Wind farm and power grid bidirectional coupling dynamic simulation system, method, device and medium

Abstract

The application relates to the technical field of wind farm simulation, and discloses a wind farm and power grid bidirectional coupling dynamic simulation system, a method, equipment and a medium. The wind farm and power grid bidirectional coupling dynamic simulation system comprises a wind farm level controller, a power grid model and a wind farm station model. The wind farm station model comprises a wind flow field module and at least one wind turbine module. The at least one wind turbine module is connected with the wind farm level controller, the power grid model and the wind flow field module. The wind flow field module is configured to acquire wind wheel surface wind speed of a current time step and output the wind wheel surface wind speed to the wind turbine module. The wind turbine module is configured to acquire wind turbine power information of a next time step according to the wind wheel surface wind speed of the current time step and an instruction signal of the wind farm level controller of the current time step. The power grid model is configured to acquire power supply parameters of the at least one wind turbine module of the next time step according to the wind turbine power information of the next time step. The application expands the application scene of wind farm dynamic simulation and improves the dynamic simulation accuracy.

Description

Technical Field

[0001] This application relates to the field of wind farm simulation technology, and in particular to a dynamic simulation system, method, equipment and medium for bidirectional coupling between wind farm and power grid. Background Technology

[0002] With the large-scale integration of renewable energy into the power grid, wind power, as an important clean energy source, is having an increasingly significant impact on the grid. During grid-connected operation, wind farms are affected not only by external wind conditions and meteorological factors but also by a closely coupled relationship with the grid's operating status. Extreme wind condition changes causing significant fluctuations in wind farm output power can affect grid stability, especially for wind farms operating in weak or off-grid conditions. Simultaneously, grid instability can also affect wind turbines within the wind farm, causing adverse effects such as turbine drivetrain oscillations and increased fatigue loads. Therefore, high-fidelity simulation of the dynamic characteristics of wind farms and their grid connection is currently a crucial foundation for wind farm design, control strategy optimization, and grid stability analysis.

[0003] However, current wind farm simulation systems have shortcomings and are unable to provide effective support for wind farm design, control strategy optimization, and grid stability analysis. Summary of the Invention

[0004] The purpose of this application is to provide a dynamic simulation system, method, equipment and medium for bidirectional coupling between wind farms and power grids, thereby expanding the application scenarios of dynamic simulation of wind farms and improving the accuracy of dynamic simulation of wind farms and power grids.

[0005] To address the aforementioned technical problems, this application provides a dynamic simulation system for bidirectional coupling between a wind farm and a power grid, comprising: a wind farm-level controller, a power grid model, and a wind farm station model. The wind farm station model includes a wind flow field module and at least one wind turbine module. The at least one wind turbine module is connected to the wind farm-level controller, the power grid model, and the wind flow field module, respectively. The wind flow field module is configured to acquire the wind turbine surface speed at the current time step and output it to the wind turbine module. The wind turbine module is configured to acquire wind turbine power information for the next time step based on the wind turbine surface speed at the current time step and the command signal of the wind farm-level controller at the current time step, and transmit it to the power grid model. The power grid model is configured to acquire power supply parameters for the next time step of the at least one wind turbine module based on the wind turbine power information of the at least one wind turbine module at the next time step, and feed them back to the wind turbine module.

[0006] This application also provides a dynamic simulation method for bidirectional coupling between wind farms and power grids, applied to a dynamic simulation system for bidirectional coupling between wind farms and power grids. The system includes a wind farm-level controller, a power grid model, and a wind farm station model. The wind farm station model includes a wind flow field module and at least one wind turbine module. The at least one wind turbine module is connected to the wind farm-level controller, the power grid model, and the wind flow field module, respectively. The method includes: the wind flow field module acquiring the wind turbine surface speed at the current time step and outputting it to the wind turbine module; the wind turbine module acquiring wind turbine power information for the next time step based on the wind turbine surface speed at the current time step and the command signal from the wind farm-level controller at the current time step, and transmitting it to the power grid model; and the power grid model acquiring the power supply parameters for the next time step of the at least one wind turbine module based on the wind turbine power information from the at least one wind turbine module, and feeding them back to the wind turbine module.

[0007] This application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the above-described dynamic simulation method for bidirectional coupling between wind farms and power grids.

[0008] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described dynamic simulation method for bidirectional coupling between wind farms and power grids.

[0009] In addition, the wind turbine module includes an aerodynamic module, a whole-machine dynamics and control module, and a power generation and conversion module. The aerodynamic module is configured to calculate the aerodynamic force on the wind turbine blades based on the wind speed at the rotor surface and the wind turbine operating state at the current time step, and feed the aerodynamic force back to the airflow field module. The airflow field module obtains the wake field information by solving the dynamic wake model driven by the aerodynamic force to update the airflow field at the next time step. The airflow field module obtains the wind speed at the rotor surface under the updated airflow field at the next time step. The aerodynamic module is also configured to send the aerodynamic force to the whole-machine dynamics and control module. The whole-machine dynamics and control module is configured to calculate the aerodynamic force and the actual electromagnetic force of the generator at the current time step based on the aerodynamic force and the actual electromagnetic force of the generator at the current time step. The system obtains the wind turbine operating status for the next time step based on the torque and the wind turbine operating status at the current time step, and feeds it back to the aerodynamic module. The overall dynamics and control module is also configured to obtain the command signal of the wind farm-level controller at the current time step, and send the command signal and the wind turbine operating status at the current time step to the power generation and converter module. The power generation and converter module is configured to obtain the actual electromagnetic torque and wind turbine power information for the next time step based on the command signal, the wind turbine operating status, and the power supply parameters at the current time step, and feed it back to the overall dynamics and control module. The power generation and converter module is configured to send the wind turbine power information for the next time step to the power grid model.

