Fault recovery path evaluation method for flexible interconnection power distribution network in low-voltage power distribution area

Abstract

The invention discloses a low-voltage distribution area flexible interconnection power distribution network fault recovery path evaluation method, which comprises the following steps: positioning to obtain a fault node according to captured fault information and power grid topology information; taking the fault node as a root node, and searching all distributed energy storage units which have a direct or indirect electrical connection relationship with the root node; taking each distributed energy storage unit as a center, establishing fault recovery alternative networks comprising the fault nodes through load switching iteration, and calculating load and performance evaluation results of each fault recovery alternative network; and in combination with the load and performance evaluation result of each fault recovery alternative network, judging whether each fault recovery alternative network meets the set electrical boundary constraint and calculating the recovery cost of the fault recovery alternative network, and selecting the fault recovery path with the minimum recovery cost from the fault recovery alternative networks meeting the set electrical boundary constraint as the fault recovery path. The fault recovery efficiency and effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of flexible interconnected distribution networks in low-voltage distribution stations, and in particular to a fault recovery path assessment method for flexible interconnected distribution networks in low-voltage distribution stations. Background Art

[0002] In the flexible interconnected distribution network of low-voltage distribution substations, the determination of fault recovery paths is crucial to ensure the stable operation of the power system. Traditional fault recovery methods often rely on manual operations, which are inefficient and prone to errors. In addition, traditional fault recovery strategies often ignore the role of distributed energy storage units in the fault recovery process, resulting in a less than optimized recovery process.

[0003] In the prior art, although there are some fault recovery methods based on automatic control, these methods are often only targeted at specific distribution network structures or fault types, lacking versatility and flexibility. At the same time, these methods often do not fully consider the topology of the power grid, branch impedance, node load type and other parameters in determining the fault recovery path, resulting in unsatisfactory recovery efficiency and effect. Summary of the invention

[0004] The purpose of the present invention is to provide a method for evaluating the fault recovery path of a flexible interconnected distribution network in a low-voltage distribution station area, which can improve the fault recovery efficiency and effect.

[0005] The technical solution provided by this application is:

[0006] In a first aspect, the present application provides a method for evaluating a fault recovery path of a low-voltage distribution station area flexible interconnected distribution network, comprising the following steps:

[0007] Obtain the grid topology information of the flexible interconnected distribution network in the low-voltage distribution substation area;

[0008] According to the captured fault information and the power grid topology information, a faulty node in the flexible interconnected distribution network is located to obtain a faulty node;

[0009] Taking the fault node as the root node, searching for all distributed energy storage units that are directly or indirectly electrically connected to the root node in the flexible interconnected distribution network according to the set traversal direction and backtracking direction;

[0010] Taking each of the distributed energy storage units as the center, establishing a fault recovery candidate network including the fault node through load switching iteration, and calculating the load and performance evaluation results of each fault recovery candidate network;

[0011] Combined with the load and performance evaluation results of each fault recovery candidate network, determine whether each fault recovery candidate network meets the set electrical boundary constraints, and calculate the recovery cost of each fault recovery candidate network. Select the fault recovery candidate network with the smallest recovery cost from the fault recovery candidate networks that meet the set electrical boundary constraints to generate a fault recovery path for the faulty node.

[0012] In a possible implementation, locating a faulty node in the flexible interconnected distribution network to obtain a faulty node according to the captured fault information and the power grid topology information includes:

[0013] Collect fault information from the monitoring system of the distribution network;

[0014] Clean, standardize and normalize the collected fault information;

[0015] Extracting fault-related features from fault data;

[0016] Encoding the power grid topology information and the fault-related features extracted from the fault data to obtain a fault feature vector, and calculating the similarity between the fault feature vector and the known fault feature vectors in the fault feature library, and determining the features related to the fault node location based on the similarity;

[0017] After determining the features related to the location of the faulty node, the location of the faulty node is determined based on the features related to the location of the faulty node.

[0018] In a possible implementation, all distributed energy storage units that have a direct or indirect electrical connection with the root node are searched for in the flexible interconnected distribution network according to the set traversal direction and backtracking direction, wherein the specified traversal direction includes the electrical flow direction, and the backtracking direction includes: a reverse electrical flow direction, a backtracking direction determined according to the parent-child relationship of the tree, a backtracking direction determined based on a search queue or stack, a backtracking direction determined based on a predefined backtracking rule, and a backtracking direction determined in combination with power grid protection and control logic; the optimal backtracking direction is selected according to the actual situation of the power grid.

