Distribution network relay protection method based on dynamic setting

Abstract

This application discloses a dynamic setting-based distribution network relay protection method, belonging to the field of relay protection technology. The method includes: obtaining equipment aging risk relationships based on historical fault information of power equipment and dynamic grid connection topology; obtaining power transfer risk relationships based on historical operating data of power equipment and dynamic grid connection topology; constructing a setting optimization objective function based on the minimum setting correction number and the minimum impact area; obtaining grid connection probability and a set of grid connection topologies based on current load data, dynamic grid connection relationships, and dynamic grid connection topology; and obtaining a dynamic setting strategy through iterative optimization using the setting optimization objective function, equipment aging risk relationships, power transfer risk relationships, grid connection probability, and set of grid connection topologies. The beneficial effect of this application is to improve the timeliness and reliability of relay protection.

Description

Technical Field

[0001] This application relates to the field of relay protection technology, and in particular to a distribution network relay protection method based on dynamic setting. Background Technology

[0002] With the continuous advancement of smart grid construction, distributed power sources (such as photovoltaic, wind power, and energy storage) and microgrid systems are being connected to the distribution network on a large scale, transforming the distribution network from a traditional radial unidirectional power supply structure into a complex dynamic network with multiple power sources and multiple topologies.

[0003] In related technologies, distribution network relay protection setting methods are typically based on static topology and fixed operating modes, relying on pre-set short-circuit current calculations and protection setting configurations. Therefore, when distributed power sources connect to the grid, microgrids switch operating modes, or power is transferred after a distribution network fault, the system topology changes frequently, leading to changes in the magnitude, direction, and distribution characteristics of the short-circuit current. Traditional fixed setting values ​​are prone to causing protection maloperation, failure to operate, or coordination failure. Furthermore, existing methods only consider single risk factors such as short-circuit faults, but in actual operation, frequent topology switching accelerates the aging of equipment such as circuit breakers and tie switches, resulting in relay protection failure or lag.

[0004] The patent, "A Power Relay Protection Monitoring Method, Equipment, and Medium Based on Intelligent Matching," publication number CN120150059 A, published on June 13, 2025, discloses the following method: Step S1, obtaining power fault data and power usage data of power lines based on line numbers; Step S2, setting relay protection measures for power lines based on power fault data; Step S3, collecting real-time operating data of different power lines and analyzing and judging the operating status of power lines based on real-time operating data; Step S4, obtaining the real-time determined duration of the fault interval corresponding to the power line; Step S5, analyzing the protection efficiency of the corresponding relay protection measures for the power line based on the determined duration. This scheme constructs relay protection measures through power line fault prediction; however, when fault prediction deviates, the relay protection measures cannot be adjusted in a timely manner, causing delays in relay protection.

[0005] The patent, "A Method, Device, and Storage Medium for Fault Diagnosis of Electrical System Relay Protection," publication number CN120085083A, published on June 3, 2025, specifically discloses a method for efficient processing and analysis of power system relay protection data by combining U-MAP and kernel ridge regression techniques. First, U-MAP is used for feature selection and data preprocessing to capture nonlinear structures and complex patterns in the data. Then, kernel ridge regression is used for classification and prediction, improving the accuracy and response speed of relay protection. Although this scheme predicts relay protection faults, it still relies on updating the model based on already generated electrical signals and matching protection strategies. All protection mechanisms need to be calculated and triggered uniformly, resulting in low efficiency. Summary of the Invention

[0006] This application addresses the problems of low efficiency and poor accuracy in existing relay protection technologies, which rely on fault prediction results for adjustment. It provides a dynamic setting-based distribution network relay protection method. This method obtains the power equipment fault probability and relay protection deviation risk under various grid connection conditions by considering equipment aging risk and power transfer risk. Then, based on the grid connection probability, power equipment fault probability, and relay protection deviation risk, it outputs relay protection setting strategies for all conditions. Furthermore, it obtains the optimal dynamic setting strategy when no risk currently exists, based on the minimum number of setting corrections and the minimum impact area. It prioritizes outputting setting sheets, and when a grid connection prediction deviation occurs, it corrects the pre-output setting sheets, thereby reducing the relay protection strategy adjustment time and improving the reliability and timeliness of relay protection.

[0007] To achieve the aforementioned technical objectives, this application provides a technical solution: a distribution network relay protection method based on dynamic setting, comprising the following steps: constructing a hierarchical topology structure of main grid, distribution network, and microgrid based on the main grid structure, distribution network structure, and microgrid structure; constructing dynamic grid connection relationships and dynamic grid connection topology based on historical grid connection data and the hierarchical topology structure of main grid, distribution network, and microgrid; obtaining equipment aging risk relationships based on historical fault information of power equipment and the dynamic grid connection topology; obtaining power transfer risk relationships based on historical operating data of power equipment and the dynamic grid connection topology; constructing a setting optimization objective function based on the minimum number of switching operations and the minimum impact area; obtaining grid connection probability and a set of grid connection topologies based on current load data, dynamic grid connection relationships, and the dynamic grid connection topology; and obtaining a dynamic setting strategy through iterative optimization using the setting optimization objective function, equipment aging risk relationships, power transfer risk relationships, grid connection probability, and set of grid connection topologies.

