CN116696681A - Method and related device for early warning of abnormal acceleration of wind generating set - Google Patents
Method and related device for early warning of abnormal acceleration of wind generating set Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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Abstract
The application discloses a method and a related device for early warning of abnormal acceleration of a wind generating set, wherein the method comprises the following steps: when the wind generating set continuously generates power in a target time period, determining a target statistical data set from a plurality of statistical data sets according to acceleration influence data of the wind generating set in the target time period, wherein different statistical data sets are set according to different acceleration influence data of the wind generating set under a simulation operation condition and correspond to different acceleration early warning data; determining acceleration characteristic data of the wind generating set belonging to the target statistical data set through acceleration of the wind generating set in the target time period; and under the condition that the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set. Therefore, the method avoids that the acceleration amplitude of the wind generating set is always kept at a higher level under the actual operation condition, so that the service life of the wind generating set is ensured.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to a method and a related device for early warning of abnormal acceleration of a wind power generator set.
Background
The acceleration of the wind turbine generator system changes with data having a certain influence on the acceleration of the wind turbine generator system, for example, the acceleration amplitude of the wind turbine generator system changes with the wind speed data of the wind turbine generator system and the like.
In the related art, the acceleration of the wind generating set is generally monitored, and if the absolute value of the acceleration amplitude exceeds the early warning threshold value of the acceleration amplitude, the wind generating set is immediately early warned so as to stop the wind generating set due to faults. The early warning threshold value of the acceleration amplitude is generally larger than the absolute value of the acceleration amplitude extreme value of the wind generating set under the simulation operation condition, so that the wind generating set is prevented from frequent early warning of fault shutdown under the actual operation condition.
However, the early warning threshold value of the acceleration amplitude is fixed, and the situation exists that the absolute value of the acceleration amplitude of the wind generating set under the actual operation condition in a longer period of time is larger than the extreme value of the acceleration amplitude of the wind generating set under the simulation operation condition, but smaller than the early warning threshold value of the acceleration amplitude; namely, the acceleration amplitude of the wind generating set is always kept at a higher level under the actual operation condition, so that the fatigue load of an actual tower of the wind generating set is higher, and the service life of the wind generating set is seriously influenced.
Disclosure of Invention
In view of the above, the embodiment of the application provides a method and a related device for early warning of abnormal acceleration of a wind generating set, so as to avoid that the acceleration amplitude of the wind generating set is always kept at a higher level under the actual operation condition, reduce the actual tower fatigue load of the wind generating set, and further ensure the service life of the wind generating set.
In a first aspect, an embodiment of the present application provides a method for early warning of an abnormal acceleration of a wind turbine generator system, where the method includes:
if the wind generating set continuously generates power in a target time period, determining a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind generating set in the target time period, wherein different statistical data sets are set based on different acceleration influence data of the wind generating set under a simulation operation condition, and different statistical data sets correspond to different acceleration early warning data;
determining acceleration characteristic data of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set in the target time period;
and if the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
Optionally, the acceleration early warning data is determined based on acceleration characteristic data of the wind generating set under the simulated operation condition corresponding to the statistical data set.
Optionally, the determining a target statistical data set from a plurality of statistical data sets based on acceleration influence data for the wind generating set in the target time period includes:
acquiring an acceleration influence data average value corresponding to acceleration influence data based on the acceleration influence data of the wind generating set in the target time period;
the target set of statistics is determined from a plurality of the sets of statistics based on the acceleration impact data average.
Optionally, the method further comprises:
storing the acceleration characteristic data to the target statistics set;
if the first accumulated number of the acceleration feature data under the target statistical data set is larger than or equal to the target accumulated number corresponding to the target statistical data set, determining the duty ratio of the acceleration feature data under the target statistical data set to the target acceleration early warning data based on the first accumulated number and the second accumulated number of the acceleration feature data under the target statistical data set to the target acceleration early warning data;
And if the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
Optionally, different statistics data sets correspond to different early warning duty ratios, or the different statistics data sets correspond to the target early warning duty ratio.
Optionally, the method further comprises:
determining an early warning output value of the target statistical data set based on whether the acceleration characteristic data is matched with target acceleration early warning data corresponding to the target statistical data set;
counting the sum of early warning output values of a plurality of the statistical data sets;
and if the sum of the early warning output values is greater than or equal to a preset sum, early warning the abnormal acceleration of the wind generating set.
Optionally, the acceleration influence data includes any one of wind speed data, power data, rotational speed data and pitch angle data; the acceleration characteristic data includes an acceleration amplitude extremum or an acceleration dominant frequency.
