A wind turbine generator safe operation regulation system

Abstract

The present application relates to the technical field of operation regulation, in particular to a wind turbine safety operation regulation system, the system comprising a state sensing module, a fault coupling identification module, a state transition control module, a regulation strategy screening module and an interface execution isolation module. The present application forms a transition path sequence through the historical operation state label and state transition characteristic extraction, realizes fine control of the state transition mechanism, matches and compares the target parameter interval in the process of screening the control instruction, avoids the regulation action incompatible with the current working condition, determines the risk event and sets the interface permission isolation strategy before the instruction execution, can improve the fault identification accuracy and response pertinence, effectively avoid the execution abnormality of the regulation instruction caused by the sudden working condition, and improve the safety robustness of the wind turbine whole cycle operation and the real-time closed-loop consistency of the regulation effect.

Description

Technical Field

[0001] This invention relates to the field of operation control technology, and in particular to a wind turbine safe operation control system. Background Technology

[0002] Operation and control technology is a core component of the wind power technology system, involving the control and management of wind turbines during operation, including status monitoring, power output management, energy conversion efficiency adjustment, load allocation, and abnormal condition identification. This technology encompasses real-time status monitoring of wind turbines, optimization of operating parameters, regulation of power output stability, grid-connected operation coordination, and fault detection and diagnosis strategies. Its aim is to ensure efficient, safe, and stable operation of wind turbines under complex environments such as wind speed fluctuations and grid disturbances. Operation and control technology typically relies on wind farm SCADA systems, wind resource assessment models, power prediction models, and grid interaction control algorithms, emphasizing data interoperability and joint decision-making mechanisms among multiple systems to improve the overall economic efficiency and reliability of the wind power system.

[0003] The wind turbine safe operation control system is an integrated system for the safe control and dynamic adjustment of wind turbines. Its main purpose is to collect and analyze parameters such as wind speed, current, voltage, rotational speed, mechanical load, and vibration to achieve real-time identification, risk assessment, and control response of the wind turbine's operating status. The system aims to prevent wind turbines from experiencing reduced operating efficiency or safety accidents due to abnormal operating conditions, thereby ensuring the stability and lifespan of wind power equipment, while also improving the grid connection quality and power generation efficiency of wind farms.

[0004] Traditional control systems lack mechanisms for extracting periodic trend structures and determining combined changes in parameter fluctuation trend identification and cross-parameter coupled state identification. This makes it difficult to cope with the multi-parameter linkage effects caused by sudden changes in operating conditions. In the fault identification stage, they rely solely on single-point threshold judgment or static indicator warnings, resulting in insufficient accuracy in identifying complex fault characteristics. In terms of state control, they have not established clear state transition paths and response sequences, and rely solely on the current state to execute control commands. This can easily lead to state jumps and loss of control or time delays in the action of control commands, causing problems such as power fluctuations and electrical load over-limits. These control defects are more likely to be exposed, especially during rapid switching of grid-connected operating conditions or under extreme weather conditions. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a wind turbine safe operation control system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a wind turbine safe operation control system, the system comprising:

[0007] The state perception module acquires the operating parameters collected by the SCADA system in the wind turbine, performs single-cycle difference on the joint trend sequence of current, temperature rise and output power, determines whether the fluctuation direction has continuously reversed within three cycles and is accompanied by the maximum difference exceeding the single-cycle change threshold, and generates a set of operating state parameter fluctuation characteristics.

[0008] Based on the set of operating parameters fluctuation features, the fault coupling identification module determines whether there is a combined coupling difference that exceeds the set fault coupling critical threshold, marks the corresponding operating condition node as a high fault coupling point, and obtains the fault coupling node location information.

[0009] Based on the fault coupling node location information, the state transition control module extracts the historical command response cycle, state switching rate and average running state dwell time between state pairs, calculates whether the migration association value exceeds the state transition trigger benchmark value, sets the state pair as the path to be transferred, and generates a state transition path identifier sequence.

[0010] The control strategy filtering module obtains the instruction scheme set bound to the endpoint state based on the state transition path identifier sequence, determines whether there are any conflicts between the current running parameters and the instruction requirements, removes control actions with mismatched parameters, and generates a control scheme execution list.

[0011] The present invention improves upon this invention by including the following: the set of operating parameters fluctuation features includes statistics on the difference in wind turbine rotation period, samples of output power variation rate, and temperature rise time series fluctuation indicators; the fault coupling node location information includes high-risk state combination point identifiers, parameter coupling strength sorting labels, and state label indexes within the combination interval; the state transition path identifier sequence specifically includes a set of migration state chain numbers, a set of state association probability sequences, and an index table pointing to operating state transition paths; and the control scheme execution list includes a set of valid instruction codes, parameter matching success instruction identifiers, and instruction path numbers corresponding to state targets.

[0012] The present invention is improved in that the state sensing module includes:

[0013] The data acquisition submodule acquires the operating parameters collected by the SCADA system in the wind turbine, including rotor speed, current value, voltage value, temperature rise value and output power value. It monitors the speed data of the rotor blade root sensor, the voltage data of the generator bus voltage node, and the power output data of the pitch system power channel. It calls the measurement time series and establishes a basic data matrix to obtain basic information on operating parameters.

[0014] Based on the aforementioned basic information of operating parameters, the slope extraction submodule extracts three sets of sequences: current, temperature rise, and output power. It calculates the average slope change value of the sequences in adjacent time periods, extracts the difference sample between the current and previous cycles from the single-cycle difference, and calculates the power disturbance response degree by combining it with the standard time interval of the current measurement cycle. It then filters samples whose disturbance response degree exceeds the threshold range, marks slope anomalies, and obtains the slope mutation screening results.

[0015] Based on the slope change filtering results, the fluctuation identification submodule determines whether there is a direction reversal signal within three consecutive cycles in the current, temperature rise and output power sequences, identifies the sample number corresponding to the maximum fluctuation value, filters the time window range, and calculates the fluctuation range by combining the difference between the maximum value in the difference sample and the average fluctuation threshold of the cycle, and generates the operating state parameter fluctuation feature set.

[0016] The present invention is improved in that the fault coupling identification module includes:

[0017] Based on the set of operating parameters fluctuation characteristics, the parameter pairing submodule combines three sets of parameter pairs according to the rate of change of rotational speed, rate of change of electromagnetic torque, voltage drop gradient, current response slope, temperature rise increment, and spindle load change. These pairs are then classified into three types of parameter pairing forms according to structural coupling relationships: speed-torque, voltage-current, and temperature rise-load. A pairing matrix is ​​established, and the time synchronization interval value within the current measurement cycle is called to generate parameter combination pairing information.

