CN116641842A - Wind turbine running control method, device, equipment and storage medium - Google Patents
Wind turbine running control method, device, equipment and storage medium Download PDFInfo
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- CN116641842A CN116641842A CN202310514994.8A CN202310514994A CN116641842A CN 116641842 A CN116641842 A CN 116641842A CN 202310514994 A CN202310514994 A CN 202310514994A CN 116641842 A CN116641842 A CN 116641842A
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/04—Automatic control; Regulation
- F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
- F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
- F03D7/045—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with model-based controls
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/0276—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling rotor speed, e.g. variable speed
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/72—Wind turbines with rotation axis in wind direction
Abstract
The application discloses a wind turbine generator operation control method, a device, equipment and a storage medium, relating to the technical field of wind power generation, comprising the following steps: acquiring corresponding historical wind speed data and historical wind direction data of all wind turbines, and determining associated wind turbines of the target wind turbines; generating wind speed prediction models corresponding to the target wind turbine generator in different preset wind direction sectors; determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, determining a current anemometer running state based on the obtained measured wind speeds of the first anemometer and the second anemometer in the target wind turbine and the current predicted wind speed, and controlling the target wind turbine. Therefore, the state of the wind turbine anemometer can be accurately identified, a corresponding control strategy is executed, the shutdown caused by the failure of the wind turbine anemometer is reduced, and the generated energy is improved.
Description
Technical Field
The invention relates to the technical field of wind power generation, in particular to a method, a device, equipment and a storage medium for controlling the operation of a wind turbine generator.
Background
The wind generating set operates in complex environments, in severe weather such as strong wind, sand storm, freezing and the like, and in extremely complex mechanical and electrical structures, so that the normal and stable operation of the wind generating set is subjected to great test. When the wind turbine generator system is in response to severe weather, the key indexes of the main control scheduling of the wind turbine generator system are wind speeds of the wind turbine generator system, such as start-stop, pitch variation and other control strategies. Meanwhile, the wind speed is a key data variable for calculating the power curve K value and the generated energy of the wind turbine generator. In actual operation, the failure of the anemometer directly affects the operation of the wind turbine, so that data loss is not available, or the wind turbine is stopped, the generated energy is lost, and the economy of the wind turbine is not facilitated.
Currently, in order to solve such problems, a plurality of anemometers are often configured for a wind turbine generator, so that after the anemometer fails, another anemometer is switched in time. The above solution has a great effect in case of transient faults of the anemometer, such as when data measurement is constant due to freezing, but is difficult to work when the anemometer is slowly faulty, often it takes a long time to find the fault and switch the anemometer, and the state of the other standby anemometer is unknown. How to identify the anemometer state of the wind turbine generator, and detect the occurrence of faults in advance, so that when the wind turbine generator is in the anemometer fault state, available wind speed data is used as a unit control input, and the method is very critical to the normal and stable operation of the wind turbine generator.
In summary, the method accurately and timely identifies the anemometer state of the wind turbine to obtain accurate wind speed input so as to maintain normal and stable operation of the wind turbine, and is a technical research problem to be solved by the technicians in the wind power field at present.
Disclosure of Invention
In view of the above, the present application aims to provide a method, a device, equipment and a storage medium for controlling operation of a wind turbine, which can accurately identify the state of an anemometer of the wind turbine, execute a corresponding control strategy, reduce shutdown caused by failure of the anemometer, and promote the generated energy. The specific scheme is as follows:
in a first aspect, the application discloses a wind turbine generator operation control method, which comprises the following steps:
acquiring data of cabin wind speeds and cabin wind directions of all wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and determining associated wind turbines with association between the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbine in each preset wind direction sector;
generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator;
Determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine;
determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state.
Optionally, the data acquisition of the nacelle wind speed and the nacelle wind direction of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data includes:
collecting data of the cabin wind speeds and the cabin wind directions of all the wind turbines within a preset time period, and performing data standard processing on the collected data to obtain corresponding historical wind speed data and historical wind direction data; the data specification processing includes a missing value processing, a time axis alignment processing, and an invalid data elimination processing.
Optionally, the determining that the associated wind turbine generator set exists an association between the historical wind speed data of the wind turbine generator and the historical wind speed data of the target wind turbine generator set in each preset wind direction sector includes:
Dividing wind directions into a preset number of wind direction sectors according to a preset dividing rule, and dividing the historical wind direction data of the target wind turbine generator into all wind direction sectors;
acquiring first historical wind speed data corresponding to the historical wind direction data of the target wind turbine in each wind direction sector, and acquiring second historical wind speed data corresponding to other wind turbines at the same moment;
and determining the associated wind generation set corresponding to the target wind generation set in each wind direction sector based on the first historical wind speed data and the historical second wind speed data.
