threshold of L1 is 2.4 times the rated current, and the time delay is 0.16 seconds; the current threshold of L2 is 2.8 times the rated current, and the time delay is 0.42 seconds, and so on to obtain a complete protection configuration plan.

[0044] In a specific embodiment, the process of executing step S105 may specifically include the following steps: Convert the protection configuration plan into a parameter format recognizable by the simulation system, load it into the real-time digital simulation platform, and construct a power grid fault simulation environment; Set a conventional working condition group in the power grid fault simulation environment, including basic load, peak load, and light load operating states, and sequentially trigger the fault events of each virtual fault point; For each fault event in the conventional working condition group, record the action time and tripping sequence of each protection device, and draw a time sequence distribution diagram of the protection device actions; Set an extreme working condition group in the power grid fault simulation environment, including large load fluctuations, multi-point simultaneous faults, and power output mutation states, and trigger key node faults; Extract the action time difference between the main protection and the backup protection from the fault response data of the extreme working condition group to form a protection coordination margin statistical table; Integrate the time sequence distribution diagram of the protection device actions and the protection coordination margin statistical table into a protection action sequence diagram and a coordination time interval report.

[0045] Specifically, the protection configuration scheme is converted into a parameter format recognizable by the simulation system, and this process involves data format conversion and parameter mapping. The operating current thresholds and time delay parameters of each protection device included in the protection configuration scheme need to be reorganized according to the data structure requirements of the simulation system, including parameter name mapping, unit conversion, and data type conversion. For example, the optimized current threshold of "2.4 times the rated current" is converted into a specific ampere value; the time delay parameter is converted into the millisecond unit required by the simulation system. After the conversion is completed, the parameter file is loaded into the Real-Time Digital Simulator (RTDS). RTDS is a real-time simulation device dedicated to power system analysis, which can accurately simulate the electrical characteristics of grid components and the operation logic of protection devices. A power grid fault simulation environment is constructed in the RTDS, including power source models, transformer models, line models, load models, and protection device models, to form a complete power grid simulation system. In the power grid fault simulation environment, a set of normal operating conditions is set to simulate various conditions that the power grid may encounter during normal operation. The set of normal operating conditions includes three typical operating states: the base load state, which is the operating state of the power grid at the average load level, usually 60-70% of the design capacity; the peak load state, which is the operating state of the power grid under the maximum load condition, usually close to 90-100% of the design capacity; the light load operating state, which is the operating state of the power grid under low load conditions, usually 30-40% of the design capacity. For each operating state, the fault events at each virtual fault point are triggered in sequence. The triggering method is to set a fault injection module in the simulation system to simulate the occurrence of short-circuit faults at each virtual fault point according to a preset time series, including fault types such as single-phase grounding, two-phase short circuit, two-phase grounding, and three-phase symmetrical short circuit.

[0046] For each fault event in the set of normal operating conditions, record the action time and tripping sequence of each protection device. The action time refers to the time point from the occurrence of the fault to the protection device issuing a tripping command, recorded in milliseconds; the tripping sequence refers to the arrangement of multiple protection devices acting in chronological order. For each fault type at each fault point, record which protection devices act, the time points of their actions, and the time intervals between them. Through data visualization technology, these time series data are plotted as a time-order distribution diagram of the protection device actions. This distribution diagram uses a time axis to represent, and the action times of each protection device are marked on the axis, visually showing the time relationship of the protection actions, which is convenient for analyzing the coordination and selectivity of the protection actions.

[0047] Set up an extreme condition group in the power grid fault simulation environment to simulate the operating state of the power grid under abnormal conditions. The extreme condition group includes three unconventional states: a large load fluctuation state, which simulates the situation where the load changes violently in a short period of time, such as the load suddenly increasing from 40% to 90% or decreasing from 90% to 40% within 5 minutes; a multi-point simultaneous fault state, which simulates the situation where faults occur simultaneously or almost simultaneously at multiple locations in the power grid, such as two adjacent lines short-circuiting at the same time; a power output mutation state, which simulates the situation where the power of a generator set or a power input point changes rapidly, such as the output of a certain power point decreasing by 50% in a short period of time. Under these extreme conditions, key node faults are mainly triggered, that is, faults are simulated at nodes that play a key role or have a large influence range in the power grid, and the response of the protection system is observed.

