Multi-active filter centralized control system and method for offshore wind farm cluster

Abstract

The application provides a multi-active filter centralized control system and method for offshore wind farm groups. The system comprises: a plurality of harmonic measurement units, each of which is used for synchronously measuring harmonic data; a plurality of high-voltage active filters; a centralized control master station connected with the harmonic measurement units and the controllers of the active filters through a communication network; wherein the centralized control master station is used for: collecting the harmonic data of each harmonic measurement unit in real time; establishing or calling a harmonic impedance network model of the network based on the topological structure and element parameters of the offshore wind farm group electrical network; determining the harmonic responsibility weight of each harmonic source to the observation point in the network; inputting the harmonic responsibility weight of each harmonic source to the observation point in the network into a pre-established compensation current optimization model to obtain the optimal compensation current instruction of each active filter, and performing control. The technical scheme provided by the application greatly improves the overall filtering efficiency and system stability.

Description

Technical Field

[0001] This application relates to the fields of power system automation and power quality control technology, and in particular to a centralized control system and method for multiple active filters for offshore wind farm clusters. Background Technology

[0002] With the large-scale and clustered development of offshore wind power, multiple wind farms are often electrically connected to onshore control centers via submarine cables, forming a closely interconnected offshore wind farm cluster. To suppress the large amount of harmonics generated by power electronic equipment such as wind turbine converters during grid-connected operation, it is usually necessary to install multiple high-voltage active filters distributed on the busbars of each offshore substation or onshore control center.

[0003] Currently, the commonly used control method in engineering is for each active power filter (APF) to operate independently. Each filter performs independent closed-loop compensation based solely on harmonic voltage or current commands collected from its local measurement point. However, in the tightly coupled network of offshore wind farms, the electrical distance between the filter installation points is very short, and the common coupling point of the system's harmonic impedance is not a single node. This independent operation mode can lead to serious "harmonic cancellation" or "interference" problems: when one APF injects compensation current into the grid to compensate for a certain harmonic, this current will change the harmonic voltage at other APF installation points through network coupling. The local controllers of other APFs may mistakenly interpret this change as a new harmonic disturbance and issue a reverse compensation current in an attempt to cancel it out. As a result, the compensation actions of multiple APFs interfere with and cancel each other out, causing huge internal losses in equipment capacity, a significant decrease in overall filtering efficiency, and difficulty in effectively reducing the total harmonic distortion rate of the system. More seriously, this negative interaction between controllers may trigger harmonic resonance or system oscillation, directly threatening the safe and stable operation of the power grid. Existing technologies lack an effective solution for coordinating the collaborative work of multiple APFs from a system-wide perspective. Some studies have proposed simple master-slave control or capacity ratio allocation strategies, but none have deeply considered the impact of network harmonic impedance characteristics on the coupling between APFs, failing to fundamentally solve the dynamic interaction problem caused by the network structure. Therefore, there is an urgent need to propose a system and method that can achieve dynamic optimization allocation and collaborative control of compensation responsibilities among multiple APFs based on a whole-network model. Summary of the Invention

[0004] This application provides a centralized control system and method for multiple active filters in offshore wind farm clusters, which at least solves the technical problem that the harmonic compensation actions of multiple independently operating active filters in offshore wind farm clusters cancel each other out due to network coupling, resulting in severe internal losses, which leads to low overall filtering efficiency and may cause system oscillation.

[0005] The first aspect of this application proposes a centralized control system for multiple active filters in an offshore wind farm cluster, the system comprising:

[0006] Multiple harmonic measurement units are deployed at the grid connection point or feeder of each wind farm to synchronously measure harmonic data. Multiple high-voltage active filters are distributed and installed within the preset range of each harmonic source; The co-control master station is connected to the controllers of each harmonic measurement unit and each active filter through a communication network; The co-control master station is used for: Harmonic data from each of the aforementioned harmonic measurement units are collected in real time; Based on the topology and component parameters of the electrical network of an offshore wind farm cluster, a harmonic impedance network model of the network is established or invoked. Based on the harmonic data and the harmonic impedance network model, the harmonic responsibility weight of each harmonic source to the observation point in the network is determined. The harmonic responsibility weights of each harmonic source to the observation points in the network are input into the pre-established compensation current optimization model, and the optimal compensation current command of each active filter is obtained by optimization solution. The optimal compensation current command is sent to the corresponding active filter for execution control.

