Method and device for evaluating the operation of a wind turbine

Abstract

The application provides a kind of wind turbine operating condition evaluation method and device, belong to wind power generation technical field. Among them, the evaluation method of the application includes: extracting the data of multiple wind turbines in a predetermined time period on a predetermined platform;Draw the power curve of each wind turbine, and classify the data;Eliminate the abnormal power generation data of the wind turbine, and fit the actual power curve of the wind turbine;Statistical power loss value when the performance of the unit component is reduced or limited power;According to the power loss value of the wind turbine component, the total loss of electric quantity is obtained.The evaluation method of the application can effectively identify the performance reduction of the unit component, and the loss of annual power generation is counted, the technical support is provided for the targeted development of hardware technical improvement, and the overall benefit of wind farm is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wind power generation, and particularly relates to a method and device for evaluating the operation of a wind turbine. BACKGROUND

[0002] With the development of big data technology, we can conduct a unit survey on the historical data of each wind farm and each unit of a new energy intelligent operation and maintenance center, scientifically and quantitatively analyze the power generation performance and power loss of wind turbines in a wind farm, and especially the power loss, which includes the power loss caused by the power limitation of the equipment itself, the power loss caused by manual power limitation, and the power loss caused by power grid scheduling. Currently, there is no scientific and effective quantitative method.

[0003] Through scientific big data analysis, the power loss caused by unit power limitation and fault shutdown is very obvious. Based on this, the present application provides a method and device for evaluating the operation of a wind turbine, which mainly analyzes the power limitation problem, finds the power loss point, and improves the power in a special way to improve the overall income of the wind farm. SUMMARY

[0004] The present application aims to at least solve one of the technical problems existing in the prior art, and provides a method and device for evaluating the operation of a wind turbine.

[0005] In one aspect of the present application, a method for evaluating the operation of a wind turbine is provided, which comprises:

[0006] extracting the data of a plurality of wind turbines in a preset time period on a preset platform;

[0007] drawing the power curve of each wind turbine and classifying the data;

[0008] eliminating the abnormal power generation data of the wind turbine and fitting the actual power curve of the wind turbine;

[0009] statistically analyzing the power loss value when the performance of the unit components decreases or is limited;

[0010] obtaining the total loss power according to the power loss value of the wind turbine components.

[0011] Optionally, the data includes at least one of the unit number, the information wind speed, the power, the generator speed, the power limitation flag, the variable pitch angle, and the component temperature.

[0012] Optionally, the classification is performed according to the following classification principles, which include: selecting the data when the wind turbine is stopped, the data when the wind turbine is limited, and the data when the wind turbine is normally generating power, and obtaining the scatter point distribution of the wind speed and power of the wind turbine.

[0013] Optionally, the abnormal power generation data includes data of unit shutdown and data corresponding to unit power limitation.

[0014] Optionally, the fitting the actual power curve of the wind turbine includes:

[0015] The wind speed is divided into 225 intervals according to every 0.1 m / s, from the starting wind speed 2.5 m / s to the off-grid wind speed 25 m / s, and the power in each interval is counted respectively, and then the average power value of each interval is obtained, to obtain the corresponding relationship of wind speed and average power value, and the actual power curve of wind speed and power is drawn.

[0016] Optionally, the counting the power loss value when the performance of the unit component is degraded or limited includes:

[0017] The average wind speed and the corresponding power of the wind turbine when the performance of the unit component is degraded or limited are obtained.

[0018] The power loss value is obtained according to the average wind speed and the corresponding power.

[0019] Optionally, the obtaining the power loss value according to the average wind speed and the corresponding power includes:

[0020] Referring to the corresponding generated power B of the fitted actual power curve of the wind turbine, the actual generated power b when the performance of the wind turbine component is degraded is subtracted to obtain the power loss value bb of the single wind turbine component performance degradation time.