[0048] Extract the time difference between the main protection and the backup protection action times from the fault response data of the extreme condition group. For each pair of configured main and backup protections, record their action times under extreme conditions, calculate the time difference between the two, and form a protection coordination margin statistical table. The coordination margin refers to the difference between the backup protection action time and the main protection action time, which reflects the coordination margin of the protection configuration under extreme conditions. The protection coordination margin statistical table records the time difference distribution of each main and backup protection pair under different extreme conditions, including statistical indicators such as the minimum value, average value, and standard deviation, and is used to evaluate the robustness of the protection configuration.

[0049] Integrate the protection device action time sequence distribution diagram and the protection coordination margin statistical table into a protection action sequence diagram and a coordination time interval report. The protection action sequence diagram is a comprehensive chart that shows the action sequence and time relationship of the protection device under various operating conditions and fault conditions. The coordination time interval report is a document that details the time difference between the main and backup protections, including the coordination situation under normal and extreme conditions, as well as the marking and analysis of situations that do not meet the coordination requirements. These two pieces of information together constitute the key results of the protection configuration scheme verification and provide a basis for finally determining the protection parameters.

[0050] Taking the protection configuration verification of a certain 66 kV substation as an example to illustrate the above process: Convert the parameters of the 5 overcurrent protection devices in the optimized protection configuration scheme into a format recognizable by RTDS, including parameters such as the operating current threshold of 450 A for P1 and a time delay of 0.2 seconds. Establish a complete power grid model in RTDS, including 2 input lines, 3 output lines, 2 transformer groups, and corresponding protection devices. Set up a normal operating condition group and simulate faults on each line in turn under the basic load state (total load of 25 MW). When simulating a three-phase short-circuit fault at a distance of 5 km from the substation on line L1, the operating time of P1 is recorded as 0.25 seconds, the operating time of P3 (backup protection) is 0.65 seconds, and the time difference is 0.4 seconds. Set up extreme operating conditions, such as simulating the case where the load suddenly increases from 25 MW to 45 MW, trigger a fault at the same location, the operating time of P1 becomes 0.22 seconds, the operating time of P3 becomes 0.57 seconds, and the time difference is 0.35 seconds, still meeting the coordination requirements. Integrate all test data into a protection action sequence diagram, which clearly shows the action sequence of each protection device under different fault conditions; at the same time, generate a coordination time interval report, showing that the average value of the main and backup protection time difference under normal operating conditions is 0.42 seconds, and the minimum value under extreme operating conditions is 0.32 seconds, verifying the effectiveness and robustness of the protection configuration scheme.

[0051] In a specific embodiment, the process of performing step S106 may specifically include the following steps: Perform a safety re-verification on the protection action sequence diagram, check whether all protection action timings meet the coordination requirements, and screen out the protection parameter sets that meet the standards; According to the margin data in the coordination time interval report, sort the protection parameter sets by priority to determine the key protection device parameter download order list; According to the communication protocol specifications of each protection device manufacturer, convert the format of the protection parameter set to generate a device-specific parameter file that complies with the IEC 61850 standard; Establish an encrypted and secure communication channel, connect to the communication interfaces of each protection device, and create a parameter download session; Group and transmit the device-specific parameter file to the corresponding protection device according to the download order list to implement parameter configuration; Through the remote verification mechanism, perform parameter read-back and comparison verification on the configured protection device to confirm the completion of the protection configuration implementation.

