CN117689076A - Mountain wind farm fan blade icing prediction method and program product - Google Patents
Mountain wind farm fan blade icing prediction method and program product Download PDFInfo
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Abstract
The invention discloses a mountain wind power plant fan blade icing prediction method and a program product, wherein the method is provided with a plurality of fan blade icing prediction models corresponding to a plurality of mountain wind power plant micro-terrain areas one by one, and comprises the following steps: based on the current mountain wind power plant micro-terrain area, selecting a fan blade icing prediction model corresponding to the current mountain wind power plant micro-terrain area as a current fan blade icing prediction model; based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm; and inputting the meteorological element prediction result into a current fan blade icing prediction model, and obtaining the predicted fan blade icing thickness based on the formula d=f (g (A), m (B)). The invention can timely and accurately predict the icing condition of the fan blade.
Description
Technical Field
The invention relates to the technical field of power grids, in particular to a method, equipment, medium and program product for predicting ice coating of a fan blade of a mountain wind farm.
Background
The blade is a power spring of a wind driven generator (fan for short), is one of key components of the fan, and the quality of the state of the blade directly influences the performance and the power generation efficiency of the whole machine.
The fan is generally installed in mountain region and limit region, and when ambient humidity is great and the temperature is less than zero degree, the blade is very easy icing. Typically, blade icing occurs first at the airfoil-sensitive leading edge, which significantly reduces the blade lift coefficient, increases the blade drag coefficient, and results in reduced power generation. When icing is serious, the airfoil stall attack angle can be advanced, the blade enters a stall area, and the pneumatic characteristics are severely fluctuated, so that the blade flutter is caused, even the resonance of the whole machine is caused, the additional load fluctuation and structural vibration of the blade can greatly damage the fatigue life of the blade. Meanwhile, the additional weight of ice cubes and the huge change of the lift resistance coefficient caused by ice coating can obviously increase the static load and the dynamic load of the whole machine, and the ultimate overload is most likely to be finally caused, so that the blade is broken and even the fan overturns as a disaster result. Therefore, when the blade is seriously frozen, the machine should be stopped, so that the damage caused by the operation of the fan with ice can be prevented, and the more serious icing caused by the fact that the blade continues to rotate rapidly can be avoided. However, the shutdown of the blower can cause huge economic loss to the wind farm. Therefore, the research on the deicing technology of the fan blade has great significance for improving the safety, the reliability and the electric quantity of the fan, and the deicing prediction of the fan blade can provide a basis for deicing.
In the process of realizing the technical scheme of the embodiment of the invention, the inventor at least discovers that the following technical problems exist in the prior art:
at present, most wind power plant icing prediction is based on wind power plant environment historical data and on-site sensor data to form a sample set for wind turbine icing prediction. However, when icing is predicted, the fan freezing process has begun.
The wind power plant icing prediction technology still has the series problems that the icing time, the icing thickness, the icing range and other information of the fan blade cannot be accurately predicted, a scientific logic judgment basis is lacked for starting and stopping a fan blade deicing system, and great difficulty is brought to accurate and efficient deicing work.
In summary, the prior art cannot predict the icing condition of the fan blade timely and accurately.
Disclosure of Invention
The embodiment of the invention provides a method, equipment, medium and program product for predicting ice coating of fan blades of a mountain wind power plant, which solve the technical problem that the prior art cannot predict the ice coating condition of the fan blades timely and accurately.
In one aspect, the embodiment of the invention provides an icing prediction method for a mountain wind farm fan blade, which is applied to an icing prediction system for the mountain wind farm fan blade, wherein the icing prediction system for the mountain wind farm fan blade is provided with a plurality of fan blade icing prediction models corresponding to a plurality of mountain wind farm micro-terrain areas one by one, and the method comprises the following steps: selecting a fan blade icing prediction model corresponding to a current mountain wind power plant micro-terrain area as a current fan blade icing prediction model based on the current mountain wind power plant micro-terrain area; based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm; inputting the meteorological element prediction result into the current fan blade icing prediction model, and obtaining the predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness.
Optionally, before the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area is selected as the current fan blade icing prediction model, the method further includes: and dividing the mountain wind power plant micro-terrain area according to the altitude sum and the micro-terrain characteristics.
Optionally, before the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area is selected as the current fan blade icing prediction model, the method further includes: acquiring a meteorological element detection value of the current mountain wind power plant micro-terrain area; and establishing the current fan blade icing prediction model based on the meteorological element detection value.