[0021] Optionally, the obtaining the total loss power according to the power loss value of the wind turbine component includes:

[0022] According to the performance degradation classification of the wind turbine component, the 1…n power loss values of each single wind turbine component performance degradation in the data of the wind turbine in the preset time period are accumulated to obtain the corresponding total loss power.

[0023] The total loss power is divided by the corresponding preset time period length to obtain the total loss power.

[0024] Optionally, the preset time period ranges from 5 minutes to 15 minutes; and / or,

[0025] The preset platform is a smart operation and maintenance platform.

[0026] In another aspect of the present application, a device for evaluating the operation of a wind turbine is provided, comprising an extraction module, a classification module, a fitting module, a statistical module and a calculation module, wherein,

[0027] The extraction module is used for extracting data of a plurality of wind turbines in a preset time period on a preset platform.

[0028] The classification module is used for drawing a power curve of each wind turbine and classifying the data;

[0029] The fitting module is used for eliminating abnormal power generation data of the wind turbine and fitting an actual power curve of the wind turbine;

[0030] The statistical module is used for counting a power loss value when a component performance of the wind turbine is degraded or limited;

[0031] The calculation module is used for obtaining a total loss power according to the power loss value of the component of the wind turbine.

[0032] The present application provides a kind of wind turbine operating condition evaluation method, comprising: extracting the data of multiple wind turbines in preset time period on the preset platform;Draw the power curve of each wind turbine, and the data is classified;Eliminate the abnormal power generation data of the wind turbine, and fit the actual power curve of the wind turbine;Count the power loss value when the component performance of the wind turbine is degraded or limited;According to the power loss value of the component of the wind turbine, obtain total loss power.The evaluation method of the present application can effectively identify the component performance degradation condition of unit, and the loss of annual power generation is counted, and targeted hardware technical improvement is carried out to provide technical support, guarantee the overall income of wind farm. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 It is a flow chart of the wind turbine operating condition evaluation method of an embodiment of the present application;

[0034] Figure 2 It is a wind speed power scatter plot and fitting curve schematic diagram of the wind turbine of another embodiment of the present application;

[0035] Figure 3 It is the theoretical limit power loss result of another embodiment of the present application;

[0036] Figure 4 It is a structure schematic diagram of the wind turbine operating condition evaluation device of another embodiment of the present application. DETAILED DESCRIPTION

[0037] To make those skilled in the art better understand the technical solutions of the present application, the present application will be further described in detail below with reference to the drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the protection scope of the present application.

[0038] As Figure 1As shown, in one aspect of the present application, a method S100 for evaluating the operation of a wind turbine generator is provided, which comprises the following specific steps S110-S150:

[0039] S110, extracting data of multiple wind turbine generators in a preset time period on a preset platform.

[0040] Specifically, in this embodiment, the ten-minute data of 33 units in a wind farm in 2020 is counted in the smart operation and maintenance platform center, that is, the preset time period is 10 minutes, and the ten-minute data includes at least one of unit number, information wind speed, power, generator speed, power limit flag, variable pitch angle, and component temperature. The component temperature includes gear box oil temperature, generator shaft temperature, and frequency converter IGBT temperature. That is, this embodiment proposes a method for evaluating the operation of a unit based on big data on a new energy smart operation and maintenance platform.

[0041] It should be noted that the above ten-minute data mainly contains the average value of each information according to the ten-minute scale.

[0042] S120, drawing a power curve of each wind turbine generator and classifying the data.

[0043] Specifically, the following classification principles are used for classification in this embodiment, including: selecting data when the wind turbine generator is stopped, data when the wind turbine generator is limited power, and data when the wind turbine generator is normally generating power, and obtaining the scatter distribution of the wind speed and power corresponding to the wind turbine generator, as shown in Figure 2 .

[0044] S130, removing the non-normal power generation data of the wind turbine generator and fitting the actual power curve of the wind turbine generator.

