Data management method and device of wind power plant, storage medium and electronic device

Abstract

The invention discloses a data management method and device of a wind power plant, a storage medium, an electronic device and a computer program product. The method comprises the following steps: collecting monitoring data collected by each sensor in the wind power plant through a local server; transmitting the monitoring data to a local database for storage through a local server, and transmitting the monitoring data to a cloud server; responding to an interaction request of a first object installed with preset client software through a local server so as to perform data interaction with the first object; and responding to an access request of the second object through the cloud server so as to display the monitoring data to the second object. And the local server can provide more flexible and timely data response. The cloud server can improve the data sharing efficiency. Through cooperative work of the local server and the cloud server, internal safe and rapid data access and external convenient data sharing are taken into consideration.

Description

Technical Field

[0001] This application relates to the field of wind power, and in particular, to a data management method and device for a wind farm, a storage medium, an electronic device, and a computer program product. Background Art

[0002] With the transformation of the global energy structure, wind energy, as one of the renewable clean energies, has been increasingly emphasized in its development and utilization. In the operation of a wind farm, the available wind energy resources are converted into mechanical energy and then into electrical energy to be supplied to a specific power grid. During the operation of the wind farm, a large amount of wind power data is collected and stored in the local server of the wind farm. The wind power data includes, but is not limited to, the operation status data of the wind farm, the equipment status data, and the power grid operation status data.

[0003] In the related art, the architecture of the data management system of a wind farm usually adopts the Client / Server (C / S) architecture or the Browser / Server (B / S) architecture.

[0004] However, the methods in the related art have problems of insufficient data security or sharing efficiency. Summary of the Invention

[0005] Embodiments of this application provide a data management method and device for a wind farm, a storage medium, an electronic device, and a computer program product.

[0006] According to one aspect of the embodiments of this application, a data management method for a wind farm is provided. The data management system of the wind farm includes a local server and a cloud server. The method includes: collecting, by the local server, monitoring data collected by each sensor in the wind farm; transmitting, by the local server, the monitoring data to the local database for storage and transmitting the monitoring data to the cloud server; responding, by the local server, to an interaction request of a first object installed with a preset client software to perform data interaction with the first object; and responding, by the cloud server, to an access request of a second object to display the monitoring data to the second object.

[0007] In an exemplary embodiment, transmitting the monitoring data to the cloud server includes: packing the monitoring data into a standard file in a preset format; determining a target transmission method in response to the real-time requirement of the first object for the monitoring data; and transmitting the standard file to the cloud server by using the target transmission method.

[0008] In an exemplary embodiment, after the monitoring data is transmitted to the cloud server, the method further includes: parsing the monitoring data by the cloud server to screen out historical data and real-time data in the monitoring data; storing the historical data and the real-time data into a monitoring database, and storing the real-time data into a real-time database, where the real-time database is used to respond to the access request of a second object.

[0009] In an exemplary embodiment, after the historical data and the real-time data are stored into the monitoring database and the real-time data is stored into the real-time database, the method further includes: checking, by the cloud server, whether the historical data stored in the monitoring database is complete; in the case where it is determined that there is missing historical data stored in the monitoring database, sending a data supplement request to the local server; in response to the data supplement request by the local server, transmitting corresponding supplementary historical data to the cloud server; receiving, by the cloud server, the supplementary historical data transmitted by the local server, and storing the supplementary historical data into the monitoring database.

[0010] In an exemplary embodiment, the cloud server responds to the access request of a second object to display the monitoring data to the second object, including: receiving, by the cloud server, the access request of the second object; calling target monitoring data from the real-time database according to the access request of the second object; and displaying the target monitoring data to the second object.

[0011] In an exemplary embodiment, the local server responds to the interaction request of a first object installed with a preset client software to perform data interaction with the first object, including: receiving, by the local server, the interaction request; determining whether the object sending the interaction request is installed with the preset client software; in the case where it is determined that the object sending the interaction request is installed with the preset client software, performing permission verification on the object, where the object installed with the preset client software is the first object; and in the case where the object permission verification is passed, performing data interaction with the object in response to the interaction request.

[0012] According to another aspect of the embodiments of the present application, there is also provided a data management device for a wind farm, the device includes: a data collection module, configured to collect monitoring data collected by each sensor in the wind farm through the local server; a data transmission module, configured to transmit the monitoring data to the local database for storage and transmit the monitoring data to the cloud server through the local server; a data interaction module, configured to perform data interaction with a first object in response to the interaction request of the first object installed with a preset client software through the local server; and a data display module, configured to display the monitoring data to a second object in response to the access request of the second object through the cloud server.

[0013] According to another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the above-mentioned data management method for a wind farm when running.

[0014] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the above-mentioned processor executes the above-mentioned data management method for a wind farm through the computer program.

[0015] According to another aspect of the embodiments of the present application, there is also provided a computer program product including a computer program, and the steps of the methods described in various embodiments of the present application are implemented when the computer program is executed by a processor.

[0016] The above-mentioned data management method for a wind farm, through the collaborative work of the local server and the cloud server, ensures the secure storage and remote backup of data, providing a solid data foundation for the normal operation of the wind farm. At the same time, the use of the preset client software ensures that internal professionals can obtain timely and accurate wind farm status information, while the access interface of the cloud server allows external users to access wind farm data through the Internet, greatly expanding the application scope of the data and enhancing the flexibility and responsiveness of the system. This hybrid architecture not only improves the security and reliability of the data, but also significantly improves the data sharing efficiency, providing strong support for the remote monitoring, centralized management, and intelligent decision-making of the wind farm. Through dual storage on the local and cloud sides, the system also enhances the data recovery ability and redundancy, providing a strong guarantee for the continuous operation of the wind farm. In summary, the method of the present application constructs a secure and open wind farm monitoring system, meeting the dual requirements of modern wind power operation for data security and sharing. It can not only efficiently collect and process various real-time monitoring data in the wind farm, but also achieve a balance between internal secure data access and external convenient data sharing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0019] Figure 1It is a hardware structure block diagram of the data management method for a wind farm according to an embodiment of the present application;

