CN114492936A - Wind power plant fan flying wadding intrusion early warning method based on numerical weather forecast - Google Patents

Abstract

The invention discloses a numerical weather forecast-based wind power plant fan flying wadding disturbance early warning method, which is used for analyzing the relation between growth characteristics and meteorological conditions aiming at poplar varieties in an early warning area and a peripheral radiation area thereof, determining the weather conditions of flying wadding, and establishing a meteorological early warning index of flying wadding disturbance by combining with the characteristics of a wind power plant fan. And early warning is given to the flying wadding invasion of the fan in a period of time in the future based on the observation data of the ground meteorological station and the numerical weather forecast result. The wind power plant fan flying wadding intrusion early warning method based on numerical weather forecast can effectively forecast the flying wadding starting time, judge the flying wadding grade and early warn the flying wadding intrusion condition in advance, is beneficial to fan maintenance personnel to formulate a reasonable maintenance plan, can obviously improve the wind power plant fan cleaning construction operation efficiency, provides a powerful basis for formulating a reasonable fan guarantee maintenance operation plan, and simultaneously improves the fan operation efficiency, prolongs the fan key component service life and reduces the wind power plant operation maintenance cost.

Description

An early warning method for wind farm fan flying flocculent infestation based on numerical weather forecast

technical field

The invention relates to the cross field of wind farm fan maintenance and weather forecasting and early warning, in particular to a wind farm fan flying flock intrusion early warning method based on numerical weather forecast.

Background technique

Poplars are distributed in Northwest my country, North China, Northeast China and the Yangtze River Basin, etc. The biological characteristics of their growth and development are closely related to the meteorological environment. Relevant studies have shown that when certain conditions are met, such as temperature, humidity and precipitation, poplar capsules gradually crack and produce flying flocs.

Poplar flycatcher not only reduces environmental quality, endangers people's health, and threatens the safety of public transportation, but also affects the safe and stable operation of wind farm fans. When the gear box and generator in the fan cabin are blocked by flying flakes, the ventilation volume will be reduced, and the cooling efficiency will be reduced, resulting in frequent high temperature failures of the gear box and generator, which will lead to a decrease in power generation and reduce the overall use of the unit. life.

Therefore, based on the weather forecast information, carrying out the early warning of flying flocculent intrusion for wind farm fans has important guiding role and economic value in carrying out the flying flocculent cleaning operation of the wind turbine, improving the operating efficiency of the wind turbine, prolonging the life of the key components of the wind turbine, and reducing the operation and maintenance cost of the wind farm. .

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a kind of early warning method for the infestation of wind farm fans based on numerical weather forecast, which can effectively predict the occurrence time of flying flocs, judge the level of flying flocs, and warn the infestation of flying flocs in advance, which is helpful for fan maintenance personnel to formulate Reasonable maintenance plan to improve the efficiency of blower cleaning.

In order to achieve the above object, the present invention provides the following technical solutions:

A method for early warning of wind farm fan flying flocculent infestation based on numerical weather forecast, comprising the following steps:

S1: Determine whether there are poplar trees around the wind farm, and determine the initial meteorological conditions of the flocculation period according to the species of poplar trees;

S2: Determine the meteorological factors that affect the concentration of flying flocs after they are produced;

S3: Determine the certified meteorological stations of the wind farm, correct the meteorological factors of the certified meteorological stations, and obtain the historical meteorological factors of the location of the wind farm;

S4: Acquire and process the meteorological factor data corresponding to the numerical weather forecast;

S5: Determine the infestation level of the wind farm fans and the meteorological factor threshold corresponding to each level;

S6. According to the historical meteorological factors and forecast meteorological factors of the wind farm, the initial date of the flying flocculent is calculated in a rolling manner, and the early warning level of the flying flocculent infestation of the fans of the wind farm is judged.

作为判断飞絮初始的气象因子。Further, in step S1, the effective accumulated temperature _Te , the daily average temperature

As a meteorological factor for judging the initial stage of flying floes.

日平均风速

日平均相对湿度

日累积降水量P、日照时数S。Further, the meteorological factors that affect the concentration of flying flocs after the flying flocs are produced in step S2 include: daily average temperature

Average daily wind speed

Average daily relative humidity

Daily cumulative precipitation P, sunshine hours S.

Further, the meteorological factors of the certified meteorological station in step S3 include: historical data of temperature, wind speed, humidity, precipitation, and sunshine hours.

Further, the method of correcting the meteorological factors of the reference weather station in step S3 is: according to the height difference between the wind farm and the reference station, using an empirical formula, correct the historical temperature sequence of the reference station, and obtain the position of the wind farm. historical temperature series.

