A method and system for multi-machine coordinated fast frequency support of a deep-sea wind farm

Abstract

The application belongs to the field of wind power generation rapid frequency support, and specifically discloses a deep-sea wind farm multi-machine cooperative rapid frequency support method and system, which comprises the following steps: representing the communication topology of the wind farm by using algebraic graph theory, and obtaining the Laplacian matrix in the undirected graph; considering the rotor speed safety constraint of the wind turbine, combining the rotor speed of the wind turbine, and constructing the consistency state factor of the wind turbine; constructing a dynamic process model of the node state, determining the control protocol of the node state based on the consistency state factor of the wind turbine and the Laplacian matrix of the undirected graph; and applying the control protocol of the node state to the active current inner loop of the wind turbine, so as to realize the cooperative frequency support control of the deep-sea wind farm on the power grid. The application can fully exert the frequency support capability of the wind farm.

Description

Technical Field

[0001] This application belongs to the field of rapid frequency support for wind power generation, and more specifically, relates to a method and system for rapid frequency support for multi-machine coordinated operation in deep-sea wind farms. Background Technology

[0002] System inertia is a fundamental requirement for the safe operation of the power grid. With the continuous large-scale integration of wind power, system inertia is constantly decreasing, and the risk of frequency instability is increasing. Low inertia has become a stumbling block in building a new type of power system. Offshore wind power, as a typical wind power generation scenario, has broad development prospects and a huge installed capacity, serving as a large "power bank" supporting the power grid. Enabling it to have frequency support capabilities is a crucial way to solve the low inertia problem of new power systems. Several power grid accidents have already occurred due to insufficient frequency support capabilities; therefore, ensuring that offshore wind farms possess frequency support capabilities is urgently needed.

[0003] Regarding frequency support control in wind farms, existing wind farm cluster control strategies can be broadly categorized into two types based on their control methods: centralized and distributed cluster control. Under centralized cluster control, the wind farm integrates received system scheduling commands and operational information such as wind speed. The frequency controller then obtains the active power setpoint for frequency support, and the turbine power allocation module distributes this setpoint to each turbine according to its operating characteristics and a specific allocation strategy, maximizing the wind farm's frequency support capability. However, existing centralized cluster control treats the wind farm as a single turbine, failing to consider the differences in frequency support capabilities among different turbines. This can easily lead to turbines exceeding speed limits and becoming disconnected from the grid, even causing the grid frequency to deteriorate further than when the wind farm does not participate in frequency regulation. Under distributed cluster control, each wind turbine only needs to communicate with its neighboring turbines to determine its own control objectives, thus eliminating the need for communication with the control center. The goal of distributed control is to match the supporting power provided by each wind turbine with its own supporting capacity, with wind turbines with stronger supporting capacity outputting more power and those with weaker supporting capacity outputting less power. However, due to the lack of communication with the control center, this method suffers from problems such as long signal interaction response time and poor convergence. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this application is to provide a method and system for rapid frequency support for multi-turbine coordination in deep-sea wind farms. This aims to solve the problem that in existing wind farm cluster control methods, centralized cluster control treats the wind farm as a single unit, failing to consider the differences in frequency support capabilities of different wind turbine units. This can easily lead to turbine speed exceeding limits and loss of synchronization with the grid, or even cause the grid frequency to deteriorate further than when the wind farm does not participate in frequency regulation.

[0005] To achieve the above objectives, in a first aspect, this application provides a method for rapid frequency support of multi-machine coordination in deep-sea wind farms, comprising the following steps:

[0006] Step S1: Use algebraic graph theory to characterize the communication topology of the wind farm and obtain the Laplace matrix in the undirected graph; where a node in the undirected graph represents a wind turbine in the wind farm; nodes with communication channels are neighbors.

[0007] Simultaneously considering the safety constraints of the fan's rotor speed, and combining the fan's rotor speed, a consistency state factor for the fan is constructed.

[0008] Step S2: Construct a dynamic process model of node states. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, determine the control protocol of the node states so that the consistency state factor of the wind turbine converges to the same value.

[0009] Step S3: Apply the node state control protocol to the active current inner loop of the wind turbine to achieve coordinated frequency support control of the grid by the deep-sea wind farm.

