Blade icing monitoring method and device of wind generating set and storage medium

Abstract

The invention provides a blade icing monitoring method and device of a wind generating set and a storage medium, the wind generating set comprises a variable pitch system, the variable pitch system comprises a power device, and the blade icing monitoring method comprises the steps that current working parameters of the power device and the theoretical blade root load of the wind generating set during variable pitch are obtained; the current blade root load of the wind generating set is determined according to the current working parameters; and according to the current blade root load and the theoretical blade root load, blade icing information of the wind generating set is determined, and the blade icing information is used for representing the possibility of blade icing. According to the invention, the current blade root load is equivalently determined according to the current working current of the power device, and then the possibility of icing of the blade is speculated in combination with the theoretical blade root load, so that additional purchase of equipment is not needed, the requirement on the computing power of the controller is low, and the implementation can be realized by using a conventional master control PLC; therefore, the reliability and the accuracy of blade icing monitoring are improved under the condition that the cost of a unit is not increased.

Description

Technical Field

[0001] The present disclosure relates to the field of wind power generation, and more specifically, to a blade icing monitoring method, device and storage medium for a wind generator set. Background Art

[0002] Blades are an important part of wind turbines. Blade icing will reduce the life of wind turbine blades and pose a risk of blade breakage. Blade icing will also directly affect the output of wind turbines. Therefore, in the context of reducing costs and increasing efficiency, higher requirements are placed on the accuracy, effectiveness and economy of blade icing monitoring.

[0003] At present, the main methods for blade icing monitoring include sensor monitoring, video monitoring, power curve matching, and SCADA (Supervisory Control And Data Acquisition) big data feature extraction. Among them, sensor monitoring and video monitoring require additional equipment purchases, which increases the cost of wind turbines; and the main control PLC (Programmable Logic Controller) often cannot meet the computing power requirements of big data feature extraction. Therefore, at present, for wind power generation main control, the main method of blade icing monitoring is power matching, but this method has problems with low reliability and accuracy. Summary of the invention

[0004] Therefore, how to improve the reliability and accuracy of blade icing monitoring without increasing the cost of the unit is crucial to reducing costs and increasing efficiency of wind turbines.

[0005] In a general aspect, a method for monitoring blade icing of a wind turbine is provided, wherein the wind turbine comprises a pitch control system, wherein the pitch control system comprises a power unit, and the method for monitoring blade icing comprises: acquiring current operating parameters of the power unit and a theoretical blade root load of the wind turbine during pitch control; determining a current blade root load of the wind turbine according to the current operating parameters; and determining blade icing information according to the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of blade icing of the wind turbine.

[0006] Optionally, determining the current blade root load of the wind turbine generator set according to the current operating parameters includes: obtaining a torque conversion relationship and a pitch system transmission ratio of the power device, wherein the torque conversion relationship is used to represent a conversion relationship between the operating parameters of the power device and the output torque; determining a current output torque corresponding to the current operating parameters according to the current operating parameters and the torque conversion relationship; determining the current blade root load according to the current output torque and the pitch system transmission ratio.

[0007] Optionally, the torque conversion relationship is obtained by the following steps: performing a load characteristic test on the power device to obtain multiple sets of corresponding working parameters and output torques; performing fitting processing on the multiple sets of corresponding working parameters and output torques to obtain the torque conversion relationship.

[0008] Optionally, the blade icing monitoring method also includes: obtaining blade monitoring information determined by at least one blade operation monitoring system, wherein the at least one blade operation monitoring system is used to monitor the operation of the blades of the wind turbine generator set, and the blade monitoring information is used to indicate the possibility of blade icing of the wind turbine generator set; and correcting the blade icing information in combination with the blade monitoring information.

[0009] Optionally, determining the blade icing information based on the current blade root load and the theoretical blade root load includes: determining a ratio of the current blade root load to the theoretical blade root load, recorded as a load ratio; and determining the blade icing information based on the load ratio and at least one load ratio threshold.

[0010] Optionally, the wind turbine generator set includes at least three blades, wherein determining the blade icing information based on the current blade root load and the theoretical blade root load includes: performing statistical processing on the current blade root loads corresponding to each of the at least three blades to obtain an impeller imbalance, wherein the impeller imbalance is used to represent the difference between the current blade root loads corresponding to each of the at least three blades; and determining the blade icing information based on the impeller imbalance and at least one imbalance threshold.

[0011] Optionally, the blade icing monitoring method further includes: when the blade icing information indicates that the possibility of blade icing exceeds an alarm threshold, outputting blade icing alarm information, wherein the blade icing alarm information is used to prompt that the blade may have been frozen; and / or when the blade icing information indicates that the possibility of blade icing exceeds a shutdown threshold, outputting shutdown prompt information or a shutdown instruction, wherein the shutdown prompt information is used to prompt to stop operating the wind turbine generator set, and the shutdown instruction is used to control the wind turbine generator set to stop operating.

[0012] Optionally, the blade icing monitoring method also includes: storing the current blade root load determined each time in association with corresponding time information to obtain a historical blade root load sequence; determining a predicted blade root load at a future target moment based on the current blade root load and a load prediction model, wherein the load prediction model is determined based on the historical blade root load sequence; determining predicted blade icing information based on the predicted blade root load and the theoretical blade root load, wherein the predicted blade icing information is used to indicate the possibility that the blades of the wind turbine generator set are expected to be frozen at the future target moment.

[0013] In another general aspect, a blade icing monitoring device for a wind turbine is provided, wherein the wind turbine comprises a pitch system, wherein the pitch system comprises a power unit, and the blade icing monitoring device comprises: an acquisition unit configured to acquire current operating parameters of the power unit and a theoretical blade root load of the wind turbine during pitch change; a determination unit configured to determine a current blade root load of the wind turbine based on the current operating parameters; the determination unit is further configured to determine blade icing information based on the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of blade icing of the wind turbine.