Further, in step S4, the hourly temperature, wind speed, humidity, precipitation, and sunshine data of the numerical weather forecast for the next seven days at the wind farm location are obtained, and these meteorological factors are processed into daily data.

Further, in step S5, it is determined that the wind farm blower is infested by three levels, and the corresponding warnings include red warning, yellow warning and blue warning. Infestation, the blue warning indicates that the fan is infested by light fluff.

Further, step S5 determines the thresholds of temperature, wind speed, humidity, precipitation, and sunshine hours corresponding to the warning level.

Further, step S6 uses the daily average temperature and the effective accumulated temperature to determine the initial date of the flying floes according to the revised historical meteorological factors of the wind farm and the meteorological factors predicted in the next 7 days.

Further, based on the initial date of the flying flocculent, the daily average temperature, daily average wind speed, daily average relative humidity, daily accumulated precipitation, and sunshine hours are used to judge the early warning level of the flying flocculent infestation of wind farm fans.

Compared with the prior art, the beneficial effects of the present invention are:

According to the numerical weather forecast-based early warning method for infestation of wind farm fans by flying flocculents, the relationship between growth characteristics and meteorological conditions is analyzed for poplar species in the early warning area and its surrounding radiation areas, and the weather conditions for the occurrence of flying flocs are determined, combined with wind farm fans. characteristics, and establish a meteorological early warning index of flying flocculent infestation. Based on the observation data of ground meteorological stations and the results of numerical weather forecasting, an early warning is made for the infestation of wind turbines in the future. The method of the invention can effectively predict the occurrence time of flying flocs, judge the level of flying flocs, and warn the infestation of flying flocs in advance, which is helpful for fan maintenance personnel to formulate a reasonable maintenance plan, and can significantly improve the efficiency of wind farm fan cleaning and construction. Reasonable wind turbine guarantee and maintenance operation plan provides a strong basis, and at the same time improves the operation efficiency of wind turbines, prolongs the life of key components of wind turbines, and reduces the operation and maintenance costs of wind farms.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only described in the present invention. For some of the embodiments, those of ordinary skill in the art can also obtain other drawings according to these drawings.

FIG. 1 is a schematic flowchart of an early warning method provided by an embodiment of the present application.

FIG. 2 is the meteorological factor values obtained by the numerical weather forecast for the next 7 days (April 11 to 17) provided by the embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in Figure 1, a kind of early warning method of wind farm fan flying flocculent infestation based on numerical weather forecast of the present invention specifically includes the following steps:

作为判断飞絮初始的气象因子。(1) Judging whether there are poplar trees around the wind farm, comprehensively considering the meteorological conditions of poplar varieties and their flowering and budding stages, to determine the effective accumulated temperature T _e and the daily average temperature

As a meteorological factor for judging the initial stage of flying floes.

日平均风速

日平均相对湿度

日累积降水量P、日照时数S。(2) Determine the meteorological factors that affect the concentration of flying flocs after they are produced, these factors include the daily average temperature

Average daily wind speed

Average daily relative humidity

Daily cumulative precipitation P, sunshine hours S.

(3) Determine the certified meteorological stations of the wind farm, and extract the historical data of temperature, wind speed, humidity, precipitation, and sunshine hours of the certified meteorological stations. According to the height difference between the wind farm and the reference station, an empirical formula is used to correct the historical temperature sequence of the reference station to obtain the historical temperature sequence of the wind farm location.

(4) Obtain the hourly temperature, wind speed, humidity, precipitation, and sunshine data of the numerical weather forecast for the next 7 days at the location of the wind farm, and process these meteorological factors into daily data.

(5) Determine the three levels of flock infestation of wind farm fans, and the corresponding early warnings include red early warning, yellow early warning and blue early warning. A blue alert indicates that the fan is infested by mild flying fluff. Determine the thresholds of temperature, wind speed, humidity, precipitation, and sunshine hours corresponding to the warning level respectively.

(6) According to the revised historical meteorological factors of the wind farm and the meteorological factors predicted in the next 7 days, the daily average temperature and the effective accumulated temperature are used to determine the initial date of the flying floe; The average relative humidity, daily accumulated precipitation, and sunshine hours are used to judge the early warning level of the infestation of wind farm fans.