[0045] Specifically, the non-normal power generation data of this embodiment includes data when the unit is stopped and data corresponding to the unit limited power. The data corresponding to the unit limited power includes data when the unit is limited power due to the performance degradation of the unit components, such as high gear box oil temperature, high generator shaft temperature, and high frequency converter IGBT temperature.

[0046] Further, the fitting of the actual power curve of the wind turbine generator in this embodiment includes: dividing 225 intervals from the starting wind speed 2.5 m / s to the off-grid wind speed 25 m / s according to every 0.1 m / s as a step, and respectively counting the power in each interval, and then obtaining the average value of each power to obtain the corresponding relationship between the wind speed and the average power value of each interval, and drawing the actual power curve of the wind speed and the power.

[0047] For example, the data after the abnormal power generation of the unit is removed, the wind speed is divided into 225 small intervals according to every 0.1 m / s, from the starting wind speed 2.5 m / s to the off-grid wind speed 25 m / s, for example, [2.5-2.6) is the second interval, the wind speed clustering corresponding to the second interval is 2.5 m / s, [2.6-2.7) is the second interval, the wind speed clustering corresponding to the second interval is 2.6 m / s, … [24.9-25) is the 225th interval, the wind speed clustering corresponding to the 225th interval is 25 m / s, the power in each interval is respectively counted, and the average power of each interval is calculated; in the range of 2.5 m / s to 25 m / s, the corresponding relationship of the wind speed and the average power value of the divided 225 small intervals is obtained, and the actual power curve of the wind speed and the power is drawn, as shown in Figure 2

[0048] S140, the power loss value when the performance of the unit component is reduced or the power is limited is counted.

[0049] Specifically, the average wind speed a and the corresponding power b of the wind turbine when the performance of the unit component is reduced or the power is limited are obtained, that is, the actual power generation data; the average wind speed and the corresponding power are used to obtain the power loss value. That is,

[0050] The average wind speed and the corresponding power are used to obtain the power loss value, including: referring to the corresponding power B of the actual power curve of the wind turbine, subtracting the actual power b when the performance of the wind turbine component is reduced, to obtain the power loss value bb of the single wind turbine component performance reduction time.

[0051] For example, when the performance of the component is reduced, such as high gear box oil temperature, the average wind speed a and the power b corresponding to the ten-minute point when the oil temperature is high are recorded. The average wind speed a corresponding to the time when the oil temperature is high is referred to the power B corresponding to the actual power curve, to obtain the power loss bb of the time when the oil temperature is high.

[0052] S150, the total loss power is obtained according to the power loss value of the wind turbine component.

[0053] Specifically, according to the performance reduction classification of the wind turbine component, the 1…n power loss values of each single wind turbine component performance reduction in the data of the wind turbine in the preset time period are accumulated to obtain the corresponding total loss power, and the total loss power is divided by the corresponding preset time period to obtain the total loss power.

[0054] For example, in the ten-minute data of the unit in one year, the 1…n bb of each single component performance reduction are accumulated to obtain the corresponding total loss power C, and the C is finally divided by the corresponding ten minutes to obtain the total loss power.

[0055] ​It should be understood that the power generation loss caused by the performance degradation of the high temperature generator shaft, high temperature converter IGBT, high temperature control cabinet and other components can be calculated by the above-mentioned power loss calculation method when the power is limited due to high oil temperature. Here is not repeated.

[0056] This embodiment takes the wind speed-power scatter plot and fitting curve of a certain wind farm No. 30 unit as an example, as shown in Figure 2 , the operation of the unit in the past year is described in detail, especially the quantitative method of the power loss caused by the performance degradation of the unit components. Through scientific big data analysis, the power loss caused by power limitation and fault shutdown of the unit is very obvious. The method of quantifying the power generation performance and power loss of the wind turbine in the wind farm, especially the power loss, including the power loss caused by the power limitation of the equipment itself, manual power limitation and power grid dispatching, is described.