[0020] Figure 2 It is a flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0021] Figure 2a It is a schematic architecture diagram of a data management method for a wind farm according to an embodiment of the present application;

[0022] Figure 2b It is a schematic diagram of a data management system for a wind farm according to an embodiment of the present application;

[0023] Figure 3 It is the second flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0024] Figure 4 It is the third flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0025] Figure 5 It is the fourth flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0026] Figure 5a It is a schematic diagram of the interaction process between a local server and a cloud server according to an embodiment of the present application;

[0027] Figure 6 It is the fifth flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0028] Figure 7 It is the sixth flowchart of a data management method for a wind farm according to an embodiment of the present application;

[0029] Figure 8 It is a structure block diagram of a data management device for a wind farm according to an embodiment of the present application. Detailed implementation manners

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0031] It should be noted that the terms "first", "second", etc. in the description, claims, and the above-mentioned drawings of this application are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0032] The method embodiments provided in the embodiments of this application can be executed on a computer terminal or a similar computing device. Taking running on a computer terminal as an example, Figure 1 is a hardware structure block diagram of a computer terminal for the data management method of a wind power plant in the embodiments of this application. As Figure 1 shown, the computer terminal may include one or more ( Figure 1 only one is shown in the figure) processors 102 (the processor 102 may include, but is not limited to, a microprocessor (abbreviated as MPU) or a programmable logic device (abbreviated as PLD)) and a memory 104 for storing data. In an exemplary embodiment, the above-mentioned computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only illustrative and does not limit the structure of the above-mentioned computer terminal. For example, the computer terminal may further include more or fewer components than Figure 1 shown in the figure, or have an equivalent function to Figure 1 shown in the figure or different configurations with more functions than Figure 1 shown in the figure.

[0033] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the data management method of the wind power plant in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above-mentioned method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the computer terminal through a network. Examples of the above-mentioned network include but are not limited to the Internet, intranet, local area network, mobile communication network, and combinations thereof.

[0034] The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by a communication provider of a computer terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 can be a radio frequency (Radio Frequency, abbreviated as RF) module, which is used to communicate with the Internet wirelessly.

[0035] As described in the background art, during the operation of a wind power plant, a large amount of wind power data is collected and stored in the local server of the wind power plant. The wind power data includes, but is not limited to, the operating status data of the wind power plant, the equipment status data, the grid operating status data, etc., which are hereinafter collectively referred to as monitoring data. Among the monitoring data, the grid operating status data is usually named "grid data", which includes, but is not limited to, grid frequency, grid voltage, grid current, active power, reactive power, grid fault information, etc. These data have high real-time requirements. The grid operating status data is the basis for the operation status of the wind power plant and requires the wind power plant to make timely responses. Therefore, the grid data is given extremely high priority in the management of the wind power plant and is transmitted in real time to the remote server of the wind power plant for storage and display. During the operation of the wind power plant, the requirement of real-time performance poses high requirements for the management and operation and maintenance of the wind power plant. The operation and maintenance personnel of the wind power plant need to respond to the operation status of the wind farm within a short time. Therefore, the operation and maintenance personnel of the wind power plant need to be able to quickly obtain the operation status data of the wind power plant. Currently, the operation and maintenance personnel of the wind power plant view the operation status data of the wind power plant in the local server of the wind power plant. It is difficult for the operation and maintenance personnel to obtain the operation status data of the wind farm in the management of the wind power plant, resulting in low operation and maintenance efficiency of the operation and maintenance personnel of the wind power plant and affecting the operation and maintenance quality of the wind power plant. To solve the problem that it is difficult for the operation and maintenance personnel to obtain the operation status data of the wind farm in a timely manner, in some wind farms with remote servers, the operation and maintenance personnel obtain the operation status data of the wind farm through the remote server. The remote server is usually located in an area outside the wind farm, and there is a network delay problem with the local server of the wind farm, making it difficult for the operation and maintenance personnel to obtain the operation status data of the wind farm in a timely manner, affecting the operation and maintenance efficiency of the wind farm. It is difficult for the operation and maintenance personnel of the wind power plant to obtain the operation status data of the wind farm in a timely manner, affecting the operation and maintenance efficiency of the operation and maintenance personnel of the wind power plant. Therefore, in view of the above technical problems, the data management method of the wind power plant of the present application is provided, which can balance the data security and the data sharing efficiency.

[0036] In this embodiment, a data management method for a wind power plant is provided. Figure 2 It is a flowchart of an optional data management method for a wind power plant according to an embodiment of the present application. The data management system of the wind power plant includes a local server and a cloud server. The process includes the following steps S200 - S230:

[0037] Step S200, collect the monitoring data collected by each sensor in the wind power plant through the local server.

[0038] Specifically, the local server is located at the center of the internal network of the wind farm and is responsible for aggregating the real-time monitoring data collected by various sensors distributed throughout the wind farm. These data include, but are not limited to, the operating status of wind power generating units, environmental parameters (such as temperature, humidity, wind speed), and other key indicators, which are the basis for the operation optimization and fault prediction of the wind farm.

[0039] Exemplarily, the local server is equipped with a variety of different data interfaces and can communicate efficiently with various sensors. The sensors transmit the collected raw data to the local server via wireless or wired networks. The data collection module in the server is responsible for receiving this data and performing preliminary preprocessing on it, such as data format conversion, outlier detection, and timestamp addition, to ensure the quality and usability of the data. In addition, the server may also use specific protocols and packet encapsulation technologies for subsequent data transmission and storage.

[0040] Step S210, transmit the monitoring data to the local database for storage and to the cloud server through the local server.

[0041] Specifically, the monitoring data is not only stored in the local database for quick access and on-site analysis, but also transmitted to the cloud server through the network to achieve remote storage and redundant backup of the data. This step ensures that the data will not be lost even in the case of a local system failure, and at the same time enables remote users to access and analyze the data.