[0014] Optionally, the determination unit is further configured to: obtain the torque conversion relationship and the pitch system transmission ratio of the power device, wherein the torque conversion relationship is used to represent the conversion relationship between the working parameters of the power device and the output torque; determine the current output torque corresponding to the current working parameters according to the current working parameters and the torque conversion relationship; determine the current blade root load according to the current output torque and the pitch system transmission ratio.

[0015] Optionally, the torque conversion relationship is obtained by the following steps: performing a load characteristic test on the power device to obtain multiple sets of corresponding working parameters and output torques; performing fitting processing on the multiple sets of corresponding working parameters and output torques to obtain the torque conversion relationship.

[0016] Optionally, the acquisition unit is also configured to acquire blade monitoring information determined by at least one blade operation monitoring system, wherein the at least one blade operation monitoring system is used to monitor the operation condition of the blades of the wind turbine generator set, and the blade monitoring information is used to indicate the possibility of blade icing of the wind turbine generator set; the determination unit is further configured to correct the blade icing information in combination with the blade monitoring information.

[0017] Optionally, the determination unit is further configured to: determine a ratio of the current blade root load to the theoretical blade root load, recorded as a load ratio; and determine the blade icing information according to the load ratio and at least one load ratio threshold.

[0018] Optionally, the wind turbine generator set includes at least three blades, and the determination unit is further configured to: perform statistical processing on current blade root loads corresponding to each of the at least three blades to obtain an impeller imbalance, wherein the impeller imbalance is used to represent the difference between current blade root loads corresponding to each of the at least three blades; and determine the blade icing information based on the impeller imbalance and at least one imbalance threshold.

[0019] Optionally, the blade icing monitoring device also includes an output unit, which is configured to: output blade icing alarm information when the blade icing information indicates that the possibility of blade icing exceeds an alarm threshold, wherein the blade icing alarm information is used to prompt that the blade may have been frozen; and / or output shutdown prompt information or a shutdown instruction when the blade icing information indicates that the possibility of blade icing exceeds a shutdown threshold, wherein the shutdown prompt information is used to prompt to stop operating the wind turbine, and the shutdown instruction is used to control the wind turbine to stop operating.

[0020] Optionally, the blade icing monitoring device also includes: a storage unit, configured to store the current blade root load determined each time in association with corresponding time information to obtain a historical blade root load sequence; a prediction unit, configured to determine the predicted blade root load at a future target moment based on the current blade root load and a load prediction model, wherein the load prediction model is determined based on the historical blade root load sequence; the determination unit is further configured to determine predicted blade icing information based on the predicted blade root load and the theoretical blade root load, wherein the predicted blade icing information is used to indicate the possibility that the blades of the wind turbine are expected to freeze at the future target moment.

[0021] In another general aspect, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute a blade icing monitoring method for a wind turbine according to an embodiment of the present disclosure.

[0022] In another general aspect, a computer device is provided, comprising: at least one processor; and at least one memory storing computer executable instructions, wherein the computer executable instructions, when executed by the at least one processor, cause the at least one processor to execute a blade icing monitoring method for a wind turbine generator set according to an embodiment of the present disclosure.

[0023] The present disclosure proposes a blade icing monitoring method, device and storage medium for a wind turbine generator set. The current blade root load is determined based on the current working current of the power unit, and then the possibility of blade icing is inferred in combination with the theoretical blade root load. No additional equipment is required, and the computing power requirement for the controller is low. It can be achieved using a conventional main control PLC, thereby improving the reliability and accuracy of blade icing monitoring without increasing the cost of the unit, helping to reduce costs and increase efficiency of wind turbine generator sets and ensure safe operation of the unit. In addition, the current blade root load obtained in the middle can also be saved for use by other related functions of the wind turbine generator set, which helps to improve data utilization and save computing power.

[0024] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and other objects and features of the present invention will become more apparent through the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0026] Figure 1 is a flow chart showing a method for monitoring blade icing of a wind turbine generator set according to an embodiment of the present disclosure;

[0027] Figure 2 is a schematic diagram showing a fitting process of the output torque of a pitch motor and the current of the pitch motor according to a specific embodiment of the present disclosure;

[0028] Figure 3 is a schematic flow chart showing a method for monitoring blade icing of a wind turbine generator set according to a specific embodiment of the present disclosure;

[0029] Figure 4 is a block diagram showing a blade icing monitoring device of a wind turbine generator set according to an embodiment of the present disclosure;

[0030] Figure 5 is a block diagram illustrating a computer device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0031] The following specific embodiments are provided to help the reader obtain a comprehensive understanding of the methods, devices and / or systems described herein. However, after understanding the disclosure of the present application, various changes, modifications and equivalents of the methods, devices and / or systems described herein will be clear. For example, the order of operations described herein is only an example and is not limited to those orders set forth herein, but can be changed as will be clear after understanding the disclosure of the present application, except for operations that must occur in a specific order. In addition, for greater clarity and simplicity, the description of features known in the art may be omitted.

[0032] The features described herein can be implemented in different forms and should not be construed as being limited to the examples described herein. Rather, the examples described herein have been provided to illustrate only some of the many possible ways to implement the methods, devices, and / or systems described herein, which will be clear after understanding the disclosure of the present application.

[0033] As used herein, the term "and / or" includes any one of the associated listed items and any combination of any two or more.

[0034] Although terms such as "first", "second", and "third" may be used herein to describe various members, components, regions, layers, or portions, these members, components, regions, layers, or portions should not be limited by these terms. Instead, these terms are only used to distinguish one member, component, region, layer, or portion from another member, component, region, layer, or portion. Therefore, without departing from the teachings of the examples described herein, the first member, first component, first region, first layer, or first portion referred to in the examples may also be referred to as the second member, second component, second region, second layer, or second portion.

[0035] In the specification, when an element (such as a layer, a region, or a substrate) is described as being “on”, “connected to”, or “coupled to” another element, the element may be directly “on”, “connected to”, or “coupled to” another element, or one or more other elements may be present therebetween. Conversely, when an element is described as being “directly on”, “directly connected to”, or “directly coupled to” another element, there may be no other elements present therebetween.

