Wind generating set performance early warning method and related device

Abstract

The invention discloses a wind generating set performance early warning method and a related device. The method comprises the following steps: acquiring operation parameters of a wind generating set; according to the operation parameters of the wind generating set, calculating a total integral value by using a dynamic warehouse division integral algorithm; judging whether the performance of the wind generating set is abnormal or not according to the calculated total integral value; when the performance of the wind generating set is abnormal, early warning is triggered, the method and the related device can achieve early warning of the performance of the wind generating set, and adaptability is high.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power generation early warning, and relates to a wind turbine generator performance early warning method and related device. BACKGROUND

[0002] The wind turbine generator has advantages of low carbon, high precision, high flexibility, high automation degree, high price and complex structure. The wind turbine generator, especially the transmission system, will cause huge economic loss and even catastrophic accidents once a fault or damage occurs. At present, when judging whether the performance of the wind turbine generator has a problem, a fixed interval method is mostly used to judge whether the detected parameter is in the fixed interval. When the parameter is not in the fixed interval, it is considered that the performance of the wind turbine generator has a problem. However, due to the differences in the operating environment and the body parameters of each unit, the fixed interval method cannot effectively adapt to each wind turbine generator, thereby causing a large error in judgment. SUMMARY

[0003] The application aims to overcome the shortcomings of the prior art and provide a wind turbine generator performance early warning method and related device, which can realize wind turbine generator performance early warning and has high adaptability.

[0004] To achieve the above object, the application discloses a wind turbine generator performance early warning method, which comprises the following steps:

[0005] obtaining operating parameters of the wind turbine generator;

[0006] calculating a total integral value by using a dynamic binning integral algorithm according to the operating parameters of the wind turbine generator;

[0007] judging whether the performance of the wind turbine generator is abnormal according to the calculated total integral value;

[0008] triggering early warning when the performance of the wind turbine generator is abnormal.

[0009] The wind turbine generator performance early warning method further improves in that:

[0010] Further, the total integral value S_total = ΣS_i, wherein S_i is the contribution value of the i-th bin, S_i = ΔP x PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i-th bin, and ΔP is an adjustable parameter.

[0011] Further, the process of judging whether the performance of the wind turbine generator is abnormal according to the calculated total integral value is:

[0012] When the total integral value S_total is greater than or equal to 1.3*S_ref, it is considered that the performance of the wind turbine generator set is abnormal, wherein the reference value S_ref is the moving average value of S_total of the wind turbine generator set in the previous 12 months.

[0013] Further, the process of triggering a warning when the performance of the wind turbine generator set is abnormal is:

[0014] When the total integral value S_total is greater than 1.3*S_ref, a first-level warning is triggered, wherein the reference value S_ref is the moving average value of S_total of the wind turbine generator set in the previous 12 months.

[0015] When the total integral value S_total is greater than 1.5*S_ref, a second-level warning is triggered.

[0016] The application discloses a wind turbine generator set performance warning system, comprising:

[0017] An acquisition module is configured to acquire operation parameters of a wind turbine generator set.

[0018] A calculation module is configured to calculate a total integral value by using a dynamic bin integral algorithm according to the operation parameters of the wind turbine generator set.

[0019] A judgment module is configured to judge whether the performance of the wind turbine generator set is abnormal according to the calculated total integral value.

[0020] A warning module is configured to trigger a warning when the performance of the wind turbine generator set is abnormal.

[0021] The wind turbine generator set performance warning system further improves in that:

[0022] Further, the total integral value S_total = ΣS_i, wherein S_i is the contribution value of the i-th bin, S_i = ΔP*PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i-th bin, and ΔP is an adjustable parameter.

[0023] Further, the process of judging whether the performance of the wind turbine generator set is abnormal according to the calculated total integral value is:

[0024] When the total integral value S_total is greater than or equal to 1.3*S_ref, it is considered that the performance of the wind turbine generator set is abnormal, wherein the reference value S_ref is the moving average value of S_total of the wind turbine generator set in the previous 12 months.

[0025] Further, the process of triggering a warning when the performance of the wind turbine generator set is abnormal is:

[0026] When the total integral value S_total>1.3*S_ref, a first level early warning is triggered, wherein the reference value S_ref is the moving average value of S_total in the previous 12 months of the wind turbine generator set;

[0027] When the total integral value S_total>1.5*S_ref, a second level early warning is triggered.

