Wind turbine generator sets and their control methods and systems

Abstract

A wind turbine generator set and its control method and system are disclosed. The method includes: selecting recommended control commands from the standard control commands of the wind turbine generator set; for each recommended control command, determining the recommended state of the recommended control command based on data from an accessed third-party system, cached data from a data acquisition and monitoring control system, and a preset recommendation logic of the recommended control command, wherein the preset recommendation logic is determined by a calculation factor and operator of a preset format; and sending the recommended control command in the recommended state to the target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control command.

Description

Technical Field

[0001] This disclosure generally relates to the field of wind power generation technology, and more specifically to wind turbine generators and their control methods and systems. Background Technology

[0002] Currently, a centralized internal system is often used to connect multiple external systems, collect data from each external system, and make corrections based on the data from each external system (such as electrical distance). Different logic corrections are applied for different electrical distance conditions. Then, control commands are sent to the external systems (the controlled objects) based on the corrected results to achieve intelligent control. However, the above technologies only collect and analyze data from the external systems themselves to achieve intelligent control of the external systems themselves. This results in limited data reliance for intelligent control of external systems. Furthermore, the control logic in these technologies is strongly correlated with the external systems, leading to poor scalability. Summary of the Invention

[0003] The embodiments of this disclosure provide a wind turbine generator set and its control method and system, which can effectively solve the problems of limited data and poor scalability of control logic in the prior art.

[0004] In one general aspect, a control method for a wind turbine generator set is provided, comprising: selecting recommended control commands from standard control commands of the wind turbine generator set; for each recommended control command, determining a recommended state of the recommended control command based on data from an accessed third-party system, cached data from a data acquisition and monitoring control system, and a preset recommendation logic of the recommended control command, wherein the preset recommendation logic is determined by a calculation factor and operator of a preset format; and sending the recommended control command in the recommended state to a target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control command.

[0005] Optionally, the preset recommendation logic includes multiple sub-recommendation logics. The preset recommendation logic, based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommendation control instruction, determines the recommendation status of the recommendation control instruction. This includes: for each of the multiple sub-recommendation logics, selecting the computational data required by the sub-recommendation logic from the data from the third-party system and the cached data, and inputting the computational data into the sub-recommendation logic to obtain the corresponding recommendation result; in response to all the recommendation results of the sub-recommendation logics indicating success, determining that the recommendation control instruction has entered the recommended state.

[0006] Optionally, inputting computational data into sub-recommendation logic to obtain corresponding recommendation results includes: inputting computational data into sub-recommendation logic according to the preset format of computational factors in sub-recommendation logic to obtain the recommendation expression corresponding to sub-recommendation logic; splitting the recommendation expression into sub-expressions by brackets; splitting the sub-expressions into logical factor expressions by logical operators; splitting the logical factor expressions into relational factor expressions by relational operators; performing arithmetic operations on each relational factor expression to obtain relational operation results; performing logical operations on each logical factor expression based on the relational operation results to obtain logical operation results; and performing operations on each sub-expression based on the logical operation results to obtain the recommendation result corresponding to the sub-recommendation logic.

[0007] Optionally, in response to the success indication of recommendation results for all sub-recommendation logics, the recommendation control instruction is determined to enter the recommended state, including: in response to the success indication of recommendation result for the i-th sub-recommendation logic in the preset recommendation logic, the recommendation control instruction is determined to enter the i-th recommendation state, and the recommendation control instruction is moved from the (i-1)-th recommendation state cache to the i-th recommendation state cache, where i = 1, 2, ..., N-1, N is the number of multiple sub-recommendation logics, and N is a positive integer; in response to the success indication of recommendation result for the N-th sub-recommendation logic in the preset recommendation logic, the recommendation control instruction is determined to enter the recommended state, and the recommendation control instruction is moved from the (N-1)-th recommendation state cache to the recommended state cache.

[0008] Optionally, based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommendation control instruction, the recommendation status of the recommendation control instruction is determined, which further includes: in response to the failure of the recommendation result indication of any sub-recommendation logic in the preset recommendation logic, the recommendation control instruction is deleted from all recommendation status caches, and it is determined that the recommendation control instruction has not entered the recommended state.

[0009] Optionally, in response to the success indication of all sub-recommendation logics, determining that the recommendation control instruction has entered the recommended state further includes: for each of the multiple sub-recommendation logics, performing the following processing: periodically inputting the corresponding operation data of the sub-recommendation logic into the sub-recommendation logic within a preset time period, and in response to the success indication of the recommendation result of the sub-recommendation logic in each period, finally determining that the recommendation result of the sub-recommendation logic indicates success.

[0010] Optionally, before determining the recommended status of the recommended control instruction based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction, the method further includes: downloading the configuration file of the recommended control instruction from the database; querying the standard control instructions of the target wind turbine generator in the database using the configuration file to obtain the information of the standard control instruction corresponding to the recommended control instruction; and configuring the recommended control instruction based on the information of the standard control instruction corresponding to the recommended control instruction, the preset recommendation logic, and the configuration file.

[0011] Optionally, before determining the recommended status of the recommended control instruction based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction, the method further includes: configuring the access information of the third-party system to be accessed; accessing the third-party system according to the access information, and obtaining the data from the third-party system.

[0012] Optionally, after sending the recommended control command in the recommended state to the target wind turbine, the method further includes: updating the monitoring page, wherein the monitoring page includes a wind turbine display area, a recommended control command display area, and a recommended control command sending method switching area.

[0013] In another general aspect, a control system for a wind turbine generator set is provided. The control system includes a presentation service, an application service, and an execution gateway. The presentation service selects recommended control instructions from the standard control instructions of the wind turbine generator set, wherein the recommended control instructions are standard control instructions that can be intelligently recommended. The application service, for each recommended control instruction, determines the recommended state of the recommended control instruction based on data from an accessed third-party system, cached data from a data acquisition and monitoring control system, and a preset recommendation logic for the recommended control instruction. The preset recommendation logic is determined by operation factors and operators in a preset format. The execution gateway sends the recommended control instructions in the recommended state to the target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control instructions.

[0014] Optionally, the preset recommendation logic includes multiple sub-recommendation logics. For each sub-recommendation logic, the application service selects the computational data required by the sub-recommendation logic from the data and cached data of the third-party system, and inputs the computational data into the sub-recommendation logic to obtain the corresponding recommendation result. In response to the success indication of the recommendation results of all sub-recommendation logics, the recommendation control instruction is determined to enter the recommended state.

[0015] Optionally, the application service inputs the computational data into the sub-recommendation logic according to the preset format of the computational factors in the sub-recommendation logic to obtain the recommendation expression corresponding to the sub-recommendation logic; the recommendation expression is split into sub-expressions by brackets; the sub-expressions are split into logical factor expressions by logical operators; the logical factor expressions are split into relational factor expressions by relational operators; arithmetic operations are performed on each relational factor expression to obtain the relational operation results; logical operations are performed on each logical factor expression based on the relational operation results to obtain the logical operation results; and operations are performed on each sub-expression based on the logical operation results to obtain the recommendation result corresponding to the sub-recommendation logic.

[0016] Optionally, in response to a successful recommendation result indication of the i-th sub-recommendation logic in the preset recommendation logic, the application service determines that the recommendation control instruction enters the i-th recommendation state and moves the recommendation control instruction from the (i-1)-th recommendation state cache to the i-th recommendation state cache, where i = 1, 2, ..., N-1, N is the number of multiple sub-recommendation logics, and N is a positive integer; in response to a successful recommendation result indication of the N-th sub-recommendation logic in the preset recommendation logic, the application service determines that the recommendation control instruction enters the recommended state and moves the recommendation control instruction from the (N-1)-th recommendation state cache to the recommended state cache.