Optionally, after the current fan blade icing prediction model is established, the method further includes: acquiring a meteorological element historical value of the current mountain wind power plant micro-terrain area; and correcting the current fan blade icing prediction model based on the meteorological element historical value.
Optionally, the meteorological element observed value of the current mountain wind farm micro-terrain area is specifically: wind field basic data, satellite monitoring data, microclimate monitoring data and geographic data of the current mountain wind power field micro-terrain area.
Optionally, before the weather element prediction result is input into the current fan blade icing prediction model, the method further includes: and correcting the weather element prediction result.
On the other hand, the embodiment of the invention also provides computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the mountain wind farm fan blade icing prediction method when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, wherein the computer program realizes the steps of the mountain wind farm fan blade icing prediction method when being executed by a processor.
The embodiment of the invention also provides a computer program product, which comprises a computer program, wherein the computer program realizes the steps of the mountain wind farm fan blade icing prediction method when being executed by a processor.
One or more technical solutions provided in the embodiments of the present invention at least have the following technical effects or advantages:
the mountain wind farm fan blade icing prediction method is applied to a mountain wind farm fan blade icing prediction system, the mountain wind farm fan blade icing prediction system is provided with a plurality of fan blade icing prediction models corresponding to a plurality of mountain wind farm micro-terrain areas one by one, and the method comprises the following steps: selecting a fan blade icing prediction model corresponding to a current mountain wind power plant micro-terrain area as a current fan blade icing prediction model based on the current mountain wind power plant micro-terrain area; based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm; inputting the meteorological element prediction result into the current fan blade icing prediction model, and obtaining the predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness.
According to the invention, according to the micro-terrain area of the current mountain wind power plant and the micro-terrain where the fan blades are located, the corresponding fan blade icing prediction model is selected as the current fan blade icing prediction model, the current fan blade icing prediction model is generated according to the characteristics of the micro-terrain area of the current mountain wind power plant, the fan blade icing prediction model is more fit with the field environment, the accuracy of predicting the icing thickness of the fan blade can be improved, for example, the 24-hour icing prediction accuracy reaches more than 70%, and the technical problem that the icing condition of the fan blade cannot be accurately predicted in the prior art is solved.
According to the weather element prediction result of the current wind power plant micro-terrain area, the method can generate the predicted fan blade icing thickness in advance based on the formula d=f (g (A), m (B)), so that the technical problem that the fan blade icing condition cannot be predicted timely in the prior art is solved, for example, the weather element prediction result is weather elements after 3 days, the predicted fan blade icing thickness can be generated 3 days in advance, and the fan blade icing condition can be obtained timely. Therefore, the invention can timely and accurately predict the icing condition of the fan blade.
Further, before the selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model, the method further comprises: and dividing the mountain wind power plant micro-terrain area according to the altitude sum and the micro-terrain characteristics. The mountainous wind farm micro-terrain areas with different characteristics can be divided.
Still further, before the selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model, the method further comprises: acquiring a meteorological element detection value of the current mountain wind power plant micro-terrain area; and establishing the current fan blade icing prediction model based on the meteorological element detection value. The current fan blade icing prediction model can be generated.
Still further, after the establishing the current fan blade icing prediction model, the method further includes: acquiring a meteorological element historical value of the current mountain wind power plant micro-terrain area; and correcting the current fan blade icing prediction model based on the meteorological element historical value. The accuracy of the current fan blade icing prediction model can be improved.
Furthermore, the meteorological element observation value of the current mountain wind farm micro-terrain area is specifically: wind field basic data, satellite monitoring data, microclimate monitoring data and geographic data of the current mountain wind power field micro-terrain area. Comprehensive and diversified meteorological element observations can be obtained.
Still further, before the inputting the weather element prediction result into the current fan blade icing prediction model, the method further includes: and correcting the weather element prediction result. The accuracy of the weather element prediction result can be improved.
Drawings
FIG. 1 is a flow chart of a mountain wind farm fan blade icing prediction method in an embodiment of the invention;
FIG. 2 is a flow chart of a mesoscale-large vortex simulation mode in an embodiment of the present invention;
FIG. 3 is an overall flow chart of a mountain wind farm fan blade icing prediction and early warning system in an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, equipment, medium and program product for predicting ice coating of fan blades of a mountain wind power plant, which solve the technical problem that the prior art cannot predict the ice coating condition of the fan blades timely and accurately.
