CN117932875A - Wind turbine generator tower sweeping risk assessment method and system - Google Patents
Wind turbine generator tower sweeping risk assessment method and system Download PDFInfo
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- CN117932875A CN117932875A CN202311713050.XA CN202311713050A CN117932875A CN 117932875 A CN117932875 A CN 117932875A CN 202311713050 A CN202311713050 A CN 202311713050A CN 117932875 A CN117932875 A CN 117932875A
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Abstract
The embodiment of the invention provides a wind turbine generator tower sweeping risk assessment method and system, and belongs to the technical field of wind power generation. The method comprises the following steps: collecting operation retention information of each wind turbine in a target evaluation area, and preprocessing the operation retention information; correcting the operation retention information after pretreatment to obtain wind direction information of each wind turbine generator; based on the preprocessed operation retention information and wind direction information of each wind turbine, performing operation scene simulation on each wind turbine to obtain extreme negative shear values of each wind turbine; and carrying out target evaluation area tower scanning risk evaluation based on the extreme negative shear value of each wind turbine. According to the scheme, the risk assessment of wind turbine generator tower sweeping is carried out through the coupling topography factors, so that the accuracy of a risk assessment structure is ensured.
Description
Technical Field
The invention relates to the technical field of wind power generation, in particular to a wind turbine generator tower sweeping risk assessment method and a wind turbine generator tower sweeping risk assessment system.
Background
In recent years, along with the large development of fan blades, the existing wind energy resource evaluation theory is not satisfied with the safety requirement of the sweeping tower of the unit blades in China, and the geometrical complexity, the geometrical nonlinearity and the weak structural rigidity of the hundred-meter-level blades lead to extremely complex aeroelastic coupling dynamic response rules under the rotation condition, so that the wind resource evaluation such as negative shear, turbulence and wind gust face the risk of failure. The existing tower sweeping risk assessment scheme based on numerical simulation needs to ensure that the acquired data are accurate. However, in actual situations, as the complexity of the terrain increases, the corresponding numerical value acquisition error becomes larger and larger, so that the tower scanning risk assessment result based on the numerical simulation scheme is unreliable, and the accuracy is difficult to be ensured. Aiming at the problem of low accuracy of the existing wind turbine generator system tower sweeping scheme, a new wind turbine generator system tower sweeping risk assessment scheme needs to be created.
Disclosure of Invention
The embodiment of the invention aims to provide a wind turbine generator tower sweeping risk assessment method and system, which are used for at least solving the problem of low accuracy of the existing wind turbine generator tower sweeping scheme.
In order to achieve the above object, a first aspect of the present invention provides a risk assessment method for wind turbine generator system tower sweeping, the method comprising: collecting operation retention information of each wind turbine in a target evaluation area, and preprocessing the operation retention information; correcting the operation retention information after pretreatment to obtain wind direction information of each wind turbine generator; based on the preprocessed operation retention information and wind direction information of each wind turbine, performing operation scene simulation on each wind turbine to obtain extreme negative shear values of each wind turbine; and carrying out target evaluation region tower scanning risk evaluation based on the extreme negative shear value of each wind turbine and a preset extreme negative shear value threshold value.
Optionally, the operation retention information of each wind turbine generator includes: historical operation data of the wind turbine and setting state data of the wind turbine; the historical operation data of the wind turbine generator set comprises: one or more of wind direction information, wind speed information, generator rotating speed and actual power information of each wind turbine generator at each sampling moment; the setting state information of the wind turbine generator comprises: one or more of pitch angle, nacelle position, and nacelle position terrain information.
Optionally, the preprocessing the operation retention information includes: based on the data type, carrying out data classification on the operation retention information to obtain a plurality of data sets; and in each data set, invalid data identification is carried out, and rejection processing is carried out on the invalid data, so that operation retention information after pretreatment is completed is obtained.
Optionally, the correcting the preprocessed operation retention information to obtain wind direction information of each wind turbine generator includes: determining initial wind direction information of each wind turbine generator based on the preprocessed operation retention information; determining wind direction deviation values of the positions of the wind turbines based on the initial wind direction information of the wind turbines and the main direction information acquired by a wind measuring tower at the corresponding sampling time; and correcting the preprocessed operation retention information based on the wind direction deviation value of each wind turbine position to obtain the actual incoming flow position of each wind turbine position as wind direction information of each wind turbine.
Optionally, based on the preprocessed operation retention information and wind direction information of each wind turbine, performing operation scene simulation on each wind turbine to obtain an extreme negative shear value of each wind turbine, including: based on the preprocessed operation retention information, constructing a three-dimensional geographic model of the target evaluation area; dividing the constructed three-dimensional geographic model into a plurality of sectors by taking the center of the model as the center of a circle, and respectively performing wind field simulation in each mountain area; based on the simulation result, obtaining a simulated extreme negative shear value of each wind turbine corresponding to each sector; screening out wind turbines to be calibrated, and calibrating and/or correcting the simulated extreme negative shear value of the wind turbines to be calibrated based on the topographic parameter information fed back by the laser radar preset by the calibration target to obtain the extreme negative shear value of each wind turbine.