Optionally, the determining, based on the first historical wind speed data and the historical second wind speed data, the associated wind turbine corresponding to the target wind turbine in each wind direction sector includes:
determining a similarity value of the first historical wind speed data and the second historical wind speed data;
and determining the wind turbines of which the similarity value is larger than a first preset similarity threshold value in the other wind turbines as the associated wind turbine of the target wind turbine so as to obtain the associated wind turbines of the target wind turbine in each wind direction sector.
Optionally, the determining the current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed includes:
Determining a first similarity between the measured wind speed of the first anemometer and the measured wind speed of the second anemometer, a second similarity between the measured wind speed of the first anemometer and the current predicted wind speed, and a third similarity between the measured wind speed of the second anemometer and the current predicted wind speed, respectively;
determining a current anemometer operational state based on the first similarity, the second similarity, and the third similarity.
Optionally, the determining the current anemometer operation state based on the first similarity, the second similarity, and the third similarity includes:
if the first similarity and the second similarity are both larger than a second preset similarity threshold value, judging that the first anemometer and the second anemometer are both in a normal running state;
if the first similarity is greater than the second preset similarity threshold and the second similarity is not greater than the second preset similarity threshold, judging that the first anemometer and the second anemometer are in a fault state;
if the first similarity and the second similarity are not greater than the second preset similarity threshold, and the third similarity is greater than the second preset similarity threshold, judging that the first anemometer is in a fault state and the second anemometer is in a normal running state;
And if the first similarity and the third similarity are not greater than the second preset similarity threshold value and the second similarity is greater than the second preset similarity threshold value, judging that the first anemometer is in a normal running state and the second anemometer is in a fault state.
Optionally, the controlling the fan in the target wind turbine unit by using the target wind speed determined based on the current operation state of the anemometer includes:
if the first anemometer and the second anemometer are in a normal running state, selecting any one of the measured wind speed of the first anemometer and the measured wind speed of the second anemometer to control a fan in the target wind turbine;
if the first anemometer is in a fault state and the second anemometer is in a normal running state, selecting a measured wind speed of the second anemometer to control a fan in the target wind turbine;
if the second anemometer is in a fault state and the first anemometer is in a normal running state, selecting a measured wind speed of the first anemometer to control a fan in the target wind turbine;
And if the first anemometer and the second anemometer are in a fault state, selecting the current predicted wind speed to control a fan in the target wind turbine.
In a second aspect, the present application discloses a wind turbine generator operation control device, including:
the relevant wind turbine generator system determining module is used for acquiring data of the cabin wind speeds and the cabin wind directions of all the wind turbine generators to obtain corresponding historical wind speed data and historical wind direction data, and determining relevant wind turbine generators with relevance between the historical wind speed data of the relevant wind turbine generator system and the historical wind speed data of the target wind turbine generator system in each preset wind direction sector;
the model generation module is used for generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator;
the predicted wind speed generation module is used for determining the current predicted wind speed of the target wind turbine by utilizing the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring the measured wind speed of a first anemometer and the measured wind speed of a second anemometer in the target wind turbine;
And the fan control module is used for determining the current anemometer running state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling the fan in the target wind turbine by utilizing the target wind speed determined based on the current anemometer running state.
In a third aspect, the present application discloses an electronic device, comprising:
a memory for storing a computer program;
and the processor is used for executing the computer program to realize the wind turbine running control method.
In a fourth aspect, the present application discloses a computer readable storage medium for storing a computer program, where the computer program when executed by a processor implements the foregoing method for controlling operation of a wind turbine generator.