The technical scheme of an embodiment of the invention aims to solve the problems, and the general idea is as follows:
the mountain wind farm fan blade icing prediction method is applied to a mountain wind farm fan blade icing prediction system, the mountain wind farm fan blade icing prediction system is provided with a plurality of fan blade icing prediction models which are in one-to-one correspondence with a plurality of mountain wind farm micro-terrain areas, and the method comprises the following steps: based on the current mountain wind power plant micro-terrain area, selecting a fan blade icing prediction model corresponding to the current mountain wind power plant micro-terrain area as a current fan blade icing prediction model; based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm; inputting a meteorological element prediction result into a current fan blade icing prediction model, and obtaining a predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness. According to the invention, a corresponding fan blade icing prediction model is selected from a plurality of fan blade icing prediction models to serve as the current fan blade icing prediction model according to the current mountain wind power plant micro-terrain area, the current fan blade icing prediction model is generated according to the characteristics of the current mountain wind power plant micro-terrain area, the fan blade icing prediction model is more fit with the field environment, the accuracy of predicting the fan blade icing thickness can be improved, for example, the 24-hour icing prediction accuracy reaches more than 70%, and the technical problem that the fan blade icing condition cannot be accurately predicted in the prior art is solved. According to the weather element prediction result of the current wind power plant micro-terrain area, the invention can predict the icing thickness of the fan blade in advance based on the formula d=f (g (A), m (B)), solves the technical problem that the icing condition of the fan blade cannot be predicted in time in the prior art, for example, the weather element prediction result is weather element after 3 days, the icing thickness of the fan blade can be predicted in advance by 3 days, and the icing condition of the fan blade can be obtained in time. Therefore, the invention can timely and accurately predict the icing condition of the fan blade.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. It will be apparent that the described embodiments of the invention are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The mountain wind farm fan blade icing prediction method is applied to a mountain wind farm fan blade icing prediction system, and the mountain wind farm fan blade icing prediction system is provided with a plurality of fan blade icing prediction models which are in one-to-one correspondence with a plurality of mountain wind farm micro-terrain areas. Specifically, the mountain wind power plant fan blade icing prediction system generates different fan blade icing prediction models according to different mountain wind power plant micro-terrain areas, and the mountain wind power plant micro-terrain areas correspond to the fan blade icing prediction models one by one. In the following, a micro-terrain area of a Tianhu mountain wind farm will be described as an example.
Referring to fig. 1, a detailed description is given of a method for predicting ice coating on a fan blade of a mountain wind farm according to an embodiment of the present invention.
Step 101: based on the current mountain wind power plant micro-terrain area, selecting a fan blade icing prediction model corresponding to the current mountain wind power plant micro-terrain area as a current fan blade icing prediction model;
step 102: based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm;
step 103: inputting a meteorological element prediction result into a current fan blade icing prediction model, and obtaining a predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness.
When the mountain wind farm fan blade icing prediction system is started, starting to execute step 101: and selecting a fan blade icing prediction model corresponding to the current mountain wind power plant micro-terrain area as a current fan blade icing prediction model based on the current mountain wind power plant micro-terrain area.
Step 101 is implemented in the following steps: and acquiring the current mountain wind power plant micro-topography area as a Tianhu mountain wind power plant micro-topography area. Based on a microtopography area of a Tianhu mountain wind power plant, a Tianhu mountain wind turbine blade icing prediction model is selected from a plurality of wind turbine blade icing prediction models in a mountain wind power plant wind turbine blade icing prediction system to serve as a current wind turbine blade icing prediction model, and the current wind turbine blade icing prediction model is a Tianhu mountain wind turbine blade icing prediction model.
After the current fan blade icing prediction model is obtained, step 102 is performed: and based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, obtaining a meteorological element prediction result of the current mountain wind power plant micro-terrain area through a medium-small scale mode coupling multiple nested numerical prediction algorithm.
Step 102 is implemented in the following manner: and generating weather element prediction results such as precipitation, flow field, vertical temperature profile and the like based on coupling nesting of the mesoscale numerical prediction mode and the small scale mode by using a multiple nesting numerical prediction algorithm of the mesoscale mode coupling of the super-computing platform.