[0019] In one possible implementation, if there is an electrically isolated area in the power grid, the area is skipped during the search for all distributed energy storage units that are directly or indirectly electrically connected to the root node, or the electrical isolation boundary is explicitly processed in the search algorithm.

[0020] In a possible implementation, the set electrical boundary constraints include: voltage range constraints, equipment capacity constraints, network topology constraints and safety constraints; the restoration cost comprehensively considers load transfer amount, operation cost and time cost.

[0021] In a second aspect, the present application provides an electronic device, including: a memory and a processor;

[0022] The memory is used to store computer programs;

[0023] The processor is used to call the computer program to execute the method as described above.

[0024] In a third aspect, the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0025] In a fourth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0026] The specific implementation methods of the second to fourth aspects of the present application can refer to the implementation methods of the first aspect, which will not be repeated here.

[0027] Beneficial effects:

[0028] Compared with the prior art, this application has the following technical differences:

[0029] Comprehensive consideration of grid parameters: In the process of determining the fault recovery path, this application comprehensively considers the grid topology information, including the initial topology structure parameters of the distribution network, branch impedance parameters, and node load type parameters, making the recovery path more reasonable and efficient.

[0030] Fully utilize distributed energy storage units: This application fully utilizes the distributed energy storage units in the flexible interconnected distribution network. Through load switching iteration, a fault recovery alternative network including fault nodes is established, thereby achieving more optimized fault recovery.

[0031] Restoration path selection based on load calculation: In the process of selecting alternative networks, this application selects the fault recovery alternative network with the lowest recovery cost based on the set electrical boundary constraints and the load size of each alternative network, thereby ensuring the efficiency and effectiveness of fault recovery.

[0032] Versatility and flexibility: This application does not rely on a specific distribution network structure or fault type, has strong versatility and flexibility, and can be widely used in various low-voltage distribution substations and flexible interconnected distribution networks.

[0033] Through the above technical differences, the present application effectively solves the problems existing in the background technology:

[0034] Improved fault recovery efficiency and effectiveness: This application achieves a more reasonable and efficient fault recovery path determination by comprehensively considering the grid topology information and making full use of distributed energy storage units, thereby improving the efficiency and effectiveness of fault recovery.

[0035] Enhanced versatility and flexibility of fault recovery: This application does not rely on a specific distribution network structure or fault type, has strong versatility and flexibility, and can adapt to the fault recovery needs of flexible interconnected distribution networks in different low-voltage distribution substations.

[0036] Reduced error rate of manual operation: This application implements the determination of fault recovery path based on automatic control technology, reduces reliance on manual operation, reduces error rate, and improves the accuracy and reliability of fault recovery. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution of the present application will be clearly and completely described below in conjunction with the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0038] A method for evaluating a fault recovery path of a low-voltage distribution station area flexible interconnected distribution network comprises the following steps:

[0039] S1. Obtaining the grid topology information of the flexible interconnected distribution network of the low-voltage distribution station area;

[0040] The power grid topology information includes the initial topology structure parameters of the distribution network, branch impedance parameters and node load type parameters;

[0041] Specifically, since the data management system (DMS) stores the initial topological parameters of the distribution network, which describe the connection relationship between various devices (such as transformers, lines, switches, etc.) in the distribution network, the grid topology information of the flexible interconnected distribution network of the low-voltage distribution substation area can be obtained from the data management system.

[0042] In addition, the data management system also stores the devices in the distribution network as nodes and edges through graph theory algorithms, and represents the topological structure of the distribution network through the connection relationship between nodes and edges. The distribution network search methods used in the implementation of graph theory algorithms can be divided into two categories: Breadth-first Search (BFS) and Depth-first Search (DFS). The search method can traverse the distribution network structure to obtain the connection relationship between each node and branch in the distribution network.

[0043] Breadth-first Search (BFS) algorithm

[0044] The BFS algorithm is an algorithm for traversing or searching a tree or graph. The algorithm starts from the root (or an arbitrary node), explores the nearest neighbor node, and then continues to explore the neighbor nodes of each neighbor node, and so on. If all nodes have been visited, the algorithm ends. This process can also be seen as traversing the graph layer by layer.

[0045] In this application, the steps to implement the BFS algorithm in the distribution network are as follows:

[0046] Initialization: Select a starting node (for example, a failure node with the highest failure rate determined based on historical failure data) and mark it as visited. At the same time, create a queue and enqueue the starting node.

[0047] Start loop: While the queue is not empty, perform the following steps:

[0048] Take a node from the queue.

[0049] Traverse all the unvisited neighbor nodes of this node.

[0050] Mark each unvisited neighbor node as visited and add it to the queue.

