New energy electric field frequency modulation control system

Abstract

The invention relates to the field of wind power plant control systems, and particularly discloses a new energy electric field frequency modulation control system, which comprises a data acquisition module used for acquiring operation data of each fan in a wind power plant in real time and acquiring power grid frequency information; the fan characteristic analysis module is used for analyzing operation characteristics of each fan under different working conditions and establishing a fan power-wind speed model and a comprehensive operation characteristic model; and the power calculation and distribution module is used for calculating frequency modulation power required by the wind power plant according to the power grid frequency deviation and the operation characteristics of the fan and distributing the frequency modulation power by adopting an optimization algorithm. According to the new energy electric field frequency modulation control system, through accurate fan characteristic modeling and comprehensive consideration of various factors, a more accurate fan nonlinear operation characteristic model is established, the accuracy of power calculation is greatly improved, and frequency modulation power calculation errors caused by complex fan operation characteristics are effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of wind farm control systems, and in particular to a new energy wind farm frequency modulation control system. Background Art

[0002] With the growing global demand for clean energy, new energy wind farms have developed rapidly and occupied an increasingly important position in the power system. As a major form of new energy power generation, the output power of wind farms has significant volatility, which is mainly attributed to the intermittent and uncertain nature of wind energy itself. At the same time, the operating characteristics of wind turbines are relatively complex. In different wind speed ranges, the power-wind speed curve of wind turbines shows nonlinear changes, not a simple linear relationship. However, the traditional frequency modulation power calculation method often uses a simple linear model. This rough calculation method will inevitably lead to deviations in the calculation of frequency modulation power demand when facing the actual operation of wind turbines. In addition, due to differences in manufacturing processes and installation locations, the actual operating characteristics of each wind turbine in the wind farm are different. However, many wind farms currently use a unified power allocation strategy when allocating power, without fully considering the differences in characteristics between individual wind turbines, making it difficult to accurately make the wind farm output power that meets the frequency modulation requirements. This series of problems ultimately leads to a large deviation between the actual power and the target power of the wind farm during the frequency modulation process, affecting the precise regulation of the grid frequency.

[0003] Therefore, it is necessary to propose a new energy electric field frequency modulation control system to solve the above problems. Summary of the invention

[0004] The main purpose of the present invention is to provide a new energy electric field frequency modulation control system, which can effectively solve the problems in the background technology.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] A new energy electric field frequency modulation control system, comprising:

[0007] A data acquisition module is used to collect the operating data of each wind turbine in the wind farm and the grid frequency information in real time, wherein the operating data of the wind turbine includes but is not limited to wind speed, wind turbine output power, pitch angle, and generator efficiency;

[0008] The fan characteristic analysis module is used to analyze the operating characteristics of each fan under different working conditions and establish a fan power-wind speed model and a comprehensive operating characteristic model;

[0009] The power calculation and allocation module is used to calculate the frequency modulation power required by the wind farm according to the grid frequency deviation and the operating characteristics of the wind turbine, and to allocate the frequency modulation power using an optimization algorithm;

[0010] The frequency modulation execution module controls the operating parameters of the wind turbines according to the frequency modulation power instructions of each wind turbine determined by the power calculation and allocation module to realize the frequency modulation output of the wind farm;

[0011] The monitoring and evaluation module is used to monitor various parameters in the frequency regulation process of the wind farm in real time, including but not limited to wind turbine operating parameters, grid frequency, and wind farm output power. It also evaluates the frequency regulation effect and adjusts and optimizes system parameters and control strategies based on the evaluation results.

[0012] Preferably, the specific implementation steps of the fan characteristic analysis module include:

[0013] S1.1: Using the historical operation data acquired by the data acquisition module, the power-wind speed curve of the wind turbine is fitted by a data fitting algorithm to obtain a nonlinear power-wind speed model of different wind turbines;

[0014] S1.2: Analyze the influence of pitch angle and generator efficiency on wind turbine output power, and establish a comprehensive operation characteristic model through multivariate regression analysis. The correction formula of pitch angle to power is: P corr =P×f(β), where P corr is the corrected power, P is the original power, β is the pitch angle, and f(β) is the pitch angle correction function;

[0015] The generator efficiency formula is: η = h(P, N), where P is the wind turbine output power, N is the generator speed, and h is a function of the relationship between generator efficiency and power and speed;

[0016] S1.3: Calculate the mean and standard deviation of each wind turbine characteristic parameter to quantify the degree of variation between wind turbines.