Acquiring meteorological element observations of a micro-terrain area of a Tianhu mountain wind power plant, for example: the observed value of the meteorological element is an observed sequenceWherein S is 0 Each meteorological element observation is represented, n represents a time step, and the time resolution of the meteorological element observation is 15 minutes.
6 multiscale simulation regions were designed. First, a mesoscale simulation was performed in the mesoscale simulation areas numbered D01, D02, and D03. Then, three small-scale simulation areas with design numbers D04, D05, and D06, respectively, inside the middle-scale simulation area are assigned to the large-vortex simulation. To capture the impact of mesoscale circulation on local weather development, mesoscale simulation was employed. In all simulations, the D04 small-scale simulation region was driven by the D03 medium-scale simulation region, which provided the initial and boundary conditions required for operation of the D04 small-scale simulation region, which was interpolated horizontally in time by overlapping quadratic methods and vertically in the vertical direction by linear logarithmic methods.
In all mode simulations, there are 51 sigma layers in the vertical direction.
As shown in fig. 2, large vortex simulation is embedded in the innermost subdomain of the mesoscale numerical prediction mode, and the prediction result of the innermost subdomain of the mesoscale numerical prediction mode is used as an initial field of the large vortex simulation, so that the timeliness and the accuracy of the prediction are improved through the rapid cycle assimilation prediction system. Since large vortex simulation is inherently a search for a suitable filtering scale, multiple experiments are required in adjusting the grid scale to search for an optimally combined nested grid scheme of the mesoscale-large vortex simulation coupling mode. The key to the adjustment is the adjustment of d02 mode integration, because d02 is a subdomain of d01, while d02 is a parent domain of d03, d02 plays a role in going up and down. The mode integral adjustment of d02 is mainly to adjust the grid scale of the domain and the parameterization scheme of the domain. The comparison with the observed values of the meteorological elements is performed according to the standard that the average relative error is not more than 15 percent. Because the number of nesting layers is large, the nesting scheme needs to be adjusted layer by layer from the global scale of the outer layer to the internal small scale.
Based on a mesoscale-large vortex simulation coupling mode, a plurality of sets of nested layer by layer and a numerical forecasting mode which is amplified step by step are built by taking a Tianhu mountain wind power plant as a center, wherein the horizontal resolution of a level with highest precision can reach 30m multiplied by 30m. And (3) obtaining a weather element prediction result of the micro-topography area of the Tianhu mountain wind power plant through mode integration, wherein the time resolution is 15 minutes.
With continued reference to fig. 1, after obtaining the weather element prediction result of the current mountain wind farm micro-terrain area, step 103 is started to be executed: inputting a meteorological element prediction result into a current fan blade icing prediction model, and obtaining a predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness.
Step 103 is performed in the specific implementation process, for example: based on the weather element prediction results of precipitation, flow field, vertical temperature profile and the like of a mesoscale numerical prediction mode of 3km multiplied by 3km, the weather mountain fan blade icing prediction model outputs a fan blade icing prediction result, and the specific process is as follows.
Step one, constructing a measurement equation
P t ＝X t β t +ε t
Wherein P is a predicted amount, P t ＝[p 1 ,p 2 ,...,p l ] T t ，β t Is a regression coefficient matrix, b is a regression coefficient, and beta t ＝[b 1 ,b 2 ,...,b l ] T t ，ε t For measuring noise, the noise is an l-dimensional random vector, T represents transposition, T represents the T-th moment, and X t To be a predictor matrix, x l，m-1 As the forecasting factor, l is the forecasting time length, m is the number of meteorological elements, and
applying a least square method to construct a forecast equation:
wherein the method comprises the steps ofX is the weather element prediction result t For the predictor matrix->And the regression coefficient estimated value at the time t.
Step two: taking data at the time t+delta t, repeating the first step to obtain the regression coefficient estimated value at the time t+delta t
Step three: estimating the variance W of dynamic noise:
step four: according to step one, component-by-component residuals (delta can be calculated in step three 1 ,δ 2 ,...,δ l ) Thereby, the variance matrix V of the measurement noise can be calculated:
step five: let t beError variance matrix is C t (m×m dimensions), i.e.:
C t-1 ＝0
step six: assume thatIs a good approximation of the icing thickness, then its dynamic noise and measurement noise ε can be considered t The random vectors with the mean value of 0, which are not related to each other, are respectively set as W and V. The generalized least square method is applied, and then:
R t ＝C t-1 +W
the above formula constitutes the recurrence from the time t-1 to the time t, the recurrence is sequentially performed by taking the time step length as 15 minutes, and the calculation of the icing thickness of the fan at each time in the future of the wind power plant can be realized by utilizing the equivalent value sequentially determined from the step one to the step five.
