A power system security analysis method, system, device and medium of a distributed architecture

Abstract

The application discloses a kind of distributed architecture's electric power system safety analysis method, system, equipment and medium, method includes: setting voltage fluctuation range, extracting the power grid operation data outside the voltage fluctuation range;The power grid operation data is carried out primary evaluation analysis, and voltage abnormal node is positioned by primary evaluation analysis result;Obtain the primary index of voltage abnormal node, and evaluate the voltage fluctuation damping capacity of voltage abnormal node;According to voltage fluctuation damping capacity, execute path switching mechanism;By extracting power grid operation data, multi-level evaluation analysis is carried out to position voltage abnormal node and calculate path carrying capacity, and then execute load redistribution to generate load balancing data and generate path switching scheme accordingly, overcome the problem that existing static topology presetting is difficult to adapt to power layout change in real time, avoid the voltage fluctuation and local overload caused by cross-regional transfer, can complete transfer path reconstruction and the distribution of carrying capacity in a short time.

Description

Technical Field

[0001] This invention relates to the field of power system security analysis technology, and in particular to a distributed architecture power system security analysis method, system, device and medium. Background Technology

[0002] With the integration of distributed power sources, the power grid is gradually adopting a distributed architecture, and the power transfer capacity has become a relatively important indicator. Most existing power transfer schemes are based on static topology presets. When the layout of the main grid power source is adjusted due to maintenance or fault, existing technologies have difficulty tracking the changes in node load, which can easily lead to a mismatch between the selected backup path and the actual load transfer.

[0003] Changes in power supply locations can lead to an expansion of the failure range of the original power transfer scheme. For example, in urban power distribution networks, local power supply adjustments may force loads to be transferred across regions to remote backup power sources. This not only increases line losses but also causes voltage fluctuations or local overloads due to untimely cross-regional coordination. In such cases, each analysis unit needs to reconstruct the power transfer scheme, but existing technologies are unable to complete the load redistribution in a short period of time.

[0004] Therefore, how to quickly identify changes in power supply paths and restructure the solution in power layout adjustment scenarios is a technical problem that needs to be solved. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a distributed architecture power system security analysis method, system, equipment and medium solution analysis method to solve the problem of voltage fluctuation or local overload caused by untimely cross-regional coordination.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a power system security analysis method with a distributed architecture, comprising: setting a voltage fluctuation range and extracting power grid operation data outside the voltage fluctuation range; performing a first-level evaluation analysis on the power grid operation data and locating voltage anomaly nodes based on the first-level evaluation analysis results; obtaining first-level indicators of the voltage anomaly nodes and evaluating their voltage fluctuation mitigation capabilities; executing a path switching mechanism based on the voltage fluctuation mitigation capabilities and obtaining the target transfer path after the path switching mechanism; performing a second-level evaluation analysis on the target transfer path, calculating the carrying capacity of each transfer path based on the second-level evaluation analysis results, performing load redistribution operations, and generating load balancing data; and generating a path switching scheme in response to the acquisition of the load balancing data.

[0008] As a preferred embodiment of the power system security analysis method with distributed architecture described in this invention, the method includes: identifying multiple scheduling instructions sent to the same power transfer path within the same time period in the power grid operation data, and recording abnormal conflict information through scheduling results; Based on the abnormal conflict information, the transmission time of power grid operation data between each communication node is obtained, and a voltage fluctuation propagation time sequence diagram is constructed based on the transmission time. Based on the voltage fluctuation propagation timing diagram, the voltage characteristic value of each communication node is calculated. When the voltage characteristic value exceeds the preset normal operation threshold, the communication node is identified as a voltage abnormality node.

[0009] As a preferred embodiment of the power system security analysis method with a distributed architecture described in this invention, the step of evaluating the voltage fluctuation mitigation capability of the voltage anomaly node includes: Intermediate calculation parameters are obtained by calculating the primary indicators of the voltage anomaly nodes; Based on the intermediate calculation parameters, the power grid topology characteristics are extracted, and a resource allocation matrix is ​​constructed. The timeliness coefficient is calculated by using the resource call matrix, and the power transfer path is filtered based on the timeliness coefficient to obtain the power supply path that is lacking. By comparing the ratio of the number of power supply paths lacking supply to the total number of paths, and combining the primary indicators of each voltage anomaly node, the node capacity gap is calculated, and the voltage fluctuation mitigation capability is assessed based on the node capacity gap.

[0010] As a preferred embodiment of the power system security analysis method with distributed architecture described in this invention, the path switching mechanism includes a first path switching and a second path switching. The steps of the first path switching include: A temporary power transfer path is generated based on the voltage fluctuation mitigation capability assessment results of each voltage anomaly node, and power flow redistribution data after switching the temporary power transfer path is obtained. The power flow redistribution data is filtered, and the overload risk transfer path is obtained based on the filtering results. The path load data of the overload risk transfer path is collected. The power exchange imbalance data between regions is calculated by using path load data, and key areas in the overload risk transfer path are screened based on the power exchange imbalance data.

[0011] The beneficial effect of this preferred technical solution is that it avoids the overload risk of temporary power transfer paths by assessing the cross-regional power exchange imbalance.

[0012] As a preferred embodiment of the power system security analysis method with a distributed architecture described in this invention, the second path switching steps specifically include: Obtain parameter information for key areas and calculate optimized switching parameters for different switching paths based on the parameter information; The temporary supply transfer path is adjusted based on the optimized switching parameters to form a reconstructed supply transfer path; Obtain the equipment response parameters for reconstructing the supply path, filter the equipment response parameters, and obtain the target supply path based on the filtering results.

[0013] The beneficial effect of this preferred technical solution is that by optimizing the switching parameters to reconstruct the path, the security of the generated target transfer path is ensured.