[0018] The difference calculation submodule constructs a slope change vector based on the time step difference within the measurement period according to the parameter combination pairing information, calculates and obtains the coupling deviation coefficient between combinations, sorts each group of coupling deviation coefficients, extracts combinations that are higher than the set coupling critical threshold, and generates a high deviation combination sequence.

[0019] The coupling positioning submodule calls the high deviation combination sequence, identifies the corresponding operating condition node number, determines whether the node has historical trend data of parameter slope change within a continuous period, if so, marks the node as a high-risk coupling point and adds it to the positioning list, establishes the arrangement order information of the coupling combination contained in each node, and generates fault coupling node positioning information.

[0020] The present invention is improved in that the state transition control module includes:

[0021] The state pair identification submodule extracts the operating state label of the current wind turbine under the high coupling node based on the fault coupling node location information, cross-compares it with the label value in the state label mapping set, calls the adjacency matrix path set between labels, filters the data pair set with associated edge weights, and obtains the label adjacency state pair set.

[0022] The migration determination submodule extracts the average value of the instruction response cycle, state switching rate and running state dwell time corresponding to the state pair based on the set of adjacent state pairs of the label, and obtains the current wind speed fluctuation amplitude and wind turbine torque response time as superposition factors to calculate the migration intensity value of the state pair. It then determines whether the migration intensity value exceeds the state transition trigger benchmark value. If it does, the state pair is marked as a path to be transferred, and a migration intensity screening result is generated.

[0023] The path construction submodule, based on the migration intensity filtering results, calls the existing target state number sequence in the state label path dictionary, rearranges the node index order in the target state sequence, connects the path identifier set between the state label and the target state node, establishes the label mapping information of the target state path, and generates the state transition path identifier sequence.

[0024] The present invention is improved in that the regulation strategy screening module includes:

[0025] The instruction extraction submodule obtains the state transition path identifier sequence, calls the policy library instruction index table corresponding to the endpoint state number, filters the control instruction entries bound to the current node, extracts the action type, applicable state number and control target parameter set corresponding to each instruction, and generates a target instruction index set.

[0026] The parameter verification submodule, based on the target instruction index set, calls the current, wind turbine speed change duration and winding temperature rise limit required by each instruction, and determines whether each operating value is within the threshold range required by the instruction. It then filters out valid instruction items that meet the constraints and obtains the parameter adaptation filtering results.

[0027] The channel filtering submodule adapts the filtering results based on the parameters, matches the executable channel number in the control path mapping table according to the valid instruction item, determines whether the channel is in an available state and has not triggered the protection restriction logic, removes channel items with action conflicts or execution path conflicts, and generates a control scheme execution list.

[0028] The present invention has an improvement, wherein the system further includes:

[0029] The interface execution isolation module determines whether there is an abnormal event where the voltage drop continuously decreases within the instruction cycle and is accompanied by a negative current jump exceeding the short-term drop threshold, based on the control scheme execution list. If the event is met, the interface issuing permission of the corresponding control instruction is frozen and the interface port status is recorded to obtain the control command execution isolation flag.

[0030] The control command execution isolation marker specifically refers to the interface channel freeze number, the position in the control command waiting list, and the fault status identification label.

[0031] The present invention is improved in that the interface execution isolation module includes:

[0032] The signal extraction submodule, based on the control scheme execution list, calls the bus voltage jump value, current negative slope time slice distribution, and wind turbine speed instantaneous response state corresponding to each channel in the controller according to the execution channel number of the control command, extracts the sampling sequence according to the channel period, constructs the parameter matrix, and generates control signal monitoring information;

[0033] Based on the control signal monitoring information, the anomaly identification submodule determines whether there is a voltage value decreasing trend at two or more consecutive time points in each record, and whether it is accompanied by a current jump amplitude greater than the short-term drop threshold. It then filters the set of anomaly channel numbers to obtain the anomaly channel index sequence.

[0034] The permission freeze submodule calls the abnormal channel index sequence, locates the current status in the interface management unit according to the control instruction number corresponding to the marked channel, determines whether the status is in the execution pre-queue, and if so, stops the instruction issuance and records the status label and channel status at the time of freeze, establishes a control channel freeze registration table, and generates a control command execution isolation mark.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0036] In this invention, by performing periodic difference and trend slope reversal identification on the time-series operating parameters collected by the SCADA system, a fluctuation set containing the joint variation characteristics of wind turbine, electrical, and thermal loads is constructed. Based on this feature set, a slope difference normalization sorting method is introduced to identify the combined coupling relationship between parameters, and potential high-coupling fault nodes in the operating conditions are identified accordingly. By combining historical operating state tags and state transition characteristics, a migration path sequence is extracted to achieve refined control of the state transition mechanism. In the process of screening control commands, the target parameter range is matched and compared to avoid control actions that are incompatible with the current operating conditions. Before the command is executed, the risk event is judged by combining the transient electrical parameter change trend and setting the interface permission isolation strategy. This can improve the accuracy of fault identification and the specificity of response, while effectively avoiding execution anomalies of control commands caused by sudden operating conditions, thereby improving the safety robustness of the wind turbine's full-cycle operation and the real-time closed-loop consistency of the control effect. Attached Figure Description

[0037] Figure 1 This is a system flowchart of the present invention;

[0038] Figure 2 This is a flowchart of the state sensing module of the present invention;

[0039] Figure 3 This is a flowchart of the fault coupling identification module of the present invention;

[0040] Figure 4 This is a flowchart of the state transition control module of the present invention;

[0041] Figure 5 This is a flowchart of the control strategy screening module of the present invention;

[0042] Figure 6 This is a flowchart of the interface execution isolation module of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0044] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0045] Please see Figure 1 The present invention provides a technical solution: a wind turbine safe operation control system, the system including a state perception module, a fault coupling identification module, a state transition control module, a control strategy screening module and an interface execution isolation module;

[0046] The state perception module acquires the operating parameters collected by the SCADA system in the wind turbine, including rotor speed, current value, voltage value, temperature rise value and output power value. Based on the time series measurement results of the rotor blade root sensor, generator bus voltage node and pitch system power channel, it extracts the fluctuation slope change of adjacent time periods, performs single-cycle difference on the joint trend sequence of current, temperature rise and output power, determines whether the fluctuation direction has continuously reversed within three cycles and is accompanied by the maximum difference exceeding the single-cycle change threshold, and generates a set of operating state parameter fluctuation features.

