CN115543942A - Wind generating set operation data processing method and device based on cloud computing service - Google Patents

Abstract

The disclosure relates to a wind generating set operation data processing method and device based on cloud computing service. The wind generating set operation data processing method based on the cloud computing service comprises the following steps: acquiring an original compressed file containing wind generating set operation data from a cloud server; screening the original compressed file according to a preset screening condition to obtain an effective compressed file; converting the valid compressed file into a compressed file in a target format, the target format comprising columnar storage; and sending the compressed file in the target format to a cloud server. By adopting the method and the device, the storage cost of the operating data of the wind generating set can be reduced, and the reading efficiency of the operating data of the wind generating set can be improved.

Description

Wind power generation unit operation data processing method and device based on cloud computing service

technical field

The present disclosure relates to the field of wind power generation, and more specifically, to a method and device for processing operation data of a wind power generating set based on cloud computing services.

Background technique

In recent years, wind power technology has continued to develop rapidly, and wind power grid-connected installed capacity has grown rapidly. The wind farm SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control) system can realize the wind farm system-wide fan monitoring and the collection of data such as wind turbine and wind farm faults, and can continuously update these data in real time. The data processing system collects data from wind turbines and wind farms sequentially or offline, and stores and controls the data to meet the needs of remote monitoring or algorithm development using historical data.

With the increase in the number of wind turbines connected, the characteristics of high data frequency, large amount of data collection, and non-unique data collection channels are gradually revealed. The current wind turbine data processing system still uses a non-distributed time-series database as the core method, which has high storage costs and is not easy to expand, and the performance of the wind turbine data processing system may be seriously degraded due to the impact of data volume.

Contents of the invention

In order to solve the above problems, the present disclosure proposes a cloud computing service-based method and device for processing operation data of a wind power generating set.

According to an aspect of the present disclosure, there is provided a cloud computing service-based wind power generating set operating data processing method, the cloud computing service-based wind power generating set operating data processing method may include: obtaining from a cloud server including wind power generating set operating data the original compressed file; filter the original compressed file according to preset filter conditions to obtain an effective compressed file; convert the effective compressed file into a compressed file in a target format, and the target format includes columnar storage; The compressed file in the target format is sent to the cloud server.

Optionally, the step of converting the effective compressed file into a compressed file in the target format may include: extracting the file path and file name of the effective compressed file; associating the file path and the file name , to obtain an intermediate variable; input the intermediate variable to a preset format conversion function to obtain a compressed file in the target format.

Optionally, the step of converting the valid compressed file into a compressed file in the target format may further include: in the case of failure to convert the valid compressed file into a compressed file in the target format, converting the valid compressed file Convert the data in the predetermined format into data in a predetermined format; compress the data in the predetermined format to obtain an intermediate compressed file; return and execute the method of extracting the file path and file name of the effective compressed file according to the intermediate compressed file step.

Optionally, the preset filtering conditions may include: the format of the original compressed file is a preset format and/or the file name of the original compressed file includes a fan number; The step of filtering original compressed files to obtain valid compressed files may include: removing original compressed files that do not meet any of the preset filtering conditions from the original compressed files to obtain valid compressed files.

Optionally, the step of filtering the original compressed file according to preset filtering conditions to obtain a valid compressed file may include: determining the fan number and file date according to the file name of the original compressed file; The original compressed files are all the same, read the wind power generating set operating data in the original compressed file; retain the original compressed file corresponding to the wind generating set operating data with the largest number of columns, rows or numerical values, and obtain the effectively compresses the files described above.

Optionally, the step of filtering the original compressed files according to preset filtering conditions to obtain valid compressed files may include: decompressing the original compressed files; screening out the original compressed files that failed to decompress, and retaining the successfully decompressed files. the original compressed file to obtain the effective compressed file.

Optionally, the step of converting the effective compressed file into a compressed file in the target format may include: removing quality column data from the data in the effective compressed file, and the quality column data is data indicating a fan manufacturer .