[0014] As a preferred embodiment of the power system security analysis method with a distributed architecture described in this invention, the step of screening key areas based on power exchange balance data includes: Calculate the power exchange imbalance coefficient based on the path load data; Summarize all cross-regional power exchange imbalance coefficients, identify power anomaly areas, and calculate the self-sufficiency rate by the ratio of power output to load demand within each power anomaly area. By screening out areas with unbalanced load distribution ratios in areas of abnormal power through self-sufficiency rate, the load power of each node in the areas with unbalanced load distribution ratios is statistically analyzed, and the load density value is calculated. The load density values ​​are weighted and summed to obtain a comprehensive risk index, and key areas are selected based on the comprehensive risk index.

[0015] The beneficial effect of this preferred technical solution is that it enables the screening of potential cross-regional power anomalies.

[0016] As a preferred embodiment of the power system security analysis method with a distributed architecture described in this invention, the step of generating a path switching scheme includes: Based on load balancing data, calculate cross-regional load deviation rate and voltage monitoring data, count the number of power outages, and obtain power supply indicators. Extract abnormal conflict information from the power supply indicators, calculate the conflict frequency and voltage fluctuation amplitude, and plot the power supply change curve; Based on the power supply change curve and power supply indicators, select path combinations and generate path switching schemes.

[0017] Secondly, the present invention provides a distributed architecture power system security analysis system, comprising: a data extraction module for setting a voltage fluctuation range and extracting power grid operation data outside the voltage fluctuation range; a primary evaluation module for performing primary evaluation analysis on the power grid operation data and locating voltage anomaly nodes based on the primary evaluation analysis results; a voltage fluctuation mitigation capability evaluation module for obtaining primary indicators of voltage anomaly nodes and evaluating the voltage fluctuation mitigation capability of the voltage anomaly nodes; a path switching module for executing a path switching mechanism based on the voltage fluctuation mitigation capability and obtaining the target transfer path after the path switching mechanism; a secondary evaluation module for performing secondary evaluation analysis on the target transfer path, calculating the carrying capacity of each transfer path based on the secondary evaluation analysis results, performing load redistribution operations, and generating load balancing data; and a scheme generation module for generating path switching schemes in response to the acquisition of the load balancing data.

[0018] Thirdly, the present invention provides an electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of a power system security analysis method with a distributed architecture.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the power system security analysis method of the distributed architecture.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention extracts power grid operation data for multi-level evaluation and analysis to locate abnormal voltage nodes and calculate path carrying capacity, and then performs load redistribution to generate load balancing data and generate path switching schemes accordingly. This overcomes the problem that existing static topology presets are difficult to adapt to changes in power supply layout in real time, avoids voltage fluctuations and local overloads caused by cross-regional transfers, and can complete the reconfiguration of transfer paths and allocation of carrying capacity in a short time. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the overall process of a power system security analysis method with a distributed architecture according to an embodiment of the present invention. Detailed Implementation

[0023] To make the above-mentioned objects, features, and advantages of the present invention more readily understood, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0024] Example 1, referring to Figure 1 As an embodiment of the present invention, a power system security analysis method with a distributed architecture is provided, comprising: Set a voltage fluctuation range and extract power grid operation data outside the voltage fluctuation range.

[0025] The power grid operation data is subjected to a first-level evaluation and analysis, and the voltage anomaly nodes are located based on the results of the first-level evaluation and analysis.

[0026] Obtain primary indicators for nodes with abnormal voltage and assess their ability to mitigate voltage fluctuations.

[0027] Based on the voltage fluctuation mitigation capability, a path switching mechanism is executed to obtain the target power transfer path after the path switching mechanism.

[0028] A secondary evaluation analysis is performed on the target transfer path. Based on the results of the secondary evaluation analysis, the carrying capacity of each transfer path is calculated, load redistribution is performed, and load balancing data is generated.

[0029] In response to the acquisition of load balancing data, a path switching scheme is generated.

[0030] It should be noted that changes in power supply locations can lead to an expansion of the failure range of the original power transfer scheme. For example, in urban power distribution networks, local power supply adjustments may force loads to be transferred across regions to remote backup power sources. This not only increases line losses but also causes voltage fluctuations or local overloads due to untimely cross-regional coordination. In such cases, each analysis unit needs to reconstruct the power transfer scheme, but existing technologies are unable to complete the load redistribution in a short period of time.

[0031] Therefore, this invention extracts grid operation data for multi-level evaluation and analysis to locate voltage anomaly nodes and calculate path carrying capacity, and then performs load redistribution to generate load balancing data and generate path switching schemes accordingly. This overcomes the problem that existing static topology presets cannot adapt to changes in power supply layout in real time, avoids voltage fluctuations and local overloads caused by cross-regional transfers, and can complete the reconfiguration of power transfer paths and allocation of carrying capacity in a short time.

[0032] Example 2, refer to Figure 1As an embodiment of the present invention, a power system security analysis method with a distributed architecture is provided, comprising: S1: Set the voltage fluctuation range and extract the power grid operation data outside the voltage fluctuation range.

[0033] During the operation of a distributed power system, grid voltage deviations can occur due to fluctuations in renewable energy access or sudden increases or decreases in load. To accurately detect potential safety hazards, the system first needs to establish a clear benchmark for voltage anomaly detection. In this embodiment, step S1 specifically includes the following sub-steps: S1.1: Set voltage fluctuation range The system references the rated operating voltage of the distributed power grid under analysis and the allowable voltage deviation ratio of the grid to define the voltage fluctuation range by constructing a quantitative boundary model. Specifically, the upper and lower limits of the voltage fluctuation range are calculated using the following formulas: In the formula, This is the upper limit of the set voltage fluctuation range, in kV. This is the lower limit of the set voltage fluctuation range, in kV. The rated operating voltage of the distributed power grid to be analyzed; The system's preset allowable deviation ratio.

