A frequency modulation control method and system for a thermal power generating unit

Abstract

The application discloses a frequency modulation control method and system for a thermal power unit, and relates to the technical field of frequency modulation control, which comprises the following steps: collecting a frequency modulation instruction signal of a power grid, decomposing the frequency modulation instruction signal to obtain a plurality of eigenmode function components and a residual component; performing frequency spectrum analysis on each eigenmode function component, marking the component with a main frequency exceeding a high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculating a fluctuation amplitude and a change rate; generating a thermal system control instruction through a PID control algorithm to adjust a coal supply amount and a main steam pressure; for the high-frequency disturbance component, generating an auxiliary compensation control instruction through a fuzzy control algorithm; converting the thermal system control instruction and the auxiliary compensation control instruction into operation parameters of a thermal power unit control mechanism and issuing the operation parameters for execution; and when a control effect deviation continuously exceeds a deviation threshold, triggering an optimization process, which significantly improves the frequency modulation stability and equipment safety of the unit in a new energy high-proportion access power grid environment.

Description

Technical Field

[0001] This invention relates to the field of frequency regulation control technology, specifically to a frequency regulation control method and system for thermal power units. Background Technology

[0002] In traditional power grid frequency regulation control strategies, power grid frequency regulation commands are usually directly transmitted to the control loop of thermal power units to achieve rapid adjustment of the power grid frequency. In this process, the frequency regulation command signal is not subjected to detailed frequency component analysis, but is regarded as a unified control signal, which directly acts on the thermal system and turbine control mechanisms of the thermal power unit. According to the received command, the thermal power unit responds to the changing needs of the power grid frequency by adjusting the coal feed rate, main steam pressure, and turbine inlet valve opening.

[0003] However, this control method, which does not distinguish the frequency components of the command signal, has significant shortcomings. Due to the large inertia of the thermal system of thermal power units, when the frequency regulation command contains high-frequency disturbance components, such as commands that change frequently within one minute due to wind power or photovoltaic fluctuations, the thermal system has difficulty effectively tracking these high-frequency changes. The undecomposed high-frequency components directly act on the control mechanism, leading to an abnormal increase in the frequency of equipment operation. For example, the coal feeder needs to start and stop 2 to 3 times per minute, and the regulating valve repeatedly opens and closes, which in turn exacerbates equipment wear. Specifically, the life of the coal feeder belt is shortened by about 30%, and the leakage rate of the regulating valve seals increases by 20%. In addition, the lag response of the thermal system to high-frequency disturbances means that the control actions cannot be timely converted into changes in steam flow, resulting in a significant deterioration in the frequency regulation effect. Specifically, the deviation between the actual output of the unit and the command target widens, and the frequency regulation accuracy decreases by 15% to 20%, failing to meet the grid's demand for rapid frequency stability adjustment. This defect is particularly prominent in grid environments with a high proportion of new energy sources, because the volatility of new energy sources further increases the complexity and difficulty of grid frequency regulation. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] To address the shortcomings of existing technologies, this invention provides a frequency regulation control method and system for thermal power units. It accurately separates high-frequency disturbance components from low-frequency components in the frequency regulation command using adaptive mode decomposition technology. Furthermore, considering the large inertia of the thermal system and the rapid response of the turbine control valves, it employs PID control and fuzzy control to generate coordinated commands. This solves the problems of high equipment operation frequency, increased losses, and decreased frequency regulation accuracy caused by the failure to distinguish command frequency components in traditional methods. It significantly improves the frequency regulation stability and equipment safety of the unit in environments with a high proportion of new energy connected to the grid.

[0006] (II) Technical Solution

[0007] To achieve the above objectives, the present invention provides the following technical solution: a frequency regulation control method for thermal power units, comprising:

[0008] The frequency regulation command signal of the power grid is collected, and the frequency regulation command signal is decomposed by an adaptive mode decomposition algorithm to obtain multiple intrinsic mode function components and residual components.

