Modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration

Abstract

This invention discloses a modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration, specifically relating to the field of intelligent distribution network relay protection technology. It addresses the problems of resource contention in cloud-based collaborative protection systems leading to delayed fault diagnosis and the inability to generate protection strategies within the fault clearing time window. By real-time monitoring of the resource load status of cloud computing nodes, dynamic preemption priorities are generated based on grid topology vulnerability and the collaborative needs of associated circuit breakers. Reliability attenuation control is implemented using the fault current waveform distortion rate. When the necessity of resource preemption exceeds a threshold, periodic task threads are frozen and computing resources are released, while a high-priority communication channel is opened. Fault waveform compression commands are sent to the target circuit breaker terminal to obtain edge preprocessing feature vectors. Within the released resources, protection strategy optimization is performed to generate reclosing parameters, which are then sent and executed via the high-priority channel, achieving rapid response to fault diagnosis tasks.

Description

Technical Field

[0001] This invention relates to the field of smart distribution network relay protection technology, and more specifically, to a modular reclosing circuit breaker protection system based on smart electrical cloud collaboration. Background Technology

[0002] In the field of smart distribution network protection, adopting a cloud-based collaborative circuit breaker protection system can improve fault handling efficiency. Typically, electrical quantity data collected by distributed terminals is uploaded to the cloud platform, and protection strategy optimization (such as adaptive reclosing parameter adjustment) is achieved through centralized computing. The system is then distributed to local circuit breakers for execution, relying on the cloud to complete core fault diagnosis and decision-making, thus balancing protection accuracy and the need for intensive operation and maintenance.

[0003] However, existing cloud-based collaborative circuit breaker protection systems face a fundamental conflict between dynamic resource allocation and real-time performance assurance: when the cloud platform processes multiple computing tasks simultaneously (such as periodic equipment status monitoring and batch terminal data cleaning), sudden fault diagnosis requests may enter a queuing state due to instantaneous saturation of computing resources. In this case, the cloud cannot complete the generation and distribution of strategies within the power system fault clearing time window, causing local circuit breakers to be forced to degrade and execute non-optimized protection logic, resulting in the failure of collaborative performance. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration includes:

[0007] The load monitoring module is used by the cloud platform to monitor the resource load status of each computing node in real time.

[0008] The priority generation module is used to respond to fault diagnosis requests and generate dynamic preemption priorities based on the vulnerability of the power grid topology in the protection area where the target circuit breaker is located and the degree of coordinated operation requirements of associated circuit breakers.

[0009] The reliable attenuation module is used to extract the waveform distortion rate of the fault current. If it does not fall within the threshold range of the historical fault database, the reliability attenuation processing is applied to the dynamic preemption priority.

[0010] The resource preemption module is used to determine the necessity of resource preemption based on the resource load status and the dynamic preemption priority after processing. If it exceeds the resource preemption threshold, the periodic task thread is frozen, computing resources are released, and a high-priority communication channel is opened.

[0011] The feature extraction module is used to send fault recording compression instructions to the target circuit breaker terminal through a high-priority communication channel and to receive the fault feature vector after edge preprocessing.

[0012] The strategy execution module is used to perform protection strategy optimization within the released resources based on fault feature vectors, generate reclosing parameters, and send them to the target circuit breaker terminal for execution through a high-priority communication channel.

[0013] Furthermore, the cloud platform monitors the resource load status of each computing node in real time, including:

[0014] Obtain the curve of CPU utilization of the computing node over time;

[0015] Obtain the curve of memory usage of compute nodes over time;

[0016] The cumulative duration exceeding the preset CPU utilization threshold is calculated based on the CPU utilization curve.

[0017] The maximum duration for which the memory usage rate continuously exceeds the preset memory usage rate threshold is calculated based on the memory usage rate curve.

[0018] The cumulative duration percentage is combined with the maximum duration to form a quantitative indicator of resource load status.

[0019] Furthermore, in response to fault diagnosis requests, a dynamic preemption priority is generated based on the vulnerability of the power grid topology in the protection zone where the target circuit breaker is located and the degree of coordinated operation requirement of associated circuit breakers, including:

[0020] After responding to the fault diagnosis request, the power grid topology vulnerability value is multiplied by the coordinated action requirement value, and then multiplied by a preset priority scaling factor to generate a dynamic preemption priority.

[0021] Furthermore, the method for obtaining numerical values ​​of power grid topology vulnerability is as follows:

[0022] Obtain the real-time topology connection relationship of the protection zone where the target circuit breaker is located;

[0023] Perform N-1 security checks on the real-time topology connections and use the proportion of branches that fail the checks as the first factor.

[0024] The proportion of critical load power to total load power within the protection zone is calculated as the second factor.

[0025] Multiplying the first factor by the second factor yields the power grid topology vulnerability value.

[0026] Furthermore, the method for obtaining the collaborative action demand value is as follows:

[0027] Measure the actual operating timing margin of the associated circuit breaker;

[0028] Read the preset standard coordination time difference;

[0029] The ratio of the absolute difference between the actual timing margin and the standard coordination time difference to the standard coordination time difference is used as the value of the coordinated action requirement.

[0030] Furthermore, the waveform distortion rate of the fault current is extracted. If it does not fall within the historical fault database threshold range, the reliability of the dynamic preemption priority is reduced, including:

[0031] Extract the fault current and perform discrete sampling on the fault current waveform to obtain the current sequence;

[0032] The root mean square error between the current sequence and the standard sine wave is calculated as the waveform distortion rate.

[0033] Read the upper limit and lower limit of waveform distortion rate thresholds for various fault types from the historical fault database;

[0034] Determine whether the waveform distortion rate is simultaneously greater than the lower limit of the waveform distortion rate threshold and less than the upper limit of the waveform distortion rate threshold;

[0035] When the waveform distortion rate is less than the lower limit of the waveform distortion rate threshold or greater than the upper limit of the waveform distortion rate threshold, the dynamic preemption priority will be multiplied by the preset attenuation coefficient.

[0036] When the waveform distortion rate is both greater than the lower limit of the waveform distortion rate threshold and less than the upper limit of the waveform distortion rate threshold, the dynamic preemption priority remains unchanged.

[0037] Furthermore, the necessity of resource preemption is determined based on the resource load status and the dynamic preemption priority after processing. If it exceeds the resource preemption threshold, the periodic task thread is frozen, computing resources are released, and a high-priority communication channel is opened, including:

[0038] The processed dynamic preemption priority is mapped to the resource preemption demand value;

[0039] Determine the current resource stress factor based on the resource load status;

[0040] Multiplying the resource acquisition demand value by the resource scarcity coefficient yields a quantitative value for the necessity of resource acquisition.

[0041] Compare the quantitative value of the necessity of resource preemption with the preset resource preemption threshold;

[0042] When the resource preemption necessity quantification value is greater than the resource preemption threshold, a thread freeze instruction is sent to the operating system to suspend the periodic task thread;

[0043] Reclaim computing resources occupied by suspended threads;

[0044] Create a high-priority communication channel that is independent of the regular channel in the communication protocol stack.

[0045] Furthermore, a fault recording compression command is sent to the target circuit breaker terminal via a high-priority communication channel, and the edge-preprocessed fault feature vector is received, including:

[0046] Transmit fault recording compression instructions carrying compression format identifiers to the target circuit breaker terminal through the established high-priority communication channel.

[0047] The target circuit breaker terminal performs format conversion processing on the original fault recording data according to the compression format identifier;

[0048] The target circuit breaker terminal performs feature extraction calculations on the format-converted fault recording data to generate a fault feature vector.

[0049] The target circuit breaker terminal encapsulates the fault feature vector into a data packet;

[0050] Receive data packets carrying fault feature vectors returned by the target circuit breaker terminal through a high-priority communication channel;

[0051] Parse data packets to extract fault feature vectors after edge preprocessing.