Optionally, the target format may include any one of the following: Parquet, ORC, CarbonData.

Optionally, the cloud computing service-based wind power generating set operation data processing method may further include: according to the record of the storage path of the compressed file in the target format in the cloud server, determine the wind power generating set within a preset period. Data integrity, the data integrity is used to characterize the ratio of the number of compressed files in the target format for each wind turbine generating set within the preset period to the number of days included in the preset period.

Optionally, the method for processing operating data of a wind power generating set based on a cloud computing service may further include: extracting the operating data of a wind generating set from the compressed file in the target format; The unit component early warning model obtains an early warning result, and the early warning result is used to indicate the abnormal condition of the wind power generation unit component.

According to another aspect of the present disclosure, a cloud computing service-based wind power generating set operation data processing device is provided, and the cloud computing service-based wind power generating set operating data processing device includes: an acquisition unit configured to obtain from a cloud server The original compressed file containing the operating data of the wind power generating set; the filtering unit is configured to filter the original compressed file according to preset filtering conditions to obtain an effective compressed file; the format conversion unit is configured to convert the effective compressed file It is a compressed file in a target format, and the target format includes columnar storage; a sending unit configured to send the compressed file in the target format to a cloud server.

Optionally, the format conversion unit may be configured to: extract the file path and file name of the effective compressed file; associate the file path with the file name to obtain an intermediate variable; convert the intermediate variable to input to a preset format conversion function to obtain a compressed file in the target format.

Optionally, the format converting unit may also be configured to: convert the data in the valid compressed file into data in a predetermined format when converting the valid compressed file into a target format compressed file fails; Compressing the data in the predetermined format to obtain an intermediate compressed file; returning to the step of extracting the file path and file name of the effective compressed file according to the intermediate compressed file.

Optionally, the preset filtering condition may include that the format of the original compressed file is a preset format and/or the file name of the original compressed file includes a fan number; and the filtering unit may be configured to: select from the removing original compressed files that do not meet any of the preset filtering conditions from the original compressed files to obtain a valid compressed file.

Optionally, the screening unit may be configured to: determine the fan number and file date according to the file name of the original compressed file; read the original compressed file for the original compressed file whose fan number and file date are the same The operating data of the wind power generating set in the file; the original compressed file corresponding to the operating data of the wind generating set with the largest number of columns, rows or numerical values is retained to obtain the effective compressed file.

Optionally, the filtering unit may be configured to: decompress the original compressed files; filter out the original compressed files that fail to be decompressed, keep the original compressed files that are successfully decompressed, and obtain the effective compressed files.

Optionally, the format conversion unit may be configured to: remove quality column data from the data of the effective compressed file, where the quality column data is data indicating a fan manufacturer.

Optionally, the target format may include any one of the following: Parquet, ORC, CarbonData.

Optionally, the cloud computing service-based wind power generating set operation data processing device may further include: a data integrity determination unit configured to determine, according to the storage path record of the compressed file in the target format in the cloud server, The data integrity of the wind power generating set within a preset period, the data integrity is used to characterize the number of compressed files in the target format for each wind generating set within the preset period and the preset The ratio of the number of days included in the period.

Optionally, the cloud computing service-based wind power generating set operation data processing device may further include: a data extraction unit configured to extract wind power generating set operating data from the compressed file in the target format; an early warning unit configured to In order to input the operation data of the wind generating set into the early warning model of the components of the wind generating set to obtain the early warning result, the early warning result is used to indicate the abnormal condition of the components of the wind generating set.

According to another aspect of the present disclosure, there is provided a system comprising at least one computing device and at least one storage device storing instructions, wherein the instructions, when executed by the at least one computing device, cause the at least one computing device to Executing the above-mentioned cloud computing service-based wind power generating set operation data processing method.

According to another aspect of the present disclosure, there is provided a computer-readable storage medium storing instructions, wherein, when the instructions are executed by at least one computing device, the at least one computing device is caused to execute the cloud-based computing service as described above. The method for processing the operation data of the wind power generating set.