[0010] More preferably,

[0011] The Laplace matrix of the undirected graph in step S1 is ;in, Adjacency matrix ; Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. Pointing to node The directed edge, ;otherwise, ; } This represents the sum of the edge sets consisting of ordered pairs of corresponding nodes; Represents a finite and non-empty set of nodes; n The number of nodes; Represents the real number field.

[0012] More preferably, the consistency state factor of the wind turbine in step S1 is:

[0013]

[0014] in, For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ; This is the minimum rotor speed of the fan; This is the maximum rotor speed of the fan.

[0015] More preferably, the dynamic process model of the node state in step S2 is as follows:

[0016]

[0017]

[0018] in, For the first i Control protocol for typhoon generator consistency state factor; The uniformity convergence coefficient; n Number of nodes; adjacency matrix ; Representing an edge The weights; Represents the real number field.

[0019] More preferably, in step S3, the q-axis reference value of the inner loop of the active current of the wind turbine... for:

[0020]

[0021] in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases .

[0022] Secondly, this application provides a multi-machine coordinated fast frequency support system for deep-sea offshore wind farms, comprising:

[0023] The adjacency matrix acquisition module is used to represent the communication topology of a wind farm using algebraic graph theory and obtain the adjacency matrix in an undirected graph. In this module, a node in the undirected graph represents a wind turbine in the wind farm, and nodes with communication channels are neighbors.

[0024] The consistency state factor construction module is used to construct the Laplace matrix of an undirected graph based on the adjacency matrix of the undirected graph; at the same time, considering the rotor speed safety constraint of the wind turbine, the consistency state factor of the wind turbine is constructed in combination with the rotor speed of the wind turbine.

[0025] The control protocol construction module is used to build a dynamic process model of the node state. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, it determines the control protocol of the node state so that the consistency state factor of the wind turbine converges to the same value.

[0026] The frequency support control module is used to apply the control protocol of the node status to the active current inner loop of the wind turbine, so as to realize the coordinated frequency support control of the deep-sea wind farm to the power grid.

[0027] More preferably, the Laplace matrix of the undirected graph in the consistency state factor construction module is: ;in, Adjacency matrix ; Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. Pointing to node The directed edge, ;otherwise, ; } This represents the sum of the edge sets consisting of ordered pairs of corresponding nodes; Represents a finite and non-empty set of nodes; n The number of nodes; Represents the real number field.

[0028] More preferably, the consistency state factor of the wind turbine in the consistency state factor construction module is:

[0029]

[0030] in, For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ; This is the minimum rotor speed of the fan; This is the maximum rotor speed of the fan.

[0031] More preferably, the dynamic process model of node states in the control protocol construction module is as follows:

[0032]

[0033]

[0034] in, For the first i Control protocol for typhoon generator consistency state factor; The uniformity convergence coefficient; n Number of nodes; adjacency matrix ; Representing an edge The weights; Represents the real number field.

[0035] More preferably, the q-axis reference value of the active current inner loop of the wind turbine in the frequency support control module... for:

[0036]

[0037] in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases .

[0038] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or a further preferred implementation of the first aspect.

[0039] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or a further preferred implementation of the first aspect.

[0040] Fifthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or a further preferred implementation of the first aspect.

[0041] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0042] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0043] This application provides a method for rapid frequency support of multiple turbines in deep-sea wind farms. The method constructs a consistency state factor of the wind turbine that reflects the frequency support capability of the wind turbine, considering the safety constraint of the rotor speed of the wind turbine. The control protocol of the node state is determined to ensure that the consistency state factor of the wind turbine converges to the same value, so that the frequency support power of the wind turbine can be matched with the frequency regulation capability. Therefore, this application can give full play to the frequency support capability of the wind farm.

[0044] This application provides a method for rapid frequency support of multi-turbine coordination in deep-sea wind farms. Since the consistency state factor of the wind turbine is constructed only using the rotor speed of the wind turbine unit ( Therefore, using only the kinetic energy of the wind turbine to quickly support the grid frequency does not affect the power generation efficiency of the wind turbine under normal operating conditions and does not require any additional energy storage system. Thus, the multi-machine coordinated rapid frequency support method for deep-sea wind farms provided in this application has high economic efficiency.