[0008] Furthermore, the construction of dynamic grid connection relationships and dynamic grid connection topology based on historical grid connection data and the hierarchical topology of the main distribution microgrid includes: extracting the main distribution network operation characteristics and main distribution microgrid structural characteristics under different grid connection states, constructing the influence relationship between operation characteristics and structural characteristics on grid connection, and obtaining dynamic grid connection relationships; and obtaining the dynamic grid connection topology of the hierarchical topology of the main distribution microgrid under single grid connection and multiple grid connection conditions based on the historical grid connection structure.

[0009] Furthermore, the step of obtaining equipment aging risk relationships based on historical fault information of power equipment and dynamic grid-connected topology includes: constructing a first equipment aging risk relationship related to electrical parameters based on historical fault information of power equipment in non-dynamic grid-connected topology; constructing a second equipment aging risk relationship related to electrical parameters and a third equipment aging risk relationship related to hardware actions based on historical fault information of power equipment in dynamic grid-connected topology.

[0010] Furthermore, the step of obtaining the transfer risk relationship based on the dynamic grid connection topology using historical operating data of power equipment includes: obtaining the inrush current when each dynamic grid connection topology is connected to the grid based on historical operating data of power equipment; obtaining the corresponding relay protection equipment for each dynamic grid connection topology; and constructing the transfer risk relationship based on the inrush current, relay protection equipment information, and dynamic grid connection topology information, using response timing and response deviation.

[0011] Furthermore, the step of constructing a power transfer risk relationship based on response timing and response deviation according to inrush current, relay protection equipment information, and dynamic grid connection topology information includes: constructing a first correlation between grid connection topology type and inrush current based on grid connection information and inrush current of dynamic grid connection topology; constructing protection maloperation probability based on relay protection equipment setting value and inrush current; constructing a second correlation between grid connection topology type and response time based on dynamic grid connection topology operation time and relay protection equipment operation time; constructing a third correlation between equipment aging degree and response sensitivity based on historical response deviation of dynamic grid connection topology and historical response deviation of relay protection equipment; and constructing a power transfer risk relationship based on the first correlation, protection maloperation probability, second correlation, and third correlation.

[0012] Furthermore, the objective function for setting optimization based on the minimum number of setting corrections and the minimum impact area includes: obtaining the number of setting corrections based on the number of setting corrections for the relay protection strategy; and obtaining the impact area based on the power outage range caused by the relay protection.

[0013] Furthermore, the step of obtaining the grid connection probability and the set of grid connection topologies based on the current load data, dynamic grid connection relationship, and dynamic grid connection topology includes: obtaining the grid connection probability of each distribution network and / or microgrid based on the current load data of the main distribution microgrid, the current operation data of the main distribution microgrid, and the dynamic grid connection relationship, and retrieving the grid connection topology of each distribution network and / or microgrid in the dynamic grid connection topology.

[0014] Furthermore, the step of obtaining a dynamic setting strategy through iterative optimization of the objective function, equipment aging risk relationship, power transfer risk relationship, grid connection probability, and grid topology set includes: calculating equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship; obtaining the relay protection equipment operation probability and relay protection equipment setting deviation based on the equipment aging risk data and power transfer risk data; and outputting a dynamic setting strategy based on the relay protection equipment operation probability and relay protection equipment setting deviation according to the objective function.

[0015] Furthermore, the calculation of equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship includes: obtaining equipment aging risk data for each power device based on each grid connection topology and equipment aging risk relationship; obtaining inrush current prediction values ​​based on each grid connection topology and the first correlation; obtaining relay protection device setting constraint values ​​based on protection maloperation probability and inrush current prediction values; obtaining power device response timing chains based on each grid connection topology and the second correlation; obtaining power device response sensitivity based on equipment aging risk data and the third correlation; and obtaining power transfer risk data corresponding to each grid connection topology using relay protection device setting constraint values, power device response timing chains, and power device response sensitivity.

[0016] Furthermore, the step of obtaining the relay protection device operation probability and relay protection device setting deviation based on equipment aging risk data and power transfer risk data includes: obtaining the relay protection device operation probability based on equipment aging risk data; obtaining the power equipment response timing deviation value based on the power equipment response timing chain and power equipment response sensitivity; and using the power equipment response timing deviation and relay protection device setting constraint value as the relay protection device setting deviation.