In a second aspect, an embodiment of the present application provides a device for early warning of an abnormal acceleration of a wind turbine generator system, where the device includes: the device comprises a first determining unit, a second determining unit and a first early warning unit;
The first determining unit is configured to determine, if the wind turbine generator is continuously generating power in a target time period, a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind turbine generator in the target time period, where different statistical data sets are set based on different acceleration influence data of the wind turbine generator under a simulated operation condition, and different statistical data sets correspond to different acceleration early warning data;
the second determining unit is used for determining acceleration characteristic data of the wind generating set corresponding to the target statistical data set according to the acceleration of the wind generating set in the target time period;
and the early warning unit is used for early warning the abnormal acceleration of the wind generating set if the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set.
Optionally, the acceleration early warning data is determined based on acceleration characteristic data of the wind generating set under the simulated operation condition corresponding to the statistical data set.
Optionally, the first determining unit is configured to:
acquiring an average value of acceleration influence data corresponding to acceleration influence data based on the acceleration influence data of the wind generating set in the target time period;
A target set of statistics is determined from the plurality of sets of statistics based on the acceleration impact data average.
Optionally, the apparatus further comprises: the device comprises a storage unit, a third determining unit and a second early warning unit;
the storage unit is used for storing the acceleration characteristic data to the target statistical data set;
the third determining unit is configured to determine, if the first accumulated number of the acceleration feature data in the target statistics data set is greater than or equal to the target accumulated number corresponding to the target statistics data set, a duty ratio of the acceleration feature data in the target statistics data set to the target acceleration early warning data based on the first accumulated number and the second accumulated number of the acceleration feature data in the target statistics data set to the target acceleration early warning data;
and the second early warning unit is used for early warning the abnormal acceleration of the wind generating set if the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set.
Optionally, the different statistical data sets correspond to different early warning duty ratios, or the different statistical data sets all correspond to the target early warning duty ratio.
Optionally, the apparatus further comprises: the system comprises a fourth determining unit, a counting unit and a third early warning unit;
A fourth determining unit, configured to determine an early warning output value of the target statistics data set based on whether the acceleration feature data matches target acceleration early warning data corresponding to the target statistics data set;
the statistics unit is used for counting the sum of early warning output values of a plurality of statistics data sets;
and the third early warning unit is used for early warning the abnormal acceleration of the wind generating set if the sum of the early warning output values is greater than or equal to the preset sum.
Optionally, the acceleration influence data includes any one of wind speed data, power data, rotational speed data and pitch angle data; the acceleration characteristic data includes an acceleration magnitude extremum or acceleration dominant frequency.
In a third aspect, embodiments of the present application provide a computer device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the method for early warning of abnormal acceleration of the wind turbine generator set according to the first aspect according to the instruction in the program code.
In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, where the computer readable storage medium is configured to store program code, where the program code, when executed by a computer, is configured to perform the method for early warning of an acceleration anomaly of a wind turbine generator set according to the first aspect.
Compared with the prior art, the application has at least the following advantages:
by adopting the technical scheme of the embodiment of the application, when the wind generating set continuously generates electricity in the target time period, the target statistical data set is determined from a plurality of statistical data sets according to the acceleration influence data of the wind generating set in the target time period, and different statistical data sets are set according to different acceleration influence data of the wind generating set under the simulation operation condition and correspond to different acceleration early warning data; determining acceleration characteristic data of the wind generating set belonging to the target statistical data set through acceleration of the wind generating set in the target time period; and under the condition that the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set. Therefore, the acceleration influence data of the wind generating set in the target time period is needed to be used, the target acceleration early warning data corresponding to the target statistical data set is determined in a targeted manner from different acceleration early warning data corresponding to the plurality of statistical data sets, whether the acceleration of the wind generating set in the target time period is abnormal is judged more accurately, the situation that the acceleration amplitude of the wind generating set is always maintained at a higher level under the actual operation working condition is avoided, the actual tower fatigue load of the wind generating set is reduced, and accordingly the service life of the wind generating set is guaranteed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a system frame related to an application scenario in an embodiment of the present application;
FIG. 2 is a flow chart of a method for early warning of abnormal acceleration of a wind turbine generator system according to an embodiment of the present application;
FIG. 3 is a graph showing the extreme value of the acceleration amplitude of a wind turbine generator set under different simulated operating conditions according to an embodiment of the present application;
FIG. 4 is a flowchart of another method for early warning of abnormal acceleration of a wind turbine generator system according to an embodiment of the present application;
FIG. 5 is a flowchart of another method for early warning of abnormal acceleration of a wind turbine generator system according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a device for early warning of abnormal acceleration of a wind turbine generator system according to an embodiment of the present application.