[0057] The evaluation method of the operation of the wind turbine will be further described in combination with specific embodiments:

[0058] This example takes the ten-minute data of 33 units of a certain wind farm running for one year in 2020 as an example. The power loss quantification is shown in Table 1, Table 2 and Figure 3

[0059] Table 1: Summary of power loss of wind turbine

[0060]

[0061] As can be seen from the above table, the average wind speed of the wind turbine is 4.60 m / s, the average power limitation percentage of the unit is 12.93%, the percentage of normal power generation without power limitation is 58.62%, the percentage of shutdown operation is 28.45%, and the theoretical equivalent power generation hours of the unit are 1987.6 h.

[0062] According to the data analysis of the unit in 2020, the power loss caused by the power limitation of the unit is very obvious. The power loss caused by the power limitation (including high temperature of components, manual power limitation, dispatching power limitation and performance degradation of the unit) is 616.47 MWh, which is equivalent to 410.98 h of power loss per unit. According to the actual statistical situation of the site, the dispatching power limitation is rare, and the power limitation loss is mainly caused by manual power limitation or other factors that cause the unit to not be able to fully generate power. The power limitation of the key components of the unit is mainly caused by the overheating of the gear box oil temperature.

[0063] Table 2: Power loss table of key components of each wind turbine

[0064]

[0065] ​From the above table, it can be seen that the wind farm unit has a large area of high oil temperature load, the average unit oil temperature high load is 16.07 MWh, the total loss of power is 530.26 MWh, the total loss of hours is 353.51 hours, and the proportion is 2.61% (11 units have over-temperature limit power. 1 unit has cabin temperature over-temperature limit power, and other limit power conditions lose more power, such as manual limit power or dispatch limit power, a total of 19742.97 MWh, accounting for 97.05%.

[0066] From the above method, the power generation performance of the wind turbine can be quantified relatively scientifically, and the loss of wind turbine power generation caused by the performance degradation of the wind turbine components can be accurately quantified. The method provides strong data support for the hardware technical improvement direction of the old unit.

[0067] As shown in Figure 4 Another aspect of the present application provides an evaluation device 200 for the operation of a wind turbine, comprising an extraction module 210, a classification module 220, a fitting module 230, a statistical module 240 and a calculation module 250; wherein the extraction module 210 is used to extract data of a plurality of wind turbines in a preset time period on a preset platform; the classification module 220 is used to draw a power curve of each wind turbine and classify the data; the fitting module 230 is used to eliminate abnormal power generation data of the wind turbine and fit the actual power curve of the wind turbine; the statistical module 240 is used to count the power loss value when the performance of the unit components is degraded or limited power; and the calculation module 250 is used to obtain the total loss of power according to the power loss value of the wind turbine components.

[0068] The specific method of the embodiment is as follows: the ten-minute data of 33 units of a wind farm in 2020 in the intelligent operation and maintenance platform center is counted, wherein the ten-minute data mainly includes unit number, average wind speed, power, generator speed, limit power flag, variable pitch angle, component performance related temperature (such as gearbox oil temperature, generator shaft temperature, frequency converter IGBT temperature, etc.) and other information. According to the unit eliminating data during abnormal power generation, the unit's own fitted wind speed and power corresponding curve is drawn, which represents the actual wind speed and power corresponding relationship of the unit. When the performance of the components is degraded, such as high gearbox oil temperature, the average wind speed and power b of the ten-minute point corresponding to the high oil temperature are recorded when the oil temperature is high. The average wind speed corresponding to the high oil temperature is referred to the power B corresponding to the power curve, and the power loss at the time of high oil temperature limit power is B-b. The power loss corresponding to the high oil temperature is traversed in the ten-minute data of one year, and the total oil temperature high loss power is obtained. The sum of the power loss corresponding to the high oil temperature at all times is divided by 6, and the total loss of power F (unit: KW / h) is obtained.

