Method and device for determining the effect of deicing technology improvement of wind turbines

Abstract

The present disclosure proposes a method and device for determining the de-icing technical transformation effect of a wind turbine set, and relates to the technical field of wind power generation. The method includes: obtaining the operation data, operation and maintenance data, and meteorological data of the technical transformation wind turbine set during the icing period; determining the icing state of the wind turbine corresponding to the operation data according to the meteorological data and the operation data; determining the first icing rate of the technical transformation wind turbine set in the shutdown state and the second icing rate in the operation state based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data; determining the de-icing technical transformation effect of the technical transformation wind turbine set according to the first icing rate, the second icing rate, the historical icing period data, and the operation data when the icing state of the wind turbine is an un-icing state. Thus, the de-icing technical transformation effect of the technical transformation wind turbine set can be determined according to the icing rate reduction values ​​corresponding to the operation state and the shutdown state, respectively, and according to the operation data when the icing state of the wind turbine is an un-icing state, and the historical icing period data, which is very accurate and reliable.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wind power generation, and in particular to a method and device for determining the de-icing technical improvement effect of a wind turbine generator set. Background Art

[0002] In cold and wet areas, wind turbine blades are prone to ice formation, which in turn impairs the aerodynamic performance of the blades and reduces the power generation efficiency of the unit. There are many methods for blade deicing in the industry, such as surface coating, mechanical deicing, resistance wire heating deicing or gas heating deicing. By reforming the deicing method of wind turbine blades, the negative impact of environmental factors on the unit can be improved. After the technical transformation of a wind turbine, the technical transformation may fail, or the technical transformation effect may be poor or good. Accurate evaluation of the technical transformation effect of wind turbines is conducive to helping operators adjust the technical transformation method, thereby improving the power generation efficiency of wind turbines.

[0003] At present, how to evaluate the optimization effect of technical transformation on the de-icing of current wind turbine blades is a problem that needs to be solved. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] According to a first aspect of the present disclosure, a method for determining the effect of de-icing technical improvement of a wind turbine is proposed, comprising:

[0006] Obtain the operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbines during the icing period;

[0007] Determining, according to the meteorological data and the operating data, an icing state of the fan corresponding to the operating data;

[0008] Based on the operation data that the wind turbine is in a suspected icing state and the operation and maintenance data, determine a first icing rate of the technically modified wind turbine set in a shutdown state and a second icing rate in an operating state;

[0009] The deicing technical improvement effect of the technically improved wind turbine set is determined according to the first icing rate, the second icing rate, the historical icing period data, and the operation data when the wind turbine is in an uniced state.

[0010] According to a second aspect of the present disclosure, a device for determining the de-icing technical improvement effect of a wind turbine is proposed, comprising:

[0011] An acquisition module is used to obtain the operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbines during the icing period;

[0012] A first determination module, configured to determine, based on the meteorological data and the operation data, an icing state of the fan corresponding to the operation data;

[0013] A second determination module is used to determine a first icing rate of the technically modified wind turbine in a shutdown state and a second icing rate in an operating state, respectively, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data;

[0014] The third determination module is used to determine the deicing technical improvement effect of the technically improved wind turbine set according to the first icing rate, the second icing rate, the historical icing period data and the operation data of the wind turbine being in an un-iced state.

[0015] The third aspect of the present disclosure provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the present disclosure is implemented.

[0016] The fourth aspect embodiment of the present disclosure proposes a non-temporary computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method proposed in the first aspect embodiment of the present disclosure.

[0017] The fifth aspect of the present disclosure provides a computer program product. When an instruction processor in the computer program product executes, the method provided in the first aspect of the present disclosure is executed.

[0018] The method and device for determining the deicing technical improvement effect of a wind turbine set provided by the present disclosure have the following beneficial effects:

[0019] In the disclosed embodiment, the operation data, operation and maintenance data, and meteorological data of the technically modified wind turbine set during the icing period are first obtained, and then the icing state of the wind turbine corresponding to the operation data is determined based on the meteorological data and the operation data. Then, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data, the first icing rate of the technically modified wind turbine set in the shutdown state and the second icing rate in the running state are determined. Finally, based on the first icing rate, the second icing rate, the historical icing period data, and the operation data when the icing state of the wind turbine is an unicing state, the deicing technical modification effect of the technically modified wind turbine set is determined. Thus, the deicing technical modification effect of the technically modified wind turbine set can be determined based on the icing rate reduction values ​​corresponding to the running state and the shutdown state, respectively, and based on the operation data when the icing state of the wind turbine is an unicing state, and the historical icing period data, which is very accurate and reliable.