In the application, the data acquisition is carried out on the cabin wind speeds and the cabin wind directions of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and the associated wind turbines with the association between the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbine in each preset wind direction sector are determined; generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator; determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine; determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state. And then determining the wind speed which should be measured at the current moment of the anemometer in the target wind turbine according to the wind speed prediction model so as to obtain the current predicted wind speed. And determining the running states of the first anemometer and the second anemometer according to the actual wind speeds measured by the first anemometer and the second anemometer and the current predicted wind speed, so as to select a corresponding target wind speed according to the running states of the anemometers to correspondingly control fans in the target wind turbine generator. In this way, according to the current predicted wind speed and the actual wind speeds measured by the first anemometer and the second anemometer, the running state of the anemometer in the target wind turbine can be accurately identified, and then the corresponding target wind speed is selected to control the running of the fan in the target wind turbine according to the running state of the anemometer, so that the wind turbine can normally and stably run even when the anemometer fails, the downtime of the wind turbine caused by the failure of the anemometer can be reduced, and the generating capacity of a wind power plant is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for controlling operation of a wind turbine disclosed by the application;
FIG. 2 is a flowchart of a specific method for controlling operation of a wind turbine according to the present disclosure;
FIG. 3 is a schematic structural diagram of a wind turbine running control device disclosed by the application;
fig. 4 is a block diagram of an electronic device according to the present disclosure.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
At present, in order to solve the shutdown caused by the failure of the anemometer, a plurality of anemometers are often configured for the wind turbine, so that after the failure of the anemometer, another anemometer is switched in time. However, the above methods still have drawbacks when the anemometer fails slowly or multiple anemometers fail simultaneously. The application specifically introduces a method for judging the current state of the anemometer of the wind turbine by searching the anemometer wind speed distribution association rules under different sectors and predicting the wind speed of the anemometer of the target wind turbine, so as to select a corresponding control strategy, reduce the fault shutdown time of the anemometer under various conditions and improve the generated energy of a wind power plant.
Referring to fig. 1, the embodiment of the application discloses a wind turbine generator operation control method, which comprises the following steps:
step S11: and acquiring data of the cabin wind speeds and the cabin wind directions of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and determining associated wind turbines of which the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbines are associated in each preset wind direction sector.
In this embodiment, the data acquisition of the nacelle wind speeds and nacelle wind directions of all wind turbines to obtain corresponding historical wind speed data and historical wind direction data includes: collecting data of the cabin wind speeds and the cabin wind directions of all the wind turbines within a preset time period, and performing data standard processing on the collected data to obtain corresponding historical wind speed data and historical wind direction data; the data specification processing includes a missing value processing, a time axis alignment processing, and an invalid data elimination processing. The wind speed of the cabin and the wind direction of the cabin are measured data of anemometers arranged in the wind turbine, and more than one anemometer is generally arranged in the wind turbine, so that in the normal operation process of the wind turbine, the wind speed data measured by one anemometer is selected to control a fan in the wind turbine. Therefore, data acquisition is carried out on the cabin wind speeds and the cabin wind directions of all the wind turbines in the wind power plant, wherein the cabin wind speeds are used for controlling fans in the wind turbines. Because the wind turbine generator may have a fault or an improper collection method, the collected data may have invalid data and other data affecting the subsequent model training process. Therefore, data standard processing is required to be performed on the collected data so as to obtain corresponding historical wind speed data and historical wind direction data. The data specification processing includes a missing value processing, a time axis alignment processing, and an invalid data elimination processing. And then determining an associated wind turbine generator set with association between the historical wind speed data of the associated wind turbine generator set and the historical wind speed data of the target wind turbine generator set in each preset wind direction sector. Specifically, the wind direction sectors are firstly divided according to the actual situation, the total sector is 360 degrees, and the wind direction sectors can be divided into 4, 8, 12 and 16 wind direction sectors according to the actual situation. One sector is selected as a preset wind direction sector, then a historical wind speed data set of the target wind turbine generator in the preset wind direction sector is obtained, and each historical wind speed data set of other wind turbine generator at the same moment is obtained. And then calculating the similarity delta of the historical wind speed data set of the target wind turbine in the preset wind direction sector and each historical wind speed data set of other wind turbines, and when the similarity delta is closer to 1, proving that the degree of association between the two wind turbines is larger. The calculation method for determining the similarity includes methods not limited to pearson correlation coefficient, cosine distance, euclidean distance, mahalanobis distance, and the like. And determining that the wind turbine is associated after the similarity is greater than a first preset similarity threshold. In this way, the associated wind turbines with the association between the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbines in each preset wind direction sector are sequentially determined. The similarity threshold may be set empirically and practically, but needs to be higher than 0.9. It is emphasized that the number of the determined associated wind turbines is not less than 3 in order to ensure the effect of the subsequent model training and the prediction accuracy. In this way, data standard processing is carried out on the collected data of the cabin wind speeds and the cabin wind directions of all the wind turbines, and standard historical wind speed data and standard historical wind direction data are obtained, so that the accuracy of the determined associated wind turbines can be improved, and the accuracy of a subsequently generated wind speed prediction model is further improved.
Step S12: and generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator.