[0028] The application discloses a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to realize the steps of the wind turbine generator set performance early warning method.

[0029] The application discloses a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to realize the steps of the wind turbine generator set performance early warning method.

[0030] The application has the following beneficial effects:

[0031] The wind turbine generator set performance early warning method and related device have the following beneficial effects: BRIEF DESCRIPTION OF DRAWINGS

[0032] The accompanying drawings, which form a part of the specification, are included to provide a further understanding of the application and are incorporated herein in conjunction with the description of the application. The drawings are as follows:

[0033] Figure 1 The flow chart of data preprocessing in the application;

[0034] Figure 2 The flow chart of the method in the application;

[0035] Figure 3 The example diagram of three-dimensional visualization. DETAILED DESCRIPTION

[0036] Clearly, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0037] In the description of the present application, it should be understood that the terms "comprising" and "including" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0038] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms as well.

[0039] It should be further understood that the term "and / or" used in the specification and the appended claims of the present application means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations, for example, A and / or B can mean: A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0040] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range, without departing from the scope of the embodiments of the present application.

[0041] Depending on the context, the word "if" as used herein can be interpreted as meaning "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (a stated condition or event)" can be interpreted as meaning "when determined" or "in response to determining" or "when detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)".

[0042] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0043] Various structural schematic diagrams according to the disclosed embodiments of the present application are shown in the drawings. These diagrams are not drawn to scale, in which some details are exaggerated for the purpose of clear expression, and some details can be omitted. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are only exemplary, and in actuality, there can be deviations due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes and relative positions can be additionally designed by those skilled in the art according to actual needs.

[0044] Embodiment one

[0045] The performance early warning method of the wind turbine generator set described in the present application comprises the following steps:

[0046] 1) Data standardization collection;

[0047] According to the GB / T18451.2-2021 standard, the 10-minute average wind speed is obtained, with an interval step of 0.5 m / s;

[0048] 2) Three-dimensional data set construction;

[0049] Form a Point(Power, WindSpeed, Pitch) data cube;

[0050] 3) Dynamic binning integration algorithm;

[0051] Quantitative evaluation of performance degradation is achieved by power binning-maximum pitch angle integration;

[0052] The dynamic binning integration specifically includes:

[0053] ±5% of the rated power of the wind turbine is taken as the binning width (adjustable parameter ΔP);

[0054] In each power bin, data points that meet Pitch>2° are selected;

[0055] Extract the maximum value of blade opening PitchMax in each bin;

[0056] Calculate the bin contribution value: S_i = ΔP x PitchMax_i;

[0057] Total integral value: S_total = Σ S_i

[0058] 4) Set the early warning threshold;

[0059] Set the reference value S_ref as the moving average of S_total in the previous 12 months;

[0060] When S_total > 1.3 x S_ref, a first-level early warning is triggered;

[0061] When S_total > 1.5 x S_ref, a second-level early warning is triggered.

[0062] Example Two

[0063] The specific process of this embodiment is:

[0064] 1) Data preprocessing;

[0065] Time alignment: unify the timestamp to UTC time.

[0066] Data validity check, as shown in Figure 1 .

[0067] 2) Calculate the bin integral;

[0068] 21) Define the power interval (bin), from 0 to 1.1 times the rated power, with an interval of 0.05 times the rated power;

[0069] 22) Initialize the cumulative area variable S_total to 0;

[0070] 3) Traverse each power interval, for the data points falling within the interval, refer to Figure 2 , specifically:

[0071] Filter out points with a pitch angle greater than 2 degrees;

[0072] Calculate the maximum pitch angle in these points;

[0073] When there are points that meet the conditions, multiply the current interval width by the maximum pitch angle and add it to S_total.

[0074] 4) Three-dimensional visualization example;

[0075] As shown in Figure 3As shown, the X axis is the normalized power (P / P_rated); the Y axis is the pitch angle; and the Z axis is the wind speed (0.5 m / s interval), and the red marked points are the PitchMax points of each bin.

[0076] Embodiment Three

[0077] The wind turbine performance early warning system provided by the present application comprises:

[0078] The acquisition module is configured to acquire the operating parameters of the wind turbine.