By adopting the present disclosure, it is possible to reduce the storage cost of the operating data of the wind generating set and improve the reading efficiency of the operating data of the wind generating set.

Description of drawings

The above and/or other objects and advantages of the present disclosure will become more apparent by describing the embodiments below in conjunction with the accompanying drawings, wherein:

Fig. 1 is a flow chart showing a method for processing operating data of a wind power generating set based on a cloud computing service according to an exemplary embodiment of the present disclosure;

Fig. 2 is a structural block diagram showing a cloud computing service-based wind power generating set operation data processing device according to an exemplary embodiment of the present disclosure;

Fig. 3 shows a schematic structural diagram of a system including at least one computing device and at least one storage device storing instructions according to an embodiment of the present disclosure.

detailed description

Exemplary embodiments of the present disclosure will now be described in detail, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like parts. The embodiments are described below in order to explain the present disclosure by referring to the figures.

A system according to an exemplary embodiment of the present disclosure may include a wind turbine, a SCADA system, a cloud server for storing data (for example, an S3 (Simple Storage Service) cloud server or other cloud servers for storing data), capable of realizing Cloud computing services with data processing functions (for example, Lambda services or other cloud computing services with similar functions). Optionally, the system according to the exemplary embodiment of the present disclosure may further include an early warning unit implemented by a cloud computing service or a local computing device. As an important part of wind turbine status monitoring, the SCADA system can provide data for monitoring the status of the wind turbine and the operation status of the wind turbine components. When the SCADA data is sufficient, the early warning unit can be used to realize the early warning of the failure of the wind turbine components.

In an example, firstly, the operation data of the wind power generating set may be obtained through, for example, real-time acquisition by a SCADA system, offline copying, and the like. After compressing the operating data of the wind generating set to obtain a compressed file containing the operating data of the wind generating set, the compressed file can be uploaded to the cloud server. In addition, the original compressed file containing the operating data of the wind power generation unit can be obtained from the cloud server through the cloud computing service, and various data processing can be performed on the obtained original compressed file and/or the data contained therein, and then the processed compressed file can be And/or the data is sent to the cloud server for storage (the specific details of this step will be described later). In this example, the early warning unit realized by the cloud computing service or the local computing device can obtain the original compressed file from the cloud server or the compressed file processed by the cloud computing service, and use various algorithms (for example, neural network, linear regression, Decision Trees, Support Vector Machines, Bayesian Classifiers, Reinforcement Learning, Probabilistic Graphical Models, Clustering, etc.) to predict the operating state or failure of a wind turbine or a component of a wind turbine based on the data in the acquired files. For example, when the early warning unit determines that there is a risk of failure of the components of the wind power generating set, it will send early warning information to the main controller of the wind generating set, so that the main controller of the wind generating set can perform corresponding processing (such as shutting down, etc.) to avoid The occurrence of faults, or send out alarm information to notify the corresponding personnel to confirm and deal with possible fault conditions.

Fig. 1 is a flowchart illustrating a method for processing operating data of a wind power generating set based on a cloud computing service according to an exemplary embodiment of the present disclosure.

As shown in Fig. 1, in step S101, the original compressed file containing the operation data of the wind power generating set is obtained from the cloud server. As mentioned above, the operating data of the wind turbine generator contained in the original compressed file can be obtained from the SCADA system in real time or data copied offline, each original compressed file can only correspond to one wind turbine generator and date, and can be included in the original compressed file The file name of the compressed file includes the number information of the wind power generating set corresponding to the running data of the wind generating set contained in the compressed file and the time information of obtaining the running data of the wind generating set.