[0042] Exemplarily, the local server stores the preprocessed monitoring data in the local database according to a fixed data structure. The database may adopt relational database technologies such as MySQL and Oracle to ensure data consistency and easy query. For the data transmission to the cloud server, the local server can choose FTP transmission, Socket communication, or other protocols suitable for large data transmission to send the data packets to the cloud. On the cloud server side, after further processing, the data is stored in a cloud-based database such as Amazon RDS and Alibaba Cloud RDS, which have high reliability and scalability and support the storage and analysis of large-scale data.

[0043] Step S220, respond to the interaction request of the first object installed with the preset client software through the local server to perform data interaction with the first object.

[0044] Specifically, direct interaction can occur between a specific user (the first object) within the wind farm and the monitoring system (local server). The first object generally refers to professional operation and maintenance personnel or management personnel within the wind farm. Through client software installed on personal computers, tablets, or smartphones, they can directly communicate with the local server to obtain real-time status information of the wind farm or perform equipment control.

[0045] Exemplarily, a stable connection based on the TCP / IP protocol is established between the client software and the local server. When the first object initiates a data query or equipment control request through the client software, the local server immediately responds, retrieves corresponding data from the local database according to the content of the request, or directly interacts with devices such as the wind turbine controller, and then feeds back the result to the client software to achieve fast and secure data transmission and immediate execution of operation instructions.

[0046] Among them, a C / S architecture is adopted between the local server and the first object. The C / S architecture is a two-layer structure composed of a client and a server. The client installs dedicated software responsible for providing interface interaction and request services to users; the server side is responsible for receiving requests from the client and processing them, such as data storage, business logic operations, etc. The C / S architecture is usually applicable to scenarios with high requirements for data security and processing efficiency, such as enterprise internal management systems. Its advantages include fast response speed, suitability for handling complex business logics, high security, etc. It is usually applied in a local area network environment, interacting with the server through dedicated client software to achieve functions such as data collection, processing, and display. In this mode, the data transmission between the client and the server is relatively secure because the data interaction occurs in a closed network environment, reducing the risk of external attacks. However, the monitoring system in the C / S mode has relatively high requirements for the hardware configuration of the client, and data sharing is inconvenient. Whenever a new user or location needs to access the system, software must be installed and corresponding configurations made on the new client, which not only increases the system maintenance cost but also limits real-time data sharing and remote access.

[0047] Step S230, in response to the access request of the second object, the cloud server is used to display the monitoring data to the second object.

[0048] Specifically, remote access and sharing of wind farm information are achieved through the cloud server. The second object generally refers to external personnel not on the wind farm site, such as management personnel at the group headquarters, remote technical support teams, or partners. They can initiate access requests to the cloud server through a Web browser or a specific mobile application to view the wind farm monitoring data stored in the cloud, achieving cross-regional data sharing and analysis.

[0049] Exemplarily, the cloud server deploys a web service and an API interface to support remote data access. After the access request of the second object arrives at the cloud server, the server ensures the legality of the request through authentication and permission checking. Subsequently, the cloud server retrieves the monitoring data from its database and may perform tasks such as data analysis and data visualization according to the type of the request, and finally presents it to the second object in the form of intuitive charts, reports or dynamic dashboards, ensuring data security and usability.

[0050] Among them, the B / S architecture is adopted between the cloud server and the second object, which is a structure with a browser as the client. Users access the applications on the server through the browser, and the server side is responsible for processing business logic and data storage. The advantage of the B / S architecture is that users do not need to install dedicated client software and only need a browser to access the system, greatly improving the cross-platform performance and usability of the system; at the same time, the maintenance and upgrade of the system only need to be carried out on the server side, reducing the maintenance cost. Users only need to access the services provided by the system through the browser without installing additional software on the client side. This mode greatly improves the accessibility and sharing of data, and many users can access and view real-time data through the Internet at the same time, which is very suitable for remote monitoring of large-scale distributed systems. However, the data security of the B / S architecture is relatively low.

[0051] Exemplarily, the overall architecture diagram is as Figure 2a shown. The local server can obtain the monitoring data of various sensors through wireless communication, and then interact with the cloud server through the network. The first object and the second object can also interact with the local server and the cloud server through the network respectively. The specific content has been explained in the above content and will not be elaborated here. The schematic diagram of the data management system of the wind power plant is as Figure 2b shown and may include: Data acquisition and transceiver module: The system configures parameters and acquires and sends sensor parameter information. Data processing and display module: Integrated on the same control display interface through hierarchical display technology, including wind turbine electrical parameters, environmental state parameters, generator mechanical parameters, as well as alarm status, working status, etc. Generator set diagnosis module: Based on the expert system and fuzzy fault tree theory, accurately judge the fault type of the generator set and analyze the trend, and realize fault troubleshooting and early warning. Database management module: Use a unified relational database management to uniformly store the equipment status information, alarm information and user data of the generator set, and realize functions such as storage, query and deletion of various information. System management module: Set usage permissions to avoid misoperations and ensure system security.

[0052] In this embodiment, through the collaborative work of the local server and the cloud server, the secure storage and remote backup of data are ensured, providing a solid data foundation for the normal operation of the wind farm. At the same time, the use of the preset client software ensures that internal professionals can obtain timely and accurate wind farm status information, while the access interface of the cloud server allows external users to access wind farm data through the Internet, greatly expanding the application scope of the data and enhancing the flexibility and responsiveness of the system. This hybrid architecture not only improves the security and reliability of the data, but also significantly improves the data sharing efficiency, providing strong support for the remote monitoring, centralized management and intelligent decision-making of the wind farm. Through dual storage on the local and cloud sides, this system also enhances the data recovery ability and redundancy, providing a strong guarantee for the continuous operation of the wind farm. In summary, the method of this application constructs a secure and open wind farm monitoring system, meeting the dual requirements of modern wind power operation for data security and sharing. It can not only efficiently collect and process various real-time monitoring data in the wind farm, but also achieve a balance between internal secure data access and external convenient data sharing.