[0017] Optionally, the application service, in response to the failure of the recommendation result indication of any sub-recommendation logic in the preset recommendation logic, deletes the recommendation control instruction from all recommendation state caches and determines that the recommendation control instruction has not entered the recommended state.

[0018] Optionally, the application service performs the following processing for each of the multiple sub-recommendation logics: periodically inputting the corresponding computational data of the sub-recommendation logic into the sub-recommendation logic within a preset time period; responding to the recommendation result of the sub-recommendation logic in each period indicating success; and finally determining that the recommendation result of the sub-recommendation logic indicates success.

[0019] Optionally, the system also includes a database and application services. Before determining the recommended status of the recommended control instructions based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instructions, the system downloads the configuration file of the recommended control instructions from the database; uses the configuration file to query the standard control instructions of the target wind turbine generator in the database to obtain the information of the standard control instructions corresponding to the recommended control instructions; and configures the recommended control instructions based on the information of the standard control instructions corresponding to the recommended control instructions, the preset recommendation logic, and the configuration file.

[0020] Optionally, the application service configures the access information of the third-party system to be accessed before determining the recommended status of the recommended control instruction based on the data of the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction; accesses the third-party system according to the access information and obtains the data of the third-party system.

[0021] Optionally, after the recommended control command in the recommended state is sent to the target wind turbine, a service update monitoring page is displayed. The monitoring page includes a wind turbine display area, a recommended control command display area, and a recommended control command sending method switching area.

[0022] In another general aspect, a computer-readable storage medium is provided for storing instructions, wherein when the instructions are executed by at least one computing device, they cause at least one computing device to perform a control method for any of the wind turbine generators described above.

[0023] In another general aspect, a system is provided that includes at least one computing device and at least one storage device for storing instructions, wherein the instructions, when executed by the at least one computing device, cause the at least one computing device to perform a control method for any of the wind turbine generators described above.

[0024] In another general aspect, a computer program product is provided, including computer instructions that, when executed by a processor, implement the control method for a wind turbine generator as described above.

[0025] In another general aspect, a wind turbine generator set is provided, including the control device for the wind turbine generator set as described above.

[0026] According to embodiments of the present disclosure, the wind turbine generator set and its control method and system can collect data from a third-party system. This data, along with cached data from a data acquisition and monitoring control system, is processed through preset recommendation logic to determine the recommended state of a control command. The recommended control command, now in the recommended state, is then sent to the target wind turbine generator set. This allows for control of the target wind turbine generator set based on the sent control command. In other words, the present disclosure utilizes data from a third-party system and cached data from a data acquisition and monitoring control system to control the target wind turbine generator set, thus moving beyond reliance solely on data from the target wind turbine generator set (the controlled object) itself and enabling intelligent control of the target wind turbine generator set. Therefore, the present disclosure effectively solves the problems of limited data and poor control logic scalability in existing intelligent control technologies.

[0027] Further aspects and / or advantages of the general concept of this disclosure will be set forth in part in the description which follows, and in part will be clear from the description or may be learned by practice of the general concept of this disclosure. Attached Figure Description

[0028] The above and other objects and features of the embodiments of this disclosure will become clearer from the following description taken in conjunction with the accompanying drawings illustrating the embodiments, wherein: Figure 1 This is a flowchart illustrating a control method for a wind turbine generator set according to an embodiment of the present disclosure; Figure 2 This is a schematic diagram illustrating the definition flow of a recommended control instruction according to an embodiment of the present disclosure; Figure 3 This is a schematic diagram illustrating the flow of a third-party system access logic according to an embodiment of this disclosure; Figure 4 This is a schematic diagram illustrating a process of intelligent control issuing recommended control commands according to an embodiment of the present disclosure; Figure 5 This is a schematic diagram illustrating an embodiment of the present disclosure of an intelligent control page; Figure 6 This is a timing diagram illustrating an intelligent control page monitoring process according to an embodiment of the present disclosure; Figure 7 This is a control command state diagram illustrating an embodiment of the present disclosure; Figure 8 This is a schematic diagram illustrating the logic flow of the intelligent operation stage of control instructions in an embodiment of this disclosure; Figure 9 This is a schematic diagram illustrating a service list of an embodiment of the present disclosure; Figure 10 This is a block diagram illustrating the control system of a wind turbine generator set according to an embodiment of the present disclosure; Figure 11 This is a block diagram illustrating a deployment model of a control system according to an embodiment of the present disclosure. Detailed Implementation

[0029] The following detailed embodiments are provided to aid the reader in gaining a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but may be changed as will become clear upon understanding this disclosure, except for operations that must occur in a specific order. Furthermore, for clarity and conciseness, descriptions of features known in the art may be omitted.

[0030] The features described herein may be implemented in different forms and should not be construed as limited to the examples described herein. Rather, the examples described herein are provided only to illustrate some of the many feasible ways of implementing the methods, apparatus, and / or systems described herein, which will become clear upon understanding the disclosure of this application.

[0031] As used herein, the term “and / or” includes any one of the associated listed items and any combination of any two or more.

[0032] Although terms such as “first,” “second,” and “third” may be used herein to describe various components, assemblies, regions, layers, or parts, these components, assemblies, regions, layers, or parts should not be limited by these terms. Rather, these terms are used only to distinguish one component, assembly, region, layer, or part from another. Thus, without departing from the teaching of the examples described herein, the first component, first assembly, first region, first layer, or first part referred to as the first component, first assembly, first region, first layer, or first part may also be referred to as the second component, second assembly, second region, second layer, or second part.

[0033] In the specification, when an element (such as a layer, region, or substrate) is described as being "on" another element, "connected to," or "bonded to" another element, the element may be directly "on" another element, directly "connected to," or "bonded to" the other element, or one or more other elements may be present in between. Conversely, when an element is described as being "directly on" another element, "directly connected to," or "directly bonded to" another element, no other elements may be present in between.

[0034] The terminology used herein is for the purpose of describing various examples only and is not intended to limit disclosure. Unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. The terms “comprising,” “including,” and “having” indicate the presence of the described features, quantities, operations, components, elements, and / or combinations thereof, but do not preclude the presence or addition of one or more other features, quantities, operations, components, elements, and / or combinations thereof.

[0035] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains upon understanding this disclosure. Unless expressly defined herein, terms (such as those defined in a general dictionary) shall be interpreted as having a meaning consistent with their meaning in the context of the relevant field and in this disclosure, and shall not be interpreted in an idealized or overly formalistic manner.

[0036] Furthermore, in the description of the examples, detailed descriptions of well-known related structures or functions will be omitted when it is believed that such detailed descriptions would lead to a vague interpretation of this disclosure.

[0037] This disclosure provides a wind turbine generator set and its control method and system, which can solve the above-mentioned problems. The control method of the wind turbine generator set disclosed herein can be applied to a server, to the controller of a single wind turbine generator set, or to the main controller of a wind farm. This disclosure does not limit the application of this method. The server, controller, and wind turbine generator set can be connected wirelessly or via wired connection. The server can be a single server, a server cluster consisting of several servers, a cloud computing platform, or a virtualization center. The following explanation uses a server as an example.

[0038] The server selects recommended control commands from the standard control commands of the wind turbine generator set. For each recommended control command, based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control command, the server determines the recommended state of the recommended control command. The preset recommendation logic is determined by the operation factors and operators in a preset format. The recommended control commands in the recommended state are then sent to the target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control commands.

[0039] The wind turbine generator set, its control method, and system disclosed herein will be described in detail below with reference to the accompanying drawings.