In step S102, the original compressed files may be filtered according to preset filtering conditions to obtain valid compressed files. In an example, the preset filter conditions may include: the format of the original compressed file is a preset format and/or the file name of the original compressed file contains a fan number, and the original compressed file is filtered according to the preset filter conditions to obtain an effective The step of compressing the files may include: removing original compressed files that do not meet any of the preset filtering conditions from the original compressed files to obtain a valid compressed file. Specifically, for example, the preset format may include arc format, goldwind format (a compression format used in the wind power industry) and zip format. After the original compressed file is obtained from the cloud server, the filename suffix of the original compressed file may be verified to be Determine whether the file name suffix of the original compressed file is one of the preset suffixes, if it is determined that the file name suffix of the original compressed file is not one of the preset suffixes (for example, arc, goldwind and zip), you can set the The original archive is filtered out. In addition, the fan number can be obtained from the filename of the original compressed file. In one example, it may be determined whether to filter out the original compressed file of the file name corresponding to the fan number according to whether the number of digits of the fan number satisfies the limit of predetermined digits, for example, if the fan number has a specified number of digits number (for example, 9), if the fan number determined by the file name of the original compressed file has a number of digits not equal to the specified number (for example, 8 or 10), the file corresponding to the fan number can be Named raw archives are filtered out. In one example, it can also be indicated according to the number of the wind turbine number indicating the wind power generating set (for example, a number that can define a specific position in the wind turbine number (for example, the first three digits or the last three digits in the wind turbine number) number of wind power generating units) and the actual total number of wind power generating units to determine whether to screen out the corresponding original compressed file, for example, when the actual total number of wind power generating units is 400, if the file name of the original compressed file The obtained wind turbine number indicates that the wind power generating set corresponding to the original file is No. 401 (exceeding the actual total number of wind generating sets), and the original compressed file can be filtered out. In addition, the step of filtering the original compressed file according to preset filtering conditions to obtain an effective compressed file may also include: determining the fan number and file date according to the file name of the original compressed file; for the original compressed file with the same fan number and file date, Read the operating data of the wind power generating set in the original compressed file; retain the original compressed file corresponding to the operating data of the wind generating set with the largest number of columns, rows or values, so as to obtain an effective compressed file. Through the above-mentioned processing steps for the original compressed files with the same fan number and file date, the uniqueness of the compressed files of the operating data of the same wind generating set on the same day can be ensured, thereby improving the validity of the operating data of the wind generating set. In addition, filtering the original compressed files according to preset filtering conditions to obtain effective compressed files may include: decompressing the original compressed files; filtering out the original compressed files that failed to be decompressed, and retaining the original compressed files that were successfully decompressed, so as to obtain the effective compressed files. document.

In step S103, the effective compressed file may be converted into a compressed file in a target format, and the target format includes columnar storage. For example, target formats can include any of the following: Parquet, ORC, CarbonData. In an example, the step of converting a valid compressed file into a compressed file in a target format may include: extracting a file path and a file name of a valid compressed file; associating the file path with the file name to obtain an intermediate variable; inputting the intermediate variable to Preset format conversion function to get the compressed file in the target format. In another example, the step of converting the valid compressed file into the compressed file of the target format may further include: converting the data in the valid compressed file into a predetermined format data; compress the data in the predetermined format to obtain an intermediate compressed file; return and execute the step of extracting the file path and file name of the effective compressed file according to the intermediate compressed file. Specifically, taking converting a valid compressed file into a compressed file in Parquet format as an example, for example, python or spark SQL commands can be used (for example, the function dataFrame.to_parquet(resultOutputPath), wherein the input of this function is the data in the valid file, and the output The storage path of the Parquet file) to realize the conversion of the Parquet format. In the process of converting the effective compressed file into the compressed file of the Parquet format, if the format conversion fails, the format of the data in the effective compressed file can be converted to a predetermined format. (for example, string format), and reuse python or spark SQL commands to convert the format of the data into a valid compressed file of a predetermined format to perform Parquet format conversion. In addition, the schema information of the compressed file converted into the target format can be recorded in the first database table (for example, a relational database table) in the cloud server, and the storage path of the compressed file converted into the target format in the cloud service Recorded in a second database table (for example, a relational database table) in the cloud server. In addition, the step of converting the valid compressed file into a compressed file of the target format may further include: removing quality column data from the data of the valid compressed file, the quality column data being data indicating a fan manufacturer. And the step of converting the effective compressed file into the compressed file of the target format can also include modifying true and false in the data in the effective compressed file to 1 and 0 respectively, so as to satisfy the process of back-end development (for example, when using the Java language In the case of ), there may be specific requirements for the data in the compressed file.