[0020] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 A flow chart of a method for determining the de-icing technical improvement effect of a wind turbine generator set provided in one embodiment of the present disclosure;

[0023] Figure 2 A schematic flow chart of a method for determining the de-icing technical improvement effect of a wind turbine generator set provided in yet another embodiment of the present disclosure;

[0024] Figure 3 A schematic flow chart of a method for determining the de-icing technical improvement effect of a wind turbine generator set provided in another embodiment of the present disclosure;

[0025] Figure 4 A schematic diagram of the structure of a device for determining the de-icing technical improvement effect of a wind turbine generator set provided in one embodiment of the present disclosure;

[0026] Figure 5 The present invention is a block diagram of an electronic device for implementing a method for determining the de-icing technical improvement effect of a wind turbine generator set according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0028] The following describes a method, device, electronic device, and storage medium for determining the de-icing technical improvement effect of a wind turbine generator set according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0029] The present disclosure provides a method for determining the effect of a de-icing technical modification of a wind turbine generator set. The method can be executed by a device for determining the effect of a de-icing technical modification of a wind turbine generator set provided by the present disclosure, and can also be executed by an electronic device provided by the present disclosure.

[0030] The following is a method for determining the de-icing technical improvement effect of a wind turbine set provided by the present disclosure, using a device for determining the de-icing technical improvement effect of a wind turbine set provided by the present disclosure, but it is not intended to limit the present disclosure.

[0031] Figure 1A schematic flow chart of a method for determining the effect of a de-icing technical modification of a wind turbine set provided in one embodiment of the present disclosure.

[0032] like Figure 1 As shown, the method for determining the de-icing technical improvement effect of the wind turbine generator set may include the following steps:

[0033] Step 101, obtaining operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbine generator set during the icing period.

[0034] The technically modified wind turbine generator set may be a wind turbine generator set that has undergone technical modification. In the present disclosure, the technical modification may be a technical modification of the deicing technology of the wind turbine generator set, such as surface coating, mechanical deicing, resistance wire heating deicing or gas heating deicing, which is not limited here.

[0035] The operating data may be unit power data, status parameters and control parameters of each device in the wind turbine unit, etc., which are not limited here.

[0036] The meteorological data may include temperature, humidity, wind speed, wind force level, air pressure, etc. There may be many types of meteorological data, which are not limited here.

[0037] Optionally, the device can obtain operating data and meteorological data of the technically upgraded wind turbines during the icing period based on a collection device at a designated location.

[0038] Among them, the collection device can be a temperature and humidity sensor, an air pressure sensor, an anemometer, etc., which is not limited here.

[0039] Among them, the designated location can be a predetermined location, and the data measured at the designated location can be more conducive to collecting operating data and meteorological data about the technical transformation wind turbine set. For example, a power collection system can be installed at the bottom of the tower of the technical transformation wind turbine set to collect the active power of the technical transformation wind turbine set.

[0040] For example, a wind measuring tower can be erected in advance at a position 2-4 times the diameter of the wind rotor in the main wind direction of the upgraded wind turbine. Its height should be at least consistent with the height of the wind turbine hub. An anemometer, wind vane, temperature and humidity sensors, air pressure sensor, etc. can be installed at the height of the wind measuring tower hub. A power collection system can be installed at the bottom of the wind turbine tower to collect the active power of the wind turbine, as well as some control parameters and status parameters of the unit.

[0041] Among them, the operation and maintenance data may include the icing status of the technical transformation wind turbine set, such as icing or non-icing, and the operating status of the wind turbine set, such as shutdown or normal operation, etc., which are not limited here.

[0042] It should be noted that the data in the freezing period and the non-freezing period are different, and the data of the wind turbines with technical transformation and those without technical transformation are also different. In this disclosure, only the data of the wind turbines with technical transformation in the freezing period are obtained. Alternatively, the historical operation data, historical operation and maintenance data, and historical meteorological data in the historical icer can also be obtained as a reference, which is not limited here.

[0043] Step 102, determining the icing state of the fan corresponding to the operating data according to the meteorological data and the operating data.

[0044] The icing state of the fan may be an uniced state or a suspected icing state, which is not limited here.

[0045] As a possible implementation method, the device can determine the temperature and humidity corresponding to each time period during the freezing period based on meteorological data.

[0046] It should be noted that one day can be used as a time period, or half a day, six hours, one minute, or half an hour can be used as a time period, and there is no limitation here.

[0047] Specifically, the total time included in the freezing period may be determined first, for example, if there are 30 days in total, then every half hour may be regarded as a time period, and the temperature or humidity corresponding to the time period may be determined.

[0048] It should be noted that the lowest temperature in the time period can be used as the temperature corresponding to the time period, or the median temperature of the time period can be used as the temperature corresponding to the time period, without limitation here. It is understandable that the temperature corresponding to each time period in the freezing period can be determined based on specific practical experience, without limitation here. Among them, the highest humidity in the time period can be used as the temperature corresponding to the time period, or the median humidity of the time period can be used as the humidity corresponding to the time period, without limitation here.