[0053] In one embodiment, as Figure 3 shown, step S210 of transmitting the monitoring data to the cloud server includes steps S300 - S320:

[0054] Step S300, packing the monitoring data into a standard file in a preset format.

[0055] Specifically, before the data is transmitted to the cloud server, the collected monitoring data is packed to form a standard file that conforms to the preset format. This process is crucial for ensuring the integrity and consistency of the data. The standard file can be a unified data format, such as CSV, XML, JSON, etc., which is convenient for data parsing and storage.

[0056] Exemplarily, after the local server collects the monitoring data, it first performs data preprocessing, including data cleaning, outlier detection, and format conversion, etc., to ensure the quality of the data. Then, according to the preset file structure and encoding rules, the processed data is packed into a standard file. For example, the data can be converted into JSON format because JSON is a lightweight data interchange format that is easy for humans to read and write, and also easy for machines to parse and generate, and is very suitable for transmission over the network. During the packing process, a timestamp and data header information can also be added to facilitate subsequent data unpacking and record management.

[0057] Step S310, determining the target transmission method in response to the real-time requirement of the first object for the monitoring data.

[0058] Specifically, the first object may have specific requirements for the real-time nature of the monitoring data. Therefore, the local server needs to select the most suitable data transmission method according to these requirements. The choice of the transmission method directly affects the data transmission speed and efficiency.

[0059] Exemplarily, the local server evaluates the current network condition and the characteristics of the transmission protocol according to the real-time requirements of the first object, and selects FTP or Socket as the target transmission method. FTP (File Transfer Protocol) is a standard file transfer protocol, suitable for the transfer of large files, but may not meet the requirements of high real-time. Socket communication can achieve the transmission of real-time data streams and can theoretically provide a faster data transmission speed to meet the requirements of high real-time. For example, if the first object needs to obtain the latest monitoring data within a few seconds, the local server may choose Socket communication because its latency is usually lower than that of FTP.

[0060] Step S320, transfer the standard file to the cloud server using the target transmission method.

[0061] Specifically, according to the transmission method determined in the previous step, the local server sends the packaged standard file to the cloud server to complete the remote transmission and backup of the data.

[0062] Exemplarily, if the target transmission method is FTP, the local server will establish an FTP connection with the cloud server and upload the standard file. During the FTP transmission process, the data may need further encryption processing to protect the data security. If the target transmission method is Socket, the local server will establish a Socket connection with the cloud server, and then send the data stream in the standard file in real time. The cloud server receives the data stream and parses it into the standard file format for storage. When using Socket, the data may be transmitted through the TCP / IP protocol to ensure the stability and reliability of the data transmission.

[0063] In this embodiment, through the process of packaging monitoring data into standard files, selecting a transmission method according to real-time requirements, and completing the data transmission to the cloud server, the data transmission strategy proposed by the present invention ensures the efficient, secure, and real-time remote storage and backup of wind farm monitoring data. Specifically, the process of packaging data into standard files not only ensures the unity and easy processing of data but also facilitates remote data transmission and cloud storage. Selecting a transmission method according to the real-time requirements of the first object means that the local server can flexibly respond to different monitoring needs. When the real-time requirement is high, Socket communication can be used to quickly transmit data; when the real-time requirement is relatively low but the data volume is large, FTP becomes a better choice. In addition, the remote storage of data to the cloud server not only enhances the availability and redundancy of data but also allows the second object to remotely access through the Internet, thereby realizing the wide sharing of data and enhancing the flexibility and response ability of the monitoring system. Overall, this data transmission strategy improves the real-time transmission efficiency and security of monitoring data through flexible selection of transmission methods and standardization of data formats. At the same time, through the remote storage of the cloud server, it realizes the efficient sharing and disaster recovery management of data, providing strong technical support for the intelligent operation of wind farms.

[0064] In one embodiment, as Figure 4 shown, after the monitoring data is transmitted to the cloud server in step S210, the method further includes: steps S400 - S410:

[0065] Step S400, parsing the monitoring data through the cloud server to filter out historical data and real-time data in the monitoring data.

[0066] Specifically, after the data is transmitted to the cloud server, the server will further parse and classify these monitoring data. The purpose of this step is to distinguish real-time data and historical data in the data stream because real-time data needs to be quickly responded to for real-time monitoring and decision-making, while historical data is used for long-term storage and data analysis. There are significant differences in the processing methods and storage requirements between the two.

[0067] Exemplarily, the cloud server uses a data parsing algorithm to efficiently distinguish the monitoring data into real-time data and historical data according to the timestamp, type marker, or other preset classification criteria of the data. The data parsing process may involve data cleaning to remove invalid or abnormal data points, as well as data format conversion to ensure that the data meets the storage and processing requirements of the cloud server. The filtered data will be packaged or marked for subsequent classified storage and query.

[0068] Step S410, storing the historical data and real-time data in the monitoring database and storing the real-time data in the real-time database.

[0069] Among them, the real-time database is used to respond to the access requests of the second object. The real-time database not only stores real-time data but also is responsible for responding to the access requests of remote users. The second object, namely the external user, can access the real-time database through the network to obtain the real-time operation status of the wind farm, thereby realizing remote monitoring and data analysis. The real-time database is configured with a Web service interface or an API interface. When the second object issues an access request, the Web service or API service module of the cloud server will parse the request content, extract the required data query conditions, and forward the query instruction to the real-time database. The real-time database quickly retrieves data according to the query instruction and returns the result to the cloud server in formats such as JSON, XML, or other formats. Then, the cloud server presents the data to the second object in the form of a Web page, chart, or report, realizing the real-time display of data.

[0070] Specifically, storing the parsed and classified data into the corresponding database is a key step to ensure data availability and accessibility. Historical data and real-time data are stored in the monitoring database and the real-time database respectively. The monitoring database is used to store data for a long time, facilitating trend analysis and historical backtracking; the real-time database serves the current monitoring needs and provides fast data reading and response.