[0040] This disclosure proposes a control method for wind turbine generator sets. Figure 1 This is a flowchart illustrating a control method for a wind turbine generator set according to an embodiment of the present disclosure. (Refer to...) Figure 1 The control method for the wind turbine generator set includes the following steps: In step S101, a recommended control command is selected from the standard control commands of the wind turbine generator set.

[0041] As an example, the standard control commands for wind turbine generator sets may include, but are not limited to, the following control commands that wind turbine generator sets can receive: reset control commands, shutdown control commands, start-up control commands, maintenance control commands, etc. Specifically, according to the model of the wind turbine generator set, corresponding standard control commands can be set for each model of wind turbine generator set. Generally, standard control commands can realize all control functions of the wind turbine generator set, and this disclosure does not limit them.

[0042] As an example, recommended control commands are standard control commands that can be intelligently recommended and executed. Specifically, one or more standard control commands can be selected from the set of standard control commands as recommended commands, based on the owner's needs. For instance, assuming the set of standard control commands includes reset control commands, shutdown control commands, start-up control commands, and maintenance control commands, the owner can select reset control commands and shutdown commands as recommended control commands. These two commands can then be intelligently recommended and executed to control the wind turbine generator set.

[0043] In step S102, for each recommended control instruction, the recommended state of the recommended control instruction is determined based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction. The preset recommendation logic is determined by operation factors and operators in a preset format.

[0044] As an example, the aforementioned third-party systems may include, but are not limited to: health management systems and power prediction systems.

[0045] As an example, the preset format of the operational factors may include, but is not limited to, the following Table 1: Table 1 Examples of Operation Factors

[0046] As an example, the above operators may include, but are not limited to: relational operators (such as >, <, >=, <=, ==, !=), logical operators (||, &&), and arithmetic operators (+, -, ×, / , %).

[0047] As an example, the aforementioned preset recommendation logic can be determined by operation factors and operators in a preset format, supporting basic relational operations and satisfying the judgment of the switch status of remote signaling quantities and the range judgment of remote measurement quantities. This disclosure does not limit this. The aforementioned preset recommendation logic can generally be configured by the field operation and maintenance personnel of the data acquisition and monitoring control (SCADA) system according to the control specifications of the system user (power generation enterprise specifications, power grid specifications). Specifically, the recommendation logic can be shown in Table 2 below, which is not limited by this disclosure. Table 2 Example of Preset Recommendation Logic

[0048] According to embodiments of this disclosure, the preset recommendation logic includes multiple sub-recommendation logics. Determining the recommendation status of a recommendation control instruction based on data from an accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommendation control instruction can include: for each sub-recommendation logic, selecting the computational data required by the sub-recommendation logic from the data from the third-party system and the cached data, and inputting the computational data into the sub-recommendation logic to obtain the corresponding recommendation result; in response to all recommendation results from the sub-recommendation logic indicating success, determining that the recommendation control instruction has entered the recommended state. Through this embodiment, the preset recommendation logic can include multiple sub-recommendation logics, enabling complex combinations of conditions and addressing more diverse scenarios and needs.

[0049] As an example, suppose the preset recommendation logic contains two sub-recommendation logics, which are the first two rows in Table 2, namely {0-100:WTUR.WSpd.Ra.F32}>3 and {1-100, 101, 102: WTUR.WSpd.Ra.F32 : AVG}>5. At this time, the calculation data required for each sub-recommendation logic can be obtained from the data of the third-party system and the cached data of the SCADA system, such as the wind speed of the wind turbine generators numbered 100, 101, and 102. The calculation data is then input into the corresponding sub-recommendation logic to obtain the corresponding recommendation result. If the recommendation results of both sub-recommendation logics indicate success, the recommended control command can be marked as recommended.

[0050] As an example, suppose the preset recommendation logic contains two sub-recommendation logics. These two sub-recommendation logics can be calculated sequentially or in parallel, and this disclosure does not limit this.

[0051] According to embodiments of this disclosure, inputting computational data into sub-recommendation logic to obtain corresponding recommendation results may include: inputting computational data into the sub-recommendation logic according to a preset format of the computational factors in the sub-recommendation logic to obtain a recommendation expression corresponding to the sub-recommendation logic; splitting the recommendation expression into sub-expressions by brackets; splitting the sub-expressions into logical factor expressions by logical operators; splitting the logical factor expressions into relational factor expressions by relational operators; performing arithmetic operations on each relational factor expression to obtain relational operation results; performing logical operations on each logical factor expression based on the relational operation results to obtain logical operation results; and performing operations on each sub-expression based on the logical operation results to obtain the recommendation result corresponding to the sub-recommendation logic.

[0052] This embodiment provides a preset recommendation logic based on arithmetic operations, logical operations, and relational operations, which enables the dynamic processing of complex combinations of conditions and the automatic execution of preset decision logic. Compared with traditional fixed thresholds or simple condition judgments, it provides greater flexibility and adaptability, and can cope with more diverse scenarios and needs.

[0053] As an example, when the preset recommendation logic includes arithmetic operations, logical operations, and relational operations, calculations can be performed by splitting the expression based on operator precedence. Specifically, 1) recursively split the expression based on parentheses ( ) to form sub-expressions; 2) perform logical operator splitting on the independent sub-expressions to form logical factor expressions; 3) perform relational operator splitting on the logical factor expressions to form relational factor expressions; 4) perform arithmetic operations on the relational factor expressions (e.g., first split ×, / , %, then split +, -) to form arithmetic factors; 5) perform arithmetic operations >> relational operations >> logical operations step by step to obtain a logical result (true or false). It should be noted that step 4) above can be omitted, that is, arithmetic operations can be performed directly after obtaining the relational factor expressions.

[0054] As an example, assuming the preset recommendation logic's calculation formula is ((7+8×6>2+4||true)&&(6×7<30))==((6×7<20)&&false), the calculation process can be as follows: 1) Split the brackets The formula can be broken down into (A1.1&&A1.2)==(A1.3&&false), where A1.1=7+8×6>2+4||true, A1.2=6×7<30, and A1.3=6×7<20.

[0055] 2) Continue splitting the brackets. The formula is further broken down into A2.1==A2.2, without parentheses, where A2.1=A1.1&&A1.2 and A2.2=A1.3&&false.

[0056] 3) Perform logical decomposition Decompose A1.1 into B1.1||true, where B1.1=7+8×6>2+4, B1.2=A1.2, B1.3=A1.3; Split A2.1 into B2.1 && B2.2, where B2.1 = A1.1 and B2.2 = A1.2; Split A2.2 into B2.3 && false, where B2.3 = A1.3.

[0057] 4) Perform relation splitting Split B1.1 = 7 + 8×6 > 2 + 4 into C1.1 > C1.2, where C1.1 = 7 + 8×6 and C1.2 = 2 + 4; Split B1.2 = A1.2 = 6×7 < 30 into C1.3 < C1.4, where C1.3 = 6×7 and C1.4 = 30; Split B1.3 = A1.3 = 6×7 < 20 into C1.5 < C1.6, where C1.5 = 6×7 and C1.6 = 20.

[0058] 5) Perform arithmetic operations First, perform operations on arithmetic operators with high precedence, such as ×, / , %, etc., and then perform operations on arithmetic operators with low precedence, such as +, - etc., where C1.1 = 7 + 8×6 = 7 + 48 = 55 C1.2 = 2 + 4 = 6 C1.3 = 6×7 = 42 C1.5 = 6×7 = 42 6) Fill the results and return to the upper-level relational operation B1.1 = C1.1 > C1.2 = 55 > 6 = true; B1.2 = C1.3 < C1.4 = 42 < 30 = fasle; B1.3 = C1.5 < C1.6 = 42 < 20 = false.