[0052] Furthermore, based on the fault feature vector, protection strategy optimization is performed within the released resources, reclosing parameters are generated and sent to the target circuit breaker terminal for execution via a high-priority communication channel, including:

[0053] Input the fault feature vector into the preset protection action rule base for pattern matching;

[0054] When a match is successful, the corresponding reclosing parameters are output directly.

[0055] The transient stability simulation calculation module is started when matching fails.

[0056] In the transient stability simulation calculation module, an equivalent circuit model of the protection area where the target circuit breaker is located is established;

[0057] Inject the current and voltage quantities corresponding to the fault feature vector into the equivalent circuit model;

[0058] Solve for the dynamic response curve of the equivalent circuit model within a preset time window;

[0059] The optimal reclosing delay parameters are calculated based on the zero-crossing time difference of the dynamic response curve.

[0060] Encapsulate the reclosing parameters or the optimal reclosing delay parameters into control commands;

[0061] Control commands are transmitted to the target circuit breaker terminal via a high-priority communication channel;

[0062] The target circuit breaker terminal parses the control command and executes the reclosing operation.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. By dynamically preempting resources and using edge collaborative processing, the timeliness and reliability of cloud-based protection strategy generation are both improved. Unlike the traditional cloud system's passive waiting mode for resources, dynamic preemption priorities are generated by power grid topology vulnerability assessment and circuit breaker collaborative demand analysis, enabling high-value fault diagnosis tasks to trigger resource reorganization mechanisms in real time. Combined with a waveform distortion rate-driven credibility decay algorithm, the invalid occupation of resources by suspicious fault information is effectively filtered. When the necessity of resource preemption reaches a threshold, the system actively freezes periodic tasks and releases computing resources, and simultaneously opens an independent communication channel to ensure end-to-end resource protection from fault feature extraction to strategy issuance, eliminating the risk of protection degradation caused by diagnostic delays.

[0065] 2. While ensuring real-time performance, the adaptability of the protection strategy is significantly optimized. By performing fault waveform compression and feature preprocessing at the target circuit breaker terminal, the cloud computing load is greatly reduced, allowing the released resources to perform complex calculations such as transient stability simulation. Based on the dual decision-making mechanism of protection action rule base and dynamic response curve, it not only uses historical fault modes to achieve rapid parameter matching, but also accurately calculates the optimal reclosing delay through equivalent circuit simulation. The high-priority communication channel ensures that the optimized parameters are issued quickly, enabling the circuit breaker to perform adaptive reclosing within the first voltage cycle after the fault is cleared. This effectively suppresses the risk of maloperation in complex fault scenarios under the traditional fixed parameter mode and improves the reliability of distribution network fault recovery. Attached Figure Description

[0066] Figure 1 This is a schematic diagram of the modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration of the present invention;

[0067] Figure 2 This is a flowchart illustrating the reliability decay process for dynamic preemption priority in this invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Example: Figure 1 A schematic diagram of the modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration of the present invention is provided. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration includes:

[0070] The load monitoring module is used by the cloud platform to monitor the resource load status of each computing node in real time.

[0071] The priority generation module is used to respond to fault diagnosis requests and generate dynamic preemption priorities based on the vulnerability of the power grid topology in the protection area where the target circuit breaker is located and the degree of coordinated operation requirements of associated circuit breakers.

[0072] The reliable attenuation module is used to extract the waveform distortion rate of the fault current. If it does not fall within the threshold range of the historical fault database, the reliability attenuation processing is applied to the dynamic preemption priority.

[0073] The resource preemption module is used to determine the necessity of resource preemption based on the resource load status and the dynamic preemption priority after processing. If it exceeds the resource preemption threshold, the periodic task thread is frozen, computing resources are released, and a high-priority communication channel is opened.

[0074] The feature extraction module is used to send fault recording compression instructions to the target circuit breaker terminal through a high-priority communication channel and to receive the fault feature vector after edge preprocessing.

[0075] The strategy execution module is used to perform protection strategy optimization within the released resources based on fault feature vectors, generate reclosing parameters, and send them to the target circuit breaker terminal for execution through a high-priority communication channel.

[0076] The cloud platform collects real-time operational data from each computing node through the performance monitoring interface provided by the operating system kernel. For CPU utilization monitoring, it calls the operating system's process management application programming interface (API) to obtain the percentage utilization of all logical cores of the CPU at fixed sampling intervals. The sampling interval is set to, for example, 100 milliseconds, and a timestamp and the corresponding CPU utilization value are recorded for each sample. Continuous data collection is performed, generating a curve showing the CPU utilization over time. This curve is composed of a sequence of timestamps arranged in chronological order and their corresponding utilization value sequences.

[0077] For memory usage monitoring, the real-time physical memory usage of the computing nodes is read through the operating system's memory management application interface. At each sampling point, the ratio of used memory capacity to total memory capacity is calculated and converted into a percentage value. The sampling interval is also set to, for example, 100 milliseconds. During continuous sampling, timestamps and corresponding memory usage values ​​are recorded synchronously, forming a curve showing the change in memory usage over time. This curve consists of a sequence of timestamps and corresponding sequences of memory usage values.

[0078] When calculating the cumulative duration percentage based on the CPU utilization curve over time, the following steps are performed: Set a CPU utilization threshold of, for example, 80%. This threshold is determined based on stress test results of the computing node in a power protection service scenario. Specifically, when simulating peak load for power fault diagnosis, if the CPU utilization consistently exceeds this threshold, the system response delay exceeds an acceptable range. Iterate through all sampling points on the CPU utilization curve, identifying sampling points where the utilization value exceeds the set threshold. Count the periods continuously exceeding the threshold. The over-limit duration for each period is calculated by multiplying the number of sampling points within that period by the sampling interval. Accumulate the over-limit duration for all periods to obtain the total over-limit duration. The cumulative duration percentage is the total over-limit duration divided by a preset time window length, for example, 5 seconds, which corresponds to the typical time requirement for high-voltage power grid fault clearing.

[0079] When calculating the maximum duration based on the memory utilization curve over time, the following steps are performed: A memory utilization threshold is set, for example, to 75%, determined based on the compute node's memory resource reservation strategy. The sampling point sequence of the memory utilization curve is traversed to identify consecutive periods where the utilization value continuously exceeds the set threshold. The duration is calculated for each consecutive period, which is the difference between the end and start timestamps of that period. The durations of all consecutive periods are compared, and the maximum value is recorded. This maximum value is the maximum duration exceeding the preset memory utilization threshold.

[0080] When combining the cumulative duration percentage and the maximum duration to form a resource load status quantification index, a piecewise function is used for fusion processing. When the cumulative duration percentage of the CPU utilization curve is less than, for example, 30% and the maximum duration of the memory utilization curve is less than, for example, 2 seconds, the resource load status quantification index equals the cumulative duration percentage multiplied by, for example, 0.5, plus the maximum duration multiplied by, for example, 0.5. When the cumulative duration percentage is greater than or equal to, for example, 30% or the maximum duration is greater than or equal to, for example, 2 seconds, the resource load status quantification index equals the cumulative duration percentage multiplied by, for example, 0.7, plus the maximum duration multiplied by, for example, 0.3. The weight allocation of this piecewise function is determined based on resource scheduling simulation test results: its weight coefficient is increased under high CPU load scenarios to reflect its greater impact on real-time performance. The value of the resource load status quantification index is standardized to an integer range of zero to one hundred using a linear mapping function.

[0081] The CPU utilization threshold is set based on the following testing process: Under a simulated short-circuit fault scenario, the diagnostic task load is gradually increased until the CPU utilization reaches different levels. The task response latency change curve is recorded, and the utilization rate corresponding to the sudden increase in response latency is selected as the threshold. The memory utilization threshold is set based on reserving, for example, one-quarter of the total memory for emergency caching to avoid performance degradation caused by memory swapping. The weight coefficients in the piecewise function are determined through resource scheduling simulation tests: different load combination scenarios are constructed, and parameter optimization is performed with the accuracy of resource preemption decision as the optimization objective. The transformation method of the linear mapping function is: multiply the original calculation result by one hundred and then round it down.