After converting the valid compressed file into the compressed file in the target format, the compressed file in the target format can be sent to the cloud server in step S104. In addition, the method for processing the operation data of the wind power generating set based on the cloud computing service may further include: according to the record of the storage path of the compressed file in the target format in the cloud server, determining the data integrity of the wind generating set within a preset period, The data integrity is used to characterize the ratio of the number of compressed files in the target format for each wind turbine generator set within a preset period to the number of days included in the preset period. In an example, the preset period may be a year or a month. In the case that the preset period is a year, for each wind power generating set, according to the record of the storage path of the compressed file in the cloud server corresponding to the target format (for example, the second database table as mentioned above) determine a The number of compressed files in the target format in the year, and calculate the ratio of the number to the number of days in the year, and the ratio is the data integrity of the corresponding wind power generating set in the year. Furthermore, an average value between the data completeness of several wind parks can also be calculated.

In one example, the method for processing wind turbine operating data based on cloud computing services may further include: extracting wind turbine operating data from a compressed file in a target format; inputting the wind turbine operating data into a wind turbine component early warning model to obtain Early warning results for indicating abnormal conditions of wind turbine components. In another example, an application program interface (API) (e.g., GETAPI or POST API) for requesting wind turbine operating data may also be constructed locally, and the acquired wind turbine operating data may be input to wind turbine components The early warning model (for example, the early warning model constructed by using the artificial neural network algorithm) obtains the early warning results used to indicate the abnormal conditions of the wind turbine components (for example, the failure of the wind turbine gearbox, the failure of the wind turbine generator bearing, etc.). Wherein, the early warning model of the components of the wind power generating set may be an early warning model for the whole wind generating set (for example, an early warning model for predicting the performance degradation of the wind generating set (including the type of degradation and/or the start time of the degradation, etc.) or the health degree ), it can also be an early warning model for a single component (eg, generator winding, grid-side reactor, grid-side inverter, grid-side converter controller, motor-side rectifier, pitch capacitor, etc.). In addition, the wind turbine failure early warning method may be based on a single variable threshold value, for example, an early warning may be issued when the temperature exceeds 50 degrees. Specifically, for the main control system, the temperature of the generator winding can be monitored; for the converter system, the grid-side reactor, grid-side inverter, grid-side converter controller, motor-side rectifier, and motor-side controller cabinet can be monitored temperature; for the pitch system, it can monitor the temperature of the pitch motor, pitch capacitor, pitch control cabinet, and pitch inverter. Since the effectiveness of the wind turbine operating data in the compressed file stored in the target format after the above data processing is improved, when the wind turbine operating data in the compressed file stored in the target format after the above data processing is used as wind power When the early warning model of the generator set is input, the accuracy of the early warning of the wind turbine component can be improved.

The above steps S101 to S104 can all be performed by cloud computing services (for example, Lambda services or other cloud computing services with similar functions).

Fig. 2 is a structural block diagram showing a cloud computing service-based wind power generating set operation data processing device according to an exemplary embodiment of the present disclosure.

As shown in FIG. 2 , according to an embodiment of the present disclosure, the cloud computing service-based wind power generating set operating data processing device 200 may include: an acquisition unit 201 configured to acquire an original compressed file containing wind generating set operating data from a cloud server The filtering unit 202 is configured to filter the original compressed file according to preset filtering conditions to obtain an effective compressed file; the format conversion unit 203 is configured to convert the effective compressed file into a compressed file in a target format, so The target format includes columnar storage; the sending unit 204 is configured to send the compressed file in the target format to a cloud server.

