CN110657064B

CN110657064B - Wind power plant cluster control system, method, control device and storage medium

Info

Publication number: CN110657064B
Application number: CN201810688526.1A
Authority: CN
Inventors: 平立发; 黄晓芳; 韩则胤
Original assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Current assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Priority date: 2018-06-28
Filing date: 2018-06-28
Publication date: 2020-06-30
Anticipated expiration: 2038-06-28
Also published as: CN110657064A

Abstract

The embodiment of the application provides a wind power plant cluster control system, a method, control equipment and a storage medium, wherein the system comprises: the real-time subsystem is used for communicating with equipment in the wind power plant through a first communication network, acquiring real-time data in the wind power plant, generating corresponding first equipment control information according to the real-time data, and sending the control information to corresponding control equipment through the first communication network; the non-real-time subsystem is used for communicating with equipment in the wind power plant through a second communication network to obtain non-real-time data in the wind power plant, generating corresponding second equipment control information according to the non-real-time data, sending the control information to corresponding control equipment through the second communication network, storing the real-time data and the non-real-time data to a local database, and sending the real-time data and the non-real-time data to a cloud database of the cloud subsystem for storage. According to the scheme of the embodiment of the invention, the data interaction effect in the wind power plant can be effectively improved, and the control requirement of equipment is met.

Description

Wind power plant cluster control system, method, control device and storage medium

Technical Field

The invention relates to the technical field of wind power plant control, in particular to a wind power plant cluster control system, a wind power plant cluster control method, a wind power plant cluster control device and a storage medium.

Background

With the gradual deepening of the intelligent interconnection technology in the industrial field and the continuous enhancement of big data intelligent learning and cloud computing processing capacity, the technical research of wind power plant level control gradually becomes a new mainstream, and a plurality of mature technical achievements appear. Currently, each mainstream wind power plant actively performs research on wind power plant level Control modes at different levels, and gradually introduces plant level Control products oriented to different application objects, such as WindBoost introduced by GE, PowerPLUS of Vestas for improving the power of the whole plant, Control under a Storm condition realized by Storm Control of Enercon, and the like.

In the prior art, a bus communication mode is mostly adopted in a wind power plant control system at the present stage, and is limited by a bus communication standard bottleneck, so that a use scene with multiple slave stations and large data volume is difficult to support, a multi-controller distributed control mode has to be adopted, and the equipment complexity and the economic cost are increased. In addition, due to the bus communication mode, all data of the wind power plant are mixed on one network, so that the problems of network blockage, frequent data packet loss and the like are often caused, the data interaction effect of the wind power plant is not ideal, and the control effect of equipment in the wind power plant is influenced.

In addition, at present, wind farm control is usually developed only for a certain function or around a specific application scene, and the device has poor expandability, poor operation capability and low user experience satisfaction. A wind power plant control system which is oriented to various application requirements, high in reliability and strong in performance is urgently needed in the market.

Disclosure of Invention

The purpose of the embodiment of the present application is to at least solve one of the above technical defects, especially the problem that the data interaction effect in the existing wind farm control system is not ideal. The technical scheme adopted by the embodiment of the application is as follows:

in a first aspect, an embodiment of the present application provides a wind farm cluster control system, where the system includes a non-real-time subsystem, and a real-time subsystem and a cloud-end subsystem which are respectively in communication connection with the non-real-time subsystem;

the real-time subsystem is used for communicating with equipment in the wind power plant through a first communication network according to the first configuration information to acquire real-time data in the wind power plant, generating corresponding first equipment control information according to the real-time data, sending the first equipment control information to corresponding control equipment in the wind power plant through the first communication network, and sending the real-time data to the non-real-time subsystem;

the non-real-time subsystem is used for communicating with equipment in the wind power plant through a second communication network according to second configuration information to acquire non-real-time data in the wind power plant, generating corresponding second equipment control information according to the non-real-time data, sending the second equipment control information to corresponding control equipment in the wind power plant through the second communication network, receiving real-time data sent by the real-time subsystem, storing the real-time data and the non-real-time data into a local database, and sending the real-time data and the non-real-time data to the cloud subsystem;

the cloud subsystem is used for receiving the real-time data and the non-real-time data sent by the non-real-time subsystem and storing the real-time data and the non-real-time data into a cloud database;

the data transmission rate of the first communication network is greater than the data transmission rate of the second communication network.

In a second aspect, an embodiment of the present application provides a wind farm cluster control method, where the method includes:

according to the first configuration information, the real-time data in the wind power plant are obtained through communication between the first communication network and equipment in the wind power plant, corresponding first equipment control information is generated according to the real-time data, and the first equipment control information is sent to corresponding control equipment in the wind power plant through the first communication network;

according to the second configuration information, communicating with equipment in the wind power plant through a second communication network to obtain non-real-time data in the wind power plant, generating corresponding second equipment control information according to the non-real-time data, and sending the second equipment control information to corresponding control equipment in the wind power plant through the second communication network; the data transmission rate of the first communication network is greater than that of the second communication network;

storing the real-time data and the non-real-time data in a local database;

and storing the real-time data and the non-real-time data into a cloud database.

In a third aspect, an embodiment of the present application provides a wind farm cluster control device, including a memory and a processor;

the memory has stored therein computer program instructions;

the processor is configured to read the computer program instructions to execute the wind farm cluster control method shown in the second aspect of the embodiment of the present application.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where computer program instructions are stored in the storage medium, and when the computer program instructions are executed by a processor, the processor implements the wind farm cluster control method shown in the second aspect of the embodiment of the present application.

The technical scheme provided by the embodiment of the application has the following beneficial effects: the wind power plant cluster control system, the method, the control device and the storage medium of the embodiment of the application are provided with the real-time subsystem, the non-real-time subsystem and the non-real-time subsystem at the same time, a wind power plant communication networking mode simultaneously comprising the first communication network and the second communication network is adopted, real-time data and non-real-time data are separately transmitted, real-time data acquisition and rapid transmission of control information of the first device based on the real-time data are guaranteed through the real-time subsystem, millisecond-level high-speed data interaction with a wind generating set is achieved, and the phenomena of network congestion or frequent data packet loss and the like caused by mixing of all data on one network channel in the prior art are changed. In the time domain, the processing of real-time data and the processing of non-real-time data are respectively realized in a real-time subsystem and a non-real-time subsystem, and the memory pressure of a control system is released to the maximum extent on the premise of ensuring the stability of control output. In addition, the non-real-time subsystem provides database support for the real-time subsystem, the high-efficiency data processing and high-efficiency data interaction capacity of the real-time subsystem is better guaranteed, backup storage of real-time data and non-real-time data is achieved through the configuration of the cloud subsystem, and the reliability of data storage and management of the wind power plant is further improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.