Optionally, the constructing the three-dimensional geographic model for the target evaluation area based on the preprocessed operation retention information includes: reading the position of each wind turbine generator set and the topographic information of the corresponding position based on the preprocessed operation retention information; based on the position of each wind turbine generator and the topographic information of the corresponding position, obtaining the area information and the topographic information of the whole target evaluation area as a target scene; and constructing a three-dimensional geographic model based on the target scene and a preset three-dimensional modeling algorithm to obtain a virtual three-dimensional scene of the target evaluation area.
Optionally, the rule for obtaining the simulated extreme negative shear value of each wind turbine under each sector based on the simulation result is as follows:
wherein, A wind shear simulation value of the height of the position h of the wind turbine generator on the ith sector; /(I)The wind shear simulation value of h height at the wind measuring tower point position on the ith sector; /(I)The measured value of the wind shear of the h height at the wind tower point position on the ith sector; /(I)The wind shear result value of the height of the position h of the wind turbine generator on the ith sector is obtained; /(I)And the simulated extreme negative shear value of the corresponding wind turbine generator set.
Optionally, the screening out the wind turbine generator to be calibrated, and based on the topographic parameter information fed back by the laser radar preset by the calibration target, calibrating and/or correcting the simulated extreme negative shear value of the wind turbine generator to be calibrated to obtain the extreme negative shear value of each wind turbine generator, including: respectively comparing wind direction information of each wind turbine generator based on the simulation result with wind direction information of each wind turbine generator obtained by correction, and selecting the corresponding wind turbine generator as a wind turbine generator to be corrected when the deviation value of the wind direction information of each wind turbine generator exceeds a preset angle deviation threshold value; performing laser radar presetting at the actual position or the simulation position of each wind turbine generator to be calibrated, performing terrain parameter acquisition through the laser radar, and taking the wind shear value measured by the laser radar as the wind shear value of the corresponding wind turbine generator when the deviation between the terrain parameter information acquired by the laser radar and the terrain parameter information of the position of the corresponding wind turbine generator is smaller than a preset terrain deviation threshold; if the deviation between the wind shear value obtained by each wind turbine generator based on the laser radar and the wind shear result value obtained based on the simulation result is larger than a wind shear deviation threshold value, the wind shear value obtained based on the laser radar is used as the wind shear result value to correct the simulation extreme negative shear value, and the extreme negative shear value of the corresponding wind turbine generator is obtained; otherwise, the simulated extreme negative shear value is directly used as the extreme negative shear value of the corresponding wind turbine generator.
Optionally, performing the risk assessment of the target assessment area for tower scanning based on the extreme negative shear value of each wind turbine generator set and a preset extreme negative shear value threshold value, including: acquiring an extreme negative shear value judgment rule based on a knowledge graph base, and acquiring an extreme negative shear value threshold value of each height position of the wind turbine generator set based on the judgment rule; comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping; and traversing tower scanning risk judging results of all the wind turbines to obtain tower scanning risk assessment results of the target assessment area.
The second aspect of the invention provides a risk assessment system for wind turbine generator system tower sweeping, which comprises: the collecting unit is used for collecting operation retention information of each wind turbine in the target evaluation area and preprocessing the operation retention information; the correction unit is used for correcting the preprocessed operation retention information to obtain wind direction information of each wind turbine generator; the simulation unit is used for performing operation scene simulation on each wind turbine based on the preprocessed operation retention information and wind direction information of each wind turbine to obtain extreme negative shear values of each wind turbine; and the evaluation unit is used for carrying out target evaluation area tower scanning risk evaluation based on the extreme negative shear value of each wind turbine and a preset extreme negative shear value threshold value.
In another aspect, the present invention provides a computer readable storage medium, where instructions are stored on the computer readable storage medium, and when the computer runs on a computer, the computer is caused to perform the wind turbine generator tower sweeping risk assessment method.
Through the technical scheme, the geographical environment information of the historical operating states of the wind turbines is determined based on the operation retention information of the wind turbines in the target evaluation area. And then, based on the information, performing simulation so as to ensure that coupling influence factors such as topographic data, running states and the like are brought into risk assessment of the tower, thereby solving the problem of low accuracy of assessment results caused by the fact that the coupling diversified influence factors cannot be coupled in a numerical simulation scheme. And carrying out corresponding position tower scanning risk assessment by calculating the extreme negative shear value of each wind turbine, and ensuring the accuracy of the tower scanning risk assessment by coupling the terrain change factors.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
FIG. 1 is a flow chart of steps of a wind turbine generator system tower sweeping risk assessment method according to an embodiment of the present invention;
FIG. 2 is a secondary verification flow chart based on lidar provided by an embodiment of the present invention;
Fig. 3 is a system structure diagram of a risk assessment system for wind turbine generator system tower sweeping according to an embodiment of the invention.
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
Fig. 1 is a flow chart of a method for evaluating risk of wind turbine generator system tower sweeping according to an embodiment of the invention. As shown in fig. 1, an embodiment of the present invention provides a wind turbine generator tower sweeping risk assessment method, which includes:
Step S10: and collecting operation retention information of each wind turbine in the target evaluation area, and preprocessing the operation retention information.
Specifically, the topography factors are introduced into the risk assessment of the tower sweeping, so that the topography information of the building position of the wind turbine is required to be acquired besides the operation parameter information of the wind turbine when the data acquisition is carried out by the scheme.