[0034] Using the above formula, the final voltage fluctuation range is expressed as an interval. Specific calculation example: Assume the rated operating voltage of a certain distributed power grid branch to be analyzed is... For 10kV, its allowable steady-state voltage deviation ratio Set the value to 5%, then substitute the value into the formula above for calculation: Upper limit kV; lower limit value kV.

[0035] Therefore, the system sets the voltage fluctuation range of this branch to a numerical range of [9.5kV, 10.5kV]. Any voltage state that deviates from this specific numerical range will be regarded as an abnormal fluctuation by the system.

[0036] S1.2: Extracting power grid operation data under abnormal operating conditions After obtaining the voltage fluctuation range, the system collects the voltage status of each power transfer path in the distributed power grid in real time and compares it with the numerical boundary of the voltage fluctuation range.

[0037] When the real-time voltage value of a certain power transfer path is monitored Meet the conditions or At that time, the system starts the data capture program. The power grid operation data includes at least the sequence of dispatch instructions issued by the dispatch center, as well as the communication node interaction messages between various communication nodes.

[0038] S2: Perform a first-level evaluation and analysis on the power grid operation data, and locate the voltage anomaly nodes based on the results of the first-level evaluation and analysis; In this embodiment, the primary evaluation and analysis of the power grid operation data, and the location of voltage anomaly nodes based on the primary evaluation and analysis results, specifically includes the following three sub-steps: S2.1: Identify multiple scheduling instructions sent to the same power transfer path within the same time period in the power grid operation data, and record abnormal conflict information through scheduling results; In distributed power grids, frequent dispatch interventions often induce voltage fluctuations. The system first sets a sliding time window for command recognition. In this embodiment, the time window is set to 500 milliseconds. The system uses this time window to traverse the previously extracted transfer path operation data and identify the path in... All scheduling instructions issued to the same transfer path within a time period form a scheduling instruction set. ,in This represents the total number of scheduling instructions within that time period.

[0039] Next, the system analyzes the action attributes of each scheduling instruction in the set, such as switch closing, switch opening, reactive power compensation equipment activation, and reactive power compensation equipment deactivation. In order to quantify whether there are physical or logical contradictions or conflicts between these instructions, the system calculates the scheduling instruction conflict index of the power transfer path within the current time window. The specific calculation formula is as follows: In the formula, and This is the sequence index number of the instruction; Let be the action mutual exclusion determination function, when the first... The instruction and the first The action attributes of each instruction are mutually exclusive in physical logic. For example, when one instruction requests closing the power supply and another instruction requests opening the isolation, the function value is 1. When the two instructions are compatible or the same, the function value is 0. and The first The and the first The timestamp of the instruction issuance; The absolute value of the time interval between instructions; The time decay constant is set in this embodiment. Milliseconds are used to characterize the higher the weight of a conflict caused by a mutual exclusion instruction with a closer time interval. It is a natural constant.

[0040] In this embodiment, the system presets a conflict determination threshold of 0.5. When the calculated... When an abnormal conflict occurs, the system determines that an abnormal conflict exists and generates abnormal conflict information containing the transfer path ID, conflict time interval, and conflict index value for recording.

[0041] Specific calculation example: Suppose that within a 500-millisecond window, the system issues two commands to a certain transfer path ( Command 1 is issued at 100ms, and its action is to activate the reactive power compensation equipment; Command 2 is issued at 150ms, and its action is to deactivate the reactive power compensation equipment. Since activation and deactivation are physically mutually exclusive actions, The time interval is 50ms. Substitute the values ​​into the formula to calculate: Since 0.606 > 0.5, the system confirms that an abnormal conflict has occurred and records the abnormal conflict information.

[0042] S2.2: Based on the abnormal conflict information, obtain the transmission time of power grid operation data between each communication node, and construct a voltage fluctuation propagation time sequence diagram based on the transmission time; After confirming the abnormal conflict information, the system retrieves the communication node interaction messages generated in the corresponding conflict time window of the power transfer path. Assuming that the power transfer path contains n communication nodes connected in series, the system obtains the actual transmission time of power grid operation data between adjacent communication nodes, such as node K to node K+1, by parsing the timestamp in the message header.

[0043] To quantify the interference caused by abnormal collisions to the communication network, the system compares the actual transmission time with the historical reference transmission time under collision-free conditions and calculates the delay distortion coefficient between adjacent nodes. Specifically, the difference between the actual transmission time and the historical reference transmission time is calculated, and the ratio of the difference to the historical reference transmission time is used as the delay distortion coefficient. The larger the delay distortion coefficient, the more severe the abnormal collision interference and the higher the congestion level of the communication segment. Subsequently, based on the above actual transmission time and delay distortion coefficient, the system constructs a voltage fluctuation propagation timing diagram.

[0044] The timing graph is represented as a directed graph within the system, where the vertex set V represents each communication node on the transfer path; the directed edge set E represents the propagation direction of the fluctuation data, i.e. from node K to node K+1. The attribute of each directed edge is assigned a tuple (T,d), where T is the timing trigger time of the fluctuation data arriving at node K+1, and d is the time delay distortion coefficient.

[0045] Through this step, the system generates a time series diagram with precise timestamps and delay distortion weights, which visually maps the propagation trajectory of abnormal signals in the communication network.

[0046] S2.3: Based on the voltage fluctuation propagation timing diagram, calculate the voltage characteristic value of each communication node. When the voltage characteristic value exceeds the preset normal operation threshold, the communication node is regarded as a voltage abnormal node. Specifically, based on the aforementioned timing diagram, the system extracts the instantaneous voltage fluctuation rate of each communication node at the corresponding timing trigger time. The calculation method is to divide the difference between the actual instantaneous voltage value collected by the node at the timing trigger time and the voltage reference value of the node in a stable period before the timing trigger time by the rated operating voltage of the node.