[0007] Preferably, the harmonic impedance network model is a mathematical model characterizing the voltage-current relationship of the electrical network of the offshore wind farm group at each harmonic frequency; The co-control master station is also used to identify and update the harmonic impedance network model online based on changes in the operating status of the electrical network.

[0008] Furthermore, determining the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic data and the harmonic impedance network model includes: Based on the harmonic data and the harmonic impedance network model, the quantitative index of the harmonic influence of each harmonic source on the observation point in the electrical network is calculated. Based on the harmonic impact quantification index and the installation location information of each active filter, the harmonic responsibility weight of each harmonic source to the observation point in the network is generated.

[0009] Furthermore, the step of calculating the quantitative index of the harmonic impact of each harmonic source on the observation points in the electrical network based on the harmonic data and the harmonic impedance network model includes: Based on the transmission impedance relationship in the harmonic impedance network model and the harmonic data, the contribution of each harmonic source to the harmonic voltage at the observation point is calculated. Alternatively, based on the harmonic impedance network model, by solving the partial derivatives of the harmonic voltage at each observation point in the harmonic data with respect to the injected current of each harmonic source, a sensitivity coefficient can be obtained to quantify the degree of influence of each harmonic source on the harmonic voltage at the observation point. The quantitative indicators of harmonic influence include: the contribution or sensitivity coefficient of harmonic voltage at the observation point.

[0010] Furthermore, the generation of harmonic responsibility weights for each harmonic source to the observation points in the network, based on the harmonic influence quantification index and the installation location information of each active filter, includes: One or more observation points for each active filter are determined based on the electrical connection relationships of each active filter. For each observation point, the harmonic influence quantification index is used to sort them, and one or more harmonic sources with the largest harmonic influence quantification index are initially identified as candidate responsible harmonic sources of the active filter. Based on the candidate responsible harmonic source delineation results of each active filter, a preliminary harmonic responsibility allocation mapping relationship is formed; Based on the harmonic influence quantification index, the active filter and candidate responsible harmonic source relationship of each group in the preliminary mapping relationship are assigned values ​​and calculated to obtain the harmonic responsibility weight.

[0011] Furthermore, the process of establishing the compensation current optimization model includes: An objective function is constructed with the goal of minimizing the total harmonic distortion rate of the electrical network of the offshore wind farm group and the comprehensive index of suppressing the interaction between active filters. Using the real-time available capacity constraints of each active filter, the node voltage safety constraints of the electrical network, and the phase constraints of each harmonic compensation current as constraints, a compensation current optimization model is constructed in conjunction with the objective function.

[0012] Furthermore, the objective function is calculated as follows:

[0013] In the formula, This is a comprehensive indicator value. The harmonic responsibility weight for observation point i, Let i be the harmonic voltage distortion rate at observation point i. This is the transpose of the compensation current command vector for the m-th active filter. Let be the equivalent harmonic coupling impedance between the installation points of the m-th active filter and the n-th active filter. Let be the compensation current command vector for the nth active filter. This is the interaction inhibition coefficient.

[0014] Furthermore, the compensation current optimization model is optimized and solved using quadratic programming, interior point method, sequential quadratic programming, or distributed alternating direction multiplier method.

[0015] Preferably, the communication network adopts a synchronization mechanism based on the IEEE 1588 precise time protocol and has channel redundancy or ring network self-healing function to ensure the synchronous acquisition of the harmonic data and the real-time reliable issuance of the optimal compensation current command.

[0016] The second aspect of this application proposes a method for centralized collaborative control of multiple active filters in offshore wind farm clusters, including: Harmonic data from each of the aforementioned harmonic measurement units are collected in real time; Based on the topology and component parameters of the electrical network of an offshore wind farm cluster, a harmonic impedance network model of the network is established or invoked. Based on the harmonic data and the harmonic impedance network model, the harmonic responsibility weight of each harmonic source to the observation point in the network is determined. The harmonic responsibility weights of each harmonic source to the observation points in the network are input into the pre-established compensation current optimization model, and the optimal compensation current command of each active filter is obtained by optimization solution. The optimal compensation current command is sent to the corresponding active filter for execution control.