[0017] Preferably, the specific implementation steps of the power calculation and allocation module include:

[0018] S2.1: According to the grid frequency deviation Δf, determine the total frequency regulation power demand P of the wind farm according to the grid frequency regulation requirements req , using the proportional-integral control algorithm to calculate P req =K p Δf+K i ∫Δfdt, where K p and K i are the proportional and integral coefficients of the PI controller;

[0019] S2.2: Particle swarm optimization algorithm is used to req Assigned to each fan, let the frequency modulation power assigned to the i-th fan be P i , the optimization objective function is: Where P i,outis the frequency modulation power actually output by the i-th wind turbine, and n is the number of wind turbines in the wind farm.

[0020] Preferably, the implementation steps of the monitoring and evaluation module include:

[0021] S3.1: Establish a monitoring interface to display the operating status of each wind turbine, power distribution and grid frequency change curve;

[0022] S3.2: Use frequency modulation accuracy index to quantitatively evaluate the frequency modulation effect, where the frequency modulation accuracy index is: Where T is the evaluation period, P act is the actual frequency modulation power, P tar is the target FM power;

[0023] S3.3: According to the evaluation results, adjust the algorithm parameters in the power calculation and allocation optimization module.

[0024] Preferably, it also includes a fault diagnosis and fault tolerance module, which is used to receive fault data from the data acquisition module, the wind turbine characteristic analysis module, the power calculation and allocation module, the frequency regulation execution module and the wind turbine, and can take fault tolerance measures when a fault occurs to maintain the frequency regulation function of the wind farm or switch to a safe operation mode.

[0025] Preferably, it also includes an energy system integration module, which is used to coordinate the frequency regulation actions of the energy storage device and the wind turbine in the wind farm, and optimize the charging and discharging strategy of the energy storage system according to the grid frequency requirements and the wind turbine output power conditions, so as to achieve coordinated frequency regulation of the energy storage system and the wind farm.

[0026] Preferably, the implementation steps of the energy system integration module include:

[0027] S4.1: Monitor the state of charge and charging and discharging power limit parameters of the energy storage system in real time, and calculate the frequency regulation power component that the energy storage system should bear by combining the operation data of the wind turbine and the grid frequency deviation;

[0028] S4.2: Adopt the model predictive control method to determine the optimal charging and discharging power sequence of the energy storage system according to the dynamic characteristics of the energy storage system, cost factors and future grid frequency change trends;

[0029] S4.3: Cooperate with the frequency regulation execution module to synchronously send the control instructions of the energy storage system and the frequency regulation control signal of the wind turbine to ensure that the two work together.

[0030] Preferably, it also includes a meteorological prediction and preprocessing module, which accesses meteorological forecast data, predicts and analyzes future wind speed and wind direction meteorological conditions of the wind farm, and adjusts the operation strategy and frequency modulation preparation of the wind farm in advance according to the meteorological forecast results.

[0031] Preferably, the implementation steps of the weather forecast and preprocessing module include:

[0032] S5.1: Establish a data interface with a meteorological service provider or meteorological monitoring agency to obtain meteorological forecast data for the area where the wind farm is located, including but not limited to short-term and medium-term wind speed, wind direction, temperature, and air pressure information;

[0033] S5.2: Use meteorological data processing and analysis algorithms to process and optimize meteorological forecast data;

[0034] S5.3: Adjust the operating parameters of the wind turbine in advance based on the weather forecast results.

[0035] Preferably, it also includes a communication and coordination module, which is used for communication between each wind turbine, each module, the control center and the power grid dispatching center, and coordinates data interaction and command transmission between each module.