[0082] The calculation of resource load status metrics is performed by an independent monitoring agent. This agent is deployed on each computing node and performs data collection and calculation at fixed intervals, writing the results to a shared memory area. The monitoring agent automatically reduces the sampling frequency when the CPU is under high load; for example, when the utilization rate exceeds 90%, the sampling interval is adjusted to 200 milliseconds. During memory utilization monitoring, only the physical memory directly used by applications is counted, ignoring operating system cache memory.

[0083] The sampling points for the CPU utilization curve are stored using a circular buffer structure, with a buffer capacity of, for example, 1000 sampling points. The buffer capacity for the memory utilization curve is set to, for example, 500 sampling points. Exceeding-limit period identification uses a state machine algorithm: the initial state is "not exceeded"; when a sampling point exceeds the threshold, the period is marked as starting and the state switches, until a sampling point below the threshold is detected, marking the period as ending. The maximum duration calculation uses a dynamic update mechanism: when a new continuous period is detected, it is immediately compared and updated with the current maximum value.

[0084] The calculation of resource load status quantification indicators includes an anomaly handling mechanism: if the cumulative duration percentage exceeds 100% or the maximum duration exceeds the time window length, the indicator value is directly set to the maximum value of one hundred. Before outputting the indicator, a smoothing filter is performed: the arithmetic mean of the three most recent calculations is taken as the final output value, and the filter window size is set according to the inertial characteristics of load changes. When the monitoring agent program starts, a self-calibration process is executed: 100 consecutive idle data collections are performed to determine the baseline offset; subsequent data collections are deducted from this offset to eliminate system errors.

[0085] Data reads from the shared memory region employ atomic operations to ensure consistency. The resource scheduling module accesses metric values ​​via memory mapping, verifying the data checksum on each read to prevent transmission errors. An alarm is triggered and the system switches to a standby computing node if three consecutive reads fail. The monitoring agent periodically outputs resource load logs containing raw sampled data and intermediate values ​​from the computation process, used for offline analysis to verify metric accuracy. Log files are stored on a rolling time basis, with a maximum size limit for a single file set, for example, 10 megabytes.

[0086] When responding to a fault diagnosis request, the system obtains the real-time topology connection relationship of the protection zone where the target circuit breaker is located from the power grid energy management system. The real-time topology connection relationship is represented by a node-branch model, including the connection status and switch positions of electrical equipment such as buses, transformers, and transmission lines. The acquisition process is implemented through a common power system communication protocol, such as synchronizing topology change information once per second. The protection zone boundary is determined based on the upstream and downstream electrical distances of the target circuit breaker, including, for example, the bus directly connected to the target circuit breaker and adjacent equipment at two levels.

[0087] When performing N-1 safety checks on real-time topology connections, the system traverses all branches within the protection zone, simulating a fault by disconnecting only one branch at a time. AC power flow calculations are performed for each disconnection condition using the Newton-Raphson method iteratively, with convergence criteria of node power imbalance less than 0.01 MW and a maximum of 20 iterations. The verification criteria are: after disconnecting any branch, the power of the remaining branches does not exceed 90% of the rated transmission capacity, and the node voltage deviation does not exceed 5% of the nominal voltage. The number of branches failing the verification is counted, and their proportion to the total number of branches is calculated as the first factor. For example, if the protection zone contains 20 branches, and disconnecting 4 of them results in an over-limit situation, then the first factor is 20%. The line impedance matrix and transformer turns ratio data required for power flow calculations are obtained in real-time from the power grid parameter database.

[0088] When calculating the proportion of critical load power to total load power within the protected area, critical loads are defined as loads whose power outage would result in significant safety or economic losses. The system identifies critical loads from a pre-set load attribute tag library in the power grid dispatching system. Tags include three categories: "medical emergency loads," "national security loads," and "continuous production loads." The system acquires the total active power value of the protected area in real time and simultaneously reads the total active power of critical loads via smart meters using the DLMS / COSEM protocol. The second factor is the percentage of the total active power of critical loads divided by the total active power of all loads. The data acquisition period is set to, for example, 200 milliseconds.

[0089] When multiplying the first factor and the second factor to obtain the power grid topology vulnerability value, the system performs numerical standardization: both the first and second factors are percentage values, and the product is divided by 10000 to convert it into a real number between 0 and 1. When the protection zone includes a key substation, the first factor is multiplied by a coefficient of 1.5; when it includes a primary load, the second factor is multiplied by a coefficient of 1.2, and the upper limit of the corrected value is limited to 1.0.

[0090] When measuring the actual operating timing margin of the associated circuit breaker, the system collects the timestamps of the associated circuit breaker's operating events through a synchronous phasor measurement device. The actual operating timing margin is the millisecond-level time difference between the trip command issuance time and the fault detection initiation time. Clock synchronization uses the PTP protocol to ensure an error of less than 1 microsecond. If the associated circuit breaker has no historical operating records, the average operating time of the same type of fault in the most recent three months is used as an estimate.

[0091] When reading the preset standard coordination time difference, the system retrieves the parameters from the relay protection setting database by device number index. For ring network structures, the minimum coordination time difference principle is adopted; for example, 250 milliseconds is the default for 110 kV devices, and 300 milliseconds is the default for 220 kV devices. If there is no record in the database, it is generated according to the default rules for the voltage level.

[0092] When calculating the required degree of coordinated action, the system performs three steps: calculating the absolute difference between the actual timing margin and the standard coordination time difference; dividing the difference by the standard coordination time difference; and converting it to a percentage. For example, when the standard coordination time difference is 300 milliseconds and the actual timing margin is 250 milliseconds, the absolute difference is 50 milliseconds, and the ratio is 16.67%.

[0093] The dynamic preemption priority is generated by multiplying the power grid topology vulnerability value by the coordinated action demand value (converted to a real number between 0 and 1), and then multiplying by a preset priority scaling factor. For example, multiplying the power grid topology vulnerability value of 0.12 by the coordinated action demand value of 0.1667 yields 0.02, which, when multiplied by a scaling factor of 100, results in priority 2. The preset priority scaling factor has an initial value of 100 and is dynamically adjusted based on the resource preemption success rate over the past hour: it increases by a step of 5 when the success rate is below 90%, and decreases by a step of 5 when the success rate is above 95% and the system load rate is below 70%, with the adjustment range limited to 50 to 150.

[0094] The dynamic preemption priority generation process implements boundary protection: if the calculation result is less than 1, it is forcibly set to 1; if it is greater than 100, it is forcibly set to 100. Median filtering is performed before output, taking the median of the current result and the previous two values. The calculation timeout threshold is set to 50 milliseconds; if the timeout occurs, the previous valid value is output.

[0095] The system records a complete calculation log, including timestamps, protection zone numbers, first factors, second factors, grid topology vulnerability values, associated circuit breaker numbers, actual action timing margins, standard coordination time differences, coordinated action requirement values, preset priority scaling factors, and final priority values. Log entries are stored in chronological order and support retrieval by fault type for decision effectiveness analysis.

[0096] Critical loads are defined based on the terms of the power supply contract, while key substations are determined based on historical power grid operation data. During the N-1 safety check, if AC power flow calculations time out or oscillate, the algorithm automatically switches to a DC power flow approximation algorithm. Timing margin measurement data storage uses a ring buffer structure, retaining the 10 most recent records for data quality verification. Coordinated action demand calculation supports multi-level coordination modes; when multiple associated circuit breakers exist, the parameters of the nearest upstream circuit breaker are used as the benchmark.