[0079] The calculation module is configured to calculate a total integral value by using a dynamic binning integral algorithm according to the operating parameters of the wind turbine.

[0080] The judgment module is configured to judge whether the performance of the wind turbine is abnormal according to the calculated total integral value.

[0081] The early warning module is configured to trigger an early warning when the performance of the wind turbine is abnormal.

[0082] The wind turbine performance early warning system provided by the present application is further improved in that:

[0083] In this embodiment, the total integral value S_total = ΣS_i, wherein S_i is the contribution value of the i-th bin, S_i = ΔP x PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i-th bin, and ΔP is an adjustable parameter.

[0084] In this embodiment, the process of judging whether the performance of the wind turbine is abnormal according to the calculated total integral value is:

[0085] When the total integral value S_total is greater than or equal to 1.3 x S_ref, it is considered that the performance of the wind turbine is abnormal, wherein the reference value S_ref is the moving average value of S_total in the previous 12 months of the wind turbine.

[0086] In this embodiment, the process of triggering an early warning when the performance of the wind turbine is abnormal is:

[0087] When the total integral value S_total > 1.3 x S_ref, a first-level early warning is triggered, wherein the reference value S_ref is the moving average value of S_total in the previous 12 months of the wind turbine.

[0088] When the total integral value S_total > 1.5 x S_ref, a second-level early warning is triggered.

[0089] The division of the modules in the embodiments of the present application is illustrative, and is merely a logical function division. In actual implementation, another division manner can be used. In addition, each function module in each embodiment of the present application can be integrated in one processor, or can be physically separated, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module.

[0090] Embodiment four

[0091] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the wind turbine performance early warning method when executing the computer program, for example, including: obtaining the operating parameters of the wind turbine; calculating the total integral value by using a dynamic binning integral algorithm according to the operating parameters of the wind turbine; determining whether the performance of the wind turbine is abnormal according to the calculated total integral value; triggering an early warning when the performance of the wind turbine is abnormal; the total integral value S_total = ∑S_i, wherein S_i is the contribution value of the i th bin, S_i = ΔP × PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i th bin, and ΔP is an adjustable parameter; the process of determining whether the performance of the wind turbine is abnormal according to the calculated total integral value is: when the total integral value S_total is greater than or equal to 1.3 × S_ref, it is considered that the performance of the wind turbine is abnormal, wherein the reference value S_ref is the moving average value of S_total of the wind turbine in the previous 12 months. The process of triggering an early warning when the performance of the wind turbine is abnormal is: when the total integral value S_total > 1.3 × S_ref, a first-level early warning is triggered, wherein the reference value S_ref is the moving average value of S_total of the wind turbine in the previous 12 months; when the total integral value S_total > 1.5 × S_ref, a second-level early warning is triggered. The memory can include a memory, for example, a high-speed random access memory, and can also include a non-volatile memory, for example, at least one disk memory, etc.; the processor, the network interface, and the memory are connected to each other through an internal bus, which can be an industry standard architecture bus, a peripheral component interconnect standard bus, an extended industry standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store a program, specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0092] Embodiment five

[0093] A computer readable storage medium stores a computer program, the computer program is executed by a processor to implement steps of the wind turbine performance early warning method, for example, including: obtaining operating parameters of a wind turbine; calculating a total integral value by using a dynamic sub-bin integral algorithm according to the operating parameters of the wind turbine; determining whether the performance of the wind turbine is abnormal according to the calculated total integral value; triggering an early warning when the performance of the wind turbine is abnormal; the total integral value S_total = ∑S_i, wherein S_i is a contribution value of an i-th sub-bin, S_i = ΔP × PitchMax_i, PitchMax_i is a maximum value of a blade opening in the i-th sub-bin, and ΔP is an adjustable parameter; the process of determining whether the performance of the wind turbine is abnormal according to the calculated total integral value is: when the total integral value S_total is greater than or equal to 1.3 × S_ref, it is considered that the performance of the wind turbine is abnormal, wherein S_ref is a moving average value of S_total of the wind turbine in the previous 12 months; the process of triggering an early warning when the performance of the wind turbine is abnormal is: when the total integral value S_total > 1.3 × S_ref, a first-level early warning is triggered, wherein S_ref is a moving average value of S_total of the wind turbine in the previous 12 months; and when the total integral value S_total > 1.5 × S_ref, a second-level early warning is triggered. Specifically, the computer readable storage medium includes but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory can include a random access memory (RAM) and / or a cache memory, etc. The non-volatile memory can include a read-only memory (ROM), a hard disk, a flash memory, an optical disk, a magnetic disk, etc.