FIG. 1 illustrates a schematic structural diagram of a wind farm cluster control system provided in an embodiment of the present application;

FIG. 2 is a schematic structural diagram of a wind farm cluster control system provided in another embodiment of the present application;

FIG. 3 is a schematic structural diagram of a wind farm cluster control system provided in another embodiment of the present application;

FIG. 4 is a schematic structural diagram illustrating a wind farm cluster control system provided in yet another embodiment of the present application;

FIG. 5 illustrates a schematic diagram of a real-time subsystem provided in an embodiment of the present application;

FIG. 6 is a schematic structural diagram of a wind farm cluster control system provided in another embodiment of the present application;

FIG. 7 illustrates a schematic structural diagram of a non-real-time subsystem provided in an embodiment of the present application;

FIG. 8 is a schematic structural diagram illustrating a wind farm cluster control system provided in an embodiment of the present application;

fig. 9 shows a data transmission link schematic diagram of a wind turbine generator set provided in a specific embodiment of the present application;

FIG. 10 shows a schematic structural diagram of a wind farm cluster control device provided in an embodiment of the present application;

the meaning of the various reference symbols of the embodiments of the invention is explained below:

1000-cluster control system;

100-a real-time subsystem; 110-a real-time decision module;

111-decision scheduling unit; 112-decision boundary control unit;

200-a non-real time subsystem; 210-a local database; 220-non-real-time decision module;

230-a decision evaluation module; 240-human-computer interaction module; 250-a log module;

221-decision agent forwarding unit;

300-a cloud subsystem; 310-cloud database; 320-cloud decision module;

400-safety isolation subsystem.

Detailed Description

Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

The terms referred to in this application will first be introduced and explained:

real-time subsystem (RT): the hardware carrier of the control method refers to a control mode of a communication period within a second level, and the hardware carrier can be a Programmable Logic Controller (PLC), a control card, a Controller using a control chip as a center, and the like.

Non-real time subsystem (Non-real System, NRT): the control mode of the communication period of more than second level is generally referred, the hardware carrier can be a server, an industrial personal computer and the like, and the operating system can be DOS, OS/2, UNIX, LINUX, Windows, VxWords, Netware and the like.

Cloud Computing System (CCT): the universal remote control system can be an enterprise self-built cloud platform, and can also be commercial cloud platforms such as an Array cloud, an Amazon cloud and a Baidu cloud.

Decider (Decision Module, DM): refers to a separate software program or hardware with modular functions developed to implement a certain event of the wind farm cluster control system. The decision maker can execute independent execution logic operation, and make corresponding decision or generate corresponding control information according to a data processing strategy pre-configured in the decision maker.

In order to uniformly control a plurality of wind generating sets in a wind farm, a wind farm control system needs to be configured in the wind farm. Currently, wind farm control is usually developed only for a certain function or around a specific application scenario, and the device expandability is poor. At present, the communication mode of the wind power plant control system mostly adopts a bus communication standard, and is limited by the standard bottleneck of the bus communication mode, so that the control system is difficult to support the use scene of the wind power plant with a plurality of slave stations and large data volume, a multi-controller distributed control mode has to be adopted, and the equipment complexity and the economic cost are increased. Due to the limitation of the quality of the wind power plant communication network, the bus communication mode also has inevitable influence on the acquisition of data in the wind power plant and the issuing of control instructions,

the wind power plant cluster control system and method provided by the application aim to solve the technical problems in the prior art.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 1 shows a schematic structural diagram of a wind farm cluster control system provided in an embodiment of the present application. As shown in fig. 1, the cluster control system 1000 may include a real-time subsystem 100, a non-real-time subsystem 200, and a cloud-end subsystem 300, where the real-time subsystem 100 and the cloud-end subsystem 300 are respectively connected to the real-time subsystem 200 in a communication manner.

The real-time subsystem 100 is configured to communicate with a device in the wind farm through a first communication network according to the first configuration information, acquire real-time data in the wind farm, generate corresponding first device control information according to the real-time data, send the first device control information to a corresponding control device in the wind farm through the first communication network, and send the real-time data to the non-real-time subsystem 200.

The non-real-time subsystem 200 is configured to communicate with a device in the wind farm through a second communication network according to the second configuration information, acquire non-real-time data in the wind farm, generate corresponding second device control information according to the non-real-time data, send the second device control information to a corresponding control device in the wind farm through the second communication network, receive real-time data sent by the real-time subsystem, store the real-time data and the non-real-time data in the local database 210, and send the real-time data and the non-real-time data to the cloud subsystem 300; the data transmission rate of the first communication network is greater than that of the second communication network;

the cloud subsystem 300 is configured to receive the real-time data and the non-real-time data sent by the non-real-time subsystem 200, and store the real-time data and the non-real-time data in the cloud database 310.

In the embodiment of the application, a first communication network and a second communication network are relative, the first communication network refers to a communication network with a real-time communication function, and generally refers to a communication network with a communication period not greater than a set time; the second communication network is a non-real-time communication network, and generally refers to a communication network with a communication period longer than a set time. The set time is usually in the unit of second level, that is, a communication network with a communication period within the second level can be regarded as a real-time communication network, and a communication network with a communication period above the second level can be regarded as a non-real-time communication network.

In practical application, the first communication network and the second communication network may be two physically separated parallel networks, or may open up a dedicated network bandwidth for real-time data under the condition of sharing one communication network by a technical means, or separate real-time data transmission from ordinary data transmission by using a special communication mode. The data transmission mode may be a wired transmission mode such as a conventional cable and an optical fiber, or a wireless transmission mode such as radio and quantum.