In this embodiment, different wind speed prediction models of the target wind turbine generator set corresponding to different preset wind direction sectors are generated based on the historical wind speed data of the target wind turbine generator set in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator set. After the associated wind turbines of the target wind turbine in each preset wind direction sector are determined. The wind speed distribution change rule of the historical wind speed data of the target wind turbine in each preset wind direction sector and the historical wind speed data of the associated wind turbine can be learned through a convolutional neural network; the convolutional neural network in the training process comprises an input layer, a convolutional layer, an activation function layer, a pooling layer, a full connection layer and an output layer, and a ReLU (Rectified Linear Unit, i.e. a modified linear unit) linear activation function is selected. The performance of the model is then evaluated by the loss function and the model parameters are updated by the optimization algorithm. The loss function in the optimization process can select mean square error and average absolute error, and the optimization algorithm can select a random gradient descent method. Thus, different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors can be generated.
Step S13: determining the current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring the measured wind speed of a first anemometer and the measured wind speed of a second anemometer in the target wind turbine.
In this embodiment, after different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors are obtained, corresponding prediction can be performed on the real-time wind speed of the target wind turbine generator according to the wind speed prediction models to obtain the current predicted wind speed of the target wind turbine generator. Acquiring current wind direction data measured by the target wind turbine generator at the current moment, selecting a corresponding wind speed prediction model according to the wind direction data, and simultaneously acquiring current wind speed data of the associated wind turbine generator in a wind direction sector corresponding to the current wind direction data of the target wind turbine generator. And inputting the current wind speed data of the associated wind turbine generator into the customs prediction model to obtain the current predicted wind speed of the target wind turbine generator. And acquiring the measured wind speed of the first anemometer and the measured wind speed of the second anemometer in the current target wind turbine. The measured wind speed of the first anemometer and the measured wind speed of the second anemometer are wind speeds actually measured by the first anemometer and the second anemometer.
Step S14: determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state.
In this embodiment, the determining the current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed includes: determining a first similarity between the measured wind speed of the first anemometer and the measured wind speed of the second anemometer, a second similarity between the measured wind speed of the first anemometer and the current predicted wind speed, and a third similarity between the measured wind speed of the second anemometer and the current predicted wind speed, respectively. Wherein, the similarity between the determined wind speeds can use a pearson correlation coefficient. Determining a current anemometer operational state based on the first similarity, the second similarity, and the third similarity. The determining a current anemometer operational state based on the first similarity, the second similarity, and the third similarity includes: if the first similarity and the second similarity are both larger than a second preset similarity threshold value, judging that the first anemometer and the second anemometer are both in a normal running state; if the first similarity is greater than the second preset similarity threshold and the second similarity is not greater than the second preset similarity threshold, judging that the first anemometer and the second anemometer are in a fault state; if the first similarity and the second similarity are not greater than the second preset similarity threshold, and the third similarity is greater than the second preset similarity threshold, judging that the first anemometer is in a fault state and the second anemometer is in a normal running state; and if the first similarity and the third similarity are not greater than the second preset similarity threshold value and the second similarity is greater than the second preset similarity threshold value, judging that the first anemometer is in a normal running state and the second anemometer is in a fault state. The generation formula of the second preset similarity threshold may be described as follows:
ε＝θ×ε'
Wherein epsilon' is the maximum similarity between the target anemometer fault data set and the predicted wind speed, and theta is an empirical coefficient.
When any one of the first similarity, the second similarity and the third similarity is smaller than the second preset similarity threshold, corresponding alarm operation is triggered so as to remind a technician of carrying out corresponding processing on the anemometer in time.
In this embodiment, the controlling, by using the target wind speed determined based on the current anemometer operation state, a fan in the target wind turbine includes: if the first anemometer and the second anemometer are in a normal running state, selecting any one of the measured wind speed of the first anemometer and the measured wind speed of the second anemometer to control a fan in the target wind turbine; if the first anemometer is in a fault state and the second anemometer is in a normal running state, selecting a measured wind speed of the second anemometer to control a fan in the target wind turbine; if the second anemometer is in a fault state and the first anemometer is in a normal running state, selecting a measured wind speed of the first anemometer to control a fan in the target wind turbine; and if the first anemometer and the second anemometer are in a fault state, selecting the current predicted wind speed to control a fan in the target wind turbine. If the first anemometer and the second anemometer are in a normal running state, the target wind turbine can select any wind speed control fan measured by the anemometer to generate power, and if the first anemometer is in the normal running state and the second anemometer fails, the target wind turbine selects the wind speed control fan measured by the first anemometer to generate power and alarms at the same time, so that a technician is reminded of timely carrying out corresponding maintenance treatment operation on the second anemometer. If the second anemometer is in a normal running state and the first anemometer fails, the target wind turbine generator selects a wind speed control fan measured by the second anemometer to generate power, and simultaneously alarms so as to remind a technician of timely performing corresponding maintenance processing operation on the first anemometer. If the first anemometer and the second anemometer are in a fault state, the target wind turbine temporarily selects a current predicted wind speed to control a fan to generate power, so that normal operation of the target wind turbine is temporarily maintained, and meanwhile, an alarm is given to remind a technician of timely carrying out corresponding maintenance processing operation on the first anemometer and the second anemometer. Therefore, the shutdown caused by the fault of the anemometer can be reduced, and the power generation amount of the wind turbine can be improved to a certain extent.