[0049] Furthermore, when the temperature corresponding to any time period is less than a first threshold and the humidity is greater than a second threshold, it can be determined that the fan icing state of the operation data corresponding to any time period is a suspected icing state.

[0050] The first threshold may be a temperature threshold, such as 2° C., and the second threshold may be a relative humidity threshold, such as 80%. Specifically, the first threshold and the second threshold may be set based on actual experience and are not limited here.

[0051] The relative humidity can be the percentage of the water vapor pressure in the air to the saturated water vapor pressure at the same temperature.

[0052] It should be noted that if the temperature corresponding to any time period is less than the first threshold and the humidity is greater than the second threshold, the operating data recorded in any time period can be determined as data in a suspected icing state, that is, it can be considered that under such temperature and humidity conditions, the wind turbine may be in an icing state, and thus the icing state of the wind turbine in the operating data corresponding to the time period can be determined as a suspected icing state.

[0053] It should be noted that if the operation and maintenance data records the icing of the fan unit, then regardless of the temperature and humidity values, the operation data will be classified as data in a suspected icing state.

[0054] Alternatively, the device may also determine that the fan icing state of the operating data corresponding to any time period is a non-icing state when the temperature corresponding to any time period is greater than the first threshold and / or the humidity is less than the second threshold.

[0055] It should be noted that if the temperature corresponding to any time period is greater than the first threshold, or the humidity is less than the second threshold, or the temperature is greater than the first threshold and the humidity is less than the second threshold, then the fan icing state of the operating data corresponding to the time period can be determined as a non-icing state, that is, the conditions for icing of the wind turbine are not met.

[0056] If the freezing of the fan unit is not recorded in the operation and maintenance data, the operation data will be classified as data in a non-freezing state regardless of the temperature and humidity values.

[0057] Step 103, based on the operation data and operation and maintenance data of the wind turbine in the suspected icing state, determine the first icing rate of the technically modified wind turbine in the shutdown state and the second icing rate in the operating state.

[0058] The first icing rate may be the ratio of the icing time of the technical transformation wind turbine in the shutdown state to the time of the suspected icing state. The second icing rate may be the ratio of the icing time of the technical transformation wind turbine in the running state to the time of the suspected icing state.

[0059] It should be noted that after the operation data is classified according to the icing state of the fan, the operation data can be divided into icing data in the time period of the suspected icing state and icing data in the non-icing state. Then, the time period of the shutdown state and the time period of the operating state in the suspected icing state can be determined according to the operation and maintenance data, and the time proportion of the shutdown state time period in the total suspected icing state is determined as the first icing rate, and the time proportion of the operating state time period in the total suspected icing state is determined as the second icing rate.

[0060] Step 104, determining the deicing effect of the technical transformation of the technical transformation wind turbine according to the first icing rate, the second icing rate, the historical icing period data, and the operation data of the wind turbine when the icing state is the unicing state.

[0061] As a possible implementation method, the device can calculate the average suspected freezing time and wind frequency distribution when the fan freezing state is a suspected freezing state based on historical freezing period data and operating data, meteorological data and operation and maintenance data of the current freezing period. The average suspected freezing time can be the average value of the suspected freezing time in the historical period and the current freezing period. The wind frequency distribution can be a relationship diagram of wind speed and frequency distribution in a suspected freezing state calculated based on historical freezing period data and current freezing period data. Furthermore, the measured wind power curve can also be calculated based on the operating data when the fan freezing state is an unfrozen state.

[0062] Furthermore, the first power generation increase value without freezing after the technical modification can be calculated based on the reduced freezing rate of the wind turbine after the technical modification, the measured wind power curve and wind frequency distribution, and the suspected freezing time. The power generation difference value caused by the shutdown of the wind turbine due to freezing after the technical modification can be calculated based on the reduced freezing rate of the shutdown data after the technical modification, the measured power curve and wind frequency distribution. Similarly, the power generation difference value caused by freezing during the operation of the wind turbine can be calculated.

[0063] Afterwards, the various power generation difference values ​​can be added together to determine the power generation improvement effect of the technically modified wind turbine set due to the technical transformation. If the power generation improvement is greater than the threshold, it means that the de-icing technical transformation effect of the technically modified wind turbine set is successful. If the power generation improvement is less than the threshold, it means that the de-icing technical transformation effect of the technically modified wind turbine set is a failure.