[0052] Specifically, the sixth step of the intelligent configuration method for the power grid overcurrent protection device focuses on the actual configuration implementation process of protection parameters. First, perform a security re-verification on the protection action sequence diagram, which is a re-audit and confirmation of the simulation results. During the re-verification, key checks are made to ensure that all protection action timings meet the coordination requirements, including: whether the action time difference between the primary protection and the corresponding backup protection is greater than the safety margin (usually 0.3 - 0.5 seconds); whether the protection device can promptly cut off the fault (generally, it is required that the fault current duration does not exceed 2 seconds); whether the protection action area conforms to the selectivity principle (only operates on faults within its own area and remains stable for external faults). By setting verification criteria, check each set of action timing data in the protection action sequence diagram, and filter out the set of protection parameters that meet all safety standards. If a certain set of parameters does not meet the coordination requirements under specific conditions, mark it as unqualified and exclude it from the candidate solutions.

[0053] According to the margin data in the coordination time interval report, prioritize the set of protection parameters. The coordination margin refers to the margin between the actual time difference and the minimum safety margin. The larger the margin, the more conservative the configuration, the stronger the anti-interference ability, but it may lead to an increase in protection action delay. According to the requirements of different operating environments, set the margin evaluation criteria. For example, on important lines, prioritize the solutions with larger margins, and on general lines, accept solutions with moderate margins. By comprehensively evaluating the coordination margins of each parameter combination under different working conditions, determine the final protection parameter solution adopted. At the same time, according to the power grid structure and protection importance, determine the key protection device parameter distribution order list. Key protection devices are usually those in important positions in the network structure (such as main lines, key nodes) or performing important functions (such as protection at the main power supply entrance). The parameter configuration priorities of these devices are relatively high.

[0054] According to the communication protocol specifications of each protection device manufacturer, perform format conversion on the set of protection parameters. Protection devices in the power system may come from different manufacturers and have different parameter formats and communication protocol requirements. To achieve unified configuration, the optimized protection parameters need to be converted into formats recognizable by each device. IEC 61850 is an international standard for intelligent power device communication and is widely used in substation automation systems. Convert the parameters into device-specific parameter files that conform to the IEC 61850 standard, including adding device identification information in the file header, mapping the parameters to standard logical nodes and data objects, and organizing the parameter data according to the standard structure. The generated parameter files usually adopt the XML format and contain detailed device descriptions, parameter values, and configuration information.

[0055] Establish an encrypted secure communication channel and connect to the communication interfaces of each protection device. The power system protection device belongs to critical infrastructure, and its parameter configuration must be carried out through a secure communication method. The encrypted secure communication channel adopts the SSL / TLS protocol and uses an asymmetric encryption algorithm to encrypt the transmitted data to ensure that the parameter information is not stolen or tampered with during transmission. Connect to the communication interfaces of each protection device through the station control layer network or a dedicated engineer station, which may be a serial port (RS-232 / 485) or an Ethernet interface (RJ45 / fiber optic). After establishing the communication connection, perform identity authentication and permission verification to create a parameter download session and prepare for subsequent operations.

[0056] Group and transmit the device-specific parameter files to the corresponding protection devices according to the download order list to implement parameter configuration. The parameter download adopts a grouping strategy to avoid system instability caused by configuring all protection devices simultaneously. Usually, the main protection devices at critical locations are configured first. After verifying their normal operation, the associated backup protection devices are configured, and finally, the protection devices at ordinary locations are configured. For each protection device, write the content of the parameter file into the parameter area of the device in sequence according to its parameter configuration interface specification, including current setting values, time characteristic parameters, function switch settings, etc. During the parameter writing process, set up a timeout detection and error retry mechanism to ensure the reliable completion of the configuration process.

[0057] Perform parameter read-back and comparison verification on the configured protection devices through a remote verification mechanism to confirm the completion of the protection configuration implementation. After the configuration is completed, immediately read the actual configuration parameters from the protection device and compare them with the target parameters downloaded to check for parameter reception errors or setting failures. The comparison verification includes aspects such as whether the parameter values are consistent, whether the function settings are correct, and whether the communication is normal. For the devices that pass the verification, mark them as successfully configured; for the devices that fail the verification, record the error information, analyze the reasons, and re-execute the configuration process until all devices are successfully configured. Finally, generate a configuration report to record the configuration process, parameter values, and verification results of each protection device, which serves as important materials for system maintenance and fault analysis.