[0047] The system extracts the time delay distortion coefficients on directed edges ending at nodes from the time sequence graph and weights them with the instantaneous voltage fluctuation rate of the physical layer to calculate the comprehensive voltage characteristic value of the node. The calculation method is to multiply the voltage fluctuation rate weight coefficient by the instantaneous voltage fluctuation rate, and add the result of multiplying the time delay distortion weight coefficient by the time delay distortion coefficient. In this embodiment, the voltage fluctuation rate weight coefficient is set to 0.7, indicating that physical voltage fluctuation is the main judgment criterion. In this embodiment, the time delay distortion weight coefficient is set to 0.3, indicating that communication distortion is used as the verification criterion.

[0048] The system presets a normal operation threshold. In this embodiment, the normal operation threshold is set to 0.15 based on historical safe operation big data statistics. The system traverses all communication nodes on the power transfer path. When the comprehensive voltage characteristic value of a certain communication node is greater than the normal operation threshold, the system determines that the node cannot suppress the current fluctuations and communication shocks on its own and marks it as a voltage abnormal node.

[0049] Specific calculation example: Suppose a node has a calculated instantaneous voltage fluctuation rate of 0.12 and an associated time delay distortion coefficient of 0.23. Substituting these values ​​into the above calculation method: adding 0.7 multiplied by 0.12 to the result of 0.3 multiplied by 0.23, we get 0.153. Since the calculated result 0.153 > 0.15, the system confirms that the node has crossed the safety threshold, officially establishing it as a voltage anomaly node, and outputs its location information.

[0050] S3: Obtain the primary indicators of voltage anomaly nodes and assess their ability to mitigate voltage fluctuations. Specifically, the primary indicator for voltage anomaly nodes, assessing their voltage fluctuation mitigation capabilities, is achieved through the following four sub-steps: S3.1: Intermediate calculation parameters are obtained by calculating the primary indicators of voltage anomaly nodes; Specifically, the system extracts two core primary indicators of the voltage anomaly node under the current operating conditions: reactive power regulation margin and node dynamic equivalent impedance. The reactive power regulation margin reflects the reactive power support capability that the reactive power compensation equipment connected to the node can still provide, while the node dynamic equivalent impedance reflects the physical characteristics of the node in resisting voltage fluctuations in the power grid topology. The smaller the impedance, the stronger the support.

[0051] To eliminate interference from differences in node hardware, the system couples the two primary indicators mentioned above to obtain intermediate calculation parameters. The calculation method is to divide the reactive power regulation margin by the node dynamic equivalent impedance. The larger the value, the higher the efficiency of the node voltage regulation.

[0052] Specific calculation example: Taking the previously identified voltage anomaly node A as an example, the system extracts its current reactive power regulation margin as 60 Mvars and the node's dynamic equivalent impedance as 4 ohms. Substituting into the above calculation method: dividing 60 by 4 yields 15. The intermediate calculation parameter for node A is determined to be 15.

[0053] S3.2: Extract power grid topology characteristics based on the intermediate calculation parameters and construct a resource allocation matrix; Relying solely on the self-regulation of nodes is often insufficient to smooth out drastic fluctuations, requiring support from surrounding nodes. The system uses the anomalous node as the center and searches outwards for all candidate supporting nodes with reactive power regulation capabilities within a preset electrical radius, forming a candidate resource set. Based on this, the system extracts the grid topology characteristics, i.e., calculates the topological electrical distance between the anomalous node and each candidate supporting node.

[0054] Next, the system integrates the intermediate calculation parameters with the topological electrical distance to construct a resource call matrix. The i-th row of the matrix represents abnormal nodes, and the j-th column represents candidate supporting nodes. The elements are calculated by dividing the intermediate calculation parameters by the topological electrical distance, where the larger the value, the more effective the candidate supporting nodes are in being called to smooth out the fluctuations of abnormal nodes.

[0055] Specific calculation example: Taking node A as the intermediate calculation parameter (15), the system retrieves candidate supporting nodes B and C, extracts the topological electrical distance: the distance from node A to B is 2, and the distance from node A to C is 3. Substituting these values ​​into the above calculation method, dividing 15 by 2 gives 7.5; dividing 15 by 3 gives 5. The system constructs matrix elements, which intuitively show that the effectiveness of calling node B is significantly higher than that of node C. S3.3: Calculate the timeliness coefficient through the resource call matrix, and filter the transfer paths based on the timeliness coefficient to obtain the lacking power supply paths; Power grid security control is highly time-sensitive. The system obtains the action execution delay required for each candidate support node from receiving the regulation command to actually outputting reactive power. Combining this with the aforementioned resource call weights, the system calculates the timeliness coefficient of each candidate support node by dividing the resource call weight by the action execution delay.

[0056] For a power transfer path containing multiple supporting nodes, the system adopts the barrel effect principle, taking the minimum value among the timeliness coefficients of all associated nodes on the path as the overall path timeliness coefficient of the power transfer path. The system compares this coefficient with a preset path timeliness threshold. In this embodiment, the path timeliness threshold is set to 10. If the overall path timeliness coefficient of a power transfer path is less than 10, it indicates that the path is too slow to respond and cannot meet the needs of smoothing fluctuations, and it is marked as a path lacking power supply.

[0057] Specific calculation example: Given that node B has a weight of 7.5 and a latency of 20ms; node C has a weight of 5 and a latency of 50ms, substitute the values ​​into the above calculation method to calculate the timeliness coefficient: divide 7.5 by 20 to get 0.375; divide 5 by 50 to get 0.1.

[0058] Assuming that power transfer path 1 contains only node B, its overall timeliness coefficient is 0.375; and power transfer path 2 contains only node C, its overall timeliness coefficient is 0.1. Therefore, the system will accurately select power transfer path 2 as the path with insufficient power supply.