[0009] Spectral analysis is performed on each intrinsic mode function component to extract the dominant frequency and energy percentage. Components whose dominant frequency exceeds the high-frequency disturbance frequency threshold are marked as high-frequency disturbance components, and the fluctuation amplitude and rate of change are calculated.

[0010] For the intrinsic mode function components and residual components whose main frequency does not exceed the high-frequency disturbance frequency threshold, the thermal system control command is generated by the PID control algorithm to adjust the coal feed rate and main steam pressure. For the high-frequency disturbance components, the auxiliary compensation control command is generated by the fuzzy control algorithm.

[0011] The thermal system control commands and auxiliary compensation control commands are converted into operating parameters of the target thermal power unit control mechanism and issued for execution. The operating status of the target thermal power unit and the grid frequency response are monitored in real time. When the control effect deviation continues to exceed the deviation threshold, the optimization process is triggered.

[0012] Furthermore, the adaptive mode decomposition algorithm is an improved set empirical mode decomposition algorithm, including:

[0013] Based on the minimum time constant in the thermal system of the target thermal power unit, the decomposition scale parameter λ is set to 1 / 5 to 1 / 2 of the minimum time constant; an adaptive noise amplitude is introduced, and the white noise amplitude is dynamically adjusted according to 0.1 times the standard deviation σ of the original signal; eigenmode function components are generated by 100 ensemble average decompositions, and the period of the highest frequency component is ≤λ.

[0014] Furthermore, the frequency modulation command signal is denoted as x(t), and N sets of Gaussian white noise sequences are generated. A set of Gaussian white noise is added to x(t) in the order of the Gaussian white noise sequences to obtain N sets of noisy signals. Empirical mode decomposition is performed on each set of noisy signals to obtain multiple intrinsic mode function components and one residual component. The N sets of decomposition results are integrated, and the arithmetic mean of the intrinsic mode function components of the same order is calculated to obtain several final intrinsic mode function components. The arithmetic mean of the residual components is calculated to obtain a final residual component.

[0015] Furthermore, the maximum time constant in the thermal system of the target thermal power unit is selected, and the high-frequency disturbance frequency threshold is set to 1 / 2π times the reciprocal of the maximum time constant. Fast Fourier transform is performed on each intrinsic mode function component to extract the dominant frequency and energy proportion. Intrinsic mode function components whose dominant frequency exceeds the high-frequency disturbance frequency threshold are marked as high-frequency disturbance components, and their fluctuation amplitude and rate of change are calculated. Among them, the fluctuation amplitude is the peak-to-valley difference of the time-domain signal of the intrinsic mode function component, and the rate of change is the absolute maximum value of the instantaneous rate of change of the time-domain signal of the intrinsic mode function component.

[0016] Furthermore, the generation of thermal system control commands includes:

[0017] The residual component is superimposed with the intrinsic mode function component whose main frequency does not exceed the high-frequency disturbance frequency threshold to form the total low-frequency target value; PID parameters are set, including proportional coefficient, integral time, and derivative time; control commands are output through the PID control algorithm to adjust the coal feed rate; based on the control deviation signal output by the PID, the coal feed rate is changed by adjusting the speed of the coal feeder, with the adjustment range being ±10% of the rated coal feed rate, while maintaining the main steam pressure at ±0.2MPa of the set value.

[0018] Furthermore, the generation of auxiliary compensation control commands includes:

[0019] Using the fluctuation amplitude and rate of change of the high-frequency disturbance component as input, a fuzzy control algorithm is used to output the fine adjustment amount of the turbine control valve. Among them, the fuzzy subset of fluctuation amplitude is {small, medium, large}, with a universe of discourse [0, 10]; the fuzzy subset of rate of change is {slow, medium, fast}, with a universe of discourse [0, 5]; the fuzzy subset of control valve fine adjustment amount is {negative large, negative small, zero, positive small, positive large}, with a universe of discourse [-3, 3]. The fine adjustment amount is dynamically calculated according to the control rules, and the rate of change of control valve opening is limited to ≤0.5% / second.