[0059] 7) Fill the results and return to the upper-level logical operation A1.1 = B1.1 || true = true || true = true; A1.2 = B1.2 = false; A1.3 = B1.3 = false; A2.1 = B2.1 && B2.2 = A1.1 && A1.2 = true && false = false; A2.2 = B2.3 && fasle = A1.3 && false = false && fasle = false.

[0060] 8) Fill the results and return to the upper level for continued operation The conversion formula of the operation formula for the preset recommendation logic A2.1 == A2.2 = false == false = true. Thus, the result of the operation formula can be obtained as true, indicating that the recommendation result of the preset recommendation logic indicates success.

[0061] According to embodiments of this disclosure, in response to the success indication of recommendation results from all sub-recommendation logics, determining that the recommendation control instruction enters the recommended state may include: in response to the success indication of the recommendation result of the i-th sub-recommendation logic in the preset recommendation logic, determining that the recommendation control instruction enters the i-th recommendation state, and moving the recommendation control instruction from the (i-1)-th recommendation state cache to the i-th recommendation state cache, where i = 1, 2, ..., N-1, N is the number of multiple sub-recommendation logics, and N is a positive integer; in response to the success indication of the recommendation result of the N-th sub-recommendation logic in the preset recommendation logic, determining that the recommendation control instruction enters the recommended state, and moving the recommendation control instruction from the (N-1)-th recommendation state cache to the recommended state cache.

[0062] According to embodiments of this disclosure, in response to a failure of the recommendation result indication in any of the sub-recommendation logics in the preset recommendation logic, the recommendation control instruction is deleted from all recommendation state caches, and it is determined that the recommendation control instruction has not entered the recommended state.

[0063] Through the above embodiments, multiple sub-recommendation logics can be judged in layers, which can not only provide real-time feedback to the user on the judgment progress, but also avoid the computational waste caused by completing the judgment all at once. For example, if the final result of the judgment is failure, it is very likely that the failure was caused by a certain step. The subsequent calculations after that step can be completely ignored. However, the judgment only outputs the final result, that is, the subsequent calculations will still be performed, thus leading to a waste of computing resources.

[0064] As an example, suppose the preset recommendation logic of the recommended control instruction contains two sub-recommendation logics, where N is 2. First, the calculation process of the first sub-recommendation logic is initiated. If the calculation result indicates that the recommendation result of the first sub-recommendation logic is successful, the recommended control instruction enters the first recommended state and is written to the first recommended state cache. If the calculation result indicates that the recommendation result of the first sub-recommendation logic fails, the calculation of the preset recommendation logic for this recommended control instruction is stopped, and the calculation is recalculated in the next full-scale wind turbine control rule verification loop. If the recommendation result of the first sub-recommendation logic is successful, the calculation process of the second sub-recommendation logic is initiated. If the calculation result indicates that the recommendation result of the second sub-recommendation logic is successful, the recommended control instruction enters the recommended state and is moved from the first recommended state cache to the recommended state cache. If the calculation result indicates that the recommendation result of the second sub-recommendation logic fails, the calculation of the preset recommendation logic for this recommended control instruction is stopped, and the calculation is recalculated in the next full-scale wind turbine control rule verification loop.

[0065] It should be noted that the full-scale fan control rule verification loop refers to the periodic calculation of the recommended rules for the control command configuration of all fans.

[0066] According to embodiments of this disclosure, in response to all sub-recommendation logics indicating success, the recommendation control instruction is determined to enter the recommended state. The process further includes: for each of the multiple sub-recommendation logics, the following processing is performed: periodically inputting the corresponding computational data of the sub-recommendation logic into the sub-recommendation logic within a preset duration; and in response to all sub-recommendation logics indicating success in each period, the recommendation result of the sub-recommendation logic is finally determined to be successful. This embodiment sets a duration for each recommendation state, avoiding temporary recommendation states, i.e., errors in computational data detection leading to incorrect control.

[0067] As an example, to avoid detection errors in the computational data, the recommendation result calculated based on the erroneous data would also be incorrect. Therefore, to avoid sudden detection errors, the same recommendation logic can be computed multiple times to prevent such unexpected situations. This embodiment sets a preset time period within which the same recommendation logic can be computed periodically. Only if the computation result of each period indicates success is the recommendation result of the recommendation logic ultimately determined to be successful.

[0068] As an example, the above-mentioned preset duration is not mandatory, and it is also possible not to set the preset duration. Moreover, the preset duration of each sub-recommendation logic can be the same or different, and this disclosure does not impose any restrictions on this.

[0069] As an example, assuming a preset duration is set, i.e., entering the thread for calculating the preset duration, taking the preset recommendation logic of the current recommendation control instruction as an example that includes two sub-recommendation logics, this thread includes the following steps: 1) When the first sub-recommendation logic of the current recommendation control instruction is being processed, if the processing time of the sub-recommendation logic has not reached the preset time, the information of the current recommendation control instruction is stored in the "preset time not reached cache" as temporary cache data, and then the process proceeds to step 2). 2) Retrieve the temporary cache data from the "Cache Not Reached for Preset Duration". Calculate whether the time the temporary cache data was added to the "Cache Not Reached for Preset Duration" and the current time (i.e., the computation time) have reached the preset duration. If the computation time has reached the preset duration and the periodic recommendation results within that preset duration indicate success, move the current recommendation control instruction to the "Recommendation Instruction Cache" and proceed to step 3). If the computation time has not reached the preset duration, skip this step and proceed directly to step 3). 3) Retrieve other recommendation control instructions from the "Recommended Instruction Cache" and calculate whether the operation time of the second sub-recommendation logic of the other recommendation control instructions has reached the preset time. If the operation time has reached the preset time and the periodic recommendation results all indicate success within the preset time, or if no preset time is configured for the second sub-recommendation logic, then move the other recommendation control instructions from the "Recommended Instruction Cache" to the "Recommended Instruction Cache" and return to process 1) to repeat the calculation. If the operation time has not reached the preset time, then directly return to process 1) to repeat the calculation.

[0070] According to embodiments of this disclosure, before determining the recommended status of a recommended control instruction based on data from an accessed third-party system, cached data from a data acquisition and monitoring control system, and preset recommendation logic for the recommended control instruction, the method further includes: downloading a configuration file for the recommended control instruction from a database; querying the database for standard control instructions for the target wind turbine generator using the configuration file to obtain information about the standard control instruction corresponding to the recommended control instruction; and configuring the recommended control instruction based on the information about the standard control instruction corresponding to the recommended control instruction, the preset recommendation logic, and the configuration file. Through this embodiment, when configuring a recommended control instruction, it is determined whether the target wind turbine generator has defined a standard control instruction corresponding to the recommended control instruction. If a corresponding standard control instruction is defined, the recommended control instruction is configured; if no corresponding standard control instruction is defined, it indicates that the recommended control instruction is not applicable to the target wind turbine generator, and no further configuration processing is required.

[0071] As an example, standard control commands can be defined for each wind turbine generator set. These standard control commands may include, but are not limited to, the following attributes: unique identifier, Chinese description of the command, English description of the command, Chinese description of the parameters, English description of the parameters, whether to display the identifier, sorting order, control pre-check conditions, set of monitoring points associated with the control command, whether to use the quick command identifier, Chinese prompt when the pre-check conditions fail, and English prompt when the pre-check conditions fail.

[0072] As an example, the database mentioned above could be a PostgreSQL-based database called Highgo, or other relational databases, and this disclosure does not limit the scope of the database.

[0073] As an example, recommended control commands can be selected according to the user's needs. It should be noted that when selecting recommended control commands, the standard control commands do not need to be defined; only the names of the standard control commands are required. After determining which standard control commands are recommended, the recommended control commands can be defined. To configure the recommended control command, the configuration file for the recommended control command can be downloaded from the database. This configuration file may contain the identifier of the recommended control command. Based on the identifier, the database is queried for the standard control commands of the target wind turbine generator set. If the information of the corresponding standard control command is found, it means that the recommended control command is applicable to the target wind turbine generator set. At this point, the recommended control command can be configured based on the information of the corresponding standard control command, the configuration file, and the preset recommendation logic.