[0071] Exemplarily, for historical data, the cloud server writes it into the monitoring database, and the monitoring database may adopt big data storage technologies such as Hadoop HDFS, Google Bigtable, etc. to support the long-term storage and efficient retrieval of massive data. For real-time data, the cloud server stores it in the real-time database, and the real-time database may be based on time series databases or caching technologies such as Redis, InfluxDB, etc. to ensure low-latency data reading and high-frequency updates. At the same time, there may be a data synchronization mechanism between the real-time database and the monitoring database to regularly archive real-time data into the monitoring database for long-term data preservation.

[0072] In this embodiment, the cloud server parses the monitoring data transmitted from the local server of the wind farm, distinguishes real-time data and historical data, and stores them in the real-time database and the monitoring database respectively. The present invention constructs an efficient and flexible data storage and access system. Specifically, the data parsing technology of the cloud server ensures the validity and availability of the data. The classified storage of historical data and real-time data not only reduces the pressure of data processing, but also optimizes the efficiency of data query. Storing real-time data in a high-speed real-time database can quickly respond to the access requests of remote users, realize the real-time monitoring of the operation status of the wind farm, and improve the response speed and decision-making efficiency of the system. Historical data is stored in the monitoring database for a long time, providing a basis for in-depth data mining such as trend analysis and fault backtracking, and enhancing the analysis ability of the system. In addition, the elastic expansion and high availability of the cloud server ensure the stability and reliability of the data storage system, and can maintain good performance even in the case of a sharp increase in data volume. In summary, through data parsing and classified storage in the cloud, the present invention realizes the real-time nature of remote monitoring and the in-depth analysis ability of historical data, providing strong data support for the remote management and intelligent operation of the wind farm.

[0073] In one embodiment, as Figure 5 shown, after storing historical data and real-time data in the monitoring database and storing real-time data in the real-time database in step S410, the method further includes steps S500-S530:

[0074] Step S500, check whether the historical data stored in the monitoring database is complete through the cloud server.

[0075] Specifically, this step is to ensure the integrity of the historical data in the monitoring database on the cloud server. Due to possible network interruptions, file transfer errors, etc. during the data transmission process, resulting in partial loss or damage of the historical data, the cloud server needs to regularly check the integrity of the historical data to verify whether there is data missing.

[0076] Exemplarily, the cloud server scans and verifies the historical data stored in the monitoring database by running an integrity check script or algorithm. This process may include methods such as data proofreading, hash value comparison, data point counting, etc. to confirm whether there is any omission or abnormality in the data. For example, the system can check whether the data points per minute or per hour are complete according to the time series attributes of the data. If it is found that the data at a certain time point is missing, the missing time period is recorded to provide a basis for subsequent data supplement requests.

[0077] Step S510, in the case of determining that there is missing historical data stored in the monitoring database, send a data supplement request to the local server.

[0078] Specifically, once the cloud server discovers missing historical data during the integrity check, it will send a data supplementation request to the local server via the network, instructing the local server to provide the data records for the missing time period to fill the gap in the cloud data.

[0079] Exemplarily, the cloud server generates a data supplementation request containing information such as the time period and type of the missing data, and sends it to the local server via the network. The request may use HTTP, SMTP or other custom communication protocols to ensure that the request can be accurately conveyed to the destination. After receiving the request, the local server will put it into the request queue and wait for subsequent processing.

[0080] Step S520, in response to the data supplementation request, the local server transmits the corresponding supplementary historical data to the cloud server.

[0081] Specifically, after receiving the data supplementation request, the local server will search for and extract the data for the missing time period from its local database, then repackage and transmit it to the cloud server via the network to complete the supplementary upload of the data.

[0082] Exemplarily, the data supplementation module of the local server parses the data supplementation request to determine the specific historical data to be supplemented. Then, this module retrieves the data records for the corresponding time interval from the local database, which may be implemented through SQL query statements or other database interfaces, and then repackages these historical data into a format that meets the receiving standard of the cloud server, such as common data exchange formats like JSON and XML. Finally, the local server uses methods such as FTP, Socket or HTTPS to transmit the supplementary data to the cloud server. During this process, the stability, speed and security of data transmission are key considerations, and the local server may also encrypt the data to prevent the risk of leakage that may occur during transmission.

[0083] Step S530, the cloud server receives the supplementary historical data transmitted by the local server and stores the supplementary historical data in the monitoring database.

[0084] Specifically, after receiving the supplementary data, the cloud server performs data parsing and verification to ensure that the reissued data is accurate and error-free, and then stores it in the monitoring database to complete the supplementation and improvement of the historical data.

[0085] Exemplarily, the receiving module of the cloud server is responsible for listening for the supplementary data transmission from the local server. After receiving the supplementary data, it uses a parsing algorithm that matches the data packaging to decode and restore the data packet, and verifies the integrity and accuracy of the data. If the data is correct, the cloud server inserts this supplementary historical data into the corresponding time period in the monitoring database, which may be achieved through the batch import function of the database or SQL insert statements. After the data supplementation is completed, the cloud server will run the integrity check again to ensure that all missing data has been supplemented and the historical data chain in the database is complete without omission.

[0086] Exemplarily, as Figure 5a shown, it is a schematic diagram of the interaction process between the local server and the cloud server. The server host of the local server collects monitoring data, transmits it to the local database, and packages it into a standard file for transmission to the cloud server. The transmission method can be selected from FTP, Socket, etc. The cloud server can also supplement historical data through the local server. Figure 5a The specific content in

[0087] In this embodiment, by regularly checking the integrity of the historical data by the cloud server and initiating a data supplementation request to the local server when data is found to be missing, the monitoring data management method proposed by the present invention effectively ensures the integrity and reliability of the historical data stored in the cloud. Specifically, the integrity check mechanism can timely detect data missing due to reasons such as network fluctuations and transmission errors. By requesting the local server to supplement the data, the gap in the cloud data can be quickly filled, avoiding monitoring decision-making mistakes or data analysis biases caused by incomplete data. The data supplementation process between the local server and the cloud server not only strengthens the redundant storage of data but also improves the self-repair ability of the data management system. When data is accidentally lost in the cloud, the local server can serve as the second source of data, quickly respond to the supplementation request of the cloud server, and provide the required historical data to ensure the continuity and stability of the data stream of the entire monitoring system. In addition, through the secondary transmission and storage of data, the system also enhances data security protection. Even if the cloud data is attacked or damaged, it can be restored through the local data, greatly improving the risk resistance ability of the monitoring system. In summary, the present invention constructs a self-improving data management process through the collaborative work of the cloud and the local server, provides an effective solution for the data security and reliability of the wind farm monitoring system, and at the same time optimizes the storage and use efficiency of the monitoring data.