The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

Taking the early warning of flying flocculent infestation of a wind farm in Jiangsu Province in the next 7 days (April 11 to April 17) on April 10, 2021 as an example, a method for early warning of flying flocculent infestation of wind farm fans based on numerical weather forecast is described. Implementation steps:

(1) The main tree species distributed around the wind farm are aspen and black poplar. Considering the meteorological conditions of their growth and development stages such as flowering and budding, it is judged that the meteorological conditions for the start of the flying flakes are the effective accumulated temperature ≥ 480 ℃, and the daily average temperature is stable ≥ 14 °C.

日平均风速

日平均相对湿度

日累积降水量P、日照时数S。其中，温度、日照时数与飞絮浓度呈正相关；湿度与飞絮浓度呈负相关性；降水会抑制杨絮飘飞；风速在一定区间有助于杨絮飘飞，风速超过一定时，飞絮向远方传播，对风机的侵扰威胁减弱。(2) Determine the meteorological factors that affect the concentration of flying flocs after they are produced, these indicators include the daily average temperature

Average daily wind speed

Average daily relative humidity

Daily cumulative precipitation P, sunshine hours S. Among them, temperature and sunshine hours are positively correlated with the concentration of flying flocs; humidity is negatively correlated with the concentration of flying flocs; precipitation will inhibit the flying of poplars; the wind speed is in a certain range to help the flying of poplars, and when the wind speed exceeds a certain level, the flying The flocs spread to the distance, and the threat of intrusion to the fan is weakened.

(3) Determine the reference weather station of the wind farm, and extract the historical data of daily average temperature, daily average wind speed, daily average relative humidity, daily accumulated precipitation, and sunshine hours of the reference weather station. According to the height difference between the wind farm and the reference station, the following empirical formula is used to revise the historical temperature sequence of the reference station to obtain the historical temperature sequence of the wind farm location:

为风电场位置日平均温度，

为参证气象站日平均温度，H为风电场海拔，H_sta为参证气象站海拔。in,

is the daily average temperature at the location of the wind farm,

is the daily average temperature of the reference weather station, H is the altitude of the wind farm, and H _sta is the altitude of the reference weather station.

日平均风速

日平均相对湿度

日累积降水量P、日照时数S，其中日照时数为辐照度E大于等于120W/m²的时数之和。(4) Rollingly obtain the temperature (T), wind speed (W), relative humidity (RH), precipitation (P), irradiance (E) data of the numerical weather forecast for the next 7 days at the wind farm location, with a data resolution of 1 hour . Calculate the daily average temperature for the next 7 days according to the obtained hourly numerical weather forecast data

Average daily wind speed

Average daily relative humidity

Daily cumulative precipitation P, sunshine hours S, where sunshine hours are the sum of the hours when the irradiance E is greater ^than or equal to 120W/m2.

(5) It is determined that the infestation of the wind farm fans is divided into three levels, and the corresponding early warnings include red early warning, yellow early warning and blue early warning. The daily average temperature, daily average wind speed, daily average relative humidity, daily cumulative precipitation, and sunshine hours corresponding to each warning level are determined as shown in Table 1. When the meteorological factor meets multiple warning conditions at the same time, the highest warning level is preferred.

Table 1 Classification of early warning levels

Calculate the effective accumulated temperature according to the historical temperature series of the wind farm, and determine the starting date of the flying flocculent based on the effective accumulated temperature ≥ 480 ℃ and the daily average temperature is stable above 14 ℃ for two consecutive days. On the 25th, it indicated that the warning period was after the start date of the flying fluff. Further according to the meteorological factor threshold indicators of the early warning, it is judged that in the next seven days (April 11 to April 17), there will be no early warning for one day, that is, no flying floc infestation will occur; three days will be blue warning, and there will be mild flying flakes. The flock infestation occurs; there are two days of yellow warning, and there will be moderate flying flock infestation; one day, it is a red warning, and there will be severe flying flock infestation. The meteorological factors obtained from the numerical weather forecast from April 11 to 17 are shown in Figure 2, and the corresponding early warning results are shown in Table 2.

Table 2 Early warning results of flying flocculent infestation in a wind farm in Jiangsu in the next 7 days on April 10, 2021

date Warning level April 11, 2021 none April 12, 2021 blue alert April 13, 2021 blue alert April 14, 2021 blue alert April 15, 2021 Yellow Alert April 16, 2021 red alert April 17, 2021 Yellow Alert

To sum up, carrying out the early warning service for wind farm fan flying floes intrusion based on the above method can significantly improve the efficiency of wind farm fan cleaning and construction, and provide a strong basis for formulating a reasonable fan protection and maintenance operation plan.