[0074] As an example, Figure 2 The process of defining recommended control instructions is shown, such as Figure 2 As shown, this process can be configured based on calculation rules, and may include the following flow: 1) Open the "Intelligent Control Recommended Instruction" configuration page. If the recommended control instruction is not found in the database, it means that no recommended control instruction (such as start-up, stop, reset, maintenance, etc.) has been defined. In this case, the configuration page cannot display the configuration information of the recommended control instruction, and the process terminates abnormally. If the recommended control instruction has been defined, proceed to step 2). 2) Select the recommended control instruction, download the corresponding configuration document, and query the database for the standard control instructions of the target wind turbine generator set according to the configuration document. If no information of the standard control instruction corresponding to the recommended control instruction is found, it means that the corresponding standard control instruction (i.e., the basic details of the control instruction) has not been defined, and the recommended control instruction cannot be configured, and the process terminates abnormally; if the corresponding standard control instruction has been defined, proceed to process 3). 3) In the configuration document, based on the basic details of the corresponding standard control instructions and the corresponding preset recommended logic, configure the information of the recommended control instructions, and proceed to process 4). 4) Import the updated configuration document of the recommended control instruction into the database, which completes the configuration of the recommended control instruction for intelligent control.

[0075] 5) The process ends.

[0076] According to embodiments of this disclosure, before determining the recommended state of a recommended control instruction based on data from the accessed third-party system, cached data of the data acquisition and monitoring control system, and preset recommendation logic of the recommended control instruction, the method further includes: configuring access information for the third-party system to be accessed; accessing the third-party system according to the access information; and obtaining data from the third-party system. Through this embodiment, multiple third-party systems can be accessed and applied to corresponding preset recommendation logic. Therefore, if a new third-party system subsequently accesses the system, only a data interface needs to be provided for access, thereby expanding the data upon which the control depends.

[0077] As an example, recommended control commands for intelligent control can be calculated based on data from sources other than the SCADA system itself. This means it can support data access from third-party systems (such as power prediction systems and health management systems) and can make intelligent control recommendations based on data sources transmitted from these third-party systems. For instance, the health management system can provide health measurement point information and early warning data measurement point information through an SDK (Software Development Kit) interface, which can then be used as calculation data for recommended control commands. The power prediction system can provide an electric field-level power prediction file, which the SCADA system can then acquire and parse to obtain predicted wind speed, predicted temperature, predicted humidity, predicted atmospheric pressure, and predicted wind direction angle data for the next N days, which can then be used as calculation data for recommended control commands.

[0078] Figure 3 The process of configuring third-party system access logic is demonstrated, such as... Figure 3 As shown, the third-party system integration process is as follows: 1) Open the "Third-Party System Access Configuration Interface" and enter the judgment logic; 2) If there is no health management system, the health management system cannot be connected; if there is a health management system, proceed to step 3) to enter the detailed configuration process. 3) Configure the access information of the health management system, which may include, but is not limited to, the following information: the server address of the health management system, the health measurement point information and early warning data measurement point information of the health management system, and the measurement point mapping information of the early warning data measurement point information in the SCADA system (used to cache the acquired early warning measurement point data of the health management system in the real-time memory of the SCADA system). 4) The health management system access process is completed, proceed to step 5), namely, the data access of the power prediction system; 5) If there is no power prediction system, the connection to the power prediction system cannot be completed; if there is a power prediction system, proceed to step 6) to enter the detailed configuration process. 6) Configure the access information of the power prediction system, which may include, but is not limited to, the following information: the IP information of the server where the power prediction file of the power prediction system is located, the SSH (Secure Shell) port information of the server where the power prediction file of the power prediction system is located, the SSH login username of the server where the power prediction file of the power prediction system is located, the SSH login password of the server where the power prediction file of the power prediction system is located, the directory address where the power prediction file of the power prediction system is located, and the configuration of the number of days for parsing future data in the power prediction file; 7) The power prediction system access process is complete; 8) The process ends.

[0079] return Figure 1 In step S103, the recommended control command that is in the recommended state is sent to the target wind turbine generator set, so as to control the target wind turbine generator set based on the sent recommended control command.

[0080] As an example, recommended control commands can be issued manually or intelligently, and this disclosure does not limit the scope of the recommendations.

[0081] As an example, when monitoring personnel (such as operators, supervisors, etc.) select the manual issuance mode for recommended control commands, the recommended control commands that are already in the recommended state need to be manually issued by the monitoring personnel. At this time, when executing the control issuance, a series of verifications can be performed. The specific control issuance process is as follows: 1) Open the intelligent control page. If there is no wind turbine generator set for which a recommended command is to be issued, the recommended control command cannot be issued. If there is a wind turbine generator set for which a recommended command is to be issued, the command can be issued manually, proceeding to step 2). 2) Click the control button associated with the recommended control command to enter process 3). Generally, one wind turbine corresponds to one control button because recommended control commands are issued one by one. 3) Perform the operator verification step, which requires verifying the username and password of the operator who issued the manual control. If the operator's username and password verification fails, the recommended control command cannot be issued; if the operator's username and password verification succeeds, proceed to step 4). 4) The guardian verification step requires a manually controlled guardian to verify the username and password. If the guardian's username and password verification fails, the recommended control command cannot be issued; if the guardian's username and password verification succeeds, the process will proceed to the issuance page and step 5). 5) Enter the corresponding recommended control instruction issuance page. If the recommended control instruction has control parameters, the monitoring personnel need to enter the corresponding control parameters and click the issue button. 6) The process is complete, and the recommended control command has been successfully issued.

[0082] As an example, when monitoring personnel (such as operators, supervisors, etc.) select the intelligent control mode for issuing recommended control commands, the recommended control commands in the recommended state can be issued to the wind turbine generator through intelligent control. Figure 4 The process of intelligent control issuing recommended control commands was demonstrated.

[0083] According to embodiments of this disclosure, after issuing recommended control commands in a recommended state to the target wind turbine generator set, the method further includes: updating the monitoring page. The monitoring page includes a wind turbine generator set display area, a recommended control command display area, and a recommended control command issuance method switching area. This embodiment provides a monitoring page that allows users to monitor different states of recommended control commands and switch between multiple issuance methods, thus enabling monitoring-assisted decision-making and directly replacing the core monitoring interface of centralized monitoring.

[0084] As an example, this embodiment also provides a monitoring function, that is, the provided intelligent control page can be used as the main monitoring page for SCADA system monitoring personnel to monitor equipment data. Figure 5 This demonstrates a smart control page (i.e., the aforementioned monitoring page), such as Figure 5 As shown, this smart control page may contain, but is not limited to, the following areas: 1) Wind Turbine Generator Display Area. This area can group wind turbine generators according to monitoring status dimensions (such as maintenance, fault, warning, shutdown, normal, etc.) and display the number of wind turbine generators containing recommended control commands for the recommended status and the number of wind turbine generators containing recommended control commands for the recommended status under each monitoring status dimension.

[0085] 2) Recommendation Control Instruction Display Area. This area may contain today's recommendation information, which can be displayed as a curve showing the increasing trend of each recommendation control instruction's quantity today; it may also contain a matrix display of recommendation control instructions, which can show detailed information on recommendation control instructions that meet the conditions and are currently recommended.