[0036] Compared with the prior art, the present invention provides a new energy electric field frequency modulation control system, which has the following beneficial effects:

[0037] The frequency regulation control system of the new energy electric field, through precise wind turbine characteristic modeling and comprehensive consideration of multiple factors, establishes a more accurate nonlinear operating characteristic model of the wind turbine, greatly improves the accuracy of power calculation, and effectively reduces the frequency regulation power calculation error caused by the complex operating characteristics of the wind turbine. Secondly, the optimized power allocation strategy uses advanced optimization algorithms and fully considers the individual differences between wind turbines. It can more reasonably allocate frequency regulation power and significantly reduce the deviation between actual power and target power, thereby greatly improving the frequency regulation accuracy and enhancing the reliability of wind farm frequency regulation. In addition, the closed-loop monitoring and adaptive adjustment functions can monitor various system operation parameters in real time, and automatically optimize system parameters and control strategies according to the frequency regulation effect, so that the system can better adapt to the dynamic changes of the wind farm operating environment and the grid frequency regulation requirements, further improve the stability and adaptability of the system, and effectively promote the efficient and stable access and consumption of new energy electricity in the power grid, and provide stronger support for ensuring the safe and stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the connection principle of the system of the present invention. DETAILED DESCRIPTION

[0039] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0040] like Figure 1 As shown, a new energy electric field frequency regulation control system includes a data acquisition module, a wind turbine characteristic analysis module, a power calculation and allocation module, a frequency regulation execution module, a monitoring and evaluation module, etc., wherein the data acquisition module is used to collect the operating data of each wind turbine in the wind farm in real time and collect the grid frequency information. Specifically, it is necessary to install various sensors on each wind turbine in the wind farm to measure the corresponding operating parameters. The sensors include but are not limited to wind speed sensors, wind direction sensors, temperature sensors, speed sensors, current sensors, voltage sensors, etc., and transmit the data to the central data processing unit through a data transmission network (optical fiber network or wireless sensor network), establish a communication connection with the grid monitoring system, obtain the grid frequency data, and ensure the synchronization and accuracy of the data. The collected wind turbine operating data includes but is not limited to wind speed, wind turbine output power, pitch angle, generator efficiency, and collects grid frequency information to determine the frequency regulation demand according to the grid frequency deviation;

[0041] The wind turbine characteristic analysis module is used to analyze the operating characteristics of different wind turbines under various working conditions, establish an accurate wind turbine power-wind speed model and a comprehensive operating characteristic model that considers other factors (pitch angle, generator efficiency, etc.), and identify the characteristic differences between wind turbines due to manufacturing differences, installation locations, etc., to provide a basis for subsequent power calculation and allocation; the specific implementation steps include:

[0042] Step 1: Using the historical operation data acquired by the data acquisition module, a data fitting algorithm (preferably the least squares method) is used to fit the power-wind speed curve of the wind turbine to obtain a nonlinear power-wind speed model of different wind turbines;

[0043] Step 2: Analyze the influence of other operating parameters on the wind turbine output power, and establish a comprehensive operating characteristic model through multiple regression analysis and other methods. The correction formula of pitch angle to power is: P corr =P×f(β), where P corr is the corrected power, P is the original power, β is the pitch angle, and f(β) is the pitch angle correction function;

[0044] The generator efficiency formula is: η = h(P, N), where P is the wind turbine output power, N is the generator speed, and h is a function of the relationship between generator efficiency and power and speed;

[0045] Step 3: Calculate the mean and standard deviation of each fan characteristic parameter to quantify the degree of difference between fans.

[0046] The power calculation and allocation module is used to accurately calculate the frequency modulation power required by the wind farm according to the grid frequency deviation and the operating characteristics of the wind turbines. At the same time, based on the characteristic differences of each wind turbine, an optimization algorithm is used to reasonably allocate the frequency modulation power to minimize the deviation between the wind farm output power and the target frequency modulation power.