[0059] S3.4: By comparing the ratio of the number of power supply deficiencies to the total number of paths, and combining the primary indicators of each voltage anomaly node, calculate the node capacity gap, and assess the voltage fluctuation mitigation capability based on the node capacity gap; specifically, the system comprehensively evaluates the final mitigation capability based on the macroscopic path defect ratio and the node's own performance.

[0060] The system calculates the node capacity gap of the voltage anomaly node by multiplying the intermediate calculation parameters by the ratio of the number of power supply failure paths to the total number of candidate power transfer paths. This calculation adjusts the node's theoretical maximum regulation efficiency according to the proportion of its failed paths to obtain the capacity gap.

[0061] The system compares and evaluates the calculated node capacity gap with a preset gap safety benchmark value. In this embodiment, the gap safety benchmark value is set to 5.0. When the node capacity gap is less than or equal to 5.0, the voltage fluctuation mitigation capability of the node is evaluated as sufficient, and it can recover on its own and through qualified paths. When the node capacity gap is greater than 5.0, the voltage fluctuation mitigation capability of the node is evaluated as insufficient, and the subsequent path switching mechanism must be forcibly triggered.

[0062] Specific calculation example: Taking node A as an example, its intermediate calculation parameter is 15, the total number of paths is path 1 and path 2, and the number of missing paths is path 2. Substituting into the above calculation method: multiplying 15 by 1 and dividing by 2 gives 7.5. Since the calculation result 7.5 > 5.0, the system finally evaluates the voltage fluctuation suppression capability of the voltage anomaly node A as insufficient.

[0063] S4: Based on the voltage fluctuation smoothing capability, execute the path switching mechanism and obtain the target transfer path after the path switching mechanism; In this embodiment, the path switching mechanism in step S4 includes a first path switching and a second path switching. The first path switching includes three steps from S4.1 to S4.3: S4.1: Generate a temporary power transfer path based on the voltage fluctuation mitigation capability assessment results of each voltage anomaly node, and obtain power flow redistribution data after switching the temporary power transfer path; First, the system eliminates the lack of power supply paths and calculates the comprehensive adaptability score for the remaining qualified candidate nodes. The calculation method is to multiply the static adjustment capability weight coefficient by the resource call weight, and add the result of multiplying the dynamic response speed weight coefficient by the timeliness coefficient. In this embodiment, the static adjustment capability weight coefficient is set to 0.6, and the dynamic response speed weight coefficient is set to 0.4.

[0064] The system selects the link with the lowest locked impedance at the node with the highest score as the temporary power transfer path. It uses a digital twin model to predict power redistribution data, including the expected active power transfer. The calculation method is to multiply the missing load power at the node by the ratio of the equivalent impedance of the replaced path to the equivalent impedance of the temporary power transfer path.

[0065] The power flow redistribution data also includes the predicted voltage rise, which is calculated by dividing the expected dynamic reactive power increment by the node's rated operating voltage.

[0066] For example: Taking over the aforementioned node A, select node B (resource call weight is 7.5, timeliness coefficient is 0.375), calculate the comprehensive adaptability score, assuming the node's missing load power is 10MW, the equivalent impedance of the replaced path is 4, the equivalent impedance of the temporary transfer path is 2, the expected dynamic reactive power increment is 5Mvar, and the node's rated operating voltage is 10kV, then according to the above calculation method, the active power transfer power is calculated to be 20MW, and the predicted voltage rise value is 0.5kV.

[0067] S4.2: Filter the power flow redistribution data, obtain the overload risk transfer path based on the filtering results, and collect the path load data of the overload risk transfer path; Specifically, the system calculates the overload judgment ratio by dividing the expected active power transfer by the line thermal stability limit power under the current operating conditions. When the overload judgment ratio is greater than 1, it is identified as an overload risk transfer path, and the voltage, current and actual transmission power at both ends of the path are extracted in real time as path load data.

[0068] For example, continuing from the above, assume that the expected active power transfer of this temporary power transfer path is 15MW, and the current line thermal stability limit power is 12MW. Substituting into the above calculation method, the overload judgment ratio is calculated as 15 divided by 12, which equals 1.25. Since 1.25 is greater than 1, the system classifies this path as an overload risk power transfer path and issues an instruction to collect its real-time path load data.

[0069] S4.3: Calculate the power exchange imbalance data between regions using path load data, and select key areas in the overload risk transfer path based on the power exchange imbalance data. This includes four steps from A1 to A4: A1: The system calculates the power exchange imbalance coefficient of inter-regional tie lines based on path load data. This is done by dividing the real-time transmitted active power in the path load data by the steady-state power exchange baseline value in the scheduling plan. The system presets anomaly detection thresholds, such as 30%, and summarizes all inter-regional coefficients, identifying the areas at both ends of tie lines with a power exchange imbalance coefficient greater than 0.3 as power anomaly areas.

[0070] A2: For power anomaly areas, calculate their internal self-sufficiency rate by dividing the actual output of each power node in the area by the actual demand of each load node. The system filters out power anomaly areas with a self-sufficiency rate of less than 1, meaning that the internal power supply cannot meet the demand, and marks them as areas with unbalanced load distribution.

[0071] A3: Calculate the load density for the unbalanced region: In the formula: D is the load density value; Pi is the load power of the i-th node in the imbalance area; S is the physical power supply area of ​​the imbalance area; M is the total number of nodes in the area.

[0072] A4: The load density values ​​of all unbalanced areas in the entire network are weighted and summed according to the importance of the areas to obtain the comprehensive risk index: In the formula: R is the comprehensive risk index; wj is the weight coefficient of the j-th imbalanced area, which is determined according to the area's voltage level or hub status; Dj is the load density value of the j-th imbalanced area; N is the total number of imbalanced areas.