[0047] The fault coupling identification module is based on the operating state parameter fluctuation feature set. It calls three sets of parameters: the rate of change of rotational speed and the rate of change of electromagnetic torque, the voltage drop gradient and the current response slope, and the temperature rise increment and the spindle load change. It sorts the parameters by the normalized value of the slope difference between the two parameter combinations to determine whether there is a combination coupling difference that exceeds the set fault coupling critical threshold. If there is, the corresponding operating condition node is marked as a high fault coupling point, and the combination coupling order of the corresponding point in the parameter space is established to obtain the fault coupling node location information.

[0048] The state transition control module, based on the fault coupling node location information, calls the current wind turbine's operating state label and adjacent state path set, extracts the state pairs corresponding to the fault highly coupled node identifiers, performs state label interactive queries, determines whether a transition critical pair is formed, extracts the historical command response cycle, state switching rate and operating state dwell time average between state pairs, calculates whether the transition correlation value exceeds the state transition trigger benchmark value, if it exceeds, sets the state pair as the path to be transferred, constructs a path identifier chain pointing to the target state, and generates a state transition path identifier sequence;

[0049] The control strategy screening module obtains the instruction scheme set bound to the final state based on the state transition path identifier sequence, and matches the required current peak range, wind turbine deceleration time and winding temperature rise limit corresponding to the control instruction. It determines whether there are any conflicts between the current operating parameters and the instruction requirements. If there are no conflicts, the execution channel matching screening is performed on the scheme set to remove control actions with mismatched parameters and generate a control scheme execution list.

[0050] The interface execution isolation module calls the bus voltage jump value, current negative slope time slice distribution and wind turbine speed instantaneous response status within the execution cycle of the controller according to the control scheme execution list. It determines whether there is an abnormal event where the voltage drop continuously decreases within the command cycle and is accompanied by a current negative jump exceeding the short-term drop threshold. If the condition is met, the interface issuing permission of the corresponding control command is frozen and the interface port status is recorded to obtain the control command execution isolation flag.

[0051] The set of operational parameter fluctuation features includes statistics on the difference in wind turbine rotation period, samples of output power change rate, and temperature rise time series fluctuation indicators. The fault coupling node location information includes high-risk state combination point identifiers, parameter coupling strength sorting labels, and state label indexes within the combination interval. The state transition path identifier sequence specifically includes a set of migration state chain numbers, a set of state association probability order sets, and an index table pointing to operational state transition paths. The control scheme execution list includes a set of valid instruction codes, parameter matching success instruction identifiers, and instruction path numbers corresponding to state targets. The control command execution isolation marker specifically refers to the interface channel freeze number, the position of the control instruction waiting list, and the fault state identification label.

[0052] Please see Figure 2The state awareness module includes:

[0053] The data acquisition submodule acquires the operating parameters collected by the SCADA system in the wind turbine, including rotor speed, current value, voltage value, temperature rise value and output power value. It monitors the speed data of the rotor blade root sensor, the voltage data of the generator bus voltage node, and the power output data of the pitch system power channel. It calls the measurement time series and establishes a basic data matrix to obtain basic information on operating parameters.

[0054] The system acquires wind turbine rotor speed, current, voltage, temperature rise, and output power values ​​from the SCADA system. The acquisition cycle is set to 10 seconds per complete sampling cycle. A total of 60 sets of speed data points are acquired using the rotor blade root sensor. The speed data is recorded in r / min. Within each sampling cycle, a single set of data is extracted at the second level to form a speed sequence. The generator bus voltage is detected through bus measurement points, with a set range of 0V to 1200V. In actual sampling, the detection range commonly falls between 620V and 740V. 60 data points are acquired per cycle, and the voltage value is... Data acquisition and pairing are performed using a 10ms synchronization alignment timestamp. The power output of the pitch system's power channels is measured in kW, and the maximum value is set to 2100kW based on wind speed monitoring values. In this example, 54 power output points are collected. Some missing data segments due to sudden wind speed drops need to be marked. During the data alignment process, the data collected from the three channels are aligned with the main control system timestamp as the reference, constructing a unified 60×5-dimensional basic data matrix. Each column represents speed, current, voltage, temperature rise, and power, respectively. To illustrate the validity of the example, data from one measurement cycle is selected as follows:

[0055] Table 1. Monitoring Parameters of Wind Turbine Units

[0056]

[0057] As shown in Table 1, the rotational speed shows a steady upward trend, the voltage remains above 700V, and the power output increases synchronously. After completing the synchronization of the three channels, a basic data matrix is ​​constructed to obtain the basic information of the operating parameters.

[0058] The slope extraction submodule extracts three sets of sequences—current, temperature rise, and output power—based on basic operating parameter information. It calculates the average slope change of these sequences over adjacent time periods, extracts the difference between the current and previous cycles from the single-cycle difference, and combines this with the standard time interval of the current measurement cycle using the following formula:

[0059] ;

[0060] The power disturbance response is calculated and obtained. Samples with disturbance response exceeding the threshold range are screened and slope anomalies are marked to obtain slope mutation screening results.

[0061] in, Represents the electrical disturbance response. This represents the normalized value of temperature rise within the current period. This represents the normalized value of the temperature rise in the previous period. This represents the normalized output power value during the current measurement period. This represents the normalized value of the average duration of current change. This represents the wind speed variation intensity coefficient, used to reflect the level of background meteorological excitation during disturbances. Its value is derived from the ratio of the maximum to the minimum wind speed within the measurement period. This represents the normalized voltage value for the current cycle. This represents the normalized voltage value of the previous cycle. This is a meteorological background excitation correction factor used to improve the sensitivity of the calculation to sudden wind speed disturbances;