[0010] In addition, the overall dynamics and control module is also configured to transmit the wind turbine power information and key wind turbine status quantities of the next time step to the wind farm level controller; the wind farm level controller is configured to update the command signal of the next time step according to the wind turbine power information and key wind turbine status quantities of the next time step; the key wind turbine status quantities include at least the pitch angle, generator speed, and component load.

[0011] In addition, the wind turbine power information of the next time step includes the actual active power and actual reactive power injected into the bus of the power grid model; the power supply parameters of the next time step include the terminal voltage amplitude, voltage phase and line frequency of the bus of the wind turbine module connected to the power grid model; the power grid model is configured to calculate the equivalent injection current of at least one wind turbine module based on the wind turbine power information of the next time step, obtain the power supply parameters of the next time step based on the equivalent injection current of at least one wind turbine module, and feed them back to the power generation converter module.

[0012] In addition, the power grid model is configured to simulate power grid transients, which include any of the following types: voltage dips, short-circuit faults, open-circuit faults, and low-frequency oscillations.

[0013] In addition, the dynamic simulation system for bidirectional coupling between wind farms and power grids also includes: a hybrid collaborative controller, at least one load farm model, at least one energy storage station model, a load farm-level controller connected to the load farm model, and an energy storage farm-level controller connected to the energy storage station model; the hybrid collaborative controller is connected to the wind farm-level controller, the load farm-level controller, and the energy storage farm-level controller respectively.

[0014] In addition, the dynamic simulation system for bidirectional coupling between wind farms and power grids also includes: a photovoltaic power station model and a photovoltaic field-level controller connected to the photovoltaic power station model; the hybrid collaborative controller is also connected to the photovoltaic field-level controller.

[0015] The technical solution provided in this application has at least the following advantages:

[0016] This application constructs a wind flow field module and at least one wind turbine module in a wind farm site model. The wind flow field module can simulate the wind conditions inside the wind flow field, thereby obtaining accurate wind speed at the rotor surface in the current time step. The wind turbine module obtains the wind turbine power information for the next time step based on the wind speed at the rotor surface in the current time step and the command signal from the wind farm-level controller in the current time step. The power grid model obtains the power supply parameters of the wind turbine module for the next time step based on the wind turbine power information in the next time step. This enables multi-physics coupling simulation between the wind farm-level controller, the power grid model, and the wind farm site model, achieving bidirectional coupling simulation of wind farm dynamics and power grid dynamics. This expands the application scenarios of wind farm dynamic simulation and improves the accuracy of dynamic simulation of wind farms and power grids. Attached Figure Description

[0017] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0018] Figure 1 This is a schematic diagram of the structure of a dynamic simulation system for bidirectional coupling between a wind farm and a power grid according to an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of the dynamic airflow field output by the airflow field module;

[0020] Figure 3 This is the circuit diagram between the power grid model and the wind turbine module;

[0021] Figure 4 This is a schematic diagram of the specific structure of a dynamic simulation system for bidirectional coupling between a wind farm and a power grid according to an embodiment of this application;

[0022] Figure 5This is a schematic diagram of the structure of a dynamic simulation system for bidirectional coupling between a wind farm and a power grid in a source-grid-load-storage scenario.

[0023] Figure 6 It is the active power timing sequence of the source-grid-load-storage side under the source-grid-load simulation scenario;

[0024] Figure 7 It is the wind speed amplitude at each wind turbine in the source-grid-load-storage simulation scenario;

[0025] Figure 8 This is a time series diagram of the generator speed, pitch angle, hub center torque Mx, and tower base bending moment My of each wind turbine under the source-grid-load-storage simulation scenario;

[0026] Figure 9 This is a timing diagram of the electrical output of each wind turbine in a power grid-load-storage simulation scenario.

[0027] Figure 10 This is a flowchart illustrating a dynamic simulation method for bidirectional coupling between a wind farm and a power grid according to an embodiment of this application.

[0028] Figure 11 This is a structural block diagram of an electronic device according to another embodiment of this application. Detailed Implementation

[0029] As can be seen from the background technology, current wind farm simulation systems have shortcomings and are unable to provide effective support for wind farm design, control strategy optimization, and grid stability analysis.

[0030] Analysis revealed that the main reasons for the deficiencies in current wind farm simulations are: existing wind farm models oversimplify wind conditions, failing to reflect the actual wind condition differences between wind turbines within the wind farm; multiple physical processes in the wind farm cannot be simulated uniformly; power system simulation tools focus only on the power system portion, and wind farm-level simulations often use aggregated wind turbine modules for simplification; and whole-machine simulation software for wind turbines focuses on the aerodynamic-mechanical-control aspects of a single turbine, failing to model multiple turbines and dynamic airflow fields, thus failing to reflect the actual wind condition differences between wind turbines within the wind farm. These reasons result in insufficient simulation effects for wind farms.

[0031] To address the aforementioned technical problems, this application provides a two-way coupled dynamic simulation system for wind farms and power grids, comprising: a wind farm-level controller, a power grid model, and a wind farm station model. The wind farm station model includes a wind flow field module and at least one wind turbine module. The at least one wind turbine module is connected to the wind farm-level controller, the power grid model, and the wind flow field module, respectively. The wind flow field module is configured to acquire the wind turbine surface speed at the current time step and output it to the wind turbine module. The wind turbine module is configured to acquire the wind turbine power information for the next time step based on the wind turbine surface speed at the current time step and the command signal from the wind farm-level controller at the current time step, and transmit it to the power grid model. The power grid model is configured to acquire the power supply parameters for the next time step of the at least one wind turbine module based on the wind turbine power information of the at least one wind turbine module at the next time step, and feed them back to the wind turbine module.