Preferably, the operation retention information of each wind turbine generator includes: historical operation data of the wind turbine and setting state data of the wind turbine; the historical operation data of the wind turbine generator set comprises: one or more of wind direction information, wind speed information, generator rotating speed and actual power information of each wind turbine generator at each sampling moment; the setting state information of the wind turbine generator comprises: one or more of pitch angle, nacelle position, and nacelle position terrain information.
In the embodiment of the invention, the pitch angle data is used for monitoring whether to open or close the blade; the cabin position and the wind direction jointly determine the incoming wind direction; wind speed is used to calculate turbulence; the rotating speed and the actual power of the generator illustrate the power generation state of the fan at the moment.
Further, the preprocessing the operation retention information includes: based on the data type, carrying out data classification on the operation retention information to obtain a plurality of data sets; and in each data set, invalid data identification is carried out, and rejection processing is carried out on the invalid data, so that operation retention information after pretreatment is completed is obtained.
In the embodiment of the invention, after the data acquisition is completed, the data type (the historical operation data of the wind turbine and the setting state data of the wind turbine) is required to be subjected to data classification to obtain a plurality of data sets, and the corresponding item processing is conveniently carried out through different data sets, so that the condition that the whole data set needs to be traversed every time of data acquisition is avoided, and the data processing efficiency is improved. Preferably, the invalid data identification includes identifying blade angle opening data, data with the rotation speed of the generator being 0 or data with the actual power being 0, and eliminating the invalid data to reduce the volume of the data.
Preferably, the method and the system take SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control system) data of the wind turbine as operation retention information for data acquisition. The SCADA system is a DCS and electric power automatic monitoring system based on a computer; the method has wide application fields, and can be applied to various fields such as data acquisition and monitoring control, process control and the like in the fields of electric power, metallurgy, petroleum, chemical industry, fuel gas, railways and the like. Among the power systems, the SCADA system is most widely used and the technology development is most mature. The remote control system plays an important role in a remote control system, and can monitor and control on-site operation equipment to realize various functions such as data acquisition, equipment control, measurement, parameter adjustment, various signal alarms and the like, namely a four-remote function. RTU (remote terminal unit), FTU (feeder terminal unit) is an important component thereof. Plays a quite important role in the comprehensive automation construction of the transformer substation.
In the embodiment of the invention, the data acquisition is performed based on the SCADA system, so that the data acquisition system constructed by the existing scheme can be directly utilized to perform data acquisition, a new acquisition system is not required to be reconstructed, and the system upgrading cost is reduced. On the other hand, by utilizing the characteristic of full data acquisition of the SCADA system, the accuracy of data acquisition can be ensured, and the second-level time sequence data of the wind turbine generator can be acquired through the SCADA system so as to adapt to the characteristic of changeable wind field conditions and ensure the accuracy of subsequent evaluation results.
Of course, besides SCADA data, any other data acquisition system capable of acquiring wind turbine running information and topographic information can be used as another real-time mode of the scheme of the invention, and the data acquisition system falls into the protection scope of the scheme of the invention.
Step S20: and correcting the operation retention information after pretreatment to obtain wind direction information of each wind turbine generator.
Specifically, determining initial wind direction information of each wind turbine generator based on the preprocessed operation retention information; determining wind direction deviation values of the positions of the wind turbines based on the initial wind direction information of the wind turbines and the main direction information acquired by a wind measuring tower at the corresponding sampling time; and correcting the preprocessed operation retention information based on the wind direction deviation value of each wind turbine position to obtain the actual incoming flow position of each wind turbine position as wind direction information of each wind turbine.
In the embodiment of the invention, because of the influence of the topography factors or when the fan is installed, the fan does not point to the north direction, the wind direction data of the unit needs to be corrected so as to ensure the accuracy of the incoming flow direction of the corresponding point position. Based on this, the present approach corrects the collected incoming flow direction in order to perform subsequent negative shear predictions based on the accurate incoming flow direction.
Based on this, the corresponding correction rule is:
Actual incoming flow wind direction= (nacelle position+wind direction data) 57.3+father device
The cabin position and wind direction data represent collected incoming wind directions, and the incoming wind directions are simulated through specific construction positions of the cabin and wind direction positions collected by the wind towers. The degree is calculated according to the main wind direction of the anemometer tower, and the calculation formula is as follows:
is defined = wind tower main direction-nacelle position main direction.
Step S30: and performing operation scene simulation on each wind turbine based on the preprocessed operation retention information and wind direction information of each wind turbine to obtain the extreme negative shear value of each wind turbine.
Specifically, the position of each wind turbine generator and the topographic information of the corresponding position are read based on the preprocessed operation retention information; based on the position of each wind turbine generator and the topographic information of the corresponding position, obtaining the area information and the topographic information of the whole target evaluation area as a target scene; and constructing a three-dimensional geographic model based on the target scene and a preset three-dimensional modeling algorithm to obtain a virtual three-dimensional scene of the target evaluation area.
In the embodiment of the invention, the scheme needs to perform simulation scene construction aiming at the topographic parameters, and three-dimensional geographic model construction is performed through three-dimensional modeling algorithms such as GIS (geographic information system) and the like so as to obtain a three-dimensional scene instead of a target area, and wind field condition simulation is performed in the three-dimensional scene, so that topographic factors can be brought into a reference sequence, and simulation accuracy is ensured.