Step seven: based on the following formula, the predicted fan blade icing thickness is obtained:
d＝f(g(A),m(B))
wherein g (A) is a prediction result of a medium-small scale mode coupling multiple nested numerical prediction meteorological element, m (B) is a micro-terrain area fan blade icing model, f is a current fan blade icing prediction model, and d is a predicted fan blade icing thickness.
It should be noted that, in the wind farm fan blade icing prediction method of the embodiment of the present invention, no sequence is executed between the step 101 and the step 102, and the step 101 may be executed first, then the step 102 may be executed, or the step 102 may be executed first, then the step 101 may be executed, which is not a limitation of the present invention.
In order to divide the mountain wind farm micro-terrain areas with different characteristics, before selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model in step 101, the method further includes: and dividing the mountain wind power plant micro-terrain area according to the altitude sum and the micro-terrain characteristics.
In a specific implementation, for example: and acquiring the altitude and micro-topography characteristics of the wind power plant, and dividing the micro-topography area of the mountain wind power plant according to the difference of the altitude and the micro-topography characteristics. The region with the altitude and the micro-terrain features in the same range can be divided into the micro-terrain regions of the same mountain wind farm. For example, the Taihe county region wind farm can be divided into a Tianhu mountain wind farm micro-terrain region, a fishing typhoon wind farm micro-terrain region and a tea garden wind farm micro-terrain region, and the 22 fan set of the Tianhu mountain wind farm can be divided into a plurality of micro-terrain regions, so that the division precision can be adjusted according to actual requirements.
In order to generate the current fan blade icing prediction model, before selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model in step 101, the method further comprises: acquiring a meteorological element detection value of a current mountain wind power plant micro-terrain area; and establishing a current fan blade icing prediction model based on the meteorological element detection value.
In a specific implementation, for example: according to the characteristics of icing types such as rime, rime and mixed rime of the blades, the meteorological element detection values of the micro-terrain areas of the Tianhu mountain wind power plant are obtained, wherein the meteorological elements comprise air pressure, temperature, humidity, wind speed, wind direction, tip speed, precipitation and the like. Aiming at the difficulties of different weather and complex geographical environment of a Tianhu mountain wind power plant, the method is used for carrying out on-site detection in a mode of deploying fine detection of a cloud radar, a microwave radiometer and a laser wind radar, and detecting weather microclimate characteristics and geographical characteristics of a fan group taking a Tianhu mountain booster station as the center in an icing period to obtain meteorological elements such as air pressure, temperature, humidity, wind speed, wind direction, tip speed, precipitation, air cloud water content, temperature profile and the like so as to obtain data conditions for establishing a Tianhu mountain wind turbine blade icing prediction model aiming at unique topographic characteristics and meteorological characteristics of Tianhu mountain. The microwave radiometer uses the microwave principle to calculate the high altitude temperature profile by inversion. The cloud testing radar is used for transmitting electromagnetic waves through an antenna and detecting high-altitude clouds by utilizing a receiving system to receive the reflected electromagnetic waves. The laser wind-finding radar collects particle scattering echo information in the air by using a laser receiving and transmitting system, and then analyzes and calculates the measurement data to directly obtain real-time three-dimensional wind field data with high resolution and high precision. Through the technical means, the cloud water particle phase state, the cloud droplet diameter, the heights of different cloud layers and the three-dimensional wind fields with different heights in the high-altitude atmosphere can be identified.
And establishing a special fan icing model of the Tianhu mountain wind power plant cluster based on the detection value of the meteorological elements detected in the field.
In order to improve the accuracy of the current fan blade icing prediction model, after the current fan blade icing prediction model is established, the method further comprises: acquiring a meteorological element historical value of a current mountain wind power plant micro-terrain area; and correcting the current fan blade icing prediction model based on the meteorological element historical value.
In a specific implementation, for example: taking a river and western wind power plant in an ice disaster important area in 2008 as a research object, and acquiring a meteorological element history value of a micro-topography area of the mountain wind power plant in the lake in 2008. And using the weather element historical value of the micro-terrain area of the weather mountain wind power plant in 2008 as a correction data set, and correcting the weather mountain wind turbine blade icing prediction model by using the correction data set.