[0097] Figure 2 A flowchart illustrating the reliability attenuation processing for dynamic preemption priority in this invention is provided. The original waveform data of the fault current of the target circuit breaker is obtained from a fault recording device. The fault current waveform is acquired through a current transformer and discretely sampled at a fixed sampling rate via an analog-to-digital converter. The sampling rate is set based on the transient characteristics of the power system, for example, 128 points per cycle, corresponding to a sampling interval of 156.25 microseconds for a 50 Hz system. The discrete sampling process continuously records complete data for three cycles after the fault occurs, generating a current sequence containing a timestamp sequence and a current amplitude sequence. The current amplitude unit is uniformly converted to kiloamperes, and the conversion factor is determined based on the current transformer ratio parameters.

[0098] When calculating the root mean square error (RMSE) between the current sequence and a standard sine wave, the standard sine wave is generated according to the following rules: the frequency is consistent with the system's rated frequency, for example, 50 Hz; the amplitude is the peak value of the effective current value in the first half-cycle before the fault occurs; and the phase angle is synchronized with the voltage zero-crossing point at the moment of the fault. The RMSE calculation uses a discrete point-to-point comparison method: for each sampling point of the current sequence, the square of the difference between it and the corresponding standard sine wave value is calculated; the squares of the differences from all sampling points are accumulated; and the accumulated value is divided by the total number of sampling points and the square root is taken. The calculation result is used as the waveform distortion rate, in kiloamperes.

[0099] When retrieving waveform distortion rate threshold ranges from the historical fault database, the database employs a relational database storage structure. Each fault record contains a fault type code, a lower threshold value for waveform distortion rate, and an upper threshold value for waveform distortion rate. Fault type codes are categorized according to common fault classification standards; for example, a single-phase ground fault is coded as TP1, and a phase-to-phase short-circuit fault is coded as TP2. The lower and upper threshold values ​​are determined through statistical analysis of historical data: typical event cases are selected for each fault type, and the quantiles of their waveform distortion rates are calculated as the threshold values. Database queries use the current fault type code as the index field.

[0100] When determining whether the waveform distortion rate is simultaneously greater than the lower threshold and less than the upper threshold, a numerical comparison logic operation is performed. The comparison process uses floating-point double-precision calculation, with precision retained to four decimal places. For example, if the waveform distortion rate is 2.354 kA, and the lower threshold for a single-phase ground fault is 1.200 kA and the upper threshold is 3.500 kA, then the interval condition is satisfied.

[0101] When the waveform distortion rate is less than the lower limit of the waveform distortion rate threshold or greater than the upper limit of the waveform distortion rate threshold, the priority will be dynamically multiplied by a preset attenuation coefficient. The initial value of the preset attenuation coefficient is set to, for example, 0.7, which is determined based on historical data analysis. The multiplication calculation is performed using floating-point arithmetic, and the result is rounded to two decimal places. For example, the original priority of 85.00 multiplied by 0.7 results in 59.50.

[0102] When the waveform distortion rate is simultaneously greater than the lower limit of the waveform distortion rate threshold and less than the upper limit of the waveform distortion rate threshold, the dynamic preemption priority value remains unchanged. No value modification is performed under this path, and the original priority is directly passed to the subsequent processing flow.

[0103] The fault current acquisition process includes data preprocessing: the raw sampled values ​​are filtered by a digital filter to eliminate the DC component; the filter is a high-pass filter with a cutoff frequency of 0.5 Hz. Outlier removal is performed at each sampling point: if the current mutation rate exceeds, for example, 10 kA / ms, the linear interpolation of the previous two sampling points is used instead. After the waveform distortion rate is calculated, the current fault waveform and calculation results are automatically stored in the historical fault database, with a storage period of 24 hours.

[0104] The threshold update mechanism for the historical fault database is as follows: New fault case data is periodically analyzed to recalculate the waveform distortion rate quantiles for various fault types. When the number of new fault cases for a certain type exceeds, for example, 20, the threshold recalculation process is triggered. The new threshold must pass an approval process before it takes effect; if the approval fails, the original threshold is retained.

[0105] The dynamic adjustment method for the preset attenuation coefficient is as follows: periodically evaluate the effectiveness of the reliability attenuation decision and statistically analyze the change in fault diagnosis accuracy after priority attenuation. If the accuracy decreases by more than 5%, the attenuation coefficient is increased by 0.1; if the accuracy increases by more than 5%, the attenuation coefficient is decreased by 0.1. The adjustment range is limited to between 0.5 and 0.9.

[0106] Waveform distortion rate calculation incorporates temperature compensation: the sampled value is proportionally corrected based on the ambient temperature sensor readings of the current transformer. Temperature sensor data is acquired in real time via a communication protocol, and the compensation coefficient is stored in the equipment calibration parameter table.

[0107] The phase synchronization method between the current sequence and the standard sine wave is as follows: extract the zero-crossing point of the voltage waveform 1 millisecond before the fault occurs as the phase reference. If the voltage channel fails, the whole-second pulse of the system timing clock is used as the synchronization signal. If the synchronization error exceeds 200 microseconds, the backup synchronization scheme is activated.

[0108] The root mean square error (RMSE) calculation employs a segmented processing mechanism: the current sequence is divided into multiple sub-segments according to cycles, and the distortion rate of each sub-segment is calculated independently before averaging. This processing can suppress local distortion interference caused by transient processes. The sub-segment division is based on automatic marking of voltage zero-crossing points, and each cycle contains, for example, 128 sampling points.

[0109] The log records the attenuation operation of dynamic preemption priority, including fault waveform characteristic values, waveform distortion rate, lower threshold value, upper threshold value, original priority, attenuation coefficient, and new priority. Log entries are associated with fault waveform recording file numbers, supporting waveform data traceability and review.

[0110] Special handling for waveform distortion exceeding the threshold: If multiple consecutive faults result in distortion rates exceeding the threshold range, a current transformer calibration alarm is triggered. An equipment calibration work order is automatically generated, containing the percentage deviation between the current waveform distortion rate and the historical average. The calibration cycle is dynamically adjusted based on the equipment's operating years; for example, new equipment is calibrated once in its first year, and every six months thereafter after five years of operation.

[0111] Version management of preset attenuation coefficients: A new version number is generated after each coefficient adjustment, and the old coefficient values ​​are retained in the historical parameter database. Rollback is supported; if a new coefficient causes a diagnostic error, the system can revert to the previous version. The version change log includes the modification time, adjustment basis, and expected impact information.

[0112] The fault current waveform is stored using a lossy compression algorithm with a compression ratio set to, for example, 4:1. A checksum is added to the compressed data; if the checksum fails, the original data is automatically retransmitted. Waveform files are stored by device partition, with a maximum file size limit of 10 megabytes.

[0113] The standard sine wave amplitude calibration method in the root mean square error calculation is as follows: When the first half-cycle of a fault is invalid, 1.5 times the peak value of the rated current is taken as the default amplitude. When phase synchronization fails, the fault initiation point is taken as the zero-phase reference. When cross-cycle situations occur in sub-segment division, the calculation weights are adjusted proportionally according to the actual number of sampling points.

[0114] Validation of waveform distortion rate results: When the calculated result is greater than 20 kA, the verification process is initiated. The verification uses a dual-algorithm parallel calculation: the main algorithm is the root mean square error method, and the auxiliary algorithm is the total harmonic distortion rate method. When the difference between the two exceeds 10%, the average value is taken as the final result.

[0115] Historical fault database case selection criteria: Only cases within the current transformer's calibration period and with a fault resistance of less than 10 ohms are included. Before adding new cases to the database, waveform quality testing is performed; cases with a signal-to-noise ratio below 40 dB are automatically removed. Threshold recalculation uses a rolling window mechanism, retaining the latest 100 valid records each time.

[0116] The evaluation period for the attenuation coefficient is set to 30 days, and the evaluation data is derived from the most recent 100 fault diagnosis records. Accuracy statistics exclude invalid cases caused by communication interruptions. The coefficient adjustment operation is automatically executed during system idle time, and a data snapshot is created before execution for rollback.