Detailed Description
In order to make the present application better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
At present, the early warning threshold value of the preset acceleration amplitude is larger than the acceleration amplitude extreme value of the wind generating set under the simulation operation working condition, the absolute value of the acceleration amplitude exceeding the early warning threshold value of the acceleration amplitude is judged by monitoring the acceleration of the wind generating set, and the wind generating set is immediately early warned so as to stop faults. However, the inventor finds that the early warning threshold value of the acceleration amplitude is fixed, and the situation that the absolute value of the acceleration amplitude of the wind generating set under the actual operation condition in a longer period of time is larger than the extreme value of the acceleration amplitude of the wind generating set under the simulation operation condition and smaller than the early warning threshold value of the acceleration amplitude exists; namely, the acceleration amplitude of the wind generating set is always kept at a higher level under the actual operation condition, so that the fatigue load of an actual tower of the wind generating set is higher, and the service life of the wind generating set is seriously influenced.
In order to solve the problem, in the embodiment of the application, when the wind generating set continuously generates electricity in a target time period, a target statistical data set is determined from a plurality of statistical data sets according to acceleration influence data of the wind generating set in the target time period, and different statistical data sets are set according to different acceleration influence data of the wind generating set under a simulation operation condition and correspond to different acceleration early warning data; determining acceleration characteristic data of the wind generating set belonging to the target statistical data set through acceleration of the wind generating set in the target time period; and under the condition that the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set. Therefore, the acceleration influence data of the wind generating set in the target time period is needed to be used, the target acceleration early warning data corresponding to the target statistical data set is determined in a targeted manner from different acceleration early warning data corresponding to the plurality of statistical data sets, whether the acceleration of the wind generating set in the target time period is abnormal is judged more accurately, the situation that the acceleration amplitude of the wind generating set is always maintained at a higher level under the actual operation working condition is avoided, the actual tower fatigue load of the wind generating set is reduced, and accordingly the service life of the wind generating set is guaranteed.
For example, one of the scenarios of the embodiments of the present application may be applied to the scenario shown in fig. 1. The scene comprises the wind generating set 101 and the controller 102, and the controller 102 adopts the implementation mode provided by the embodiment of the application to realize the early warning of the abnormal acceleration of the wind generating set 101.
First, in the above application scenario, although the description of the actions of the implementation manner provided by the embodiment of the present application is performed by the controller 102; however, the embodiment of the present application is not limited in terms of execution subject, and the operations disclosed in the embodiments provided by the embodiment of the present application may be executed.
Next, the above-described scenario is merely one example of a scenario provided by the embodiment of the present application, and the embodiment of the present application is not limited to this scenario.
The specific implementation mode of the method and the device for early warning the abnormal acceleration of the wind generating set in the embodiment of the application is described in detail by the embodiment with reference to the attached drawings.
Referring to fig. 2, a flow chart of a method for early warning of abnormal acceleration of a wind turbine generator system according to an embodiment of the present application is shown. In this embodiment, the method may include, for example, the following steps:
step 201: if the wind generating set continuously generates power in the target time period, determining a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind generating set in the target time period, wherein different statistical data sets are set based on different acceleration influence data of the wind generating set under the simulation operation working condition, and the different statistical data sets correspond to different acceleration early warning data.
In the related art, the acceleration of the wind generating set is monitored, and if the absolute value of the acceleration amplitude exceeds the early warning threshold value of the acceleration amplitude, the wind generating set is immediately early warned so as to stop the fault. The early warning threshold value of the acceleration amplitude is fixed under different operation conditions of the wind generating set, and the situation that the absolute value of the acceleration amplitude of the wind generating set under the actual operation conditions in a longer period of time is larger than the extreme value of the acceleration amplitude of the wind generating set under the simulation operation conditions and smaller than the early warning threshold value of the acceleration amplitude exists; namely, the acceleration amplitude of the wind generating set is always kept at a higher level under the actual operation condition, so that the fatigue load of an actual tower of the wind generating set is higher, and the service life of the wind generating set is seriously influenced.
Based on the above, the acceleration of the wind generating set is considered to change to a certain extent along with the change of the operation condition of the wind generating set; see, for example, the profile of the acceleration amplitude extremum of the wind turbine under the different simulated operating conditions shown in fig. 3. In the graph, wind speed data aiming at a wind generating set under different simulation operation conditions are taken as horizontal axis data, and acceleration amplitude extremum of the wind generating set under different simulation operation conditions is taken as vertical axis data, wherein a plurality of scattered points corresponding to each wind speed data represent the acceleration amplitude extremum of a plurality of wind generating sets under the simulation operation conditions corresponding to the wind speed data. Based on this graph, it can be seen that the acceleration amplitude extremum of the wind park increases with increasing wind speed data for the wind park.