[0020] Furthermore, when the directions of the thermal system control command and the auxiliary compensation control command conflict, the total energy percentage of all high-frequency disturbance components is calculated; if the total energy percentage is ≤30%, the thermal system control command is executed and the auxiliary compensation control command is paused; if the total energy percentage is >30%, the auxiliary compensation control command is executed first and the thermal system control command is executed after a 5-second delay.

[0021] Furthermore, for the coal feed command, the speed command output by the PID is converted into the frequency conversion signal of the coal feeder motor, with 4~20mA corresponding to the minimum to maximum coal feed; for the main steam pressure command, the pressure setpoint is converted into the control signal of the boiler drum pressure transmitter, with 4~20mA corresponding to 0~20MPa; for the valve opening command, it is converted into the position signal of the servo mechanism, with 4~20mA corresponding to 0~100% opening, the total opening being the sum of the pre-opening and the fine adjustment, and the single adjustment amplitude ≤1%; the converted signals are sent to the coal feeder control cabinet, the boiler control system, and the turbine valve servo mechanism in real time.

[0022] Furthermore, data on the actual load, main steam pressure, valve opening, and grid frequency of the target thermal power unit are collected; the grid frequency deviation is calculated, which is the absolute value of the difference between the actual grid frequency and the target frequency. When the control effect deviation exceeds the deviation threshold for 10 seconds, the optimization process is triggered.

[0023] The optimization process includes: analyzing the spectrum of the current high-frequency disturbance component through Fast Fourier Transform; if there is a component with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 5%, the decomposition scale parameter is adjusted to the original value × 0.8; if the low-frequency component contains a component with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 3%, the decomposition scale parameter is adjusted to the original value × 1.2.

[0024] A frequency regulation control system for a thermal power unit includes:

[0025] The signal decomposition module acquires the frequency modulation command signal from the power grid and uses an adaptive mode decomposition algorithm to decompose the frequency modulation command signal to obtain multiple intrinsic mode function components and residual components.

[0026] The spectrum analysis module performs spectrum analysis on each intrinsic mode function component, extracts the dominant frequency and energy percentage, marks the components whose dominant frequency exceeds the high-frequency disturbance frequency threshold as high-frequency disturbance components, and calculates the fluctuation amplitude and rate of change.

[0027] The control command generation module generates thermal system control commands through a PID control algorithm for intrinsic mode function components and residual components whose main frequency does not exceed the high-frequency disturbance frequency threshold, thereby adjusting the coal feed rate and main steam pressure. For high-frequency disturbance components, it generates auxiliary compensation control commands through a fuzzy control algorithm.

[0028] The optimization module converts thermal system control commands and auxiliary compensation control commands into operating parameters for the target thermal power unit's control mechanism and issues them for execution. It monitors the target thermal power unit's operating status and grid frequency response in real time. When the control effect deviation continues to exceed the deviation threshold, the optimization process is triggered.

[0029] (III) Beneficial Effects

[0030] This invention provides a frequency regulation control method and system for thermal power units, which has the following beneficial effects:

[0031] (1) The frequency regulation command of the power grid is accurately decomposed by the adaptive mode decomposition algorithm. The decomposition parameters are dynamically set by combining the minimum time constant of the thermal system of the thermal power unit and the noise processing is optimized to achieve effective stripping of high frequency disturbance components. This avoids the response lag problem caused by mode aliasing in traditional control and provides a non-overlapping frequency component basis for subsequent frequency division control strategies, thereby improving the adaptability of the unit to the new energy fluctuating power grid and the frequency regulation stability.

[0032] (2) By accurately setting the high-frequency disturbance frequency threshold through the maximum time constant of the thermal system of the thermal power unit, and by combining spectrum analysis to extract the main frequency and energy ratio of each component, the high-frequency disturbance component is identified and marked, the fluctuation amplitude and change rate of the high-frequency disturbance are accurately quantified, and key parameter inputs are provided for subsequent fuzzy control. This ensures that the high-frequency component is accurately separated and guided to the turbine control valve fast response channel, avoiding equipment loss caused by the thermal system due to response lag or malfunction, and improving the processing accuracy of high-frequency components in the frequency regulation command.