In this embodiment, first, data acquisition is performed on the cabin wind speeds and the cabin wind directions of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and an associated wind turbine in which the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbine in each preset wind direction sector are associated is determined; generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator; determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine; determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state. And then determining the wind speed which should be measured at the current moment of the anemometer in the target wind turbine according to the wind speed prediction model so as to obtain the current predicted wind speed. And determining the running states of the first anemometer and the second anemometer according to the actual wind speeds measured by the first anemometer and the second anemometer and the current predicted wind speed, so as to select a corresponding target wind speed according to the running states of the anemometers to correspondingly control fans in the target wind turbine generator. In this way, according to the current predicted wind speed and the actual wind speeds measured by the first anemometer and the second anemometer, the running state of the anemometer in the target wind turbine can be accurately identified, and then the corresponding target wind speed is selected to control the running of the fan in the target wind turbine according to the running state of the anemometer, so that the wind turbine can normally and stably run even when the anemometer fails, the downtime of the wind turbine caused by the failure of the anemometer can be reduced, and the generating capacity of a wind power plant is improved.
The embodiment specifically describes a method for judging the current running state of the anemometer based on the wind speed distribution association rule of the anemometer, and the embodiment specifically describes a method for determining the associated wind turbine of the target wind turbine.
Referring to fig. 2, the embodiment of the application discloses a specific method for confirming an associated unit, which comprises the following steps:
step S21: dividing the wind direction into a preset number of wind direction sectors according to a preset dividing rule, and dividing the historical wind direction data of the target wind turbine generator into each wind direction sector.
In this embodiment, first, a target wind turbine generator is used as a center, and wind directions are divided into a preset number of wind direction sectors according to a preset division rule. Wherein the total sector is 360 degrees, and the number of wind direction sectors can be 4, 8, 12 and 16. After the wind direction sectors are divided, the historical direction data of the target wind turbine generator are divided into the wind direction sectors according to wind directions.
Step S22: and acquiring first historical wind speed data corresponding to the historical wind direction data of the target wind turbine in each wind direction sector, and acquiring second historical wind speed data corresponding to other wind turbines at the same moment.
In this embodiment, after the historical direction data of the target wind turbine generator is divided into the wind direction sectors according to the wind direction, first historical wind speed data corresponding to the historical direction data of the target wind turbine generator in each wind direction sector is obtained, and second historical wind speed data corresponding to other wind turbine generator at the same time is obtained. For example, if there are five first historical wind speed data corresponding to the historical direction data of the target wind turbine in a certain wind direction sector, determining the moments of the five historical wind speed data, and then obtaining the historical wind speed data of other wind turbines at the same moment.
Step S23: and determining a similarity value of the first historical wind speed data and the second historical wind speed data.
In this embodiment, determining the similarity value of the first historical wind speed data and the second historical wind speed data may use pearson correlation coefficient to calculate:
suppose target wind turbine generator R 1 Is [ x ] 1 ,x 2 …,x n ]Other wind turbine generators R 2 Is [ y ] 1 ,y 2 …,y n ]The similarity δ of the two is:
wherein, the liquid crystal display device comprises a liquid crystal display device,represents the average value of the first historical wind speed data, and Y represents the average value of the second historical wind speed data. In addition, the similarity can be calculated by cosine distance, euclidean distance, mahalanobis distance and other methods.
Step S24: and determining the wind turbines of which the similarity value is larger than a first preset similarity threshold value in the other wind turbines as the associated wind turbine of the target wind turbine so as to obtain the associated wind turbines of the target wind turbine in each wind direction sector.
In this embodiment, after the similarity value is obtained, comparing the similarity value with the first preset similarity threshold, and determining a wind turbine with the similarity threshold greater than the first preset similarity threshold as an associated wind turbine of the target wind turbine, so as to obtain an associated wind turbine of the target wind turbine in each wind direction sector. It should be emphasized that the first preset similarity threshold may be set according to experience and actual situations, and the number of the associated wind turbines may not be less than 3. Thus, the greater the number of associated wind turbines, the greater the accuracy of the prediction of the wind speed prediction model generated using the historical wind speed data of the associated wind turbines.