[0036] The terms used herein are only used to describe various examples and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. The terms "comprise", "include" and "have" indicate the presence of the described features, quantities, operations, components, elements and / or combinations thereof, but do not exclude the presence or addition of one or more other features, quantities, operations, components, elements and / or combinations thereof.

[0037] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by a person of ordinary skill in the art to which the present disclosure belongs after understanding the present disclosure. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0038] Furthermore, in the description of examples, when it is considered that a detailed description of a well-known related structure or function would cause vague interpretation of the present disclosure, such a detailed description will be omitted.

[0039] The following will be combined Figures 1 to 5 The present invention introduces a blade icing monitoring method, device and storage medium for a wind turbine generator set provided by an embodiment of the present invention.

[0040] An embodiment of one aspect of the present disclosure provides a method for monitoring blade icing of a wind turbine generator set. The wind turbine generator set includes a pitch control system, and the pitch control system includes a power device. Figure 1 The flowchart of the blade icing monitoring method of the wind turbine generator set according to the embodiment of the present disclosure is shown. The execution subject of the method can be the existing main control PLC of the wind turbine generator set, or the field-level controller of the entire wind farm, or an additional computing and control device.

[0041] Reference Figure 1 In step S101, the current operating parameters of the power device and the theoretical blade root load of the wind turbine generator set when the pitch is changed are obtained.

[0042] The working parameters of the power device are parameters that reflect the working state of the power device and can be directly detected. For example, the power device is usually a motor, and the corresponding working parameters can be current. It should be understood that for other power devices that appear after the scheme of the present disclosure, the working parameters can be selected according to actual conditions. Since the specific structure of the power device does not affect the implementation of the method of the present disclosure, when the method of the present disclosure is used to monitor blade icing of wind turbines with other power devices, it also falls within the protection scope of the present disclosure. The current working parameter is the current real-time detection value of the working parameter. It should be understood that this real-time nature includes delays that are technically within a reasonable range, rather than real-time in a strict sense.

[0043] The theoretical blade root load of a wind turbine during pitch change indicates the load on the blade root when the turbine is operating normally and changing pitch, which is obtained through theoretical calculation during turbine design. It reflects the load when the blade is not frozen under ideal conditions and can be used as a reference for determining whether the blade is frozen in subsequent steps. As an example, this calculation can be performed using design software such as bladed.

[0044] In step S102, the current blade root load of the wind turbine generator set is determined according to the current working parameters. The current blade root load represents the load currently applied to the blade root by the pitch system, and the current working parameters reflect the actual working state of the power device of the pitch system, and are related to the driving energy ultimately output by the pitch system. This driving energy ultimately acts on the blade root, and is also related to the current blade root load. When the blades are frozen, the blades may become heavier due to ice coating, and there may also be ice at the blade root that limits the rotation of the blades, so the load actually applied to the blade root by the pitch system is related to the icing condition of the blades. Therefore, this step can reflect the icing condition of the blades by determining the current blade root load using the current working parameters.

[0045] In step S103, blade icing information is determined based on the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of blade icing of the wind turbine. The current blade root load determined in step S102 is only an isolated absolute value. By introducing the theoretical blade root load as a reference, it is helpful to finally determine the possibility of blade icing, obtain blade icing information, and realize blade icing monitoring.

[0046] According to the blade icing monitoring method of the wind turbine generator set in the embodiment of the present disclosure, the current blade root load is determined based on the current working current of the power device, and then the possibility of blade icing is inferred in combination with the theoretical blade root load. No additional equipment is required, and the computing power requirement of the controller is low. It can be implemented using a conventional main control PLC, thereby improving the reliability and accuracy of blade icing monitoring without increasing the cost of the unit, helping to reduce costs and increase efficiency of wind turbine generator sets and ensure safe operation of the unit. In addition, the current blade root load obtained in the middle can also be saved for use by other related functions of the wind turbine generator set, which helps to improve data utilization and save computing power.

[0047] Optionally, step S102 includes: obtaining the torque conversion relationship of the power device and the transmission ratio of the pitch system, wherein the torque conversion relationship is used to represent the conversion relationship between the working parameters of the power device and the output torque; determining the current output torque corresponding to the current working parameters according to the current working parameters and the torque conversion relationship; determining the current blade root load according to the current output torque and the pitch system transmission ratio. As an example, the product of the current output torque and the pitch system transmission ratio can be determined as the current blade root load. Considering that the driving energy output by the pitch system is used to drive the blades to rotate, the driving energy can be quantitatively represented in the form of a relatively stable torque value, and its size is also related to the working parameters and the blade root load generated thereby. In addition, in addition to the power device that provides power, the pitch system often also includes an intermediate transmission device, such as a reducer, which can reduce the speed output by the power device and amplify the output torque. By first determining the current output torque corresponding to the current working parameters for a single power unit, and then extending it to the entire variable pitch system, and adjusting the current output torque in combination with the variable pitch system transmission ratio, the current blade root load that the variable pitch system ultimately acts on the blade root can be obtained, thus achieving reliable calculation of the current blade root load. Of course, similar to the current blade root load, the current output torque and other data described later can also be saved as needed for use by other related functions of the wind turbine generator set.

[0048] As an example, the torque conversion relationship is obtained by the following steps: performing a load characteristic test on the power unit to obtain multiple sets of corresponding working parameters and output torques; performing fitting processing on the multiple sets of corresponding working parameters and output torques to obtain the torque conversion relationship. By performing a load characteristic test and performing fitting processing on the obtained data, such as performing linear fitting, a relatively reliable torque conversion relationship can be obtained, which helps to achieve reliable calculation of the current blade root load. It should be understood that the step of determining the torque conversion relationship is usually performed before blade icing monitoring, the load characteristic test can be performed by a technician, the fitting processing can be performed by a computer device, and it can be an external device independent of the execution body of the blade icing monitoring method.

[0049] Next, step S103 is described in further detail.