In the embodiment of the present application, the real-time data refers to data with a sampling frequency not less than a set frequency, and correspondingly, the non-real-time data refers to data with a sampling frequency greater than the set frequency. In practical application, according to the actual control requirement of the wind power plant, which real-time data are required to be acquired and which non-real-time data are configured in the wind power plant through the first configuration information and the second configuration information. For a wind farm, real-time data generally refers to data which has a large influence on the operation of a wind turbine generator and has a high requirement on the timeliness, for example, information such as wind speed of the wind turbine generator, temperature of the wind turbine generator, wind direction and the like. Real-time data and non-real-time data in the wind farm can be obtained by setting sampling points in the wind farm.

The Wind power plant cluster control system is a Wind Farm level control system (WFC), and comprises a real-time subsystem, a non-real-time subsystem and a cloud subsystem, a Wind power plant communication networking mode comprising a first communication network and a second communication network is adopted, real-time data and non-real-time data are separately transmitted, the real-time subsystem ensures real-time data acquisition and rapid transmission of first equipment control information based on the real-time data, millisecond-level high-speed data interaction with a Wind generating set is realized, acquisition and processing of the non-real-time data are realized through the non-real-time subsystem, and comprehensiveness of the non-real-time data information can be ensured.

According to the cluster control system, real-time data can be rapidly transmitted by using the first communication network and is not mixed with common non-real-time data to be transmitted, so that network resources are reasonably distributed, and the phenomena of network congestion, transmission flash or frequent data packet loss and the like caused by the fact that all data are mixed on one network channel in the prior art are changed. In the time domain, a high-speed operation task (processing of real-time data) and a common operation task (processing of non-real-time data) are respectively realized in a real-time subsystem and a non-real-time subsystem, and the memory pressure of a control system is released to the maximum extent on the premise of ensuring the stability of control output.

In addition, in order to better ensure the processing capacity of the real-time subsystem 100 on real-time data and ensure the data interaction efficiency of the real-time subsystem 100 and the wind generating set, the real-time subsystem 100 may not be configured with a database, the local database 210 of the non-real-time subsystem 200 provides a database support for the real-time subsystem 100, the real-time subsystem 100 only needs to store a small amount of necessary real-time data in a memory, and a large amount of real-time data and non-real-time data are stored in the non-real-time subsystem 200 with low real-time requirement, so that the real-time subsystem 100 better meets the requirements of fast data acquisition and equipment control of the wind farm. It can be seen that the non-real-time subsystem 200 provides database support for the real-time subsystem 100, and the real-time subsystem 100 fills a blank that the non-real-time subsystem 200 cannot exchange high-speed data with a plurality of wind generating sets and quickly control the wind generating sets.

Through the cloud subsystem 300, the real-time data and the non-real-time data stored in the local database 210 of the non-real-time subsystem 200 can be stored in the cloud database for backup, so that the reliability of data storage of the wind power plant is further improved. In addition, by providing the cloud subsystem 300, data stored in the local database 210 for a time exceeding a set time period can be periodically cleaned, so that the storage pressure of the local database 210 is reduced, and the non-real-time subsystem 200 is optimized.

In the embodiment of the application, the control equipment in the wind power plant comprises a wind generating set controller and wind power plant level control equipment; the devices in the wind farm include control devices in the wind farm, and wind farm level sensing detection devices.

For a single Wind Turbine Generator (WTG), a Wind Turbine Generator controller is a control core of the single WTG, a Wind farm level control device containing a WTG main control system is a device for controlling the whole Wind farm including a plurality of WTGs in the Wind farm, and the Wind farm level control device is used for realizing the overall control of the Wind farm. The wind power plant field level sensing detection device is used for integrally detecting the environment and the like of a plurality of WTGs and/or a wind power plant in the wind power plant.

In an actual wind farm, a Condition monitoring System (CMS System) including various wind generating set sensing and detecting devices may be further provided in the wind generating set controller to collect more comprehensive Condition information of the wind generating set. Correspondingly, the equipment in the wind power plant can also comprise sensing detection equipment of each wind generating set.

The real-time subsystem 100 and the non-real-time subsystem 200 can communicate with the wind generating set controllers of the WTGs through a first communication network and a second communication network respectively to acquire real-time data and non-real-time data of the WTGs in the wind power plant, and communicate with the wind power plant field level control device and the wind power plant field level sensing detection device to acquire field level real-time data and field level non-real-time data of the wind power plant.

It should be noted that, in order to meet two data interaction requirements of real-time and non-real-time timeliness, the cluster control system according to the embodiment of the present application needs to change the traditional single-line wind farm communication network into a real-time communication network and a non-real-time communication network, that is, the wind farm data transmission network needs to have both real-time communication and non-real-time communication functions.

In the embodiment of the present application, the real-time subsystem 100 and the non-real-time subsystem 200 may be communicatively connected through a third communication network. The non-real-time subsystem 200 and the cloud subsystem 300 may be in communication connection through a fourth communication network; the data transmission rate of the first communication network is greater than that of the third communication network, and the data transmission rate of the first communication network is greater than that of the fourth communication network.

It should be noted that, since the timeliness requirement of the process of sending the real-time data to the non-real-time subsystem 200 for storage in the local database 210 and sending the real-time data and the non-real-time data to the cloud subsystem 300 for storage in the cloud database 310 is not high, the third communication network and the fourth communication network generally use a non-real-time communication network. It is to be understood that the third communication network and the fourth communication network may be the same communication network as the second communication network or different communication networks.

In this embodiment, the cloud subsystem 300 may be further configured to process data in the cloud database 310 according to the configured data processing policy, and send a processing result to the non-real-time subsystem 200;

the non-real-time subsystem 200 may be further configured to receive the processing result, and adjust or generate a wind farm control strategy based on the processing result.

The non-real-time subsystem 200 is limited by the server storage space and the memory thereof, and cannot perform analysis operation based on a large amount of data, the cloud subsystem 300 can bear the task based on a pre-configured data processing strategy and a large amount of data stored in the cloud database 310, and can return the operation result to the non-real-time subsystem 200, and the non-real-time subsystem 200 adjusts or generates a wind farm control strategy based on the processing result, and pushes the processing result to the wind turbine generator set for application.

In practical application, the cloud subsystem 300 can execute a complex decision algorithm, and can embed a distributed data mining module, a data combing module and the like according to requirements to complete analysis and operation of a large amount of data.