[0058] Taking the implementation of the protection configuration of a certain 110 kV substation as an example: The safety of the protection scheme that has passed the simulation verification is re-verified to confirm that the time difference of all protection pairs is greater than the safety limit of 0.3 seconds, and the minimum time difference is 0.32 seconds (the L2-L4 protection pair under extreme load fluctuation conditions), which meets the coordination requirements. According to the coordination margin data, L1, as the protection device of the main line, has a coordination margin of more than 0.4 seconds under various working conditions and the highest priority; L3 is connected to important loads and has the second highest priority; the rest are sorted according to the margin size. The optimized parameters are converted into the formats supported by the devices of each manufacturer, such as the XML configuration file of the ABB REF615 protection device, the parameter table of the Siemens 7SJ62 protection device, etc. Connect to the substation network through an encrypted VPN channel to establish a secure communication session with each protection device. In the order of priority, the parameters of the L1 protection device are issued first, and its current starting value is configured as 480 A, the time characteristic is normal inverse time limit, and the time coefficient is 0.2, etc.; after confirming the successful configuration of L1, the protection devices of L3, L2, L4, and L5 are configured in sequence. After the configuration is completed, the parameters are read back, and it is found that the actual time coefficient of the L4 device is set to 0.22, which does not match the target value of 0.20, and it is successfully corrected by reissuing. Finally, it is verified and confirmed that the parameter configurations of all protection devices meet the design requirements, and the entire protection configuration implementation process is completed.

[0059] The intelligent configuration method of the grid overcurrent protection device in the embodiment of the present application has been described above. Next, the intelligent configuration system of the grid overcurrent protection device in the embodiment of the present application will be described. Please refer to Figure 2 , an embodiment of the intelligent configuration system of the grid overcurrent protection device in the embodiment of the present application includes: An acquisition module, configured to acquire the connection relationship and operating parameters of buses, lines, and transformers through a grid monitoring system, clean and convert the acquired data to obtain a standardized grid topology database; A setting module, configured to set multiple virtual fault points in key protection areas according to the standardized grid topology database, calculate the short-circuit current values and distribution characteristics under each fault point, and generate a fault feature library; An extraction module, configured to extract the pairing relationship between the main protection and the backup protection based on the fault feature library, construct an action time difference table and a protection coverage rate index, and form a set of protection coordination constraint conditions; An optimization module, configured to perform combined optimization on the action current threshold and time delay parameters of each protection device according to the set of protection coordination constraint conditions, and output a protection configuration scheme that meets the coordination requirements; A simulation module, configured to use the protection configuration scheme to simulate the fault response under normal and extreme working conditions through a grid simulation system, and generate a protection action sequence diagram and a coordination time interval report; A distribution module, configured to convert the optimized protection parameters into a device-specific format according to the protection action sequence diagram and the coordination time interval report, and distribute them to each protection device through a secure channel to complete the implementation of protection configuration.

[0060] Through the collaborative cooperation of the above-mentioned various components and the implementation of the intelligent configuration method for grid overcurrent protection devices, the solution has achieved remarkable beneficial effects. First, by collecting the real-time data of buses, lines, and transformers through the grid monitoring system, cleaning and unit conversion processing are carried out, and a standardized grid topology database is established, effectively solving the problem of data inconsistency and providing a high-quality data basis for subsequent analysis. Second, virtual fault points are set in key protection areas and the short-circuit current characteristics under various fault conditions are calculated to form a comprehensive fault feature library, greatly improving the comprehensiveness and accuracy of fault analysis. Based on the fault feature library, the pairing relationship between the main protection and the backup protection is extracted, a time difference table and a coverage rate index are constructed, and a complete set of protection coordination constraint conditions is formed. This data-driven constraint modeling method significantly reduces the dependence on manual experience and ensures the scientific nature of protection configuration. On this basis, the action current threshold and time delay parameters of the protection device are combined and optimized through a hybrid genetic algorithm. The characteristics of this algorithm can effectively handle multi-variable non-linear optimization problems and avoid falling into local optimal solutions. The combination of its global search ability and local fine-tuning mechanism enables the solution to find the optimal protection parameter combination in a complex grid environment, improving the sensitivity, selectivity, and coordination of the protection system. The grid simulation system is used to simulate the fault response under normal and extreme conditions to verify the reliability of the solution under various conditions. In particular, the robustness of the solution is improved through extreme condition tests. And the parameters are distributed to each protection device through a secure channel to ensure the security and reliability of data transmission. Overall, this method realizes the full-process automation from data collection, feature extraction, constraint modeling to parameter optimization, simulation verification, and implementation configuration, significantly improving the intelligent level of grid overcurrent protection configuration. Especially in the application of the hybrid genetic algorithm, the self-adaptive characteristics of the algorithm are fully considered. By dynamically adjusting the crossover and mutation probabilities and the parameter search step size, it effectively adapts to the complexity and variability of the specific application field of grid protection. While maintaining the global search ability, the algorithm can finely adjust the parameters of key protection devices, so as to find the optimal protection solution under multiple constraint conditions, greatly reducing the risks of protection misoperation and refusal to operate, and improving the security and reliability of grid operation.