[0064] In the disclosed embodiment, the operation data, operation and maintenance data, and meteorological data of the technically modified wind turbine set during the icing period are first obtained, and then the icing state of the wind turbine corresponding to the operation data is determined based on the meteorological data and the operation data. Then, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data, the first icing rate of the technically modified wind turbine set in the shutdown state and the second icing rate in the running state are determined. Finally, based on the first icing rate, the second icing rate, the historical icing period data, and the operation data when the icing state of the wind turbine is an unicing state, the deicing technical modification effect of the technically modified wind turbine set is determined. Thus, the deicing technical modification effect of the technically modified wind turbine set can be determined based on the icing rate reduction values ​​corresponding to the running state and the shutdown state, respectively, and based on the operation data when the icing state of the wind turbine is an unicing state, and the historical icing period data, which is very accurate and reliable.

[0065] Figure 2 A schematic flow chart of a method for determining the de-icing technical improvement effect of a wind turbine generator set provided in yet another embodiment of the present disclosure.

[0066] like Figure 2 As shown, the method for determining the de-icing technical improvement effect of the wind turbine generator set may include the following steps:

[0067] Step 201, obtaining operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbine generator set during the icing period.

[0068] Step 202: Determine the icing state of the fan corresponding to the operating data according to the meteorological data and the operating data.

[0069] It should be noted that the specific implementation of steps 201 and 202 may refer to the above embodiments and will not be described in detail here.

[0070] Step 203: Draw a first measured power curve using the operating data of the fan when the icing state is the non-icing state.

[0071] The first measured power curve may be a wind power curve drawn based on operating data of the wind turbine after technical modification from an icing state to a non-icing state.

[0072] As a possible implementation method, the operating data of the wind turbine from the icing state to the non-icing state may be first cleaned and normalized, and then the wind speed may be divided according to a specified interval, and a first measured power curve may be drawn.

[0073] Among them, the power and wind speed are based on the parameters measured at the pre-set designated location.

[0074] The specified interval may be a wind speed interval of 0.5 m / s, that is, 0.5 m / s may be selected with reference to the IEC61400-12-1:2005 standard, thereby ensuring the accuracy and convergence of the calculation results. In the present disclosure, a wind speed and a wind turbine net power output may be uniquely determined based on each wind speed interval.

[0075] Specifically, during the operation of the wind turbine, the power changes with the wind speed at all times. Therefore, we can first determine the wind turbine output power corresponding to each wind speed, then calculate the average wind speed and average power in each interval, and then draw the first measured power curve to depict the functional relationship between the net electric power output of the wind turbine and the wind speed.

[0076] Step 204 : Compare the second measured power curve with the first measured power curve to determine the difference.

[0077] The second measured power curve is determined based on historical operating data of the non-icing state before the technical transformation. It should be noted that the second measured power curve can be a measured power curve determined based on historical data and historical operating data of the non-icing state before the technical transformation.

[0078] After the first measured power curve is determined, the first measured power curve and the second measured power curve may be compared to obtain a difference.

[0079] Step 205 , when the difference does not meet the preset condition, it is determined that the deicing effect of the technical transformation of the current wind turbine generator set is a failure.

[0080] Optionally, if the output power corresponding to each wind speed in the second measured power curve is greater than the output power corresponding to the first measured power curve, or if the difference between the output power corresponding to each wind speed in the second measured power curve and the output power corresponding to the first measured power curve is less than a preset threshold, it means that the de-icing effect of the current technical transformation wind turbine set has failed.

[0081] Step 206, determining the deicing effect of the technical transformation of the technical transformation wind turbine according to the first icing rate, the second icing rate, the historical icing period data, and the operation data of the wind turbine when the icing state is the unicing state.

[0082] It should be noted that the specific implementation of step 206 can refer to the above embodiment and will not be described in detail here.

[0083] In the disclosed embodiment, the operation data, operation and maintenance data and meteorological data of the technical transformation wind turbine set during the icing period are first obtained, and then the icing state of the wind turbine corresponding to the operation data is determined based on the meteorological data and the operation data, and then the first measured power curve is drawn using the operation data of the wind turbine icing state being a non-icing state, and then the second measured power curve and the first measured power curve are compared to determine the difference, wherein the second measured power curve is determined based on the operation data before the technical transformation, and then if the difference does not meet the preset conditions, the deicing effect of the current technical transformation wind turbine set is determined to be a failure, and finally the deicing technical transformation effect of the technical transformation wind turbine set is determined based on the first icing rate, the second icing rate, the historical icing period data and the operation data of the wind turbine icing state being a non-icing state. Therefore, it is possible to directly determine whether the deicing technical transformation effect is good based on the second measured power curve and the first measured power curve, and if the difference does not meet the preset conditions, the deicing effect of the technical transformation wind turbine set is determined to be a failure.

[0084] Figure 3 A schematic flow chart of a method for determining the de-icing technical improvement effect of a wind turbine set provided in another embodiment of the present disclosure.

[0085] like Figure 3 As shown, the method for determining the de-icing technical improvement effect of the wind turbine generator set may include the following steps:

[0086] Step 301, obtaining operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbine generator set during the icing period.

[0087] Step 302: Determine the icing state of the fan corresponding to the operating data according to the meteorological data and the operating data.