[0062] Based on the basic operating parameters, three sequences are extracted: current, temperature rise, and output power. Each sequence is 60 units in length. First, the length of the sequence is calculated. Item and the The difference between the terms is divided by the 1-second interval between the two points to obtain the average slope change value sequence. After obtaining the slope difference value sequence for the current period, it is subtracted from the corresponding term of the slope sequence of the previous period to calculate the difference sample. Taking output power as an example, the output power at the 20th second and the 19th second are 1542kW and 1534kW respectively, with a slope of 8kW / s. This point is substituted into the difference sequence, and then combined with the standard time interval of 10 seconds for measurement period to perform unit conversion, so that the slope difference value has a unified time base. Then, the wind speed variation intensity parameter is called. The value is obtained from the ratio of the maximum wind speed of 16.2 m / s to the minimum wind speed of 13.4 m / s:

[0063] ;

[0064] Substitute into the formula to calculate the disturbance response:

[0065] ;

[0066] The calculation logic of this formula is as follows: temperature rise change value This indicates the intensity of thermal disturbance to the equipment, and is a power-current-time composite factor. The combined factor is used to construct a dynamic comprehensive factor for load, which is then combined with the wind speed disturbance excitation factor. The amplitude is adjusted, and finally the square root of the voltage difference is used. As the denominator for disturbance suppression, it reflects the stability characteristics of the system itself. The formula comprehensively reflects the system's state sensitivity under the influence of multiple sources of disturbance.

[0067] The parameters are explained below:

[0068] Power disturbance response;

[0069] , The normalized temperature rise values ​​are derived from the actual temperature rise values ​​of 63.5℃ and 54.6℃, respectively, and normalized to the rated upper limit of 120℃.

[0070] Normalized output power, the original value is 1480kW, normalized to the maximum of 2100kW;

[0071] : Normalized value of average current change time, the original value is 6.8s, normalized to a period of 10s;

[0072] Wind speed fluctuation intensity, calculated based on the ratio of the maximum to the minimum wind speed change;

[0073] , : Voltage normalization value, the original values ​​are 744V and 780V, normalized to 1200V;

[0074] The threshold for slope mutation screening was set at 0.065. This value was derived from the lower bound of the 95% confidence interval of the slope disturbance response distribution in 2000 wind power operation samples. The test data showed that most non-abnormal sample values ​​were concentrated between 0.02 and 0.06. Therefore, the upper limit was set at 0.065 as the dynamic anomaly standard to avoid missing edge state samples. The sample disturbance result was 0.0775, which clearly exceeded the threshold. Therefore, it was judged as an abnormal sample, and the slope mutation screening result was obtained.

[0075] The fluctuation identification submodule determines whether a direction reversal signal appears in the current, temperature rise, and output power sequences within three consecutive cycles based on the slope change filtering results. It identifies the sample number corresponding to the maximum fluctuation value and filters the time window range. Combining the difference between the maximum value in the difference sample and the average fluctuation threshold of the cycle, it calculates the fluctuation range and generates a set of fluctuation features of the operating parameters.

[0076] Based on the sample numbers marked as anomalous in the slope mutation screening results, the original data segments of these samples in the current, temperature rise, and output power sequences are retrieved. A five-point window is constructed, extending two time points forward and two backward from each anomalous point. It is then determined whether the sign change sequence of the corresponding slope within the window exhibits an alternating positive and negative reversal structure over three consecutive periods. If this structure is satisfied, it is recorded as a direction reversal signal. Simultaneously, the fluctuation range is determined centered on the reversal point, and the difference between the maximum and minimum values ​​of each parameter is extracted. For example, in a power sequence, the maximum power in a certain window is 1635kW. The minimum value is 1550kW, so the range is 85kW. The average fluctuation threshold of the cycle is set to 75kW. The setting is calculated with reference to the average effective power fluctuation amplitude within 20 operating cycles. The average value is 73.4kW, which is rounded to 75kW as the discrimination threshold. The sample range of 85kW has exceeded the threshold and meets the fluctuation change condition. Therefore, this point is confirmed as the main trigger point of the fluctuation. Its index, timestamp and parameter combination are marked into the feature set. Finally, all sampling segments that meet the three-cycle reversal condition and fluctuation amplitude condition are counted to generate the operating state parameter fluctuation feature set.

[0077] Please see Figure 3 The fault coupling identification module includes:

[0078] The parameter pairing submodule is based on the operating state parameter fluctuation feature set. According to the speed change rate, electromagnetic torque change rate, voltage drop gradient, current response slope, temperature rise increment and spindle load change, it combines three sets of parameter pairs and classifies them into three types of parameter pairing forms according to the structural coupling relationship: speed-torque, voltage-current and temperature rise-load. It establishes a pairing matrix and calls the time synchronization interval value in the current measurement cycle to generate parameter combination pairing information.

[0079] Six types of parameters were acquired from the set of operating state parameter fluctuation characteristics: speed change rate, electromagnetic torque change rate, voltage drop gradient, current response slope, temperature rise increment, and spindle load change. Sixty sets of data were extracted from each parameter within each 10-second sampling period. After normalization, the normalized value range was mapped to [0,1] for subsequent combination calculations. Based on a predefined structural coupling method, the parameters were divided into three combinations: speed and electromagnetic torque, voltage and current, and temperature rise and spindle load, corresponding to the rotating power chain, electrical drive chain, and thermo-mechanical coupling chain, respectively. This combination logic originates from the unit's power and stress transmission path, from spindle speed to generator torque, electrical side voltage driving current response, and the temperature rise process reflecting the energy evolution of load and structure interaction. Three sets of combinations are established into two-dimensional arrays. The normalized values ​​of the two parameters at each time point are arranged side by side to construct a 60-row × 2-column data pair array. Due to the signal acquisition delay and synchronization error of different wind turbine systems, a system synchronization mechanism needs to be introduced. This system sets the synchronization window to ±0.5s, that is, based on the median time point, the average value of the two parameter data pairs within 0.5s before and after is calculated to filter out instantaneous interference and timing deviation. For example, at the 12th second, the normalized voltage value is 0.62 and the current value is 0.57. The data before and after are 0.63, 0.58 and 0.61, 0.56, respectively. The average paired values ​​are 0.62 and 0.57, which constitute the voltage-current combination data point at this time point. Thus, a combination sequence is constructed to generate parameter combination pairing information.

[0080] The difference calculation submodule constructs a slope change vector based on the time step difference within the measurement period, according to the parameter combination pairing information, using the formula:

[0081] ;

[0082] The coupling deviation coefficient between combinations is obtained through calculation. Each group of coupling deviation coefficients is sorted, and combinations with a deviation higher than the set coupling critical threshold are extracted to generate a high deviation combination sequence.