[0050] In some embodiments, optionally, the blade icing monitoring method according to the embodiment of the present disclosure further includes: when the blade icing information indicates that the possibility of blade icing exceeds the alarm threshold, outputting blade icing alarm information, wherein the blade icing alarm information is used to prompt that the blade may have been frozen; and / or when the blade icing information indicates that the possibility of blade icing exceeds the shutdown threshold, outputting shutdown prompt information or shutdown instructions, wherein the shutdown prompt information is used to prompt the wind turbine to stop running, and the shutdown instruction is used to control the wind turbine to stop running. By outputting corresponding information under different icing risks, the monitoring results can be externalized and output in time, which helps to reduce the harm caused by blade icing. Specifically, by outputting blade icing alarm information when it is speculated that the blade may have been frozen, it can prompt the staff to verify in time, arrange subsequent processing solutions, eliminate risks, and help improve the unit output and extend the life of the blade. By outputting shutdown prompt information to prompt the staff to shut down when it is speculated that the blade may be severely frozen, or directly outputting a shutdown instruction to control the unit to stop running, it can be shut down in time, reduce the risk of major hazards (such as blade breakage), and ensure safe operation. As an example, only one of the above situations can be configured, or both of the above situations can be configured at the same time, and the present disclosure does not limit this. For the latter, it should be understood that the alarm threshold will be less than the shutdown threshold. At this time, the two output information can be associated. When the possibility of blade icing exceeds the shutdown threshold, only the shutdown prompt information or shutdown instruction is output, and the blade icing alarm information is no longer output; the two information can also be output independently, which means that when the possibility of blade icing exceeds the shutdown threshold, it will also exceed the alarm threshold at the same time, and the blade icing alarm information and the shutdown prompt information or shutdown instruction are output at the same time. The present disclosure also does not limit this.

[0051] It should also be noted that when executing the blade icing monitoring method according to the embodiment of the present disclosure, the blade icing information can be designed as a value calculated based on the current blade root load and the theoretical blade root load, and the specific values ​​of the alarm threshold and the shutdown threshold are configured in the program of the method, and the size relationship between the blade icing information and the alarm threshold and / or the shutdown threshold is directly compared; the blade icing information can also be designed as an identifier representing yes or no, for example, 00 is used to indicate that the possibility of blade icing does not exceed the alarm threshold, 01 is used to indicate that the possibility of blade icing exceeds the alarm threshold, 10 is used to indicate that the possibility of blade icing does not exceed the shutdown threshold, and 11 is used to indicate that the possibility of blade icing exceeds the shutdown threshold. At this time, since the alarm threshold and / or the shutdown threshold will not be used in the process of executing the method, the alarm threshold and the shutdown threshold can be just a concept, for example, respectively indicating that obvious icing may have occurred and severe icing that endangers the safety of the unit has occurred, so there is no need to configure the specific values ​​of the alarm threshold and the shutdown threshold in the program of the method. The above two situations belong to the implementation of the present disclosure.

[0052] For the second situation above, that is, the situation where the blade icing information is designed as an indicator representing yes or no, optionally, step S103 includes: determining the ratio of the current blade root load to the theoretical blade root load, recorded as the load ratio; determining the blade icing information according to the load ratio and at least one load ratio threshold. This embodiment introduces at least one load ratio threshold, which is essentially consistent with the first situation above, that is, the blade icing information is designed as a value calculated according to the current blade root load and the theoretical blade root load, and the specific values ​​of the alarm threshold and the shutdown threshold are configured in the program of the method, and the size relationship between the blade icing information and the alarm threshold and / or the shutdown threshold is directly compared. At this time, the alarm threshold and the shutdown threshold in the first situation can be corresponded to two different load ratio thresholds in the second situation, which are recorded as the load ratio alarm threshold and the load ratio shutdown threshold, respectively, while the alarm threshold and the shutdown threshold in the second situation can still be just a concept. This embodiment can intuitively reflect the degree of deviation of the current blade root load from the theoretical blade root load by determining the load ratio, thereby reflecting the degree of icing on the blade. Since the load ratio is a relative value rather than an absolute value, it can be well compatible with different load sizes, thereby combining the load ratio thresholds common to different units to realize the judgment of the possibility of icing, which helps to simplify the execution strategy, reduce the amount of information storage and processing, and save computing power.

[0053] It should be noted that since a wind turbine generator set often includes at least three blades and each blade has an independent pitch control system, this embodiment can be used to perform icing monitoring on each blade separately. At this time, in order to ensure the monitoring effect, when it is determined that the possibility of icing on any blade is high (for example, exceeding the alarm threshold or exceeding the shutdown threshold), the blade icing information can be determined as a high possibility of icing on the blades of the unit.

[0054] As an example, for the case where the load ratio alarm threshold and the load ratio shutdown threshold are configured at the same time, referring to the above embodiment, for a single blade, the alarm-related judgment can be associated with the shutdown-related judgment, that is, the load ratio alarm threshold and the load ratio shutdown threshold are used to divide the numerical range of the load ratio into three sections, and the icing possibility of the corresponding blade is determined according to which section the load ratio belongs to; on this basis, for all blades, the two judgments can also be associated, and the judgment result with the greatest possibility of blade icing among all blades is used as the final blade icing information. During actual execution, the load ratio with the greatest possibility can be directly selected from all blades. The larger one is used as a representative. The blade icing information of the unit is determined based on the relationship between this maximum value and the load ratio alarm threshold and the load ratio shutdown threshold. The alarm-related judgment and the shutdown-related judgment can also be separated for all blades, so that the blade icing information includes whether the possibility of blade icing exceeds the alarm threshold and whether the possibility of blade icing exceeds the shutdown threshold. If the possibility of icing of any blade exceeds the alarm threshold, it is determined that the possibility of blade icing of the unit exceeds the alarm threshold. At the same time, if the possibility of icing of any blade exceeds the shutdown threshold, it is determined that the possibility of blade icing of the unit exceeds the shutdown threshold. In addition, for a single blade, the alarm-related judgment and the shutdown-related judgment can also be separated. At this time, the two judgments naturally need to be separated for all blades, which will not be repeated here.