[0045] This application provides a method for rapid frequency support of multi-machine coordination in deep-sea wind farms, which applies the control protocol of node status to the active current inner loop of the wind turbines. for The station consistency coordination component in the frequency drop When the frequency increases The method of multi-machine coordinated fast frequency support for deep-sea wind farms provided in this application is easy to implement and has high feasibility. It only introduces a control branch in the inner loop of the active current of the wind turbine and does not change the vector control structure widely used in wind power generation. Attached Figure Description

[0046] Figure 1 This is one of the flowcharts illustrating the multi-machine coordinated rapid frequency support method for offshore wind farms provided in this application embodiment;

[0047] Figure 2 This is the main circuit topology of the direct-drive fan provided in the embodiments of this application;

[0048] Figure 3 This is the communication topology for offshore wind farms provided in the embodiments of this application;

[0049] Figure 4(a) is a comparison of the simulation results of the power grid frequency change curves after a sudden drop in power grid frequency, without any control strategy, using the traditional method, and using the method of this application, provided in the embodiments of this application.

[0050] Figure 4(b) is a simulation comparison of the output power change curves of the first, sixth and twenty-first wind turbines after a sudden drop in grid frequency, without any control strategy, using the traditional method and using the method of this application.

[0051] Figure 4(c) Comparison of simulation results of the rotor angular velocity change curves of the first, sixth and twenty-first wind turbines after a sudden drop in grid frequency, without any control strategy, using the traditional method and using the method of this application.

[0052] In Figures 4(a), 4(b), and 4(c), the solid lines represent simulation results without any control method, the dotted lines represent simulation results using traditional methods, and the dashed lines represent simulation results of this application.

[0053] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] In this article, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The symbol " / " in this article indicates that the related objects are in an "or" relationship; for example, A / B means A or B.

[0056] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects.

[0057] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0058] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more.

[0059] The embodiments of this application are described below with reference to the accompanying drawings.

[0060] This application enables deep-sea wind farms to provide frequency support when frequency disturbances are detected, with a fast response speed, significantly improving grid frequency stability. Specifically, firstly, each wind turbine in the wind farm is considered as a node in a graph, and the communication topology of the wind farm is represented using algebraic graph theory; secondly, the Laplace matrix of the graph is calculated to determine the consistency state factor of the nodes; then, a dynamic process model of the node state is established to determine the control protocol of the node state; finally, the control protocol is applied to the active current inner loop of the wind turbine to achieve coordinated frequency support control of the grid by the deep-sea wind farm. The offshore wake effect is strong, the operating conditions of wind turbines are complex, and their frequency support capabilities vary. Existing research generally adopts centralized control, equating the wind farm with a single turbine, without considering the differences in frequency support capabilities of different wind turbines. This can easily lead to turbine speed exceeding limits and loss of synchronization with the grid, and may even cause the grid frequency to deteriorate further than when the wind farm does not participate in frequency regulation. The multi-turbine coordinated frequency support control method for offshore wind farms proposed in this application can match the frequency support power of wind turbine units with their frequency regulation capabilities, thus fully leveraging the frequency support capabilities of the wind farm.

[0061] Example 1

[0062] like Figure 1 As shown in the figure, this application provides a method for rapid frequency support of multi-turbine collaboration in deep-sea wind farms, which specifically includes the following steps:

[0063] Step S1: Use algebraic graph theory to characterize the communication topology of the wind farm and obtain the Laplace matrix in the undirected graph; where a node in the undirected graph represents a wind turbine in the wind farm; nodes with communication channels are neighbors.

[0064] Simultaneously considering the safety constraints of the fan's rotor speed, and combining the fan's rotor speed, a consistency state factor for the fan is constructed.

[0065] Step S2: Construct a dynamic process model of node states. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, determine the control protocol of the node states so that the consistency state factor of the wind turbine converges to the same value.

[0066] Step S3: Apply the node state control protocol to the active current inner loop of the wind turbine to achieve coordinated frequency support control of the grid by the deep-sea wind farm.

[0067] The strong wake effect at sea leads to complex operating conditions for wind turbines, with varying frequency support capabilities. Existing research generally employs centralized control, treating wind farms as single turbines, without considering the differences in frequency support capabilities among different wind turbines. This can easily lead to turbines exceeding speed limits and losing synchronization with the grid, or even worsening the grid frequency compared to when the wind farm does not participate in frequency regulation. Therefore, this application provides a multi-turbine coordinated frequency support control method for deep-sea wind farms, which can match the frequency support power of wind turbines with their frequency regulation capabilities, fully utilizing the frequency support capacity of the wind farm.