[0073] When the overall risk index exceeds the preset risk threshold, the imbalanced areas with the largest weighted contribution will be screened and marked as key areas.

[0074] Example: Assume a cross-regional tie line has a real-time power of 14MW and a planned power of 10MW. According to the calculation method in A1 above, the power exchange imbalance coefficient is 1.4. Since 1.4 is greater than 0.3, the connected area X is identified as a power anomaly area. Assume the total power output in area X is 80MW and the total load demand is 100MW. According to the calculation method in A2 above, the self-sufficiency rate is 0.8. Since 0.8 is less than 1, it is marked as an imbalance area. Assume the loads of the three nodes in area X are 5MW, 10MW, and 15MW respectively, and the area is 2 square kilometers. Substituting these values ​​into the formula in A3 above, the load density is calculated to be 15MW / km². 2 Assuming region X is a core hub with a weight of 1.2, if this is the only unbalanced region in the entire network, the comprehensive risk index calculated by substituting into the above A4 formula is 18. If the risk threshold is set to 15, since 18 is greater than 15, the system will ultimately designate region X as a key region.

[0075] The second path switching includes three steps, S4.5 to S4.7: S4.5: Obtain parameter information for key areas and calculate optimized switching parameters for different switching paths based on the parameter information; The system extracts the real-time voltage deviation, available capacity of adjustable transformers, and dynamic impedance of each candidate node in the key area, and calculates the optimized switching parameters for different candidate switching paths. The calculation method is to multiply the voltage recovery effect weight by the expected voltage rise value, and subtract the impedance penalty weight multiplied by the comprehensive dynamic impedance. In this embodiment, the voltage recovery effect weight is set to 0.7, and the impedance penalty weight is set to 0.3.

[0076] A higher value indicates that the path maximizes voltage support while reducing impedance loss. For example, assume candidate path A has an expected voltage rise of 0.5kV and a dynamic impedance of 5; candidate path B has an expected voltage rise of 0.3kV and a dynamic impedance of 2. Based on the above calculation method, the optimized switching parameters for path A are calculated as 0.35 multiplied by 0.5 minus 0.3 multiplied by 5, which equals -1.325; the optimized switching parameters for path B are calculated as 0.35 multiplied by 0.3 minus 0.3 multiplied by 2, which equals -0.495. The comparison shows that the optimized switching parameters for path B are superior.

[0077] S4.6: Adjust the temporary power transfer path based on optimized switching parameters to form a reconstructed power transfer path; specifically, the system eliminates inferior candidate paths with large negative values ​​based on the ranking of optimized switching parameters. For the retained high-scoring paths, the system performs topology replacement on the sections of the original temporary power transfer path that are at "overload risk" through a digital twin model, introduces low-impedance backup branches, and recalculates the network power flow to form a reconstructed power transfer path.

[0078] For example, continuing from the previous example, the system removes path A. The system extracts path B as a low-impedance backup branch. In the digital twin model, path B replaces the most heavily loaded grid section in the original temporary power transfer path, and a new reconfigurable power transfer path that avoids the heavy-load bottleneck is generated.

[0079] S4.7: Obtain the equipment response parameters for reconstructing the supply path, filter the equipment response parameters, and obtain the target supply path based on the filtering results; The system issues a pre-simulation command to obtain the equipment response parameters of relevant devices along the reconfiguration path, such as circuit breakers and transformers. These parameters include the expected inrush current and mechanical action time. The system then calculates the equipment response pass rate. In the formula: Q is the equipment response qualification; Irated is the rated current of the equipment; Iimpact is the expected inrush current during switching; λ is the response attenuation coefficient, which is set to 0.1 in this embodiment; t is the time required for the equipment to complete the action.

[0080] The system selects the reconfiguration and transfer path that meets the criteria (e.g., equipment response qualification rate greater than 0.8) and has the lowest overall cost, and finally determines it as the target transfer path and issues the actual switching command.

[0081] For example, assuming the circuit breaker on the reconfiguration path has a rated current of 2000A, an expected switching inrush current of 3000A, and a mechanical action time of 50ms, substituting into the above formula, the qualification rate is calculated as 2000 divided by 3000 multiplied by the natural constant -0.1 multiplied by 50, which equals 0.643. Since 0.643 is less than 0.8, the equipment response is deemed unqualified, and the system automatically postpones the evaluation to the next alternative reconfiguration path until a final target transfer path that meets the response requirements is selected.

[0082] S5: Perform a secondary evaluation analysis on the target transfer path, calculate the carrying capacity of each transfer path based on the results of the secondary evaluation analysis, perform load redistribution operations, and generate load balancing data; In this embodiment, a secondary evaluation analysis is performed on the target transfer path. Based on the results of the secondary evaluation analysis, the carrying capacity of each transfer path is calculated, and a load redistribution operation is performed to generate load balancing data. Specifically, this includes three steps: S5.1 to S5.3. S5.1: Conduct a secondary assessment of the target supply path and related paths, and calculate the carrying capacity of each supply path.

[0083] After path switching, the system performs real-time evaluation of the target path and surrounding associated paths affected by power flow, and calculates the actual available carrying capacity of each path. The calculation method is to multiply the thermal stability limit power of the line under the current environment by 1 and subtract the difference of the reserved safety margin coefficient, and then subtract the current real-time transmission power of the line. In this embodiment, the reserved safety margin coefficient is set to 10%.

[0084] S5.2: Perform load redistribution operations based on carrying capacity.

[0085] The system extracts the total amount of load to be transferred and redistributes it according to the available carrying capacity of each path in a weighted proportion. The calculation method is to multiply the total amount of load to be transferred by the ratio of the actual available carrying capacity of the j-th path to the total available carrying capacity of all participating paths, and obtain the redistributed load amount allocated to the j-th path.

[0086] S5.3: Generate load balancing data.