That is, the acceleration of the wind turbine generator is influenced by the wind speed data of the wind turbine generator, and any one of the wind speed data, the power data, the rotational speed data, and the pitch angle data may be used as acceleration influence data in response to the power data, the rotational speed data, the pitch angle data, and the like. The acceleration amplitude extremum is used for representing the acceleration related characteristic of the wind generating set, and the acceleration dominant frequency can also be used for representing the acceleration related characteristic of the wind generating set, so that the acceleration amplitude extremum or the acceleration dominant frequency can be used as acceleration characteristic data.
In the embodiment of the application, different statistical data sets are correspondingly set based on different acceleration influence data of the wind generating set under the simulation operation condition; based on acceleration characteristic data of the wind generating set under the simulation operation working condition corresponding to each statistic data set, acceleration early warning data corresponding to each statistic data set are determined so as to be used for measuring whether the acceleration of the wind generating set under the actual operation working condition is abnormal or not; wherein, different statistics data sets correspond to different acceleration early warning data.
As an example, when the acceleration characteristic data is an acceleration amplitude extremum, for any one of the above-mentioned statistical data sets i, taking the product of the acceleration amplitude extremum of the wind generating set under the simulation operation condition corresponding to the statistical data set and a preset multiple as acceleration early warning data corresponding to the statistical data set, that is, an early warning threshold value of the acceleration amplitude extremum. Specifically, the product of the maximum value of the acceleration amplitude of the wind generating set and the preset multiple under the simulation operation condition corresponding to the statistical data set and the product of the minimum value of the acceleration amplitude of the wind generating set and the preset multiple under the simulation operation condition corresponding to the statistical data set are used as acceleration early warning data corresponding to the statistical data set, namely, the early warning threshold value a of the maximum value of the acceleration amplitude i1 And an early warning threshold value a of an acceleration amplitude minimum value i2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein the preset multiple is greater than 1, for example, the preset multiple may be 1.15. Similarly, the acceleration characteristic data may be an average acceleration amplitude value or an equivalent acceleration amplitude value.
As another example, when the acceleration characteristic data is the acceleration dominant frequency, for any one of the above-mentioned statistical data sets i, the acceleration dominant frequency h of the wind generating set under the simulated operation condition corresponding to the statistical data set is based on i And presetting a deviation coefficient k, and determining the acceleration early warning data corresponding to the statistical data set as the upper and lower deviation limits of the acceleration dominant frequency. Specifically, wind power generation under simulated operation conditions corresponding to the statistical data setAcceleration dominant frequency h of unit i Combining the difference between 1 and the preset deviation coefficient k and the sum of 1 and the preset deviation coefficient k to determine that the acceleration early-warning data corresponding to the statistical data set is the deviation lower limit (1-k) h of the acceleration dominant frequency i And an upper deviation limit (1+k) h of the acceleration dominant frequency i The method comprises the steps of carrying out a first treatment on the surface of the Wherein k is less than 1, for example, k has a value ranging from 0.1 to 0.2.
On the basis of the above description, when the wind turbine generator system continuously generates power in the target period, the acceleration influence data of the wind turbine generator system in the target period and the acceleration of the wind turbine generator system in the target period are taken as 1 data segment, the acceleration influence data of the wind turbine generator system in the target period is needed to pass through, and the corresponding statistical data set of the data segment is determined from different statistical data sets to be taken as the target statistical data set.
When step 201 is specifically implemented, firstly, an average value of acceleration influence data needs to be calculated for acceleration influence data of a wind generating set in a target time period; and then, the acceleration influence data is averaged, different acceleration influence data of the wind generating set are matched under the simulation operation working conditions corresponding to different statistic data sets, and a target statistic data set is determined from a plurality of statistic data sets based on a matching result. Thus, in an alternative implementation of the embodiment of the present application, step 201 may comprise, for example, the following steps a-B:
step A: and obtaining an average value of acceleration influence data corresponding to the acceleration influence data based on the acceleration influence data of the wind generating set in the target time period.
And (B) step (B): a target set of statistics is determined from the plurality of sets of statistics based on the acceleration impact data average.
As one example, when the target period is 1 minute and the acceleration influence data is wind speed data, calculating a wind speed data average value based on wind speed data for the wind turbine generator set within 1 minute; and matching the average value of the wind speed data with different wind speed data of the wind generating set under the simulation operation working condition corresponding to different statistical data sets, and determining a target statistical data set from a plurality of statistical data sets based on a matching result.
Step 202: and determining acceleration characteristic data of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set in the target time period.
In the embodiment of the present application, in step 201, after determining a target statistics data set from a plurality of statistics data sets based on acceleration influence data of a wind turbine generator set in a target time period, acceleration feature data, which belongs to the target statistics data set and characterizes acceleration related features of the wind turbine generator set, is determined by the acceleration of the wind turbine generator set in the target time period.
