Wind power participation system frequency modulation value evaluation method and system

Abstract

The invention relates to the technical field of electric power automation, in particular to a wind power participation system frequency modulation value evaluation method and system, and the method comprises the following steps: obtaining the operation data of a wind turbine generator, correcting abnormal data, analyzing the relation between output power and frequency deviation, monitoring the state of a part, and obtaining a health constraint frequency modulation capacity boundary. Through analyzing the motion characteristics and intensity of frequency modulation, the unit frequency modulation cost is calculated, a marginal cost curve is constructed, the optimal frequency modulation capacity is identified, and a unit frequency modulation value analysis result is obtained. According to the invention, through data correction, the accuracy and reliability of basic data are improved, the relationship between output power and power grid frequency deviation is analyzed, the health index is calculated in combination with the component state, the health constraint capacity boundary is obtained, and the dynamic adaptation of the unit operation state to the frequency modulation capacity upper limit is realized; the frequency modulation cost is calculated by combining the operation energy consumption and the component loss, the optimal capacity is identified by using marginal cost and net income analysis, and accurate evaluation of the wind power participation system frequency modulation value is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power automation, and particularly to a method and system for evaluating the value of wind power participating in system frequency modulation. Background Art

[0002] The technical field of power automation includes power system operation control, equipment automatic regulation, and new energy grid connection collaborative technology. This field takes the power network as the core research object, focuses on the real-time monitoring, feedback regulation, and dynamic optimization of the power generation, transmission, and distribution links. Its core technologies cover power grid frequency stability control, unit output coordination strategy, data-driven decision-making model, and new energy unit grid connection adaptability transformation. At the system level, the dynamic balance between the power generation side and the load side is achieved through automatic devices to solve the problems of frequency fluctuations caused by the lag of traditional frequency modulation resources and the randomness of new energy output. Specifically, it involves technical modules such as frequency modulation capacity allocation algorithms, unit control instruction generation, and multi-source data fusion analysis.

[0003] Among them, a method for evaluating the value of wind power participating in system frequency modulation refers to a correlation model based on the active power regulation characteristics of wind turbines and the grid frequency deviation, which quantitatively evaluates the technical contribution and economic value of wind power in the frequency modulation process. The method aims at technical matters such as wind power frequency modulation capacity measurement, response time parameter analysis, and frequency modulation cost accounting. By constructing the dynamic response curves of wind turbine power and frequency, combining the frequency modulation demand threshold and the unit operation constraint conditions, a determination rule for the availability of frequency modulation capacity is established. Based on the data acquisition device, wind speed, power output, and grid frequency fluctuation data are obtained, and the mapping relationship between wind power frequency modulation capacity and frequency deviation is analyzed using a linear regression model, and the economic input and market revenue of frequency modulation services are calculated.

[0004] The traditional technology for evaluating the value of wind power participating in system frequency modulation relies on a static linear model to correlate the frequency modulation capacity with the frequency deviation, without considering the influence of non-linear factors such as converter voltage fluctuation and pitch angle adjustment delay during the dynamic response process of the unit, resulting in the deviation of the capacity measurement result from the actual working condition. The fixed regression coefficient cannot adapt to the difference in the output characteristics of the unit in different wind speed intervals, causing the misalignment between the frequency modulation capacity allocation and the actual demand. Using a preset threshold to determine the availability of frequency modulation capacity ignores the dynamic constraint of the equipment health state on the capacity upper limit. For example, when the gearbox vibration intensifies or the converter overheats, the capacity is still allocated according to the rated value, triggering protection shutdown or permanent damage to components, resulting in problems such as reduced credibility of frequency modulation capacity, decreased equipment reliability, and short-sighted economic decision-making. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, the embodiments of the present invention provide a method and system for evaluating the value of wind power participating in system frequency modulation. The technical solution is as follows: To achieve the above object, the present invention adopts the following technical solution. A method for evaluating the value of a wind power participating in system frequency modulation includes the following steps: S1: Obtain the operation data of the wind turbine, analyze the deviation characteristics between the unit power and the theoretical power curve. According to the comparison result between the unit power deviation characteristics and the preset tolerance, mark the abnormal data segments, and combine the power and frequency data of adjacent units to obtain the corrected operation data; S2: Based on the corrected operation data, call the DC-side voltage data of the converter and the pitch angle command change rate data, analyze the collaborative response characteristics between the active current command of the converter and the pitch angle command, calculate the relationship between the output power of the converter and the grid frequency deviation, and generate a dynamic response coefficient; S3: Call the dynamic response coefficient, collect the converter temperature data and the main frequency amplitude data of the gearbox vibration, combine the output power data, calculate the component health index in real time, and calculate the frequency modulation capacity correction factor according to the health degree of the unit to obtain the frequency modulation capacity boundary under health constraints; S4: Based on the frequency modulation capacity boundary under health constraints, analyze the frequency modulation action type and the adjustment amplitude characteristics according to the pitch angle command change rate, the converter power command change rate, and the frequency modulation action duration. Divide the frequency modulation action intensity level according to the adjustment amplitude characteristics, and calculate the total frequency modulation cost to obtain the unit frequency modulation cost.

[0006] As a further solution of the present invention, the corrected operation data is specifically the verification timestamp, the corrected power value, and the frequency deviation sequence. The dynamic response coefficient includes the frequency deviation gain factor, the converter equivalent time constant, and the pitch system response delay. The frequency modulation capacity boundary under health constraints specifically refers to the frequency modulation capacity correction factor, the component health index, and the capacity boundary calculation result. The unit frequency modulation cost includes the additional energy consumption of the control system, the converted value of the component fatigue loss, and the estimated opportunity cost data.

[0007] As a further solution of the present invention, the steps of obtaining the operation data of the wind turbine, analyzing the deviation characteristics between the unit power and the theoretical power curve, according to the comparison result between the unit power deviation characteristics and the preset tolerance, marking the abnormal data segments, and combining the power and frequency data of adjacent units to obtain the corrected operation data are specifically as follows: S101: Obtain the operation data of the wind turbine, call the real-time wind speed data, the active power data, and the grid frequency deviation data, calculate the deviation value between the actual power of the unit and the theoretical power curve, and generate the unit power deviation value; S102: Call the unit power deviation value, compare the deviation value with the preset tolerance threshold, mark the abnormal data segments, and generate the abnormal data segment marking result; S103: Based on the marked results of the abnormal data segments, call the average power data and average frequency data of adjacent units in the same time period to correct the marked abnormal data segments, and generate the corrected operation data.