[0055] In addition, for the above-mentioned situation where the blade icing information is designed as an indicator representing yes or no, still based on the situation that the wind turbine generator set includes at least three blades, optionally, step S103 includes: statistically processing the current blade root loads corresponding to each of the at least three blades to obtain the impeller imbalance, wherein the impeller imbalance is used to represent the difference between the current blade root loads corresponding to each of the at least three blades; and determining the blade icing information according to the impeller imbalance and at least one imbalance threshold. First of all, it should be noted that the impeller imbalance is used to represent the imbalance of each blade of the wind turbine generator set, and is usually calculated by the clearance value of each blade in the related art. This embodiment can effectively utilize the calculated current blade root load by using the difference between the current blade root loads of each blade to represent the impeller imbalance, thereby monitoring the imbalance of the icing degree of multiple blades and broadening the monitoring range of the blade icing situation. As an example, the impeller imbalance can be the ratio of the difference between the maximum value and the minimum value of the current blade root load corresponding to each blade divided by the average value of the current blade root load corresponding to each blade. It should be understood that the blade icing determination process based on impeller imbalance and the blade icing determination process based on load ratio, although they are aimed at different icing situations, the data processing process during monitoring is the same, and similar to at least one load ratio threshold including a load ratio alarm threshold and a load ratio shutdown threshold, at least one imbalance threshold may also include an imbalance alarm threshold and an imbalance shutdown threshold. To save space, the icing monitoring and determination process based on impeller imbalance will not be described in detail here.

[0056] For the case where both the blade icing determination process based on impeller imbalance and the blade icing determination process based on load ratio are covered, the two determination processes can be executed independently at the same time without affecting each other, or the two determination processes can be executed one after the other, that is, when the conclusion of one of the determination processes is that no alarm or shutdown is required, the other determination process is executed, and the order can be selected randomly or set in advance as needed, and the present disclosure does not impose any restrictions on this.

[0057] In some embodiments, optionally, the blade icing monitoring method according to the embodiment of the present disclosure further includes: obtaining blade monitoring information determined by at least one blade operation monitoring system, wherein at least one blade operation monitoring system is used to monitor the operation of the blades of the wind turbine generator set, and the blade monitoring information is used to indicate the possibility of blade icing of the wind turbine generator set; and correcting the blade icing information in combination with the blade monitoring information. It can be seen that the blade icing information is the possibility of blade icing inferred according to the embodiment of the present disclosure in combination with the current blade root load and the theoretical blade root load, and the blade operation monitoring system is another data processing system that can also be used to monitor the possibility of blade icing. The obtained blade monitoring information is similar to the blade icing information, but because it is information obtained using different raw data and / or different data processing strategies, it belongs to different information. By combining the blade monitoring information that can also indicate the possibility of blade icing, the blade icing information is corrected, and different monitoring methods can be combined and used, and the monitoring results obtained by different monitoring methods can be summarized, so as to obtain the comprehensive corrected blade icing information, which helps to improve the scalability of the solution. As an example, the blade operation monitoring system may be an execution system of the existing blade icing monitoring method introduced in the background technology section of the present disclosure, or may be other systems that can implement blade icing monitoring, and the present disclosure does not limit this.

[0058] It should be understood that when aggregating the monitoring results, that is, when correcting the blade icing information in combination with the blade monitoring information, different implementation methods can be flexibly selected.

[0059] As an example, referring to the two design scenarios of blade icing information mentioned above, for the first scenario, that is, the blade icing information is designed to be a numerical value calculated based on the current blade root load and the theoretical blade root load, and the specific values ​​of the alarm threshold and the shutdown threshold are configured in the program of the method, and the blade icing information is directly compared with the alarm threshold and / or the shutdown threshold. In this case, the blade monitoring information is also a corresponding numerical value. The blade monitoring information and blade icing information can be converted to the same dimension first, or the information can be dimensionlessly processed, and then the processed values ​​can be statistically processed to obtain statistical values ​​(such as mean value, weighted mean value, mode, preset quantile, etc.) as the corrected blade icing information.

[0060] For the second situation, that is, the situation where the blade icing information is designed to be an identification representing yes or no (corresponding to representing icing or non-icing), the blade monitoring information is also an identification representing yes or no (corresponding to representing icing or non-icing), and a set value N can be configured, N is a positive integer less than or equal to the sum of the number of blade operation monitoring systems and 1. For example, if the number of blade monitoring systems is 3, then N is a positive integer less than or equal to 4, that is, N can be any value of 1, 2, 3, and 4. All blade monitoring information and blade icing information are aggregated together. If there are at least N pieces of information representing icing, that is, the number of pieces of information representing icing is greater than or equal to N. , then the corrected blade icing information is determined to represent icing, otherwise the corrected blade icing information is determined to represent non-icing; for the case where different intervention measures need to be further distinguished when determining icing, such as the case where there are two intervention measures, alarm and shutdown, a set value can be configured for each intervention measure, and the set values ​​configured can be the same or different, so as to achieve independent aggregation of each intervention measure, or no distinction can be made, as long as there are at least N information representing icing as a whole, and then a certain number of intervention measures are selected to be executed, for example, one with a higher proportion can be selected from alarm and shutdown to be executed, or both can be executed. Further, priorities can be configured for all blade monitoring information and blade icing information respectively. When the number of information representing icing is greater than or equal to 1 and less than N, if there is information with a higher priority representing icing, the corrected blade icing information is still determined to represent icing, otherwise the corrected blade icing information is determined to represent non-icing. Of course, when the number of information representing icing is less than 1, that is, 0, the corrected blade icing information is directly determined to represent non-icing.