It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any relationship between these entities or operations. any such actual relationship or sequence exists. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device that includes a list of elements includes not only those elements, but also includes not explicitly listed or other elements inherent to such a process, method, article or apparatus. Without further limitation, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

Each embodiment in this specification is described in a related manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the apparatus embodiments, the electronic device embodiments, the computer-readable storage medium embodiments, and the computer program product embodiments, since they are basically similar to the method embodiments, the descriptions are relatively simple, and for relevant details, refer to the method embodiments part of the description.

The above-mentioned embodiments are only specific implementations of the present application, and are used to illustrate the technical solutions of the present application, but not to limit them. The protection scope of the present application is not limited thereto. Detailed description, those of ordinary skill in the art should understand: any person skilled in the art is within the technical scope disclosed in this application, and it can still modify the technical solutions described in the foregoing embodiments or can easily think of changes, Alternatively, equivalent replacements are made to some of the technical solutions; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the present application. All should be covered within the scope of protection of this application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims (10)

1. A wind power plant fan flying wadding intrusion early warning method based on numerical weather forecast is characterized by comprising the following steps:

s1: judging whether poplar trees exist around the wind power plant, and determining the initial meteorological conditions of the flying time of the poplar trees according to the varieties of the poplar trees;

s2: determining meteorological factors influencing the flying floc concentration after the flying floc is generated;

s3: determining a participating meteorological station of a wind power plant, correcting meteorological factors of the participating meteorological station to obtain historical meteorological factors of the position of the wind power plant;

s4: acquiring and processing meteorological factor data corresponding to the numerical weather forecast;

s5: determining the flying wadding intrusion grade of a fan of a wind power plant and a meteorological factor threshold value corresponding to each grade;

and S6, rolling to calculate the initial flying catkin date according to the historical meteorological factors and the forecast meteorological factors of the wind power plant, and judging the early warning level of the wind power plant fan flying catkin intrusion.

2. The numerical weather forecast-based wind farm fan flying catkin intrusion warning method according to claim 1, wherein in step S1, effective accumulated temperature T is used_eAverage daily temperature

As a meteorological factor for judging the initial flying catkin.

3. The wind farm fan flying floc intrusion early warning method based on numerical weather forecast according to claim 1, wherein the meteorological factors influencing the concentration of flying flocs after the flying flocs are generated in step S2 comprise: average daily temperature

Average daily wind speed

Average daily relative humidity

Daily cumulative precipitation P and sunshine hours S.

4. The wind farm fan flying catkin intrusion early warning method based on numerical weather forecast according to claim 1, wherein the step S3 of proving meteorological factors of a meteorological station comprises: historical temperature, wind speed, humidity, precipitation, sunshine hours data.

5. The wind farm fan flying catkin intrusion early warning method based on numerical weather forecast according to claim 4, characterized in that the method for correcting meteorological factors of the witness-participating meteorological station in step S3 is as follows: and correcting the historical temperature sequence of the reference station by adopting an empirical formula according to the height difference between the wind power plant and the reference station to obtain the historical temperature sequence of the position of the wind power plant.

6. The numerical weather forecast-based wind farm fan flying catkin disturbance early warning method according to claim 1, characterized in that time-by-time temperature, wind speed, humidity, precipitation and sunshine data of a weather forecast of a value of 7 days in the future at the position of the wind farm are obtained in step S4, and the meteorological factors are processed into day-by-day data.

7. The wind farm fan flying wadding intrusion early warning method based on the numerical weather forecast according to claim 1, characterized in that step S5 determines that wind farm fan flying wadding intrusion is in three levels, the corresponding early warnings include a red early warning, a yellow early warning and a blue early warning, the red early warning indicates that the fan is severely flying wadding intrusion, the yellow early warning indicates that the fan is moderately flying wadding intrusion, and the blue early warning indicates that the fan is slightly flying wadding intrusion.

8. The wind farm fan flying catkin intrusion early warning method based on numerical weather forecast of claim 7, characterized in that step S5 determines the temperature, wind speed, humidity, precipitation and sunshine hours threshold values corresponding to the early warning level.

9. The wind farm fan flying wadding intrusion early warning method based on the numerical weather forecast as recited in claim 1, wherein step S6 is implemented to determine the initial date of flying wadding by using the daily average temperature and the effective accumulated temperature according to the corrected historical meteorological factors of the wind farm and the meteorological factors forecasted in the next 7 days.

10. The wind farm fan flying wadding intrusion early warning method based on the numerical weather forecast according to claim 9, characterized in that the wind farm fan flying wadding intrusion early warning level is judged by utilizing daily average temperature, daily average wind speed, daily average relative humidity, daily accumulated precipitation and sunshine hours based on the initial flying wadding date.

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