[0032] In this embodiment, a wind flow field module and at least one wind turbine module are constructed in the wind farm site model. The wind flow field module can simulate the wind conditions inside the wind flow field, thereby obtaining the accurate wind speed at the rotor surface in the current time step. The wind turbine module obtains the wind turbine power information for the next time step based on the wind speed at the rotor surface in the current time step and the command signal of the wind farm level controller in the current time step. The power grid model obtains the power supply parameters of the wind turbine module for the next time step based on the wind turbine power information in the next time step. This realizes multi-physics coupling simulation between the wind farm level controller, the power grid model, and the wind farm site model, and achieves bidirectional coupling simulation of wind farm dynamics and power grid dynamics, improving the accuracy of dynamic simulation of wind farm and power grid.

[0033] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0034] One embodiment of this application relates to a dynamic simulation system for bidirectional coupling between a wind farm and a power grid, as shown in the schematic diagram below. Figure 1As shown, the dynamic simulation system for bidirectional coupling between wind farms and power grids in this embodiment includes: a wind farm-level controller 101, a power grid model 102, and a wind farm station model 103. The wind farm station model includes a wind flow field module 1031 and at least one wind turbine module (wind turbine 1, wind turbine 2, wind turbine 3, ..., wind turbine n). The at least one wind turbine module is connected to the wind farm-level controller 101, the power grid model 102, and the wind flow field module 1031. It can be understood that at least one wind turbine module (wind turbine 1, wind turbine 2, wind turbine 3, ..., wind turbine n) is located within the wind flow field module 1031, and the wind flow field module 1031 records the position information of each wind turbine.

[0035] The wind flow field module 1031 in this embodiment is configured to acquire the wind turbine surface wind speed at the current time step and output it to the wind turbine module (wind turbine 1, wind turbine 2, wind turbine 3, ..., wind turbine n); the wind turbine module is configured to acquire the wind turbine power information for the next time step based on the wind turbine surface wind speed at the current time step and the command signal of the wind field level controller 101 at the current time step, and transmit it to the power grid model 102; the power grid model 102 is configured to acquire the power supply parameters for the next time step of at least one wind turbine module based on the wind turbine power information of at least one wind turbine module at the next time step, and feed them back to the wind turbine module.

[0036] This application embodiment constructs a multi-physics coupled simulation between a wind farm-level controller 101, a power grid model 102, and a wind farm station model 103. This dynamic wind flow field-multi-wind turbine-wind farm control-power grid multi-physics coupled simulation system, with the wind farm as the core application scenario, can realize bidirectional coupled simulation of wind farm dynamics (including: dynamic wind flow field, mutual influence of multiple wind turbines, dynamic response of multiple wind turbines, wind farm control strategies, etc.) and power grid dynamics, thereby significantly improving the accuracy of dynamic simulation of wind farms and power grids.

[0037] The simulation architecture of the dynamic simulation system for bidirectional coupling between wind farms and power grids in this application embodiment is divided into three main parts: wind farm station model 103, wind farm-level controller 101, and power grid model 102.

[0038] The wind farm site model 103 consists of a wind flow field module 1031 and at least one wind turbine module. It is used to simulate the wind condition evolution, aerodynamics of multiple wind turbines, wake, mechanical, electromagnetic, and control aspects within the wind farm, as well as the coupling relationships between wind turbines through wake and electrical topology. Current wind farm models oversimplify wind condition modeling, failing to reflect the real wind condition differences between wind turbines within the wind farm. Furthermore, traditional wind farm-level simulations often use aggregated wind turbine modules, neglecting turbine location information and failing to provide location-level spatially resolved wind speeds. They also cannot accurately simulate complex dynamic wind flow fields such as terrain, meteorological changes, local wind direction differences, and wake effects, resulting in inaccurate calculations of wind turbine aerodynamic loads and output power.

[0039] Therefore, in this embodiment of the application, a wind flow field module 1031 is set up. The wind flow field module 1031 is used to generate the wind speed of each space distribution inside the wind farm and dynamically update it as the simulation time progresses. Specifically, the wind flow field module 1031 of this application embodiment considers the influence of terrain undulation factors on wind conditions, such as: local backflow areas behind mountains caused by mountain blocking, low wind speed areas, and the funnel effect between two mountains. It can simulate terrain undulation factors in the wind flow field, and supports steady-state wind and dynamic wind that changes over time. It can simulate complex meteorological events at the wind field level, such as: sudden changes in wind direction, cold front passage, downburst, etc. Therefore, the wind flow field module 1031 of this application embodiment can simulate wind conditions under various meteorological conditions in real wind field environments. Thus, through simulation, wind condition information of various areas inside the wind flow field can be obtained. The wind speed of the impeller surface of the wind turbine module (wind turbine 1, wind turbine 2, wind turbine 3, ..., wind turbine n) at the current time step can be extracted and output to the corresponding wind turbine module as the input of the aerodynamic module in the wind turbine module.

[0040] Because existing power system simulation tools (such as PSSE, DIgSILENT, etc.) do not have a wind turbine module, and whole-machine simulation software (such as Bladed, etc.) cannot model the entire wind farm and wake interaction, the current wind turbine module cannot simulate the dynamic wake of multiple wind turbines and the reverse influence of wind turbine status on the wind turbine field. Even after coupling the existing power system and whole-machine simulation software, it is also impossible to form a dynamic wind farm-level feedback relationship. As a result, the existing tools lack the ability to solve wind turbine field and model the dynamics of multiple wind turbines at the same time.