[0061] In some embodiments, optionally, the blade icing monitoring method according to the embodiment of the present disclosure further includes: associating and storing the current blade root load determined each time with the corresponding time information to obtain a historical blade root load sequence; determining the predicted blade root load at the future target moment according to the current blade root load and the load prediction model, wherein the load prediction model is determined based on the historical blade root load sequence; determining the predicted blade icing information according to the predicted blade root load and the theoretical blade root load, wherein the predicted blade icing information is used to indicate the possibility that the blades of the wind turbine generator set will be frozen at the future target moment. By saving and using the historical blade root load sequence, a load prediction model is obtained, which can be used to predict the predicted blade root load at the future target moment related to the current blade root load, thereby predicting the possibility of icing at the future target moment, realizing early detection of problems, and helping to achieve further cost reduction and efficiency improvement of the wind turbine generator set, and fully ensuring the safe operation of the unit. In addition, the predicted blade root load can also be saved for use by other related functions of the wind turbine generator set, which helps to improve data utilization and save computing power. As an example, the future target moment can be a future moment from the current set time. When constructing a historical blade root load sequence, a sequence can be constructed separately for each wind turbine generator set, and a corresponding load prediction model can be determined to achieve targeted predictions for different wind turbine generator sets. The load prediction model can be, for example, a neural network model. At this time, in order to save computing power, the current blade root load determined each time can be exported to an external device, and the load prediction model can be trained on the external device. When determining the predicted blade root load, the current blade root load can also be exported to the external device first for subsequent updating of the load prediction model, and the predicted blade root load can be directly calculated on the external device, and then returned to the device executing the blade icing monitoring method to determine the predicted blade icing information in combination with the theoretical blade root load. The specific determination process can refer to the determination process of the blade icing information, which will not be repeated here.

[0062] Next, a blade icing monitoring method according to a specific embodiment of the present disclosure is introduced.

[0063] In this specific embodiment, the wind turbine generator set includes three blades, each blade is equipped with a pitch system, the power device of the pitch system is a pitch motor, the working parameter used is the pitch motor current, and the executor of the blade icing monitoring method is the main control PLC of the wind turbine generator set. The current blade root load is estimated by reading the pitch motor current in real time, and then the blade icing is indirectly monitored through the current blade root load, and early warning and prediction are performed.

[0064] This specific embodiment mainly includes the above-mentioned data preparation, formal monitoring, and future icing prediction. Among them, the preliminary data preparation part specifically includes the preparation of the torque conversion relationship of the variable pitch motor. The load characteristic test of the variable pitch motor of the wind turbine generator set can be carried out first to obtain the output torque of the variable pitch motor, the variable pitch motor current and other data; then the output torque of the variable pitch motor and the variable pitch motor current are linearly fitted (refer to Figure 2 , each data point in the figure represents a set of corresponding values ​​of the variable pitch motor current and the output torque of the variable pitch motor), and the torque estimation formula for calculating the output torque of the variable pitch motor from the variable pitch motor current is obtained, that is, Figure 2 The function expression of the fitting curve shown is used as the torque conversion relationship of the variable pitch motor.

[0065] The formal monitoring part is performed by the main control PLC of the wind turbine generator set. The process is shown in Figure 3 , specifically including the following steps:

[0066] a) Communicate with the pitch system to obtain the current pitch motor current in real time, and obtain the current output torque of the pitch motor through the current pitch motor current and torque estimation formula.

[0067] b) Calculate the product of the current output torque and the transmission ratio of the pitch system as the current blade root load.

[0068] c) Calculate the ratio of the current blade root load to the theoretical blade root load as the load ratio.

[0069] d) Determine whether the load ratio exceeds the limit. Specifically, when the load ratio is greater than or equal to the load ratio alarm threshold, determine that the load ratio exceeds the limit; otherwise, determine that the load ratio does not exceed the limit.

[0070] e) When it is determined that the load ratio exceeds the limit, the specific intervention measures are further determined in combination with the load ratio shutdown threshold. When the load ratio is less than the load ratio shutdown threshold, a blade icing alarm message is output; when the load ratio is greater than or equal to the load ratio shutdown threshold, a shutdown command is output.

[0071] f) When it is determined that the load ratio does not exceed the limit, calculate the impeller unbalance, impeller unbalance = (maximum value of the current blade root load of the three blades - minimum value of the current blade root load of the three blades) / average value of the current blade root load of the three blades.

[0072] g) Determine whether the impeller imbalance exceeds the limit. Specifically, when the impeller imbalance is greater than or equal to the imbalance alarm threshold, determine that the impeller imbalance exceeds the limit; otherwise, determine that the impeller imbalance does not exceed the limit; and when it is determined that the impeller imbalance does not exceed the limit, do not process and return to step a).

[0073] h) When it is determined that the impeller imbalance exceeds the limit, the specific intervention measures are further determined in combination with the impeller imbalance shutdown threshold. When the impeller imbalance is less than the imbalance shutdown threshold, a blade icing alarm message is output. When the impeller imbalance is greater than or equal to the imbalance shutdown threshold, a shutdown command is output.

[0074] It should be understood that as long as the wind turbine generator set is not shut down or the blade icing monitoring process is not interrupted, the above steps can be continuously cycled. Specifically, when the wind turbine generator set is not shut down for reasons other than blade icing monitoring, and the blade icing monitoring process is not interrupted, for steps e) and h), if the blade icing alarm information is output, then return to step a), while the alarm is issued, while continuing to monitor the blade icing situation; if the shutdown command is output, the wind turbine generator set is shut down, and the pitch system also stops running. Even if the process returns to step a), the pitch motor current can no longer be obtained, and the process ends naturally.

[0075] In the process of executing the above steps, the current output torque, the current blade root load and the corresponding time information determined each time may be saved for subsequent use.

[0076] In the future icing prediction part, the neural network model is trained using the historical blade root load sequence consisting of the current blade root load determined each time and the corresponding time information to obtain or update the load prediction model, and then the latest current blade root load is input into the load prediction model to obtain the predicted blade root load at the future target moment, and then refer to steps c) to h) to execute, except that the current blade root load is replaced by the predicted blade root load. Accordingly, the conclusion obtained is also the conclusion for the predicted blade root load.