In this embodiment, the wind direction is first divided into a preset number of wind direction sectors according to a preset division rule, and the historical wind direction data of the target wind turbine generator is divided into each wind direction sector; acquiring first historical wind speed data corresponding to the historical wind direction data of the target wind turbine in each wind direction sector, and acquiring second historical wind speed data corresponding to other wind turbines at the same moment; determining a similarity value of the first historical wind speed data and the second historical wind speed data; and determining the wind turbines of which the similarity value is larger than a first preset similarity threshold value in the other wind turbines as the associated wind turbine of the target wind turbine so as to obtain the associated wind turbines of the target wind turbine in each wind direction sector. The method comprises the steps of determining an associated wind turbine generator set with strong correlation of wind speed distribution rules of a target wind turbine generator under different wind direction sectors by utilizing first historical wind speed data and second historical wind speed data. In this way, the wind speed of the target wind turbine can be predicted and judged according to the wind speed of the associated wind turbine.
As described with reference to fig. 3, the embodiment of the present application further correspondingly discloses a wind turbine generator operation control device, including:
The association unit determining module 11 is used for acquiring data of cabin wind speeds and cabin wind directions of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and determining associated wind turbines of which the historical wind speed data of the associated wind turbines and the historical wind speed data of the target wind turbines in each preset wind direction sector exist;
the model generating module 12 is configured to generate different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator;
a predicted wind speed generation module 13, configured to determine a current predicted wind speed of the target wind turbine using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and obtain a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine;
a fan control module 14 for determining a current anemometer operational state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling a fan in the target wind turbine using a target wind speed determined based on the current anemometer operational state.
In this embodiment, first, data acquisition is performed on the cabin wind speeds and the cabin wind directions of all the wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and an associated wind turbine in which the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbine in each preset wind direction sector are associated is determined; generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator; determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine; determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state. And then determining the wind speed which should be measured at the current moment of the anemometer in the target wind turbine according to the wind speed prediction model so as to obtain the current predicted wind speed. And determining the running states of the first anemometer and the second anemometer according to the actual wind speeds measured by the first anemometer and the second anemometer and the current predicted wind speed, so as to select a corresponding target wind speed according to the running states of the anemometers to correspondingly control fans in the target wind turbine generator. In this way, according to the current predicted wind speed and the actual wind speeds measured by the first anemometer and the second anemometer, the running state of the anemometer in the target wind turbine can be accurately identified, and then the corresponding target wind speed is selected to control the running of the fan in the target wind turbine according to the running state of the anemometer, so that the wind turbine can normally and stably run even when the anemometer fails, the downtime of the wind turbine caused by the failure of the anemometer can be reduced, and the generating capacity of a wind power plant is improved.
In some specific embodiments, the association unit determining module 11 may specifically include:
the data acquisition unit is used for acquiring the data of the cabin wind speeds and the cabin wind directions of all the wind turbines within a preset time period, and carrying out data standard processing on the acquired data to obtain corresponding historical wind speed data and historical wind direction data; the data specification processing includes a missing value processing, a time axis alignment processing, and an invalid data elimination processing.
In some specific embodiments, the association unit determining module 11 may specifically include:
the wind direction sector dividing unit is used for dividing wind directions into a preset number of wind direction sectors according to a preset dividing rule and dividing the historical wind direction data of the target wind turbine generator into all wind direction sectors;
the wind speed acquisition unit is used for acquiring first historical wind speed data corresponding to the historical wind direction data of the target wind turbine generator in each wind direction sector and acquiring second historical wind speed data corresponding to other wind turbine generator at the same moment;
and the associated wind turbine generator system determining submodule is used for determining the associated wind turbine generator system corresponding to the target wind turbine generator system in each wind direction sector based on the first historical wind speed data and the historical second wind speed data.
In some specific embodiments, the association unit determining submodule 11 may specifically include:
a first similarity determination unit configured to determine a similarity value of the first historical wind speed data and the second historical wind speed data;
and the associated wind turbine generator unit determining unit is used for determining the wind turbine generator unit with the similarity value larger than a first preset similarity threshold value in the other wind turbine generator units as the associated wind turbine generator unit of the target wind turbine generator unit so as to obtain the associated wind turbine generator unit of the target wind turbine generator unit in each wind direction sector.