[0017] The beneficial effects of this application are as follows: 1. By constructing a hierarchical topology structure of main grid, distribution grid, and microgrid, it is convenient to intuitively obtain the dynamic grid connection relationship between the main grid, distribution grid, and microgrid by combining historical grid connection data and observing the dynamic changes in the connections between the layers, thus simplifying the complex power grid structure. Furthermore, based on the changes in the connection relationships at different levels, the aging risk relationship of equipment affected by grid connection and the transfer risk relationship can be obtained. At the same time, based on the minimum number of setting corrections and the minimum impact area, a setting optimization objective function is constructed, so that even if a deviation from the predicted situation occurs under the condition of advance dynamic setting, the number of setting corrections required and the impact area can be reduced, thereby maximizing the accuracy and timeliness of relay protection under grid connection conditions.

[0018] 2. By calculating equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship, the system displays the failure probability and relay protection deviation risk of each power device under different grid connection conditions. Then, based on the setting optimization objective function, relay protection device operation probability, and relay protection device setting deviation, the system obtains a relay protection device setting strategy that minimizes the number of setting corrections, has the smallest impact range, and the highest probability compared to all grid connection conditions. This ensures that the setting values ​​of the relay protection devices after grid connection are adapted to the current grid connection situation, and that the corresponding relay protection devices are adjusted in a timely manner when deviations occur in the grid connection prediction, thus ensuring the accuracy and reliability of relay protection. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the distribution network relay protection method based on dynamic setting proposed in this application.

[0020] Figure 2 This is a flowchart illustrating the construction of the transfer risk relationship based on the dynamically set distribution network relay protection method of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely one preferred embodiment of this application and are only used to explain this application. They do not limit the scope of protection of this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] like Figure 1 As shown, the distribution network relay protection method based on dynamic setting includes the following steps:

[0023] A hierarchical topology of main network, distribution network, and microgrid is constructed based on the main network structure, distribution network structure, and microgrid structure;

[0024] Based on historical grid connection data and the hierarchical topology of the main and distribution microgrids, a dynamic grid connection relationship and dynamic grid connection topology are constructed.

[0025] Based on historical fault information of power equipment and dynamic grid topology, the relationship between equipment aging risks is obtained;

[0026] Based on historical operating data of power equipment and dynamic grid topology, the risk relationship of power transfer is obtained;

[0027] Construct a tuning optimization objective function based on the minimum number of tuning corrections and the minimum influence region;

[0028] Based on current load data, dynamic grid connection relationships, and dynamic grid connection topology, obtain the grid connection probability and the set of grid connection topologies;

[0029] The dynamic tuning strategy is obtained by iterative optimization of the objective function, equipment aging risk relationship, power transfer risk relationship, grid connection probability, and grid topology set.

[0030] In this embodiment, by constructing a hierarchical topology of main grid, distribution grid, and microgrid, the dynamic grid connection relationship between the main grid, distribution grid, and microgrid can be intuitively obtained by combining historical grid connection data and observing the dynamic changes in the connections between the layers, simplifying the complex power grid structure. Furthermore, based on changes in the connection relationships at different levels, the aging risk relationship of equipment affected by grid connection and the risk relationship of power transfer can be obtained. Simultaneously, a setting optimization objective function is constructed based on the minimum number of setting corrections and the minimum impact area. This ensures that even if deviations from the predicted situation occur under advance dynamic setting, the number of setting corrections required and the impact area can be minimized, thereby maximizing the accuracy and timeliness of relay protection under grid connection conditions.

[0031] Specifically, constructing a hierarchical topology based on the main network structure, distribution network structure, and microgrid structure includes:

[0032] Construct a main network topology layer based on the main network structure;

[0033] Each distribution network topology layer is constructed based on its respective distribution network structure, with each distribution network including at least one distribution network topology layer.

[0034] Each microgrid topology layer is constructed based on its own microgrid structure, with each microgrid including at least one microgrid topology layer.

[0035] For a given main grid system, there are multiple distribution grid systems and microgrid systems. Therefore, each distribution grid structure constructs a distribution grid topology layer, and each microgrid structure constructs a microgrid topology layer. Since all electrical equipment participates in grid connection for each distribution grid system and each microgrid system, each distribution grid system and microgrid system is treated as a whole. This simplifies the complex power grid relationships into relationships between overall structures, reducing analytical complexity and improving analytical efficiency.

[0036] Based on historical grid connection data and the hierarchical topology of the main and distribution microgrids, a dynamic grid connection relationship and dynamic grid connection topology are constructed, including:

[0037] Extract the main and distribution network operation characteristics and main and distribution microgrid structure characteristics under different grid connection states, construct the influence relationship between operation characteristics and structure characteristics on grid connection, and obtain dynamic grid connection relationship;

[0038] Based on historical grid connection structures, obtain the dynamic grid connection topology of the hierarchical topology of the main and distribution microgrids under single and multiple grid connection scenarios.