[0087] Based on the allocation results, the system calculates the overall network load balancing index: In the formula: E is the load balancing index, and the closer the value is to 1, the more balanced the remaining margin of each path is. The remaining available margin after allocating to the j-th path, which is the actual available carrying capacity minus the redistributed load; The average remaining available margin of all participating paths; L is the total number of participating paths.

[0088] The system packages the allocated load value, remaining margin, and balance index of each path to generate load balancing data.

[0089] For example, assume that after the switch, the maximum power of both target path A and associated path B is 50MW, and the real-time power of A is 20MW and B is 30MW. According to the calculation method in S5.1 above, the available carrying capacity is calculated as follows: the actual available carrying capacity of path A is 50 multiplied by 0.9 minus 20 equals 25MW, and the actual available carrying capacity of path B is 50 multiplied by 0.9 minus 30 equals 15MW, for a total available capacity of 40MW. Assuming the total load to be allocated is 30MW, the allocation is calculated proportionally according to the calculation method in S5.2 above: the redistributed load allocated to path A is 30 multiplied by 25 divided by 40 equals 18.75MW, and the redistributed load allocated to path B is 30 multiplied by 15 divided by 40 equals 11.25MW. After allocation, the remaining margin of path A is 25 minus 18.75 equals 6.25MW, and the remaining margin of path B is 15 minus 11.25 equals 3.75MW. According to the formula in S5.3 above, the load balancing index is calculated to be 0.4. The system outputs the above allocation scheme and the load balancing index of 0.4 as the load balancing data.

[0090] S6: In response to the acquisition of load balancing data, generate a path switching plan; specifically, generating a path switching plan in response to the acquisition of load balancing data includes three steps: S6.1 to S6.3. S6.1: Calculate the cross-regional load deviation rate and voltage monitoring data based on load balancing data, count the number of power outages, and obtain power supply indicators; The system calculates the cross-regional load deviation rate based on load balancing data: In the formula: δ is the cross-regional load deviation rate; N is the total number of evaluation regions; ρi is the actual load rate of the i-th region; ρstd is the standard load rate benchmark value.

[0091] Simultaneously, the average voltage deviation within the evaluation period is extracted, and the number of power outages is counted. The above three data items are combined to generate a power supply index set.

[0092] Example: Assuming two regions are being evaluated (N=2), with a standard load rate of 80%, region 1 load rate of 85%, and region 2 load rate of 95%, substituting into the above formula yields a cross-region load deviation rate of 0.0875. Assuming an average voltage deviation of 0.5kV and one interruption, the power supply index set is (0.0875, 0.5kV, 1 interruption).

[0093] S6.2: Extract abnormal conflict information from the power supply indicators, calculate the conflict frequency and voltage fluctuation amplitude, and plot the power supply change curve; The system extracts abnormal conflict information from the power supply indicators, calculates the conflict frequency within the evaluation period, and calculates the voltage fluctuation amplitude. The calculation method is to subtract the voltage of the previous moment from the current moment to obtain the voltage fluctuation amplitude. With the time series as the horizontal axis, the conflict frequency and voltage fluctuation amplitude are mapped to the vertical axis to draw a two-dimensional power supply change curve.

[0094] Example: Assuming the current voltage is 9.8kV and the previous voltage was 10.2kV, the voltage fluctuation is calculated to be -0.4kV using the above method. If two collisions occur within one hour, the collision frequency is 2. The system then plots points on a coordinate system to create a trend curve based on this.

[0095] S6.3: Based on the power supply change curve and power supply indicators, select path combinations and generate a path switching scheme; The system calculates the path fit score for each candidate path combination based on the smoothness of the power supply change curve and power supply indicators. In the formula: F is the path fit score; ΔV is the allowable threshold for voltage fluctuation; δ is the voltage fluctuation amplitude; δ is the cross-regional load deviation rate. For collision frequency; , , The weighting coefficients are set to 0.4, 0.3, and 0.3 respectively in this embodiment. The path combination with the highest weight and no risk of power outage is selected to generate the final path switching scheme.

[0096] For example, continuing from the previous example, assuming the fluctuation allowable threshold is 1.0kV, substituting into the above formula, the score of a candidate combination is calculated as 0.4 multiplied by 1.4 plus 0.3 multiplied by 0.9125 plus 0.3 multiplied by -1, which equals 0.3475. The system compares all candidate combinations, selects the combination with the highest positive score, solidifies it, and outputs it as the final path switching scheme.

[0097] Example 3 illustrates a distributed architecture power system security analysis method. It should be noted that the technical solution of this distributed architecture power system security analysis system belongs to the same concept as the technical solution of the distributed architecture power system security analysis method described above. Details not described in detail in the technical solution of the distributed architecture power system security analysis system in this example can be found in the description of the technical solution of the distributed architecture power system security analysis method described above.

[0098] This embodiment also provides a distributed architecture power system security analysis system, including: The data extraction module is used to set the voltage fluctuation range and extract power grid operation data outside the voltage fluctuation range; The primary assessment module is used to perform primary assessment and analysis on the power grid operation data, and to locate voltage anomaly nodes based on the results of the primary assessment and analysis. The voltage fluctuation mitigation capability assessment module is used to obtain the primary indicators of the voltage anomaly node and assess the voltage fluctuation mitigation capability of the voltage anomaly node. The path switching module is used to execute a path switching mechanism based on the voltage fluctuation smoothing capability and obtain the target transfer path after the path switching mechanism. The secondary evaluation module is used to perform secondary evaluation analysis on the target transfer path, calculate the carrying capacity of each transfer path based on the secondary evaluation analysis results, perform load redistribution operations, and generate load balancing data. The scheme generation module is used to generate a path switching scheme in response to the acquisition of the load balancing data.