As an example, when the target time period is 1 minute and the acceleration characteristic data is an acceleration amplitude extremum, the acceleration amplitude extremum of the wind turbine generator set belonging to the target statistical data set is determined according to the acceleration of the wind turbine generator set within 1 minute, that is, the acceleration amplitude maximum value and the acceleration amplitude minimum value of the wind turbine generator set belonging to the target statistical data set are determined.
As an example, when the target time period is 1 minute and the acceleration characteristic data is the acceleration dominant frequency, determining the acceleration dominant frequency of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set within 1 minute; the acceleration dominant frequency refers to a frequency point corresponding to the maximum spectrum energy in the spectrum energy distribution situation obtained by performing fast Fourier transform on the acceleration of the wind generating set within 1 minute.
Step 203: if the acceleration characteristic data are matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
In the embodiment of the present application, after determining the acceleration characteristic data of the wind turbine generator set belonging to the target statistics data set according to the acceleration of the wind turbine generator set in the target time period in step 202, it is required to determine whether the acceleration characteristic data of the wind turbine generator set belonging to the target statistics data set matches the target acceleration early warning data corresponding to the target statistics data set, if yes, the acceleration abnormality of the wind turbine generator set is indicated, and if yes, the acceleration abnormality of the wind turbine generator set is required to be early warned.
As an example, when the target statistic data set is the statistic data set 1 and the acceleration characteristic data is the acceleration amplitude extremum, the acceleration amplitude maximum value of the wind generating set belonging to the statistic data set 1 is greater than or equal to the pre-warning threshold value a of the corresponding acceleration amplitude maximum value of the statistic data set 1 i1 Alternatively, the minimum value of the acceleration amplitude of the wind generating set belonging to the statistical data set 1 is smaller than or equal to the early warning threshold value a of the corresponding minimum value of the acceleration amplitude of the statistical data set 1 i2 And early warning the abnormal acceleration of the wind generating set.
As an example, when the target statistic data set is the statistic data set 1 and the acceleration characteristic data is the acceleration dominant frequency, the acceleration dominant frequency of the wind generating set belonging to the statistic data set 1 is less than or equal to the deviation lower limit (1-k) h of the acceleration dominant frequency corresponding to the statistic data set 1 i Alternatively, the acceleration dominant frequency of the wind generating set belonging to the statistical data set 1 is greater than or equal to the deviation upper limit (1+k) h of the acceleration dominant frequency corresponding to the statistical data set 1 i And early warning the abnormal acceleration of the wind generating set.
In addition, after the acceleration characteristic data of the wind generating set belonging to the target statistical data set is determined according to the acceleration of the wind generating set in the target time period, the acceleration characteristic data can be stored into the target statistical data set; in this way, whether the first accumulated number of the acceleration characteristic data under the target statistical data set is larger than or equal to the target accumulated number corresponding to the target statistical data set is judged, and the target accumulated number represents the reference sample size required by the early warning acceleration abnormality corresponding to the target statistical data set. If yes, determining a second accumulation number of the acceleration characteristic data under the target statistical data set matched with the target acceleration early warning data, and calculating the duty ratio of the acceleration characteristic data under the target statistical data set matched with the target acceleration early warning data, namely the ratio of the second accumulation number to the first accumulation number through the first accumulation number and the second accumulation number. Based on the above, whether the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set is judged, if yes, the acceleration abnormality of the wind generating set is indicated, and early warning of the acceleration abnormality of the wind generating set is needed. Thus, in an alternative implementation of the embodiment of the present application, the method may further comprise, for example, the following step C-step E:
Step C: and storing the acceleration characteristic data to a target statistical data set.
Step D: and if the first accumulated number of the acceleration characteristic data under the target statistical data set is larger than or equal to the target accumulated number corresponding to the target statistical data set, determining the duty ratio of the acceleration characteristic data under the target statistical data set to the target acceleration early warning data based on the first accumulated number and the second accumulated number of the acceleration characteristic data under the target statistical data set to the target acceleration early warning data.
Step E: and if the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
For different statistical data sets, different early warning duty ratios can be set, and the same early warning duty ratio can also be set, so that different statistical data sets all correspond to the target early warning duty ratio. Therefore, in an alternative implementation manner of the embodiment of the present application, different statistics data sets correspond to different pre-warning duty ratios, or different statistics data sets each correspond to a target pre-warning duty ratio. For example, the target early warning duty cycle may range from 5% to 10%.