[0068] It should be noted that the fan is either a doubly-fed fan or a direct-drive fan. The technical solution of this application will be specifically illustrated below using a direct-drive fan as an example.

[0069] like Figure 2 The diagram shows the main circuit topology of a direct-drive fan. Figure 2 In this context, PMSG represents a direct-drive wind turbine, MSC represents a machine-side converter, GSC represents a grid-side converter, and PLL represents a phase-locked loop. Indicates the rotor angular velocity. Indicates the rotor rotation angle. This represents the phase angle signal output by the frequency-locked loop. This indicates the mechanical power input to the direct-drive fan. This represents the DC-side capacitor voltage. This indicates the electromagnetic power output of the direct-drive fan. This indicates the output voltage of the direct-drive fan. This indicates the output current of the direct-drive fan. This indicates the output filter inductor of the grid-side converter. E The internal potential of the grid-side converter GSC is defined as follows: , This represents the reactive power output of the direct-drive wind turbine to the power grid. This indicates the line reactance connecting the direct-drive wind turbine to the power grid. This represents the grid voltage. In generator-side converter control, This represents the given value of the rotor angular velocity. This indicates a PI controller for rotor angular velocity. The stator current q-axis component output by the rotor angular velocity PI controller. The stator current q-axis component is the stator current in the single-machine inertia response. The q-axis component of the stator current for station consistency and coordinated control. This represents the given value of the stator current q-axis. This represents the given value of the stator current d-axis. This represents the given modulation voltage for the generator-side converter. In grid-side converter control... This indicates the setpoint value of the DC-side capacitor voltage. This indicates a DC voltage PI controller. The d-axis setpoint represents the output current of the direct-drive fan. This represents the reactive power setpoint output by the direct-drive wind turbine to the power grid. PI Q This indicates a reactive power PI controller. The q-axis setpoint represents the output current of the direct-drive fan. This represents the given modulation voltage of the grid-side converter.

[0070] like Figure 3 The diagram shows the communication topology of a deep-sea wind farm. Figure 3 The deep-sea wind farm in the middle includes 25 wind turbines, and the electricity generated by each wind turbine is collected to the offshore AC bus through a power collection system. Figure 3 The arrows in the text indicate communication channels;

[0071] More preferably, step S1 treats each wind turbine in the wind farm as a node in an undirected graph, and uses algebraic graph theory to characterize the communication topology of the wind farm, specifically as follows:

[0072] A picture G = ( V , E ) by node set V Sum of edges E It consists of two parts, among which Represents a finite and non-empty set of nodes. The sum of the edge sets consisting of ordered pairs of corresponding nodes; nodes v i The set of neighbor nodes is represented as Each wind turbine in the wind farm is considered a node in the graph, and the communication channel between wind turbines is considered an edge of the node; if there is a communication channel between two wind turbines, the nodes they represent are called neighbors. Representation diagram G The adjacency matrix, where Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. point to The directed edge, i.e. ;otherwise ; This setting , ; , If the graph is undirected, then it is an undirected graph; an undirected graph G The path in the text refers to the path from the node. v i Start by traversing a set of different edges to the node. The ending edge set sequence; if node and If a path exists, then the node and It is connected; if it is an undirected graph G If there is a path between any two nodes in the graph, then the graph... G It is connected; in this embodiment, n is 25, and the communication topology of the wind farm is an undirected graph;

[0073] More preferably, in step S1, the Laplacian matrix of the graph is calculated to determine the consistency state factor of the nodes in the graph, specifically as follows:

[0074] Undirected graph G Laplacian matrix The definition is as follows:

[0075]

[0076] Obtain an undirected graph G After obtaining the Laplacian matrix, solve for its eigenvalues ​​for a connected undirected graph. G Its Laplacian matrix L It is positive semidefinite and has only one eigenvalue of 0.