In the cluster control system of the embodiment of the application, in space, the local database 210 and the cloud database 310 are mutually matched, and the cloud server of the cloud subsystem 300 is used for specially performing analysis and calculation of a large amount of data, so that the performance of the local server of the non-real-time subsystem 200 can be optimal. The cloud subsystem 300 is typically deployed in a remote centralized control center, and is accessed to the wind farm through a dedicated network to perform data interaction with the non-real-time subsystem 200.

In this embodiment, the cluster control system 1000 may further include a security isolation subsystem 400, as shown in fig. 2.

The security isolation subsystem 400 is configured to implement bidirectional isolation of data interaction between the non-real-time subsystem 200 and the cloud subsystem 300.

By configuring the security isolation subsystem 400, the security of bidirectional data interaction between the non-real-time subsystem 200 and the cloud subsystem 300 is improved, and the security and stability of the control system are ensured. In addition, data of bidirectional interaction between the non-real-time subsystem 200 and the cloud subsystem 300 may also be encrypted according to a predetermined manner, so as to further improve the security of data transmission, and the encryption of the data may be completed by the security isolation subsystem 400 or by the sender of the data.

It is understood that the specific implementation form of the security isolation subsystem 400 can be configured according to actual needs, and can be implemented by a proxy server, for example. In addition, a wind farm global monitoring system can be arranged on the cloud subsystem 300, so that data of a plurality of wind farms can be summarized and monitored.

In the embodiment of the present application, the real-time subsystem 100 may specifically include the real-time decision module 110, the non-real-time subsystem 200 may specifically include the non-real-time decision module 220, and the cloud-side subsystem 300 may specifically include the cloud-side decision module 320, as shown in fig. 3. Wherein:

the real-time decision module 110 is configured to invoke a corresponding first decision device in a preconfigured first decision device set according to the real-time data, and generate first device control information according to the real-time data by the corresponding first decision device, where the first decision device set includes at least one first decision device.

The non-real-time decision module 220 is configured to invoke a corresponding second decision device in a preconfigured second decision device set according to the non-real-time data, and generate second device control information by the corresponding second decision device according to the non-real-time data, where the second decision device set includes at least one second decision device.

The cloud decision module 320 is configured to invoke a third decision device in a preconfigured third decision device set, generate a corresponding decision by the third decision device based on data in the cloud database 310, and send the decision to the non-real-time subsystem 200, where the third decision device set includes at least one third decision device;

the non-real-time subsystem 200 is further configured to receive a decision, and control the wind farm based on the decision.

The decision device comprises a first decision device set, a second decision device set and a third decision device set, wherein at least one decision device is configured in each of the first decision device set, the second decision device set and the third decision device set, at least one wind power plant control strategy is configured in one decision device, and the decision device generates corresponding decisions through the configured wind power plant control strategies. The decision makers in the first decision maker set are configured with control strategies related to real-time control of the wind power plant, the decision makers in the second decision maker set are configured with control strategies related to non-real-time control of the wind power plant, and the decision makers in the third decision maker set are configured with control strategies related to data existing in the cloud database 310.

For example, the decision device of the first decision device set may be configured with an output power increasing policy or an output power decreasing policy of the wind generating set, after the real-time subsystem 100 acquires real-time data related to the output power of the wind generating set, the real-time decision module 110 may call the decision device configured with the output power increasing policy or the decision device configured with the output power decreasing policy according to the acquired real-time data, and the called decision device generates a decision for controlling the output power of the wind generating set based on the real-time data, that is, generates first device control information for controlling the output power of the wind generating set, and issues the control information to the corresponding wind generating set at a high speed through the first communication network, so as to achieve fast control of the output power of the wind generating set.

In this embodiment, the non-real-time decision module 220 may be further configured to configure and manage the first decision maker set, the second decision maker set, and the third decision maker set.

The non-real-time subsystem 200 is a management center of the whole wind farm cluster control system in the embodiment of the present application, and the non-real-time decision module 220 may be configured with a decision manager 221 to be responsible for installation, operation, data interaction, resource allocation and other operations of all decision devices in the decision device sets in the real-time subsystem 100, the non-real-time subsystem 200 and the cloud-side subsystem 300, in addition to the configuration of the second decision device set.

In this embodiment of the application, the non-real-time decision module 220 may further include a decision agent forwarding unit 221, and the real-time decision module 110 may include a decision scheduling unit 111, as shown in fig. 4.

The decision agent forwarding unit 221 is configured to send the second device control information and the decision to the real-time decision module 110 before sending the second device control information to the corresponding control device in the wind farm and before controlling the wind farm based on the decision, and is configured to receive scheduling information of the second device control information and scheduling information of the decision sent by the real-time decision module 110;

a decision scheduling unit 111, configured to receive second device control information and a decision, determine scheduling information of the first device control information, scheduling information of the second device control information, and scheduling information of the decision according to a preconfigured decision scheduling policy, and send the scheduling information of the second device control information and the scheduling information of the decision to the non-real-time decision module 220;

the real-time subsystem 100 is specifically configured to control execution of the first device control information according to scheduling information of the first device control information;

the non-real-time subsystem 200 is specifically configured to control execution of the second device control information and the decision according to scheduling information of the second device control information and scheduling information of the decision.

The decision scheduling policy may include, but is not limited to, a priority management policy of a decider, a conflict control policy between deciders, and the like. The decision scheduling unit 111 performs scheduling control on the decision makers in the decision maker set in the three subsystems based on the pre-configured decision scheduling policy. For example, the real-time decision module 110 calls a decision maker configured with an output power increasing strategy and a decision maker configured with an output power decreasing strategy of the wind generating set at the same time, and because the two decision makers conflict with each other, the decision scheduling unit 111 generates scheduling information executed by the first device control information of the decision maker with a higher priority according to the priorities of the two decision makers, and generates scheduling information not executed by the first device control information of the decision maker with a lower priority.

The decision agent forwarding unit 221 of the non-real-time decision module 220 is configured to summarize decision results of the decision makers in all the non-real-time subsystems 200 and the decision maker in the cloud subsystem 300, forward the decision results to the decision scheduling unit 111 of the real-time subsystem 100, and receive decision result scheduling information generated by the decision scheduling unit 111 according to the decision scheduling policy. The real-time subsystem 100 and the non-real-time subsystem 200 respectively control the execution of the decision result of their respective decision makers according to the scheduling information of the decision scheduling unit 111. The scheduling information mainly refers to information such as whether conflicts exist among decision results of different decision makers, whether each decision result is executed, and execution sequence.