[0077] This specific embodiment uses the current equivalent of the variable pitch motor current to convert the current blade root load, and determines whether the blade is frozen based on the load. There is no need to add additional sensors or computing and measurement equipment. It can be directly run in the main control PLC, which is simple to implement and has stronger economy and practicality. At the same time, since blade icing is directly related to the blade root load and impeller imbalance, it has strong causality. And the monitoring results obtained can be used in combination with other blade icing monitoring methods such as SCADA big data feature extraction, and have strong expansibility. In addition, the saved current output torque, current blade root load, and predicted blade root load and corresponding output torque can also be processed and analyzed, and then applied to other functions of the wind turbine generator set, with data reusability.

[0078] According to another aspect of the present disclosure, there is provided a blade icing monitoring device for a wind turbine generator set.

[0079] Figure 4is a block diagram showing a blade icing monitoring device for a wind turbine generator set according to an embodiment of the present disclosure. Figure 4 The blade icing monitoring device 400 of a wind turbine generator set includes an acquisition unit 401 and a determination unit 402 .

[0080] The acquisition unit 401 can acquire the current operating parameters of the power device and the theoretical blade root load of the wind turbine generator set when the pitch is changed.

[0081] The determination unit 402 may determine the current blade root load of the wind turbine generator set according to the current operating parameters.

[0082] The determination unit 402 may also determine blade icing information according to the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of icing of the blades of the wind turbine generator set.

[0083] Optionally, the determination unit 402 can also: obtain the torque conversion relationship of the power device and the transmission ratio of the pitch system, wherein the torque conversion relationship is used to represent the conversion relationship between the working parameters of the power device and the output torque; determine the current output torque corresponding to the current working parameters based on the current working parameters and the torque conversion relationship; determine the current blade root load based on the current output torque and the transmission ratio of the pitch system.

[0084] Optionally, the torque conversion relationship is obtained by the following steps: performing a load characteristic test on the power device to obtain multiple sets of corresponding working parameters and output torques; performing fitting processing on the multiple sets of corresponding working parameters and output torques to obtain the torque conversion relationship.

[0085] Optionally, the acquisition unit 401 can also acquire blade monitoring information determined by at least one blade operation monitoring system, wherein the at least one blade operation monitoring system is used to monitor the operation condition of the blades of the wind turbine generator set, and the blade monitoring information is used to indicate the possibility of blade icing of the wind turbine generator set; the determination unit 402 can also correct the blade icing information in combination with the blade monitoring information.

[0086] Optionally, the determination unit 402 may further: determine a ratio of a current blade root load to a theoretical blade root load, recorded as a load ratio; and determine blade icing information according to the load ratio and at least one load ratio threshold.

[0087] Optionally, the wind turbine generator set includes at least three blades, and the determination unit 402 can also: perform statistical processing on the current blade root loads corresponding to each of the at least three blades to obtain an impeller imbalance, wherein the impeller imbalance is used to represent the difference between the current blade root loads corresponding to each of the at least three blades; determine the blade icing information based on the impeller imbalance and at least one imbalance threshold.

[0088] Optionally, according to the embodiment of the present disclosure, the blade icing monitoring device 400 of the wind turbine generator set also includes an output unit (not shown in the figure), which can: output blade icing alarm information when the blade icing information indicates that the possibility of blade icing exceeds the alarm threshold, wherein the blade icing alarm information is used to prompt that the blade may have been frozen; and / or output shutdown prompt information or shutdown instructions when the blade icing information indicates that the possibility of blade icing exceeds the shutdown threshold, wherein the shutdown prompt information is used to prompt to stop the operation of the wind turbine generator set, and the shutdown instruction is used to control the wind turbine generator set to stop operating.

[0089] Optionally, according to an embodiment of the present disclosure, the blade icing monitoring device 400 of a wind turbine generator set further includes a storage unit (not shown in the figure) and a prediction unit (not shown in the figure), and the storage unit may store the current blade root load determined each time in association with the corresponding time information to obtain a historical blade root load sequence; the prediction unit may determine the predicted blade root load at a future target moment based on the current blade root load and a load prediction model, wherein the load prediction model is determined based on the historical blade root load sequence; the determination unit 402 may also determine predicted blade icing information based on the predicted blade root load and the theoretical blade root load, wherein the predicted blade icing information is used to indicate the possibility that the blades of the wind turbine generator set are expected to be frozen at a future target moment.

[0090] Regarding the device in the above embodiment, the specific manner in which each unit performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0091] The blade icing monitoring method of a wind turbine generator set according to an embodiment of the present disclosure may be written as a computer program and stored on a computer-readable storage medium. When the instructions corresponding to the computer program are executed by a processor, the blade icing monitoring method of the wind turbine generator set as described above may be implemented. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disk storage, hard disk drive (HDD), solid state drive (SSD), card storage (such as, multimedia card, secure digital (SD) card or extreme digital (XD) card), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk and any other device, any other device is configured to store computer program and any associated data, data files and data structures in a non-transitory manner and provide the computer program and any associated data, data files and data structures to a processor or computer so that the processor or computer can execute the computer program. In one example, the computer program and any associated data, data files and data structures are distributed on a networked computer system so that the computer program and any associated data, data files and data structures are stored, accessed and executed in a distributed manner by one or more processors or computers.

[0092] Figure 5 is a block diagram illustrating a computer device according to an embodiment of the present disclosure.

[0093] Reference Figure 5 The computer device 500 includes at least one memory 501 and at least one processor 502, wherein the at least one memory 501 stores a set of computer executable instructions. When the set of computer executable instructions is executed by the at least one processor 502, a method for monitoring blade icing of a wind turbine according to an exemplary embodiment of the present disclosure is executed.