In one possible embodiment, a circle is drawn with the center point of the wind farm as the origin and 1.4 times the distance between the center point and the farthest fan as the radius, and the area is used as the field simulation area. And the mesh division is carried out by adopting the mesh processing software ICEM software matched with FLUENT, the 0-360 DEG direction is divided according to the sector interval of 30 DEG, and the simulation is carried out on the sector directions in sequence.
Further, the rule for obtaining the simulated extreme negative shear value of each wind turbine corresponding to each sector based on the simulation result is as follows:
wherein, A wind shear simulation value of the height of the position h of the wind turbine generator on the ith sector; /(I)The wind shear simulation value of h height at the wind measuring tower point position on the ith sector; /(I)The measured value of the wind shear of the h height at the wind tower point position on the ith sector; /(I)The wind shear result value of the height of the position h of the wind turbine generator on the ith sector is obtained; /(I)And the simulated extreme negative shear value of the corresponding wind turbine generator set.
Preferably, the screening out the wind turbine generator to be calibrated, and based on the topographic parameter information fed back by the laser radar preset by the calibration target, calibrating and/or correcting the simulated extreme negative shear value of the wind turbine generator to be calibrated, to obtain the extreme negative shear value of each wind turbine generator, including: respectively comparing wind direction information of each wind turbine generator based on the simulation result with wind direction information of each wind turbine generator obtained by correction, and selecting the corresponding wind turbine generator as a wind turbine generator to be corrected when the deviation value of the wind direction information of each wind turbine generator exceeds a preset angle deviation threshold value; performing laser radar presetting at the actual position or the simulation position of each wind turbine generator to be calibrated, performing terrain parameter acquisition through the laser radar, and taking the wind shear value measured by the laser radar as the wind shear value of the corresponding wind turbine generator when the deviation between the terrain parameter information acquired by the laser radar and the terrain parameter information of the position of the corresponding wind turbine generator is smaller than a preset terrain deviation threshold; if wind shear value obtained by each wind turbine generator based on laser radarWind shear value obtained by a laser radar at a wind tower point of h height on an i-th sector) and a wind shear result value/>, obtained based on a simulation resultThe deviation between the wind shear values is larger than the wind shear deviation threshold value, the wind shear value/>, which is obtained based on the laser radarSimulated extreme negative shear value/>, as wind shear result valuePerforming calibration to obtain an extreme negative shear value of the corresponding wind turbine generator; otherwise, the simulated extreme negative shear value is directly used as the extreme negative shear value of the corresponding wind turbine generator.
As shown in fig. 2, in the embodiment of the invention, when the wind turbine generator to be calibrated is corrected for the extremely negative shear value, a dual judgment scheme is adopted, and first, the primary judgment of the setting position of the laser radar is performed, and only when the deviation value between the setting position of the laser radar and the actual judgment position is smaller than the preset terrain deviation threshold value, the wind shear value based on the laser radar simulation can be ensured to be the accurate wind shear value according with the current scene. However, the scheme of the invention performs secondary verification in consideration of the reasons that the laser radar also has acquisition errors, equipment faults and the like. The wind shear value acquired by the laser radar is compared with the wind shear value (height comparison) obtained based on the simulation result, and if the deviation value of the wind shear value and the wind shear value is larger than a preset wind shear deviation threshold value, the wind turbine to be calibrated is proved to have the problem of simulation errors indeed. The analog wind shear value is corrected (replaced, arithmetic mean or weighted regulation) based on the wind shear value obtained by the lidar to recalculate the extremely negative shear value. If the deviation value of the two is not greater than the preset wind shear deviation threshold value, in order to avoid error of the laser radar device, the calculated negative shear value of the simulation result is adopted as the final extreme negative shear value. According to the scheme, the problems of inaccurate wind shear result simulation and accurate failure caused by the failure of the laser radar equipment are solved through secondary judgment.
In another possible implementation manner, the screening the wind turbine generator to be calibrated, and based on the topographic parameter information fed back by the laser radar preset by the calibration target, calibrating and/or correcting the simulated extreme negative shear value of the wind turbine generator to be calibrated, to obtain the extreme negative shear value of each wind turbine generator includes: respectively comparing wind direction information of each wind turbine generator based on the simulation result with wind direction information of each wind turbine generator obtained by correction, and selecting the corresponding wind turbine generator as a wind turbine generator to be corrected when the deviation value of the wind direction information of each wind turbine generator exceeds a preset angle deviation threshold value; performing laser radar presetting at the actual position or the simulation position of each wind turbine generator to be calibrated, performing terrain parameter acquisition through the laser radar, and taking the wind shear value measured by the laser radar as the wind shear value of the corresponding wind turbine generator when the deviation between the terrain parameter information acquired by the laser radar and the terrain parameter information of the position of the corresponding wind turbine generator is smaller than a preset terrain deviation threshold; and replacing wind slice simulation war in the extreme negative shear value simulation rule based on the wind shear value to obtain a corresponding extreme negative slice value.