[0017] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects: This application proposes a centralized collaborative control system and method for multiple active power filters in offshore wind farm clusters. The system includes: multiple harmonic measurement units, which are deployed at the grid connection points or feeders of each wind farm for synchronously measuring harmonic data; multiple high-voltage active power filters, which are distributed and installed within a preset range of each harmonic source; and a collaborative control master station, which is connected to the controllers of each harmonic measurement unit and each active power filter via a communication network. The collaborative control master station is used for: real-time acquisition of harmonic data from each harmonic measurement unit; establishing or calling a harmonic impedance network model of the network based on the topology and component parameters of the offshore wind farm cluster's electrical network; determining the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic data and the harmonic impedance network model; inputting the harmonic responsibility weight of each harmonic source to the observation points in the network into a pre-established compensation current optimization model and performing optimization to obtain the optimal compensation current command for each active power filter; and issuing the optimal compensation current command to the corresponding active power filter for execution control. The technical solution proposed in this application, based on a global harmonic impedance model and real-time data, dynamically quantifies and allocates the compensation responsibility of each harmonic source to each filter, realizing the collaborative optimization control of multiple filters. This fundamentally eliminates the harmonic cancellation internal loss caused by independent operation between filters, and significantly improves the overall filtering efficiency and system stability.

[0018] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0019] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a centralized control system for multiple active filters in an offshore wind farm cluster, according to an embodiment of this application. Figure 2 This is a schematic diagram illustrating the access of a centralized control system to a wind farm and the grid side according to an embodiment of this application; Figure 3 This is a structural diagram of a centralized control method for multiple active filters in an offshore wind farm group according to an embodiment of this application.

[0020] Figure Labels Harmonic Measurement Unit 1, High Voltage Active Filter 2, Co-control Master Station 3 Detailed Implementation The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0021] This application proposes a centralized collaborative control system and method for multiple active power filters in offshore wind farm clusters. The system includes: multiple harmonic measurement units, which are deployed at the grid connection points or feeders of each wind farm for synchronously measuring harmonic data; multiple high-voltage active power filters, which are distributed and installed within a preset range of each harmonic source; and a collaborative control master station, which is connected to the controllers of each harmonic measurement unit and each active power filter via a communication network. The collaborative control master station is used for: real-time acquisition of harmonic data from each harmonic measurement unit; establishing or calling a harmonic impedance network model of the network based on the topology and component parameters of the offshore wind farm cluster's electrical network; determining the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic data and the harmonic impedance network model; inputting the harmonic responsibility weight of each harmonic source to the observation points in the network into a pre-established compensation current optimization model and performing optimization to obtain the optimal compensation current command for each active power filter; and issuing the optimal compensation current command to the corresponding active power filter for execution control. The technical solution proposed in this application, based on a global harmonic impedance model and real-time data, dynamically quantifies and allocates the compensation responsibility of each harmonic source to each filter, realizing the collaborative optimization control of multiple filters. This fundamentally eliminates the harmonic cancellation internal loss caused by independent operation between filters, and significantly improves the overall filtering efficiency and system stability.

[0022] The following description, with reference to the accompanying drawings, describes a centralized control system and method for multiple active filters in offshore wind farm clusters according to embodiments of this application.

[0023] Example 1 Figure 1 This is a structural diagram of a centralized control system for multiple active filters in an offshore wind farm cluster, according to an embodiment of this application. Figure 1 As shown, the system includes: Multiple harmonic measurement units (HMUs) 1 are deployed at the grid connection point or feeder of each wind farm to synchronously measure harmonic data. It should be noted that the harmonic data includes harmonic voltage and harmonic current.

[0024] Multiple high-voltage active power filters (APFs) are installed separately within the preset range of each harmonic source; The co-control master station 3 is connected to the controllers of each harmonic measurement unit 1 and each active filter 2 via a communication network.

[0025] In this embodiment of the disclosure, the communication network adopts a synchronization mechanism based on the IEEE 1588 precise time protocol and has channel redundancy or ring network self-healing function to ensure the synchronous acquisition of the harmonic data and the real-time reliable issuance of the optimal compensation current command.