[0061] Above Figure 2 The intelligent configuration system of the medium-voltage grid overcurrent protection device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. Next, the intelligent configuration device of the medium-voltage grid overcurrent protection device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0062] Figure 3 FIG. Figure 3 is a schematic structural diagram of an intelligent configuration device for a power grid overcurrent protection device provided by an embodiment of the present invention. The intelligent configuration device 300 for the power grid overcurrent protection device may vary greatly due to different configurations or performances, and may include one or more processors (central processing units, CPUs) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 for storing application programs 333 or data 332 (for example, one or more mass storage device ends). Among them, the memory 320 and the storage media 330 may be transient storage or persistent storage. The program stored in the storage media 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the intelligent configuration device 300 for the power grid overcurrent protection device. Further, the processor 310 may be configured to communicate with the storage media 330 and execute a series of instruction operations in the storage media 330 on the intelligent configuration device 300 for the power grid overcurrent protection device to implement the steps of the above-mentioned intelligent configuration method for the power grid overcurrent protection device.

[0063] The intelligent configuration device 300 for the power grid overcurrent protection device may further include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input / output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 3 the shown structural diagram of the intelligent configuration device for the power grid overcurrent protection device does not limit the intelligent configuration device for the power grid overcurrent protection device provided by the present invention, and may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0064] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on a computer, the computer is caused to execute the steps of the intelligent configuration method for the power grid overcurrent protection device.

[0065] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described systems, systems, and units may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0066] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a grid overcurrent protection device intelligent configuration device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0067] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A method for intelligently configuring a power grid overcurrent protection device, characterized in that: The method comprises: The connection relationship and operating parameters of busbars, lines and transformers are collected through the power grid monitoring system, and the collected data are cleaned and converted to obtain a standardized power grid topology database; According to the standardized power grid topology database, multiple virtual fault points are set in the key protection area, the short-circuit current value and distribution characteristics under each fault point are calculated, and a fault feature library is generated; Based on the fault feature library, the pairing relationship between the main protection and the backup protection is extracted, an action time difference table and a protection coverage index are constructed, and a protection coordination constraint condition set is formed; According to the protection coordination constraint condition set, the action current threshold and time delay parameter of each protection device are combined and optimized, and a protection configuration scheme that meets the coordination requirements is output; Using the protection configuration scheme, the fault response under normal and extreme working conditions is simulated through the power grid simulation system to generate a protection action sequence diagram and a coordination time interval report; According to the protection action sequence diagram and the coordination time interval report, the optimized protection parameters are converted into a device-specific format and sent to each protection device through a secure channel to complete the protection configuration implementation.