[0083] in, This represents the combined coupling deviation coefficient. This represents the change in slope per unit time for the first term in the parameter pair. This represents the change in slope per unit time of the second term in the parameter pair. This represents the normalized value of wind speed fluctuation amplitude. This represents the normalized value of the wind turbine acceleration. This represents the normalized value of the maximum oscillation frequency in the current period. This represents the normalized value of the periodic amplitude of temperature rise changes;

[0084] Based on the parameter pairing information, extract the normalized parameter sequence of each pairing data, and perform a difference operation at adjacent time points to obtain the parameter items. and That is, the slope changes of two items per unit time, and then the absolute value of their difference is calculated to construct a coupling difference index. The representative periodic samples are as follows:

[0085] Table 2 Example table of parameters for slope difference

[0086]

[0087] As shown in Table 2, the difference reaches 0.016 in the combination of 20 seconds and 30 seconds, which is considered a relatively high deviation. This difference is then multiplied by the wind speed fluctuation range. With wind turbine acceleration The sum of these, in this period The result was obtained by normalizing the maximum wind speed of 15.8 m / s and the minimum wind speed of 13.1 m / s. The maximum vibration frequency in the denominator is obtained by normalizing the calculation based on the wind turbine acceleration. Normalized from the current cycle principal shaft vibration frequency, the temperature rise change period amplitude is... Substituting into the formula, we get:

[0088] ;

[0089] The calculation logic of this formula is as follows: In the molecule Reflects the magnitude of dynamic deviation between parameters, and the disturbance excitation factor After multiplication, we obtain the excitation amplification term, and the denominator part... The system damping correction term reflects the system's own oscillation characteristics and thermal buffering capacity. The overall structure reflects the degree of coupling distortion under strong excitation and weak response conditions. The larger the calculation result, the more severe the imbalance of the coupling structure. The coupling critical threshold is set to 0.0062. Based on the coupling index statistics of the 80th quantile in 500 samples, the result 0.0076 is greater than the threshold and is marked as a high-deviation coupling combination. It is added to the high-deviation combination sequence to obtain the high-deviation combination sequence.

[0090] The coupling positioning submodule calls the high deviation combination sequence, identifies the corresponding operating condition node number, determines whether the node has historical trend data of parameter slope change within a continuous period, if so, marks the node as a high-risk coupling point and adds it to the positioning list, establishes the arrangement order information of the coupling combination contained in each node, and generates fault coupling node positioning information.

[0091] The parameter pair index information in the high deviation combination sequence is called and mapped to the running status node number in the structural condition record table of the system. For example, the node number corresponding to the speed-torque combination is N45. The slope historical change trend sequence is checked in this node. This sequence indicates whether there is a record of slope change direction reversal within three consecutive cycles from the current cycle to the previous five cycles. The judgment criteria are the same as those for slope change. It is required that the slope polarity of the difference between the previous and next cycles reverses more than twice, and at least one slope difference is greater than 0.02. For example, if the record in node N45 is positive-negative-positive and the corresponding differences are 0.015, 0.027, and 0.022 respectively, then the reversal + strength condition is met, the node is confirmed to be abnormal, and it is marked as a high-risk coupling point. The three sets of parameters associated with its structure are sorted according to the degree of deviation. The sorting order is recorded as voltage-current, temperature rise-load, and speed-torque. The sorting information is written into the location list to form a node-corresponding structural sequence mapping table. Finally, the index binding relationship between the operating condition node and the deviation source is established, and the fault coupling node location information is generated.

[0092] Please see Figure 4 The state transition control module includes:

[0093] The state pair identification submodule extracts the operating state labels of the wind turbine under the high coupling node based on the fault coupling node location information, cross-compares them with the label values ​​in the state label mapping set, calls the adjacency matrix path set between labels, filters the data pair set with associated edge weights, and obtains the label adjacency state pair set.

[0094] Retrieve the index information of highly coupled nodes recorded in the fault-coupled node location information, for example, the node number is set to This node is marked as an abnormally high-risk operating condition area within the current measurement period. Based on the current wind turbine status monitoring system, the real-time operating status tags recorded under this node are extracted. This label represents the status identification number of the wind turbine under multiple operating indicators (current, wind speed, speed, etc.). A pre-stored status label mapping set is invoked; the mapping set contains a total of [number missing] labels. , will the current tag With the rest The status labels are respectively composed of State pair, where This process iterates through and compares all possible label combinations, and then calls the state label adjacency matrix in the system. The matrix is dimension, any element Indicates status label and The adjacency weights between them. If there exist... This means that a reachable path exists between the two states, indicating a correlation. Given the source state label, query the corresponding state label with a non-zero weight in the adjacent path, such as... , , Their adjacency weights are respectively , , All of these values ​​are higher than the typical distinguishing lower limit of 0.10 for unrelated states. The set of state pairs with association weights is selected as the label adjacency state pair set, and its corresponding label index and adjacency matrix weights are recorded. Finally, this set will serve as the input data source for subsequent state transition evaluation.

[0095] The migration determination submodule extracts the average value of the instruction response cycle, state switching rate, and running state dwell time corresponding to the tag adjacency state pair based on the set of tag adjacency state pairs. It also obtains the current wind speed fluctuation amplitude and the wind turbine torque response time as superposition factors, using the formula:

[0096] ;

[0097] The migration strength value of the state pair is obtained by calculation. It is determined whether the migration strength value exceeds the state transition triggering benchmark value. If it exceeds the benchmark value, the state pair is marked as a path to be transferred and the migration strength filtering result is generated.

[0098] in, Indicates the migration intensity value. This represents the normalized value of the instruction response cycle. This represents the normalized value of the state transition rate. This represents the normalized average value of the runtime dwell time. This represents the normalized value of wind speed fluctuation amplitude. This represents the normalized value of the wind turbine torque slope. This represents the normalized difference in peak speed. This represents the normalized standard deviation of the axial vibration frequency of the unit's main shaft. This represents the weighted adjustment term for the uncertainty of state transition caused by changes in vibration amplitude;

[0099] Based on the set of label adjacency state pairs, for each state pair in the set... Extract key metrics from the historical state transition process, including:

[0100] The normalized value of the instruction response cycle is denoted as This represents the average time required for the system to respond after a control command is issued;

[0101] The normalized value of the state transition rate is denoted as This indicates the frequency of status label switching per unit of time;

[0102] The normalized average of the current state dwell time is denoted as , which represents the average duration for which the unit remains unchanged under the current state.