[0077] Frequency support essentially involves increasing power output when the frequency drops and decreasing power output when the frequency rises. For wind turbines, the power generated by rapid frequency support originates from the rotor's kinetic energy, which is closely related to the turbine's rotor speed. x i Represents the first in the topological graph i The consistency state factor of a typhoon turbine must also be related to its rotational speed; since the rotor motion equation of the turbine is:

[0078]

[0079] in, The mechanical power input to the fan. The electromagnetic power output by the fan. This refers to the rotor inertia of the fan. This refers to the rotor speed of the fan;

[0080] Integrating the rotor motion equations of the wind turbine yields:

[0081]

[0082] in, Let be the initial rotor speed of the wind turbine; therefore, the rotor kinetic energy used for frequency support is related to the square difference between the current speed and the initial speed; meanwhile, because there are safety constraints on the rotor speed, the lower limit is generally . The upper limit is Therefore, in this application, the first... i The consistency state factor of the typhoon generator is:

[0083]

[0084] Among them, the consistency state factor is used to reflect the frequency support capability of the wind turbine; For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ;

[0085] More preferably, step S2 establishes a dynamic process model of the node state and determines the control protocol for the node state, specifically as follows:

[0086] The change in the consistency state factor of the wind turbine can be described by a first-order dynamic process. Therefore, this application establishes the following dynamic process model for the node state:

[0087]

[0088] in, For the first i Control protocol for typhoon generator consistency state factor; if the first i Typhoon machine and the j If the typhoon generator has a communication channel, then the weight... ;otherwise The purpose of the control protocol is to ensure that the consistency state factors of the wind turbines within the wind farm converge to the same value; therefore... for:

[0089]

[0090] in, The uniformity convergence coefficient ranges from 0 to 4; the control protocol of the entire wind farm is expressed in matrix form as follows:

[0091]

[0092] Because of the Laplacian matrix L A It is positive semi-definite and has only one eigenvalue of 0, therefore Since there are no eigenvalues ​​in the positive half-plane, the system is asymptotically stable, and the control protocol enables the wind turbine consistency state factor to converge to the same value.

[0093] More preferably, step S3 applies the control protocol to the active current inner loop of the wind turbine to achieve coordinated frequency support control of the grid by the deep-sea wind farm, specifically as follows:

[0094] For the first in the wind farm i Typhoon machines, such as Figure 2 As shown in the control diagram of the machine-side converter, the q-axis reference value of its inner current loop is... It consists of three parts, and can be represented as:

[0095]

[0096] in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases ; It can be represented as:

[0097]

[0098] in, f The grid frequency measured at the grid connection point, and the droop factor. The value range is 0~3; the proportionality coefficient The value range is 0 to 3;

[0099] Since this application utilizes only the rotor kinetic energy of the wind turbine to quickly support the grid frequency, it does not affect the power generation efficiency of the wind turbine under normal operating conditions and does not require any additional energy storage system. Therefore, the method provided by this application is highly economical. Since the method provided by this application only introduces a control branch in the inner loop of the active current of the wind turbine and does not change the vector control structure widely used in wind power generation, it is easy to implement and has high feasibility. Since the multi-machine coordinated frequency support control method for deep-sea wind farms proposed in this application can match the frequency support power of the wind turbine with its frequency regulation capability, it can fully utilize the frequency support capability of the wind farm.

[0100] To better illustrate the effectiveness of the method provided in this application, a simulation study was conducted using a wind farm consisting of 25 typical 8MW direct-drive wind turbines as an example. Before the fault occurred, the system power was in a balanced state, and the system frequency was the rated frequency of 50Hz. At 45 seconds, the system load suddenly increased by 50MW. Figures 4(a), 4(b), and 4(c) are comparison diagrams of the simulation effects of the method provided in this application after a sudden drop in grid frequency, without any control strategy, using the traditional method, and using the method of this application. In Figure 4(a), the solid line represents the change curve of grid frequency without any strategy; in Figure 4(b), the solid line represents the change curve of output power of the first, sixth, and twenty-first wind turbines without any strategy; and in Figure 4(c), the solid line represents the change curve of rotor angular velocity of the first, sixth, and twenty-first wind turbines without any strategy. The points in Figure 4(a) The line in Figure 4(b) represents the change curve of the power grid frequency under the traditional method. The dotted line in Figure 4(b) represents the change curve of the output power of the first, sixth, and twenty-first wind turbines under the traditional method. The dotted line in Figure 4(c) represents the change curve of the rotor angular velocity of the first, sixth, and twenty-first wind turbines under the traditional method. The dashed line in Figure 4(a) represents the change curve of the power grid frequency under the method of this application. The dashed line in Figure 4(b) represents the change curve of the output power of the first, sixth, and twenty-first wind turbines under the method of this application. The dashed line in Figure 4(c) represents the change curve of the rotor angular velocity of the first, sixth, and twenty-first wind turbines under the method of this application.