[0047] The specific steps include:

[0048] Step 1: According to the grid frequency deviation Δf, determine the total frequency regulation power demand P of the wind farm according to the grid frequency regulation requirements req , using the proportional-integral (PI) control algorithm to calculate P req =K p Δf+K i ∫Δfdt, where K p and K i are the proportional and integral coefficients of the PI controller;

[0049] Step 2: Use particle swarm optimization algorithm to req Assigned to each fan, let the frequency modulation power assigned to the i-th fan be P i , the optimization objective function is: Where P i,out is the frequency modulation power actually output by the i-th wind turbine, n is the number of wind turbines in the wind farm, and the constraints include the upper and lower limits of power and speed limit of each wind turbine;

[0050] The frequency modulation execution module is used to control the operating parameters (pitch angle, generator torque, etc.) of the wind turbines according to the frequency modulation power instructions of each wind turbine determined by the power calculation and allocation optimization module, so as to realize the frequency modulation output of the wind farm;

[0051] The monitoring and evaluation module is used to monitor various parameters in the frequency regulation process of the wind farm in real time, including wind turbine operating parameters, grid frequency, wind farm output power, etc., and evaluate the frequency regulation effect at the same time, and adjust and optimize the system parameters and control strategies according to the evaluation results;

[0052] The specific implementation steps include:

[0053] Step 1: Establish a monitoring interface to intuitively display the operating status of each wind turbine, power distribution, grid frequency change curve and other information;

[0054] Step 2: Use performance evaluation indicators (frequency modulation accuracy indicators Where T is the evaluation period, P act is the actual frequency modulation power, P tar Quantitative evaluation of the frequency modulation effect is performed (target frequency modulation power);

[0055] Step 3: According to the evaluation results, adjust the algorithm parameters (PI controller coefficients, particle swarm optimization algorithm parameters) in the power calculation and allocation optimization module to improve the frequency modulation accuracy and system performance.

[0056] This application, by comprehensively considering multiple factors, establishes a more accurate nonlinear operating characteristic model of the fan, improves the accuracy of power calculation, adopts advanced optimization algorithms for frequency modulation power distribution, fully considers the differences between fans, and effectively reduces the deviation between actual power and target power. At the same time, it has real-time monitoring and evaluation functions, and can automatically adjust system parameters and control strategies according to the frequency modulation effect to achieve adaptive optimization operation of the system.

[0057] In addition, the system also includes a fault diagnosis and fault tolerance module, which is used to monitor the operating status of each component of the wind farm frequency regulation control system and the wind turbine itself in real time, and promptly discover possible faults, such as sensor failure, communication failure, wind turbine hardware failure, etc., and can take fault tolerance measures when a fault occurs, so as to maintain the frequency regulation function of the wind farm as much as possible or switch to a safe operation mode, so as to avoid the frequency regulation of the entire wind farm being out of control or causing adverse effects on the power grid due to local faults;

[0058] The specific implementation method is that a fault diagnosis model can be established. Based on the parameter range and operating rules of each device during normal operation, the fault can be judged by comparing the real-time data with the normal threshold. For sensor failure, multi-sensor redundant measurement and data consistency verification methods can be used. When the deviation between a certain sensor data and other redundant sensor data exceeds the set range and lasts for a certain period of time, the sensor is judged to be faulty. Corresponding fault-tolerant strategies are formulated for different types of faults. When a sensor fails, data fusion or model-based estimation methods can be used to replace the faulty sensor data. When the fan hardware fails, the power output of the faulty fan can be reduced or its operation can be completely stopped according to the severity of the fault, and the frequency modulation power allocation strategy of other fans can be adjusted accordingly to compensate for the power loss of the faulty fan.

[0059] The system also includes an energy system integration module, which is used to coordinate the frequency modulation of the energy storage device (battery energy storage system, supercapacitor, etc.) in the wind farm and the wind turbine, giving full play to the fast charging and discharging characteristics of the energy storage system, further improving the flexibility and accuracy of the wind farm frequency modulation, and optimizing the charging and discharging strategy of the energy storage system according to the grid frequency demand and the wind turbine output power, realizing the coordinated frequency modulation of the energy storage system and the wind farm, and at the same time extending the service life of the energy storage system and improving its economy;

[0060] The specific implementation steps are:

[0061] Step 1: Real-time monitoring of the energy storage system's state of charge (SOC), charging and discharging power limits and other parameters, combined with the wind turbine's operating data and grid frequency deviation, calculates the frequency regulation power component that the energy storage system should bear. When the grid frequency drops and power needs to be increased, if the wind turbine's frequency regulation power is insufficient, a portion of the frequency regulation power demand can be allocated to the energy storage system for discharge supplementation based on the energy storage system's SOC and power capacity. Conversely, when the grid frequency rises and power needs to be absorbed, the energy storage system can be controlled to charge;

[0062] Step 2: Adopt advanced energy storage management strategies, preferably based on model predictive control (MPC) methods, consider multi-objective optimization such as dynamic characteristics of energy storage systems, cost factors, and future grid frequency change trends, and determine the optimal charging and discharging power sequence of energy storage systems. For example, the MPC optimization objective function can include minimizing wind farm frequency regulation power deviation, maximizing energy storage system service life, minimizing energy storage system operating costs, and other sub-objectives, and meet constraints such as SOC upper and lower limits and power limits of the energy storage system;

[0063] Step 3: Work closely with the frequency regulation execution module to synchronously send the control instructions of the energy storage system and the frequency regulation control signal of the wind turbine to ensure that the two work together to achieve precise regulation of the grid frequency.

[0064] It also includes a meteorological forecasting and preprocessing module, which is used to access meteorological forecast data, and forecast and analyze the meteorological conditions such as wind speed and wind direction of the wind farm in the future. At the same time, according to the meteorological forecast results, the operation strategy and frequency modulation preparation of the wind farm are adjusted in advance to cope with the impact of the upcoming meteorological changes on the output power of the wind farm, and improve the foresight and stability of frequency modulation;

[0065] The specific implementation steps include:

[0066] Step 1: Establish a data interface with a professional meteorological service provider or meteorological monitoring agency to obtain high-resolution meteorological forecast data for the area where the wind farm is located, including short-term (several hours) and medium-term (several days) wind speed, wind direction, temperature, air pressure and other information.

[0067] Step 2: Use meteorological data processing and analysis algorithms, preferably time series analysis and machine learning models (neural networks), to process and optimize meteorological forecast data to improve the accuracy of meteorological forecasts, and use historical meteorological data and wind turbine operation data to train the neural network so that it can better predict the output power change trend of the wind turbine under different meteorological conditions.

[0068] Step 3: According to the weather forecast results, adjust the operating parameters of the wind turbine in advance, such as pre-adjusting the pitch angle and optimizing the start and stop plan of the wind turbine, so as to reduce the impact of power fluctuations caused by weather changes on the frequency regulation system. At the same time, provide the weather forecast information to the power calculation and allocation optimization module, so that it can consider the impact of future weather conditions when formulating the frequency regulation strategy, and make power reserves or adjust the power allocation plan in advance.

[0069] It also includes a communication and coordination module, which is used to ensure efficient and stable communication between each wind turbine, data acquisition unit, control center and power grid dispatching center in the wind farm, and coordinate data interaction and command transmission between different modules to ensure the coordinated work of the entire frequency regulation control system. The communication and coordination module adopts high-speed and reliable communication network technology, preferably industrial Ethernet or a dedicated wireless communication network, to establish a multi-level communication architecture, and adopts a low-latency and high-bandwidth communication link between the wind turbine and the local data acquisition unit to ensure the rapid transmission of real-time data. Redundant communication lines are used between the data acquisition unit and the control center to improve the reliability of communication. An interface that meets the power grid communication standards is established between the control center and the power grid dispatching center to realize the interaction of frequency regulation instructions and power grid status information.