In one example, the format conversion unit 203 may be configured to: extract the file path and file name of the effective compressed file; associate the file path with the file name to obtain an intermediate variable; convert the intermediate variable to input to a preset format conversion function to obtain a compressed file in the target format. In this example, the format converting unit 203 may also be configured to: convert the data in the valid compressed file into data in a predetermined format when converting the valid compressed file into a target format compressed file fails; Compressing the data in the predetermined format to obtain an intermediate compressed file; returning to the step of extracting the file path and file name of the effective compressed file according to the intermediate compressed file.

In an example, the preset filter condition may include that the format of the original compressed file is a preset format and/or the file name of the original compressed file contains a fan number, and the filtering unit 202 may be configured to: from the original compressed file Remove the original compressed files that do not meet any of the preset filter conditions to obtain a valid compressed file.

In an example, the screening unit 202 may be configured to: determine the fan number and file date according to the file name of the original compressed file; for the original compressed file whose fan number and file date are the same, read the original compressed The operating data of the wind power generating set in the file; the original compressed file corresponding to the operating data of the wind generating set with the largest number of columns, rows or numerical values is retained to obtain the effective compressed file. In another example, the filtering unit 202 may be configured to: decompress the original compressed files; filter out the original compressed files that failed to be decompressed, keep the original compressed files that were successfully decompressed, and obtain valid compressed files.

In an example, the format converting unit 203 may be configured to: remove quality column data from the data of the effective compressed file, where the quality column data is data indicating a wind turbine manufacturer. Additionally, target formats can include any of the following: Parquet, ORC, CarbonData.

In an example, the cloud computing service-based wind power generating set operation data processing device 200 may further include: a data integrity determination unit 205 configured to record the storage path of the compressed file in the target format in the cloud server, determining the data completeness of the wind power generating set within a preset period, the data integrity being used to characterize the relationship between the number of compressed files in the target format for each wind generating set within the preset period and the preset Set the ratio of the number of days included in the period. In another example, the wind power generating set operating data processing device 200 based on cloud computing services may further include: a data extraction unit 206 configured to extract the wind generating set operating data from the compressed file in the target format; an early warning unit 207 , configured to input the operation data of the wind power generating set into the early warning model of the wind power generating set components to obtain an early warning result, the early warning result being used to indicate the abnormal condition of the wind power generating set components.

Each unit included in the cloud computing service-based wind power generating set operation data processing device according to an exemplary embodiment of the present disclosure may be respectively configured as software, hardware, firmware or any combination of the above-mentioned items to perform specific functions. For example, these devices may correspond to dedicated integrated circuits, may also correspond to pure software codes, and may also correspond to modules combining software and hardware. In addition, one or more functions implemented by these devices may also be uniformly performed by components in a physical entity device (for example, a processor, a client or a server, etc.). The specific operations shown above in conjunction with FIG. 1 may be performed by corresponding units in the device shown in FIG. 2 , and details of the specific operations will not be repeated here.

Fig. 3 shows a schematic structural diagram of a system including at least one computing device and at least one storage device storing instructions according to an embodiment of the present disclosure.

As shown in FIG. 3 , a system 300 provided according to an embodiment of the present disclosure may include at least one computing device (for example, a processor) 301 and at least one storage device 302 storing instructions, wherein the instructions are executed by the at least one When the computing device 301 is running, the at least one computing device 301 is prompted to execute the method for processing the operation data of the wind power generating set based on the cloud computing service described in any one of the foregoing embodiments.