[0101] The strong wake effect at sea can cause wind turbines in a wind farm to operate in different states at the same time, resulting in complex operating conditions and varying frequency support capabilities. As shown in Figures 4(a), 4(b), and 4(c), the operating points of the first, sixth, and twenty-first turbines differ significantly. Existing research generally adopts centralized control, treating the wind farm as a single unit without considering the differences in frequency support capabilities among different wind turbines. This can easily lead to turbines exceeding their speed limits and becoming out of sync with the grid, or even worsening the grid frequency compared to when the wind farm does not participate in frequency regulation. As shown in Figures 4(a), 4(b), and 4(c), the twenty-first turbine became unstable due to its excessively low speed, which prevented it from returning to its initial state, causing severe deterioration of the grid frequency. The multi-turbine coordinated frequency support control method for offshore wind farms proposed in this application can match the frequency support power of wind turbines with their frequency regulation capabilities, fully utilizing the frequency support capacity of the wind farm.

[0102] Example 2

[0103] This application provides a multi-machine coordinated high-frequency support system for deep-sea offshore wind farms, comprising:

[0104] The adjacency matrix acquisition module is used to represent the communication topology of a wind farm using algebraic graph theory and obtain the adjacency matrix in an undirected graph. In this module, a node in the undirected graph represents a wind turbine in the wind farm, and nodes with communication channels are neighbors.

[0105] The consistency state factor construction module is used to construct the Laplace matrix of an undirected graph based on the adjacency matrix of the undirected graph; at the same time, considering the rotor speed safety constraint of the wind turbine, the consistency state factor of the wind turbine is constructed in combination with the rotor speed of the wind turbine.

[0106] The control protocol construction module is used to build a dynamic process model of the node state. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, it determines the control protocol of the node state so that the consistency state factor of the wind turbine converges to the same value.

[0107] The frequency support control module is used to apply the control protocol of the node status to the active current inner loop of the wind turbine, so as to realize the coordinated frequency support control of the deep-sea wind farm to the power grid.

[0108] More preferably, the Laplace matrix of the undirected graph in the consistency state factor construction module is: ;in, Adjacency matrix ; Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. Pointing to node The directed edge, ;otherwise, ; This represents the sum of the edge sets consisting of ordered pairs of corresponding nodes; Represents a finite and non-empty set of nodes; n The number of nodes; Represents the real number field.

[0109] More preferably, the consistency state factor of the wind turbine in the consistency state factor construction module is:

[0110]

[0111] in, For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ; This is the minimum rotor speed of the fan; This is the maximum rotor speed of the fan.

[0112] More preferably, the dynamic process model of node states in the control protocol construction module is as follows:

[0113]

[0114]

[0115] in, For the first i Control protocol for typhoon generator consistency state factor; The uniformity convergence coefficient is denoted as .

[0116] More preferably, the q-axis reference value of the active current inner loop of the wind turbine in the frequency support control module... for:

[0117]

[0118] in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases .

[0119] It is understood that the detailed functional implementation of each of the above modules can be found in the description of the aforementioned method embodiments, and will not be repeated here.

[0120] It should be understood that the above system is used to execute the methods in the above embodiments. The corresponding program modules in the system are similar in implementation principle and technical effect to those described in the above methods. The working process of the system can be referred to the corresponding process in the above methods, and will not be repeated here.

[0121] Based on the methods in the above embodiments, such as Figure 5 As shown in the illustration, this application provides an electronic device that may include a processor 810, a communications interface 820, a memory 830, and a communication bus 840. The processor 810, communications interface 820, and memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions stored in the memory 830 to execute the methods described in the above embodiments.