[0008] As a further solution of the present invention, based on the corrected operation data, call the DC side voltage data of the converter and the pitch angle command change rate data, analyze the collaborative response characteristics of the active current command of the converter and the pitch angle command, calculate the relationship between the output power of the converter and the grid frequency deviation, and the steps of generating the dynamic response coefficient are specifically as follows: S201: Based on the corrected operation data, call the DC side voltage data of the converter and the pitch angle command change rate data, analyze the synchronous phase difference between the active current command of the converter and the pitch angle command, and generate the synchronous phase difference between active power and pitch angle; S202: Call the synchronous phase difference between active power and pitch angle, combine with the grid frequency deviation data, extract the proportional coefficient of the change amplitude of the converter output power to the amplitude of the frequency deviation, and generate the power-frequency gain coefficient; S203: Based on the power-frequency gain coefficient, calculate the response delay time difference between the power regulation command of the converter and the pitch angle action command, and generate the dynamic response coefficient.

[0009] As a further solution of the present invention, the specific formula for extracting the proportional coefficient of the change amplitude of the converter output power to the amplitude of the frequency deviation is: ; Calculate the power-frequency gain coefficient and generate the power-frequency gain coefficient; Wherein, represents the power-frequency gain coefficient at the th sampling moment, represents the change amplitude of the converter output power at the th sampling moment, represents the amplitude of the grid frequency deviation data at the th sampling point, represents the synchronous phase difference value between active power and pitch angle at the th sampling moment, is the index of the target sampling point currently calculated, is the index of the frequency deviation data to be statistically summed, is the total number of samples of the frequency deviation data.

[0010] As a further solution of the present invention, call the dynamic response coefficient, collect the converter temperature data and the main vibration frequency amplitude data of the gearbox, combine with the output power data, calculate the component health index in real time, and calculate the frequency modulation capacity correction factor according to the health degree of the unit, and the steps of obtaining the health constraint frequency modulation capacity boundary are specifically as follows: S301: Invoke the dynamic response coefficient, collect the converter temperature data and the main frequency amplitude data of the gearbox vibration, calculate the temperature deviation rate and the vibration amplitude deviation rate in real time by comparing with the rated operating parameters, and obtain the component health index; S302: Based on the component health index, combined with the output power data, calculate the frequency modulation capacity correction ratio by analyzing the relationship between the health index and the output power, and generate the frequency modulation capacity correction factor; The specific formula for calculating the frequency modulation capacity correction ratio is: ; Calculate the frequency modulation capacity correction ratio and generate the frequency modulation capacity correction factor; Wherein, represents the frequency modulation capacity correction ratio, represents the component health index at the th sampling moment, represents the actual output power value of the unit at the th sampling moment, represents the arithmetic mean of the component health indexes within the current sampling window, represents the total number of sampling points within the sampling window, represents the index number of the th time point in the sampling window, is a small positive constant to avoid a zero denominator; S303: Invoke the frequency modulation capacity correction factor, combined with the rated frequency modulation capacity of the unit, to obtain the frequency modulation capacity boundary under health constraints.

[0011] As a further solution of the present invention, based on the frequency modulation capacity boundary under health constraints, according to the pitch angle command change rate, the converter power command change rate, and the frequency modulation action duration, analyze the frequency modulation action type and the adjustment amplitude characteristics, divide the frequency modulation action intensity level according to the adjustment amplitude characteristics, and calculate the total frequency modulation cost. The steps for obtaining the unit frequency modulation cost are specifically as follows: S401: Based on the frequency modulation capacity boundary under health constraints, analyze the activity degree of the pitch angle and the converter power command during the frequency modulation duration, identify the adjustment action type and the adjustment amplitude characteristics, and generate the frequency modulation action characteristic data; S402: Invoke the frequency modulation action characteristic data, compare with the preset frequency modulation intensity grading benchmark, identify the action intensity level, and establish the frequency modulation action intensity level; S403: According to the frequency modulation action intensity level and the frequency modulation duration, calculate the additional energy consumption and the component loss cost, and obtain the unit frequency modulation cost.

[0012] As a further solution of the present invention, the method further includes: S5: Invoke the unit's frequency regulation cost and the frequency regulation capacity boundary under health constraints, calculate the marginal cost curve per unit of frequency regulation capacity, combine the wind speed prediction data and the real-time electricity price, identify the optimal frequency regulation capacity by calculating the net benefits of multiple frequency regulation capacity intervals, and obtain the analysis results of the unit's frequency regulation value; The analysis results of the unit's frequency regulation value are specifically the optimal capacity analysis result, the expected net frequency regulation benefit amount, and the frequency regulation marginal cost curve.

[0013] As a further solution of the present invention, the steps of invoking the unit's frequency regulation cost and the frequency regulation capacity boundary under health constraints, calculating the marginal cost curve per unit of frequency regulation capacity, combining the wind speed prediction data and the real-time electricity price, identifying the optimal frequency regulation capacity by calculating the net benefits of multiple frequency regulation capacity intervals, and obtaining the analysis results of the unit's frequency regulation value are specifically as follows: S501: Invoke the unit's frequency regulation cost data and the frequency regulation capacity boundary under health constraints, divide multiple frequency regulation capacity intervals within the capacity boundary, evaluate the cost change amount corresponding to each interval, and establish a marginal cost curve; S502: Based on the marginal cost curve, combine the wind speed prediction information and the real-time market electricity price, calculate the net benefits of multiple frequency regulation capacity intervals, and obtain the interval net benefit data; S503: Invoke the interval net benefit data, identify the optimal frequency regulation capacity by comparing the net benefits at each capacity level, and calculate the expected net benefit to obtain the analysis results of the unit's frequency regulation value.

[0014] On the other hand, a system for evaluating the value of wind power participating in system frequency regulation is provided. This system is applied to the method for evaluating the value of wind power participating in system frequency regulation. The system includes: The data correction module obtains the operation data of the wind turbine generator set, analyzes the deviation characteristics between the unit power and the theoretical power curve, compares the power deviation amplitude with the preset tolerance threshold, marks the abnormal data segments, and combines the power volatility of adjacent units and the grid frequency volatility to obtain the corrected operation data; The response coordination module invokes the corrected operation data, extracts the voltage volatility on the DC side of the converter and the pitch angle command change rate, counts the synchronous fluctuation period of the active current command of the converter and the pitch angle command, calculates the correlation coefficient between the grid frequency deviation and the output power, and generates a dynamic response coefficient; The health constraint module invokes the dynamic response coefficient, collects the temperature gradient data of the converter and the main vibration frequency amplitude of the gearbox, calculates the component health index according to the temperature gradient deviation rate and the vibration amplitude deviation rate, and combines the unit output power data to generate a health constraint frequency regulation capacity boundary; The frequency modulation cost accounting module extracts the pitch angle command change rate and the converter power command change rate based on the health-constrained frequency modulation capacity boundary, analyzes the frequency modulation action type and the adjustment amplitude characteristics, divides the frequency modulation action intensity level according to the adjustment amplitude characteristics, calculates the energy consumption and equipment loss cost corresponding to each level, and generates the unit frequency modulation cost. The frequency modulation value evaluation module calls the unit frequency modulation cost and the health-constrained frequency modulation capacity boundary, calculates the cost increment per unit frequency modulation capacity, combines the wind speed prediction power distribution and the real-time electricity price, and identifies the optimal frequency modulation capacity by analyzing the net income of each frequency modulation capacity interval, and generates the unit frequency modulation value analysis result.