[0088] Step 303, based on the operation data of the wind turbine in the suspected icing state and the operation and maintenance data, determine the first icing rate of the technically modified wind turbine in the shutdown state and the second icing rate in the operating state.

[0089] Step 304 , plotting a first measured power curve using the operating data of the fan when the icing state is the non-icing state.

[0090] It should be noted that the specific implementation of step 301, step 302, step 303, and step 304 can refer to the above embodiment and will not be described in detail here.

[0091] Step 305, determining the first time when the freezing state of the fan is a suspected freezing state in each time period in the current freezing period, and the second time when the freezing state of the fan is a suspected freezing state in each time period in each historical freezing period in the historical freezing period data, wherein the historical freezing period data contains data of at least three historical freezing periods.

[0092] The first time may be the total time during which the freezing state of the fan is in a suspected freezing state in each time period in the current freezing period.

[0093] The second time may be the total time during which the wind turbine icing state is in a suspected icing state in each historical time period during the historical icing period.

[0094] Step 306: determine the average of the first time and each of the second times as the suspected freezing time.

[0095] The suspected freezing time may be the average time during which the freezing state of the fan is in the suspected freezing state determined based on the current freezing period and the historical freezing period.

[0096] For example, if the current first time is 12 days, and the second times are 10 days, 14 days, and 16 days respectively, the suspected freezing time can be calculated to be 13 days.

[0097] Step 307, determining the average wind frequency distribution corresponding to the suspected icing state according to the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time.

[0098] Specifically, after obtaining the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time, they can be divided according to temperature and humidity, and then the average suspected icing wind speed and wind frequency distribution in recent years, that is, the average wind frequency distribution, can be calculated.

[0099] The wind speed and wind frequency distribution may include the corresponding relationship between each wind speed and frequency distribution.

[0100] Among them, wind speed frequency can characterize the frequency of wind speed occurrence in each wind speed range. It is an important parameter in wind energy resource assessment and wind farm planning and design. It can well describe the status of wind energy resources at the wind farm site and directly affect the wind turbine selection, power generation estimation and economic benefit evaluation in wind farm construction.

[0101] It should be noted that the wind speed data is random and can be statistically processed according to the time series. Then, a wind speed frequency distribution model can be used to describe the wind speed frequency distribution characteristics of the wind farm.

[0102] Step 308, based on the difference between the historical freezing rate before the technical transformation and the first freezing rate and the difference between the historical freezing rate and the second freezing rate, respectively determine the first freezing rate difference corresponding to the shutdown state and the second freezing rate difference corresponding to the operating state.

[0103] Among them, the historical freezing rate can be the proportion of freezing time before the technical transformation in the suspected freezing time.

[0104] The first freezing rate difference may be a difference between the first freezing rate and the historical freezing rate, that is, a freezing rate reduction value corresponding to the shutdown state in the current suspected freezing data.

[0105] The second freezing rate difference may be a difference between the second freezing rate and the historical freezing rate, that is, a freezing rate reduction value corresponding to the operating state in the current suspected freezing data.

[0106] Step 309, determining the sum of the first freezing rate and the second freezing rate as the freezing rate after technical modification.

[0107] Step 310: determine a first power generation improvement value according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, the first measured power curve, the suspected icing time, and the average wind frequency distribution.

[0108] Specifically, the first icing rate reduction probability can be calculated according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, and then the first power generation improvement value can be calculated according to the following formula:

[0109] The first power generation increase value = the first icing rate reduction probability × the average wind frequency distribution value × the suspected icing time × the first measured power curve value.

[0110] Step 311: determine a second power generation increase value according to the first icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution.

[0111] Specifically, the second power generation increase value can be calculated according to the following formula:

[0112] The second power generation increase value = the first icing rate difference × the average wind frequency distribution value × the suspected icing time × the first measured power curve value.

[0113] Step 312: determining a third power generation increase value according to the second icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution.

[0114] Specifically, the second power generation increase value can be calculated according to the following formula:

[0115] The third power generation improvement value=the second icing rate difference value×the average wind frequency distribution value×the suspected icing time×the first measured power curve value.

[0116] Step 313: determining the de-icing technical improvement effect of the technical improvement wind turbine generator set according to the first power generation improvement value, the second power generation improvement value and the third power generation improvement value.

[0117] Specifically, the sum of the first power generation increase value, the second power generation increase value and the third power generation increase value can be determined as the power generation increase value of the current technically upgraded wind turbine after the technical upgrade.

[0118] It should be noted that if the power generation increase value of the current wind turbine after the technical transformation is greater than the preset threshold, that is, the power generation increase value is large, then it means that the de-icing technical transformation effect is good; if the power generation increase value of the current wind turbine after the technical transformation is lower than or equal to the preset threshold, that is, the power generation increase value is small, then it means that the de-icing technical transformation effect is poor.