In the embodiment of the invention, on the premise of not considering the stability of the laser radar equipment, the scheme of the invention can also perform field detection and analog detection based on the condition of terrain deviation, so that the actual measurement data of the laser radar is directly used as accurate data to replace the original data, and the accuracy of the data is ensured. According to the scheme, the simulation error caused by the installation position and the azimuth of the unit is avoided by adding the laser radar complement measurement mode, and the accuracy of a simulation result can be ensured.
In one possible embodiment, the machine site wind direction is compared with the SCADA corrected wind direction, and if the main wind direction deviates by more than 30 degrees, further lidar compensation is required. When the laser radar wind measurement is carried out, shielding exists at the periphery of the position of the selected laser radar as far as possible, the terrain similarity is consistent with the terrain similarity at the periphery of the unit, namely the difference between the terrain complexity RIX at the periphery of the selected laser radar and the terrain similarity at the periphery of the unit is less than 5. Because the terrain similarity of the laser radar and the machine position is consistent, the wind shear reflected by each height of the laser radar represents the wind shear of the incoming flow of the machine set.
In the embodiment of the invention, the laser radar can be set in the field or in a scene with similar complexity, so as to ensure that the obtained extreme negative shear value is accurate.
Step S40: and carrying out target evaluation region tower scanning risk evaluation based on the extreme negative shear value of each wind turbine and a preset extreme negative shear value threshold value.
Specifically, acquiring an extreme negative shear value judgment rule based on a knowledge graph library, and acquiring an extreme negative shear value threshold value of each height position of the wind turbine generator based on the judgment rule; comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping; and traversing tower scanning risk judging results of all the wind turbines to obtain tower scanning risk assessment results of the target assessment area.
In the embodiment of the invention, the wind turbine generator system construction standards exist, the standards can be pre-stored in a preset knowledge graph base in advance, and the extreme negative shear value judgment rule is directly acquired based on the knowledge graph base when the judgment is carried out subsequently. For example, the EWS wind condition determination formula for IEC:
wherein, Designing an extremely negative shear value for the z-height; /(I)The hub height of the wind turbine generator system; z is the test height; /(I)Wind speed is referenced for hub height.
Based on the extreme negative shear value determination rule, a designed extreme negative shear value for each height position may be obtained as an extreme negative shear value threshold. Comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping. According to the scheme, the position with the risk of scanning the tower can be identified in the target area, so that accurate risk assessment of scanning the tower can be conveniently carried out.
Furthermore, the method provided by the scheme of the invention can be applied to the beginning of wind turbine generator set construction, and the risk assessment of tower sweeping at each position point is carried out in a target construction area, so that the position with high risk is screened out before construction, and the construction safety is ensured.
In the embodiment of the invention, the quick systematic wind resource risk assessment is carried out on the machine position aiming at the wind resource condition of the machine set operation. Aiming at the problem of whether the wind power plant set is provided with the blade tower sweeping, a quick evaluation method for the risk of the wind power plant set tower sweeping is formed based on SCADA data and topography, effective technical support is provided for the wind turbine generator set safety evaluation method under the non-IEC working condition, potential safety hazards of the wind turbine generator set are reduced, and risks of the wind turbine generator set are reduced.
Fig. 3 is a system structure diagram of a risk assessment system for wind turbine generator system tower sweeping according to an embodiment of the invention. As shown in fig. 3, an embodiment of the present invention provides a risk assessment system for tower sweeping of a wind turbine, where the system includes:
the collecting unit is used for collecting operation retention information of each wind turbine in the target evaluation area and preprocessing the operation retention information.
Specifically, the topography factors are introduced into the risk assessment of the tower sweeping, so that the topography information of the building position of the wind turbine is required to be acquired besides the operation parameter information of the wind turbine when the data acquisition is carried out by the scheme.
Preferably, the operation retention information of each wind turbine generator includes: historical operation data of the wind turbine and setting state data of the wind turbine; the historical operation data of the wind turbine generator set comprises: one or more of wind direction information, wind speed information, generator rotating speed and actual power information of each wind turbine generator at each sampling moment; the setting state information of the wind turbine generator comprises: one or more of pitch angle, nacelle position, and nacelle position terrain information.
In the embodiment of the invention, the pitch angle data is used for monitoring whether to open or close the blade; the cabin position and the wind direction jointly determine the incoming wind direction; wind speed is used to calculate turbulence; the rotating speed and the actual power of the generator illustrate the power generation state of the fan at the moment.
Further, the preprocessing the operation retention information includes: based on the data type, carrying out data classification on the operation retention information to obtain a plurality of data sets; and in each data set, invalid data identification is carried out, and rejection processing is carried out on the invalid data, so that operation retention information after pretreatment is completed is obtained.
In the embodiment of the invention, after the data acquisition is completed, the data type (the historical operation data of the wind turbine and the setting state data of the wind turbine) is required to be subjected to data classification to obtain a plurality of data sets, and the corresponding item processing is conveniently carried out through different data sets, so that the condition that the whole data set needs to be traversed every time of data acquisition is avoided, and the data processing efficiency is improved. Preferably, the invalid data identification includes identifying blade angle opening data, data with the rotation speed of the generator being 0 or data with the actual power being 0, and eliminating the invalid data to reduce the volume of the data.