[0051] End: When the queue is empty, it means that all reachable nodes have been visited and the search is over.

[0052] The characteristic of the BFS algorithm is that it starts from the root node, traverses all neighbor nodes first, and then traverses the neighbor nodes of the next layer, traversing all nodes in the graph layer by layer. In the distribution network, this helps to quickly find all nodes and branches directly connected to the faulty node. This method is suitable for rapid response and fault location, especially for quickly identifying the affected area when a fault occurs. Therefore, if you need to quickly locate the fault and evaluate the directly affected area, you can give priority to the BFS algorithm.

[0053] Depth-first Search (DFS) algorithm

[0054] The DFS algorithm is an algorithm for traversing or searching a tree or graph. The algorithm searches the branches of the graph as deeply as possible. When all the edges of node v have been explored, the search will backtrack to the starting node of the edge where node v was found. This process continues until all nodes reachable from the source node have been found. If there are still undiscovered nodes, one of them is selected as the source node and the above process is repeated. The whole process is repeated until all nodes have been visited.

[0055] In this application, the steps to implement depth-first search in the distribution network are as follows:

[0056] Initialization: Select a starting node (for example, a faulty node with the highest failure rate determined based on historical failure data) and mark it as visited. At the same time, create a stack (or recursive function) to store the path.

[0057] Start recursion or loop: For the current node, perform the following steps:

[0058] Traverse all the unvisited neighbor nodes of this node.

[0059] For each unvisited neighbor node, mark it as visited and make it the new current node, continuing the recursion or loop.

[0060] When all neighbor nodes of the current node have been visited, return to the previous layer (or pop the stack).

[0061] End: The search ends when all reachable nodes have been visited and there are no more nodes to return.

[0062] The characteristic of the DFS algorithm is to traverse the branches of the graph as deeply as possible until there are no more nodes that can be accessed in the branch, and then go back to the previous node to continue searching. In the distribution network, all reachable nodes and branches directly or indirectly connected to the faulty node can be found as much as possible, which helps to fully understand the connection relationship of the power grid, especially in a complex power grid structure. Therefore, if you need to fully understand all possible connection paths of the faulty node, you can give priority to the DFS algorithm.

[0063] The branch impedance parameters describe the electrical characteristics of each branch in the distribution network, such as resistance and reactance. These parameters can usually be obtained through offline measurement or online estimation. In the DMS, the impedance parameters of each branch are also stored.

[0064] The node load type parameter describes the load type and size of each node in the distribution network. These parameters can be obtained indirectly by monitoring the electrical quantities such as voltage, current and power of the node, or directly by directly measuring the electrical parameters of the load equipment. In this application, the node load type parameters are also stored through DMS, and updated in real time or regularly to reflect the changes in the distribution network load.

[0065] S2. According to the captured fault information and the power grid topology information, locate the faulty node in the flexible interconnected distribution network to obtain the faulty node;

[0066] In this application, the operating status of the power grid is monitored in real time through sensors and monitoring equipment equipped in the flexible interconnected distribution network. When a fault occurs in the power grid, these devices will capture fault information, such as abnormal current, voltage reduction, equipment failure, etc. The fault information will be sent to the above-mentioned data management system (DMS).

[0067] When locating a faulty node, the grid topology information is used to analyze the possible location and scope of the fault. For example, based on the voltage and current changes when the fault occurs, combined with the topology of the grid, a preliminary judgment can be made on which branches or nodes the fault may occur. Specifically, based on the captured fault information and grid topology information, a faulty node location algorithm can be used to accurately determine the location of the faulty node.

[0068] The process of accurately determining the location of the faulty node based on the faulty node location algorithm is as follows:

[0069] Fault information is collected from the monitoring system of the distribution network, including voltage, current, power, etc. when the fault occurs.

[0070] The collected fault information is cleaned, standardized and normalized to eliminate noise, outliers and dimensional inconsistency.

[0071] Extract fault-related features from fault data, such as the magnitude of voltage sag, the rate of current change, etc.

[0072] The grid topology information and the fault-related features extracted from the fault data are encoded (for example, input into the XGboost model) to obtain a fault feature vector, and the similarity between the fault feature vector and the known fault feature vectors in the fault feature library is calculated. Based on the similarity, the features related to the location of the fault node are determined, such as the impedance of the branch where the fault node is located, the electrical parameters of the adjacent nodes, etc.

[0073] After determining the features related to the location of the faulty node, the location of the faulty node is determined based on the features related to the location of the faulty node.