[0119] In the disclosed embodiment, the operation data, operation and maintenance data and meteorological data of the technically modified wind turbine set during the icing period are first obtained, and then the icing state of the wind turbine corresponding to the operation data is determined based on the meteorological data and the operation data. Then, based on the operation data when the icing state of the wind turbine is a suspected icing state and the operation and maintenance data, a first icing rate of the technically modified wind turbine set in a shutdown state and a second icing rate in an operating state are determined respectively. The operation data when the icing state of the wind turbine is a non-icing state is used to draw a first measured power curve, and the first time when the icing state of the wind turbine is a suspected icing state in each time period in the current icing period and each second time when the icing state of the wind turbine is a suspected icing state in each time period in each historical icing period in the historical icing period data are determined, wherein the historical icing period data contains data of at least three historical icing periods, and the average of the first time and each second time is determined as the suspected icing time, and the suspected icing time is determined according to the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time. The average wind frequency distribution corresponding to the quasi-icing state, according to the first difference between the historical icing rate before the technical transformation and the first icing rate and the second difference between the historical icing rate and the second icing rate, respectively determine the first icing rate difference corresponding to the shutdown state and the second icing rate difference corresponding to the running state, determine the sum of the first icing rate and the second icing rate as the icing rate after the technical transformation, determine the first power generation increase value according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, the first measured power curve, the suspected icing time and the average wind frequency distribution, then determine the second power generation increase value according to the first icing rate difference, the first measured power curve, the suspected icing time and the average wind frequency distribution, then determine the third power generation increase value according to the second icing rate difference, the first measured power curve, the suspected icing time and the average wind frequency distribution, then determine the de-icing technical transformation effect of the technically modified wind turbine set according to the first power generation increase value, the second power generation increase value and the third power generation increase value. Therefore, the first icing rate difference, the second icing rate difference, the probability of ice rate reduction after technical modification, the average wind frequency distribution value, the suspected icing time, and the first measured power curve value can be combined to calculate the power generation increase of the wind turbine in the shutdown state, the power generation increase in the operating state, and the power generation increase in the un-iced state to determine the de-icing effect of the wind turbine, so that the determination of the de-icing effect of the wind turbine is more accurate and reliable.

[0120] Figure 4 It is a structural schematic diagram of a device for determining the de-icing technical improvement effect of a wind turbine set provided according to an embodiment of the present disclosure.

[0121] like Figure 4As shown, the device 400 for determining the de-icing technical improvement effect of the wind turbine generator set may include: an acquisition module 410 , a first determination module 420 , a second determination module 430 and a third determination module 440 .

[0122] An acquisition module is used to obtain the operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbines during the icing period;

[0123] A first determination module, configured to determine, based on the meteorological data and the operation data, an icing state of the fan corresponding to the operation data;

[0124] A second determination module is used to determine a first icing rate of the technically modified wind turbine in a shutdown state and a second icing rate in an operating state, respectively, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data;

[0125] The third determination module is used to determine the deicing technical improvement effect of the technically improved wind turbine set according to the first icing rate, the second icing rate, the historical icing period data and the operation data of the wind turbine being in an un-iced state.

[0126] Optionally, the acquisition module is specifically used to:

[0127] Based on the collection device at the designated location, the operation data and meteorological data of the technically upgraded wind turbines during the icing period are obtained.

[0128] Optionally, the first determining module is specifically configured to:

[0129] Based on the meteorological data, determining the temperature and humidity corresponding to each time period in the freezing period;

[0130] When the temperature corresponding to any time period is less than a first threshold value and the humidity is greater than a second threshold value, determining that the fan icing state of the operation data corresponding to any time period is a suspected icing state;

[0131] or,

[0132] When the temperature corresponding to any time period is greater than the first threshold and / or the humidity is less than the second threshold, it is determined that the fan icing state of the operation data corresponding to any time period is a non-icing state.

[0133] Optionally, the first determining module further includes:

[0134] A drawing unit, used for drawing a first measured power curve using the operation data of the wind turbine when the icing state is a non-icing state;

[0135] a comparing unit, configured to compare a second measured power curve with the first measured power curve to determine a difference, wherein the second measured power curve is determined based on historical operating data in a non-icing state before the technical modification;

[0136] The determination unit is used to determine that the deicing effect of the technical transformation of the current wind turbine generator set is a failure when the difference does not meet the preset condition.

[0137] Optionally, the drawing unit is specifically used to:

[0138] Data cleaning and normalization are performed on the operating data of the fan from the icing state to the non-icing state;

[0139] The wind speed is divided into specified intervals, and a first measured power curve is drawn.