In addition, in step 202, according to the acceleration of the wind generating set in the target time period, after determining the acceleration characteristic data of the wind generating set belonging to the target statistical data set, the early warning output value of the target statistical data set may be determined by determining whether the acceleration characteristic data of the wind generating set belonging to the target statistical data set matches the target acceleration early warning data corresponding to the target statistical data set; then, combining the early warning output values of the plurality of statistical data sets, and calculating the sum of the early warning output values of the plurality of statistical data sets; and finally, judging whether the sum of the early warning output values is larger than or equal to a preset sum, if so, indicating that the acceleration of the wind generating set is abnormal, and if so, early warning the acceleration of the wind generating set is required. Thus, in an alternative implementation of the embodiment of the present application, the method may further comprise, for example, the following steps F-H:
Step F: and determining an early warning output value of the target statistical data set based on whether the acceleration characteristic data is matched with target acceleration early warning data corresponding to the target statistical data set.
As an example, when the acceleration characteristic data matches the target acceleration early warning data corresponding to the target statistical data set, determining that the early warning output value of the target statistical data set is 1; otherwise, when the acceleration characteristic data is not matched with the target acceleration early warning data corresponding to the target statistical data set, the early warning output value of the target statistical data set is determined to be 0.
Step G: and counting the sum of early warning output values of a plurality of statistical data sets.
In the concrete implementation of the step G, the sum operation can be directly carried out on the early warning output values of the plurality of statistical data sets to obtain the sum of the early warning output values of the plurality of statistical data sets; and the method can also carry out weighting operation on the early warning output values of a plurality of statistical data sets on the basis that each statistical data set has weight, so as to obtain the sum of the early warning output values of the plurality of statistical data sets.
Step H: if the sum of the early warning output values is larger than or equal to the preset sum, early warning is carried out on the abnormal acceleration of the wind generating set.
According to the various implementation manners provided by the embodiment, when the wind generating set continuously generates electricity in the target time period, the target statistical data set is determined from the plurality of statistical data sets according to the acceleration influence data of the wind generating set in the target time period, and different statistical data sets are set according to different acceleration influence data of the wind generating set under the simulation operation working condition and correspond to different acceleration early warning data; determining acceleration characteristic data of the wind generating set belonging to the target statistical data set through acceleration of the wind generating set in the target time period; and under the condition that the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set. Therefore, the acceleration influence data of the wind generating set in the target time period is needed to be used, the target acceleration early warning data corresponding to the target statistical data set is determined in a targeted manner from different acceleration early warning data corresponding to the plurality of statistical data sets, whether the acceleration of the wind generating set in the target time period is abnormal is judged more accurately, the situation that the acceleration amplitude of the wind generating set is always maintained at a higher level under the actual operation working condition is avoided, the actual tower fatigue load of the wind generating set is reduced, and accordingly the service life of the wind generating set is guaranteed.
On the basis of the embodiment, taking acceleration influence data as wind speed data and acceleration characteristic data as an acceleration amplitude extremum as an example, referring to fig. 4, a flow diagram of another method for early warning of abnormal acceleration of a wind generating set in the embodiment of the application is shown. In this embodiment, the method may include, for example, the steps of:
step 401: and judging whether the wind generating set continuously generates electricity in the target time period, if so, executing step 402.
Step 402: and determining a target statistical data set from a plurality of statistical data sets based on wind speed data of the wind generating set in a target time period, wherein different statistical data sets are set based on different wind speed data of the wind generating set under a simulation operation condition, and the different statistical data sets correspond to early warning thresholds of different acceleration amplitude extreme values.
Step 403: and determining an acceleration amplitude extremum of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set in the target time period.
Step 404: and storing the acceleration amplitude extreme value of the wind generating set belonging to the target statistical data set.
Step 405: and judging whether the first accumulated number of the acceleration amplitude extreme values under the target statistical data set is greater than or equal to the target accumulated number corresponding to the target statistical data set, if so, executing step 406.
Step 406: and determining the duty ratio of the early warning threshold value of the acceleration amplitude extremum matched with the target acceleration amplitude extremum under the target statistical data set based on the first accumulated number and the second accumulated number of the early warning threshold value of the acceleration amplitude extremum matched with the target acceleration amplitude extremum under the target statistical data set, wherein the early warning threshold value of the target acceleration amplitude extremum corresponds to the target statistical data set.
Step 407: and judging that the duty ratio is greater than or equal to the target early warning duty ratio corresponding to the target statistical data set, if yes, executing step 408.
Step 408: and early warning the abnormal acceleration of the wind generating set.
In addition, taking acceleration influence data as wind speed data and acceleration characteristic data as acceleration dominant frequency as an example, referring to fig. 5, a flow diagram of another method for early warning of abnormal acceleration of a wind generating set in the embodiment of the application is shown. In this embodiment, the method may include, for example, the steps of:
step 501: and judging whether the wind generating set continuously generates electricity in a target time period, if so, executing step 502.