[0041] Therefore, this application embodiment not only constructs the airflow field module 1031, but also considers the wake effect of the wind turbines. It can form a dynamic closed loop with each wind turbine module, meaning that the influence of the wind turbines on the airflow field will change the wind conditions at the downstream turbine locations (downstream wind turbines), and the operating state of the wind turbines will also, in turn, affect the entire airflow field through the wake, forming a dynamic feedback relationship at the wind field level. It also possesses the ability to solve airflow fields and model the dynamics of multiple wind turbines. For example... Figure 2 The image shown is a schematic diagram of the dynamic airflow field output by the airflow field module, illustrating the wind conditions in various regions within the airflow field. Figure 2 The wake effect of the wind turbine module feedback was demonstrated.

[0042] Current power system simulation tools focus only on the power system itself, and wind turbine simulation software focuses on the aerodynamics, mechanics, and control of a single turbine. However, they cannot model multiple turbines and dynamic airflow fields. Existing simulation frameworks lack a unified platform to support airflow field modules, aerodynamic modules for all turbines, dynamic models of mechanical components, generator and inverter models, and control systems. This makes it difficult to obtain high-fidelity multi-physics coupled dynamic behavior within wind farms, and multi-physics processes in wind farms cannot be simulated uniformly. This results in wind farm-level controllers being unable to evaluate the effectiveness of their strategies in a high-fidelity environment. If the evaluation environment is insufficient, lacking a simulation environment that simultaneously includes dynamic airflow fields, multiple turbine modules, multi-turbine control, and grid dynamic feedback, strategies such as active power allocation and reactive power regulation of wind farm-level controllers are difficult to develop and verify under real system-level coupling conditions. Consequently, they cannot provide effective support for wind farm design, control strategy optimization, and grid stability analysis.

[0043] Therefore, the wind turbine module in this embodiment independently models each wind turbine in the wind farm. The wind turbine module in this embodiment includes an aerodynamic module, a whole-machine dynamics and control module, and a power generation and conversion module, thereby achieving high-fidelity multi-physics coupled dynamic behavior within the wind farm. The working principles of the aerodynamic module, the whole-machine dynamics and control module, and the power generation and conversion module will be described in detail later, and will not be described in detail here.

[0044] The wind farm-level controller 101 in this embodiment is responsible for uniformly coordinating the output and operating status of the wind turbines in the entire wind farm, planning the actual output of active and reactive power of each wind turbine, and feeding back the key operating status of each wind turbine module to the wind farm-level controller 101 for control decisions.

[0045] Power grid model 102 describes the transmission line topology of a specific wind farm, where each wind turbine module has an independent electrical path, such as... Figure 3 The diagram shows the circuit schematic between the power grid model and the wind turbine modules. Each wind turbine module (wind turbine 1, wind turbine 2, wind turbine 3, ..., wind turbine n) is independently connected to the transmission line network of the power grid model 102.

[0046] Current wind farm simulations cannot simultaneously simulate the impact of all wind turbines within a wind farm with a dynamic wind flow field on the transient characteristics of the power grid, as well as the feedback of power grid transients (such as voltage dips, short-circuit faults, open-circuit faults, low-frequency oscillations, etc.) on the aerodynamic forces, transmission chain torques, component loads, and control behaviors of all wind turbines within the farm. They lack the ability to simulate two-way dynamic coupling between the wind farm and the power grid. However, the wind farm and power grid two-way coupled dynamic simulation system of this application, through the construction of a multi-physics coupling simulation between the wind farm-level controller 101, the power grid model 102, and the wind farm model 103, can simulate the power grid transients of the power grid model 102. These power grid transients include any of the following types: voltage dips, short-circuit faults, open-circuit faults, low-frequency oscillations, etc. That is, the wind farm and grid bidirectional coupling dynamic simulation system of this application embodiment can also simulate various fault states of the grid model 102. Through bidirectional coupling simulation of wind farm dynamics and grid dynamics, the operating conditions of wind turbines under grid fault states can be simulated, which improves the accuracy of wind farm simulation of grid faults and provides effective support for wind farm design, control strategy optimization and grid stability analysis.

[0047] As shown in Figure 4, this is a schematic diagram of the specific structure of the wind farm and grid bidirectional coupling dynamic simulation system according to an embodiment of this application. The structure of the wind turbine module is further refined. The wind turbine module in this embodiment includes an aerodynamic module 1032, a whole-machine dynamics and control module 1033, and a power generation and converter module 1034. Among them, the aerodynamic module 1032 is used to simulate the aerodynamic forces acting on the wind turbine rotor, the whole-machine dynamics and control module 1033 is used to simulate the dynamics module of the wind turbine mechanical components and the wind turbine controller, and the power generation and converter module 1034 is used to simulate the generator module and frequency converter module of the wind turbine.

[0048] The airflow field module 1031 outputs the current time step t of each wind turbine module. n The wind speed at the rotor surface (via data stream A1) is transmitted to the corresponding aerodynamic module 1032 of the wind turbine module. The aerodynamic module 1032 is configured to adjust according to the current time step t. n Wind speed on the wind turbine surface, current time step t n Fan operating status S n The aerodynamic forces acting on the wind turbine blades are calculated and fed back to the airflow field module 1031 via data stream A2. The airflow field module 1031 obtains wake field information by solving the dynamic wake model driven by the aerodynamic forces, thus updating the airflow field for the next time step and forming a wake loop. That is, after the aerodynamic forces (via data stream A2) are fed back to the airflow field module 1031, the module uses its internal dynamic wake model, with the aerodynamic forces as input, to solve for the wake field information. The airflow field module 1031 then recalculates the wind conditions in each region of the wind field, updating the airflow field for the next time step. Therefore, the next time step t can be obtained based on the updated airflow field.n+1 The wind speed on the rotor surface, so as to be in the next time step t n+1 This is used to form a wake closed loop. The aerodynamic module 1032 is also configured to send aerodynamic forces (via data stream B1) to the overall dynamics and control module 1033.