[0088] In one embodiment, as Figure 6 shown, step S230, in response to the access request of the second object by the cloud server to display the monitoring data to the second object. It includes: steps S600 - S620:

[0089] Step S600: Receive an access request of a second object through a cloud server.

[0090] Specifically, the second object usually refers to users outside the wind farm, such as those in a remote monitoring center, decision-makers in the group headquarters, or partners. These users may need to view the real-time operation status or historical data of the wind farm for decision-making support, operation and maintenance guidance, or data analysis. This step ensures that the cloud server can receive access requests from the second object in a timely manner.

[0091] Exemplarily, the cloud server is deployed with a Web service interface that can listen for HTTP or HTTPS requests on a specific port. When the second object sends an access request through a Web browser or a specific application, the Web service interface of the cloud server will receive these requests. The requests may contain parameters such as user identity information, access permissions, the time period or specific metrics of the data required, and these parameters are used for subsequent data retrieval and permission verification.

[0092] Step S610: Invoke target monitoring data from a real-time database according to the access request of the second object.

[0093] Specifically, this step is the core part of data access. The cloud server retrieves and invokes target monitoring data from the real-time database according to the request content of the second object. The target monitoring data is a set of data that is most relevant to the current query requirements of the second object, which may be the latest segment of the real-time data stream or historical data records filtered according to specific conditions.

[0094] Exemplarily, the cloud server parses the parameters in the access request to generate a database query statement (such as an SQL statement). The query statement will be sent to the real-time database, and the database quickly retrieves the target monitoring data according to the query conditions. The retrieval process may involve the use of data indexes to improve query efficiency. In addition, the real-time database may also adopt a data caching technology to store frequently accessed data in memory, reducing disk access latency and further accelerating the data response speed. The retrieved data will be packaged into a format suitable for network transmission and prepared to be sent to the second object.

[0095] Step S620: Display the target monitoring data to the second object.

[0096] Specifically, this step is the final link of data display. The cloud server sends the invoked target monitoring data to the second object through the network and displays it to the user in an intuitive and easy-to-understand form, such as charts, dashboards, or data reports.

[0097] Exemplarily, the cloud server converts the target monitoring data into a Web page or API response format, such as HTML, JSON, or XML. The data may be embedded in dynamically generated charts, dashboards, or data reports to facilitate the second object's intuitive understanding of the operating status of the wind farm. In addition, the cloud server may also provide a data API, allowing the second object to directly obtain data through a programming interface, providing flexibility for data analysis and integration applications. The data transmission process may use the HTTPS protocol to ensure data security and privacy protection.

[0098] In this embodiment, by receiving the access request through the cloud server and performing permission verification, the security of data access is ensured, and unauthorized access is prevented. The efficient retrieval mechanism of the real-time database, combined with data caching and indexing technologies, significantly shortens the time for data query and invocation, improves the data response speed, enabling the second object to timely obtain the latest operating status of the wind farm. The diversification of data display, such as charts, dashboards, or data reports, and the provision of API interfaces meet the needs of different user groups for data intuitiveness and analysis depth, enhancing the convenience and accuracy of remote monitoring and decision-making. In addition, the data transmission using the HTTPS protocol protects the security of data during transmission and reduces the risk of data leakage. In summary, through the efficient data processing and secure data transmission of the cloud server, the present invention realizes the remote real-time monitoring and intelligent analysis of the wind farm monitoring data, providing strong technical support for the remote management and intelligent decision-making of wind power operation.

[0099] In one embodiment, as Figure 7 shown, in step S220, the local server responds to the interaction request of the first object installed with the preset client software to perform data interaction with the first object. It includes: steps S700 - S730:

[0100] Step S700, the local server receives the interaction request.

[0101] Specifically, the local server receives the interaction request from the first object. The first object is usually an operation and maintenance personnel or manager within the wind farm, who initiate requests through the preset client software installed on personal computers or mobile devices to obtain real-time data of the wind farm or perform equipment control.

[0102] Exemplarily, the local server listens on a specific network port, waiting to receive the interaction request. The request may be sent through HTTP, TCP, or other suitable network protocols, containing necessary parameters such as the request type (such as data request, control instruction), requester identification information (such as username, device ID), etc. The network service module of the local server receives these requests and records them in the request log for subsequent processing.

[0103] Step S710: Determine whether the object sending the interaction request has installed a preset client software.

[0104] Specifically, to ensure the security and controllability of data interaction, the local server needs to confirm whether the object sending the request is the expected client software. This is because only authorized client software can conduct legitimate data interaction with the local server, and unauthorized software or devices will be blocked.

[0105] Exemplarily, the local server checks the client identifier carried in the request message and compares it with the pre-stored list of authorized clients. The client identifier may include information such as the version number of the client software, digital signature, device fingerprint, etc. The local server identifies the legitimacy and type of the requesting software through these identifiers to determine whether it is preset as software that can conduct data interaction with the local server. If no matching item is found for the client identifier in the list, the local server will reject this request and may generate a warning record to notify the administrator of a potential illegal access attempt.

[0106] Step S720: When it is determined that the object sending the interaction request has installed the preset client software, perform permission verification on the object.

[0107] Among them, the object that has installed the preset client software is the first object.