In some specific embodiments, the fan control module 14 may specifically include:
a second similarity determination unit configured to determine a second similarity between the measured wind speed of the second anemometer and the current predicted wind speed, and a third similarity between the measured wind speed of the second anemometer and the current predicted wind speed, respectively;
and the anemometer state confirmation sub-module is used for determining the current anemometer operation state based on the first similarity, the second similarity and the third similarity.
In some specific embodiments, the anemometer status confirmation sub-module may specifically include:
the first state confirmation unit is used for judging that the first anemometer and the second anemometer are in a normal running state if the first similarity and the second similarity are both larger than a second preset similarity threshold value;
a second state confirmation unit, configured to determine that the first anemometer and the second anemometer are both in a fault state if the first similarity is greater than the second preset similarity threshold and the second similarity is not greater than the second preset similarity threshold;
a third state confirmation unit, configured to determine that the first anemometer is in a fault state and the second anemometer is in a normal running state if the first similarity and the second similarity are not greater than the second preset similarity threshold and the third similarity is greater than the second preset similarity threshold;
and the fourth state confirmation unit is used for judging that the first anemometer is in a normal running state and the second anemometer is in a fault state if the first similarity and the third similarity are not larger than the second preset similarity threshold value and the second similarity is larger than the second preset similarity threshold value.
In some specific embodiments, the fan control module 14 may specifically include:
the first control unit is used for selecting any one of the measured wind speed of the first anemometer and the measured wind speed of the second anemometer to control the fan in the target wind turbine if the first anemometer and the second anemometer are in a normal running state;
the second control unit is used for selecting the measured wind speed of the second anemometer to control the fan in the target wind turbine generator if the first anemometer is in a fault state and the second anemometer is in a normal running state;
the third control unit is used for selecting the measured wind speed of the first anemometer to control the fan in the target wind turbine generator if the second anemometer is in a fault state and the first anemometer is in a normal running state;
and the fourth control unit is used for selecting the current predicted wind speed to control the fans in the target wind turbine generator set if the first anemometer and the second anemometer are in a fault state.
Further, the embodiment of the present application further discloses an electronic device, and fig. 4 is a block diagram of an electronic device 20 according to an exemplary embodiment, where the content of the diagram is not to be considered as any limitation on the scope of use of the present application.
Fig. 4 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input output interface 25, and a communication bus 26. The memory 22 is configured to store a computer program, where the computer program is loaded and executed by the processor 21 to implement relevant steps in the wind turbine running control method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the present embodiment may be specifically an electronic computer.
In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 25 is used for acquiring external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application requirement, which is not limited herein.
The memory 22 may be a carrier for storing resources, such as a read-only memory, a random access memory, a magnetic disk, or an optical disk, and the resources stored thereon may include an operating system 221, a computer program 222, and the like, and the storage may be temporary storage or permanent storage.
The operating system 221 is used for managing and controlling various hardware devices on the electronic device 20 and computer programs 222, which may be Windows Server, netware, unix, linux, etc. The computer program 222 may further comprise a computer program capable of performing other specific tasks in addition to the computer program capable of performing the wind turbine generator operation control method performed by the electronic device 20 as disclosed in any of the previous embodiments.
Further, the application also discloses a computer readable storage medium for storing a computer program; the computer program, when executed by the processor, realizes the wind turbine running control method disclosed in the foregoing. For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing has outlined rather broadly the more detailed description of the application in order that the detailed description of the application that follows may be better understood, and in order that the present principles and embodiments may be better understood; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (10)
1. The wind turbine generator operation control method is characterized by comprising the following steps of:
acquiring data of cabin wind speeds and cabin wind directions of all wind turbines to obtain corresponding historical wind speed data and historical wind direction data, and determining associated wind turbines with association between the historical wind speed data of the wind turbines and the historical wind speed data of the target wind turbine in each preset wind direction sector;
generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator;
Determining a current predicted wind speed of the target wind turbine by using the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring a measured wind speed of a first anemometer and a measured wind speed of a second anemometer in the target wind turbine;
determining a current anemometer operating state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling fans in the target wind turbine by utilizing a target wind speed determined based on the current anemometer operating state.
2. The wind turbine generator operation control method according to claim 1, wherein the data collection of the nacelle wind speeds and nacelle wind directions of all wind turbine generators to obtain corresponding historical wind speed data and historical wind direction data includes:
collecting data of the cabin wind speeds and the cabin wind directions of all the wind turbines within a preset time period, and performing data standard processing on the collected data to obtain corresponding historical wind speed data and historical wind direction data; the data specification processing includes a missing value processing, a time axis alignment processing, and an invalid data elimination processing.