[0039] Historical grid connection data includes at least the main grid operation data, distribution network operation data, and microgrid operation data before grid connection. Operation data includes at least voltage, current, power, load, and frequency data. Principal component analysis or neural network learning algorithms are used to extract the main and distribution network operation characteristics and the main-distribution-microgrid structural characteristics under different grid connection states. The impact of different main and distribution network operation characteristics and main-distribution-microgrid structural characteristics on grid connection selection is obtained, and dynamic grid connection relationships are acquired. Simultaneously, based on the structural changes of the hierarchical topology of the main-distribution-microgrid during grid connection, the dynamic grid connection topology under single and multiple grid connection scenarios is obtained, facilitating subsequent refinement of the impact on the structure undergoing state changes. It is understood that although this embodiment constructs a separate grid connection topology for microgrid connection, since microgrids are typically connected through the distribution network, distribution network relay protection settings are usually included in the microgrid relay protection settings.

[0040] Based on historical fault information of power equipment and dynamic grid topology, the relationships of equipment aging risks are obtained, including:

[0041] Construct a first equipment aging risk relationship based on historical fault information of power equipment in a non-dynamic grid-connected topology;

[0042] Based on historical fault information of power equipment in a dynamic grid-connected topology, a second equipment aging risk relationship related to electrical parameters and a third equipment aging risk relationship related to hardware actions are constructed.

[0043] Based on whether the equipment operates under grid connection conditions, the topology is divided into dynamic grid-connected topologies and non-dynamic topologies. For non-dynamic topologies, the relationship between electrical parameters and equipment failures is obtained based on historical fault information of power equipment to construct a first equipment aging risk relationship. For dynamic topologies, the relationship between electrical parameters and equipment failures is obtained based on historical fault information of power equipment to construct a second equipment aging risk relationship, and the relationship between equipment operation and equipment failures is obtained based on power equipment failure information to construct a third equipment aging risk relationship. By constructing separate equipment aging risks based on the differences in equipment operation under grid connection conditions, the accuracy of aging patterns under both static and dynamic operating states is improved, thereby enhancing the accuracy of equipment failure prediction.

[0044] Specifically, based on historical fault information of power equipment in a dynamic grid-connected topology, a second equipment aging risk relationship related to electrical parameters and a third equipment aging risk relationship related to hardware actions are constructed, including:

[0045] The historical fault information of power equipment corresponding to the dynamic grid-connected topology is divided into a first fault set where no equipment action occurs and a second fault set where equipment action occurs.

[0046] Construct a second equipment aging risk relationship based on the first fault set;

[0047] Construct a third equipment aging risk relationship based on the second set of faults.

[0048] Historical fault information for power equipment includes at least the equipment's electrical parameters, operational information, and environmental data from the time of commissioning to the time of failure. Electrical parameters include voltage, current, and power. Environmental data includes temperature and humidity. Operational information includes the number of operations and frequency. It is understood that in this embodiment, the power grid line is also considered a type of power equipment. Whether or not the power grid line is connected is used as the criterion for determining whether an operation has occurred; for example, if the power grid line changes from a current-carrying state to a current-free state, it is considered that the power grid line has operated.

[0049] In some feasible embodiments, the steps for constructing the equipment aging risk relationship are as follows:

[0050] S01: Perform data preprocessing on historical fault information of power equipment to remove outliers and fill in missing values;

[0051] S02: Based on the equipment fault type, the historical fault information of the power equipment will be divided into the first category to obtain the fault set corresponding to the equipment fault type;

[0052] S031: For each fault set in a non-dynamic grid-connected topology, extract the equipment electrical parameter characteristics and equipment environmental characteristics, construct a linear relationship between the equipment electrical parameter characteristics, equipment environmental characteristics and fault probability based on linear regression analysis, and obtain the first equipment aging risk relationship;

[0053] S032: For each fault set in the dynamic grid-connected topology, a second division is performed based on whether there is equipment action, to obtain the first fault set and the second fault set;

[0054] S033: Extract the equipment electrical parameter characteristics and equipment environmental characteristics from the first fault set, construct the linear relationship between the equipment electrical parameter characteristics, equipment environmental characteristics and fault probability based on linear regression analysis, and obtain the second equipment aging risk relationship;

[0055] S034: Extract the equipment action features from the second fault set, construct the relationship between equipment action features and fault probability based on fault tree analysis, and obtain the third equipment aging risk relationship;

[0056] S04: Construct the equipment aging risk relationship based on the first equipment aging risk, the second equipment aging risk relationship, and the third equipment aging risk relationship.

[0057] The electrical parameter characteristics of the equipment include at least time-domain characteristics, frequency-domain characteristics, and trend characteristics. The operational characteristics of the equipment include at least frequency and quality characteristics. In some cases, machine learning models such as random forests can also be used to construct relationships related to equipment aging risks.

[0058] Based on historical operating data of power equipment and dynamic grid topology, the risk relationships of power transfer are obtained, including:

[0059] The inrush current during grid connection of each dynamic grid-connected topology is obtained based on historical operating data of power equipment.