In order to obtain comprehensive and diversified meteorological element observations, the meteorological element observations of the current mountain wind farm micro-terrain area are specifically: wind farm base data, satellite monitoring data, microclimate monitoring data and geographic data of a current mountain wind farm microtopography area.
In a specific implementation, for example: wind field basic data are obtained by accessing a wind field of a mountain wind field micro-terrain area. And obtaining satellite monitoring data by accessing a satellite monitoring system. And obtaining microclimate monitoring data by accessing a microclimate monitoring system. And obtaining geographic data by accessing a geographic system.
In order to improve accuracy of the weather element prediction result, before inputting the weather element prediction result into the current fan blade icing prediction model in step 103, the method further includes: and correcting the weather element prediction result.
In a specific implementation, for example: the observed value of the meteorological element is an observed sequenceWherein S is 0 Representing each meteorological element observation, n represents a time step. The weather element prediction result is a prediction sequenceWhere S represents a weather element prediction, p represents a prediction, and n represents a time step.
Constructing a regression equation according to the observation sequence and the prediction sequencePerforming correction treatment, wherein ∈>Correcting the weather element prediction result b after processing 0 Represents the intercept, b 1 Representing regression coefficients.
The embodiment of the invention provides a mountain wind farm fan blade icing prediction and early warning system, which comprises a mountain wind farm fan blade icing prediction system and a mountain wind farm fan blade icing early warning system.
Based on the Tianhu mountain fishing typhoon electric field, the system login, GIS map information management, fan information management, weather forecast information management, fan icing prediction, fan safety operation early warning management, statistical analysis and other functional module designs are completed, and a mountain wind electric field fan blade icing prediction early warning system with the functions of icing prediction, output loss prediction, refined meteorological element display, GIS map display, live access, system management and the like is developed. The method has the advantages that the data statistics and analysis functions of the mountain wind farm fan blade icing early warning system are perfected, a sound icing early warning and forecasting mechanism is established, the prediction accuracy of factors such as the fan blade icing time, the icing thickness and the icing range is improved, a logic judgment basis is provided for starting and stopping of the deicing system, the deicing efficiency and deicing balance are improved, the system power consumption is reduced, the deicing system efficiency is improved to realize higher efficiency ice prevention and removal, and the icing electric quantity loss is further reduced.
As shown in fig. 3, the working flow of the mountain wind farm fan blade icing prediction and early warning system is as follows.
Firstly, data collection is started, and data such as air pressure, temperature, humidity, wind speed, wind direction, tip speed, precipitation, altitude, micro-topography characteristics and the like are collected. The altitude and micro-topography features are used for dividing the mountain wind farm micro-topography areas.
Icing factor selections, such as barometric pressure, temperature, humidity, wind speed, wind direction, tip speed, and precipitation, are then made from the collected data.
And then carrying out weight analysis according to the icing factor selection, the fan comprehensive load analysis and the icing increment analysis.
Next, a fan blade icing prediction model is started to be constructed, and model verification is performed.
And finally, realizing predictive early warning, and controlling the deicing system to start and stop automatically according to the predictive early warning result.
Another embodiment of the invention provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the mountain wind farm fan blade icing prediction method when executing the computer program.
Another embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of a mountain wind farm fan blade icing prediction method.
Another embodiment of the invention provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a mountain wind farm fan blade icing prediction method.
One or more technical solutions provided in the embodiments of the present invention at least have the following technical effects or advantages:
the mountain wind farm fan blade icing prediction method is applied to a mountain wind farm fan blade icing prediction system, the mountain wind farm fan blade icing prediction system is provided with a plurality of fan blade icing prediction models which are in one-to-one correspondence with a plurality of mountain wind farm micro-terrain areas, and the method comprises the following steps: based on the current mountain wind power plant micro-terrain area, selecting a fan blade icing prediction model corresponding to the current mountain wind power plant micro-terrain area as a current fan blade icing prediction model; based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm; inputting a meteorological element prediction result into a current fan blade icing prediction model, and obtaining a predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness. According to the invention, a corresponding fan blade icing prediction model is selected from a plurality of fan blade icing prediction models to serve as the current fan blade icing prediction model according to the current mountain wind power plant micro-terrain area, the current fan blade icing prediction model is generated according to the characteristics of the current mountain wind power plant micro-terrain area, the fan blade icing prediction model is more fit with the field environment, the accuracy of predicting the fan blade icing thickness can be improved, for example, the 24-hour icing prediction accuracy reaches more than 70%, and the technical problem that the fan blade icing condition cannot be accurately predicted in the prior art is solved. According to the weather element prediction result of the current wind power plant micro-terrain area, the method can generate the predicted fan blade icing thickness in advance based on the formula d=f (g (A), m (B)), so that the technical problem that the fan blade icing condition cannot be predicted timely in the prior art is solved, for example, the weather element prediction result is weather elements after 3 days, the predicted fan blade icing thickness can be generated 3 days in advance, and the fan blade icing condition can be obtained timely. Therefore, the invention can timely and accurately predict the icing condition of the fan blade.