Step 502: and determining a target statistical data set from a plurality of statistical data sets based on wind speed data of the wind generating set in a target time period, wherein different statistical data sets are set based on different wind speed data of the wind generating set under a simulation operation condition, and the different statistical data sets correspond to upper and lower deviation limits of different acceleration dominant frequencies.
Step 503: and determining the acceleration dominant frequency of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set in the target time period.
Step 504: and storing the acceleration dominant frequency of the wind generating set belonging to the target statistical data set.
Step 505: and judging whether the first accumulated number of the acceleration dominant frequencies under the target statistical data set is greater than or equal to the target accumulated number corresponding to the target statistical data set, if so, executing step 506.
Step 506: and determining the ratio of the upper limit and the lower limit of the deviation of the acceleration dominant frequency matching the target acceleration dominant frequency under the target statistical data set based on the first accumulated number and the second accumulated number of the early warning threshold value of the acceleration dominant frequency matching the target acceleration dominant frequency under the target statistical data set.
Step 507: and judging that the duty ratio is greater than or equal to the target early warning duty ratio corresponding to the target statistical data set, if yes, executing step 508.
Step 508: and early warning the abnormal acceleration of the wind generating set.
Aiming at the method for early warning the abnormal acceleration of the wind generating set, the embodiment of the application also provides a device for early warning the abnormal acceleration of the wind generating set.
Referring to fig. 6, a schematic structural diagram of a device for early warning of abnormal acceleration of a wind turbine generator system in an embodiment of the present application is shown. In this embodiment, the apparatus may specifically include: a first determination unit 601, a second determination unit 602, and an early warning unit 603;
the first determining unit 601 is configured to determine, if the wind turbine generator is continuously generating power in a target period of time, a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind turbine generator in the target period of time, where different statistical data sets are set based on different acceleration influence data of the wind turbine generator under a simulated operation condition, and the different statistical data sets correspond to different acceleration early warning data;
a second determining unit 602, configured to determine acceleration feature data of the wind turbine generator set corresponding to the target statistics data set according to acceleration of the wind turbine generator set in the target time period;
The first early warning unit 603 is configured to early warn that the acceleration of the wind generating set is abnormal if the acceleration characteristic data matches the target acceleration early warning data corresponding to the target statistics data set.
In an optional implementation manner of the embodiment of the application, the acceleration early warning data is determined based on acceleration characteristic data of the wind generating set under the simulation operation condition corresponding to the statistical data set.
In an alternative implementation manner of the embodiment of the present application, the first determining unit 601 is configured to:
acquiring an average value of acceleration influence data corresponding to acceleration influence data based on the acceleration influence data of the wind generating set in the target time period;
a target set of statistics is determined from the plurality of sets of statistics based on the acceleration impact data average.
In an alternative implementation manner of the embodiment of the present application, the apparatus further includes: the device comprises a storage unit, a third determining unit and a second early warning unit;
the storage unit is used for storing the acceleration characteristic data to the target statistical data set;
the third determining unit is configured to determine, if the first accumulated number of the acceleration feature data in the target statistics data set is greater than or equal to the target accumulated number corresponding to the target statistics data set, a duty ratio of the acceleration feature data in the target statistics data set to the target acceleration early warning data based on the first accumulated number and the second accumulated number of the acceleration feature data in the target statistics data set to the target acceleration early warning data;
And the second early warning unit is used for early warning the abnormal acceleration of the wind generating set if the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set.
In an optional implementation manner of the embodiment of the present application, different statistics data sets correspond to different pre-warning duty ratios, or different statistics data sets all correspond to the target pre-warning duty ratio.
In an alternative implementation manner of the embodiment of the present application, the apparatus further includes: the system comprises a fourth determining unit, a counting unit and a third early warning unit;
a fourth determining unit, configured to determine an early warning output value of the target statistics data set based on whether the acceleration feature data matches target acceleration early warning data corresponding to the target statistics data set;
the statistics unit is used for counting the sum of early warning output values of a plurality of statistics data sets;
and the third early warning unit is used for early warning the abnormal acceleration of the wind generating set if the sum of the early warning output values is greater than or equal to the preset sum.
In an optional implementation manner of the embodiment of the present application, the acceleration influence data includes any one of wind speed data, power data, rotation speed data and pitch angle data; the acceleration characteristic data includes an acceleration magnitude extremum or acceleration dominant frequency.