[0060] Based on each dynamic grid-connected topology, the corresponding relay protection equipment is obtained. Based on the inrush current, relay protection equipment information, and dynamic grid-connected topology information, the transfer risk relationship is constructed according to the response timing and response deviation.

[0061] It is understandable that the relay protection devices obtained based on various dynamic grid-connected topologies may be included in both dynamic and non-dynamic grid-connected topologies. In power transfer scenarios, the amplitude and duration of the inrush current directly affect the insulation life of the equipment and the probability of relay protection maloperation. If the inrush current exceeds the relay protection setting value, it may trigger false tripping, leading to power transfer failure. Alternatively, high-frequency inrush current may cause equipment heating or mechanical stress accumulation, increasing the risk of hidden faults during the power transfer process. Dynamic grid-connected topologies are structures whose state changes due to power transfer. To a certain extent, the inrush current caused by power transfer primarily affects the dynamic grid-connected topology. Therefore, calculating the power transfer risk for dynamic grid-connected topologies is crucial to ensure that the relay protection setting value is adapted to possible power transfer situations, thereby ensuring the safety and stability of the power grid during the power transfer process.

[0062] like Figure 2 As shown, the risk relationship for power transfer is constructed based on the inrush current, relay protection equipment information, and dynamic grid topology information, according to the response timing and response deviation. This includes:

[0063] Based on grid connection information of dynamic grid connection topology and inrush current, a first correlation relationship between grid connection topology type and inrush current is constructed.

[0064] Construct the probability of protection maloperation based on the setting value of relay protection equipment and the inrush current;

[0065] A second correlation between grid topology type and response time is constructed based on the action time of dynamic grid topology and the action time of relay protection equipment.

[0066] A third correlation between equipment aging degree and response sensitivity is constructed based on the historical response deviation of dynamic grid-connected topology and the historical response deviation of relay protection equipment.

[0067] The risk relationship for transferring supply is constructed based on the first association, the probability of false activation, the second association, and the third association.

[0068] In this embodiment, a first correlation is established between the grid connection information of the dynamic grid-connected topology and the inrush current to reflect the response characteristics of different grid-connected topology types when subjected to inrush current. A protection maloperation probability is established between the relay protection device setting value and the inrush current to quantify the risk of maloperation of the relay protection device under the influence of inrush current. A second correlation is established between the operating time of the dynamic grid-connected topology and the operating time of the relay protection device to reflect the degree of matching between the grid-connected topology and the relay protection device in terms of response time. A response sensitivity impact relationship is established between the historical response deviation of the dynamic grid-connected topology and the historical response deviation of the relay protection device to reflect the influence of equipment aging on the device's response sensitivity. Furthermore, a multi-factor transfer risk relationship is constructed based on the first correlation, the protection maloperation probability, the second correlation, and the third correlation to quantify the risk of relay protection setting value deviation under transfer conditions.

[0069] The tuning optimization objective function is constructed based on the minimum number of tuning corrections and the minimum influence region, including:

[0070] The number of setting corrections is obtained based on the number of times the relay protection strategy is set;

[0071] The affected area is obtained based on the power outage range caused by relay protection.

[0072] In this embodiment, the number of setting corrections for a single relay protection operation is calculated based on the number of relay protection device setting corrections compared to all other relay protection strategies. The affected area is then calculated based on the power outage range caused by this relay protection strategy. The objective function for setting optimization is:

[0073] ;

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] Where minF represents the tuning optimization objective function, This indicates that the number of tuning corrections affects the weight. , Indicates the weight of the influence area. , Indicates the number of tuning corrections. Indicates the affected area, and I indicates the number of relay protection devices. This represents the number of setting corrections for the i-th relay protection device, and K represents the number of power supply nodes. This represents the true value of the influence of the k-th power supply node. This represents the load fluctuation value of the k-th power supply node when the relay protection equipment switches under the current dynamic setting strategy.

[0079] If the load of a power supply node fluctuates when the relay protection device switches, it is considered that the power supply node is affected by the relay protection device switching and is recorded as 1. If the load of a power supply node does not fluctuate when the relay protection device switches, it is considered that the power supply node is not affected by the relay protection device switching and is recorded as 0.

[0080] Based on current load data, dynamic grid connection relationships, and dynamic grid connection topology, the grid connection probability and the set of grid connection topologies are obtained, including:

[0081] Based on the current load data of the main distribution microgrid, the current operation data of the main distribution microgrid, and the dynamic grid connection relationship, obtain the grid connection probability of each distribution network and / or microgrid, and retrieve the grid connection topology of each distribution network and / or microgrid in the dynamic grid connection topology.