2. The intelligent configuration method of the power grid overcurrent protection device according to claim 1, characterized in that: The connection relationship and operation parameters of the busbar, line and transformer are collected through the power grid monitoring system, and the collected data are cleaned and converted to units to obtain a standardized power grid topology database, including: The voltage level and rated load data of each bus are obtained through intelligent electronic devices, and the line impedance parameters and transformer rated capacity information are extracted from the power system equipment management database to build an initial network connection map; Performing linear interpolation processing on the missing values ​​in the initial network connection map, eliminating abnormal data points using the median rule, and forming a normalized network parameter table; Converting the physical quantities in the normalized network parameter table into a standard unit system, converting the impedance parameters into per-unit values, and generating a standard parameter set with a unified reference benchmark; The standard parameter set is integrated into a topological description matrix of a node-branch structure, and equipment operation status identifiers and connection relationship weights are added to construct a standardized power grid topology database.

3. The intelligent configuration method of the power grid overcurrent protection device according to claim 1, characterized in that: According to the standardized power grid topology database, multiple virtual fault points are set in the key protection area, the short-circuit current value and distribution characteristics under each fault point are calculated, and a fault feature library is generated, including: Scanning the standardized power grid topology database through a network criticality assessment algorithm to identify line intersections, transformer connection points and load-intensive areas, and determine the scope of critical protection areas; In the key protection area, virtual fault points are set according to the principle of uniform electrical distance distribution, and the density of virtual fault points is increased in areas where the current gradient changes significantly, so as to form a fault point distribution grid; For each fault point in the fault point distribution grid, single-phase grounding, two-phase short circuit, two-phase grounding and three-phase symmetrical short circuit types are simulated respectively to generate a multi-type fault scenario set; The improved node voltage method is used to calculate the short-circuit current amplitude, phase angle and distribution characteristics of each fault scenario in the multi-type fault scenario set, and a current distribution matrix is ​​constructed; The current distribution matrix is ​​associated with the fault type and location information, and a grid element bearing capacity boundary value marker is added to generate a fault feature library including the fault type, location and current characteristics.

4. The intelligent configuration method of the power grid overcurrent protection device according to claim 1, characterized in that: Based on the fault feature library, the pairing relationship between the main protection and the backup protection is extracted, an action time difference table and a protection coverage index are constructed, and a protection coordination constraint condition set is formed, including: Performing a grid structure analysis on the fault feature library, identifying the connection relationship between the protection areas, and determining a pairing table of the main protection and the backup protection according to the protection cascade principle; For each pair of protection devices in the pairing table of the main protection and the backup protection, extract the action response time under the corresponding fault scenario, calculate the time difference between the two, and form a time ladder coordination matrix; Selecting the pairing combinations whose time difference is less than the preset safety limit from the time ladder coordination matrix, marking them as coordination risk points, and generating a time difference constraint table; The protection range of each protection device is scanned by the current overlap analysis method, the protection coverage times of the network nodes are calculated, and the coverage thermal distribution diagram is generated; Convert the coverage rate thermal distribution map into a numerical coverage rate index, determine the protection dead zone and repeated protection area, and establish coverage rate constraint conditions; The time difference constraint table and coverage constraint conditions are integrated, and the sensitivity limit and selectivity requirements of the protection device are added to generate a protection coordination constraint condition set.

5. The intelligent configuration method of the power grid overcurrent protection device according to claim 1, characterized in that: The step of combining and optimizing the action current threshold and time delay parameters of each protection device according to the protection coordination constraint condition set, and outputting a protection configuration scheme that meets the coordination requirements, includes: Normalizing the protection coordination constraint condition set, converting the time difference constraint and the coverage constraint into standard weight coefficients, and constructing a protection parameter optimization objective function; Taking the action current threshold and time delay parameters of each protection device as variables, a parameter search space is established, the parameter change step and boundary conditions are set, and an initial parameter combination set is generated; Performing crossover and mutation operations on the initial parameter combination set through a hybrid genetic algorithm to generate multiple sets of candidate protection parameter schemes, and calculating the constraint violation degree of each scheme; The candidate protection parameter schemes are sorted and screened according to the constraint violation degree, and the parameter combinations that meet the coordination constraints and have better objective function values ​​are retained to form a preferred scheme pool; For the parameter combinations in the preferred solution pool, local fine adjustment is performed, and a smaller change step size is adopted for the parameters of the key protection devices to obtain a finely adjusted parameter set; A combination with an optimal objective function value is selected from the finely tuned parameter set and integrated into a protection configuration scheme including the action current threshold and time delay parameters of each protection device.