[0026] Specifically, the centralized control system includes: multiple harmonic measurement units (HMUs) 1: deployed at the grid connection points of each wind farm or key feeder for synchronously measuring harmonic voltage and harmonic current data; a control master station 3: connected to all HMUs and each APF controller via a high-speed communication network; and multiple high-voltage active power filters (APFs) 2: distributed near each harmonic source.

[0027] The co-control master station 3 performs the following steps: Step S1: Real-time acquisition and acquisition of all harmonic data measured by HMU through the communication network.

[0028] Step S2: Based on the network topology parameters and real-time data, identify or call the preset full-system harmonic impedance network model online.

[0029] Step S3: Using the minimum harmonic distortion rate of the entire network and avoiding the interaction between APFs as the comprehensive objective function, the optimal harmonic compensation command for each APF under the current operating conditions is calculated using the aforementioned harmonic impedance model. The core of this calculation is the "dynamic harmonic responsibility allocation algorithm," which assigns each APF the harmonic component it is most responsible for compensating, thus achieving "decoupling" of its compensation range in terms of harmonic impedance.

[0030] Step S4: Send the calculated optimal compensation instruction to the corresponding APF execution unit through the communication network.

[0031] Step S5: Each APF generates a corresponding compensation current and injects it into the power grid according to the received instructions.

[0032] In this embodiment of the disclosure, the co-control master station 3 is used for: Harmonic data from each of the harmonic measurement units 1 are collected in real time; Based on the topology and component parameters of the electrical network of an offshore wind farm cluster, a harmonic impedance network model of the network is established or invoked. Based on the harmonic data and the harmonic impedance network model, the harmonic responsibility weight of each harmonic source to the observation point in the network is determined. It should be noted that the harmonic impedance network model is a mathematical model that characterizes the voltage-current relationship of the electrical network of the offshore wind farm group at each harmonic frequency. In this embodiment of the disclosure, determining the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic data and the harmonic impedance network model includes: 1. Based on the harmonic data and the harmonic impedance network model, calculate the quantitative index of the harmonic influence of each harmonic source on the observation point in the electrical network; 2. Based on the harmonic influence quantification index and the installation location information of each active filter, generate the harmonic responsibility weight of each harmonic source to the observation point in the network.

[0033] The step of calculating the quantitative index of the harmonic impact of each harmonic source on the observation points in the electrical network based on the harmonic data and the harmonic impedance network model includes: Based on the transmission impedance relationship in the harmonic impedance network model and the harmonic data, the contribution of each harmonic source to the harmonic voltage at the observation point is calculated. Alternatively, based on the harmonic impedance network model, by solving the partial derivatives of the harmonic voltage at each observation point in the harmonic data with respect to the injected current of each harmonic source, a sensitivity coefficient can be obtained to quantify the degree of influence of each harmonic source on the harmonic voltage at the observation point. The quantitative indicators of harmonic influence include: the contribution or sensitivity coefficient of harmonic voltage at the observation point.

[0034] The step of generating the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic influence quantification index and the installation location information of each active filter includes: One or more observation points for each active filter are determined based on the electrical connection relationships of each active filter. For each observation point, the harmonic influence quantification index is used to sort them, and one or more harmonic sources with the largest harmonic influence quantification index are initially identified as candidate responsible harmonic sources of the active filter. Based on the candidate responsible harmonic source delineation results of each active filter, a preliminary harmonic responsibility allocation mapping relationship is formed; Based on the harmonic influence quantification index, the active filter and candidate responsible harmonic source relationship of each group in the preliminary mapping relationship are assigned values ​​and calculated to obtain the harmonic responsibility weight.

[0035] The harmonic responsibility weights of each harmonic source to the observation points in the network are input into the pre-established compensation current optimization model, and the optimal compensation current command of each active filter 2 is obtained by optimization solution. In this embodiment of the disclosure, the process of establishing the compensation current optimization model includes: An objective function is constructed with the goal of minimizing the total harmonic distortion rate of the electrical network of the offshore wind farm group and the comprehensive index of suppressing the interaction between active filters. Using the real-time available capacity constraints of each active filter, the node voltage safety constraints of the electrical network, and the phase constraints of each harmonic compensation current as constraints, a compensation current optimization model is constructed in conjunction with the objective function.