Preferably, the method and the system take SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control system) data of the wind turbine as operation retention information for data acquisition. The SCADA system is a DCS and electric power automatic monitoring system based on a computer; the method has wide application fields, and can be applied to various fields such as data acquisition and monitoring control, process control and the like in the fields of electric power, metallurgy, petroleum, chemical industry, fuel gas, railways and the like. Among the power systems, the SCADA system is most widely used and the technology development is most mature. The remote control system plays an important role in a remote control system, and can monitor and control on-site operation equipment to realize various functions such as data acquisition, equipment control, measurement, parameter adjustment, various signal alarms and the like, namely a four-remote function. RTU (remote terminal unit), FTU (feeder terminal unit) is an important component thereof. Plays a quite important role in the comprehensive automation construction of the transformer substation.
In the embodiment of the invention, the data acquisition is performed based on the SCADA system, so that the data acquisition system constructed by the existing scheme can be directly utilized to perform data acquisition, a new acquisition system is not required to be reconstructed, and the system upgrading cost is reduced. On the other hand, by utilizing the characteristic of full data acquisition of the SCADA system, the accuracy of data acquisition can be ensured, and the second-level time sequence data of the wind turbine generator can be acquired through the SCADA system so as to adapt to the characteristic of changeable wind field conditions and ensure the accuracy of subsequent evaluation results.
Of course, besides SCADA data, any other data acquisition system capable of acquiring wind turbine running information and topographic information can be used as another real-time mode of the scheme of the invention, and the data acquisition system falls into the protection scope of the scheme of the invention.
And the correction unit is used for correcting the preprocessed operation retention information to obtain wind direction information of each wind turbine generator.
Specifically, determining initial wind direction information of each wind turbine generator based on the preprocessed operation retention information; determining wind direction deviation values of the positions of the wind turbines based on the initial wind direction information of the wind turbines and the main direction information acquired by a wind measuring tower at the corresponding sampling time; and correcting the preprocessed operation retention information based on the wind direction deviation value of each wind turbine position to obtain the actual incoming flow position of each wind turbine position as wind direction information of each wind turbine.
In the embodiment of the invention, because of the influence of the topography factors or when the fan is installed, the fan does not point to the north direction, the wind direction data of the unit needs to be corrected so as to ensure the accuracy of the incoming flow direction of the corresponding point position. Based on this, the present approach corrects the collected incoming flow direction in order to perform subsequent negative shear predictions based on the accurate incoming flow direction.
Based on this, the corresponding correction rule is:
Actual incoming flow wind direction= (nacelle position+wind direction data) 57.3+father device
The cabin position and wind direction data represent collected incoming wind directions, and the incoming wind directions are simulated through specific construction positions of the cabin and wind direction positions collected by the wind towers. The degree is calculated according to the main wind direction of the anemometer tower, and the calculation formula is as follows:
is defined = wind tower main direction-nacelle position main direction.
The simulation unit is used for performing operation scene simulation on each wind turbine based on the preprocessed operation retention information and wind direction information of each wind turbine to obtain extreme negative shear values of each wind turbine.
Specifically, the position of each wind turbine generator and the topographic information of the corresponding position are read based on the preprocessed operation retention information; based on the position of each wind turbine generator and the topographic information of the corresponding position, obtaining the area information and the topographic information of the whole target evaluation area as a target scene; and constructing a three-dimensional geographic model based on the target scene and a preset three-dimensional modeling algorithm to obtain a virtual three-dimensional scene of the target evaluation area.
In the embodiment of the invention, the scheme needs to perform simulation scene construction aiming at the topographic parameters, and three-dimensional geographic model construction is performed through three-dimensional modeling algorithms such as GIS (geographic information system) and the like so as to obtain a three-dimensional scene instead of a target area, and wind field condition simulation is performed in the three-dimensional scene, so that topographic factors can be brought into a reference sequence, and simulation accuracy is ensured.
In one possible embodiment, a circle is drawn with the center point of the wind farm as the origin and 1.4 times the distance between the center point and the farthest fan as the radius, and the area is used as the field simulation area. And the mesh division is carried out by adopting the mesh processing software ICEM software matched with FLUENT, the 0-360 DEG direction is divided according to the sector interval of 30 DEG, and the simulation is carried out on the sector directions in sequence.
Further, the rule for obtaining the simulated extreme negative shear value of each wind turbine corresponding to each sector based on the simulation result is as follows:
wherein, A wind shear simulation value of the height of the position h of the wind turbine in the i direction; /(I)A wind shear analog value of h height at a wind tower point in the i direction; /(I)The measured value of wind shear of h height at the position of the wind tower point in the i direction; /(I)The wind shear result value of the height of the position h of the wind turbine in the i direction; /(I)And the simulated extreme negative shear value of the corresponding wind turbine generator set.