[0074] Based on the above fault node location determination process, the use of a fault node location algorithm to accurately determine the location of the fault node brings the following technical benefits:

[0075] Fast response and location: By real-time monitoring and collection of fault information, combined with advanced fault algorithms, it is possible to quickly respond to and locate faults. This greatly shortens the time for fault discovery and processing, and improves the stability of the power grid and the reliability of power supply.

[0076] Improve diagnostic accuracy: Cleaning, standardizing and normalizing fault information, as well as extracting key features from fault data, can eliminate the impact of noise and outliers and ensure the accuracy of fault diagnosis. In addition, using advanced machine learning models (such as XGboost) to calculate feature vector similarity further improves the accuracy of fault node location.

[0077] Adaptability to complex grid structures: The fault algorithm can handle complex grid topology information and is not restricted by a specific grid structure or fault type. This makes the algorithm widely applicable and flexible and can be applied to various low-voltage distribution substations in flexible interconnected distribution networks.

[0078] Reduce maintenance costs: By accurately locating the faulty node, maintenance personnel can be quickly dispatched to the site for repair, reducing unnecessary inspections and troubleshooting. This greatly reduces maintenance costs and improves the efficiency of fault handling.

[0079] Optimize resource allocation: Accurate fault node location can help power system dispatchers better understand the operating status of the power grid and make more reasonable resource allocation decisions. For example, during the fault recovery process, the operating status of the distributed energy storage unit can be adjusted according to the location of the fault node to optimize the fault recovery process.

[0080] S3, taking the fault node as the root node, searching for all distributed energy storage units that have a direct or indirect electrical connection relationship with the root node in the flexible interconnected distribution network according to the set traversal direction and backtracking direction;

[0081] The prescribed traversal direction is, for example, the electrical flow direction, and the tracing direction is, for example:

[0082] Reverse electrical flow direction:

[0083] If the electrical power flow in the power grid is bidirectional, the backtracking direction can be the opposite direction to the current traversal direction (i.e., the electrical power flow direction). For example, when the algorithm visits a node and continues to search along the electrical power flow direction, if backtracking is required, the edge opposite to the electrical power flow direction can be selected to return to the node at the previous level.

[0084] The backtracking direction is determined by the parent-child relationship of the tree:

[0085] During the search process, the topology of the power grid can be viewed as a tree structure, where the faulty node is the root node and the other nodes are child nodes. In this case, the backtracking direction is to return to the parent node along the parent-child relationship of the tree.

[0086] Backtracking direction determined based on the search queue or stack:

[0087] Use a queue to store the nodes to be visited. When backtracking is needed, the previous state (the last visited node) can be taken out from the queue. A stack is usually used to store the order in which nodes are visited. When backtracking is needed, the current node can be popped from the stack to return to the previous node.

[0088] The backtracking direction is determined based on predefined backtracking rules:

[0089] The backtracking direction can be defined according to the specific requirements or operation rules of the power grid. For example, a rule can be defined so that the search algorithm always selects the path with the shortest electrical distance or the smallest electrical parameter (such as impedance) when backtracking.

[0090] The retracement direction determined by combining the grid protection and control logic:

[0091] In flexible interconnected distribution networks, there are usually complex protection and control logics to ensure the stable operation of the power grid. The search algorithm can be combined with these logics to define the backtracking direction when implemented. For example, when backtracking, nodes or paths that have not triggered protection actions or have not been isolated can be given priority.

[0092] The search starts from the faulty node, first searching all nodes adjacent to the root node, then searching the neighbors of these nodes, and so on. During the search process, when the search algorithm accesses a distributed energy storage unit, it marks it as found and records its connection relationship with the faulty node.

[0093] The search algorithm may adopt the BFS algorithm or the DFS algorithm.

[0094] The various backtracking direction determination strategies mentioned in the above scheme have the following main benefits in the process of determining the fault recovery path of the flexible interconnected distribution network in the low-voltage distribution substation area:

[0095] Improve search efficiency: By using the electrical flow direction as the traversal direction and combining it with the reverse electrical flow direction as the backtracking direction, the search algorithm is able to follow the actual path of power transmission, avoiding invalid searches and repeated visits, thereby improving search efficiency.

[0096] The parent-child relationship backtracking method of the tree can clearly track the search path, making the backtracking operation more intuitive and efficient.

[0097] Optimize resource utilization: The use of queues and stacks enables the search algorithm to systematically manage the nodes to be visited, ensuring that it can quickly return to the correct location when backtracking is needed, avoiding waste of resources.

[0098] The backtracking direction determined based on the predefined backtracking rules can select the optimal backtracking direction (path) according to the actual situation of the power grid, thereby optimizing the utilization of power grid resources.