Further, before selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model, the method further comprises: and dividing the mountain wind power plant micro-terrain area according to the altitude sum and the micro-terrain characteristics. The mountainous wind farm micro-terrain areas with different characteristics can be divided.
Still further, before selecting the fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area as the current fan blade icing prediction model, the method further comprises: acquiring a meteorological element detection value of a current mountain wind power plant micro-terrain area; and establishing a current fan blade icing prediction model based on the meteorological element detection value. The current fan blade icing prediction model can be generated.
Still further, after establishing the current fan blade icing prediction model, the method further comprises: acquiring a meteorological element historical value of a current mountain wind power plant micro-terrain area; and correcting the current fan blade icing prediction model based on the meteorological element historical value. The accuracy of the current fan blade icing prediction model can be improved.
Furthermore, the meteorological element observation values of the micro-terrain area of the current mountain wind farm are specifically: wind farm base data, satellite monitoring data, microclimate monitoring data and geographic data of a current mountain wind farm microtopography area. Comprehensive and diversified meteorological element observations can be obtained.
Still further, before inputting the meteorological element prediction result into the current fan blade icing prediction model, further comprises: and correcting the weather element prediction result. The accuracy of the weather element prediction result can be improved.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. The mountain wind farm fan blade icing prediction method is applied to a mountain wind farm fan blade icing prediction system, and is characterized in that the mountain wind farm fan blade icing prediction system is provided with a plurality of fan blade icing prediction models corresponding to a plurality of mountain wind farm micro-terrain areas one by one, and the method comprises the following steps:
selecting a fan blade icing prediction model corresponding to a current mountain wind power plant micro-terrain area as a current fan blade icing prediction model based on the current mountain wind power plant micro-terrain area;
based on the meteorological element observation value of the current mountain wind power plant micro-terrain area, a meteorological element prediction result of the current mountain wind power plant micro-terrain area is obtained through a medium-small scale mode coupling multiple nested numerical prediction algorithm;
inputting the meteorological element prediction result into the current fan blade icing prediction model, and obtaining the predicted fan blade icing thickness based on a formula d=f (g (A), m (B)), wherein g (A) is a medium-small scale mode coupling multiple nested numerical prediction meteorological element prediction result, m (B) is a micro-terrain area fan blade icing model, f is the current fan blade icing prediction model, and d is the predicted fan blade icing thickness.
2. The method of claim 1, wherein prior to said selecting as the current fan blade icing prediction model a fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area, the method further comprises:
and dividing the mountain wind power plant micro-terrain area according to the altitude sum and the micro-terrain characteristics.
3. The method of claim 1, wherein prior to said selecting as the current fan blade icing prediction model a fan blade icing prediction model corresponding to the current mountain wind farm micro-terrain area, the method further comprises:
acquiring a meteorological element detection value of the current mountain wind power plant micro-terrain area;
and establishing the current fan blade icing prediction model based on the meteorological element detection value.
4. The method of claim 3, wherein after said establishing said current fan blade icing prediction model, said method further comprises:
acquiring a meteorological element historical value of the current mountain wind power plant micro-terrain area;
and correcting the current fan blade icing prediction model based on the meteorological element historical value.
5. The method according to claim 1, wherein the meteorological element observations of the current mountain wind farm micro-terrain area are in particular:
wind field basic data, satellite monitoring data, microclimate monitoring data and geographic data of the current mountain wind power field micro-terrain area.
6. The method of claim 1, further comprising, prior to said inputting the meteorological element prediction result into the current fan blade icing prediction model:
and correcting the weather element prediction result.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-6 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-6.
9. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-6.
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