[0015] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include: Through data correction, the accuracy and reliability of the basic data are improved. By analyzing the relationship between the output power and the grid frequency deviation, and combining the component status to calculate the health index, the health-constrained capacity boundary is obtained, realizing the dynamic adaptation of the unit operation state to the upper limit of the frequency modulation capacity. Combining the operation energy consumption and component loss to calculate the frequency modulation cost, and using marginal cost and net income analysis to identify the optimal capacity, realizing the accurate evaluation of the value of wind power participating in system frequency modulation. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1 It is a schematic diagram of the working process of the present invention; Figure 2 It is a system flow chart of the present invention. Detailed Embodiments

[0018] The following will describe the technical solutions in the present invention with reference to the drawings.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0020] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same. "of", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same.

[0021] In the embodiments of the present invention, sometimes subscripts such as W 1 may be written in a non-subscript form such as W1. When the difference is not emphasized, their intended meanings are the same.

[0022] To make the technical problems, technical solutions, and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0023] Please refer to Figure 1 , the present invention provides a technical solution, a method for evaluating the value of wind power participating in system frequency modulation, including the following steps: S1: Obtain the operating data of the wind turbine, analyze the deviation characteristics between the unit power and the theoretical power curve, mark the abnormal data segments according to the comparison results of the unit power deviation characteristics and the preset tolerance, and combine the power and frequency data of adjacent units to obtain the corrected operating data; S2: Based on the corrected operating data, call the DC-side voltage data of the converter and the pitch angle command change rate data, analyze the collaborative response characteristics between the active current command of the converter and the pitch angle command, calculate the relationship between the output power of the converter and the grid frequency deviation, and generate a dynamic response coefficient; S3: Call the dynamic response coefficient, collect the converter temperature data and the main vibration frequency amplitude data of the gearbox, combine the output power data, calculate the component health index in real time, and calculate the frequency modulation capacity correction factor according to the health of the unit to obtain the health-constrained frequency modulation capacity boundary; S4: Based on the health-constrained frequency modulation capacity boundary, analyze the frequency modulation action type and adjustment amplitude characteristics according to the pitch angle command change rate, converter power command change rate, and frequency modulation action duration, divide the frequency modulation action intensity level according to the adjustment amplitude characteristics, and calculate the total frequency modulation cost to obtain the unit frequency modulation cost; S5: Call the unit frequency modulation cost and the health-constrained frequency modulation capacity boundary, calculate the marginal cost curve of the unit frequency modulation capacity, combine the wind speed prediction data and the real-time electricity price, identify the optimal frequency modulation capacity by calculating the net benefits of multiple frequency modulation capacity intervals, and obtain the analysis result of the unit frequency modulation value; The specific corrected operation data are the verification timestamp, the corrected power value, and the frequency deviation sequence. The dynamic response coefficients include the frequency deviation gain factor, the converter equivalent time constant, and the pitch system response delay. The health constraint frequency regulation capacity boundary specifically refers to the frequency regulation capacity correction factor, the component health index, and the capacity boundary calculation result. The unit's frequency regulation cost includes the additional energy consumption of the control system, the converted value of component fatigue loss, and the estimated opportunity cost data. The analysis result of the unit's frequency regulation value is specifically the optimal capacity analysis result, the expected net frequency regulation income amount, and the frequency regulation marginal cost curve.

[0024] The steps to obtain the operation data of the wind turbine generator set, analyze the deviation characteristics between the unit power and the theoretical power curve, mark the abnormal data segments according to the comparison result between the unit power deviation characteristics and the preset tolerance, and obtain the corrected operation data in combination with the power and frequency data of adjacent units are as follows: S101: Obtain the operation data of the wind turbine generator set, call the real-time wind speed data, active power data, and grid frequency deviation data, calculate the deviation value between the actual power of the unit and the theoretical power curve, and generate the unit power deviation value;

[0025] The real-time wind speed sub-module obtains the wind speed measurement data through the anemometer installed at the position of the wind turbine hub, obtains the actual output active power data through the real-time voltage and current measurement equipment on the converter side, and obtains the real-time grid frequency deviation data through the frequency measurement device at the grid interface. Taking the theoretical power curve provided by the wind turbine manufacturer as the reference basis, it is stored in the wind turbine control unit in line, covering the theoretical output power in each wind speed interval corresponding to the unit nameplate capacity. The real-time wind speed value is collected and input to the control unit to obtain the theoretical power value corresponding to the current wind speed. The difference operation is performed between the actually measured active power and the theoretical power, using the formula: ; Calculate the power deviation value , where is the unit power deviation value (unit: kW), is the theoretical output power (unit: kW), is the actually measured active power (unit: kW).

[0026] Assume that the real-time wind speed value is 12 m / s, the power value given by the theoretical power curve is 1200 kW, and the actually measured unit power is 1100 kW. Substitute the set values for calculation: ; The calculation result shows that the power deviation value is a positive 100 kW, that is, the actual power is less than the theoretical power, and the actual operating power of the wind turbine is in the interval below the theoretical value. Thus, the specific deviation amplitude of the unit power in the current real-time state is determined, and this data is recorded for the subsequent abnormal data segment identification link.

[0027] S102: Call the unit power deviation value, compare the deviation value with the preset tolerance threshold, mark the abnormal data segment, and generate the marking result of the abnormal data segment; The power deviation data processing sub-module calls the tolerance threshold pre-stored by the SCADA system to perform the absolute value comparison operation of the difference item by item with the power deviation value obtained by real-time calculation. The tolerance threshold is determined with reference to the rated capacity of the unit. The specific set tolerance is ±5% of the rated power of the unit. Take the absolute value of the power deviation value obtained by real-time calculation and perform the difference comparison operation with the absolute value of the tolerance threshold. Use the formula: ; Calculate the difference , where is the power deviation difference (unit: kW), is the power deviation value (unit: kW), is the tolerance threshold (unit: kW).

[0028] Suppose the power deviation value is 120 kW and the tolerance threshold is set to 100 kW. Substitute the set value for calculation: ; The calculation result shows that the absolute value of the power deviation value has exceeded the tolerance threshold by 20 kW. At this time, the sub-module marks the data as an abnormal state and records the current timestamp. For example, mark the data collected at the time "from 10:05 to 10:10 on March 1, 2024" as abnormal, and limit the subsequent data processing operations within this time period.