[0099] Enhanced system reliability: Defining the backtracking direction in conjunction with the protection and control logic of the power grid ensures that the search algorithm avoids nodes and paths that have triggered protection actions or been isolated during the recovery process, thereby improving the reliability and safety of the system.

[0100] By selecting the path with the shortest electrical distance or the smallest electrical parameter (such as impedance) for backtracking, the impact of the fault on the power grid can be further reduced and the robustness of the system can be improved.

[0101] Strong adaptability: The above strategy provides a variety of ways to determine the backtracking direction, which can be flexibly selected according to the specific situation and needs of the power grid, and has strong adaptability. Whether it is a simple tree structure or a complex flexible interconnected distribution network, a suitable backtracking strategy can be found.

[0102] Different backtracking strategies can complement each other, allowing the search algorithm to remain efficient and accurate in a complex and changing power grid environment.

[0103] If there are electrically isolated areas in the power grid (such as parts isolated by circuit breakers), these electrically isolated areas are skipped during the search process, that is, after the search algorithm identifies the electrically isolated areas, it chooses not to enter these areas but continues to search in other areas; or, these electrically isolated boundaries are explicitly handled in the search algorithm.

[0104] Explicitly handling electrical isolation boundaries in the search algorithm can be achieved by following the following steps:

[0105] Identify electrical isolation boundaries:

[0106] First, determine which parts of the grid are electrically isolated, such as by identifying devices such as circuit breakers and disconnect switches that are in the open state. These devices divide the grid into multiple independent electrically isolated areas.

[0107] Construct a topology graph of the electrically isolated area: For each electrically isolated area, you can construct its topology separately to more clearly understand the connection relationship between nodes and edges in the area.

[0108] Mark electrical isolation boundaries: In the topology diagram of the entire power grid, mark the locations of all electrical isolation boundaries. This can be done by adding special edges or nodes in the diagram to represent electrical isolation boundaries.

[0109] Processing in the search algorithm: When the search traverses to an electrical isolation boundary, specific actions need to be taken, such as:

[0110] a. Skip the electrically isolated area:

[0111] If a distributed energy storage unit directly connected to the faulty node is found, you can choose to skip the entire electrical isolation area and continue searching other unisolated areas.

[0112] b. Record quarantine information:

[0113] Information about the electrical isolation boundaries encountered, such as the identifier of the electrical isolation area, boundary devices, etc., is recorded to facilitate decision making during the search process.

[0114] c. Processing during backtracking:

[0115] During the backtracking process, if the backtracking path passes through the electrical isolation boundary, the electrical isolation area is skipped and other non-isolated areas are continued to be searched.

[0116] The difference between skipping electrically isolated regions during the search process and explicitly handling these electrically isolated boundaries in the search algorithm is this: suppose there is a faulty node in the power grid, and the grid is divided into two electrically isolated regions A and B by circuit breakers. If the algorithm chooses to skip the electrically isolated region, it may completely ignore region B during the search process and only search region A. If the algorithm explicitly handles the electrically isolated boundaries, it may record this information when it finds the boundary of region B and decide not to enter region B. It may also record this boundary information for subsequent analysis or decision-making. Therefore, explicit processing can be used to manage the search path more carefully to ensure that the isolated region is not mistakenly entered.

[0117] Explicitly addressing electrical isolation boundaries in the fault recovery path determination algorithm for a power grid has the following technical benefits:

[0118] Improve search efficiency: Skipping electrically isolated areas can greatly reduce the complexity of the search because the algorithm does not need to perform useless searches inside these areas, which can significantly improve search efficiency, especially in large, complex power grids.

[0119] Optimize resource allocation: By identifying electrically isolated areas, the algorithm can more accurately understand the actual operating status of the power grid and optimize resource allocation. For example, during fault recovery, the algorithm can prioritize the restoration of non-isolated areas directly connected to the faulty node to ensure power supply to critical loads.

[0120] Enhanced system reliability: Explicitly handling electrical isolation boundaries ensures that the algorithm does not mistakenly enter an isolated area during the search and backtracking process, thereby avoiding possible erroneous operations, helping to reduce the impact of erroneous operations on grid stability and improving system reliability.

[0121] Improve algorithm accuracy: Constructing a topological map of the electrical isolation area and marking the electrical isolation boundaries can enable the algorithm to more accurately understand the structure and connection relationship of the power grid, help the algorithm make more accurate decisions during the search process, and improve the accuracy and reliability of the fault recovery path.

[0122] Support for distributed control: Distributed control is an important feature in flexible interconnected distribution networks. Explicitly handling electrical isolation boundaries allows different control units to operate independently in their respective electrical isolation areas, reducing mutual dependence and interference, and helping to achieve more flexible and efficient distributed control.