[0117] Calibration method for temperature compensation coefficient: 11 calibration points are set within the range of -10 degrees Celsius to +60 degrees Celsius. 100 sets of data are collected at each calibration point to fit a linear compensation curve. The compensation formula is: Compensated current value = Original sampled value × [1 + 0.001 × (25 - Current temperature)].

[0118] The triggering conditions for calibration alarms are detailed as follows: three consecutive exceedances of the threshold or a single deviation exceeding 50% of the historical average. Work order dispatch rules: work orders are dispatched within 2 hours on weekdays and postponed to the next business day on non-working days. Calibration result feedback mechanism: new parameters must be uploaded within 24 hours of calibration; otherwise, an escalation notification will be triggered.

[0119] When mapping the processed dynamic preemption priority to resource preemption demand value, a piecewise linear interpolation method is used for the conversion. The input range of the processed dynamic preemption priority is an integer from 1 to 100, and the output range of the resource preemption demand value is an integer from 0 to 100. When the processed dynamic preemption priority is less than or equal to 30, the resource preemption demand value is equal to the processed dynamic preemption priority × 0.5; when the processed dynamic preemption priority is between 31 and 70, the resource preemption demand value is equal to 30 × 0.5 + (processed dynamic preemption priority - 30) × 1.0; when the processed dynamic preemption priority is greater than 70, the resource preemption demand value is equal to 30 × 0.5 + 40 × 1.0 + (processed dynamic preemption priority - 70) × 1.5. This mapping relationship is determined based on the system's historical load stress test results: under simulated high-priority task scenarios, when the processed dynamic preemption priority exceeds 70, the resource demand exhibits a non-linear growth characteristic.

[0120] When determining the current resource stress factor based on resource load status, the resource load status is represented by a quantified resource load status index. The current resource stress factor is calculated as: Current resource stress factor = Quantified resource load status index ÷ 100. The quantified resource load status index is obtained in real time from the resource monitoring process via shared memory. When the quantified resource load status index exceeds 95, the current resource stress factor is forcibly set to 1.0. This process avoids calculation anomalies under extreme load conditions.

[0121] When multiplying the resource preemption demand value by the current resource scarcity coefficient to obtain the quantified value of resource preemption necessity, a floating-point multiplication operation is performed. The calculation result is rounded to two decimal places. For example, multiplying the resource preemption demand value of 80.00 by the current resource scarcity coefficient of 0.85 yields 68.00. A boundary condition is set for the calculation result: if the product > 100.00, output 100.00; if < 0.00, output 0.00. This boundary protection mechanism prevents subsequent comparison operations from failing.

[0122] When comparing the quantified value of resource preemption necessity with the preset resource preemption threshold, the preset resource preemption threshold is initially set to 50.00. This threshold setting is based on system performance test data: when the quantified value of resource preemption necessity > 50, the accelerated fault diagnosis benefits brought by resource preemption outweigh the losses from periodic task pauses. The comparison operation uses the IEEE 754 standard floating-point comparison instruction, with an error tolerance set to 0.001.

[0123] When the resource preemption necessity quantification value exceeds the preset resource preemption threshold, a thread freeze command is sent to the operating system kernel. The thread freeze command is implemented through the operating system application programming interface (API) and targets periodic task threads. Periodic task threads refer to background tasks with a fixed execution cycle, such as a data backup thread with a 5-minute cycle or a log archiving thread with a 1-hour cycle. The selection rule for the freeze target is: select the top three periodic task threads with the highest CPU utilization rate that started within the last 5 minutes, excluding pre-marked critical system threads.

[0124] When reclaiming computing resources occupied by suspended threads, memory and processor core release operations are performed. Memory reclamation is implemented through the operating system's memory management interface, marking the heap and stack memory of the suspended thread as reclaimable. Processor core release is completed through the scheduler interface, releasing the binding relationship between the suspended thread and the processor core. Resource reclamation is recorded in real time: memory reclamation is accurate to megabytes, and core reclamation is accurate to the unit.

[0125] When creating a high-priority communication channel independent of the regular channel in the communication protocol stack, network resource configuration is performed. A dedicated port number range, such as 60000 to 60010, is reserved in the transport layer protocol stack. A User Datagram Protocol (UDP) socket is created, and the Type of Service field is set to the highest priority. The channel establishment process includes a bandwidth guarantee mechanism: a fixed percentage of network bandwidth, such as 30% of the total bandwidth, is reserved for the high-priority communication channel.

[0126] Resource preemption demand value mapping table maintenance mechanism: Monthly statistical analysis of resource preemption success rate. When the success rate is below 85%, the slope of the second segment of the mapping curve is increased by 0.1; when the success rate is above 95%, the slope is decreased by 0.1. The slope adjustment range is limited to between 0.3 and 2.0. Update operations are performed during system idle periods, and the version change record includes the modification time, original slope, new slope, and adjustment basis.

[0127] Periodic task thread freeze execution exception handling: If the operating system returns a freeze failure, try the next candidate thread. After three consecutive failures, trigger failover and switch to a standby compute node to perform the same operation. Upon successful freeze, register a resource release callback function, which automatically wakes up the frozen thread after the fault handling is completed.

[0128] Memory reclamation operations trigger defragmentation: When the amount of memory reclaimed in a single operation exceeds 50 megabytes, memory compaction is automatically invoked. Processor core release employs a load balancing strategy: cores bound to non-real-time tasks are released first. Resource reclamation reports include: timestamp, amount of memory reclaimed, list of released core numbers, and list of frozen thread identifiers.

[0129] The high-priority communication channel establishment process includes a fault-tolerance mechanism: when the preferred port is occupied, subsequent ports are automatically tried in the port sequence. Channel parameters are configured as follows: time-to-live value is set to 1, and the window size is fixed at 8192 bytes. Channel health monitoring: a heartbeat data packet is sent every 100 milliseconds; if three consecutive heartbeat packets are lost, channel reconstruction is triggered.

[0130] The resource stress factor calculation incorporates a trend factor: when the resource load status quantification index shows an upward trend for 5 consecutive samples, the current resource stress factor is multiplied by 1.2. Trend judgment uses linear regression to calculate the slope value of the most recent 5 sampling points; a slope > 0.5 is considered an upward trend.

[0131] Resource preemption necessity quantification value implementation time decay: at the top of the hour, the current value is multiplied by 0.95, and when the decayed value is <10.00, it is reset to zero. The decay coefficient is dynamically adjusted according to the system load rate: when the resource load status quantification index is <30, the decay coefficient is changed to 0.90.

[0132] The high-priority communication channel uses a token bucket algorithm for flow control: the token bucket capacity is set to 1,048,576 bytes, and the token generation rate is set to 3,145,728 bits / second. Data transmission is subject to burst limits: the amount of data sent in a single instance does not exceed 80% of the bucket capacity. Channel usage metrics are monitored in real time: the number of bytes sent per second is counted, and a rate-limiting mechanism is activated when the threshold is exceeded.

[0133] Resource reallocation strategy: Released memory is preferentially allocated to the data buffer of fault diagnosis tasks, and released processor cores are bound to high-priority fault calculation threads. The reallocation operation is performed within 50 milliseconds after resource reclamation is completed, and the allocation result is written to the resource allocation register.

[0134] Communication channel security mechanisms: Two-way X.509 certificate authentication is performed upon channel establishment, with certificates valid for 30 days. Data transmission is encrypted using 256-bit Advanced Encryption Standard. Key management: New keys are generated hourly and seamlessly updated via Elliptic Curve Diffie-Hellman key exchange.

[0135] Resource analysis of frozen threads: Detailed resource usage of the thread is obtained through the operating system performance interface, including thread identifier, memory usage (megabytes), processor cycle consumption, and last execution timestamp. The analysis report serves as the basis for resource reclamation.

[0136] Quality of Service (QoS) assurance for high-priority communication channels: Configure latency cap of 10 milliseconds, jitter cap of 2 milliseconds, and packet loss rate cap of 0.1%. Routing priority is implemented through the differential service code point field. Channel performance monitoring: End-to-end latency is measured every 5 seconds; channel optimization is triggered if the latency exceeds 10 milliseconds for three consecutive measurements.