[0029] S103: Based on the marking result of the abnormal data segment, call the average power data and average frequency data of adjacent units in the same time period to correct the marked abnormal data segment and generate the corrected operation data; The abnormal data segment correction sub-module calls the power data and grid frequency data of adjacent wind turbines in the same time period, and performs the average value operation for each time point marked as abnormal in turn. Call the measured data of each adjacent unit at the corresponding time point, and perform the arithmetic average calculation on the power data and frequency data of multiple units respectively. Use the formula: ; ; Calculate the average power of adjacent units and the average frequency deviation , where is the average real-time power of adjacent units (unit: kW), is the average frequency deviation of adjacent units (unit: Hz), represents the real-time power measurement value of the i-th adjacent unit (unit: kW), It represents the frequency deviation value (unit: Hz) measured in real time by the i-th adjacent unit. It represents the total number of adjacent units participating in the calculation.

[0030] Suppose that at the abnormal moment of 10:05 on March 1, 2024, the power measurement values of units numbered 02 and 03 are 1080 kW and 1090 kW respectively, and the frequency deviation values are -0.05 Hz and -0.04 Hz respectively. Substitute the set values into the calculation: ; ; The calculation results show that the correction values of the unit power data and the frequency deviation data in the corresponding abnormal data segment are 1085 kW and -0.045 Hz respectively. Subsequently, the sub-module replaces the original measurement values of the data points marked as abnormal with these values one by one, and integrates the updated data set to form a new corrected operation data set, which serves as the data basis for subsequent unit performance evaluation and frequency modulation capacity assessment.

[0031] Based on the corrected operation data, call the DC-side voltage data of the converter and the pitch angle command change rate data, analyze the collaborative response characteristics of the active current command of the converter and the pitch angle command, and calculate the relationship between the output power of the converter and the grid frequency deviation. The specific steps for generating the dynamic response coefficient are as follows: S201: Based on the corrected operation data, call the DC-side voltage data of the converter and the pitch angle command change rate data, analyze the synchronous phase difference between the active current command of the converter and the pitch angle command, and generate the synchronous phase difference between active power and pitch angle; The corrected operation data is specifically the corrected power value and the grid frequency deviation sequence. The DC-side voltage data of the converter specifically calls the real-time measurement value of the DC bus voltage of the wind turbine converter, and the pitch angle command change rate data calls the real-time pitch angle control command sequence issued by the pitch control system. By calling the active current command sequence and the pitch angle control command sequence actually output by the converter at each moment, record the amplitude data of each moment of the two on the same time axis. Taking a sampling frequency of 10 times per second as an example, select data points within a specified time period (for example, the time period is 30 seconds, a total of 300 data points). For each data point, perform Fourier transform one by one to obtain their respective instantaneous phase angle data. For example, the phase angle of the active current command of the converter is 45°, and the phase angle of the pitch angle command is 30°. Subsequently, calculate the phase difference between the two at each moment, call the phase angle data of the active current command of the converter and the phase angle data of the pitch angle command at each moment for difference operation, and calculate the phase difference through the formula: ; Among them, is the synchronous phase difference (unit: °) between the active current command and the pitch angle command, is the phase angle of the active current command of the converter (unit: °). is the phase angle of the pitch angle command (unit: °). Assume that at a certain moment, the phase angle of the active current command of the converter is 45°, and the phase angle of the pitch angle command is 30°. Substitute these values into the above formula for calculation: ;

[0032] The calculation results show that the phase difference at this moment is 15°. Store the phase difference results calculated for all moments one by one to form the synchronous phase difference between active power and pitch angle.

[0033] S202: Call the synchronous phase difference between active power and pitch angle, combine it with the power grid frequency deviation data, extract the proportional coefficient of the change amplitude of the converter output power to the amplitude of the frequency deviation, and generate the power-frequency gain coefficient; The specific formula for extracting the proportional coefficient of the change amplitude of the converter output power to the amplitude of the frequency deviation is: ; Calculate the power-frequency gain coefficient to generate the power-frequency gain coefficient; Among them, represents the power-frequency gain coefficient at the th sampling moment, represents the change amplitude of the converter output power at the th sampling moment, represents the amplitude of the power grid frequency deviation data at the th sampling point, represents the synchronous phase difference between active power and pitch angle at the th sampling moment, is the index of the target sampling point for the current calculation, is the index of the frequency deviation data to be statistically summed, is the total number of samples of the frequency deviation data.

[0034] Formula: ; Detailed explanation of the formula and the derivation process of the formula calculation: The formula is used to calculate the gain relationship between the converter output power and the power grid frequency deviation at the kth sampling moment. The result is used as a characterization index for the amplitude of the active power regulation caused by a unit frequency perturbation in the frequency regulation behavior; Parameter meanings and setting values: is the change amplitude of the converter output power at the kth moment. Assume that the sampling period is 1 second, and the collected power data are 1195 kW and 1220 kW respectively. is 25 kW; is the value of the m-th sampling point in the frequency deviation amplitude sequence. The set window is M = 5, and the corresponding collected data are: 50.01Hz, 49.98Hz, 49.95Hz, 49.93Hz, 49.90Hz. The rated frequency is 50Hz, and the frequency deviation sequence corresponds to 0.01, 0.02, 0.05, 0.07, 0.10Hz. ;

[0035] is the synchronization phase difference between the active current command and the pitch angle command at the k-th moment. The converter command phase angle is set to 78° and the pitch angle command phase angle is 66° at this moment, and the phase difference is 12°; Substitute the parameters into the formula for calculation: ; The result 0.192kW / Hz indicates the intensity of the active power regulation ability caused by the unit frequency deviation at the current moment. The larger this value, the faster the power response speed and the higher the gain of the converter. This value is used as the final generated power and frequency gain coefficient and is used as a key input item in subsequent frequency modulation behavior and capacity economy analysis.

[0036] S203: Based on the power and frequency gain coefficient, calculate the response delay time difference between the converter power regulation command and the pitch angle action command, and generate the dynamic response coefficient; The power and frequency gain coefficient specifically calls the gain coefficient data of each moment obtained in the previous calculation step. The converter power regulation command specifically calls the release time of the real-time power regulation command recorded in the fan converter control unit, and the pitch angle action command specifically calls the action command release time of the pitch control system in real time. Call the release times of each power regulation command and pitch angle action command one by one, and perform the time delay difference calculation operation one by one. For example, at a certain moment, the release timestamp of the converter power regulation command is 10:05:00.150 (hour: minute: second.millisecond), and the release timestamp of the pitch angle action command is 10:05:00.100. Calculate the difference between the two and take the absolute value to obtain the response delay time difference. Calculate the response delay time difference through the formula: ; Among them, is the response delay time difference (unit: millisecond ms), is the release timestamp of the converter power regulation command (unit: millisecond ms), is the release timestamp of the pitch angle action command (unit: millisecond ms). Assuming that at a certain moment, the release moment of the converter power regulation command is 10:05:00.150 (i.e., 150 milliseconds), and the release moment of the pitch angle action command is 10:05:00.100 (i.e., 100 milliseconds), substituting into the formula for calculation gives: ; The calculation results show that the response delay time difference at this moment is 50 ms. This step is repeatedly executed for all instruction release moments within the preset time period, and the time differences calculated at each moment are recorded one by one to form a complete response delay time difference sequence. The entire sequence is marked to form a dynamic response coefficient.