[0103] In addition, by accessing the wind turbine monitoring data for the current period, the following four disturbance factors are extracted:

[0104] Normalized value of wind speed fluctuation That is, the difference between the maximum and minimum wind speeds within the measurement period divided by the rated wind speed;

[0105] Normalized value of wind turbine torque slope This is used to reflect load disturbances when the wind turbine rotates;

[0106] Normalized difference of peak speed This refers to the difference between the maximum value and the average value of the cycle in the rotational speed data.

[0107] Normalized standard deviation of spindle axial vibration frequency It is used to measure the degree of instability of the dynamic response of the unit structure.

[0108] Substitute the above-mentioned participants into the formula:

[0109] ;

[0110] The first part of the formula The ratio of state reactivity, molecular part Reflecting state activity (i.e., the sum of control response and state transition indicators), the denominator part Introducing a stability factor for the current state, 1 represents the balance term to avoid a zero denominator; the square root after the multiplication sign expresses the cumulative disturbance term, with the internal term representing wind speed disturbance. Peak speed Adjustment term for uncertainty with vibration frequency The sum of the three items.

[0111] Actual calculations were performed using sample data (from real-time system records):

[0112] , , ;

[0113] , , , ;

[0114] The calculation is as follows:

[0115] ;

[0116] The numerical result indicates a migration strength of 0.2645 between state pairs, representing the tendency of the pair to migrate from the previous state to the next state under the current disturbance. Based on the state transition trigger baseline value of 0.21 set in the wind turbine operating data (derived from the average migration strength of the top 20% of samples with the highest migration rates across all state pairs, ensuring sufficient sensitivity and stability), because... Therefore, the state is... Marked as a path to be migrated, it is included in the migration intensity screening results.

[0117] The path construction submodule, based on the migration intensity filtering results, calls the existing target state number sequence in the state label path dictionary, rearranges the node index order in the target state sequence, connects the path identifier set between the state label and the target state node, establishes the label mapping information of the target state path, and generates the state transition path identifier sequence.

[0118] Based on the marked status in the migration strength screening results Enter the wind turbine status label path dictionary and search for the target label. All corresponding subsequent target state nodes. Based on the historical switching path, the target sequence is: The system internally stores the priority scores for state jumps between each path, such as transition stability scores. They are respectively , , Based on this, the path priorities are reordered as follows: .

[0119] The set of path identifiers from the call status label to the target node, corresponding to the following path numbers: , , , , connect to main tag Generate a new path chain from the above path sequence: And record the corresponding path sequence as Simultaneously, a mapping relationship is established between the nodes contained in the path and the path number, and the final output is a sequence of state transition path identifiers. This sequence serves as the valid path chain for the controller state machine to execute transitions and is read by the system control instruction module at the execution layer.

[0120] Please see Figure 5 The regulation strategy screening module includes:

[0121] The instruction extraction submodule obtains the state transition path identifier sequence, calls the policy library instruction index table corresponding to the endpoint state number, filters the control instruction entries bound to the current node, extracts the action type, applicable state number and control target parameter set corresponding to each instruction, and generates a target instruction index set.

[0122] Obtain the endpoint state number in the state transition path identifier sequence. After parsing the number, the current wind turbine is located at the end of its operating cycle. For example, the corresponding number "S17" indicates that it has entered the high load steady-state range. Call the instruction entry recorded in the instruction index table of the strategy library for this number. Extract the action type bound to the control instruction through structural traversal, such as "power reduction control" or "winding cooling control". Then extract the applicable state number bound to each instruction, such as "S17, S18" and its corresponding control target parameter set, such as the current peak limit of 480A, the wind turbine deceleration time of 6.2 seconds, and the winding temperature rise not exceeding 65℃. In this process, a dictionary-style access strategy should be adopted for the bound structure in the strategy library to avoid redundant extraction caused by instruction reordering. The instruction tag index sequence is established by comparing the extraction process and saved to the target instruction index set. As shown in Table 3, the strategy library instruction item data under the current endpoint state number "17" is listed.

[0123] Table 3. Policy Library Instruction Item Data Table

[0124]

[0125] As shown in Table 3, the current state "S17" corresponds to three policy instructions. Each instruction has a unique instruction number, control action type, adaptation state number and control target parameter, forming a target instruction index set.

[0126] The parameter verification submodule is based on the target instruction index set. According to the current peak range, wind turbine deceleration time and winding temperature rise limit required by each instruction, it calls the operating current, wind turbine speed change duration and winding temperature acquisition sequence in the current measurement cycle, determines whether each operating value is within the threshold range required by the instruction, filters the valid instruction items that meet the constraints, and obtains the parameter adaptation filtering results.

[0127] Based on the target instruction index set, the control target parameter items of each control instruction are parsed sequentially, and the peak current range, rotor deceleration time, and winding temperature rise limit are extracted. The thresholds are set as ±3% of the specified values ​​in the instruction. That is, the thresholds corresponding to instruction D_021 are the peak current range of 466A to 494A, rotor deceleration time of 6.01-6.39s, and winding temperature rise limit of 63.05~66.95℃. The current measurement sequence that has been synchronously acquired in the current measurement cycle is called, such as [488,489,492]A, the speed change duration sequence such as [6.15,6.22,6.28]s, and the winding temperature sequence such as [64.8,65.2,64.9]℃. The three parameters at each time step are judged against their corresponding threshold ranges. If all parameters fall into the range at a certain moment, it is marked as a valid instruction adaptation point. By counting the cumulative number of valid samples of instruction items higher than three, valid control instructions are filtered to form parameter adaptation filtering results. The above judgment process needs to clarify the method for limiting the floating space of the control target parameters. Here, the floating space of ±3% is based on the redundancy setting standard for the component load capacity during the control strategy setting process. This setting is derived from the preset redundancy tolerance band of the actual measured data of the unit's electrical load capacity, ensuring that the results have quantitative and reproducible characteristics, forming a reusable screening logic.

[0128] The channel filtering submodule, based on the parameter adaptation filtering results, matches the executable channel number in the control path mapping table according to the valid instruction item, determines whether the channel is in an available state and has not triggered the protection restriction logic, removes channel items with action conflicts or execution path conflicts, and generates a control scheme execution list.