The above-mentioned controlling the execution of the first device control information/the second device control information according to the scheduling information of the first device control information/the scheduling information of the second device control information means determining whether to transmit the corresponding control information to the corresponding control device and when to transmit the corresponding control information according to the corresponding scheduling information. The execution of the decision is controlled according to the scheduling information of the decision, that is, the non-real-time subsystem determines whether to use the decision according to the scheduling information, that is, whether to control the wind power plant based on the information.

In the embodiment of the present application, the real-time decision module 110 may further include a decision boundary control unit 112, as shown in fig. 5.

And a decision boundary control unit 112, configured to control the first device control information, the second device control information, and the decision control data to be within a preset valid data range.

The decision boundary control unit 112 is configured to limit the output result of the decision maker within a reasonable effective data range, and prevent a control instruction error caused by a decision making process error, wherein some parameters in the decision boundary control unit 112 may be configured according to a specific functional requirement of the decision maker. For example, for a decision maker configured with a wind turbine generator system output power regulation strategy, the decision boundary control unit 112 controls the value of the output power of the decision maker to be within a valid data range of a preset value, and does not adjust the value of the output power of the decision maker when the value of the output power of the decision maker is within a preconfigured valid data range, and adjusts the value of the output power of the decision maker to be within a valid data range if the value of the output power of the decision maker is not within the preconfigured valid data range.

In the embodiment of the application, the decision scheduling unit 111 and the decision boundary control unit 112 are arranged in the real-time subsystem 100 with a high requirement on data processing timeliness, so that the scheduling efficiency of decision results of each decision maker can be effectively improved, and the timeliness requirement on equipment control in a wind power plant can be better met.

In the embodiment of the present application, the non-real-time decision module 220 may further include, but is not limited to, a decision set presentation unit and/or a decision authorization control unit according to actual requirements. The decision set display unit can be used for the query and display of all decision makers in the decision maker set in the real-time subsystem 100, the non-real-time subsystem 200 and the cloud subsystem 300; the decision authorization control unit is used for authorization management of the decision makers in the decision maker set of the three subsystems, that is, which decision makers are available, which decision makers are disabled, and the like can be controlled by the unit.

In this embodiment, the real-time decision module 110 may further include a real-time system management unit, and/or a fault diagnosis and log recording unit. The real-time system management unit may be configured to manage the real-time subsystem 100, for example, setting the first configuration information, managing real-time data, and the like; the fault diagnosis and logging unit may be configured to perform real-time fault diagnosis based on real-time data acquired by the real-time subsystem according to a preconfigured fault diagnosis policy, and to log an operation log of the real-time subsystem 100.

In the embodiment of the present application, the non-real-time subsystem 200 may further include a decision evaluation module 230, as shown in fig. 6.

The decision evaluation module 230 may be configured to count operation data of the decision makers in the first decision maker set, the second decision maker set, and the third decision maker set, and/or evaluate execution effects of the decision makers in the first decision maker set, the second decision maker set, and the third decision maker set.

The decision evaluation module 230 may perform operation data statistics and execution effect evaluation on the operation effects of all the decision makers in the three subsystems, so as to be able to know the operation effect of each decision maker in the cluster control system in time. For example, for a decision maker configuring the output power boost strategy of the wind generating set, it can know how much the strategy can boost the output power of the wind generating set within a certain time through the result of performing effect evaluation on the decision maker. The evaluation of the execution effect of the decision maker can be completed by configuring a corresponding evaluation strategy according to actual needs.

In the embodiment of the present application, the non-real-time subsystem 200 may further include a human-computer interaction module 240 and/or a log module 250, as shown in fig. 7. Wherein:

a human-computer interaction module 240, configured to provide a human-computer interaction interface for a user, so that the user can view an operation state of each part in the control system, and/or perform function setting on the control system, and/or export data in the control system;

and a log module 250 for recording operation information (operation state, operation result, etc.) of each part in the control system and operation information of the control system by the user.

The human-computer interaction module 240 can provide a friendly human-computer interaction interface, so that a user can conveniently observe the running state of the whole wind power plant control system, and perform operations such as function setting, data export and the like. The log module 250 can record information such as system running state, decision maker execution state, management operation, etc.

It can be understood that, in order to implement data storage and data forwarding, the non-real-time subsystem 200 according to the embodiment of the present application further includes a data service module responsible for data acquisition of the wind farm, data storage in the local database, and data interaction with the real-time subsystem 100 and the cloud-end subsystem 300.

The wind power plant cluster control system in the embodiment of the application can be provided with a real-time subsystem 100, a non-real-time subsystem 200 and a cloud subsystem 300 at the same time, and the three subsystems are mutually independent and complementary. The real-time subsystem 100 can carry a millisecond field level control algorithm and mainly aims at high-speed operation processing tasks; the non-real-time subsystem 200 can support common operation tasks and can also receive the work of human-computer interaction management, log recording, data acquisition, uploading service and the like; the cloud subsystem 300 can be configured as required to perform tasks such as big data analysis and machine intelligent learning operation. In the time domain, a high-speed operation task and a common operation task are respectively realized in the two subsystems, and the memory pressure of a control system is released to the maximum extent on the premise of ensuring the stability of control output; in space, the local database and the cloud database are matched with each other, and the cloud server of the cloud subsystem specially executes analysis and calculation of a large amount of data, so that the performance of the local server of the non-real-time subsystem is optimal.

The wind power plant cluster control system can provide complete field-level operation platform support, and thoroughly changes the idea that the existing set of control system can only realize a single function. Based on the cluster control system of the embodiment of the application, research and development personnel can select an optimal subsystem platform or a plurality of subsystem platforms in the cluster control system to jointly develop according to factors such as control targets, control timeliness and operation data amount. Each subsystem platform provides a function template with complete functions, and developers only need to perform secondary development of a decision algorithm (decision maker) on the basis of the function template, so that development difficulty and risk are reduced, and economic cost is reduced.

In order to explain the wind farm cluster control system provided by the present application in more detail, the control system is further described below with reference to a specific embodiment.

Fig. 8 shows a schematic structural diagram of a wind farm cluster control system provided in this embodiment, as shown in the drawing, a wind farm in this embodiment includes n wind turbine generators (WTG _1, WTG _2, …/WTG _ n shown in the drawing), and the cluster control system includes a real-time subsystem, a non-real-time subsystem, a cloud-side subsystem, and a security isolation subsystem.