[0037] The steps of calling the dynamic response coefficient, collecting the converter temperature data and the main frequency amplitude data of the gearbox vibration, combining with the output power data, calculating the component health index in real time, and calculating the frequency modulation capacity correction factor according to the health degree of the unit to obtain the frequency modulation capacity boundary under health constraints are as follows: S301: Call the dynamic response coefficient, collect the converter temperature data and the main frequency amplitude data of the gearbox vibration, calculate the temperature deviation rate and the vibration amplitude deviation rate in real time by comparing with the rated operating parameters, and obtain the component health index; The dynamic response coefficient specifically calls the response delay time difference sequence calculated in the previous step. The converter temperature data calls the junction temperature of the semiconductor device measured in real time by the temperature sensor in the converter. The main frequency amplitude data of the gearbox vibration calls the main frequency amplitude of the vibration signal at the bearing position of the gearbox measured by the sensor of the vibration monitoring system. The rated operating parameters specifically call the normal operating state temperature and vibration amplitude specified by the equipment manufacturer. Calculate the difference between the real-time measured converter temperature value and the rated junction temperature (for example, the rated junction temperature is 85 °C), and obtain the temperature deviation rate through the ratio operation of the difference and the rated value. Calculate the temperature deviation rate through the formula: ; Wherein, is the converter temperature deviation rate (unit: %), is the real-time measured converter temperature (unit: °C), is the rated converter temperature (unit: °C). Assuming the real-time measured temperature is 95 °C and the rated temperature is 85 °C, substitute into the formula for calculation: ; The calculation results show that the temperature deviation rate is 11.76%. At the same time, perform the same difference operation and ratio operation on the real-time measured value and the rated value of the main frequency amplitude of the gearbox vibration (for example, the rated vibration amplitude is 0.5 mm / s) to calculate the vibration amplitude deviation rate. Obtain the temperature and vibration deviation rate data one by one through the above method, and call the deviation rate data for weighted summation processing (for example, the respective weights are all set to 0.5) to obtain the component health index.

[0038] S302: Based on the component health index, combine with the output power data, and calculate the frequency modulation capacity correction ratio by analyzing the relationship between the health index and the output power to generate the frequency modulation capacity correction factor; The specific formula for calculating the frequency modulation capacity correction ratio is as follows: ; Calculate the frequency modulation capacity correction ratio to generate a frequency modulation capacity correction factor; Among them, represents the frequency modulation capacity correction ratio, represents the component health index at the th sampling moment, represents the actual output power value of the unit at the th sampling moment, represents the arithmetic mean of the component health indices within the current sampling window, represents the total number of sampling points within the sampling window, represents the index number of the th time point in the sampling window, is a small positive constant to avoid a zero denominator.

[0039] Formula: ; Detailed explanation of the formula and the derivation process of formula calculation: The formula is used to calculate the frequency modulation capacity correction ratio, and the result is used to quantify the degree of weakening or maintaining ability of the current unit operation state on its rated frequency modulation ability, generating a frequency modulation capacity correction factor; Meaning and setting values of parameters: is the component health index at the qth sampling moment. The health indices at 5 moments are set as: 0.88, 0.82, 0.80, 0.77, 0.85; is the real-time output power data of the unit at the qth sampling moment, with the unit of kW, and is set as: 1230kW, 1210kW, 1200kW, 1180kW, 1225kW; is the mean value of the health indices within the sampling window,

[0040] is a constant fine-tuning term used to avoid a zero denominator and enhance stability, and is set as 0.01; Substitute the parameters into the formula for calculation: ; ; ; ; The result of 28637.64 indicates that under the current operating condition, the correction ratio of the frequency regulation capacity of the unit is relatively high, reflecting that the output power and the health status are highly coordinated and stable, and the frequency regulation ability remains strong. This value, as the basic quantity of the correction factor, will be used to subsequently correct the theoretical frequency regulation capacity boundary of the unit.

[0041] S303: Invoke the frequency regulation capacity correction factor, and combine it with the rated frequency regulation capacity of the unit to obtain the frequency regulation capacity boundary under health constraints; Specifically, the value calculated in the previous step is invoked for the frequency regulation capacity correction factor, and the rated frequency regulation capacity of the unit is specifically invoked from the rated frequency regulation capacity data on the nameplate of the fan when it leaves the factory (for example, 200 kW). The correction factor for the frequency regulation capacity and the value of the rated frequency regulation capacity are called one by one to perform a multiplication operation to obtain the corrected frequency regulation capacity. The specific steps of the execution are to perform a simple multiplication calculation operation by calling the rated frequency regulation capacity data and the correction factor in real time. For example, if the frequency regulation capacity correction factor is 0.8 and the rated frequency regulation capacity of the unit is 200 kW, the above values are called for calculation to obtain the frequency regulation capacity boundary under health constraints. The corrected frequency regulation capacity boundary is calculated through the formula: ; Among them, is the frequency regulation capacity boundary under health constraints (unit: kW), is the rated frequency regulation capacity of the unit (unit: kW), is the frequency regulation capacity correction factor (dimensionless). Assuming that the rated frequency regulation capacity of the unit is 200 kW and the correction factor is 0.8, substitute into the formula for calculation: ;

[0042] The value obtained from the calculation result is 160 kW, and this value is determined as the frequency regulation capacity boundary under health constraints at the current moment.

[0043] Based on the frequency regulation capacity boundary under health constraints, according to the pitch angle command change rate, the converter power command change rate, and the duration of the frequency regulation action, analyze the type of frequency regulation action and the characteristics of the adjustment amplitude, divide the intensity level of the frequency regulation action according to the characteristics of the adjustment amplitude, and calculate the total frequency regulation cost. The specific steps to obtain the frequency regulation cost of the unit are as follows: S401: Based on the frequency regulation capacity boundary under health constraints, analyze the activity degree of the pitch angle and the converter power command during the frequency regulation duration, identify the type of adjustment action and the characteristics of the adjustment amplitude, and generate frequency regulation action characteristic data; The health constraint frequency modulation capacity boundary specifically calls the corrected frequency modulation capacity value calculated in the previous step. The pitch angle command change rate specifically calls the numerical sequence of the real-time pitch angle command in the fan control system, and calls the pitch angle command data for 1 minute continuously (a total of 600 data points) at 10 sampling points per second. The change rate data of each sampling point is obtained by calculating the absolute value of the difference between two adjacent data points called at each moment. For example, if the pitch angle commands at two consecutive moments are 12° and 12.5° respectively, the change rate is calculated as 0.5° / s through the absolute difference. Record the change rates of all sampling points one by one and judge the activity degree of the pitch action based on this data. The converter power command change rate specifically calls the real-time converter power output command sequence data, and also calls the data for 1 minute continuously at 10 sampling points per second. Calculate the absolute value of the difference between the power commands at adjacent moments (for example, 1000kW and 1015kW at adjacent moments) for each sampling point to obtain the converter power change rate value (15kW / s). Subsequently, call the pitch angle change rate and the power command change rate values at each moment respectively for comparison operations, and calculate the activity degree index through the formula: ; Among them, is the comprehensive activity degree index, is the weight of the pitch angle change rate, is the pitch angle change rate (° / s), is the weight of the power command change rate, is the power command change rate (kW / s), and the weight values are set as 、 . Assuming that the pitch angle change rate is 0.5° / s and the power command change rate is 15kW / s, substituting into the formula for calculation gives: ;

[0044] The calculated comprehensive activity degree index is 9.2. Determine the adjustment action type and adjustment amplitude characteristics based on the index value, and calculate the frequency modulation action characteristic data for each moment of the above index.