[0082] Furthermore, the dynamic tuning strategy is obtained through iterative optimization of the objective function, equipment aging risk relationships, power transfer risk relationships, grid connection probability, and grid topology set, including:

[0083] Calculate equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship;

[0084] Based on equipment aging risk data and power transfer risk data, obtain the operation probability of relay protection equipment and the setting deviation of relay protection equipment;

[0085] Based on the objective function of setting optimization, a dynamic setting strategy is output according to the operating probability of the relay protection equipment and the setting deviation of the relay protection equipment.

[0086] By calculating equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship, the failure probability and relay protection deviation risk of each power equipment under different grid connection conditions are displayed. Then, based on the setting optimization objective function, relay protection equipment operation probability, and relay protection equipment setting deviation, a relay protection equipment setting strategy with the fewest setting corrections, the smallest impact range, and the highest probability compared to all grid connection conditions is obtained. This strategy ensures that the setting value of the relay protection equipment after grid connection can be adapted to the current grid connection situation, and that the corresponding relay protection equipment can be adjusted in a timely manner when deviations occur in the grid connection prediction, thus ensuring the accuracy and reliability of relay protection.

[0087] Specifically, the calculation of equipment aging risk data and power transfer risk data based on grid connection probability, grid topology, equipment aging risk relationship, and power transfer risk relationship includes:

[0088] Based on the grid connection topology and the relationship between equipment aging risk, obtain equipment aging risk data for each power equipment;

[0089] The predicted value of the inrush current is obtained based on each grid topology and the first correlation.

[0090] The setting constraint values ​​of relay protection equipment are obtained based on the protection maloperation probability and the predicted value of the inrush current.

[0091] The response timing chain of power equipment is obtained based on each grid topology and the second correlation.

[0092] The response sensitivity of power equipment is obtained based on equipment aging risk data and third-party correlations.

[0093] The transfer risk data corresponding to each grid-connected topology is obtained by using the setting constraint values ​​of relay protection equipment, the response timing chain of power equipment, and the response sensitivity of power equipment.

[0094] Furthermore, based on equipment aging risk data and power transfer risk data, the probability of relay protection equipment operation and the setting deviation of relay protection equipment are obtained, including:

[0095] Obtain the probability of relay protection equipment operation based on equipment aging risk data;

[0096] The power equipment response timing deviation value is obtained based on the power equipment response timing chain and the power equipment response sensitivity.

[0097] The timing deviation of the power equipment response and the setting constraint value of the relay protection equipment are used as the setting deviation of the relay protection equipment.

[0098] In this embodiment, the failure probability caused by the aging risk of power equipment is used to calculate the operation probability of each relay protection device under grid connection. At the same time, the response timing of the device is corrected by the change in device sensitivity caused by the aging risk. Then, the priority setting of the dynamic adjustment strategy is performed according to the operation probability and response timing of the relay protection device.

[0099] Based on the objective function of setting optimization, and considering the operating probability and setting deviation of relay protection equipment, a dynamic setting strategy is output, including:

[0100] The set of relay protection device setting strategies is obtained based on the relay protection device operation probability and relay protection device setting deviation.

[0101] The optimal dynamic setting strategy is obtained based on the set of setting strategies for relay protection equipment according to the setting optimization objective function.

[0102] In this embodiment, relay protection device operation combinations corresponding to various probability conditions are constructed based on the operation probability of the relay protection device. The setting values ​​and response timing of the relay protection device are set based on the setting deviation. The priority of the relay protection device setting strategy is obtained based on the operation probability and grid connection probability. Then, the optimal dynamic setting strategy for the relay protection device setting strategy set is obtained based on the setting optimization objective function combined with the priority of the relay protection device setting strategy. A setting value sheet is output based on the current optimal dynamic setting strategy. The optimal dynamic setting strategy satisfies both the highest grid connection probability and the highest operation probability, and also minimizes the number of setting value sheets required to adjust when there is a deviation in the grid connection prediction, thereby improving the timeliness and accuracy of relay protection.

[0103] In this embodiment, the distribution network relay protection method based on dynamic setting further includes:

[0104] Real-time acquisition of main and distribution microgrid operation data, and real-time adjustment of the optimal dynamic tuning strategy based on the main and distribution microgrid operation data;

[0105] Real-time acquisition of equipment fault data; retrieval of dynamic tuning strategies for corresponding actions based on the equipment fault data; and execution of setting corrections.

[0106] By acquiring real-time operation data of the main and distribution microgrids, the optimal dynamic setting strategy under grid-connected status is adjusted, and the setting sheet is corrected. At the same time, when a power equipment fails, the corresponding setting strategy in the relay protection equipment setting strategy set is directly retrieved to correct the setting sheet and execute relay protection. Thus, when a fault occurs, the setting sheet that does not need to be adjusted can be directly output, improving the efficiency of relay protection.