[0036] It should be noted that the objective function is calculated as follows:

[0037] In the formula, This is a comprehensive indicator value. The harmonic responsibility weight for observation point i, Let i be the harmonic voltage distortion rate at observation point i. This is the transpose of the compensation current command vector for the m-th active filter. Let be the equivalent harmonic coupling impedance between the installation points of the m-th active filter and the n-th active filter. Let be the compensation current command vector for the nth active filter. This is the interaction inhibition coefficient.

[0038] In this embodiment of the disclosure, the compensation current optimization model is optimized and solved using quadratic programming, interior point method, sequential quadratic programming, or distributed alternating direction multiplier method.

[0039] The optimal compensation current command is sent to the corresponding active filter for execution control.

[0040] It should be noted that the co-control master station 3 is also used to identify and update the harmonic impedance network model online according to the changes in the operating status of the electrical network.

[0041] For example, such as Figure 2 The diagram illustrates the centralized control system's connection to the wind farm and grid, using a system comprising two offshore wind farms and an onshore control center as an example, focusing on the common 5th and 7th harmonics. HMUs are installed at the grid connection points PCC_A and PCC_B of wind farms A and B, respectively, with one APF configured at each. The control master station is deployed at the onshore control center. The control master station continuously receives 5th and 7th harmonic data from PCC_A and PCC_B. The system model built into the control master station identifies wind farm A as the primary source of the 5th harmonic, affecting wind farm B (the identification principle involves calculating the power flow direction and magnitude of the 5th and 7th harmonics respectively). The control master station calculates using a "harmonic responsibility dynamic allocation algorithm": instructing APF_A to primarily compensate for its locally generated 5th harmonics, while instructing APF_B to compensate for the remaining 5th harmonics flowing into its PCC point and the locally generated 7th harmonics. After the two APFs execute this refined instruction, the voltage content of the 5th and 7th harmonics of the system decreases significantly, avoiding the phenomenon of either APF's operating point drifting or output cancellation.

[0042] 1. System Modeling and Initialization Input: electrical topology parameters of the wind farm group, impedance parameters of lines and transformers (at fundamental and major harmonic frequencies), installation location of each APF, and location of each harmonic measurement unit (HMU).

[0043] Modeling: Establish a full-system harmonic impedance network model (in the form of nodal admittance matrices). The model must include all harmonic frequencies (e.g., 5th, 7th, 11th, 13th, etc.). This model can be preset offline and has online fine-tuning capabilities.

[0044] Initialization: Set parameters such as the system target harmonic voltage distortion rate limit, the capacity and dynamic response constraints of each APF, and the algorithm convergence threshold.

[0045] 2. Real-time data acquisition and synchronization The control master station synchronously collects harmonic data (including harmonic voltages) reported by all HMUs through a high-speed communication network. Harmonic current ,in For harmonic order, (Numbering the measurement points).

[0046] At the same time, the operating status of each APF (such as switching status, current output, available capacity, etc.) is collected.

[0047] The data is refreshed in fixed time windows (such as every power frequency cycle or every 100ms).

[0048] 3. Quantitative Analysis of Harmonic Responsibility Based on the harmonic impedance network model and real-time measurement data, the "harmonic responsibility" of each harmonic source node (usually the grid connection point of a wind turbine or wind farm) to all key observation nodes in the network (usually the location of each HMU) is calculated.

[0049] The contribution of each harmonic source to the harmonic voltage at the observation point is quantified using the principle of harmonic current superposition or the partial derivative sensitivity method. For example, the relationship between node harmonic current and observation point harmonic voltage is obtained by calculating the transfer impedance matrix.

[0050] in, For the harmonic voltage at the observation point, For node harmonic currents, This is the transmission impedance matrix at the corresponding harmonic frequency.

[0051] The "responsibility weight matrix" of each harmonic source is calculated, reflecting the magnitude of its influence on harmonic distortion at each observation point.

[0052] 4. Optimization calculation of compensation instructions Objective function: The primary objective is to minimize the weighted sum of the total harmonic voltage distortion rate (THD_U) at all key observation points of the system, while introducing an "APF interaction suppression term" as a secondary objective.