[0045] S402: Call the frequency modulation action characteristic data, compare with the preset frequency modulation intensity grading benchmark, identify the action intensity level, and establish the frequency modulation action intensity level; The FM action characteristic data specifically calls the comprehensive activity index value obtained in the previous step. The preset FM intensity grading benchmark specifically calls the intensity level intervals formed by the statistical operation of the fan operation experience. For example, the slight level is set as 0-5, the medium level is 5-10, and the severe level is above 10. The comprehensive activity index value is called one by one for interval comparison operations, and the level corresponding to each data point is recorded. For example, at a certain moment, the activity index is 9.2, and this index value is within the medium level (5-10) interval, so it is marked as the medium level. The level marking results of all sampling points are recorded separately, and the total number of occurrences of each level is counted. The level with the most occurrences is called as the overall action intensity level, and finally the FM action intensity level of this period is determined.

[0046] S403: According to the FM action intensity level and the FM duration, calculate the additional energy consumption and component loss cost, and obtain the unit's FM cost; The FM action intensity level specifically calls the level marking results determined in the previous step, and the FM duration specifically calls the duration timestamp of the action instruction release. For example, the FM duration is set to 5 minutes (300 seconds). The additional energy consumption benchmark value per unit time and the component loss cost benchmark value corresponding to the intensity level are called. For example, the benchmark cost of the slight level is set to 0.1 yuan / kW·s, the medium level is 0.2 yuan / kW·s, and the severe level is 0.3 yuan / kW·s. The total cost corresponding to each level is obtained by multiplying the benchmark value corresponding to the intensity level by the FM duration and the FM capacity boundary value respectively. The total cost is calculated through the formula: ; Among them, is the total unit FM cost (unit: yuan), is the unit cost corresponding to the intensity level (yuan / kW·s), is the healthy constraint FM capacity boundary (kW), is the FM duration (seconds). Assume that the current action intensity level is the medium level, the unit cost is 0.2 yuan / kW·s, the healthy constraint FM capacity boundary is 160 kW, and the FM duration is 300 seconds. Substitute into the formula for calculation: ; The calculation result shows that the total unit FM cost is 9600 yuan, and this value is saved as the unit's FM cost record.

[0047] Call the unit's FM cost and the healthy constraint FM capacity boundary, calculate the marginal cost curve of the unit FM capacity, and combine the wind speed prediction data and the real-time electricity price. By calculating the net income of multiple FM capacity intervals, identify the optimal FM capacity. The steps to obtain the unit's FM value analysis result are specifically as follows:

[0048] S501: Invoke the unit frequency regulation cost data and the health-constrained frequency regulation capacity boundary. Divide multiple frequency regulation capacity intervals within the capacity boundary, evaluate the cost change amount corresponding to each interval, and establish a marginal cost curve.

[0049] Specifically, the unit frequency regulation cost data invokes the total frequency regulation cost value calculated above (e.g., 9,600 yuan), and the health-constrained frequency regulation capacity boundary invokes the capacity boundary value obtained by calculation (e.g., 160 kW). Invoke the above capacity boundary value and divide it into separate intervals every 20 kW between 0 kW and 160 kW. The specific intervals are: 0 - 20 kW, 20 - 40 kW, 40 - 60 kW, 60 - 80 kW, 80 - 100 kW, 100 - 120 kW, 120 - 140 kW, and 140 - 160 kW. Call the upper limit value and the lower limit value of each interval one by one for difference calculation, and call the unit capacity frequency regulation cost (e.g., set to 0.2 yuan / kW·s) and the frequency regulation duration value (e.g., 300 seconds), and perform the product operation of the three values. Calculate the cost change amount of the capacity interval through the formula:

[0050] ;

[0051] Among them, is the cost change amount (yuan) of the jth capacity interval, is the unit capacity frequency regulation cost (yuan / kW·s), is the upper limit value of the jth interval capacity (kW), is the lower limit value of the jth interval capacity (kW), is the frequency regulation duration (seconds). Assume that the 3rd interval is 40 - 60 kW, the unit capacity frequency regulation cost is 0.2 yuan / kW·s, and the frequency regulation duration is 300 seconds. Substitute into the formula for calculation: ; The cost change amount of the 3rd interval is calculated to be 1,200 yuan. Repeat the above steps to calculate the cost change amount of each interval and record them one by one to form a marginal cost curve.

[0052] S502: Based on the marginal cost curve, combine the wind speed prediction information and the real-time market electricity price to calculate the net benefits of multiple frequency regulation capacity intervals and obtain the interval net benefit data.

[0053] The marginal cost curve specifically calls the cost change values of multiple capacity intervals calculated in the previous step. The wind speed prediction information calls the future 1-hour predicted wind speed value provided by the wind farm meteorological system (for example, the predicted wind speed value is 12 m / s). The real-time market electricity price calls the real-time grid-connected electricity price data announced by the power grid company (for example, 0.5 yuan / kWh). Randomly call the wind speed-predicted power generation corresponding to the upper and lower limit values of each capacity interval (for example, the theoretical power generation is 1200 kWh). Perform the multiplication operation of the theoretical power generation and the real-time electricity price to obtain the income. Then call the cost change value and income value corresponding to each capacity interval to perform the difference calculation to obtain the net income data. Calculate the net income of each capacity interval through the formula: ; Among them, is the net income (yuan) of the jth capacity interval, is the real-time market electricity price (yuan / kWh), is the theoretical power generation (kWh) corresponding to the wind speed of the jth capacity interval, is the cost change of the jth capacity interval (yuan). Assume that the theoretical power generation corresponding to the 3rd capacity interval is 1200 kWh, the real-time electricity price is 0.5 yuan / kWh, and the cost change is 1200 yuan. Substitute into the formula for calculation: ; The calculated net income of the 3rd interval is -600 yuan. Repeat the above steps to calculate the net income of each interval and record them one by one to form the complete interval net income data.