[0129] Valid instruction items from the parameter adaptation filtering results, such as D_021 and D_023, are entered into the control path mapping table according to the mapping rules. Their corresponding executable channel numbers are queried; for example, D_021 maps to channel T3, and D_023 maps to channel T4. The current status flag information of the channel is extracted to determine if it is in "running state." The scheduling control log is queried to confirm that no protection logic has been triggered in the last cycle. If the channel status is "disabled" or there is an action occupation record in the previous execution cycle, the channel is marked as having an action conflict and is removed from the available channel set. Finally, all valid instruction items are matched one-to-one with their channel execution status, conflicting items are removed, and a control scheme execution list is generated. In this step, the channel availability status is determined based on the scheduling control identifier field "status." A status value of "1" indicates executable, and "0" indicates disabled. In this round of status determination, only D_021 is retained among the three available instructions, forming a unique valid control instruction scheme, and a channel execution structure index is established.

[0130] Please see Figure 6 The interface execution isolation module includes:

[0131] The signal extraction submodule is based on the control scheme execution list. According to the execution channel number of the control command, it calls the bus voltage jump value, current negative slope time slice distribution and wind turbine speed instantaneous response state corresponding to each channel in the controller, extracts the sampling sequence according to the channel period and constructs the parameter matrix to generate control signal monitoring information.

[0132] Obtain the execution channel numbers of all control commands in the control scheme execution list, extracting numbers such as T5, T7, and T11. Call the signal acquisition unit bound to these channel numbers in the controller to obtain the corresponding bus voltage jump value records, current negative slope time slice sequences, and instantaneous response states of the wind turbine speed at each time point from the data storage area. Construct a set of parameter ternary sequences based on the time point, with a uniform sampling frequency of 10Hz. The extraction period range covers the two most recent complete control cycles, and the length of each cycle is set to 12s. Thus, the sequence length obtained for each channel is 120 data points. Construct a 120×3 dimension data matrix, numbered M_5, M_7, and M_11 according to the channel number, and record the sampling time points and corresponding parameter value sequences in tabular form. The following is the data recorded for channel T5:

[0133] Table 4 Parameter Sampling Record Table for Control Channel T5

[0134]

[0135] As shown in Table 4, after extracting the periodic sequence of each channel, the voltage jump value, current change rate and wind turbine speed at different time points are combined into control signal monitoring information.

[0136] The anomaly identification submodule, based on control signal monitoring information and the periodic sequence of voltage and current, determines whether there are records in each record where the voltage value decreases at two or more consecutive time points and whether the current jump amplitude is greater than the short-term drop threshold. It then filters the set of anomaly channel numbers to obtain the anomaly channel index sequence.

[0137] Based on the control signal monitoring information constructed in paragraph 1, the data matrix corresponding to each channel is traversed sequentially. The voltage jump sequence is processed by directional difference to obtain the voltage difference between each sampling point and the previous sampling point. It is recorded whether there are two or more consecutive differences less than 0 in the sequence, indicating that the voltage is continuously decreasing. At the same time, the negative slope sequence of the current is extracted. The absolute value of each sample value is taken and compared with the short-time drop threshold of 0.12. If any sampling point satisfies the condition of continuous voltage decrease and the corresponding current jump amplitude is greater than 0.12A / s, the channel is marked as an abnormal channel and its channel number is added to the abnormal label list. The threshold 0.12 setting process is as follows: According to the data accuracy set by the controller and the normal noise jitter range of the wind power control system (approximately ±0.05A / s), two times the disturbance redundancy is retained, and 0.05×2+0.02=0.12A / s is calculated as the critical threshold for abnormal identification. By randomly selecting 8 groups of samples under different wind conditions for comparison, it is confirmed that this threshold can cover more than 85% of instantaneous jump behavior and has sufficient engineering reproducibility. On this basis, an abnormal channel index sequence is formed.

[0138] The permission freeze submodule calls the abnormal channel index sequence, locates the current status in the interface management unit according to the control instruction number corresponding to the marked channel, determines whether the status is in the execution pre-queue, and if so, stops the instruction issuance and records the status label and channel status at the time of freeze, establishes a control channel freeze registration table, and generates a control command execution isolation mark.

[0139] The abnormal channel index sequence marked in paragraph 2 is called, and its corresponding control instruction number is extracted. For example, the instruction number corresponding to channel T5 is D_021. The status management table of the interface management module is entered, and the current execution status flag of instruction D_021 is retrieved. If the status field is "pending", it means that it has not yet been sent to the execution register queue. The instruction execution status is immediately changed to "frozen", and the current freeze time tag such as "2025-07-16 10:28:00" and the channel number status is "abnormal blocking" are recorded. The freeze event information is combined into a freeze registration structure and added to the unified freeze registration list. At the same time, according to the controller module marking rules, a unique isolation flag field "ISO_D021" is generated for this instruction, which means that instruction D_021 is isolated and blocked due to the abnormality of channel T5, forming a control command execution isolation flag.

[0140] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A wind turbine safe operation control system, characterized in that, The system includes: The state perception module acquires the operating parameters collected by the SCADA system in the wind turbine, performs single-cycle difference on the joint trend sequence of current, temperature rise and output power, determines whether the fluctuation direction has continuously reversed within three cycles and is accompanied by the maximum difference exceeding the single-cycle change threshold, and generates a set of operating state parameter fluctuation characteristics. Based on the set of operating parameters fluctuation features, the fault coupling identification module determines whether there is a combined coupling difference that exceeds the set fault coupling critical threshold, marks the corresponding operating condition node as a high fault coupling point, and obtains the fault coupling node location information. Based on the fault coupling node location information, the state transition control module extracts the historical command response cycle, state switching rate and average running state dwell time between state pairs, calculates whether the migration association value exceeds the state transition trigger benchmark value, sets the state pair as the path to be transferred, and generates a state transition path identifier sequence. The control strategy filtering module obtains the instruction scheme set bound to the endpoint state based on the state transition path identifier sequence, determines whether there are any conflicts between the current running parameters and the instruction requirements, removes control actions with mismatched parameters, and generates a control scheme execution list.

2. The wind turbine safe operation control system according to claim 1, characterized in that, The set of operational parameter fluctuation features includes statistics on the difference in wind turbine rotation period, samples of output power change rate, and temperature rise time series fluctuation indicators. The fault coupling node location information includes high-risk state combination point identifiers, parameter coupling strength sorting labels, and state label indexes within the combination interval. The state transition path identifier sequence specifically includes a set of migration state chain numbers, a set of state association probability order sets, and an index table pointing to operational state transition paths. The control scheme execution list includes a set of valid instruction codes, parameter matching success instruction identifiers, and instruction path numbers corresponding to state targets.