[0123] Enhanced system scalability: As the power grid continues to grow and change, new electrical isolation areas may emerge. By explicitly handling electrical isolation boundaries, the algorithm can easily adapt to these changes without large-scale modification or reconstruction, enhancing the scalability and flexibility of the system.

[0124] Support for fault prevention and maintenance: By recording information about electrical isolation boundaries, the algorithm can provide valuable reference for subsequent fault prevention and maintenance. For example, the causes and patterns of faults in electrical isolation areas can be analyzed based on historical records, so that corresponding preventive measures can be taken or maintenance strategies can be optimized.

[0125] S4, taking each of the distributed energy storage units as the center, establishing a fault recovery candidate network including the fault node through load switching iteration, and calculating the load and performance evaluation results of each fault recovery candidate network;

[0126] Among them, calculating the load of each fault recovery alternative network involves evaluating the loads in the power grid to determine whether they can be powered by existing distributed energy storage units without violating the operating limitations of the power grid (such as voltage exceeding the limit, equipment capacity exceeding the limit, etc.).

[0127] In this application, the loads affected by the fault are traversed to check whether they can be powered by the existing distributed energy storage units.

[0128] If a load can be powered by a distributed energy storage unit, and this power supply path does not cause violations of operational restrictions in the power grid (such as voltage exceeding the limit, equipment capacity exceeding the limit, etc.), then this load is added to the alternative network centered on the distributed energy storage unit. Repeat this process, try different load combinations and connection methods, and generate multiple fault recovery alternative networks. For each generated fault recovery alternative network, calculate its total load, involving flow calculations to determine the power distribution and load level in the network, and use existing power system analysis software or write your own code to implement flow calculations. In addition, evaluate the performance of each alternative network, including indicators such as recovery time, recovery rate, voltage stability, and equipment utilization.

[0129] Recovery time assessment: Heuristic search algorithms (such as genetic algorithms, simulated annealing algorithms, etc.) can be used in combination with the switching operation time of the power grid to estimate the total time required from the occurrence of a fault to the completion of load transfer. Event time simulation can also be used to simulate the entire recovery process and accurately calculate the recovery time.

[0130] Restoration rate assessment: The load restoration rate is usually defined as the ratio of successfully restored load to the total affected load, which can be calculated by comparing the load levels before and after the failure.

[0131] The Node Restoration Rate can also be used as an indicator to measure the ratio of the number of nodes that have successfully restored power to the total number of failed nodes.

[0132] Voltage stability assessment: Power Flow Analysis is the basis for assessing voltage stability. You can use algorithms such as the Newton-Raphson Method or Fast Decoupled LoadFlow to calculate power flows and check whether the voltage is within the permitted range. Static Voltage Stability Index (such as the L index) or Continuation PowerFlow can also be used to assess voltage stability.

[0133] Equipment utilization evaluation: Equipment utilization can be obtained by calculating the ratio of the actual output of the equipment during fault recovery to its rated capacity. For distributed energy storage units (DESS), their depth of discharge (DOD) and state of charge (SOC) can also be considered as evaluation indicators.

[0134] In the grid fault recovery strategy, the fault recovery candidate network is established through load switching iteration, and the load of each candidate network is calculated and its performance is evaluated, which has the following technical benefits:

[0135] Improved restoration efficiency: By traversing the loads affected by the fault and checking whether they can be powered by DESS, multiple fault restoration candidate networks can be quickly generated. This flexible strategy can provide multiple restoration solutions in a short time, thereby improving restoration efficiency.

[0136] Optimize resource utilization: When generating alternative networks, considering operational constraints such as voltage limit and equipment capacity limit can ensure that the restoration strategy does not exceed the actual capacity of the power grid. This helps optimize the utilization of resources and avoids additional burden or risk during the restoration process.

[0137] Improve restoration quality: By calculating the load of each candidate network and evaluating its performance, the best restoration plan can be selected. These evaluation indicators, such as restoration time, restoration rate, voltage stability, and equipment utilization, can fully reflect the quality and effectiveness of the restoration plan, ensuring that the selected plan can restore the normal operation of the power grid to the greatest extent possible.

[0138] Enhanced system stability: Paying special attention to voltage stability when evaluating alternative networks ensures that restoration strategies do not negatively impact grid stability. Potential voltage issues can be identified and addressed in a timely manner, enhancing system stability, through methods such as power flow calculations and static voltage stability indices.