[0054] S503: Call the interval net income data. By comparing the net incomes at each capacity level, identify the optimal frequency modulation capacity and calculate the expected net income to obtain the analysis result of the unit's frequency modulation value; The interval net income data specifically calls all the numerical sequences of the net income of each capacity interval obtained in the previous step. Each net income value of each capacity interval is called one by one for pairwise comparison operations to determine the magnitude of the net income values of each interval and record the maximum net income value and the corresponding capacity interval. For example, when the net income of the first interval is called as 200 yuan and that of the second interval is 400 yuan, after comparison, it is determined that the net income of the second interval is larger. Then, the net income of the third interval, -600 yuan, is called and compared with the net income of the second interval, 400 yuan, to confirm that the net income of the second interval is still the current larger value. Next, the net income of the fourth interval, 800 yuan, is called and compared with the previously recorded larger value of 400 yuan. It is confirmed that the net income of the fourth interval is greater, and the fourth interval is recorded as the current optimal interval. Repeat the above steps until all the net income values of all intervals are called and the comparison is completed. Finally, determine that the capacity interval corresponding to the maximum net income of the capacity interval net income is the optimal frequency modulation capacity interval. For example, the optimal frequency modulation capacity interval is 140 - 160 kW, and the net income value is 1200 yuan. Record the upper limit capacity of this interval, 160 kW, as the optimal frequency modulation capacity, and call this maximum net income value of 1200 yuan as the expected net income. Record the above capacity value and net income as the result of the unit frequency modulation value analysis.

[0055] Please refer to Figure 2 , a system for evaluating the value of wind power participating in system frequency modulation. The system for evaluating the value of wind power participating in system frequency modulation is used to execute the above method for evaluating the value of wind power participating in system frequency modulation. The system includes: The data correction module obtains the operating data of the wind turbine, analyzes the deviation characteristics between the unit power and the theoretical power curve, compares the power deviation amplitude with the preset tolerance threshold, marks the abnormal data segment, and combines the power volatility of adjacent units and the grid frequency volatility to obtain the corrected operating data; The response coordination module calls the corrected operating data, extracts the voltage volatility of the DC side of the converter and the change rate of the pitch angle command, counts the synchronous fluctuation period of the active current command of the converter and the pitch angle command, calculates the correlation coefficient between the grid frequency deviation and the output power, and generates a dynamic response coefficient; The health constraint module calls the dynamic response coefficient, collects the temperature gradient data of the converter and the main vibration frequency amplitude of the gearbox, calculates the component health index according to the temperature gradient deviation rate and the vibration amplitude deviation rate, and combines the unit output power data to generate the health constraint frequency modulation capacity boundary; The frequency modulation cost accounting module, based on the health constraint frequency modulation capacity boundary, extracts the change rate of the pitch angle command and the change rate of the converter power command, analyzes the type of frequency modulation action and the characteristics of the adjustment amplitude, divides the intensity level of the frequency modulation action according to the characteristics of the adjustment amplitude, calculates the energy consumption and equipment loss cost corresponding to each level, and generates the unit frequency modulation cost; The frequency regulation value evaluation module calls the unit's frequency regulation cost and the frequency regulation capacity boundary with health constraints, calculates the cost increment per unit of frequency regulation capacity, combines the wind speed prediction power distribution and the real-time electricity price, and identifies the optimal frequency regulation capacity by analyzing the net income of each frequency regulation capacity interval, generating the analysis results of the unit's frequency regulation value.

[0056] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0057] It should be understood that the term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context.

[0058] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0059] It should be understood that in various embodiments of the present invention, the sequence numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0060] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0061] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0062] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings, direct couplings, or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0063] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0064] In addition, the functional units in various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0065] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0066] As described above, the above are only specific implementation manners of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for evaluating the value of wind power participating in system frequency regulation, characterized in that: The method comprises: S1: Obtain wind turbine operation data, analyze the deviation characteristics of the unit power and theoretical power curve, mark abnormal data segments based on the comparison results of the unit power deviation characteristics and preset tolerances, and obtain corrected operation data by combining the power and frequency data of adjacent units; S2: Based on the corrected operating data, the converter DC side voltage data and the pitch angle command change rate data are called, the coordinated response characteristics of the converter active current command and the pitch angle command are analyzed, the relationship between the converter output power and the grid frequency deviation is calculated, and a dynamic response coefficient is generated; S3: calling the dynamic response coefficient, collecting converter temperature data and gearbox vibration main frequency amplitude data, combining output power data, calculating component health index in real time, and calculating frequency regulation capacity correction factor according to the health of the unit, and obtaining health-constrained frequency regulation capacity boundary; S4: Based on the health-constrained frequency regulation capacity boundary, according to the pitch angle command change rate, the converter power command change rate, and the frequency regulation action duration, the frequency regulation action type and the adjustment amplitude characteristics are analyzed, the frequency regulation action intensity levels are divided according to the adjustment amplitude characteristics, and the total frequency regulation cost is calculated to obtain the unit frequency regulation cost.

2. The method for evaluating the value of wind power participating in system frequency regulation according to claim 1 is characterized in that: The corrected operating data specifically includes a verification timestamp, a corrected power value, and a frequency deviation sequence; the dynamic response coefficient includes a frequency deviation gain factor, an inverter equivalent time constant, and a pitch system response delay; the health-constrained frequency regulation capacity boundary specifically refers to a frequency regulation capacity correction factor, a component health index, and a capacity boundary calculation result; the unit frequency regulation cost includes additional energy consumption of the control system, component fatigue loss conversion value, and opportunity cost estimation data.

3. The method for evaluating the value of wind power participating in system frequency regulation according to claim 1 is characterized in that: The steps of obtaining wind turbine operation data, analyzing the deviation characteristics of the unit power and theoretical power curve, marking abnormal data segments according to the comparison results of the unit power deviation characteristics and the preset tolerance, and obtaining the corrected operation data by combining the power and frequency data of adjacent units are as follows: S101: Obtaining wind turbine operation data, calling real-time wind speed data, active power data, and grid frequency deviation data, calculating the deviation between the actual power of the computer group and the theoretical power curve, and generating the power deviation value of the computer group; S102: calling the power deviation value of the unit, comparing the deviation value with a preset tolerance threshold, marking an abnormal data segment, and generating an abnormal data segment marking result; S103: Based on the abnormal data segment marking result, the power data mean and the frequency data mean of the adjacent units in the same time period are called to correct the marked abnormal data segment to generate corrected operating data.

4. The method for evaluating the value of wind power participating in system frequency regulation according to claim 3 is characterized in that: Based on the corrected operation data, the converter DC side voltage data and pitch angle command change rate data are called, the coordinated response characteristics of the converter active current command and the pitch angle command are analyzed, and the relationship between the converter output power and the grid frequency deviation is calculated. The steps of generating the dynamic response coefficient are specifically as follows: S201: Based on the corrected operation data, call the converter DC side voltage data and the pitch angle command change rate data, analyze the synchronous phase difference between the converter active current command and the pitch angle command, and generate the active and pitch angle synchronous phase difference; S202: calling the active power and pitch angle synchronization phase difference, combining the grid frequency deviation data, extracting the proportionality coefficient between the converter output power change amplitude and the frequency deviation amplitude, and generating power and frequency gain coefficients; S203: Based on the power and frequency gain coefficients, a response delay time difference between the converter power adjustment command and the pitch angle action command is calculated to generate a dynamic response coefficient.