The following describes four parts of the cluster control system according to the present embodiment.

A real-time subsystem: the system comprises a real-time decision module, wherein the real-time decision module comprises a first decision maker set (shown in the figure), a decision scheduling unit, a decision boundary control unit, a real-time system management unit and a fault diagnosis and log recording unit.

A non-real-time subsystem: the system comprises a non-real-time decision module, a decision evaluation module, a man-machine interaction module, a log module, a data service module and a local database. Wherein the non-real-time decision module comprises a decision manager and a second set of decision makers (the non-real-time decision maker set shown in the figure). The decision manager comprises a decision set display unit, a decision authorization control unit and a decision agent forwarding unit, the data service module comprises an asynchronous data acquisition unit, a data encryption processing unit and a data forwarding unit, the asynchronous data acquisition unit is used for acquiring non-real-time data, the data encryption processing unit is used for encrypting and decrypting the data, and the decision manager specifically comprises the steps of encrypting the data to be sent to the cloud subsystem and decrypting the data received from the cloud subsystem; the data forwarding unit is used for data transmission between the non-real-time subsystem and the cloud subsystem.

Cloud subsystem: the system comprises a cloud data management module, a cloud decision module, a cloud database and a global monitoring system. The cloud data management module is used for carrying out data interaction with the non-real-time subsystem, storing the received data into a cloud database, and managing the data in the cloud database. The cloud decision module comprises a distributed data mining unit, a data combing unit and a third decision maker set (the cloud decision maker set shown in the figure).

In this embodiment, the first communication network is a communication network based on a real-time communication protocol stack (referred to as a real-time communication network for short) shown in the figure, and the communication networks between the subsystems except the first communication network and the communication networks between the subsystems and the devices in the wind farm all use the communication network based on the standard communication protocol stack (specifically, which standard communication protocol stack can be selected as required) (referred to as a non-real-time communication network for short) shown in the figure.

As shown in fig. 8, n wind turbine generators, field level control devices, and field level sensing detection devices in the wind farm are respectively connected to the wind farm network core switch through a real-time communication network and a non-real-time communication network, the real-time subsystem is connected to the wind farm network core switch through the real-time communication network to implement real-time communication with the above devices in the wind farm, thereby implementing fast acquisition of real-time data in the wind farm and efficient distribution of device control information generated based on the real-time data, the non-real-time subsystem is connected to the wind farm network core switch through the non-real-time communication network to implement non-real-time communication with the above devices, thereby implementing comprehensive acquisition of non-real-time data in the wind farm and distribution of device control information formed based on the non-real-time.

The non-real-time subsystem and the cloud subsystem realize bidirectional safety data interaction through the proxy server, the cloud subsystem realizes backup of real-time data and non-real-time data in the wind power plant, a large amount of data stored in the cloud database can be processed based on a configured data processing strategy, and a wind power plant control strategy is provided for the non-real-time subsystem. The cloud subsystem of this embodiment can carry out data mining and combing to the data in the cloud database through distributed data mining module and data combing module to can feed back mining and combing result to the non-real-time subsystem through the cloud data management module, make the non-real-time subsystem can be based on the big data analysis result adjustment of cloud subsystem or generate better wind-powered electricity generation field control strategy.

As can be seen from the figure, the cluster control system in this embodiment may have three security partitions, a first security partition for ensuring comprehensive data collection and storage in the wind farm by the non-real-time subsystem, a third security partition for realizing data backup by the cloud subsystem, and a second security partition for ensuring data interaction security between the first security partition and the third security partition by the proxy server. The cluster control system of the embodiment better meets comprehensive and safe control and data management of the wind power plant.

In order to meet the requirement of real-time data and non-real-time data interaction in a cluster control system, a data transmission network in a wind power plant also has the functions of real-time communication and non-real-time communication. Therefore, the devices in the wind farm are required to have real-time communication and non-real-time communication functions. Taking each wind generating set as an example, the data transmission link of each wind generating set is shown in fig. 9.

Each wind generating set in the wind farm corresponds to a respective wind generating set controller (a wind turbine controller shown in fig. 9), the wind turbine controller is a control core of a single wind generating set, and includes a WTG master control system, and the wind turbine controller may also be equipped with a CMS system for collecting more comprehensive state information of the wind generating set, and may provide completed data information for some decision makers in the control system. As shown in fig. 9, each of the fan controllers has real-time communication and non-real-time communication functions (a real-time communication protocol stack and a non-real-time communication protocol stack shown in the figure), and the fan controller is connected to the core switch of the wind farm network through the fan switch, transmits real-time data to the real-time subsystem through the real-time communication network, receives first device control information of the wind turbine generator system issued by the real-time subsystem, transmits non-real-time data to the non-real-time subsystem through the non-real-time communication network, and receives second device control information of the wind turbine generator system issued by the non-real-time subsystem.

It should be noted that, specific implementation schemes of the real-time communication network and the non-real-time communication network in the cluster control system in the embodiment of the present application include, but are not limited to, the schemes shown in fig. 8 and fig. 9, as long as the real-time data and the corresponding control information can be separately transmitted from the non-real-time data and the corresponding control information.

The embodiment of the present application further provides a wind farm cluster control method, which mainly includes:

storing the real-time data and the non-real-time data in a local database;

According to the wind power plant cluster control method, the wind power plant communication networking mode comprising the first communication network and the second communication network is adopted, real-time data and non-real-time data are separately transmitted, the real-time data are rapidly transmitted by using the first communication network and are not mixed with common non-real-time data to be transmitted, network resources of the wind power plant can be reasonably distributed, and the phenomena of network congestion, transmission flash or frequent data packet loss and the like caused by the fact that all data are mixed on one network channel in the prior art are changed. Real-time data and non-real-time data are respectively stored in a local database and a cloud database, so that the reliability of data management and storage of the wind power plant is guaranteed.

It should be noted that the wind farm cluster control method in the embodiment of the present application is applicable to fig. 1 of the present application and the wind farm cluster control system based on fig. 1, and the real-time subsystem in the control system may implement the relevant processing of real-time data, such as the obtaining of the real-time data and the generation of the first device control information, and the non-real-time subsystem may implement the relevant processing of non-real-time data, such as the obtaining of the non-real-time data and the generation of the second device control information, the local database may be a local database of the non-real-time subsystem, and the cloud database may be a cloud database of the cloud subsystem.