[0069] The application provides a kind of wind turbine operating condition evaluation method and device, relative to prior art has the following beneficial effects: the evaluation method of the application can effectively identify the performance decline of unit components, and the loss of annual power generation is counted, and targeted hardware technical improvement provides technical support, guarantees the overall benefit of wind farm.

[0070] It can be understood that the above embodiments are only exemplary embodiments adopted for illustrating the principles of the present application, and the present application is not limited thereto. Various modifications and improvements can be made by those skilled in the art without departing from the spirit and essence of the present application, and these modifications and improvements are also considered as the protection scope of the present application.

Claims

1. A method for evaluating the operating status of a wind turbine generator set, characterized in that, include: Extract data from multiple wind turbine units over a preset time period on a preset platform; Plot the power curve for each wind turbine and categorize the data. Remove abnormal power generation data from the wind turbine and fit the actual power curve of the wind turbine; The power loss values ​​when the performance of unit components deteriorates or power is limited include: The average wind speed and corresponding power of the wind turbine unit are obtained when the performance of the unit components deteriorates or the power is limited; The power loss value is obtained based on the average wind speed and the corresponding power. The total power loss is calculated based on the power loss values ​​of the wind turbine components.

2. The method according to claim 1, characterized in that, The data includes at least one of the following: unit number, information wind speed, power, generator speed, power limit flag, pitch angle, and component temperature.

3. The method according to claim 1, characterized in that, The following classification principles are used for classification, including: selecting data when the wind turbine is shut down, data when the wind turbine is under power limitation, and data when the wind turbine is generating power normally, and obtaining the scatter distribution of wind speed and power corresponding to the wind turbine.

4. The method according to claim 1, characterized in that, The abnormal power generation data includes data on unit shutdowns and data corresponding to unit power limits.

5. The method according to claim 1, characterized in that, The fitting of the actual power curve of the wind turbine includes: The wind speed was divided into 225 intervals in increments of 0.1 m / s, from the initial wind speed of 2.5 m / s to the off-grid wind speed of 25 m / s. The power within each interval was counted, and the average power value was obtained to obtain the correspondence between the wind speed and the average power value for each interval. The actual power curve of wind speed and power was then plotted.

6. The method according to claim 1, characterized in that, The step of obtaining the power loss value based on the average wind speed and the corresponding power includes: By referring to the expected power B corresponding to the actual power curve of the fitted wind turbine, and subtracting the actual power b when the performance of the wind turbine component deteriorates, the power loss value bb of a single wind turbine component at the moment of performance deterioration is obtained.

7. The method according to claim 1, characterized in that, The process of obtaining the total power loss based on the power loss value of the wind turbine components includes: According to the classification of performance degradation of wind turbine components, the 1...n power loss values ​​of each individual wind turbine component in the data of the wind turbine over a preset time period are accumulated to obtain the corresponding total power loss. The total power loss is divided by the corresponding preset time period to obtain the total power loss.

8. The method according to any one of claims 1 to 7, characterized in that, The preset time period ranges from 5 minutes to 15 minutes; and / or, The preset platform is an intelligent operation and maintenance platform.

9. A device for evaluating the operating status of a wind turbine generator set, characterized in that, include: The module includes an extraction module, a classification module, a fitting module, a statistics module, and a calculation module; among them, The extraction module is used to extract data from multiple wind turbine units over a preset time period on a preset platform. The classification module is used to draw the power curve of each wind turbine and classify the data; The fitting module is used to remove abnormal power generation data of the wind turbine and fit the actual power curve of the wind turbine. The statistics module is used to calculate the power loss value when the performance of unit components deteriorates or power is limited, including: The average wind speed and corresponding power of the wind turbine unit are obtained when the performance of the unit components deteriorates or the power is limited; The power loss value is obtained based on the average wind speed and the corresponding power. The calculation module is used to calculate the total power loss based on the power loss value of the wind turbine components.

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