3. The wind turbine operation control method according to claim 1, wherein determining an associated wind turbine in which there is an association between the historical wind speed data of the wind turbine and the historical wind speed data of the target wind turbine in each preset wind direction sector includes:
dividing wind directions into a preset number of wind direction sectors according to a preset dividing rule, and dividing the historical wind direction data of the target wind turbine generator into all wind direction sectors;
acquiring first historical wind speed data corresponding to the historical wind direction data of the target wind turbine in each wind direction sector, and acquiring second historical wind speed data corresponding to other wind turbines at the same moment;
and determining the associated wind generation set corresponding to the target wind generation set in each wind direction sector based on the first historical wind speed data and the historical second wind speed data.
4. A wind turbine operation control method according to claim 3, wherein said determining, based on the first historical wind speed data and the historical second wind speed data, the associated wind turbine corresponding to the target wind turbine in each wind direction sector comprises:
determining a similarity value of the first historical wind speed data and the second historical wind speed data;
And determining the wind turbines of which the similarity value is larger than a first preset similarity threshold value in the other wind turbines as the associated wind turbine of the target wind turbine so as to obtain the associated wind turbines of the target wind turbine in each wind direction sector.
5. A wind turbine operation control method according to any of claims 1-4, wherein said determining a current anemometer operational state based on measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed comprises:
determining a first similarity between the measured wind speed of the first anemometer and the measured wind speed of the second anemometer, a second similarity between the measured wind speed of the first anemometer and the current predicted wind speed, and a third similarity between the measured wind speed of the second anemometer and the current predicted wind speed, respectively;
determining a current anemometer operational state based on the first similarity, the second similarity, and the third similarity.
6. The method of claim 5, wherein determining the current anemometer operational state based on the first similarity, the second similarity, and the third similarity comprises:
If the first similarity and the second similarity are both larger than a second preset similarity threshold value, judging that the first anemometer and the second anemometer are both in a normal running state;
if the first similarity is greater than the second preset similarity threshold and the second similarity is not greater than the second preset similarity threshold, judging that the first anemometer and the second anemometer are in a fault state;
if the first similarity and the second similarity are not greater than the second preset similarity threshold, and the third similarity is greater than the second preset similarity threshold, judging that the first anemometer is in a fault state and the second anemometer is in a normal running state;
and if the first similarity and the third similarity are not greater than the second preset similarity threshold value and the second similarity is greater than the second preset similarity threshold value, judging that the first anemometer is in a normal running state and the second anemometer is in a fault state.
7. The method of claim 6, wherein controlling fans in the target wind turbine using a target wind speed determined based on the current anemometer operating state comprises:
If the first anemometer and the second anemometer are in a normal running state, selecting any one of the measured wind speed of the first anemometer and the measured wind speed of the second anemometer to control a fan in the target wind turbine;
if the first anemometer is in a fault state and the second anemometer is in a normal running state, selecting a measured wind speed of the second anemometer to control a fan in the target wind turbine;
if the second anemometer is in a fault state and the first anemometer is in a normal running state, selecting a measured wind speed of the first anemometer to control a fan in the target wind turbine;
and if the first anemometer and the second anemometer are in a fault state, selecting the current predicted wind speed to control a fan in the target wind turbine.
8. An operation control device for a wind turbine generator, comprising:
the relevant wind turbine generator system determining module is used for acquiring data of the cabin wind speeds and the cabin wind directions of all the wind turbine generators to obtain corresponding historical wind speed data and historical wind direction data, and determining relevant wind turbine generators with relevance between the historical wind speed data of the relevant wind turbine generator system and the historical wind speed data of the target wind turbine generator system in each preset wind direction sector;
The model generation module is used for generating different wind speed prediction models of the target wind turbine generator corresponding to different preset wind direction sectors based on the historical wind speed data of the target wind turbine generator in each preset wind direction sector and the historical wind speed data of the associated wind turbine generator;
the predicted wind speed generation module is used for determining the current predicted wind speed of the target wind turbine by utilizing the wind speed prediction model corresponding to the current wind direction data of the target wind turbine and the current wind speed data of the associated wind turbine, and acquiring the measured wind speed of a first anemometer and the measured wind speed of a second anemometer in the target wind turbine;
and the fan control module is used for determining the current anemometer running state based on the measured wind speeds of the first anemometer and the second anemometer and the current predicted wind speed, and controlling the fan in the target wind turbine by utilizing the target wind speed determined based on the current anemometer running state.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the wind turbine operation control method as claimed in any one of claims 1 to 7.
10. A computer readable storage medium for storing a computer program which when executed by a processor implements a method of controlling operation of a wind turbine according to any one of claims 1 to 7.
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