[0137] Resource preemption decision-making process audit: Records timestamps, processed dynamic preemption priority, resource preemption demand value, quantitative indicators of resource load status, current resource tension coefficient, quantitative value of resource preemption necessity, preset resource preemption threshold, decision results, list of frozen threads, amount of resources reclaimed, and channel port number. Audit logs are stored with AES encryption and retained for 90 days.

[0138] Calibration method for preset resource preemption threshold: Perform stress tests quarterly, gradually increase the simulated task load, record the correspondence between the quantitative value of resource preemption necessity and system response, and take the response latency inflection point value as the new threshold. The test report includes: test time, number of simulated tasks, response latency at each load point, and the calculation process of the inflection point value.

[0139] A fault recording compression command is sent to the target circuit breaker terminal via an established high-priority communication channel. This command includes a compression format identifier field. The compression format identifier field is an 8-bit binary code, where the first 3 bits indicate the sampling rate requirement, the middle 3 bits indicate the compression algorithm type, and the last 2 bits indicate the verification method. For example, the code "00101011" indicates: a sampling rate of 128 points / cycle, using a discrete cosine transform compression algorithm, with additional cyclic redundancy check. The command transmission uses the User Datagram Protocol (UDP), with the Quality of Service (QoS) flag set to the highest priority in the packet header, a timeout retransmission interval of 50 milliseconds, and a maximum of 3 retries. The encoding rules for the compression format identifier are generated based on the equipment capability configuration table, which is stored in the non-volatile memory of the target circuit breaker terminal.

[0140] After receiving the command, the target circuit breaker terminal parses the compression format identifier field and performs format conversion processing on the original fault waveform data according to the identifier field. The original fault waveform data is a sequence of continuous sampled values ​​collected by the current transformer, with a sampling interval of 156.25 microseconds. The format conversion processing includes: resampling according to the sampling rate requirements of the compression format identifier; when a reduced sampling rate is required, an anti-aliasing filter with a cutoff frequency of 40 Hz is used; initializing compression parameters according to the compression algorithm type, for example, the retention coefficient for discrete cosine transform compression is set to 0.8, which is determined based on typical fault waveform reconstruction error tests; adding a check data block, for example, the cyclic redundancy check block length is 32 bits. The processed data is converted into a standard compressed frame structure, with the frame header containing a timestamp and device identifier. When the command identifier does not match the device configuration, the default configuration is automatically enabled: sampling rate of 64 points / cycle, stroke length compression algorithm, and parity check.

[0141] The target circuit breaker terminal performs feature extraction calculations on the format-converted fault waveform data to generate a fault feature vector. Feature extraction calculation includes three steps: calculating the effective value of the fundamental component of the fault current using a full-cycle Fourier transform algorithm with a fixed number of 128 points; extracting the percentage of the second harmonic content using a 1024-point Fast Fourier Transform with a Hanning window; and calculating the waveform asymmetry by comparing the difference in the integral areas of the positive and negative half-cycles, using the formula: |positive half-cycle area - negative half-cycle area| ÷ (positive half-cycle area + negative half-cycle area). The fault feature vector is a three-dimensional floating-point array, stored in the order of [fundamental effective value (kA), harmonic content (percentage), asymmetry coefficient]. For example, a fault feature vector [3.25, 15.7, 0.12]. Anomaly handling mechanism: when the data length is less than one cycle, it is automatically padded with zeros to a complete cycle; when the Fast Fourier Transform spectral leakage exceeds 10%, a multi-signal classification algorithm is used for recalculation.

[0142] The target circuit breaker terminal encapsulates the fault feature vector into a data message. The encapsulation process performs the following operations: adding a message header containing a 4-byte sequence number and an 8-byte precise time protocol timestamp; converting each floating-point number in the feature vector to a 4-byte single-precision format according to the IEEE 754 standard; appending a 4-byte cyclic redundancy check (CRC) code, generating a polynomial of 0x04C11DB7; and adding a 2-byte length field indicating the payload size. The message structure is defined as: 0xAA55 start character (2 bytes) + sequence number (4 bytes) + timestamp (8 bytes) + feature vector data (12 bytes) + CRC code (4 bytes) + 0x55AA end character (2 bytes). After encapsulation, the data is stored in a transmission buffer with a capacity of 10 messages.

[0143] Data packets returned by the target circuit breaker terminal are received through a high-priority communication channel. Flow control is performed during reception: when network latency > 10 milliseconds, the receive window size is adjusted to 4096 bytes. Message reassembly uses a sliding window protocol with a window size of 8 messages. Reception integrity verification includes: verifying the match between the start symbol 0xAA55 and the end symbol 0x55AA; calculating the cyclic redundancy check (CRC) code and comparing it with the check value within the message; and checking sequence number continuity. A retransmission request is triggered upon verification failure, with an exponential backoff strategy for retransmission intervals: 50 milliseconds for the first retransmission, 100 milliseconds for the second, and 200 milliseconds for the third. After three consecutive failures, the system switches to a backup communication channel.

[0144] The fault feature vector after edge preprocessing is extracted from the parsed data message. The parsing process is implemented in three steps: separating the message header and payload data; converting the 12-byte feature vector data into single-precision floating-point numbers in 4-byte groups; and performing numerical validity verification. The validity verification rules are as follows: the effective value range of the fundamental frequency is limited to 0.1 kA to 50.0 kA (based on 1% to 200% of the equipment's rated current); the harmonic content percentage range is 0 to 100%; and the asymmetry coefficient range is 0 to 1. When the value exceeds the limit, an error flag is added, and the error code is encoded according to the exceedance type. After parsing, the data is stored in the diagnostic database using incremental compression: when the rate of change of the continuous vector is <5%, only the difference is stored.

[0145] Temperature compensation calculated based on feature extraction: The fundamental effective value is compensated and corrected according to the temperature sensor readings at the circuit breaker terminals. The compensation formula is: Compensated value = Original value × [1 + 0.0005 × (25 - Current temperature)]. The temperature data update frequency is 1 Hz, and the temperature sensor calibration cycle is 90 days. The compensation coefficient is determined based on the transformer temperature drift characteristic test data.

[0146] Fault tolerance mechanism for data packet parsing: When packet fragmentation is detected, a 200-millisecond reassembly timer is started; when cyclic redundancy check fails but the length is valid, the Reed-Solomon error correction algorithm is attempted to recover; when the sequence number breakpoint exceeds 5, a full synchronization request is triggered, and the full synchronization interval is at least 60 seconds.

[0147] Fault feature vector storage management: The real-time zone retains the latest 100 records, stored in double data rate synchronous dynamic random access memory; the historical zone is partitioned by hour and stored in flash memory, with a maximum capacity of 10 megabytes per partition. Retrieval uses a binary search algorithm, with the timestamp as the index field.

[0148] Compression command timeout monitoring: A 500-millisecond response timer is started when a command is sent. If no response is received within the timeout period, the terminal is marked as offline, triggering a device status alarm. Terminal online rate is statistically analyzed hourly; when it falls below 90%, a device maintenance work order is generated, with a work order response time limit of 2 hours.

[0149] Resource management for feature extraction: When processor utilization exceeds 80%, computational precision is reduced; for example, the number of points in the Fast Fourier Transform is reduced from 1024 to 512. Memory usage is capped at 10 megabytes; exceeding this limit results in the discarding of historical data according to a first-in, first-out (FIFO) principle. Computational tasks are prioritized as real-time tasks.

[0150] Bandwidth guarantee for message reception: A fixed bandwidth quota of 50 kilobits per second is allocated to feature vector messages. Packet loss policy is activated during network congestion: heartbeat messages are dropped first, followed by historical data messages. Channel performance metrics are refreshed every second, including reception success rate, average latency, and packet loss rate.