[0086] 3) Recommended control command issuance mode switching area. This area may contain a switch button for manual / intelligent control issuance. When manual control issuance mode is selected, recommended control commands in the recommended state require the monitoring personnel to manually issue the control command to advance the control. When intelligent control issuance mode is selected, recommended control commands in the recommended state do not require manual execution by the monitoring personnel and can be automatically issued.

[0087] Figure 6 The process flow diagram of the intelligent control page monitoring is shown, such as... Figure 6 As shown, monitoring personnel can open the intelligent control page and view and filter wind turbine generators related to recommended control commands that are in the recommended or recommended status according to the monitoring status dimension and the specified organization. Figure 6 The system is described as a matrix of devices. Monitoring personnel open the intelligent control page, select a specific monitoring status in the wind turbine generator display area on the left, and can then link it to the recommended control command display area on the right, showing only the detailed information of the recommended control commands for the selected monitoring status. Monitoring personnel can also filter by recommended status (e.g., recommended in progress, already recommended), recommended operation type (e.g., start-up, shutdown, reset, maintenance), site, and equipment to view the corresponding recommended control command information on the right. Finally, monitoring personnel can select the appropriate control issuance method (e.g., manual control issuance, intelligent control issuance) to issue recommended control commands to the equipment.

[0088] To facilitate understanding of the above embodiments of this disclosure, the following is in conjunction with... Figures 7 to 9 A systematic explanation will be provided.

[0089] Figure 7 The control command state diagram shown illustrates the state changes of recommended control commands at different stages. This process includes three stages: the control command definition and configuration stage, the control command intelligent calculation stage, and the control command execution and issuance stage.

[0090] 1. Control command definition and configuration stage; Define standard control commands; at this point, the control commands are in the "Standard Control Definition" state. The specific process of defining standard control commands will be discussed in detail later and will not be elaborated on here. When it is necessary to define standard control commands, users can input the required information through the definition interface to complete the configuration of the standard control commands.

[0091] Define recommended control commands; at this point, the control commands are in the "Intelligent Recommendation Definition" state. For intelligent control functions, one or more subsets of the standard control command set can be selected as recommended control commands, which can then be defined. When standard control commands need to be defined, users can input the required information through the definition interface to complete the configuration of the recommended control commands. It should be noted that recommended control commands are control commands that can be recommended and intelligently executed.

[0092] Define the recommended logic for the recommended control commands. At this point, the control commands are in the "Intelligent Recommended Logic Definition" state. For recommended control commands, the field maintenance personnel of the SCADA system can configure the recommended logic according to the control specifications of the system user (such as power generation company specifications, power grid specifications, etc.). Subsequently, after turning on the intelligent control function switch, the recommended control commands for intelligent control can begin. 2. Intelligent calculation stage of control instructions; Based on the recommendation logic configured in the recommendation control instructions, the recommendation control instructions enter the calculation process of the corresponding recommendation state. The following explanation uses an example where the preset recommendation logic contains two sub-recommendation logics, the recommendation state corresponding to the first sub-recommendation logic is described as "in progress" and the recommendation state corresponding to the second sub-recommendation logic is described as "recommended". The recommended control command first performs the calculation of the first sub-recommendation logic, that is, enters the "recommendation in progress" step. If the calculation result indicates failure, the recommended control command does not enter the "recommendation in progress" state, but waits for the next full-scale wind turbine control rule verification loop to recalculate; if the calculation result indicates success, the recommended control command enters the "recommendation in progress" state. The recommended control command in the "Recommended State" state then enters the "Recommended State Calculation" step. If the calculation result indicates failure, it returns to the "Recommended State Calculation" step. If the calculation time exceeds the calculation cycle (i.e., the cycle cycle of full-scale fan control rule verification), it returns to the "Recommended State Calculation" step. If the calculation result indicates success, the recommended control command enters the "Recommended State". After the recommended control command enters the "Recommended State", the intelligent calculation phase of the control command ends.

[0093] 3. Control command execution and issuance stage (this stage has been described in detail above, and will be briefly introduced here); If the monitoring personnel activate the intelligent automatic control mode, the SCADA system will automatically execute and issue the recommended control command in the "Recommended Status" and the recommended control command will enter the "Control Issued Status". If the monitoring personnel activate the manual control mode, the recommended control command will enter the "Control Pending Issued Status". At this time, the monitoring personnel need to manually execute the control issuance action to enter the "Control Issued Status". When the recommended control command finally enters the "Control Issued Status", the entire status life cycle of the recommended control command ends.

[0094] Figure 8 Showing Figure 7 The logical flow of the "intelligent calculation stage of control instructions" is as follows: Figure 8 As shown, the logical flow can be as follows: 1) Enter the recommendation logic operation thread, which is mainly used to calculate the recommendation logic of the recommended control instructions. First, obtain the data source participating in the recommendation logic operation. This data source may include, but is not limited to, cached data of the SCADA system itself (such as real-time data, status data, lock status, tag information, etc. of wind turbine generators) and data sources of third-party systems (such as health data of the health management system, early warning data of the health management system, prediction data of the power prediction system, etc.), and then proceed to process 2). 2) Perform the recommendation logic calculation. The specific calculation process has been described in detail above and will not be elaborated here. After the calculation is completed, proceed to step 3). 3) Determine the result of the operation. If the result is false (i.e., the result is no), proceed to step 5; if the result is true (i.e., the result is yes), proceed to step 4. 4) Determine if a preset duration is set. If a preset duration is set, cache the information of the recommendation control instruction (such as instruction definition, instruction recommendation logic, etc.) in the "Not Cached for Preset Duration" as temporary cache data. If no preset duration is set, cache the information of the recommendation control instruction in the "Instruction in Recommendation" as cached data in the recommendation process, or cache it in the "Recommended Instruction" as cached data in the recommended process. Where it is cached depends on which sub-recommendation logic is being processed. The specific processing procedure has been discussed in detail above and will not be elaborated here. The operation of the preset duration thread has also been discussed in detail above and will not be elaborated here. 5) Determine whether the information of the recommended control instruction already exists in the "Recommended Instruction Cache" and / or "Recommended Instruction Cache". If it exists in either cache, clear the information of the recommended control instruction from that cache; if it does not exist in either cache, return to process 1) and repeat the calculation.

[0095] Figure 9 This showcases a list of services provided by the intelligent control functions of the SCADA system, including... Figure 9 The equipment mentioned is a wind turbine generator set. It should be noted that this disclosure is not limited to... Figure 9 The services shown.

[0096] The above embodiments of this disclosure can connect to multiple external systems. After collecting data from external systems, the data from the data sources and SCADA system are preprocessed (e.g., processed, aggregated, or recalculated). Then, the controlled object (i.e., the wind turbine generator) is controlled according to the configured recommendation logic. This allows the recommendation logic to be calculated by combining external data sources such as environmental data and future prediction data. Moreover, the recommendation logic of this disclosure can be customized, enabling diverse intelligent control logic.

[0097] In this disclosure, the node near the wind turbine generator where the SCADA system performs data acquisition and control execution is the front-end gateway system. It should be noted that this disclosure is not limited to a self-developed front-end gateway system; any front-end system with wind turbine data acquisition and control distribution functions can be used as a substitute.

[0098] Figure 10 This is a block diagram illustrating the control system of a wind turbine generator set according to an embodiment of the present disclosure, such as... Figure 10 As shown, the system includes a presentation service 100, an application service 102, and an execution gateway 104, wherein... Presentation Service 100 selects recommended control commands from the standard control commands of the wind turbine generator set. The recommended control commands are standard control commands that can be intelligently recommended. Application Service 102 determines the recommendation status of each recommended control command based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control command. The preset recommendation logic is determined by operation factors and operators in a preset format. Execution Gateway 104 sends the recommended control commands in the recommended status to the target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control commands.