[0139] Support decision-making: Providing multiple alternative networks and detailed performance evaluation results can provide powerful decision-making support for power grid dispatchers. Dispatchers can choose appropriate recovery plans based on actual conditions, quickly respond to faults and restore normal operation of the power grid.

[0140] Improve system reliability: By considering indicators such as the depth of discharge and state of charge of distributed energy storage units, it is possible to ensure that DES S are fully utilized during fault recovery, improving their reliability and lifespan. This helps to enhance the reliability of the entire power grid and reduce the risk of power outages caused by equipment failures.

[0141] Strong adaptability: This strategy is applicable to different types of faults and grid structures and has strong adaptability. Whether it is a simple single-point fault or a complex multi-point fault, this strategy can find an effective recovery plan. At the same time, this strategy can also be flexibly adjusted and optimized according to the actual situation of the grid.

[0142] Calculate the load of each failover candidate network,

[0143] S5. Based on the load and performance evaluation results of each fault recovery candidate network, determine whether each fault recovery candidate network meets the set electrical boundary constraints, and calculate the recovery cost of each fault recovery candidate network. Select the fault recovery candidate network with the smallest recovery cost from the fault recovery candidate networks that meet the set electrical boundary constraints to generate a fault recovery path for the faulty node.

[0144] Thus, efficient and safe grid fault recovery can be achieved.

[0145] The electrical boundary constraints include:

[0146] Voltage range constraint: ensures that the voltage of all nodes is within the allowed range.

[0147] Equipment capacity constraints: Ensure that the load of all equipment (such as distributed energy storage units, transformers, lines, etc.) does not exceed its capacity limit.

[0148] Network topology constraints: Specific network connectivity or redundancy requirements may need to be met.

[0149] Safety constraints: such as short-circuit current limitation, thermal stability, etc.

[0150] Evaluate the recovery cost of the candidate network: For each candidate network for fault recovery, evaluate its recovery cost. The recovery cost can be a comprehensive indicator that combines the following indicators:

[0151] Load transfer amount: The amount of load transferred, which may be measured by the load recovery rate.

[0152] Operating costs: such as number of switch operations, equipment loss, etc.

[0153] Time cost: The time required for the recovery process.

[0154] Among them, for quantifying the recovery cost, the recovery cost is quantified into a single indicator, for example, by the following method:

[0155] Weighted summation: Assign a weight to each factor and add them together. The weight can be adjusted based on actual conditions.

[0156] Cost Function: Define a cost function that takes into account all relevant factors and outputs a single restoration cost value.

[0157] After evaluating the restoration costs of all candidate networks, it is necessary to screen out candidate networks that meet the electrical boundary constraints. For example, this can be achieved by the following steps:

[0158] Verify voltage range constraints: Check whether the voltages of all nodes are within the allowed range.

[0159] Verify device capacity constraints: Ensure that the load on all devices does not exceed their capacity limits.

[0160] Verify network topology constraints: Verify that the network meets connectivity and redundancy requirements.

[0161] Verify safety constraints: Ensure that safety constraints such as short-circuit current limit and thermal stability are not violated.

[0162] Among them, the alternative network with the lowest recovery cost is selected

[0163] From the candidate networks that meet the electrical boundary constraints, the network with the minimum recovery cost is selected as the final fault recovery path.

[0164] In the power grid fault recovery strategy, the fault recovery candidate network with the minimum recovery cost is selected based on the set electrical boundary constraints to generate the recovery path of the fault node, which has the following technical benefits:

[0165] Ensure safe and stable operation of the power grid: By considering electrical boundary conditions such as voltage range constraints, equipment capacity, network topology, and safety constraints, ensure that the selected restoration path will not put the power grid into an unsafe operating state. This helps prevent secondary faults or system crashes caused by restoration operations.

[0166] Optimize resource utilization and cost: When selecting a recovery path, resources can be optimally allocated by evaluating the recovery cost of the alternative networks, including factors such as load transfer volume, operation cost, and time cost. Selecting the network with the lowest recovery cost helps reduce the cost of the recovery process and improve resource utilization efficiency.

[0167] Improve restoration efficiency and speed: By quantifying the restoration cost and selecting the alternative network with the lowest restoration cost, the optimal restoration path can be quickly determined. This helps shorten fault restoration time and improve the restoration efficiency and power supply reliability of the power grid.

[0168] Flexibility and adaptability: The strategy takes into account a variety of electrical boundary constraints and restoration cost factors, and can be flexibly adjusted and optimized according to the actual situation of the power grid. Whether it is a simple single-point fault or a complex multi-point fault, a suitable restoration path can be found.