[0107] For example, in the power grid architecture of main grid Q, distribution networks R1, R2, R3, R4, microgrids U1, U2, and U3, the status changes of key equipment such as circuit breakers and disconnectors in the main grid, distribution networks, and microgrids during each grid connection process are recorded in advance through the control cloud platform. This includes things like switch opening and closing actions and transformer tap adjustments, thus constructing a historical grid connection database. Based on this database, the grid connection status of distribution networks R1, R2, R3, R4, U1, U2, and U3 under different load conditions in main grid Q is obtained, along with the structure of the status changes of each distribution network and microgrid during grid connection. This allows for the acquisition of dynamic grid connection relationships and dynamic grid connection topology. For example, when the main grid load Q exceeds 80% of its rated capacity, the probability of distribution networks R1 and R2 simultaneously connecting to the grid reaches 75%. This establishes a correlation between the main grid load and the grid connection status of distribution networks / microgrids (dynamic grid connection relationship). The connections between distribution networks, microgrids, and the main grid are abstracted into a directed graph, where nodes represent grid units and edges represent power connection lines. The graph structure is updated based on changes in equipment status during historical grid connections, thus obtaining the dynamic grid connection topology. Furthermore, based on current load data and the dynamic grid connection relationship, distribution networks and / or microgrids that may connect to the grid in the future can be identified. It is understandable that load forecasting methods (such as load forecasting models) can be used to obtain future load data from current load data, thereby determining the probability of future grid connection.

[0108] Next, for each distribution network and microgrid's grid-connected topology, the operating parameters of the power equipment under grid-connected conditions are obtained. Based on these operating parameters and the relationship between equipment aging risk and the actual aging risk, the aging risk data for each power equipment is calculated. Simultaneously, the magnitude and waveform of the inrush current generated under different grid-connected structures are calculated based on the grid-connected topology of each distribution network and microgrid. The sequence of actions of each power equipment during the grid-connection process under different grid-connected structures is calculated based on the grid-connected topology of each distribution network and microgrid, constructing a response timing chain. By combining the equipment aging risk data with the historical response time data of the power equipment, the response delay of the power equipment under aging conditions, i.e., the response sensitivity of the power equipment, is obtained.

[0109] The probability of relay protection device operation is obtained based on the equipment aging risk data under each grid-connected topology. The higher the equipment aging risk, the greater the probability of relay protection device operation on the corresponding line. The timing of relay protection device response is obtained based on the power equipment response timing chain and power equipment response sensitivity. The setting value of relay protection device is adjusted according to the setting constraint value of relay protection device to avoid maloperation of relay protection device due to inrush current. Based on each grid-connected topology, the operating timing and setting values ​​of relay protection devices under various grid-connected conditions were obtained, forming a set of relay protection device setting strategies. These strategies were prioritized based on the grid connection probability. The set of relay protection device setting strategies includes at least one strategy corresponding to each of distribution network R1, R2, R3, R4, microgrid U1, microgrid U2, and microgrid U3. For example, if the grid connection probability of distribution network R1 is 90% and that of distribution network R2 is 40%, then the relay protection device setting strategy for distribution network R1 has a higher priority. Then, based on the setting optimization objective function, the number of setting corrections and the affected area of ​​all relay protection device setting strategies were obtained. The setting strategy with the highest priority and the smallest number of setting corrections and affected area was output as the dynamic setting strategy. In some cases, weight coefficients corresponding to priority and the smallest number of setting corrections and affected area can be set to select the setting strategy with higher priority and the smallest number of setting corrections and affected area. Simultaneously, load data is acquired in real time, and dynamic equipment setting strategies are continuously adjusted to ensure that relay protection can be performed quickly in the event of equipment failure.

[0110] The specific embodiments described above are preferred embodiments of the distribution network relay protection method based on dynamic setting in this application, and are not intended to limit the specific implementation scope of this application. The scope of this application includes but is not limited to the specific embodiments described above. All equivalent changes made in accordance with the shape and structure of this application are within the protection scope of this application.