According to the various implementation manners provided by the embodiment, when the wind generating set continuously generates electricity in the target time period, the target statistical data set is determined from the plurality of statistical data sets according to the acceleration influence data of the wind generating set in the target time period, and different statistical data sets are set according to different acceleration influence data of the wind generating set under the simulation operation working condition and correspond to different acceleration early warning data; determining acceleration characteristic data of the wind generating set belonging to the target statistical data set through acceleration of the wind generating set in the target time period; and under the condition that the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set. Therefore, the acceleration influence data of the wind generating set in the target time period is needed to be used, the target acceleration early warning data corresponding to the target statistical data set is determined in a targeted manner from different acceleration early warning data corresponding to the plurality of statistical data sets, whether the acceleration of the wind generating set in the target time period is abnormal is judged more accurately, the situation that the acceleration amplitude of the wind generating set is always maintained at a higher level under the actual operation working condition is avoided, the actual tower fatigue load of the wind generating set is reduced, and accordingly the service life of the wind generating set is guaranteed.
In addition, the embodiment of the application also provides a computer device, which comprises a processor and a memory:
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the method for early warning the abnormal acceleration of the wind generating set according to the instructions in the program codes.
In addition, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium is used for storing program codes, and when the program codes are executed by a computer, the computer is used for executing the method for early warning the abnormal acceleration of the wind generating set.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only of the preferred embodiment of the present application, and is not intended to limit the present application in any way. While the application has been described with reference to preferred embodiments, it is not intended to be limiting. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present application or modifications to equivalent embodiments using the methods and technical contents disclosed above, without departing from the scope of the technical solution of the present application. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present application still fall within the scope of the technical solution of the present application.
Claims (10)
1. The method for early warning the abnormal acceleration of the wind generating set is characterized by comprising the following steps of:
if the wind generating set continuously generates power in a target time period, determining a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind generating set in the target time period, wherein different statistical data sets are set based on different acceleration influence data of the wind generating set under a simulation operation condition, and different statistical data sets correspond to different acceleration early warning data;
determining acceleration characteristic data of the wind generating set belonging to the target statistical data set according to the acceleration of the wind generating set in the target time period;
and if the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
2. The method of claim 1, wherein the acceleration warning data is determined based on acceleration signature data of the wind turbine generator set under simulated operating conditions corresponding to the set of statistical data.
3. The method of claim 1, wherein the determining a target set of statistics from a plurality of sets of statistics based on acceleration impact data for the wind turbine generator set over the target period of time comprises:
Acquiring an acceleration influence data average value corresponding to acceleration influence data based on the acceleration influence data of the wind generating set in the target time period;
the target set of statistics is determined from a plurality of the sets of statistics based on the acceleration impact data average.
4. The method according to claim 1, wherein the method further comprises:
storing the acceleration characteristic data to the target statistics set;
if the first accumulated number of the acceleration feature data under the target statistical data set is larger than or equal to the target accumulated number corresponding to the target statistical data set, determining the duty ratio of the acceleration feature data under the target statistical data set to the target acceleration early warning data based on the first accumulated number and the second accumulated number of the acceleration feature data under the target statistical data set to the target acceleration early warning data;
and if the duty ratio is larger than or equal to the target early warning duty ratio corresponding to the target statistical data set, early warning the abnormal acceleration of the wind generating set.
5. The method of claim 4, wherein different sets of the statistics correspond to different pre-warning duty cycles, or wherein the different sets of the statistics each correspond to the target pre-warning duty cycle.
6. The method according to claim 1, wherein the method further comprises:
determining an early warning output value of the target statistical data set based on whether the acceleration characteristic data is matched with target acceleration early warning data corresponding to the target statistical data set;
counting the sum of early warning output values of a plurality of the statistical data sets;
and if the sum of the early warning output values is greater than or equal to a preset sum, early warning the abnormal acceleration of the wind generating set.
7. The method of claim 1, wherein the acceleration-affecting data includes any one of wind speed data, power data, rotational speed data, and pitch angle data; the acceleration characteristic data includes an acceleration amplitude extremum or an acceleration dominant frequency.
8. An apparatus for early warning of an abnormal acceleration of a wind turbine generator system, comprising: the device comprises a first determining unit, a second determining unit and a first early warning unit;
the first determining unit is configured to determine, if the wind turbine generator is continuously generating power in a target time period, a target statistical data set from a plurality of statistical data sets based on acceleration influence data of the wind turbine generator in the target time period, where different statistical data sets are set based on different acceleration influence data of the wind turbine generator under a simulated operation condition, and different statistical data sets correspond to different acceleration early warning data;
The second determining unit is used for determining acceleration characteristic data of the wind generating set corresponding to the target statistical data set according to the acceleration of the wind generating set in the target time period;
and the early warning unit is used for early warning the abnormal acceleration of the wind generating set if the acceleration characteristic data is matched with the target acceleration early warning data corresponding to the target statistical data set.
9. A computer device, the computer device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the method for early warning of acceleration anomalies in a wind turbine generator set according to instructions in the program code.
10. A computer readable storage medium for storing program code, which when executed by a computer is adapted to carry out the method of pre-warning a wind power generator set of an abnormal acceleration according to any one of claims 1-7.
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