3. The wind turbine safe operation control system according to claim 2, characterized in that, The state awareness module includes: The data acquisition submodule acquires the operating parameters collected by the SCADA system in the wind turbine, including rotor speed, current value, voltage value, temperature rise value and output power value. It monitors the speed data of the rotor blade root sensor, the voltage data of the generator bus voltage node, and the power output data of the pitch system power channel. It calls the measurement time series and establishes a basic data matrix to obtain basic information on operating parameters. Based on the aforementioned basic information of operating parameters, the slope extraction submodule extracts three sets of sequences: current, temperature rise, and output power. It calculates the average slope change value of the sequences in adjacent time periods, extracts the difference sample between the current and previous cycles from the single-cycle difference, and calculates the power disturbance response degree by combining it with the standard time interval of the current measurement cycle. It then filters samples whose disturbance response degree exceeds the threshold range, marks slope anomalies, and obtains the slope mutation screening results. Based on the slope change filtering results, the fluctuation identification submodule determines whether there is a direction reversal signal within three consecutive cycles in the current, temperature rise and output power sequences, identifies the sample number corresponding to the maximum fluctuation value, filters the time window range, and calculates the fluctuation range by combining the difference between the maximum value in the difference sample and the average fluctuation threshold of the cycle, and generates the operating state parameter fluctuation feature set.

4. The wind turbine safe operation control system according to claim 3, characterized in that, The fault coupling identification module includes: Based on the set of operating parameters fluctuation characteristics, the parameter pairing submodule combines three sets of parameter pairs according to the rate of change of rotational speed, rate of change of electromagnetic torque, voltage drop gradient, current response slope, temperature rise increment, and spindle load change. These pairs are then classified into three types of parameter pairing forms according to structural coupling relationships: speed-torque, voltage-current, and temperature rise-load. A pairing matrix is ​​established, and the time synchronization interval value within the current measurement cycle is called to generate parameter combination pairing information. The difference calculation submodule constructs a slope change vector based on the time step difference within the measurement period according to the parameter combination pairing information, calculates and obtains the coupling deviation coefficient between combinations, sorts each group of coupling deviation coefficients, extracts combinations that are higher than the set coupling critical threshold, and generates a high deviation combination sequence. The coupling positioning submodule calls the high deviation combination sequence, identifies the corresponding operating condition node number, determines whether the node has historical trend data of parameter slope change within a continuous period, if so, marks the node as a high-risk coupling point and adds it to the positioning list, establishes the arrangement order information of the coupling combination contained in each node, and generates fault coupling node positioning information.

5. The wind turbine safe operation control system according to claim 4, characterized in that, The state transition control module includes: The state pair identification submodule extracts the operating state label of the current wind turbine under the high coupling node based on the fault coupling node location information, cross-compares it with the label value in the state label mapping set, calls the adjacency matrix path set between labels, filters the data pair set with associated edge weights, and obtains the label adjacency state pair set. The migration determination submodule extracts the average value of the instruction response cycle, state switching rate and running state dwell time corresponding to the state pair based on the set of adjacent state pairs of the label, and obtains the current wind speed fluctuation amplitude and wind turbine torque response time as superposition factors to calculate the migration intensity value of the state pair. It then determines whether the migration intensity value exceeds the state transition trigger benchmark value. If it does, the state pair is marked as a path to be transferred, and a migration intensity screening result is generated. The path construction submodule, based on the migration intensity filtering results, calls the existing target state number sequence in the state label path dictionary, rearranges the node index order in the target state sequence, connects the path identifier set between the state label and the target state node, establishes the label mapping information of the target state path, and generates the state transition path identifier sequence.

6. The wind turbine safe operation control system according to claim 5, characterized in that, The regulation strategy screening module includes: The instruction extraction submodule obtains the state transition path identifier sequence, calls the policy library instruction index table corresponding to the endpoint state number, filters the control instruction entries bound to the current node, extracts the action type, applicable state number and control target parameter set corresponding to each instruction, and generates a target instruction index set. The parameter verification submodule, based on the target instruction index set, calls the current, wind turbine speed change duration and winding temperature rise limit required by each instruction, and determines whether each operating value is within the threshold range required by the instruction. It then filters out valid instruction items that meet the constraints and obtains the parameter adaptation filtering results. The channel filtering submodule adapts the filtering results based on the parameters, matches the executable channel number in the control path mapping table according to the valid instruction item, determines whether the channel is in an available state and has not triggered the protection restriction logic, removes channel items with action conflicts or execution path conflicts, and generates a control scheme execution list.

7. The wind turbine safe operation control system according to claim 6, characterized in that, The system also includes: The interface execution isolation module determines whether there is an abnormal event where the voltage drop continuously decreases within the instruction cycle and is accompanied by a negative current jump exceeding the short-term drop threshold, based on the control scheme execution list. If the event is met, the interface issuing permission of the corresponding control instruction is frozen and the interface port status is recorded to obtain the control command execution isolation flag. The control command execution isolation marker specifically refers to the interface channel freeze number, the position in the control command waiting list, and the fault status identification label.

8. The wind turbine safe operation control system according to claim 7, characterized in that, The interface execution isolation module includes: The signal extraction submodule, based on the control scheme execution list, calls the bus voltage jump value, current negative slope time slice distribution, and wind turbine speed instantaneous response state corresponding to each channel in the controller according to the execution channel number of the control command, extracts the sampling sequence according to the channel period, constructs the parameter matrix, and generates control signal monitoring information; Based on the control signal monitoring information, the anomaly identification submodule determines whether there is a voltage value decreasing trend at two or more consecutive time points in each record, and whether it is accompanied by a current jump amplitude greater than the short-term drop threshold. It then filters the set of anomaly channel numbers to obtain the anomaly channel index sequence. The permission freeze submodule calls the abnormal channel index sequence, locates the current status in the interface management unit according to the control instruction number corresponding to the marked channel, determines whether the status is in the execution pre-queue, and if so, stops the instruction issuance and records the status label and channel status at the time of freeze, establishes a control channel freeze registration table, and generates a control command execution isolation mark.

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