[0099] This embodiment also provides an electronic device suitable for power system security analysis with a distributed architecture, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the power system security analysis method with a distributed architecture as proposed in the above embodiment.

[0100] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the power system security analysis method with a distributed architecture as proposed in the above embodiments.

[0101] The storage medium proposed in this embodiment and the power system security analysis method for implementing a distributed architecture proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0102] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A power system security analysis method with a distributed architecture, characterized in that, include: Set a voltage fluctuation range and extract power grid operation data outside the voltage fluctuation range; The power grid operation data is subjected to a first-level evaluation and analysis, and the voltage anomaly nodes are located based on the results of the first-level evaluation and analysis. Obtain primary indicators of voltage anomaly nodes and assess their ability to mitigate voltage fluctuations. Based on the voltage fluctuation mitigation capability, a path switching mechanism is executed to obtain the target power transfer path after the path switching mechanism. A secondary evaluation analysis is performed on the target transfer path. Based on the results of the secondary evaluation analysis, the carrying capacity of each transfer path is calculated, load redistribution is performed, and load balancing data is generated. In response to the acquisition of load balancing data, a path switching scheme is generated.

2. The power system security analysis method with a distributed architecture as described in claim 1, characterized in that, The steps for performing a first-level evaluation and analysis on the power grid operation data include: Identify multiple scheduling instructions sent to the same power transfer path within the same time period in the power grid operation data, and record abnormal conflict information through scheduling results; Based on the abnormal conflict information, the transmission time of power grid operation data between each communication node is obtained, and a voltage fluctuation propagation time sequence diagram is constructed based on the transmission time. Based on the voltage fluctuation propagation timing diagram, the voltage characteristic value of each communication node is calculated. When the voltage characteristic value exceeds the preset normal operation threshold, the communication node is identified as a voltage abnormality node.

3. The power system security analysis method with a distributed architecture as described in claim 2, characterized in that, The steps for assessing the voltage fluctuation mitigation capability of the voltage anomaly node include: Intermediate calculation parameters are obtained by calculating the primary indicators of the voltage anomaly nodes; Based on the intermediate calculation parameters, the power grid topology characteristics are extracted, and a resource allocation matrix is ​​constructed. The timeliness coefficient is calculated by using the resource call matrix, and the power transfer path is filtered based on the timeliness coefficient to obtain the power supply path that is lacking. By comparing the ratio of the number of power supply paths lacking supply to the total number of paths, and combining the primary indicators of each voltage anomaly node, the node capacity gap is calculated, and the voltage fluctuation mitigation capability is assessed based on the node capacity gap.

4. The power system security analysis method with a distributed architecture as described in claim 3, characterized in that, The path switching mechanism includes a first path switching and a second path switching; The steps of the first path switching include: A temporary power transfer path is generated based on the voltage fluctuation mitigation capability assessment results of each voltage anomaly node, and power flow redistribution data after switching the temporary power transfer path is obtained. The power flow redistribution data is filtered, and the overload risk transfer path is obtained based on the filtering results. The path load data of the overload risk transfer path is collected. The power exchange imbalance data between regions is calculated by using path load data, and key areas in the overload risk transfer path are screened based on the power exchange imbalance data.

5. The power system security analysis method with a distributed architecture as described in claim 4, characterized in that, The specific steps for the second path switching include: Obtain parameter information for key areas and calculate optimized switching parameters for different switching paths based on the parameter information; The temporary supply transfer path is adjusted based on the optimized switching parameters to form a reconstructed supply transfer path; Obtain the equipment response parameters for reconstructing the supply path, filter the equipment response parameters, and obtain the target supply path based on the filtering results.

6. The power system security analysis method with a distributed architecture as described in claim 5, characterized in that, The steps for selecting key areas based on power exchange balance data include: Calculate the power exchange imbalance coefficient based on the path load data; Summarize all cross-regional power exchange imbalance coefficients, identify power anomaly areas, and calculate the self-sufficiency rate by the ratio of power output to load demand within each power anomaly area. By screening out areas with unbalanced load distribution ratios within power anomaly regions using self-sufficiency rates, the load power of each node within these unbalanced load distribution ratios is statistically analyzed, and the load density value is calculated. The load density values ​​are weighted and summed to obtain a comprehensive risk index, and key areas are selected based on the comprehensive risk index.

7. The power system security analysis method with a distributed architecture as described in claim 6, characterized in that, The steps to generate a path switching scheme include: Based on load balancing data, calculate cross-regional load deviation rate and voltage monitoring data, count the number of power outages, and obtain power supply indicators. Extract abnormal conflict information from the power supply indicators, calculate the conflict frequency and voltage fluctuation amplitude, and plot the power supply change curve; Based on the power supply change curve and power supply indicators, select path combinations and generate path switching schemes.

8. A distributed power system security analysis system, employing the method described in any one of claims 1-7, characterized in that, include: The data extraction module is used to set the voltage fluctuation range and extract power grid operation data outside the voltage fluctuation range; The primary assessment module is used to perform primary assessment and analysis on the power grid operation data, and to locate voltage anomaly nodes based on the results of the primary assessment and analysis. The voltage fluctuation mitigation capability assessment module is used to obtain the primary indicators of the voltage anomaly node and assess the voltage fluctuation mitigation capability of the voltage anomaly node. The path switching module is used to execute a path switching mechanism based on the voltage fluctuation smoothing capability and obtain the target transfer path after the path switching mechanism. The secondary evaluation module is used to perform secondary evaluation analysis on the target transfer path, calculate the carrying capacity of each transfer path based on the secondary evaluation analysis results, perform load redistribution operations, and generate load balancing data. The scheme generation module is used to generate a path switching scheme in response to the acquisition of the load balancing data.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the power system security analysis method of the distributed architecture according to any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the power system security analysis method of the distributed architecture according to any one of claims 1 to 7.

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