[0049] refer to Figure 2 This application considers that when wind blows over the blades of a wind turbine, a "windfall shadow" region with slower wind speed and increased turbulence is formed behind the blades, similar to the wake left by a ship on the water. If a downstream wind turbine is located in this "shadow zone," power generation will decrease, and the load on the turbine will increase. If a static model is used, it assumes that the wake region behind the wind turbine responds instantaneously. However, in reality, if the wind turbine pitches or yaws, the development, deflection, and recovery of the wake take time and do not change instantaneously. Therefore, the wind flow field module 1031 of this application adopts a dynamic wake model. Compared with the static model, the dynamic wake model can simulate the physical process of the wake changing over time, which is more conducive to improving the accuracy of the acquired wake field information and improving the accuracy of the dynamic simulation of the wind flow field and the power grid.

[0050] The dynamic wake model in this application embodiment is the DWM (Dynamic Wake Meandering) model. The DWM model is a medium-fidelity engineering model used in the wind power field to simulate the dynamic characteristics of wind turbine wakes. It is recorded in Appendix E of the IEC (International Electrotechnical Commission) standard, specifically in the IEC standard with standard number IEC61400-1:2019.

[0051] The overall dynamics and control module 1033 in this embodiment is configured to adjust the aerodynamic force and the current time step t of the generator according to the aerodynamic force and the current time step t of the generator. n Actual electromagnetic torque Te_actual n Current time step t n Fan operating status S n Get the next time step t n+1 Fan operating status S n+1 Among them, the operating status S of the wind turbine n+1 At least including generator speed ω_gen n+1 Wind turbine rotation speed ω_rotor n+1 Blade pitch angle β n+1 In this application embodiment, the next time step t n+1 Fan operating status S n+1 Feedback is sent to the pneumatic module 1032, indicating the fan's operating status S. n+1The wind turbine rotation speed ω_rotor n+1 Blade pitch angle β n+1 (Through data stream B2) feedback is sent to pneumatic module 1032, as the pneumatic module 1032 will use this feedback in the next time step t. n+1 Calculate the state input quantities of the blade aerodynamic forces.

[0052] The overall dynamics and control module 1033 in this embodiment is further configured to acquire the current time step t of the wind farm level controller 101. n The instruction signal (via data stream E), current time step t n The command signals include the active power control command P_cmd n Reactive power control command Q_cmd n and set the current time step t n Command signal, current time step t n Fan operating status S n (Through data stream C1) it is sent to the power generation converter module 1034. Specifically, the overall dynamic control module 1033 sends the current time step t. n Fan operating status S n The generator speed ω_gen n Send to generator converter module 1034.

[0053] The power generation and converter module 1034 of this application embodiment is configured to adjust according to the current time step t n Command signal, current time step t n Fan operating status S n The generator speed ω_gen n Current time step t n Power supply parameters (terminal voltage amplitude U of the bus in the model of wind turbine connection to the power grid) n Voltage phase φ n Line frequency f n Get the next time step t n+1 Actual electromagnetic torque Te_actual n+1 and the next time step t n+1 The wind turbine power information, and the next time step t n+1 Actual electromagnetic torque Te_actual n+1 and the next time step t n+1 The wind turbine power information (via data stream C2) is fed back to the overall dynamic and control module 1033; the power generation converter module 1034 is configured to transmit the power at the next time step t. n+1 The wind turbine power information (via data stream D1) is sent to the power grid model 102.

[0054] Among them, the next time step t n+1The wind turbine power information includes the actual active power P_actual injected into the grid model 102 bus. n+1 and actual reactive power Q_actual n+1 Current time step t n The power supply parameters include the terminal voltage amplitude U of the wind turbine module connected to the power grid model 102 bus. n Voltage phase φ n Line frequency f n ; Next step n+1 The power supply parameters include the terminal voltage amplitude U of the wind turbine module connected to the power grid model 102 bus. n+1 Voltage phase φ n+1 Line frequency f n+1 .

[0055] The overall dynamics and control module 1033 is also configured to control the next time step t n+1 Wind turbine power information (actual active power P_actual) n+1 and actual reactive power Q_actual n+1 The wind turbine critical state variables (via data stream E) are transmitted to the wind farm-level controller 101. These critical state variables include, but are not limited to, pitch angle and generator speed ω_gen. n+1 Component loads, etc., the wind farm level controller 101 obtains the next time step t n+1 After obtaining the wind turbine power information and key status parameters, based on the next time step t n+1 The wind turbine power information and key status parameters of the wind turbine are updated in the next time step t. n+1 Command signals (including active power control command P_cmd) n+1 Reactive power control command Q_cmd n+1 ).

[0056] The power grid model 102 in this embodiment is configured to adjust according to the next time step t. n+1 Wind turbine power information (actual active power P_actual) n+1 and actual reactive power Q_actual n+1 Calculate the equivalent injection current I of at least one wind turbine module. n Specifically, the power grid model 102 will use the actual active power P_actual n+1 and actual reactive power Q_actual n+1 Based on the current power grid model 102, the terminal voltage amplitude U corresponding to the wind turbine connected to the power grid bus should be... n Voltage phase φ n Line frequency f n Calculate the equivalent injection current I of the injected power grid model 102. nThen, the power grid model 102 performs electromechanical transient solutions based on the equivalent injection current I of at least one wind turbine module. n Get the next time step t n+1 The power supply parameters (i.e., the next time step t of the power grid bus corresponding to each wind turbine module) n+1 Terminal voltage amplitude U n+1 Voltage phase φ n+1 and line frequency f n+1 ), and will the next time step t n+1 The power supply parameters (via data stream D2) are fed back to the power generation converter module 1034.