Claims

1. A method for relay protection of distribution network based on dynamic setting, characterized in that: The method comprises the following steps: constructing a main-distribution-microgrid hierarchical topology structure based on a main grid structure, a distribution grid structure, and a microgrid structure; constructing a dynamic grid-connection relationship and a dynamic grid-connection topology structure according to historical grid-connection data and the main-distribution-microgrid hierarchical topology structure; obtaining a device aging risk relationship based on the dynamic grid-connection topology structure according to historical fault information of power equipment; obtaining a transfer risk relationship based on the dynamic grid-connection topology structure according to historical operation data of power equipment; constructing a setting optimization objective function based on a minimum setting correction frequency and a minimum influence area; obtaining a grid-connection probability and a grid-connection topology structure set based on current load data, the dynamic grid-connection relationship, and the dynamic grid-connection topology structure; obtaining a dynamic setting strategy through iterative optimization of the setting optimization objective function, the device aging risk relationship, the transfer risk relationship, the grid-connection probability, and the grid-connection topology structure set; wherein, main-distribution grid operation characteristics and main-distribution-microgrid structure characteristics in different grid-connection states are extracted, an influence relationship of the operation characteristics and the structure characteristics on grid-connection is constructed, and a dynamic grid-connection relationship is obtained; constructing a first device aging risk relationship related to electrical parameters according to historical fault information of power equipment in a non-dynamic grid-connection topology structure; constructing a second device aging risk relationship related to electrical parameters and a third device aging risk relationship related to hardware action according to historical fault information of power equipment in a dynamic grid-connection topology structure; obtaining an inrush current when each dynamic grid-connection topology structure is connected according to historical operation data of power equipment; obtaining corresponding relay protection equipment for each dynamic grid-connection topology structure, and constructing a transfer risk relationship based on response time and response deviation according to the inrush current, relay protection equipment information, and dynamic grid-connection topology structure information; obtaining a setting correction frequency based on a relay protection strategy setting correction frequency; obtaining an influence area based on a power cut range caused by relay protection.

2. The distribution grid relay protection method based on dynamic setting according to claim 1, wherein: the step of constructing a dynamic grid-connection relationship and a dynamic grid-connection topology structure according to historical grid-connection data and the main-distribution-microgrid hierarchical topology structure comprises: obtaining dynamic grid-connection topology structures of the main-distribution-microgrid hierarchical topology structure in single grid-connection and multiple grid-connection cases based on historical grid-connection structures.

3. The distribution grid relay protection method based on dynamic setting according to claim 2, wherein: the step of constructing a transfer risk relationship based on response time and response deviation according to the inrush current, relay protection equipment information, and dynamic grid-connection topology structure information comprises: constructing a first association relationship between a grid-connection topology type and an inrush current based on grid-connection information of the dynamic grid-connection topology structure and the inrush current; constructing a protection misoperation probability based on a relay protection equipment setting value and the inrush current; constructing a second association relationship between the grid-connection topology type and a response time according to an action time of the dynamic grid-connection topology structure and an action time of the relay protection equipment; constructing a third association relationship between a device aging degree and a response sensitivity based on a historical response deviation of the dynamic grid-connection topology structure and a historical response deviation of the relay protection equipment; constructing the transfer risk relationship based on the first association relationship, the protection misoperation probability, the second association relationship, and the third association relationship.

4. The method of claim 1, wherein the dynamic setting-based distribution network relay protection method is characterized in that: the obtaining of the grid-connection probability and the set of grid-connection topologies based on the current load data, the dynamic grid-connection relationship, and the dynamic grid-connection topologies comprises: the obtaining of the grid-connection probability of each distribution network and / or microgrid according to the current load data of the main distribution microgrid, the current operation data of the main distribution microgrid, and the dynamic grid-connection relationship, and the calling of the grid-connection topology of each distribution network and / or microgrid in the dynamic grid-connection topologies.

5. The method of claim 1, wherein the dynamic setting-based distribution network relay protection method is characterized in that: the optimization iteration of the dynamic setting strategy based on the setting optimization objective function, the equipment aging risk relationship, the transfer supply risk relationship, the grid-connection probability, and the set of grid-connection topologies comprises: the calculation of the equipment aging risk data and the transfer supply risk data according to the grid-connection probability, the grid-connection topology, the equipment aging risk relationship, and the transfer supply risk relationship; the obtaining of the relay protection device action probability and the relay protection device setting deviation according to the equipment aging risk data and the transfer supply risk data; the output of the dynamic setting strategy based on the relay protection device action probability and the relay protection device setting deviation according to the setting optimization objective function.

6. The method of claim 5, wherein the calculation of the equipment aging risk data and the transfer supply risk data according to the grid-connection probability, the grid-connection topology, the equipment aging risk relationship, and the transfer supply risk relationship comprises: the obtaining of the equipment aging risk data of each power device according to each grid-connection topology and the equipment aging risk relationship; the obtaining of the impact current prediction value according to each grid-connection topology and the first correlation relationship; the obtaining of the relay protection device setting constraint value according to the protection misoperation probability and the impact current prediction value; the obtaining of the power device response time sequence chain according to each grid-connection topology and the second correlation relationship; the obtaining of the power device response sensitivity according to the equipment aging risk data and the third correlation relationship; the obtaining of the transfer supply risk data corresponding to each grid-connection topology according to the relay protection device setting constraint value, the power device response time sequence chain, and the power device response sensitivity.

7. The method of claim 6, wherein the obtaining of the relay protection device action probability and the relay protection device setting deviation according to the equipment aging risk data and the transfer supply risk data comprises: the obtaining of the relay protection device action probability according to the equipment aging risk data; the obtaining of the power device response time deviation value according to the power device response time sequence chain and the power device response sensitivity; the taking of the power device response time deviation and the relay protection device setting constraint value as the relay protection device setting deviation. ​ ​

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