The computing device can be deployed in a server or client, or on a node device in a distributed network environment. In addition, the computing device may be a PC computer, a tablet device, a personal digital assistant, a smart phone, a web application, or other devices capable of executing the above-mentioned set of instructions. Here, the computing device does not necessarily have to be a single computing device, but may also be any collection of devices or circuits capable of individually or jointly executing the above-mentioned instructions (or instruction sets). The computing device may also be part of an integrated control system or system manager, or may be configured as a portable electronic device that interfaces with local or remote (eg, via wireless transmission). In the computing device, a processor may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a special purpose processor system, a microcontroller, or a microprocessor. Processors may also include, by way of example and not limitation, analog processors, digital processors, microprocessors, multi-core processors, processor arrays, network processors, and the like.

Some of the operations described in the cloud computing service-based wind power generation unit operating data processing method according to an exemplary embodiment of the present disclosure can be implemented by software, and some operations can be implemented by hardware. In addition, software and hardware can also be used. Combined methods to achieve these operations. The processor can execute instructions or codes stored in one of the memory components, which can also store data. Instructions and data may also be sent and received over a network via a network interface device, which may employ any known transport protocol. The storage unit may be integrated with the processor, for example, RAM or flash memory disposed within an integrated circuit microprocessor or the like. Additionally, the storage component may comprise a separate device, such as an external disk drive, storage array, or any other storage device usable by the database system. The storage component and the processor can be operatively coupled or can communicate with each other, eg, via an I/O port, network connection, etc., such that the processor can read files stored in the storage component. Additionally, the computing device may also include a video display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, mouse, touch input device, etc.). All components of the computing device may be connected to each other via a bus and/or network.

Operations involved in the cloud computing service-based wind power generating set operating data processing method according to an exemplary embodiment of the present disclosure may be described as various interconnected or coupled functional blocks or functional diagrams. However, these functional blocks or functional diagrams may equally be integrated into a single logical device or operate along imprecise boundaries.

For example, as described above, there is provided a system comprising at least one computing device and at least one storage device storing instructions, wherein the instructions, when executed by the at least one computing device, cause the at least one computing device to perform Steps S101 to S104 described with reference to FIG. 1 . That is to say, the above-mentioned computing device can execute the method for processing the operation data of the wind power generating set based on the cloud computing service shown in FIG. 1 . Since the method for processing the operation data of the wind power generating set based on the cloud computing service has been introduced in detail in FIG. 1 above, the content of this part will not be repeated in this disclosure.

In addition, embodiments according to the present disclosure also provide a computer-readable storage medium storing instructions, wherein, when the instructions are executed by at least one computing device, the at least one computing device is prompted to execute the program described in any one of the preceding embodiments. A cloud computing service-based wind turbine operation data processing method.

By adopting the present disclosure, it is possible to reduce the storage cost of the operating data of the wind generating set and improve the reading efficiency of the operating data of the wind generating set.

Although this disclosure includes specific examples, it will be apparent to one of ordinary skill in the art that changes in form and details may be made in these examples without departing from the spirit and scope of the claims and their equivalents. Various changes. The examples described herein are to be considered in a descriptive sense only and not for purposes of limitation. Descriptions of features or aspects within each example should be considered as available for similar features or aspects in other examples. If the described techniques are performed in a different order, and/or if components in a described system, architecture, device, or circuit are combined in a different manner and/or are replaced or supplemented with other components or their equivalents, the described system, architecture , a device or a component in a circuit, suitable results can be obtained. Therefore, the scope of the present disclosure is defined not by the specific embodiments but by the claims and their equivalents, and all modifications within the scope of the claims and their equivalents will be construed as being included in the present disclosure.

Claims (13)

1. A wind generating set operation data processing method based on cloud computing service is characterized by comprising the following steps:

acquiring an original compressed file containing wind generating set operation data from a cloud server;

screening the original compressed file according to a preset screening condition to obtain an effective compressed file;

converting the valid compressed file into a compressed file in a target format, the target format comprising columnar storage;

and sending the compressed file in the target format to a cloud server.

2. The cloud computing service-based wind turbine generator system operation data processing method according to claim 1, wherein the step of converting the effective compressed file into a compressed file of a target format includes:

extracting a file path and a file name of the effective compressed file;

performing association operation on the file path and the file name to obtain an intermediate variable;

and inputting the intermediate variable into a preset format conversion function to obtain the compressed file in the target format.