[0053]

[0054] Constraints: 1. The compensation current command for each APF shall not exceed its real-time available capacity.

[0055] 2. Phase and amplitude constraints of the compensation current commands for each harmonic.

[0056] 3. Safe operating range of system node voltage.

[0057] Decoupling allocation strategy: According to the "harmonic responsibility weight matrix", each APF is assigned the harmonic source with the closest electrical distance and the highest responsibility weight as its main compensation target.

[0058] By optimizing the calculation, the voltage regulation effect generated by the compensation command current of each APF on the harmonic impedance network is made to act as independently as possible in the region near its assigned main harmonic source, thereby reducing the coupling with the compensation regions of other APFs (i.e., reducing the interaction term in the objective function).

[0059] The algorithm employs an online optimization solver (such as quadratic programming QP or interior-point method) to solve the problem in real time, obtaining a set of optimal harmonic compensation current commands for each APF that minimizes the objective function. (Including all harmonic components).

[0060] 5. Command Issuance and Execution The calculated optimal compensation current commands for each APF It is transmitted to the local controller of the corresponding APF via a high-speed communication network.

[0061] According to the instructions, the APF local controller uses a current tracking control strategy (such as hysteresis comparison, space vector modulation, etc.) to generate a PWM drive signal and control the power devices to generate corresponding compensation current to inject into the grid.

[0062] The multi-active power filter (APF) centralized control system for offshore wind farms proposed in this embodiment has the following advantages: Global Optimization: Optimization calculations at the system level achieve optimal overall filtering performance, significantly reducing the system's total harmonic distortion (THD). Elimination of Internal Losses: Through unified decision-making at the central master station, the compensation responsibilities of each APF are accurately allocated, fundamentally avoiding the problems of "harmonic cancellation" and "interference" between multiple APFs. High Stability: Through system-level impedance reshaping analysis, harmonic oscillations that may be caused by APFs can be effectively damped, improving system stability. Strong Adaptability: The central master station can dynamically adjust the control strategy according to changes in system operation (such as turbine switching), exhibiting good adaptability.

[0063] In summary, the multi-active filter centralized control system for offshore wind farm clusters proposed in this embodiment dynamically quantifies and allocates the compensation responsibility of each harmonic source to each filter based on the global harmonic impedance model and real-time data. This achieves coordinated optimization control of multiple filters, fundamentally eliminating the harmonic cancellation internal loss caused by independent operation between filters, and significantly improving the overall filtering efficiency and system stability.

[0064] Example 2 Figure 3 The flowchart below shows a method for centralized collaborative control of multiple active filters in an offshore wind farm cluster, according to an embodiment of this application. Figure 3 As shown, the method includes: Step 1: Collect harmonic data from each of the harmonic measurement units in real time; Step 2: Based on the topology and component parameters of the electrical network of the offshore wind farm cluster, establish or call the harmonic impedance network model of the network; Step 3: Based on the harmonic data and the harmonic impedance network model, determine the harmonic responsibility weight of each harmonic source to the observation point in the network; It should be noted that the harmonic impedance network model is a mathematical model that characterizes the voltage-current relationship of the electrical network of the offshore wind farm group at each harmonic frequency.

[0065] Step 4: Input the harmonic responsibility weights of each harmonic source to the observation points in the network into the pre-established compensation current optimization model, and perform optimization to obtain the optimal compensation current command for each active filter. Step 5: Send the optimal compensation current command to the corresponding active filter for execution control.

[0066] In this embodiment of the disclosure, the method further includes: Based on the changes in the operating state of the electrical network, the harmonic impedance network model is identified and updated online.

[0067] In this embodiment of the disclosure, step 3 specifically includes: Based on the harmonic data and the harmonic impedance network model, the quantitative index of the harmonic influence of each harmonic source on the observation point in the electrical network is calculated. Based on the harmonic impact quantification index and the installation location information of each active filter, the harmonic responsibility weight of each harmonic source to the observation point in the network is generated.