[0140] Optionally, the third determining module is specifically configured to:

[0141] Draw a first measured power curve using the operating data of the fan when the icing state is a non-icing state;

[0142] Determine the first time when the icing state of the fan is a suspected icing state in each time period in the current icing period, and each second time when the icing state of the fan is a suspected icing state in each time period in each historical icing period in the historical icing period data, wherein the historical icing period data includes data of at least three historical icing periods;

[0143] Determine the average of the first time and each of the second times as the suspected freezing time;

[0144] determining, according to the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time, an average wind frequency distribution corresponding to the suspected icing state;

[0145] Determine a first freezing rate difference corresponding to the shutdown state and a second freezing rate difference corresponding to the running state according to a first difference between the historical freezing rate before the technical transformation and the first freezing rate and a second difference between the historical freezing rate and the second freezing rate;

[0146] Determine the sum of the first freezing rate and the second freezing rate as the freezing rate after technical transformation;

[0147] Determine a first power generation improvement value according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, the first measured power curve, the suspected icing time, and the average wind frequency distribution;

[0148] determining a second power generation increase value according to the first icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution;

[0149] determining a third power generation increase value according to the second icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution;

[0150] The de-icing technical improvement effect of the technical improvement wind turbine generator set is determined according to the first power generation improvement value, the second power generation improvement value and the third power generation improvement value.

[0151] In the disclosed embodiment, the operation data, operation and maintenance data, and meteorological data of the technically modified wind turbine set during the icing period are first obtained, and then the icing state of the wind turbine corresponding to the operation data is determined based on the meteorological data and the operation data. Then, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data, the first icing rate of the technically modified wind turbine set in the shutdown state and the second icing rate in the running state are determined. Finally, based on the first icing rate, the second icing rate, the historical icing period data, and the operation data when the icing state of the wind turbine is an unicing state, the deicing technical modification effect of the technically modified wind turbine set is determined. Thus, the deicing technical modification effect of the technically modified wind turbine set can be determined based on the icing rate reduction values ​​corresponding to the running state and the shutdown state, respectively, and based on the operation data when the icing state of the wind turbine is an unicing state, and the historical icing period data, which is very accurate and reliable.

[0152] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0153] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0154] like Figure 5As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0155] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0156] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as a method for determining the deicing technical modification effect of a wind turbine. For example, in some embodiments, the method for determining the deicing technical modification effect of a wind turbine may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method for determining the deicing technical modification effect of the wind turbine described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the method for determining the de-icing technical modification effect of the wind turbine generator system in any other appropriate manner (for example, by means of firmware).

[0157] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0158] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0159] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0160] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0161] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0162] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0163] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0164] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for determining the effect of deicing technology improvement of a wind turbine generator set, characterized in that: include: Obtain the operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbines during the icing period; Determining, according to the meteorological data and the operating data, an icing state of the fan corresponding to the operating data; Based on the operation data that the wind turbine is in a suspected icing state and the operation and maintenance data, determine a first icing rate of the technically modified wind turbine set in a shutdown state and a second icing rate in an operating state; Determining the deicing technical improvement effect of the technical improvement wind turbine set according to the first icing rate, the second icing rate, the historical icing period data, and the operation data when the wind turbine is in an uniced state; After determining the icing state of the fan corresponding to the operating data, the method further includes: Draw a first measured power curve using the operating data of the fan when the icing state is a non-icing state; Comparing a second measured power curve with the first measured power curve to determine a difference, wherein the second measured power curve is determined based on historical operating data in a non-icing state before the technical modification; When the difference does not meet the preset condition, it is determined that the deicing effect of the technical transformation of the current wind turbine generator set is a failure; The step of determining the deicing technical improvement effect of the technical improvement wind turbine generator set according to the first icing rate, the second icing rate, the historical icing period data, and the operation data of the wind turbine when the icing state is the unicing state includes: Draw a first measured power curve using the operating data of the fan when the icing state is a non-icing state; Determine the first time when the icing state of the fan is a suspected icing state in each time period in the current icing period, and each second time when the icing state of the fan is a suspected icing state in each time period in each historical icing period in the historical icing period data, wherein the historical icing period data includes data of at least three historical icing periods; Determine the average of the first time and each of the second times as the suspected freezing time; determining, according to the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time, an average wind frequency distribution corresponding to the suspected icing state; Determine a first freezing rate difference corresponding to the shutdown state and a second freezing rate difference corresponding to the running state according to a first difference between the historical freezing rate before the technical transformation and the first freezing rate and a second difference between the historical freezing rate and the second freezing rate; Determine the sum of the first freezing rate and the second freezing rate as the freezing rate after technical transformation; Determine a first power generation improvement value according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, the first measured power curve, the suspected icing time, and the average wind frequency distribution; determining a second power generation increase value according to the first icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution; determining a third power generation increase value according to the second icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution; The de-icing technical improvement effect of the technical improvement wind turbine generator set is determined according to the first power generation improvement value, the second power generation improvement value and the third power generation improvement value.