In this embodiment of the present application, the cluster control method may further include:

and processing the data in the cloud database according to the configured data processing strategy so as to adjust or generate a wind power plant control strategy based on the processing result.

Specifically, the cloud database of the cluster control system in the embodiment of the application may process data in the cloud database according to the configured data processing strategy, send a processing result to the real-time subsystem, apply the processing result to the wind farm by the real-time subsystem, and adjust or generate the wind farm control strategy based on the processing result.

In this embodiment of the application, generating corresponding first device control information according to the real-time data may specifically include:

calling a corresponding first decision maker in a pre-configured first decision maker set according to the real-time data, and generating first equipment control information by the corresponding first decision maker according to the real-time data, wherein the first decision maker set comprises at least one first decision maker;

generating corresponding second device control information according to the non-real-time data may specifically include:

calling a corresponding second decision maker in a pre-configured second decision maker set according to the non-real-time data, and generating second equipment control information by the corresponding second decision maker according to the non-real-time data, wherein the second decision maker set comprises at least one second decision maker;

the cluster control method may further include:

and calling a third decision maker in a pre-configured third decision maker set, and generating a corresponding decision by the third decision maker based on the data in the cloud database so as to control the wind power plant based on the decision, wherein the third decision maker set comprises at least one third decision maker.

In this embodiment of the application, before sending the first device control information to the corresponding control device in the wind farm, before sending the second device control information to the corresponding control device in the wind farm, and before controlling the wind farm based on the decision, the cluster control method further includes:

determining scheduling information of the first equipment control information, scheduling information of the second equipment control information and decision scheduling information according to a pre-configured decision scheduling strategy;

and respectively controlling the execution of the first equipment control information, the second equipment control information and the decision according to the scheduling information of the first equipment control information, the scheduling information of the second equipment control information and the decision scheduling information.

and controlling the first equipment control information, the second equipment control information and the decision-making control data to be within a preset effective data range.

configuring and managing a first decision maker set, a second decision maker set and a third decision maker set; and/or counting the operation data of the decision makers in the first decision maker set, the second decision maker set and the third decision maker set; and/or evaluating the execution effect of the decision makers in the first decision maker set, the second decision maker set and the third decision maker set.

It can be understood that the wind farm cluster control method shown in any embodiment of the present application may be applied to fig. 1 or a corresponding cluster control system based on fig. 1, for example, the real-time data and the non-real-time data may be stored in a local database of a non-real-time subsystem, and the real-time data and the non-real-time data are backed up in a cloud database of a cloud subsystem, and the non-real-time subsystem may implement functions of configuration and management of the first decision maker set, the second decision maker set, and the third decision maker set, statistics of operation data of the decision makers in the sets, evaluation of execution effect, and the like. For a detailed description of the cluster control method, reference may be made to the contents of the corresponding parts in the cluster control system, which are not described herein again.

An embodiment of the present application further provides a wind farm cluster control device, and as shown in fig. 10, an electronic device 2000 shown in fig. 10 includes: a processor 2001 and a transceiver 2004. The processor 2001 is coupled to the transceiver 2004, such as via the bus 2002. Optionally, the electronic device 2000 may further include a memory 2003. It should be noted that the transceiver 2004 is not limited to one in practical applications, and the structure of the electronic device 2000 is not limited to the embodiment of the present application.

The processor 2001 and the transceiver 2004 are applied to the embodiment of the present application to realize the functions of the cluster control system in fig. 1 or based on fig. 1. The transceiver 2004 comprises a receiver and a transmitter for implementing the cluster control system data receiving and/or transmitting functions of fig. 1 or based on fig. 1.

The processor 2001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 2001 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs and microprocessors, and the like.

Bus 2002 may include a path that conveys information between the aforementioned components. The bus 2002 may be a PCI bus or an EISA bus, etc. The bus 2002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 10, but this is not intended to represent only one bus or type of bus.

The memory 2003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

Optionally, the memory 2003 is used for storing application program code for performing the disclosed aspects, and is controlled in execution by the processor 2001. The processor 2001 is used to execute application program code stored in the memory 2003 to implement the actions of the cluster control system provided in any of the embodiments of the present application.

It should be noted that the wind farm cluster control device according to the embodiment of the present application may include a plurality of processors, a plurality of transceivers, and a plurality of memories, where each processor may cooperate with one transceiver to correspondingly implement functions of one or more subsystems in the cluster control system. For example, a processor cooperates with a transceiver to implement the functions of the real-time subsystem, a processor, a transceiver, and a memory cooperate to implement the functions of the non-real-time subsystem, and a processor, a transceiver, and a memory cooperate to implement the functions of the cloud-end subsystem. Of course, if the processor is powerful enough, the functions of the real-time subsystem and the non-real-time subsystem can be realized by one processor.

The embodiment of the present application provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements a cluster control method shown in any embodiment of the present application.

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims

1. The wind power plant cluster control system is characterized by comprising a non-real-time subsystem, and a real-time subsystem and a cloud subsystem which are respectively in communication connection with the non-real-time subsystem:

the real-time subsystem is used for communicating with equipment in a wind power plant through a first communication network according to first configuration information to acquire real-time data in the wind power plant, generating corresponding first equipment control information according to the real-time data, sending the first equipment control information to corresponding control equipment in the wind power plant through the first communication network, and sending the real-time data to the non-real-time subsystem;

the non-real-time subsystem is used for communicating with equipment in the wind power plant through a second communication network according to second configuration information to acquire non-real-time data in the wind power plant, generating corresponding second equipment control information according to the non-real-time data, sending the second equipment control information to corresponding control equipment in the wind power plant through the second communication network, receiving the real-time data sent by the real-time subsystem, storing the real-time data and the non-real-time data into a local database, and sending the real-time data and the non-real-time data to the cloud subsystem;

2. The control system of claim 1,

the cloud subsystem is further used for processing the data in the cloud database according to the configured data processing strategy and sending a processing result to the non-real-time subsystem;

and the non-real-time subsystem is also used for receiving the processing result and adjusting or generating a wind power plant control strategy based on the processing result.