[0068] Furthermore, the step of calculating the quantitative index of the harmonic impact of each harmonic source on the observation points in the electrical network based on the harmonic data and the harmonic impedance network model includes: Based on the transmission impedance relationship in the harmonic impedance network model and the harmonic data, the contribution of each harmonic source to the harmonic voltage at the observation point is calculated. Alternatively, based on the harmonic impedance network model, by solving the partial derivatives of the harmonic voltage at each observation point in the harmonic data with respect to the injected current of each harmonic source, a sensitivity coefficient can be obtained to quantify the degree of influence of each harmonic source on the harmonic voltage at the observation point. The quantitative indicators of harmonic influence include: the contribution or sensitivity coefficient of harmonic voltage at the observation point.

[0069] Furthermore, the generation of harmonic responsibility weights for each harmonic source to the observation points in the network, based on the harmonic influence quantification index and the installation location information of each active filter, includes: One or more observation points for each active filter are determined based on the electrical connection relationships of each active filter. For each observation point, the harmonic influence quantification index is used to sort them, and one or more harmonic sources with the largest harmonic influence quantification index are initially identified as candidate responsible harmonic sources of the active filter. Based on the candidate responsible harmonic source delineation results of each active filter, a preliminary harmonic responsibility allocation mapping relationship is formed; Based on the harmonic influence quantification index, the active filter and candidate responsible harmonic source relationship of each group in the preliminary mapping relationship are assigned values ​​and calculated to obtain the harmonic responsibility weight.

[0070] In this embodiment of the disclosure, the process of establishing the compensation current optimization model includes: An objective function is constructed with the goal of minimizing the total harmonic distortion rate of the electrical network of the offshore wind farm group and the comprehensive index of suppressing the interaction between active filters. Using the real-time available capacity constraints of each active filter, the node voltage safety constraints of the electrical network, and the phase constraints of each harmonic compensation current as constraints, a compensation current optimization model is constructed in conjunction with the objective function.

[0071] The objective function is calculated as follows:

[0072] In the formula, This is a comprehensive indicator value. The harmonic responsibility weight for observation point i, Let i be the harmonic voltage distortion rate at observation point i. This is the transpose of the compensation current command vector for the m-th active filter. Let be the equivalent harmonic coupling impedance between the installation points of the m-th active filter and the n-th active filter. Let be the compensation current command vector for the nth active filter. This is the interaction inhibition coefficient.

[0073] It should be noted that the compensation current optimization model is optimized and solved using quadratic programming, interior point method, sequential quadratic programming, or distributed alternating direction multiplier method.

[0074] In summary, the proposed method for centralized collaborative control of multiple active filters in offshore wind farm clusters, based on a global harmonic impedance model and real-time data, dynamically quantifies and allocates the compensation responsibility of each harmonic source to each filter, realizing the collaborative optimization control of multiple filters. This fundamentally eliminates the harmonic cancellation internal loss caused by independent operation between filters, and significantly improves the overall filtering efficiency and system stability.

[0075] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0076] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0077] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A centralized control system for multiple active filters in offshore wind farm clusters, characterized in that, The system includes: Multiple harmonic measurement units are deployed at the grid connection point or feeder of each wind farm to synchronously measure harmonic data. Multiple high-voltage active filters are distributed and installed within the preset range of each harmonic source; The co-control master station is connected to the controllers of each harmonic measurement unit and each active filter through a communication network; The co-control master station is used for: Harmonic data from each of the aforementioned harmonic measurement units are collected in real time; Based on the topology and component parameters of the electrical network of an offshore wind farm cluster, a harmonic impedance network model of the network is established or invoked. Based on the harmonic data and the harmonic impedance network model, the harmonic responsibility weight of each harmonic source to the observation point in the network is determined. The harmonic responsibility weights of each harmonic source to the observation points in the network are input into the pre-established compensation current optimization model, and the optimal compensation current command of each active filter is obtained by optimization solution. The optimal compensation current command is sent to the corresponding active filter for execution control.

2. The centralized control system for multiple active filters as described in claim 1, characterized in that, The harmonic impedance network model is a mathematical model that characterizes the voltage-current relationship of the electrical network of the offshore wind farm group at each harmonic frequency. The co-control master station is also used to identify and update the harmonic impedance network model online based on changes in the operating status of the electrical network.