[0057] After all modules have completed their calculations at each time step, the calculation results are written to the output timing file for display and analysis.

[0058] The wind farm and power grid bidirectional coupling dynamic simulation system of this application embodiment performs the next round of calculation if the simulation time has not reached the set termination time of the simulation case. The program exits when the simulation time reaches the set termination time of the simulation case. Through the iterative iteration of the above simulation steps, this application embodiment achieves bidirectional coupling simulation of wind farm dynamics (including dynamic wind flow field, mutual influence of multiple wind turbines, multi-wind turbine dynamics, wind farm control strategies, etc.) and power grid dynamics, thus improving the accuracy of wind farm simulation.

[0059] This application belongs to the field of renewable energy power generation system simulation technology. It can perform high-fidelity simulation of the dynamic wind flow field, multiple wind turbines, wake, wind farm level controller, and dynamic coupling relationship between the grid model within a unified simulation framework, providing technical support for wind farm design, wind farm operation optimization, control strategy verification, and grid stability analysis.

[0060] The embodiments of this application can simulate the dynamic coupling relationship between multiple physical fields such as wind flow field, wind field, wind turbine, and power grid. Based on this, various control strategies can be explored and verified, including but not limited to wind turbine control strategy, wind turbine frequency converter control strategy, wind field level control strategy, and hybrid collaborative control strategy.

[0061] The embodiments of this application can be extended to the simulation of source-grid-load-storage scenarios, such as... Figure 5 The diagram shown is a schematic of the dynamic simulation system for bidirectional coupling between wind farm and power grid in the source-grid-load-storage scenario. The wind farm station model in this application is used as a power supply station model on the source-grid-load-storage scenario.

[0062] The dynamic simulation system for bidirectional coupling between wind farms and power grids in this application embodiment further includes: a hybrid collaborative controller, at least one load farm model, at least one energy storage station model, a load farm-level controller connected to the load farm model, and an energy storage farm-level controller connected to the energy storage station model; the hybrid collaborative controller is connected to the wind farm-level controller, the load farm-level controller, and the energy storage farm-level controller respectively. In addition to the power supply station model including the wind farm model, this application embodiment may also include other types of power supply station models, such as photovoltaic (PV) farm models; in the case of including a PV farm model, this application embodiment also includes a PV farm-level controller connected to the PV farm model, and the hybrid collaborative controller is also connected to the PV farm-level controller. The following description uses a power supply station model including a wind farm model as an example; the implementation principle of the PV farm model or a combination of multiple power supply station models is similar and will not be repeated here.

[0063] The wind farm station model in this embodiment can serve as a power supply station model on the power generation side. In this scenario, the power grid model can be extended beyond simply mounting the wind farm station model; it can also mount other power supply station models (such as photovoltaic station models) and electrical equipment (load station models). The wind farm-level controller, energy storage station-level controller, and load station-level controller are all controlled by a higher-level hybrid coordinated controller and can transmit power commands and actual power information with the hybrid coordinated controller. Specifically, the hybrid coordinated controller can issue total active power commands (P_total_cmd) and total reactive power commands (Q_total_cmd) to the wind farm-level controller, and simultaneously obtain total actual active power (P_total_actual) and total actual reactive power (Q_total_actual) from the wind farm-level controller.

[0064] The wind farm station model in this application embodiment can be used as a power supply station model on the power generation side for simulation of the source-grid-load-storage scenario. Through high-fidelity multi-physics coupling modeling and collaborative control strategies, the stability of the power grid and the ability to absorb renewable energy under the access of new energy sources can be improved.

[0065] In the source-grid-load-storage scenario, the energy storage station model is a battery energy storage system model that realizes the storage and release of energy. It includes a grid-type energy storage model to actively establish and support the voltage and frequency of the power grid in situations such as weak grid and off-grid. The load-side station model reflects the power usage characteristics of different power consumption sides. Different power consumption sides will have different load curves, which will put forward different requirements on the power change rate of the power supply side wind farm station model (or a combination of wind farm station model and other power supply station models).

[0066] The wind farm station model (or a combination of wind farm station model, photovoltaic station model, or other power supply station models), load station model, and energy storage station model in this application embodiment can all be instantiated multiple times. The simulation supports the configuration of multiple wind farm stations, multiple energy storage stations, and multiple load stations. All generation-side equipment and consumption-side equipment are connected to the grid side. Detailed network topology is established for each wind turbine, each energy storage module, and each load module. It can calculate the power flow, power loss, voltage amplitude, voltage phase, frequency, and other characteristics on the electrical connection lines, realizing functions such as dynamic power flow calculation and transient simulation. It can also simulate operating conditions such as voltage drop, line short circuit and open circuit, and low-frequency oscillation.

[0067] Power coordination among power generation, grid, load, and storage is controlled by a hybrid coordinating controller, achieving safe and stable production while ensuring optimal economy, minimal power curtailment, and minimal energy storage consumption. The input sources for the hybrid coordinating controller are: first, real-time state variables from wind farm models (or combinations of wind farm models with other power supply models), energy storage models, and load models; and second, forecast models, which provide the hybrid coordinating controller with forecasts of wind speed, irradiance, and temperature for different future periods. The wind speed forecast model within the forecast model provides wind speed forecasts for all wind turbines within the wind farm at different time scales based on global mesoscale forecast information and local wind farm measurements, which are then provided to the coordinating controller for power planning.