Preferably, the screening out the wind turbine generator to be calibrated, and based on the topographic parameter information fed back by the laser radar preset by the calibration target, calibrating and/or correcting the simulated extreme negative shear value of the wind turbine generator to be calibrated, to obtain the extreme negative shear value of each wind turbine generator, including: respectively comparing wind direction information of each wind turbine generator based on the simulation result with wind direction information of each wind turbine generator obtained by correction, and selecting the corresponding wind turbine generator as a wind turbine generator to be corrected when the deviation value of the wind direction information of each wind turbine generator exceeds a preset angle deviation threshold value; performing laser radar presetting at each position or simulation position of the wind turbine generator to be calibrated, performing terrain parameter acquisition through the laser radar, and taking a wind shear value measured by the laser radar as a wind shear value of the corresponding wind turbine generator when the deviation between the terrain parameter information acquired by the laser radar and the terrain parameter information of the position of the corresponding wind turbine generator is smaller than a preset terrain deviation threshold; if the deviation between the wind shear value obtained by each wind turbine generator based on the laser radar and the wind shear result value obtained based on the simulation result is smaller than a wind shear deviation threshold value, the wind shear value obtained based on the laser radar is used as the wind shear result value to correct the simulation extreme negative shear value, and the extreme negative shear value of the corresponding wind turbine generator is obtained; otherwise, the simulated extreme negative shear value is directly used as the extreme negative shear value of the corresponding wind turbine generator.
In one possible embodiment, the machine site wind direction is compared with the SCADA corrected wind direction, and if the main wind direction deviates by more than 30 degrees, further lidar compensation is required. When the laser radar wind measurement is carried out, shielding exists at the periphery of the position of the selected laser radar as far as possible, the terrain similarity is consistent with the terrain similarity at the periphery of the unit, namely the difference between the terrain complexity RIX at the periphery of the selected laser radar and the terrain similarity at the periphery of the unit is less than 5. Because the terrain similarity of the laser radar and the machine position is consistent, the wind shear reflected by each height of the laser radar represents the wind shear of the incoming flow of the machine set.
In the embodiment of the invention, the laser radar can be set in the field or in a scene with similar complexity, so as to ensure that the obtained extreme negative shear value is accurate.
And the evaluation unit is used for carrying out target evaluation area tower scanning risk evaluation based on the extreme negative shear value of each wind turbine and a preset extreme negative shear value threshold value.
Specifically, acquiring an extreme negative shear value judgment rule based on a knowledge graph library, and acquiring an extreme negative shear value threshold value of each height position of the wind turbine generator based on the judgment rule; comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping; and traversing tower scanning risk judging results of all the wind turbines to obtain tower scanning risk assessment results of the target assessment area.
In the embodiment of the invention, the wind turbine generator system construction standards exist, the standards can be pre-stored in a preset knowledge graph base in advance, and the extreme negative shear value judgment rule is directly acquired based on the knowledge graph base when the judgment is carried out subsequently. For example, the EWS wind condition determination formula for IEC:
wherein, Designing an extremely negative shear value for the z-height; /(I)The hub height of the wind turbine generator system; z is the test height; /(I)Wind speed is referenced for hub height.
Based on the extreme negative shear value determination rule, a designed extreme negative shear value for each height position may be obtained as an extreme negative shear value threshold. Comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping. According to the scheme, the position with the risk of scanning the tower can be identified in the target area, so that accurate risk assessment of scanning the tower can be conveniently carried out.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium is stored with instructions, and when the computer is operated on the computer, the computer is enabled to execute the wind turbine generator tower sweeping risk assessment method.
Those skilled in the art will appreciate that all or part of the steps in a method for implementing the above embodiments may be implemented by a program stored in a storage medium, where the program includes several instructions for causing a single-chip microcomputer, chip or processor (processor) to perform all or part of the steps in a method according to the embodiments of the invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The alternative embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the embodiments of the present invention are not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solutions of the embodiments of the present invention within the scope of the technical concept of the embodiments of the present invention, and all the simple modifications belong to the protection scope of the embodiments of the present invention. In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the various possible combinations of embodiments of the invention are not described in detail.
In addition, any combination of the various embodiments of the present invention may be made, so long as it does not deviate from the idea of the embodiments of the present invention, and it should also be regarded as what is disclosed in the embodiments of the present invention.
Claims (11)
1. The wind turbine generator system tower sweeping risk assessment method is characterized by comprising the following steps:
collecting operation retention information of each wind turbine in a target evaluation area, and preprocessing the operation retention information;
correcting the operation retention information after pretreatment to obtain wind direction information of each wind turbine generator;
Based on the preprocessed operation retention information and wind direction information of each wind turbine, performing operation scene simulation on each wind turbine to obtain extreme negative shear values of each wind turbine;
and carrying out target evaluation area tower scanning risk evaluation based on the extreme negative shear value of each wind turbine.
2. The method of claim 1, wherein the operation-preserving information of each wind turbine includes:
historical operation data of the wind turbine and setting state data of the wind turbine;
the historical operation data of the wind turbine generator set comprises:
one or more of wind direction information, wind speed information, generator rotating speed and actual power information of each wind turbine generator at each sampling moment;
The setting state information of the wind turbine generator comprises:
One or more of pitch angle, nacelle position, and nacelle position terrain information.
3. The method of claim 1, wherein the preprocessing the operation-preserving information comprises:
based on the data type, carrying out data classification on the operation retention information to obtain a plurality of data sets;
And in each data set, invalid data identification is carried out, and rejection processing is carried out on the invalid data, so that operation retention information after pretreatment is completed is obtained.