3. The centralized control system for multiple active filters as described in claim 2, characterized in that, The determination of the harmonic responsibility weight of each harmonic source to the observation points in the network based on the harmonic data and the harmonic impedance network model includes: Based on the harmonic data and the harmonic impedance network model, the quantitative index of the harmonic influence of each harmonic source on the observation point in the electrical network is calculated. Based on the harmonic impact quantification index and the installation location information of each active filter, the harmonic responsibility weight of each harmonic source to the observation point in the network is generated.

4. The centralized control system for multiple active filters as described in claim 3, characterized in that, The quantitative index of the harmonic impact of each harmonic source on the observation points in the electrical network, based on the harmonic data and the harmonic impedance network model, includes: Based on the transmission impedance relationship in the harmonic impedance network model and the harmonic data, the contribution of each harmonic source to the harmonic voltage at the observation point is calculated. Alternatively, based on the harmonic impedance network model, by solving the partial derivatives of the harmonic voltage at each observation point in the harmonic data with respect to the injected current of each harmonic source, a sensitivity coefficient can be obtained to quantify the degree of influence of each harmonic source on the harmonic voltage at the observation point. The quantitative indicators of harmonic influence include: the contribution or sensitivity coefficient of harmonic voltage at the observation point.

5. The centralized control system for multiple active filters as described in claim 4, characterized in that, The process of generating harmonic responsibility weights for each harmonic source to observation points in the network, based on the harmonic impact quantification index and the installation location information of each active filter, includes: One or more observation points for each active filter are determined based on the electrical connection relationships of each active filter. For each observation point, the harmonic influence quantification index is used to sort them, and one or more harmonic sources with the largest harmonic influence quantification index are initially identified as candidate responsible harmonic sources of the active filter. Based on the candidate responsible harmonic source delineation results of each active filter, a preliminary harmonic responsibility allocation mapping relationship is formed; Based on the harmonic influence quantification index, the active filter and candidate responsible harmonic source relationship of each group in the preliminary mapping relationship are assigned values ​​and calculated to obtain the harmonic responsibility weight.

6. The centralized control system for multiple active filters as described in claim 5, characterized in that, The process of establishing the compensation current optimization model includes: An objective function is constructed with the goal of minimizing the total harmonic distortion rate of the electrical network of the offshore wind farm group and the comprehensive index of suppressing the interaction between active filters. Using the real-time available capacity constraints of each active filter, the node voltage safety constraints of the electrical network, and the phase constraints of each harmonic compensation current as constraints, a compensation current optimization model is constructed in conjunction with the objective function.

7. The centralized control system for multiple active filters as described in claim 5, characterized in that, The objective function is calculated as follows: In the formula, This is a comprehensive indicator value. The harmonic responsibility weight for observation point i, Let i be the harmonic voltage distortion rate at observation point i. This is the transpose of the compensation current command vector for the m-th active filter. Let be the equivalent harmonic coupling impedance between the installation points of the m-th active filter and the n-th active filter. Let be the compensation current command vector for the nth active filter. This is the interaction inhibition coefficient.

8. The centralized control system for multiple active filters as described in claim 7, characterized in that, The compensation current optimization model is optimized and solved using quadratic programming, interior point method, sequential quadratic programming, or distributed alternating direction multiplier method.

9. The centralized control system for multiple active filters as described in claim 1, characterized in that, The communication network adopts a synchronization mechanism based on the IEEE 1588 precise time protocol and has channel redundancy or ring network self-healing function to ensure the synchronous acquisition of harmonic data and the real-time reliable issuance of the optimal compensation current command.

10. A method for centralized collaborative control of multiple active filters based on the centralized collaborative control system of any one of claims 1-9, characterized in that, The method includes: Harmonic data from each of the aforementioned harmonic measurement units are collected in real time; Based on the topology and component parameters of the electrical network of an offshore wind farm cluster, a harmonic impedance network model of the network is established or invoked. Based on the harmonic data and the harmonic impedance network model, the harmonic responsibility weight of each harmonic source to the observation point in the network is determined. The harmonic responsibility weights of each harmonic source to the observation points in the network are input into the pre-established compensation current optimization model, and the optimal compensation current command of each active filter is obtained by optimization solution. The optimal compensation current command is sent to the corresponding active filter for execution control.

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