[0099] According to embodiments of this disclosure, the preset recommendation logic includes multiple sub-recommendation logics. The application service 102 selects the computational data required by the sub-recommendation logic from the data and cached data of the third-party system for each sub-recommendation logic, and inputs the computational data into the sub-recommendation logic to obtain the corresponding recommendation result. In response to the success indication of the recommendation results of all sub-recommendation logics, the recommendation control instruction is determined to enter the recommended state.

[0100] According to embodiments of this disclosure, application service 102 inputs computational data into the sub-recommendation logic according to the preset format of the computational factors in the sub-recommendation logic to obtain the recommendation expression corresponding to the sub-recommendation logic; the recommendation expression is split into sub-expressions by brackets; the sub-expressions are split into logical factor expressions by logical operators; the logical factor expressions are split into relational factor expressions by relational operators; arithmetic operations are performed on each relational factor expression to obtain relational operation results; logical operations are performed on each logical factor expression based on the relational operation results to obtain logical operation results; and operations are performed on each sub-expression based on the logical operation results to obtain the recommendation result corresponding to the sub-recommendation logic.

[0101] According to an embodiment of this disclosure, application service 102, in response to a successful recommendation result indication of the i-th sub-recommendation logic in the preset recommendation logic, determines that the recommendation control instruction enters the i-th recommendation state, and moves the recommendation control instruction from the (i-1)-th recommendation state cache to the i-th recommendation state cache, where i = 1, 2, ..., N-1, N is the number of multiple sub-recommendation logics, and N is a positive integer; in response to a successful recommendation result indication of the N-th sub-recommendation logic in the preset recommendation logic, determines that the recommendation control instruction enters the recommended state, and moves the recommendation control instruction from the (N-1)-th recommendation state cache to the recommended state cache.

[0102] According to an embodiment of this disclosure, in response to a failure of the recommendation result indication in any of the sub-recommendation logics in the preset recommendation logic, application service 102 deletes the recommendation control instruction from all recommendation state caches and determines that the recommendation control instruction has not entered the recommended state.

[0103] According to an embodiment of this disclosure, application service 102 performs the following processing for each of the multiple sub-recommendation logics: periodically inputting the corresponding computational data of the sub-recommendation logic into the sub-recommendation logic within a preset time period; in response to the recommendation result of the sub-recommendation logic indicating success in each period, finally determining that the recommendation result of the sub-recommendation logic indicates success.

[0104] According to embodiments of this disclosure, the system further includes a database. Before determining the recommended status of a recommended control instruction based on data from an accessed third-party system, cached data from a data acquisition and monitoring control system, and preset recommendation logic for recommended control instructions, application service 102 downloads a configuration file for the recommended control instruction from the database; uses the configuration file to query the standard control instructions for the target wind turbine generator set in the database to obtain information on the standard control instructions corresponding to the recommended control instruction; and configures the recommended control instruction based on the information on the standard control instructions corresponding to the recommended control instruction, the preset recommendation logic, and the configuration file.

[0105] According to embodiments of this disclosure, before determining the recommendation status of a recommendation control instruction based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and preset recommendation logic of the recommendation control instruction, application service 102 configures access information for the third-party system to be accessed; accesses the third-party system according to the access information, and obtains data from the third-party system.

[0106] According to an embodiment of this disclosure, after a recommended control command in a recommended state is sent to the target wind turbine generator set, a service 100 update monitoring page is displayed. The monitoring page includes a wind turbine generator set display area, a recommended control command display area, and a recommended control command sending method switching area.

[0107] To facilitate understanding of the above control system, the following will be combined with... Figure 11 A systematic explanation will be provided.

[0108] Figure 11 This paper presents a deployment model for a control system capable of intelligent control. This model is a sub-functional module of a SCADA system, specifically composed of several nodes including a presentation service, an application service, an execution gateway, and a database server. The presentation service is responsible for storing static page files; the application service is responsible for the computation of backend recommendation logic and the provision of data; the execution gateway, as a key component of IoT, communicates with the specific wind turbine generator and is responsible for issuing and executing specific control commands; and the database service is responsible for storing relevant configuration data for intelligent control. The database can be a PG-based Highgo database or other relational databases; this disclosure does not limit its use.

[0109] The preset recommendation logic of the recommendation control instructions is carried on the application service. Therefore, the application service is the core calculation module, used to calculate whether the recommendation control instructions meet the mathematical formula of the preset recommendation logic. The specific modeling database table structure of the recommendation logic can be as follows, which is not limited in this disclosure:

[0110] It should be noted that the application service is the main logic processing node for intelligent control, and may include, but is not limited to, the following components: The data routing component is primarily responsible for receiving, processing, and distributing data requests sent by the presentation service. The data memory component is mainly used to store the source data and results of intelligent control calculations. The recommendation logic operation component is a core component of the application service, mainly used for recommendation logic operations of recommendation control instructions; The computational data memory component is mainly used to store temporary data during the recommendation logic operation process of recommendation control instructions; The control delivery module component is mainly used to communicate with the execution gateway node to deliver recommended control commands; The third-party system client component is mainly used to communicate with third-party systems (such as health management systems and power prediction systems) to obtain and parse the data sources of the third-party systems.

[0111] It should be noted that the application service is the core service module of the centralized control system, mainly responsible for acquiring data from third-party systems, acquiring persistent configuration data, and intelligently recommending and calculating control commands; the presentation service is the front-end static resource storage and parsing service module of the centralized control system, used for displaying front-end pages; the database service is the persistent service module of the centralized control system, used for storing configuration data; the power prediction service is a third-party system used to provide meteorological, early warning, and forecast data for the intelligent control of the centralized control system; the health management service is a third-party system used to provide equipment health data for the intelligent control of the centralized control system; and the execution gateway is the front-end service module of the centralized control system, connected to the wind turbine generator set, used to parse control messages and issue actual control commands to the wind turbine generator set using the common protocol IEC104 or Modbus protocol. In summary, this disclosure collects data from multiple external systems (such as health management systems, power prediction systems, and wind turbine front-end gateways), enabling analysis of information such as the controlled object's (wind turbine's) own operational data, the wind turbine's health data and early warning data, and the meteorological and forecast data of the wind turbine's location. This allows for the construction of a complete and powerful intelligent control analysis model. Furthermore, if new external systems are integrated in the future, they can be extended simply by providing data interfaces to the SCADA system. Therefore, this solves the problems of centralized management and scalability of data sources in intelligent control. This disclosure also designs and implements a recommendation logic engine based on arithmetic, logical, and relational operations. This engine can dynamically handle complex combinations of conditions and automatically execute preset decision logic. Compared to traditional fixed thresholds or simple conditional judgments, it provides greater flexibility and adaptability, and can cope with more diverse scenarios and needs. Therefore, it also solves the problem of scalability of the recommendation logic in intelligent control models. This disclosure integrates intelligent control into a centralized SCADA system, thereby providing a visually appealing monitoring interface. Users can monitor different stages of the intelligent control commands through a large screen, enabling both intelligent manual control and intelligent automatic control recommendations. This achieves monitoring-assisted decision-making and can directly replace the core monitoring interface of the SCADA system. Therefore, it also solves the problem of intelligent monitoring in SCADA systems.

[0112] Through the above embodiments, this disclosure can produce at least the following beneficial technical effects: 1. Reduced operating costs: Through automated monitoring and intelligent decision-making, the reliance on manual monitoring can be reduced, thus lowering labor costs. The system can automatically identify problems and perform optimization operations, such as adjusting the working status of wind turbine generators according to actual needs, reducing unnecessary human intervention and saving maintenance and operating costs.

[0113] 2. Efficiency Improvement: Intelligent control can quickly respond to system changes and automatically adjust strategies to optimize energy output. For example, it can maximize resource utilization when wind energy is abundant or adjust energy storage strategies when demand is low, thereby improving overall energy utilization efficiency and production benefits.