[0108] Specifically, permission verification is a key link to ensure data security. The local server needs to confirm whether the first object has the permission to access specific data or perform specific operations. This is based on the principle of role-based access control (RBAC), and users with different roles have different data access permissions.

[0109] Exemplarily, if the legitimacy of the client software was confirmed in the previous step, the local server will verify its permissions based on the user account information. This process may include verification of the username and password, two-factor authentication, inspection of the access token, etc., to ensure that the identity of the requester is true and correct. Permission verification may be based on the user permission table stored in the local database, which defines the data types, data ranges, and operations that each user can access. If the permission verification fails, the local server will not allow data interaction and will return an error prompt indicating insufficient permissions.

[0110] Step S730: When the object permission verification is passed, perform data interaction with the object in response to the interaction request.

[0111] Specifically, once the local server confirms the software legitimacy and permissions of the requester, it will read, process, and transmit data according to the content of the interaction request, and conduct data interaction with the first object.

[0112] Exemplarily, after the permission verification is passed, the business processing module of the local server parses the specific content of the interaction request, such as a data query request, a device control instruction, etc. According to the request type, the local server retrieves the corresponding data from its local database, uses data processing algorithms to perform necessary processing and analysis on the data, and finally responds the processed data to the first object through the communication protocols preset in the client software, such as REST API, SOAP, etc., to achieve two-way data interaction. In the device control scenario, the local server forwards the control instruction to the relevant devices in the wind farm, such as the fan controller, to execute specific control actions, and feeds back the control result to the first object to ensure that it can remotely control the wind farm devices and improve the operation and maintenance efficiency.

[0113] In this embodiment, by accurately receiving, verifying, and responding to the interaction requests of the first object through the local server, the method proposed by the present invention ensures the security of the internal monitoring data of the wind farm and the strictness of access control. Specifically, the local server effectively prevents unauthorized access and malicious operations through strict client software legality and user permission verification, ensuring the security of the core data of the wind farm. At the same time, the permission verification mechanism allows personnel at different levels to access data as needed, improving the flexibility and pertinence of data use. After the permission verification is passed, the local server can quickly respond to data interaction requests, whether it is providing wind farm status data or executing device control commands, achieving efficient and accurate results, thereby improving the operation and maintenance efficiency and management level of the wind farm. In short, through a series of strict data interaction control processes, the present invention constructs a secure and reliable internal monitoring data access platform for the wind farm, providing strong technical support for the intelligent operation of the wind farm.

[0114] Through the collaborative work of the local server and the cloud server, the efficient collection, storage, and display of the monitoring data of the wind farm are realized. The local server is responsible for the preliminary processing and permission verification of the data, ensuring the security and accuracy of the data; the cloud server undertakes the tasks of in-depth analysis and display of the data, meeting the needs of remote monitoring. In addition, by storing the data separately in the real-time database and the monitoring database, the data access speed and data analysis efficiency are effectively improved, providing strong support for the operation and maintenance decision-making of the wind farm and significantly improving the operation and management efficiency of the wind farm.

[0115] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that makes a contribution to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of various embodiments of the present application.

[0116] In this embodiment, a data management device for a wind power plant is further provided. The data management device for the wind power plant is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0117] Figure 8 is a structural block diagram of an optional data management device for a wind power plant according to an embodiment of the present application. As Figure 8 shown, it includes:

[0118] A data collection module 801, configured to collect monitoring data collected by each sensor in the wind power plant through a local server.

[0119] A data transmission module 802, configured to transmit the monitoring data to a local database for storage through a local server, and transmit the monitoring data to a cloud server.

[0120] A data interaction module 803, configured to respond to an interaction request of a first object installed with preset client software through a local server to perform data interaction with the first object.

[0121] A data display module 804, configured to respond to an access request of a second object through a cloud server to display the monitoring data to the second object.

[0122] Through the above-mentioned device, through the collaborative work of the local server and the cloud server, the secure storage and remote backup of data are ensured, providing a solid data foundation for the normal operation of the wind power plant. At the same time, the use of the preset client software ensures that internal professionals can obtain timely and accurate wind power plant status information, while the access interface of the cloud server allows external users to access wind power plant data through the Internet, greatly expanding the application scope of the data and enhancing the flexibility and responsiveness of the system. This hybrid architecture not only improves the security and reliability of the data, but also significantly improves the data sharing efficiency, providing strong support for the remote monitoring, centralized management and intelligent decision-making of the wind power plant. Through dual storage on the local and cloud sides, this system also enhances the data recovery ability and redundancy, providing a strong guarantee for the continuous operation of the wind power plant. In summary, the method of this application constructs a secure and open wind power plant monitoring system, meeting the dual requirements of modern wind power operation for data security and sharing. It can not only efficiently collect and process various real-time monitoring data in the wind power plant, but also achieve a balance between internal secure data access and external convenient data sharing.

[0123] In an exemplary embodiment, the above-mentioned data transmission module 802 is further configured to: package the monitoring data into a standard file in a preset format. Determine the target transmission method in response to the real-time requirement of the first object for the monitoring data. Transmit the standard file to the cloud server by using the target transmission method.

[0124] In an exemplary embodiment, the above-mentioned device further includes:

[0125] A data parsing module, configured to parse the monitoring data through the cloud server and filter out the historical data and real-time data in the monitoring data.

[0126] A data forwarding module, configured to store the historical data and real-time data in the monitoring database and store the real-time data in the real-time database, where the real-time database is used to respond to the access request of the second object.

[0127] In an exemplary embodiment, the above-mentioned device further includes:

[0128] A data checking module, configured to check whether the historical data stored in the monitoring database is complete through the cloud server.

[0129] A data request module, configured to send a data supplement request to the local server when it is determined that there is missing historical data stored in the monitoring database.

[0130] A data providing module, configured to transmit the corresponding supplementary historical data to the cloud server through the local server in response to the data supplement request.

[0131] A data supplement module is used to receive supplementary historical data transmitted by a local server through a cloud server and supplement the supplementary historical data into a monitoring database.