4. The method of claim 1, wherein the correcting the preprocessed operation-preserving information to obtain wind direction information of each wind turbine includes:
determining initial wind direction information of each wind turbine generator based on the preprocessed operation retention information;
determining wind direction deviation values of the positions of the wind turbines based on the initial wind direction information of the wind turbines and the main wind direction information acquired by the wind measuring tower at the corresponding sampling moment;
and correcting the preprocessed operation retention information based on the wind direction deviation value of each wind turbine position to obtain the actual incoming flow wind direction of each wind turbine position as wind direction information of each wind turbine.
5. The method according to any one of claims 1 to 4, wherein the performing an operation scene simulation on each wind turbine based on the preprocessed operation retention information and wind direction information of each wind turbine to obtain an extreme negative shear value of each wind turbine includes:
Based on the preprocessed operation retention information, constructing a three-dimensional geographic model of the target evaluation area;
dividing the constructed three-dimensional geographic model into a plurality of sectors by taking the center of the model as the center of a circle, and respectively performing wind field simulation in each sector;
Based on the simulation result, obtaining a simulated extreme negative shear value of each wind turbine corresponding to each sector;
Screening out wind turbines to be calibrated, and calibrating and/or correcting the simulated extreme negative shear value of the wind turbines to be calibrated based on the topographic parameter information fed back by the laser radar preset by the calibration target to obtain the extreme negative shear value of each wind turbine.
6. The method of claim 5, wherein constructing the three-dimensional geographic model of the target evaluation area based on the preprocessed run-time information comprises:
Reading the position of each wind turbine generator set and the topographic information of the corresponding position based on the preprocessed operation retention information;
Based on the position of each wind turbine generator and the topographic information of the corresponding position, obtaining the area information and the topographic information of the whole target evaluation area as a target scene;
and constructing a three-dimensional geographic model based on the target scene and a preset three-dimensional modeling algorithm to obtain a virtual three-dimensional scene of the target evaluation area.
7. The method of claim 5, wherein the rule for obtaining the simulated extreme negative shear value for each wind turbine under each sector based on the simulation result is:
wherein, A wind shear simulation value of the height of the position h of the wind turbine generator on the ith sector;
the wind shear simulation value of h height at the wind measuring tower point position on the ith sector;
The measured value of the wind shear of the h height at the wind tower point position on the ith sector;
the wind shear result value of the height of the position h of the wind turbine generator on the ith sector is obtained;
And the simulated extreme negative shear value of the corresponding wind turbine generator set.
8. The method according to claim 5, wherein the screening out the wind turbines to be calibrated, and calibrating and/or correcting the simulated extreme negative shear value of the wind turbines to be calibrated based on the topographic parameter information fed back by the laser radar preset by the calibration target, to obtain the extreme negative shear value of each wind turbine, includes:
Respectively comparing wind direction information of each wind turbine generator based on the simulation result with wind direction information of each wind turbine generator obtained by correction, and selecting the corresponding wind turbine generator as a wind turbine generator to be corrected when the deviation value of the wind direction information of each wind turbine generator exceeds a preset angle deviation threshold value;
performing laser radar presetting at the actual position or the simulation position of each wind turbine generator to be calibrated, performing terrain parameter acquisition through the laser radar, and taking the wind shear value measured by the laser radar as the wind shear value of the corresponding wind turbine generator when the deviation between the terrain parameter information acquired by the laser radar and the terrain parameter information of the position of the corresponding wind turbine generator is smaller than a preset terrain deviation threshold;
If the deviation between the wind shear value obtained by each wind turbine generator based on the laser radar and the wind shear result value obtained based on the simulation result is larger than a wind shear deviation threshold value, the wind shear value obtained based on the laser radar is used as the wind shear result value to correct the simulation extreme negative shear value, and the extreme negative shear value of the corresponding wind turbine generator is obtained; on the contrary, the method comprises the steps of,
The simulated extreme negative shear value is directly taken as the extreme negative shear value of the corresponding wind turbine.
9. The method of claim 1, wherein performing a target assessment area tower scanning risk assessment based on extreme negative shear values for each wind turbine includes:
Acquiring an extreme negative shear value judgment rule based on a knowledge graph base, and acquiring an extreme negative shear value threshold value of each height position of the wind turbine generator set based on the judgment rule;
Comparing the extreme negative shear value of each wind turbine unit with the extreme negative shear value threshold value of the corresponding wind turbine unit, and judging that the corresponding wind turbine unit has a tower sweeping risk if the extreme negative shear value is larger than the corresponding extreme negative shear value threshold value; otherwise, judging that the corresponding wind turbine generator does not have the risk of tower sweeping;
And traversing tower scanning risk judging results of all the wind turbines to obtain tower scanning risk assessment results of the target assessment area.
10. A wind turbine generator system tower scanning risk assessment system, the system comprising:
the collecting unit is used for collecting operation retention information of each wind turbine in the target evaluation area and preprocessing the operation retention information;
the correction unit is used for correcting the preprocessed operation retention information to obtain wind direction information of each wind turbine generator;
The simulation unit is used for performing operation scene simulation on each wind turbine based on the preprocessed operation retention information and wind direction information of each wind turbine to obtain extreme negative shear values of each wind turbine;
and the evaluation unit is used for carrying out target evaluation area tower scanning risk evaluation based on the extreme negative shear value of each wind turbine.
11. A computer readable storage medium having instructions stored thereon, which when run on a computer cause the computer to perform the wind turbine tower scanning risk assessment method of any of claims 1-9.
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