[0068] Hybrid coordinating controllers serve two main functions. First, they perform optimization calculations based on forecast data from forecasting models and the power consumption planning of load farms, planning the future power planning curves for power generation, grid, load, and storage (including wind farms and multi-storage farms) to achieve optimal economic efficiency. Second, they close the power loop of power generation, grid, load, and storage to the planned value on a smaller time scale, while stabilizing power fluctuations across all parties. The hybrid coordinating controller issues power commands to the execution units of each power generation, grid, load, and storage unit. Taking a wind farm as an example, the total power command issued by the hybrid coordinating controller is subdivided by the wind farm-level controller into the power values ​​that each wind turbine module should achieve. Then, the individual controllers of the wind turbine modules execute the power commands, transforming them into specific pitch angle and torque control signals.

[0069] like Figure 6As shown, this is the active power time series on the source, grid, and load sides under a source-grid-load-storage simulation scenario. The horizontal axis represents time, and the vertical axis represents the active power value. The five time series curves in the figure represent: the theoretical value of wind farm active power, the wind farm active power command, the actual value of wind farm active power, the actual value of load active power, and the actual value of grid power measured on the tie line. To reflect the dynamic characteristics of the wind turbine and the grid, a 50% load drop was set at 7500s in the simulation.

[0070] like Figure 7 As shown, the wind speed amplitude at each wind turbine location is displayed in a source-grid-load-storage simulation scenario. The horizontal axis represents time, and the vertical axis represents wind speed amplitude. Only the time sequence of three wind turbines (Wind Turbine 1, Wind Turbine 2, and Wind Turbine 3) is shown here. The wind speed at each turbine location is affected by terrain, weather, and wake, which better reflects the wind conditions experienced by wind turbines in a real wind field.

[0071] like Figure 8 The figures show the time series diagrams for generator speed, pitch angle, hub center torque Mx, and tower base bending moment My of each wind turbine in a source-grid-load-storage simulation scenario. The top left figure shows the time series diagram for the generator speed (GenSpeed) of the three wind turbines (Wind Turbine 1, Wind Turbine 2, and Wind Turbine 3); the top right figure shows the time series diagram for the pitch angle (Pitch) of the three wind turbines (Wind Turbine 1, Wind Turbine 2, and Wind Turbine 3); the bottom left figure shows the time series diagram for the hub center torque (Hub Mx) of the three wind turbines (Wind Turbine 1, Wind Turbine 2, and Wind Turbine 3); and the bottom right figure shows the time series diagram for the tower base bending moment (Hub Tower Base My) of the three wind turbines (Wind Turbine 1, Wind Turbine 2, and Wind Turbine 3).

[0072] like Figure 9The diagram shows the timing of the electrical output of each wind turbine in a source-grid-load-storage simulation scenario. The top left diagram shows the timing of the voltage magnitude of the bus connected to the three wind turbines (wind turbine 1, wind turbine 2, and wind turbine 3); the top right diagram shows the timing of the frequency of the three wind turbines (wind turbine 1, wind turbine 2, and wind turbine 3); the bottom left diagram shows the timing of the active power of the generators of the three wind turbines (wind turbine 1, wind turbine 2, and wind turbine 3), and displays the active power allocation commands of the three wind turbines (active power allocation command of wind turbine 1, active power allocation command of wind turbine 2, and active power allocation command of wind turbine 3); the bottom right diagram shows the timing of the reactive power of the generators of the three wind turbines (wind turbine 1, wind turbine 2, and wind turbine 3).

[0073] Another embodiment of this application relates to a dynamic simulation method for bidirectional coupling between a wind farm and a power grid, applied to a dynamic simulation system for bidirectional coupling between a wind farm and a power grid. A schematic diagram of the structure of the dynamic simulation system for bidirectional coupling between a wind farm and a power grid is shown below. Figure 1 , Figure 4 As shown in the figure, the specific flowchart of the dynamic simulation method for bidirectional coupling between wind farm and power grid in this application embodiment is as follows. Figure 10 As shown, the dynamic simulation method for bidirectional coupling between wind farms and power grids in this embodiment includes the following steps:

[0074] Step 201: The wind flow field module obtains the wind speed on the rotor surface at the current time step and outputs it to the wind turbine module.

[0075] Step 202: The wind turbine module obtains the wind turbine power information for the next time step based on the wind turbine surface wind speed at the current time step and the command signal of the wind farm level controller at the current time step, and transmits it to the power grid model.

[0076] like Figure 4 As shown, the wind turbine module further includes an aerodynamic module, a whole-machine dynamics and control module, and a power generation and converter module.

[0077] The aerodynamic module calculates the aerodynamic forces acting on the turbine blades based on the rotor surface wind speed and the turbine operating status at the current time step, and feeds this calculation back to the airflow field module. The airflow field module then uses these aerodynamic forces to solve the dynamic wake model and obtain wake field information to update the airflow field for the next time step. Based on the updated airflow field, the airflow field module obtains the rotor surface wind speed for the next time step. The aerodynamic module then sends these aerodynamic forces to the overall dynamics and control module. The overall dynamics and control module calculates the aerodynamic forces based on the actual electromagnetic torque of the generator at the current time step and the turbine operating status at the current time step. The system obtains the wind turbine operating status for the next time step and feeds it back to the aerodynamic module. The overall dynamics and control module obtains the command signal for the current time step from the wind farm-level controller and sends the command signal and the wind turbine operating status for the current time step to the generator-converter module. The generator-converter module obtains the actual electromagnetic torque and wind turbine power information for the next time step based on the command signal, the wind turbine operating status, and the power supply parameters for the current time step and feeds it back to the overall dynamics and control module. The generator-converter module sends the wind turbine power information for the next time step to the power grid model.

[0078] Step 203: The power grid model obtains the power supply parameters of at least one wind turbine module in the next time step based on the wind turbine power information of at least one wind turbine module in the next time step, and feeds them back to the wind turbine module.