[0132] In an exemplary embodiment, the above data display module 804 is further configured to: receive an access request of a second object through a cloud server. Invoke target monitoring data from a real-time database according to the access request of the second object. Display the target monitoring data to the second object.

[0133] In an exemplary embodiment, the above data interaction module 803 is further configured to: receive an interaction request through a local server. Determine whether the object sending the interaction request has installed a preset client software. In the case where it is determined that the object sending the interaction request has installed the preset client software, perform permission verification on the object, where the object installed with the preset client software is the first object. In the case where the object permission verification passes, perform data interaction with the object in response to the interaction request.

[0134] An embodiment of the present application further provides a storage medium, which includes a stored program, wherein the above program executes the method of any one of the above when running.

[0135] Optionally, in this embodiment, the above storage medium may be set to store program codes for executing the following steps:

[0136] S1, collect monitoring data collected by each sensor in a wind farm through a local server.

[0137] S2, transmit the monitoring data to a local database for storage through a local server and transmit the monitoring data to a cloud server.

[0138] S3, respond to an interaction request of a first object installed with a preset client software through a local server to perform data interaction with the first object.

[0139] S4, respond to an access request of a second object through a cloud server to display the monitoring data to the second object.

[0140] An embodiment of the present application further provides an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0141] Optionally, the above electronic device may further include a transmission device and an input / output device, where the transmission device is connected to the above processor, and the input / output device is connected to the above processor.

[0142] Optionally, in this embodiment, the above processor may be configured to execute the following steps through a computer program:

[0143] S1. Collect the monitoring data collected by each sensor in the wind farm through the local server.

[0144] S2. Transmit the monitoring data to the local database for storage through the local server, and transmit the monitoring data to the cloud server.

[0145] S3. Respond to the interaction request of the first object installed with the preset client software through the local server to perform data interaction with the first object.

[0146] S4. Respond to the access request of the second object through the cloud server to display the monitoring data to the second object.

[0147] Optionally, in this embodiment, the above storage medium may include but is not limited to: USB flash drive, read-only memory (ROM for short), random access memory (RAM for short), mobile hard disk, magnetic disk or optical disc, etc., various media that can store program codes.

[0148] The embodiment of the present application also provides a computer program product, including a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores the computer program product. When the computer program is executed by a processor, the steps of the methods in the various embodiments of the present application are implemented.

[0149] Optionally, in this embodiment, the above computer program may be set to implement the following steps when executed by a processor:

[0150] S1. Collect the monitoring data collected by each sensor in the wind farm through the local server.

[0151] S2. Transmit the monitoring data to the local database for storage through the local server, and transmit the monitoring data to the cloud server.

[0152] S3. Respond to the interaction request of the first object installed with the preset client software through the local server to perform data interaction with the first object.

[0153] S4. Respond to the access request of the second object through the cloud server to display the monitoring data to the second object.

[0154] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and will not be elaborated herein.

[0155] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present application can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a sequence different from that here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0156] The above are only the preferred embodiments of the present application and are not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data management method for a wind power plant, characterized in that, The data management system of the wind farm includes a local server and a cloud server, and the method includes: Collecting the monitoring data collected by each sensor in the wind farm through the local server; Transmitting the monitoring data to the local database for storage through the local server, and transmitting the monitoring data to the cloud server; Responding to the interaction request of the first object installed with the preset client software through the local server to perform data interaction with the first object; Responding to the access request of the second object through the cloud server to display the monitoring data to the second object.

2. The data management method for a wind power plant according to claim 1, characterized in that, The transmitting the monitoring data to the cloud server includes: Packing the monitoring data into a standard file in a preset format; Determining the target transmission method in response to the real-time requirement of the first object for the monitoring data; Transmitting the standard file to the cloud server by using the target transmission method.

3. The data management method of a wind power plant according to claim 1, wherein After transmitting the monitoring data to the cloud server, the method further includes: Parsing the monitoring data through the cloud server to screen out the historical data and real-time data in the monitoring data; Storing the historical data and the real-time data in a monitoring database, and storing the real-time data in a real-time database, where the real-time database is used to respond to the access request of the second object.

4. The data management method of the wind power plant according to claim 3, characterized in that After storing the historical data and the real-time data in the monitoring database and storing the real-time data in the real-time database, the method further includes: Checking whether the historical data stored in the monitoring database is complete through the cloud server; Sending a data supplement request to the local server when it is determined that the historical data stored in the monitoring database is missing; Responding to the data supplement request through the local server and transmitting the corresponding supplementary historical data to the cloud server; Receiving the supplementary historical data transmitted by the local server through the cloud server and storing the supplementary historical data in the monitoring database.

5. The data management method for a wind power plant according to claim 4, characterized in that The displaying the monitoring data to the second object by responding to the access request of the second object through the cloud server includes: Receiving the access request of the second object through the cloud server; Invoking the target monitoring data from the real-time database according to the access request of the second object; Displaying the target monitoring data to the second object.

6. The data management method of a wind power plant according to any one of claims 1-5, characterized in that, The performing data interaction with the first object by responding to the interaction request of the first object installed with the preset client software through the local server includes: Receiving the interaction request through the local server; Determining whether the object sending the interaction request is installed with the preset client software; Performing permission verification on the object when it is determined that the object sending the interaction request is installed with the preset client software, where the object installed with the preset client software is the first object; Performing data interaction with the object in response to the interaction request when the object permission verification passes.

7. A data management device for a wind power plant, characterized in that, The device includes: A data collection module, configured to collect monitoring data collected by various sensors in a wind farm through a local server; A data transmission module, configured to transmit the monitoring data to a local database for storage and transmit the monitoring data to the cloud server through the local server; A data interaction module, configured to, through the local server, respond to an interaction request of a first object installed with preset client software to perform data interaction with the first object; A data display module, configured to, through the cloud server, respond to an access request of a second object to display the monitoring data to the second object.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein the program, when running, executes the method according to any one of claims 1 to 6.

9. An electronic device, comprising a memory and a processor, characterized in that, A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

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