3. The cloud computing service-based wind generating set operation data processing method according to claim 2, wherein the step of converting the effective compressed file into a compressed file of a target format further comprises:

converting the data in the effective compressed file into data in a preset format under the condition that the effective compressed file is converted into a compressed file in a target format unsuccessfully;

compressing the data in the preset format to obtain an intermediate compressed file;

and returning to execute the step of extracting the file path and the file name of the effective compressed file according to the intermediate compressed file.

4. The cloud computing service-based wind turbine generator system operation data processing method according to claim 1, wherein the preset screening condition includes: the format of the original compressed file is a preset format and/or the file name of the original compressed file comprises a fan number;

and the step of screening the original compressed file according to a preset screening condition to obtain an effective compressed file comprises the following steps:

and removing the original compressed files which do not accord with any one of the preset screening conditions from the original compressed files to obtain effective compressed files.

5. The cloud computing service-based wind generating set operation data processing method according to claim 1, wherein the step of screening the original compressed file according to a preset screening condition to obtain an effective compressed file comprises:

determining the fan number and the file date according to the file name of the original compressed file;

aiming at the original compressed file with the same fan number and file date, reading the wind generating set operation data in the original compressed file;

and reserving the original compressed file corresponding to the wind generating set operation data with the maximum column number, row number or numerical value to obtain the effective compressed file.

6. The cloud computing service-based wind generating set operation data processing method according to claim 1, wherein the step of screening the original compressed file according to a preset screening condition to obtain an effective compressed file comprises:

decompressing the original compressed file;

and screening out the original compressed files which are not decompressed successfully, and reserving the original compressed files which are not decompressed successfully to obtain the effective compressed files.

7. The cloud computing service-based wind turbine generator system operation data processing method according to claim 1, wherein the step of converting the effective compressed file into a compressed file of a target format includes:

removing quality column data from data of the valid compressed file, the quality column data being data indicative of a manufacturer of the wind turbine.

8. The cloud computing service based wind turbine generator system operation data processing method according to claims 1 to 7, wherein the target format includes any one of: partial, ORC, carbonData.

9. The cloud computing service based wind power generation unit operation data processing method according to claims 1 to 7, wherein the cloud computing service based wind power generation unit operation data processing method further comprises:

and determining the data integrity of the wind generating set in a preset period according to the record of the storage path of the compressed file in the target format in the cloud server, wherein the data integrity is used for representing the ratio of the number of the compressed files in the target format for each wind generating set in the preset period to the number of days included in the preset period.

10. The cloud computing service based wind power generation unit operation data processing method according to claims 1 to 7, wherein the cloud computing service based wind power generation unit operation data processing method further comprises:

extracting wind generating set operation data from the compressed file in the target format;

and inputting the wind generating set operation data into a wind generating set component early warning model to obtain an early warning result, wherein the early warning result is used for indicating the abnormal condition of the wind generating set component.

11. A wind generating set operation data processing device based on cloud computing service is characterized by comprising:

the acquisition unit is configured to acquire an original compressed file containing the operating data of the wind generating set from a cloud server;

the screening unit is configured to screen the original compressed file according to a preset screening condition to obtain an effective compressed file;

a format conversion unit configured to convert the valid compressed file into a compressed file of a target format, the target format including columnar storage;

and the sending unit is configured to send the compressed file in the target format to a cloud server.

12. A system comprising at least one computing device and at least one storage device storing instructions, wherein the instructions, when executed by the at least one computing device, cause the at least one computing device to perform the cloud computing service based wind turbine generator set operational data processing method of any of claims 1 to 10.

13. A computer-readable storage medium storing instructions that, when executed by at least one computing device, cause the at least one computing device to perform the cloud computing service based wind park operational data processing method of any of claims 1 to 10.

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