[0079] The power grid model calculates the equivalent injection current based on the wind turbine power information of the next time step, obtains the power supply parameters of the next time step based on the equivalent injection current of at least one wind turbine module, and feeds them back to the power generation and converter module.

[0080] Another embodiment of this application relates to an electronic device, such as... Figure 11 The diagram shown is a structural block diagram of the electronic device of this embodiment. The electronic device includes at least one processor 301 and a memory 302 communicatively connected to at least one processor 301. The memory 302 stores instructions that can be executed by at least one processor 301. The instructions are executed by at least one processor 301 to enable at least one processor 301 to execute the dynamic simulation method of bidirectional coupling between wind farm and power grid as described above.

[0081] The memory 302 and processor 301 are connected via a bus, which can include any number of interconnecting buses and bridges. The bus connects various circuits of one or more processors 301 and memory 302 together. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by processor 301 is transmitted over a wireless medium via an antenna, which further receives data and transmits it to processor 301.

[0082] Processor 301 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory 302 can be used to store data used by processor 301 during operation.

[0083] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the method embodiments described above.

[0084] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0085] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A dynamic simulation system for bidirectional coupling between a wind farm and a power grid, characterized in that, include: Wind farm level controller, power grid model, wind farm station model, wherein the wind farm station model includes a wind flow field module and at least one wind turbine module; At least one of the wind turbine modules is respectively connected to the wind farm level controller, the power grid model, and the wind flow field module; The airflow field module is configured to acquire the wind turbine surface wind speed at the current time step and output it to the wind turbine module; The wind turbine module is configured to obtain the wind turbine power information for the next time step based on the wind turbine surface wind speed at the current time step and the command signal of the wind farm level controller at the current time step, and transmit it to the power grid model. The power grid model is configured to obtain the power supply parameters of at least one wind turbine module at the next time step based on the wind turbine power information of at least one wind turbine module at the next time step, and feed them back to the wind turbine module. The wind turbine module includes an aerodynamic module, a whole-machine dynamics and control module, and a power generation and converter module; The aerodynamic module is configured to calculate the aerodynamic force on the wind turbine blades based on the wind speed at the rotor surface and the wind turbine operating state at the current time step, and feed the aerodynamic force back to the airflow field module. The airflow field module obtains wake field information by solving the dynamic wake model driven by the aerodynamic force, so as to update the airflow field at the next time step. The airflow field module obtains the wind speed at the rotor surface under the updated airflow field at the next time step. The aerodynamic module is also configured to send the aerodynamic force to the overall dynamic and control module. The overall dynamics and control module is configured to obtain the wind turbine operating status of the next time step based on the aerodynamic force, the actual electromagnetic torque of the generator at the current time step, and the wind turbine operating status at the current time step, and feed it back to the aerodynamics module; the overall dynamics and control module is also configured to obtain the command signal of the wind farm level controller at the current time step, and send the command signal of the current time step and the wind turbine operating status at the current time step to the power generation and converter module; The power generation and converter module is configured to obtain the actual electromagnetic torque and wind turbine power information for the next time step based on the command signal of the current time step, the wind turbine operating status of the current time step, and the power supply parameters of the current time step, and feed them back to the whole machine dynamics and control module; the power generation and converter module is configured to send the wind turbine power information for the next time step to the power grid model.

2. The dynamic simulation system for bidirectional coupling of wind farm and power grid according to claim 1, characterized in that, The overall dynamics and control module is also configured to transmit the wind turbine power information and key wind turbine status quantities of the next time step to the wind farm level controller; the wind farm level controller is configured to update the command signal of the next time step according to the wind turbine power information and key wind turbine status quantities of the next time step; the key wind turbine status quantities include at least the pitch angle, generator speed, and component load.

3. The dynamic simulation system for bidirectional coupling of wind farm and power grid according to claim 2, characterized in that, The wind turbine power information for the next time step includes the actual active power and actual reactive power injected into the bus of the power grid model; the power supply parameters for the next time step include the terminal voltage amplitude, voltage phase, and line frequency of the bus of the wind turbine module connected to the power grid model. The power grid model is configured to calculate the equivalent injection current of at least one of the wind turbine modules based on the wind turbine power information of the next time step, obtain the power supply parameters of the next time step based on the equivalent injection current of at least one of the wind turbine modules, and feed them back to the power generation converter module.

4. The dynamic simulation system for bidirectional coupling of wind farm and power grid according to claim 1, characterized in that, The power grid model is also configured to simulate power grid transients, which include any of the following types: Voltage drop, short circuit fault, open circuit fault, low frequency oscillation.

5. The dynamic simulation system for bidirectional coupling of wind farm and power grid according to claim 1, characterized in that, The dynamic simulation system for bidirectional coupling between wind farms and power grids further includes: a hybrid collaborative controller, at least one load station model, at least one energy storage station model, a load station-level controller connected to the load station model, and an energy storage station-level controller connected to the energy storage station model. The hybrid collaborative controller is connected to the wind farm level controller, the load field level controller, and the energy storage field level controller, respectively.

6. The dynamic simulation system for bidirectional coupling of wind farm and power grid according to claim 5, characterized in that, The dynamic simulation system for bidirectional coupling between wind farms and power grids also includes: a photovoltaic power station model and a photovoltaic field-level controller connected to the photovoltaic power station model; the hybrid collaborative controller is also connected to the photovoltaic field-level controller.

7. A dynamic simulation method for bidirectional coupling between wind farms and power grids, characterized in that, The system is applied to the dynamic simulation system for bidirectional coupling between wind farms and power grids as described in any one of claims 1 to 6.

8. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the dynamic simulation method for bidirectional coupling between wind farms and power grids as described in claim 7.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic simulation method for bidirectional coupling between wind farm and power grid as described in claim 7.

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