[0094] As an example, the computer device 500 may be a PC, a tablet device, a personal digital assistant, a smart phone, or other device capable of executing the above instruction set. Here, the computer device 500 is not necessarily a single electronic device, but may also be any device or circuit collection capable of executing the above instructions (or instruction sets) individually or in combination. The computer device 500 may also be part of an integrated control system or system manager, or may be configured as a portable electronic device interconnected with a local or remote (e.g., via wireless transmission) interface.

[0095] In computer device 500, processor 502 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller, or a microprocessor. By way of example and not limitation, the processor may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0096] The processor 502 may execute instructions or codes stored in the memory 501, wherein the memory 501 may also store data. Instructions and data may also be sent and received over a network via a network interface device, wherein the network interface device may employ any known transmission protocol.

[0097] The memory 501 may be integrated with the processor 502, for example, by placing RAM or flash memory within an integrated circuit microprocessor or the like. In addition, the memory 501 may include a separate device, such as an external disk drive, a storage array, or any other storage device that can be used by a database system. The memory 501 and the processor 502 may be operatively coupled, or may communicate with each other, such as through an I / O port, a network connection, etc., so that the processor 502 can read files stored in the memory.

[0098] In addition, the computer device 500 may also include a video display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.) All components of the computer device 500 may be connected to each other via a bus and / or a network.

[0099] The specific implementation methods of the present disclosure have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that these embodiments may be modified and varied without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents. These modifications and variations should also be within the scope of protection of the claims of the present disclosure.

Claims

1. A method for monitoring blade icing of a wind turbine generator set, It is characterized in that The wind turbine generator set includes a pitch control system, the pitch control system includes a power device, and the blade icing monitoring method includes: Acquiring current operating parameters of the power device and theoretical blade root loads of the wind turbine generator set when the pitch is changed; Determining a current blade root load of the wind turbine generator set according to the current operating parameters; Blade icing information is determined according to the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of blade icing of the wind turbine generator set.

2. The blade icing monitoring method according to claim 1, It is characterized in that The determining the current blade root load of the wind turbine generator set according to the current operating parameter comprises: Acquire a torque conversion relationship of the power device and a transmission ratio of a pitch system, wherein the torque conversion relationship is used to represent a conversion relationship between an operating parameter of the power device and an output torque; Determining a current output torque corresponding to the current operating parameter according to the current operating parameter and the torque conversion relationship; The current blade root load is determined according to the current output torque and the transmission ratio of the pitch system.

3. The blade icing monitoring method according to claim 2, It is characterized in that The torque conversion relationship is obtained by the following steps: Performing a load characteristic test on the power device to obtain multiple sets of corresponding working parameters and output torques; The plurality of groups of corresponding working parameters and output torques are fitted to obtain the torque conversion relationship.

4. The blade icing monitoring method according to claim 1, It is characterized in that The blade icing monitoring method further comprises: Acquiring blade monitoring information determined by at least one blade operation monitoring system, wherein the at least one blade operation monitoring system is used to monitor the operation of the blades of the wind turbine generator set, and the blade monitoring information is used to indicate the possibility of ice formation on the blades of the wind turbine generator set; The blade icing information is corrected in combination with the blade monitoring information.

5. The blade icing monitoring method according to claim 1, It is characterized in that The determining blade icing information according to the current blade root load and the theoretical blade root load includes: Determining a ratio of the current blade root load to the theoretical blade root load, recorded as a load ratio; The blade icing information is determined according to the load ratio and at least one load ratio threshold.

6. The blade icing monitoring method according to claim 1, It is characterized in that The wind turbine generator set includes at least three blades, wherein determining blade icing information according to the current blade root load and the theoretical blade root load includes: Performing statistical processing on the current blade root loads corresponding to the at least three blades to obtain an impeller unbalance degree, wherein the impeller unbalance degree is used to represent the difference between the current blade root loads corresponding to the at least three blades; The blade icing information is determined according to the impeller imbalance and at least one imbalance threshold.

7. The blade icing monitoring method according to any one of claims 1 to 6, It is characterized in that The blade icing monitoring method further comprises: When the blade icing information indicates that the possibility of blade icing exceeds an alarm threshold, outputting blade icing alarm information, wherein the blade icing alarm information is used to indicate that the blade may have been frozen; and / or When the blade icing information indicates that the possibility of blade icing exceeds the shutdown threshold, a shutdown prompt message or a shutdown instruction is output, wherein the shutdown prompt message is used to prompt the wind turbine to stop operating, and the shutdown instruction is used to control the wind turbine to stop operating.

8. The blade icing monitoring method according to any one of claims 1 to 6, It is characterized in that The blade icing monitoring method further comprises: The current blade root load determined each time is associated and stored with corresponding time information to obtain a historical blade root load sequence; Determining a predicted blade root load at a future target moment according to the current blade root load and a load prediction model, wherein the load prediction model is determined based on the historical blade root load sequence; Predicted blade icing information is determined according to the predicted blade root load and the theoretical blade root load, wherein the predicted blade icing information is used to indicate the possibility that the blades of the wind turbine generator set are expected to be frozen at the future target moment.

9. A blade icing monitoring device for a wind turbine generator set, It is characterized in that The wind turbine generator set includes a pitch control system, the pitch control system includes a power device, and the blade icing monitoring device includes: An acquisition unit is configured to acquire current operating parameters of the power device and theoretical blade root loads of the wind turbine generator set when the pitch is changed; a determination unit, configured to determine a current blade root load of the wind turbine generator set according to the current operating parameter; The determination unit is further configured to determine blade icing information according to the current blade root load and the theoretical blade root load, wherein the blade icing information is used to indicate the possibility of icing of the blades of the wind turbine generator set.

10. A computer-readable storage medium, It is characterized in that When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute the blade icing monitoring method for a wind turbine generator set according to any one of claims 1 to 8.

11. A computer device, It is characterized in that include: at least one processor; at least one memory storing computer executable instructions, Wherein, when the computer executable instructions are executed by the at least one processor, the at least one processor is prompted to execute the blade icing monitoring method of a wind turbine generator set according to any one of claims 1 to 8.

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