[0169] Decision support: Provides powerful decision support for power grid dispatchers. By evaluating the restoration costs of multiple alternative networks and screening out networks that meet the constraints, dispatchers can make decisions quickly and select the optimal restoration plan.

[0170] Enhance system reliability: By selecting the alternative network with the lowest restoration cost as the final fault recovery path, the impact and potential risks on the power grid during the restoration process can be reduced, which helps to enhance the reliability and stability of the power grid and improve user satisfaction with power supply services.

[0171] The embodiment of the present application also provides an electronic device, including: a memory and a processor;

[0172] The memory is used to store computer programs;

[0173] The processor is used to call the computer program to execute the method as described above.

[0174] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0175] An embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0176] The embodiments of the present application also provide a cable positioning system, an electronic device, a computer-readable storage medium, and a computer program product. The specific implementation methods can refer to the specific embodiments of the above methods and will not be repeated here.

[0177] Obviously, those skilled in the art should understand that the above-mentioned units or steps of the present application can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0178] The above description of the embodiments of the present application is only a partial embodiment of the present application, which is used to enable professionals in the field to implement or use the content of the present application, and is not used to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for evaluating fault recovery paths of flexible interconnected distribution networks in low-voltage distribution areas, characterized in that: The steps include: Obtain the grid topology information of the flexible interconnected distribution network in the low-voltage distribution substation area; According to the captured fault information and the power grid topology information, a faulty node in the flexible interconnected distribution network is located to obtain a faulty node; Taking the fault node as the root node, searching for all distributed energy storage units that are directly or indirectly electrically connected to the root node in the flexible interconnected distribution network according to the set traversal direction and backtracking direction; Taking each of the distributed energy storage units as the center, establishing a fault recovery candidate network including the fault node through load switching iteration, and calculating the load and performance evaluation results of each fault recovery candidate network; Combined with the load and performance evaluation results of each fault recovery candidate network, determine whether each fault recovery candidate network meets the set electrical boundary constraints, and calculate the recovery cost of each fault recovery candidate network. Select the fault recovery candidate network with the smallest recovery cost from the fault recovery candidate networks that meet the set electrical boundary constraints to generate a fault recovery path for the faulty node.

2. The method according to claim 1, characterized in that: The method of locating a faulty node in the flexible interconnected distribution network according to the captured fault information and the power grid topology information to obtain the faulty node includes: Collect fault information from the monitoring system of the distribution network; Clean, standardize and normalize the collected fault information; Extracting fault-related features from fault data; Encoding the power grid topology information and the fault-related features extracted from the fault data to obtain a fault feature vector, and calculating the similarity between the fault feature vector and the known fault feature vectors in the fault feature library, and determining the features related to the fault node location based on the similarity; After determining the features related to the location of the faulty node, the location of the faulty node is determined based on the features related to the location of the faulty node.

3. The method according to claim 1, characterized in that The method searches for all distributed energy storage units that have a direct or indirect electrical connection with the root node in the flexible interconnected distribution network according to the set traversal direction and backtracking direction, wherein the specified traversal direction includes the electrical flow direction, and the backtracking direction includes: a reverse electrical flow direction, a backtracking direction determined according to the parent-child relationship of the tree, a backtracking direction determined based on a search queue or stack, a backtracking direction determined based on a predefined backtracking rule, and a backtracking direction determined in combination with power grid protection and control logic; and selects the optimal backtracking direction according to the actual situation of the power grid.

4. The method according to claim 1, characterized in that: If there is an electrically isolated area in the power grid, the area is skipped in the process of searching for all distributed energy storage units that have a direct or indirect electrical connection relationship with the root node, or the electrically isolated boundary is explicitly processed in the search algorithm; Among them, electrical isolation boundaries are explicitly handled in the search algorithm, including: Identify electrical isolation boundaries and mark the locations of all electrical isolation boundaries in the topology diagram of the entire power grid; When the search traverses to the electrical isolation boundary, the electrical isolation area is skipped, and other non-isolated areas are continued to be searched, and the information of the encountered electrical isolation boundary is recorded; during the backtracking process, if the backtracking path passes through the electrical isolation boundary, the electrical isolation area is skipped, and other non-isolated areas are continued to be searched.

5. The method according to claim 1, characterized in that The set electrical boundary constraints include: voltage range constraints, equipment capacity constraints, network topology constraints and safety constraints; the restoration cost comprehensively considers load transfer amount, operation cost and time cost.

6. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer programs; The processor is configured to call the computer program to execute the method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed on an electronic device, the electronic device implements the method according to any one of claims 1 to 5.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed on an electronic device, the electronic device implements the method according to any one of claims 1 to 5.