[0122] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0123] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0124] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0125] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0126] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0127] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0128] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

Claims

1. A method for rapid frequency support of multi-machine collaboration in deep-sea wind farms, characterized in that, Includes the following steps: Step S1: Use algebraic graph theory to characterize the communication topology of the wind farm and obtain the Laplace matrix in the undirected graph; where a node in the undirected graph represents a wind turbine in the wind farm; nodes with communication channels are neighbors. Simultaneously considering the safety constraints of the fan's rotor speed, and combining the fan's rotor speed, a consistency state factor for the fan is constructed. Step S2: Construct a dynamic process model of node states. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, determine the control protocol of the node states so that the consistency state factor of the wind turbine converges to the same value. Step S3: Apply the node status control protocol to the active current inner loop of the wind turbine to achieve coordinated frequency support control of the deep-sea wind farm on the power grid. The Laplace matrix of the undirected graph in step S1 is ;in, Adjacency matrix ; Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. Pointing to node The directed edge, ;otherwise, ; } This represents the sum of the edge sets consisting of ordered pairs of corresponding nodes; Represents a finite and non-empty set of nodes; n The number of nodes; Represents the real number field.

2. The method for rapid frequency support of multi-machine collaboration in deep-sea wind farms according to claim 1, characterized in that, The consistency state factor of the wind turbine in step S1 is: in, For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ; This is the minimum rotor speed of the fan; This is the maximum rotor speed of the fan.

3. The method for rapid frequency support of multi-machine collaboration in deep-sea wind farms according to claim 2, characterized in that, The dynamic process model of the node state in step S2 is as follows: in, For the first i Control protocol for typhoon generator consistency state factor; The uniformity convergence coefficient; n Number of nodes; adjacency matrix ; Representing an edge The weights; Represents the real number field.

4. The method for rapid frequency support of multi-machine collaboration in deep-sea wind farms according to claim 3, characterized in that, The q-axis reference value of the inner loop of the active current of the wind turbine in step S3 for: in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases .

5. A multi-machine coordinated high-frequency support system for deep-sea wind farms, characterized in that, include: The adjacency matrix acquisition module is used to represent the communication topology of a wind farm using algebraic graph theory and obtain the adjacency matrix in an undirected graph. In this module, a node in the undirected graph represents a wind turbine in the wind farm, and nodes with communication channels are neighbors. The consistency state factor construction module is used to construct the Laplace matrix of an undirected graph based on the adjacency matrix of the undirected graph; at the same time, considering the rotor speed safety constraint of the wind turbine, the consistency state factor of the wind turbine is constructed in combination with the rotor speed of the wind turbine. The control protocol construction module is used to build a dynamic process model of the node state. Based on the consistency state factor of the wind turbine and the Laplace matrix of the undirected graph, it determines the control protocol of the node state so that the consistency state factor of the wind turbine converges to the same value. The frequency support control module is used to apply the control protocol of the node status to the active current inner loop of the wind turbine, so as to realize the coordinated frequency support control of the deep-sea wind farm to the power grid. The Laplace matrix of the undirected graph in the consistency state factor building module is: ;in, Adjacency matrix ; Representing an edge The weight of the edge; if the edge This indicates that there exists a slave node. Pointing to node The directed edge, ;otherwise, ; } This represents the sum of the edge sets consisting of ordered pairs of corresponding nodes; Represents a finite and non-empty set of nodes; n The number of nodes; Represents the real number field.

6. The multi-machine coordinated rapid frequency support system for deep-sea wind farms according to claim 5, characterized in that, The consistency state factor of the wind turbine in the consistency state factor construction module is: in, For the first i The initial rotor speed of the typhoon generator; For the first i The current rotor speed of the typhoon generator; To ensure the safe control of the wind turbine's rotor speed during frequency drops... When the frequency increases ; This is the minimum rotor speed of the fan; This is the maximum rotor speed of the fan.

7. The multi-machine coordinated rapid frequency support system for deep-sea wind farms according to claim 6, characterized in that, The dynamic process model of node states in the control protocol construction module is as follows: in, For the first i Control protocol for typhoon generator consistency state factor; The uniformity convergence coefficient; n Number of nodes; adjacency matrix ; Representing an edge The weights; Represents the real number field.

8. The multi-machine coordinated rapid frequency support system for deep-sea wind farms according to claim 7, characterized in that, The q-axis reference value of the active current inner loop of the wind turbine in the frequency support control module. for: in, for The fundamental components in the speed are output by the outer loop PI controller. for The single-machine inertia response component; for The station consistency coordination component in the frequency drop When the frequency increases .

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