2. The method according to claim 1, characterized in that The acquisition of the operational data and meteorological data of the technically upgraded wind turbines during the icing period includes: Based on the collection device at the designated location, the operation data and meteorological data of the technically upgraded wind turbines during the icing period are obtained.

3. The method according to claim 1, characterized in that: The step of determining, based on the meteorological data and the operating data, a wind turbine icing state corresponding to the operating data comprises: Based on the meteorological data, determining the temperature and humidity corresponding to each time period in the freezing period; When the temperature corresponding to any time period is less than a first threshold value and the humidity is greater than a second threshold value, determining that the fan icing state of the operation data corresponding to any time period is a suspected icing state; or, When the temperature corresponding to any time period is greater than the first threshold and / or the humidity is less than the second threshold, it is determined that the fan icing state of the operation data corresponding to any time period is a non-icing state.

4. The method according to claim 1, characterized in that The step of drawing a first measured power curve using the operation data of the fan in a non-icing state when the fan is in an icing state includes: Data cleaning and normalization are performed on the operating data of the fan from the icing state to the non-icing state; The wind speed is divided into specified intervals, and a first measured power curve is drawn.

5. A device for determining the effect of deicing technology improvement of a wind turbine generator set, characterized in that: include: An acquisition module is used to obtain the operation data, operation and maintenance data, and meteorological data of the technically upgraded wind turbines during the icing period; A first determination module, configured to determine, based on the meteorological data and the operation data, an icing state of the fan corresponding to the operation data; A second determination module is used to determine a first icing rate of the technically modified wind turbine in a shutdown state and a second icing rate in an operating state, respectively, based on the operation data that the icing state of the wind turbine is a suspected icing state and the operation and maintenance data; A third determination module is used to determine the deicing technical improvement effect of the technical improvement wind turbine set according to the first icing rate, the second icing rate, the historical icing period data, and the operation data of the wind turbine when the icing state is an unicing state; The first determining module further includes: A drawing unit, used for drawing a first measured power curve using the operation data of the wind turbine when the icing state is a non-icing state; a comparing unit, configured to compare a second measured power curve with the first measured power curve to determine a difference, wherein the second measured power curve is determined based on historical operating data in a non-icing state before the technical modification; A determination unit, configured to determine that the deicing effect of the technical transformation of the current wind turbine generator set is a failure when the difference does not meet a preset condition; The third determination module is specifically used to: Draw a first measured power curve using the operating data of the fan when the icing state is a non-icing state; Determine the first time when the icing state of the fan is a suspected icing state in each time period in the current icing period, and each second time when the icing state of the fan is a suspected icing state in each time period in each historical icing period in the historical icing period data, wherein the historical icing period data includes data of at least three historical icing periods; Determine the average of the first time and each of the second times as the suspected freezing time; determining, according to the meteorological data corresponding to the first time and the historical meteorological data corresponding to each second time, an average wind frequency distribution corresponding to the suspected icing state; Determine a first freezing rate difference corresponding to the shutdown state and a second freezing rate difference corresponding to the running state according to a first difference between the historical freezing rate before the technical transformation and the first freezing rate and a second difference between the historical freezing rate and the second freezing rate; Determine the sum of the first freezing rate and the second freezing rate as the freezing rate after technical transformation; Determine a first power generation improvement value according to the difference between the historical icing rate before the technical transformation and the icing rate after the technical transformation, the first measured power curve, the suspected icing time, and the average wind frequency distribution; determining a second power generation increase value according to the first icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution; determining a third power generation increase value according to the second icing rate difference, the first measured power curve, the suspected icing time, and the average wind frequency distribution; The de-icing technical improvement effect of the technical improvement wind turbine generator set is determined according to the first power generation improvement value, the second power generation improvement value and the third power generation improvement value.

6. The device according to claim 5, characterized in that The acquisition module is specifically used for: Based on the collection device at the designated location, the operation data and meteorological data of the technically upgraded wind turbines during the icing period are obtained.

7. The device according to claim 5, characterized in that The first determining module is specifically configured to: Based on the meteorological data, determining the temperature and humidity corresponding to each time period in the freezing period; When the temperature corresponding to any time period is less than a first threshold value and the humidity is greater than a second threshold value, determining that the fan icing state of the operation data corresponding to any time period is a suspected icing state; or, When the temperature corresponding to any time period is greater than the first threshold and / or the humidity is less than the second threshold, it is determined that the fan icing state of the operation data corresponding to any time period is a non-icing state.

8. The device according to claim 5, characterized in that The drawing unit is specifically used for: Data cleaning and normalization are performed on the operating data of the fan from the icing state to the non-icing state; The wind speed is divided into specified intervals, and a first measured power curve is drawn.

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