[0114] 3. Preventive maintenance: Through real-time data analysis, the system can identify potential faults in advance, arrange preventive maintenance, avoid long-term downtime losses caused by sudden failures, extend the life of wind turbine generators, and reduce maintenance costs and economic losses caused by production interruptions.

[0115] 4. Resource optimization and allocation: After successful recommendation and logic matching, the automatically issued control commands help balance the load among different new energy power plants, optimize resource allocation, improve overall power generation efficiency and grid stability, and indirectly create greater economic benefits.

[0116] 5. Decision Support: The intelligent control recommendations combined with manual control modes can assist on-site monitoring personnel in making decisions on control actions in complex scenarios, freeing up a significant amount of their energy from deciding on the timing of control actions.

[0117] 6. Environmental and social benefits: The intelligent control function of the centralized monitoring system is a relatively cutting-edge business. This invention has been implemented in the SCADA system, which has improved the product's competitiveness.

[0118] According to embodiments of the present disclosure, a computer-readable storage medium for storing instructions is provided, wherein when the instructions are executed by at least one computing device, they cause at least one computing device to perform a wind turbine generator control method as described in any of the above embodiments.

[0119] According to embodiments of the present disclosure, a system is provided that includes at least one computing device and at least one storage device storing instructions, wherein the instructions, when executed by the at least one computing device, cause the at least one computing device to perform a wind turbine generator control method as described in any of the above embodiments.

[0120] According to embodiments of this disclosure, a computer program product is provided, including computer instructions that, when executed by a processor, implement the control method for a wind turbine generator as described above.

[0121] According to embodiments of this disclosure, a wind turbine generator set is provided, including the control device for the wind turbine generator set as described above.

[0122] While some embodiments of this disclosure have been shown and described, those skilled in the art will understand that modifications may be made to these embodiments without departing from the principles and spirit of this disclosure, which are defined by the claims and their equivalents.

Claims

1. A control method for a wind turbine generator set, characterized in that, include: Select the recommended control commands from the standard control commands for wind turbine generators; For each recommended control instruction, the recommended state of the recommended control instruction is determined based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction. The preset recommendation logic is determined by operation factors and operators in a preset format. Recommended control commands that are in the recommended state are sent to the target wind turbine generator set to control the target wind turbine generator set based on the sent recommended control commands.

2. The control method as described in claim 1, characterized in that, The preset recommendation logic includes multiple sub-recommendation logics, among which, The method for determining the recommendation status of the recommendation control instruction based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and preset recommendation logic of the recommendation control instruction includes: For each of the multiple sub-recommendation logics, the computational data required by the sub-recommendation logic is selected from the data of the third-party system and the cached data, and the computational data is input into the sub-recommendation logic to obtain the corresponding recommendation result; If all sub-recommendation logics indicate success, the recommendation control instruction is determined to enter the recommended state.

3. The control method as described in claim 2, characterized in that, The step of inputting the computational data into the sub-recommendation logic to obtain the corresponding recommendation result includes: According to the preset format of the operation factors in the sub-recommendation logic, the operation data is input into the sub-recommendation logic to obtain the recommendation expression corresponding to the sub-recommendation logic; The recommended expression is split into sub-expressions by using brackets as units; The subexpression is split into logical factor expressions by using logical operators as units; The logical factor expression is split into relational factor expressions by using relational operators as units; Perform arithmetic operations on each relation factor expression to obtain the relation operation results; Based on the relational operation results, logical operations are performed on each logical factor expression to obtain the logical operation results; Based on the results of the logical operations, each sub-expression is calculated to obtain the recommendation result corresponding to the sub-recommendation logic.

4. The control method as described in claim 2, characterized in that, The response that all sub-recommendation logics indicate success, and the determination that the recommendation control instruction has entered the recommended state, includes: In response to the successful recommendation result indication of the i-th sub-recommendation logic in the preset recommendation logic, it is determined that the recommendation control instruction enters the i-th recommendation state, and the recommendation control instruction is moved from the (i-1)-th recommendation state cache to the i-th recommendation state cache, where i = 1, 2, ..., N-1, N is the number of the multiple sub-recommendation logics, and N is a positive integer; In response to the successful recommendation result indication of the Nth sub-recommendation logic in the preset recommendation logic, the recommendation control instruction is determined to have entered the recommended state, and the recommendation control instruction is moved from the (N-1)th recommendation state cache to the recommended state cache.

5. The control method as described in claim 4, characterized in that, The method for determining the recommendation status of the recommendation control instruction based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and preset recommendation logic of the recommendation control instruction further includes: In response to the failure of the recommendation result indication in any of the sub-recommendation logics in the preset recommendation logic, the recommendation control instruction is deleted from all recommendation state caches, and it is determined that the recommendation control instruction has not entered the recommended state.

6. The control method as described in claim 2, characterized in that, The step of determining that the recommendation control instruction has entered the recommended state after all the recommendation results of the sub-recommendation logic indicate success also includes: For each of the multiple sub-recommendation logics, the following processing is performed: The corresponding computational data of the sub-recommendation logic is periodically input into the sub-recommendation logic within a preset time period. In response to the success of the recommendation result of the sub-recommendation logic in each cycle, the recommendation result of the sub-recommendation logic is finally determined to be successful.

7. The control method as described in claim 1, characterized in that, Before determining the recommendation status of the recommended control instruction based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction, the method further includes: Download the configuration file for the recommended control instructions from the database; The configuration file is used to query the standard control commands of the target wind turbine generator set in the database to obtain information on the standard control commands corresponding to the recommended control commands. The recommended control instruction is configured based on the information of the standard control instruction corresponding to the recommended control instruction, the preset recommendation logic, and the configuration file.

8. The control method as described in claim 1, characterized in that, Before determining the recommendation status of the recommended control instruction based on data from the accessed third-party system, cached data from the data acquisition and monitoring control system, and the preset recommendation logic of the recommended control instruction, the method further includes: Configure the access information for the third-party systems to be connected; Access the third-party system according to the access information, and obtain data from the third-party system.

9. The control method as described in claim 1, characterized in that, After issuing the recommended control commands, which are in the recommended state, to the target wind turbine, the following is also included: Update the monitoring page, which includes a wind turbine generator display area, a recommended control command display area, and a recommended control command issuance method switching area.

10. A control system for a wind turbine generator set, characterized in that, The control system includes a presentation service, an application service, and an execution gateway, wherein... The presentation service selects recommended control commands from the standard control commands of the wind turbine generator set, wherein the recommended control commands are standard control commands that can be intelligently recommended. The application service, for each recommendation control instruction, determines the recommendation status of the recommendation control instruction based on the data from the accessed third-party system, the cached data of the data acquisition and monitoring control system, and the preset recommendation logic of the recommendation control instruction. The preset recommendation logic is determined by operation factors and operators in a preset format. The execution gateway sends recommended control commands that are in the recommended state to the target wind turbine generator set, so as to control the target wind turbine generator set based on the sent recommended control commands.

11. A computer-readable storage medium for storing instructions, characterized in that, When the instruction is executed by at least one computing device, it causes the at least one computing device to perform the control method for the wind turbine generator as described in any one of claims 1 to 9.

12. A system comprising at least one computing device and at least one storage device for storing instructions, characterized in that, When the instruction is executed by the at least one computing device, it causes the at least one computing device to perform the control method for the wind turbine generator as described in any one of claims 1 to 9.

13. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the control method for the wind turbine generator set as described in any one of claims 1 to 9.

14. A wind turbine generator set, characterized in that, Including the control system of the wind turbine generator set as described in claim 10.

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