[0151] Fault feature vector transmission encryption: The feature vector data is encrypted using a 128-bit Advanced Encryption Standard (AES) algorithm, and the encryption key is updated hourly. The increased processing latency due to encryption is less than 1 millisecond, achieved through a hardware acceleration module. Key update commands are issued via an independent control channel, and the control channel authentication uses an elliptic curve digital signature algorithm.

[0152] Feature vector anomaly marking handling rules: When the error flag indicates that the fundamental effective value exceeds the limit, it is automatically replaced with the previous effective value; when the harmonic content exceeds the limit, the original value is retained but marked as suspicious data; when the asymmetry coefficient exceeds the limit, the waveform verification process is triggered. The verification is calculated by resampling the original waveform at a resampling rate of 256 points / cycle.

[0153] When fault feature vectors are input into a preset protection action rule base for pattern matching, the preset protection action rule base uses a relational database to store the matching rules. Each rule contains a feature vector range definition and a corresponding set of reclosing parameters. The feature vector range definition includes six dimensions: lower limit of fundamental RMS value, upper limit of fundamental RMS value, lower limit of harmonic content, upper limit of harmonic content, lower limit of asymmetry, and upper limit of asymmetry. The pattern matching process performs the following operations: iterates through all rule entries. When the fundamental RMS value of the fault feature vector is between the lower and upper limits of a certain rule, and the harmonic content is between the lower and upper limits of the harmonic content, and the asymmetry is between the lower and upper limits of the asymmetry, the match is considered successful. The matching accuracy is set to a floating-point tolerance range of ±0.5%. For example, a fundamental RMS value of 3.25 kA is matched within a range of 3.235 kA to 3.265 kA.

[0154] When a match is successful, the corresponding reclosing parameters are directly output. These parameters include three fields: reclosing enable flag, reclosing delay time, and reclosing count. The output process performs parameter validity checks: the reclosing delay time is limited to between 0.1 seconds and 5.0 seconds, and the reclosing count is limited to between 1 and 3 times. Upon successful validation, a parameter output event is generated, containing a timestamp, rule number, and output parameter value. For example, when matching rule R15, the output parameters are {enable flag = 1, delay time = 0.8 seconds, count = 2}.

[0155] When a match fails, the transient stability simulation calculation module is initiated. The trigger condition is that all rules are not matched consecutively. The simulation module initialization time is controlled within 10 milliseconds. The initialization process includes: loading the latest grid topology snapshot, allocating a 100-megabyte simulation memory pool, and setting a simulation step size of 50 microseconds. Automatic retry is performed upon startup failure, with a maximum of 3 retries and a retry interval of 100 milliseconds.

[0156] In the transient stability simulation calculation module, an equivalent circuit model of the protection zone where the target circuit breaker is located is established. The equivalent circuit model adopts a π-type equivalent circuit model. The modeling process includes: generating the node admittance matrix based on the real-time topology connection relationship; equating the generator with an internal resistance series voltage source, the internal resistance value is taken from the equipment parameter library; equating the load with a constant impedance, the impedance value is calculated based on the power before the fault; and equating the line with a π-type network composed of resistors, inductors, and capacitors, the parameters of which are taken from the line parameter database. Model accuracy control: parallel capacitors are retained for voltage levels of 220 kV and above, and the capacitor effect is ignored for voltage levels of 110 kV and below.

[0157] The current and voltage quantities corresponding to the fault feature vector are injected into the equivalent circuit model. The injection quantity is calculated using the fault sequence component method. For a single-phase ground fault, the injected zero-sequence current is equal to the fundamental RMS value × 0.33; for a phase-to-phase short-circuit fault, the injected negative-sequence current is equal to the fundamental RMS value × 0.5. The initial voltage phase is set to the zero-crossing point of the voltage before the fault, and the amplitude is set to the rated voltage × 0.9. The injection point is selected as the bus node where the target circuit breaker is located, and the injection duration is set to 100 milliseconds.

[0158] The dynamic response curve of the equivalent circuit model is obtained within a preset time window of 500 milliseconds. The variable-step Runge-Kutta method is used, with a relative error tolerance of 0.001. The dynamic response curve includes three-phase voltage waveforms, with one sampling point output every 50 microseconds, for a total of 10,000 sampling points. Numerical stability is monitored in real time during the solution process, and the implicit integration algorithm is switched when the matrix condition number exceeds 10,000.

[0159] The optimal reclosing delay parameter is calculated based on the zero-crossing time difference of the dynamic response curve. The calculation process involves the following steps: extracting the voltage waveform from 100 to 500 milliseconds after fault clearance; detecting the zero-crossing time of each phase voltage (the crossing point where the voltage value changes from negative to positive); calculating the standard deviation of the zero-crossing times of the three phases; taking the zero-crossing time of the phase with the smallest standard deviation as the reference time point; the optimal reclosing delay parameter is equal to the reference time point minus the fault clearance time. The calculation result is limited to the range of 0.1 seconds to 5.0 seconds; if it exceeds the range, the boundary value is used.

[0160] The reclosing parameters or optimal reclosing delay parameters are encapsulated into control instructions. The encapsulation format is defined as: 2-byte start code 0x55AA + 1-byte instruction type + 4-byte delay parameter (in milliseconds) + 1-byte reclosing count + 2-byte checksum + 2-byte end code 0xAA55. The checksum calculation uses a 16-bit summation and complement algorithm. Parameter verification is performed before encapsulation: when the delay parameter is <100 milliseconds, it is forcibly set to 100 milliseconds; when the reclosing count is >3, it is forcibly set to 3.

[0161] Control commands are transmitted to the target circuit breaker terminal via a high-priority communication channel, using a reliable user datagram protocol with retransmission mechanism. The retransmission strategy is as follows: a 50-millisecond acknowledgment timer is started after the initial transmission; retransmission occurs every 50 milliseconds if no acknowledgment is received; the maximum number of retransmissions is 5. The service type field of the data packet is set to the highest priority. The transmission timeout threshold is set to 500 milliseconds.

[0162] The target circuit breaker terminal parses the control command and executes the reclosing operation. The parsing process includes: verifying the matching of the start code and end code; calculating the checksum and comparing it with the checksum value in the command; and extracting the delay parameter and the number of reclosing attempts. The execution process is as follows: after the fault is cleared, a delay timer is started; when the timer reaches the delay parameter value, a closing pulse is issued; if closing fails and the remaining attempts are >0, the operation is repeated after an interval of 1 second. The operation results are recorded in non-volatile memory.

[0163] The preset protection action rule base update mechanism is as follows: New fault cases are analyzed weekly. When a certain fault mode occurs more than 10 times and does not match any existing rules, a new rule draft is automatically generated. New rules require manual review and confirmation, and are then hot-updated to the online database after approval. The rule validity period is set to one year.

[0164] Equivalent circuit model parameter update process: Model reconstruction is triggered when line parameters change, and a parameter change notification is received from the dispatch center. Notification processing delay is <100 milliseconds, and model reconstruction time is <50 milliseconds. Parameter version management uses an incremental tagging method.

[0165] Accelerated solution for dynamic response curves: A 50-microsecond step size is used for the first 100 milliseconds, followed by 100-microsecond step sizes thereafter. The solution is terminated early after 300 milliseconds when the curve oscillation coefficient is less than 0.1. The solution results are cached in shared memory.

[0166] Security protection for control commands: A digital signature is added before transmission, using the elliptic curve digital signature algorithm. The terminal verifies the signature validity before parsing, and the signature validity period is set to 5 minutes. If signature verification fails, the command is discarded and a security alarm is reported.

[0167] The interlocking conditions for reclosing are as follows: closing is prohibited when a permanent fault indicator is detected; operation is prohibited when the temperature of the circuit breaker's mechanical mechanism is >90℃; and execution is delayed if the number of operations exceeds 10 in the last 24 hours. The interlocking status is fed back to the control center in real time.