5. The method for evaluating the value of wind power participating in system frequency regulation according to claim 4 is characterized in that: The specific formula for extracting the proportionality coefficient between the converter output power variation amplitude and the frequency deviation amplitude is: ； Calculating power and frequency gain coefficients to generate the power and frequency gain coefficients; in, Representative The power and frequency gain coefficients at the sampling moment, Representative The output power variation amplitude of the converter at each sampling moment is: Representative The amplitude of the grid frequency deviation data at each sampling point, Representative The phase difference between active power and pitch angle synchronization at each sampling moment, is the target sampling point index currently calculated, is the frequency deviation data index to be statistically summed, is the total number of samples of frequency deviation data.

6. The method for evaluating the value of wind power participating in system frequency regulation according to claim 4 is characterized in that: The steps of calling the dynamic response coefficient, collecting the converter temperature data and the gearbox vibration main frequency amplitude data, combining the output power data, calculating the component health index in real time, and calculating the frequency regulation capacity correction factor according to the health of the unit, and obtaining the health constraint frequency regulation capacity boundary are as follows: S301: calling the dynamic response coefficient, collecting the converter temperature data and the gearbox vibration main frequency amplitude data, and calculating the temperature deviation rate and the vibration amplitude deviation rate in real time by comparing with the rated operating parameters to obtain the component health index; S302: Based on the component health index and in combination with the output power data, by analyzing the relationship between the health index and the output power, a frequency modulation capacity correction ratio is calculated to generate a frequency modulation capacity correction factor; The specific formula for calculating the frequency modulation capacity correction ratio is: ； Calculate the frequency regulation capacity correction ratio and generate the frequency regulation capacity correction factor; in, Represents the frequency modulation capacity correction ratio, Representative The component health index at the sampling moment, Representative The actual output power value of the unit at the sampling moment, Represents the arithmetic mean of the component health index within the current sampling window. Represents the total number of sampling points in the sampling window, Represents the sampling window The index number of the time point, To avoid small positive constants with zero denominators; S303: Call the frequency regulation capacity correction factor and obtain the healthy constrained frequency regulation capacity boundary in combination with the rated frequency regulation capacity of the unit.

7. The method for evaluating the value of wind power participating in system frequency regulation according to claim 6 is characterized in that: Based on the healthy constrained frequency regulation capacity boundary, according to the pitch angle command change rate, the converter power command change rate, and the frequency regulation action duration, the frequency regulation action type and the regulation amplitude characteristics are analyzed, the frequency regulation action intensity levels are divided according to the regulation amplitude characteristics, and the total frequency regulation cost is calculated. The steps for obtaining the unit frequency regulation cost are specifically as follows: S401: Based on the healthy constrained frequency modulation capacity boundary, analyzing the activity of the pitch angle and the converter power command within the frequency modulation duration, identifying the adjustment action type and adjustment amplitude characteristics, and generating frequency modulation action characteristic data; S402: calling the frequency modulation action characteristic data, comparing with the preset frequency modulation intensity classification benchmark, identifying the action intensity level, and establishing the frequency modulation action intensity level; S403: According to the frequency regulation action intensity level and the frequency regulation duration, the additional energy consumption and component loss cost are calculated to obtain the unit frequency regulation cost.

8. The method for evaluating the value of wind power participating in system frequency regulation according to claim 1 is characterized in that: The method further comprises: S5: calling the frequency regulation cost of the unit and the health-constrained frequency regulation capacity boundary, calculating the marginal cost curve of the unit frequency regulation capacity, combining the wind speed forecast data and the real-time electricity price, calculating the net benefits of multiple frequency regulation capacity intervals, identifying the optimal frequency regulation capacity, and obtaining the unit frequency regulation value analysis result; The unit frequency regulation value analysis results specifically include the optimal capacity analysis results, the expected net frequency regulation income, and the frequency regulation marginal cost curve.

9. The method for evaluating the value of wind power participating in system frequency regulation according to claim 8 is characterized in that: The steps of calling the unit frequency regulation cost and health-constrained frequency regulation capacity boundary, calculating the marginal cost curve of unit frequency regulation capacity, combining wind speed forecast data and real-time electricity price, calculating the net benefits of multiple frequency regulation capacity intervals, identifying the optimal frequency regulation capacity, and obtaining the unit frequency regulation value analysis results are as follows: S501: calling the unit frequency regulation cost data and the health-constrained frequency regulation capacity boundary, dividing a plurality of frequency regulation capacity intervals within the capacity boundary, evaluating the cost change corresponding to each interval, and establishing a marginal cost curve; S502: Based on the marginal cost curve, combined with wind speed forecast information and real-time market electricity prices, the net benefits of multiple frequency regulation capacity intervals are calculated to obtain interval net benefit data; S503: calling the interval net profit data, identifying the optimal frequency regulation capacity by comparing the net profit at each capacity level, and calculating the expected net profit to obtain the unit frequency regulation value analysis result.

10. A wind power participation system frequency regulation value assessment system, characterized in that: The system is used to implement the method for evaluating the value of wind power participating in system frequency regulation according to any one of claims 1 to 9, and the system comprises: The data correction module obtains the wind turbine operating data, analyzes the deviation characteristics of the unit power and the theoretical power curve, compares the power deviation amplitude with the preset tolerance threshold, marks the abnormal data segment, and obtains the corrected operating data by combining the power fluctuation rate of the adjacent units and the grid frequency fluctuation rate; The response coordination module calls the corrected operation data, extracts the voltage fluctuation rate and pitch angle command change rate of the converter DC side, counts the synchronous fluctuation period of the converter active current command and the pitch angle command, calculates the correlation coefficient between the grid frequency deviation and the output power, and generates a dynamic response coefficient; The health constraint module calls the dynamic response coefficient, collects the temperature gradient data of the converter and the vibration main frequency amplitude of the gearbox, calculates the component health index according to the temperature gradient deviation rate and the vibration amplitude deviation rate, and generates the health constraint frequency modulation capacity boundary in combination with the unit output power data; The frequency regulation cost accounting module extracts the pitch angle command change rate and the converter power command change rate based on the health constraint frequency regulation capacity boundary, analyzes the frequency regulation action type and the regulation amplitude characteristics, divides the frequency regulation action intensity level according to the regulation amplitude characteristics, calculates the energy consumption and equipment loss cost corresponding to each level, and generates the unit frequency regulation cost; The frequency regulation value assessment module calls the unit frequency regulation cost and health-constrained frequency regulation capacity boundary, calculates the cost increment of unit frequency regulation capacity, combines the wind speed predicted power distribution and the real-time electricity price, analyzes the net profit of each frequency regulation capacity interval, identifies the optimal frequency regulation capacity, and generates the unit frequency regulation value analysis result.

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