[0094] Those skilled in the art will appreciate that embodiments of the application can be supplied as a method, a system, or a computer program product. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) having computer usable program code embodied thereon.

[0095] The present application is described in reference to the flow diagrams and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It will be understood that each block of the flow diagrams and / or block diagrams, and combinations of blocks in the flow diagrams and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow diagrams and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0096] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0098] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the present application be limited only by the scope of the claims, including any amendments thereof, and can include any adaptations or variations of the specific embodiments discussed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0099] It is to be understood that the application is not limited to the precise construction described in the specification and shown in the drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is limited only by the claims appended hereto.

[0100] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application, any simple modification, change and equivalent structural change made according to the technical essence of the present application to the above embodiment shall still fall within the protection scope of the technical scheme of the present application.

Claims

1. A method for early warning of wind turbine generator performance, characterized in that, include: Obtain the operating parameters of the wind turbine generator set; Based on the operating parameters of the wind turbine generator set, the total integral value is calculated using a dynamic compartmentalized integral algorithm; Determine whether the performance of the wind turbine generator is abnormal based on the calculated total integral value; An early warning is triggered when the performance of the wind turbine generator set is abnormal.

2. The wind turbine generator performance early warning method according to claim 1, characterized in that, The total integral value S_total=ΣS_i, where S_i is the contribution value of the i-th compartment, S_i=ΔP×PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i-th compartment, and ΔP is an adjustable parameter.

3. The wind turbine generator performance early warning method according to claim 1, characterized in that, The process of determining whether the performance of the wind turbine generator is abnormal based on the calculated total integral value is as follows: When the total integral value S_total is greater than or equal to 1.3 × S_ref, the performance of the wind turbine generator is considered abnormal. The baseline value S_ref is the moving average of S_total for the wind turbine generator over the previous 12 months.

4. The wind turbine generator performance early warning method according to claim 1, characterized in that, The process for triggering an early warning when the performance of a wind turbine generator set malfunctions is as follows: When the total integral value S_total > 1.3 × S_ref, a Level 1 warning is triggered, where the baseline value S_ref is the moving average of S_total for the wind turbine generator over the previous 12 months. When the total integral value S_total > 1.5 × S_ref, a level 2 warning is triggered.

5. A wind turbine generator performance early warning system, characterized in that, include: The acquisition module is used to acquire the operating parameters of the wind turbine generator set; The calculation module is used to calculate the total integral value based on the operating parameters of the wind turbine generator set using a dynamic compartmentalized integral algorithm. The judgment module is used to determine whether the performance of the wind turbine generator is abnormal based on the calculated total integral value. The early warning module is used to trigger an early warning when the performance of the wind turbine generator set is abnormal.

6. The wind turbine generator performance early warning system according to claim 5, characterized in that, The total integral value S_total=ΣS_i, where S_i is the contribution value of the i-th compartment, S_i=ΔP×PitchMax_i, PitchMax_i is the maximum value of the blade opening in the i-th compartment, and ΔP is an adjustable parameter.

7. The wind turbine generator performance early warning system according to claim 5, characterized in that, The process of determining whether the performance of the wind turbine generator is abnormal based on the calculated total integral value is as follows: When the total integral value S_total is greater than or equal to 1.3 × S_ref, the performance of the wind turbine generator is considered abnormal. The baseline value S_ref is the moving average of S_total for the wind turbine generator over the previous 12 months.

8. The wind turbine generator performance early warning system according to claim 5, characterized in that, The process for triggering an early warning when the performance of a wind turbine generator set malfunctions is as follows: When the total integral value S_total > 1.3 × S_ref, a Level 1 warning is triggered, where the baseline value S_ref is the moving average of S_total for the wind turbine generator over the previous 12 months. When the total integral value S_total > 1.5 × S_ref, a level 2 warning is triggered.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the wind turbine generator performance early warning method as described in any one of claims 1-4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the wind turbine generator performance early warning method as described in any one of claims 1-4.

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