[0070] Operation principle: The data acquisition module collects the operation data of the wind turbines in the wind farm and the grid frequency data in real time, and transmits the data to the wind turbine characteristic analysis module, the power calculation and allocation optimization module and the monitoring and evaluation module respectively. After receiving the data from the data acquisition module, the wind turbine characteristic analysis module performs wind turbine characteristic analysis and modeling, establishes an accurate wind turbine power-wind speed model and a comprehensive operation characteristic model, and transmits the model parameters to the power calculation and allocation optimization module. The power calculation and allocation optimization module determines the total frequency modulation power demand of the wind farm according to the received grid frequency data and wind turbine characteristic model parameters and the preset frequency modulation power calculation algorithm, and then uses the optimization allocation algorithm to allocate the frequency modulation power to each wind turbine, and transmits the allocation instruction to the frequency modulation execution module. After receiving the power allocation instruction, the frequency modulation execution module converts the instruction into a control signal of the wind turbine, adjusts the wind turbine's pitch angle, generator torque and other operating parameters, so that the wind turbine output meets the required frequency modulation power, and realizes the frequency modulation output of the wind farm.

[0071] In addition, the monitoring and evaluation module receives in real time the wind turbine operation data and grid frequency data from the data acquisition module and the power distribution results from the power calculation and distribution optimization module, monitors the frequency modulation process, displays relevant information through a visual interface, and evaluates the frequency modulation effect according to preset evaluation indicators.

[0072] The fault diagnosis and fault tolerance module continuously monitors the operating status data of each part of the system and the fan. Once a fault is detected, it immediately performs fault diagnosis and fault tolerance processing, sends the fault alarm information to the monitoring and evaluation module, and transmits the fault tolerance measure instructions to the frequency regulation execution module to ensure that the system can still maintain a certain frequency regulation function or safe operation in the event of a fault.

[0073] During the entire system operation, the communication and coordination module ensures the stability and efficiency of data transmission and command interaction between modules, ensuring the coordinated work of the system.

[0074] If there is a wind farm energy storage system, the energy storage system integration module monitors the energy storage system parameters, wind turbine operation data, and grid frequency data in real time, and collaborates with the power calculation and distribution optimization module to calculate the frequency regulation power component of the energy storage system, and transmits the control instructions to the frequency regulation execution module to achieve coordinated frequency regulation of energy storage and wind turbines.

[0075] The meteorological prediction and preprocessing module regularly obtains meteorological forecast data, processes and analyzes it, and then transmits the results to the fan characteristic analysis module and the power calculation and allocation optimization module so that the system can respond to the impact of meteorological changes on frequency modulation in advance.

[0076] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A new energy electric field frequency modulation control system, characterized in that: include: A data acquisition module is used to collect the operating data of each wind turbine in the wind farm and the grid frequency information in real time, wherein the operating data of the wind turbine includes but is not limited to wind speed, wind turbine output power, pitch angle, and generator efficiency; The fan characteristic analysis module is used to analyze the operating characteristics of each fan under different working conditions and establish a fan power-wind speed model and a comprehensive operating characteristic model; The power calculation and allocation module is used to calculate the frequency modulation power required by the wind farm according to the grid frequency deviation and the operating characteristics of the wind turbine, and to allocate the frequency modulation power using an optimization algorithm; The frequency modulation execution module controls the operating parameters of the wind turbines according to the frequency modulation power instructions of each wind turbine determined by the power calculation and allocation module to realize the frequency modulation output of the wind farm; The monitoring and evaluation module is used to monitor various parameters in the frequency regulation process of the wind farm in real time, including but not limited to wind turbine operating parameters, grid frequency, and wind farm output power. It also evaluates the frequency regulation effect and adjusts and optimizes system parameters and control strategies based on the evaluation results.

2. A new energy electric field frequency modulation control system according to claim 1, characterized in that: The specific implementation steps of the fan characteristic analysis module include: S1.1: Using the historical operation data acquired by the data acquisition module, the power-wind speed curve of the wind turbine is fitted by a data fitting algorithm to obtain a nonlinear power-wind speed model of different wind turbines; S1.2: Analyze the influence of pitch angle and generator efficiency on wind turbine output power, and establish a comprehensive operation characteristic model through multivariate regression analysis. The correction formula of pitch angle to power is: P corr =P×f(β), where P corr is the corrected power, P is the original power, β is the pitch angle, and f(β) is the pitch angle correction function; The generator efficiency formula is: η = h(P, N), where P is the wind turbine output power, N is the generator speed, and h is a function of the relationship between generator efficiency and power and speed; S1.3: Calculate the mean and standard deviation of each wind turbine characteristic parameter to quantify the degree of variation between wind turbines.