[0168] Simulation module resource monitoring: Real-time statistics of processor utilization; when >80%, load balancing is initiated, migrating 50% of computational tasks to a backup node. Memory usage is capped at 90 MB; if exceeded, the earliest simulation results are released. A watchdog timer is set for each computational task, with a timeout threshold of 5 seconds.

[0169] Priority guarantee for command transmission: An independent transmission queue is allocated for control commands in the communication protocol stack, with a queue depth of 8 packets. Status monitoring packets are dropped first during network congestion to ensure a control command transmission success rate >99.9%. The transmission path supports dual-route switching.

[0170] Feedback mechanism for reclosing operations: An operation report is sent within 200 milliseconds after execution, including the actual action time, success flag, and remaining operation count. The report uses the same encapsulation format as the instruction. A re-query is triggered if no report is received, with a re-query interval of 1 second and a maximum of 3 times.

[0171] Storage strategy for dynamic response curves: Only key feature point data, including zero-crossing moments, extreme points, and inflection points, are saved. Stroke length encoding compression is used, with a typical compression ratio of 8:1. Curve data is stored in association with fault numbers, with a retention period of 30 days.

[0172] Optimized compensation for the best reclosing delay parameters: Based on the circuit breaker mechanical response test data, a fixed compensation time of 20 milliseconds is added. An additional compensation of 1 millisecond / ℃ is applied when the ambient temperature is <0℃, and 0.5 milliseconds / ℃ is applied when the ambient temperature is >40℃. The maximum compensation value is 100 milliseconds.

[0173] Degradation handling for pattern matching: When the rule base fails to load, a local simplified rule set is enabled. The simplified rules contain only the fundamental valid value as a single dimension. The matching timeout threshold is set to 20 milliseconds. The simplified rule set is updated monthly.

[0174] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0175] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0176] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0177] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0178] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0179] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0181] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0182] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0183] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration, characterized in that, include: The load monitoring module is used by the cloud platform to monitor the resource load status of each computing node in real time. The priority generation module, used to respond to fault diagnosis requests, generates dynamic preemption priorities based on the vulnerability of the power grid topology in the protection zone where the target circuit breaker is located and the degree of coordinated operation requirements of associated circuit breakers. This includes: After responding to the fault diagnosis request, the power grid topology vulnerability value is multiplied by the coordinated action requirement value, and then multiplied by the preset priority scaling factor to generate a dynamic preemption priority. The method for obtaining numerical values ​​of power grid topology vulnerability is as follows: Obtain the real-time topology connection relationship of the protection zone where the target circuit breaker is located; Perform N-1 security checks on the real-time topology connections and use the proportion of branches that fail the checks as the first factor. The proportion of critical load power to total load power within the protection zone is calculated as the second factor. Multiplying the first factor by the second factor yields the power grid topology vulnerability value; The method for obtaining the collaborative action demand value is as follows: Measure the actual operating timing margin of the associated circuit breaker; Read the preset standard coordination time difference; The ratio of the absolute difference between the actual timing margin and the standard coordination time difference to the standard coordination time difference is used as the value of the coordination motion demand. The reliable attenuation module is used to extract the waveform distortion rate of the fault current. If it does not fall within the threshold range of the historical fault database, the reliability attenuation processing is applied to the dynamic preemption priority. The resource preemption module is used to determine the necessity of resource preemption based on the resource load status and the dynamic preemption priority after processing. If it exceeds the resource preemption threshold, the periodic task thread is frozen, computing resources are released, and a high-priority communication channel is opened. The feature extraction module is used to send fault recording compression instructions to the target circuit breaker terminal through a high-priority communication channel and to receive the fault feature vector after edge preprocessing. The strategy execution module is used to perform protection strategy optimization within the released resources based on fault feature vectors, generate reclosing parameters, and send them to the target circuit breaker terminal for execution through a high-priority communication channel.

2. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration according to claim 1, characterized in that, The cloud platform monitors the resource load status of each computing node in real time, including: Obtain the curve of CPU utilization of the computing node over time; Obtain the curve of memory usage of compute nodes over time; The cumulative duration exceeding the preset CPU utilization threshold is calculated based on the CPU utilization curve. The maximum duration for which the memory usage rate continuously exceeds the preset memory usage rate threshold is calculated based on the memory usage rate curve. The cumulative duration percentage is combined with the maximum duration to form a quantitative indicator of resource load status.

3. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration according to claim 2, characterized in that, Extract the waveform distortion rate of the fault current. If it does not fall within the historical fault database threshold range, apply a reliability decay process to the dynamic preemption priority, including: Extract the fault current and perform discrete sampling on the fault current waveform to obtain the current sequence; The root mean square error between the current sequence and the standard sine wave is calculated as the waveform distortion rate. Read the upper limit and lower limit of waveform distortion rate thresholds for various fault types from the historical fault database; Determine whether the waveform distortion rate is simultaneously greater than the lower limit of the waveform distortion rate threshold and less than the upper limit of the waveform distortion rate threshold; When the waveform distortion rate is less than the lower limit of the waveform distortion rate threshold or greater than the upper limit of the waveform distortion rate threshold, the dynamic preemption priority will be multiplied by the preset attenuation coefficient. When the waveform distortion rate is both greater than the lower limit of the waveform distortion rate threshold and less than the upper limit of the waveform distortion rate threshold, the dynamic preemption priority remains unchanged.

4. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration according to claim 3, characterized in that, The necessity of resource preemption is determined based on the resource load status and the dynamic preemption priority after processing. If it exceeds the resource preemption threshold, the periodic task thread is frozen, computing resources are released, and a high-priority communication channel is opened, including: The processed dynamic preemption priority is mapped to the resource preemption demand value; Determine the current resource stress factor based on the resource load status; Multiplying the resource acquisition demand value by the resource scarcity coefficient yields a quantitative value for the necessity of resource acquisition. Compare the quantitative value of the necessity of resource preemption with the preset resource preemption threshold; When the resource preemption necessity quantification value is greater than the resource preemption threshold, a thread freeze instruction is sent to the operating system to suspend the periodic task thread; Reclaim computing resources occupied by suspended threads; Create a high-priority communication channel that is independent of the regular channel in the communication protocol stack.

5. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration according to claim 4, characterized in that, A fault recording compression command is sent to the target circuit breaker terminal via a high-priority communication channel, and the pre-processed fault feature vector after edge processing is received, including: Transmit fault recording compression instructions carrying compression format identifiers to the target circuit breaker terminal through the established high-priority communication channel. The target circuit breaker terminal performs format conversion processing on the original fault recording data according to the compression format identifier; The target circuit breaker terminal performs feature extraction calculations on the format-converted fault recording data to generate a fault feature vector. The target circuit breaker terminal encapsulates the fault feature vector into a data packet; Receive data packets carrying fault feature vectors returned by the target circuit breaker terminal through a high-priority communication channel; Parse data packets to extract fault feature vectors after edge preprocessing.

6. The modular reclosing circuit breaker protection system based on intelligent electrical cloud collaboration according to claim 5, characterized in that, Based on fault feature vectors, protection strategy optimization is performed within the released resources, reclosing parameters are generated and sent to the target circuit breaker terminal for execution via a high-priority communication channel, including: Input the fault feature vector into the preset protection action rule base for pattern matching; When a match is successful, the corresponding reclosing parameters are output directly. The transient stability simulation calculation module is started when matching fails. In the transient stability simulation calculation module, an equivalent circuit model of the protection area where the target circuit breaker is located is established; Inject the current and voltage quantities corresponding to the fault feature vector into the equivalent circuit model; Solve for the dynamic response curve of the equivalent circuit model within a preset time window; The optimal reclosing delay parameters are calculated based on the zero-crossing time difference of the dynamic response curve. Encapsulate the reclosing parameters or the optimal reclosing delay parameters into control commands; Control commands are transmitted to the target circuit breaker terminal via a high-priority communication channel; The target circuit breaker terminal parses the control command and executes the reclosing operation.

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