3. The control system of claim 1, further comprising:

and the safety isolation subsystem is used for realizing the bidirectional isolation of data interaction between the non-real-time subsystem and the cloud subsystem.

4. The control system of claim 1,

the real-time subsystem specifically comprises:

the real-time decision module is used for calling a corresponding first decision device in a pre-configured first decision device set according to the real-time data, and generating the first equipment control information by the corresponding first decision device according to the real-time data, wherein the first decision device set comprises at least one first decision device;

the non-real-time subsystem specifically comprises:

the non-real-time decision module is used for calling a corresponding second decision device in a pre-configured second decision device set according to the non-real-time data, and the corresponding second decision device generates the second equipment control information according to the non-real-time data, wherein the second decision device set comprises at least one second decision device;

the cloud subsystem comprises:

the cloud decision module is used for calling a third decision maker in a pre-configured third decision maker set, generating a corresponding decision by the third decision maker based on data in the cloud database, and sending the decision to the non-real-time subsystem, wherein the third decision maker set comprises at least one third decision maker;

and the non-real-time subsystem is also used for receiving the decision and controlling the wind power plant based on the decision.

5. The control system of claim 4,

the non-real-time decision module is further used for configuration and management of the first decision maker set, the second decision maker set and the third decision maker set.

6. The control system of claim 4, wherein the non-real-time decision module comprises a decision agent forwarding unit and the real-time decision module comprises a decision scheduling unit;

the decision agent forwarding unit is configured to send the second device control information and the decision to the real-time decision module before sending the second device control information to a corresponding control device in the wind farm and before controlling the wind farm based on the decision, and is configured to receive scheduling information of the second device control information and scheduling information of the decision sent by the real-time decision module;

the decision scheduling unit is configured to receive the second device control information and the decision, determine scheduling information of the first device control information, scheduling information of the second device control information, and scheduling information of the decision according to a preconfigured decision scheduling policy, and send the scheduling information of the second device control information and the scheduling information of the decision to the non-real-time decision module;

the real-time subsystem is specifically configured to control execution of the first device control information according to scheduling information of the first device control information;

the non-real-time subsystem is specifically configured to control execution of the second device control information and the decision according to scheduling information of the second device control information and scheduling information of the decision.

7. The control system of claim 6, wherein the real-time decision module further comprises:

and the decision boundary control unit is used for controlling the first equipment control information, the second equipment control information and the decision control data to be in a preset effective data range.

8. The control system of claim 4, wherein the non-real-time subsystem further comprises:

and the decision evaluation module is used for counting the operation data of the decision makers in the first decision maker set, the second decision maker set and the third decision maker set and/or evaluating the execution effect of the decision makers in the first decision maker set, the second decision maker set and the third decision maker set.

9. The control system of any one of claims 1 to 8, wherein the control devices in the wind farm include a wind generating set controller and a wind farm level control device;

the equipment in the wind power plant comprises control equipment in the wind power plant and wind power plant level sensing detection equipment.

10. The control system according to any one of claims 1 to 8, wherein the non-real time subsystem further comprises a human-machine interaction module and/or a logging module;

the human-computer interaction module is used for providing a human-computer interaction interface for a user so that the user can check the running state of each part in the control system, and/or perform function setting on the control system, and/or export data in the control system;

and the log module is used for recording the operation information of each part in the control system and the operation information of the user on the control system.

11. The control system of any one of claims 1 to 8, wherein the real-time subsystem is communicatively connected to the non-real-time subsystem via a third communication network, and the non-real-time subsystem is communicatively connected to the cloud subsystem via a fourth communication network;

the data transmission rate of the first communication network is greater than that of the third communication network, and the data transmission rate of the first communication network is greater than that of the fourth communication network.

12. A wind farm cluster control method is characterized by comprising the following steps:

according to first configuration information, communicating with equipment in a wind power plant through a first communication network to obtain real-time data in the wind power plant, generating corresponding first equipment control information according to the real-time data, and sending the first equipment control information to corresponding control equipment in the wind power plant through the first communication network;

according to second configuration information, communicating with equipment in the wind power plant through a second communication network to obtain non-real-time data in the wind power plant, generating corresponding second equipment control information according to the non-real-time data, and sending the second equipment control information to corresponding control equipment in the wind power plant through the second communication network; wherein the data transmission rate of the first communication network is greater than the data transmission rate of the second communication network;

storing the real-time data and the non-real-time data in a local database;

13. The control method according to claim 12, wherein the generating corresponding first device control information from the real-time data comprises:

calling a corresponding first decision maker in a pre-configured first decision maker set according to the real-time data, and generating the first equipment control information by the corresponding first decision maker according to the real-time data, wherein the first decision maker set comprises at least one first decision maker;

generating corresponding second device control information according to the non-real-time data includes:

calling a corresponding second decision maker in a pre-configured second decision maker set according to the non-real-time data, and generating the second equipment control information by the corresponding second decision maker according to the non-real-time data, wherein the second decision maker set comprises at least one second decision maker;

the method further comprises the following steps:

14. The control method of claim 13, wherein prior to sending the first device control information to the corresponding control device in the wind farm, prior to sending the second device control information to the corresponding control device in the wind farm, and prior to control of the wind farm based on the decision, the method further comprises:

determining scheduling information of the first device control information, scheduling information of the second device control information and scheduling information of the decision according to a pre-configured decision scheduling strategy;

and controlling the execution of the first device control information, the second device control information and the decision according to the scheduling information of the first device control information, the scheduling information of the second device control information and the decision scheduling information.

15. The control method according to claim 14, characterized in that the method further comprises:

16. The control method according to claim 13, characterized in that the method further comprises:

configuring and managing the first decision maker set, the second decision maker set and the third decision maker set; and/or the presence of a gas in the gas,

counting the operation data of the decision makers in the first decision maker set, the second decision maker set and the third decision maker set; and/or the presence of a gas in the gas,

evaluating the execution effect of the decision-makers in the first decision-maker set, the second decision-maker set and the third decision-maker set.

17. A wind farm cluster control device comprising a memory and a processor;

the memory having stored therein computer program instructions;

the processor is configured to read the computer program instructions to perform a wind farm cluster control method according to any of claims 12 to 16.

18. A computer readable storage medium, characterized in that computer program instructions are stored in the storage medium, which computer program instructions, when executed by a processor, implement the wind farm cluster control method of any of the claims 12 to 16.