3. A new energy electric field frequency modulation control system according to claim 1, characterized in that: The specific implementation steps of the power calculation and allocation module include: S2.1: According to the grid frequency deviation Δf, determine the total frequency regulation power demand P of the wind farm according to the grid frequency regulation requirements req , using the proportional-integral control algorithm to calculate P req =K p Δf+K i ∫Δfdt, where K p and K i are the proportional and integral coefficients of the PI controller; S2.2: Particle swarm optimization algorithm is used to req Assigned to each fan, let the frequency modulation power assigned to the i-th fan be P i , the optimization objective function is: Where P i,out is the frequency modulation power actually output by the i-th wind turbine, and n is the number of wind turbines in the wind farm.

4. A new energy electric field frequency modulation control system according to claim 1, characterized in that: The implementation steps of the monitoring and evaluation module include: S3.1: Establish a monitoring interface to display the operating status of each wind turbine, power distribution and grid frequency change curve; S3.2: Use frequency modulation accuracy index to quantitatively evaluate the frequency modulation effect, where the frequency modulation accuracy index is: Where T is the evaluation period, P act is the actual frequency modulation power, P tar is the target FM power; S3.3: According to the evaluation results, adjust the algorithm parameters in the power calculation and allocation optimization module.

5. The new energy electric field frequency modulation control system according to claim 1 is characterized in that: It also includes a fault diagnosis and fault tolerance module, which is used to receive fault data from the data acquisition module, the wind turbine characteristic analysis module, the power calculation and allocation module, the frequency regulation execution module and the wind turbine, and can take fault tolerance measures when a fault occurs to maintain the frequency regulation function of the wind farm or switch to a safe operation mode.

6. A new energy electric field frequency modulation control system according to claim 1, characterized in that: It also includes an energy system integration module, which is used to coordinate the frequency regulation of the energy storage device and the wind turbine in the wind farm. At the same time, according to the grid frequency requirements and the wind turbine output power, the charging and discharging strategy of the energy storage system is optimized to achieve coordinated frequency regulation of the energy storage system and the wind farm.

7. A new energy electric field frequency modulation control system according to claim 6, characterized in that: The implementation steps of the energy system integration module include: S4.1: Monitor the state of charge and charging and discharging power limit parameters of the energy storage system in real time, and calculate the frequency regulation power component that the energy storage system should bear by combining the operation data of the wind turbine and the grid frequency deviation; S4.2: Adopt the model predictive control method to determine the optimal charging and discharging power sequence of the energy storage system according to the dynamic characteristics of the energy storage system, cost factors and future grid frequency change trends; S4.3: Cooperate with the frequency regulation execution module to synchronously send the control instructions of the energy storage system and the frequency regulation control signal of the wind turbine to ensure that the two work together.

8. The new energy electric field frequency modulation control system according to claim 1 is characterized by: It also includes a meteorological prediction and preprocessing module, which accesses meteorological forecast data, predicts and analyzes the future wind speed and wind direction meteorological conditions of the wind farm, and adjusts the operation strategy and frequency modulation preparation of the wind farm in advance according to the meteorological forecast results.

9. A new energy electric field frequency modulation control system according to claim 8, characterized in that: The implementation steps of the weather forecast and preprocessing module include: S5.1: Establish a data interface with a meteorological service provider or meteorological monitoring agency to obtain meteorological forecast data for the area where the wind farm is located, including but not limited to short-term and medium-term wind speed, wind direction, temperature, and air pressure information; S5.2: Use meteorological data processing and analysis algorithms to process and optimize meteorological forecast data; S5.3: Adjust the operating parameters of the wind turbine in advance based on the weather forecast results.

10. The new energy electric field frequency modulation control system according to claim 1 is characterized in that: It also includes a communication and coordination module, which is used for communication between each wind turbine, each module, a control center and a power grid dispatching center, and coordinates data interaction and command transmission between modules.

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