6. The method for intelligent configuration of a power grid overcurrent protection device according to claim 1, characterized in that: The protection configuration scheme is used to simulate fault responses under normal and extreme working conditions through a power grid simulation system to generate a protection action sequence diagram and a coordination time interval report, including: Convert the protection configuration scheme into a parameter format recognizable by the simulation system, load it into the real-time digital simulation platform, and build a power grid fault simulation environment; In the power grid fault simulation environment, a conventional operating condition group is set, including basic load, peak load and light load operation states, and fault events of each virtual fault point are triggered in sequence; For each fault event in the conventional working condition group, record the action time and tripping sequence of each protection device, and draw a time sequence distribution diagram of the protection device action; In the power grid fault simulation environment, an extreme working condition group is set, including large load fluctuations, multi-point simultaneous faults and power output sudden changes, to trigger key node faults; Extracting the action time difference between the main protection and the backup protection from the fault response data of the extreme working condition group to form a protection coordination margin statistical table; The protection device action time sequence distribution diagram and the protection coordination margin statistics table are integrated into a protection action sequence diagram and a coordination time interval report.

7. The method for intelligent configuration of a power grid overcurrent protection device according to claim 1, characterized in that: According to the protection action sequence diagram and the coordination time interval report, the optimized protection parameters are converted into a device-specific format and sent to each protection device through a secure channel to complete the protection configuration implementation, including: Re-verify the safety of the protection action sequence diagram, check whether all protection action sequences meet the coordination requirements, and select protection parameter sets that meet the standards; According to the margin data in the coordination time interval report, the protection parameter sets are prioritized and a key protection device parameter distribution sequence table is determined; According to the communication protocol specifications of each protection device manufacturer, the protection parameter set is converted into a format to generate a device-specific parameter file that complies with the IEC 61850 standard; Establish an encrypted and secure communication channel, connect to the communication interface of each protection device, and create a parameter delivery session; Transmitting the device-specific parameter files to corresponding protection devices in groups according to the sending sequence table to implement parameter configuration; The configured protection device parameters are read back and compared and verified through the remote verification mechanism to confirm that the protection configuration has been implemented.

8. An intelligent configuration system for a power grid overcurrent protection device, characterized in that: Used to implement the intelligent configuration method of the power grid overcurrent protection device according to any one of claims 1 to 7, the power grid overcurrent protection device intelligent configuration system comprises: The acquisition module is used to collect the connection relationship and operating parameters of busbars, lines and transformers through the power grid monitoring system, clean the collected data and convert the units to obtain a standardized power grid topology database; A setting module, used to set multiple virtual fault points in the key protection area according to the standardized power grid topology database, calculate the short-circuit current value and distribution characteristics under each fault point, and generate a fault feature library; An extraction module is used to extract the pairing relationship between the main protection and the backup protection based on the fault feature library, construct an action time difference table and a protection coverage index, and form a set of protection coordination constraint conditions; An optimization module, used for combining and optimizing the action current threshold and time delay parameters of each protection device according to the protection coordination constraint condition set, and outputting a protection configuration scheme that meets the coordination requirements; A simulation module, used to utilize the protection configuration scheme to simulate fault responses under normal and extreme working conditions through a power grid simulation system, and generate a protection action sequence diagram and a coordination time interval report; The sending module is used to convert the optimized protection parameters into a device-specific format according to the protection action sequence diagram and the coordination time interval report, and send them to each protection device through a secure channel to complete the protection configuration implementation.

9. An intelligent configuration device for a power grid overcurrent protection device, characterized in that: It comprises a memory and a processor, the memory stores a computer program that can be run on the processor, and the processor implements the intelligent configuration method of the power grid overcurrent protection device according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the processor is enabled to execute the method for intelligent configuration of a power grid overcurrent protection device according to any one of claims 1 to 7.

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