[0033] (3) By using a frequency division control strategy, PID control is used to generate thermal system control commands for low-frequency components, and the coal feed rate and main steam pressure are stably adjusted. Fuzzy control is used to generate auxiliary compensation commands for high-frequency components, and the high-frequency components are quickly responded to high-frequency disturbances. The combined advantages of the speed of the turbine control valve and the large inertia of the thermal system are fully utilized, and the frequency regulation response speed and accuracy are significantly improved. At the same time, a conflict coordination mechanism is introduced to dynamically adjust the command priority according to the energy ratio of high-frequency components, avoid power oscillation caused by regulation conflicts, and ensure the stability of unit operation and equipment safety.

[0034] (4) By accurately converting control commands into operating parameters of the actuator, the closed-loop execution of commands is realized, the unit load, main steam pressure and grid frequency response are monitored in real time, and a dynamic feedback mechanism is constructed. When the control deviation continues to exceed the limit, the parameter optimization process is automatically triggered to solve the problem of reduced control effect caused by high-frequency disturbance identification deviation or changes in operating conditions, and significantly improves the adaptability and stability of the system in long-term operation. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the frequency regulation control method for thermal power units of the present invention;

[0036] Figure 2 This is a schematic diagram of the frequency regulation control method for thermal power units of the present invention;

[0037] Figure 3 This is a schematic diagram of the frequency regulation control system of the thermal power unit of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figure 1 and Figure 2 This invention provides a frequency regulation control method for thermal power units, comprising the following steps:

[0040] Step 1: Acquire the frequency regulation command signal of the power grid, and use the adaptive mode decomposition algorithm to decompose the frequency regulation command signal to obtain multiple intrinsic mode function components and residual components;

[0041] Step one includes the following:

[0042] Step 101: Through the real-time communication interface between the target thermal power unit and the power grid dispatch system, continuously collect the frequency regulation command signal issued by the power grid. This signal is a dynamic electrical signal reflecting the frequency deviation of the power grid, usually a 4~20mA analog or digital signal, containing multi-frequency component fluctuations caused by load changes, new energy fluctuations, etc., such as high-frequency fluctuations (period 10~60 seconds), medium-frequency fluctuations (period 1~10 minutes), and low-frequency fluctuations (period more than 10 minutes). To ensure the real-time performance and integrity of the signal, the sampling frequency is set to 10Hz, that is, once every 0.1 seconds. The collected signal is preprocessed, such as filtering to remove electromagnetic interference and verifying whether the signal range is within the range of 0-100MW to ensure that the signal is not distorted.

[0043] Step 102: Based on the inertial characteristics of the thermal system of the thermal power unit, set the decomposition scale parameter. Taking the minimum time constant in the thermal system of the target thermal power unit as the benchmark, the minimum time constant is denoted as τmin. Set the decomposition scale parameter λ to 1 / 5 to 1 / 2 of the minimum time constant, that is, λ∈[τmin / 5, τmin / 2].

[0044] The thermal system of a thermal power unit includes a boiler, a steam turbine, and steam pipes. Its inertia is mainly reflected in the time constant, which is obtained through unit design parameters or experimental tests. The thermal inertia time constant of a boiler is usually 30 to 180 seconds, depending on the type of boiler. For example, the time constant of a pulverized coal boiler is about 60 to 120 seconds, the time constant of a circulating fluidized bed boiler is about 100 to 180 seconds, and the time constant of a steam turbine and its steam pipes is about 5 to 30 seconds.

[0045] Step 103: Decompose the FM command signal using an improved ensemble empirical mode decomposition algorithm: The improved ensemble empirical mode decomposition (EEMD) algorithm optimizes the traditional EEMD mode aliasing problem. Specific improvements include: introducing adaptive noise amplitude, dynamically adjusting the added white noise amplitude based on the standard deviation σ of the original signal (white noise amplitude = 0.1 × σ); increasing the ensemble averaging iteration to 100 to reduce noise residue. The decomposition process is as follows:

[0046] The frequency modulation command signal is denoted as x(t). N sets of Gaussian white noise sequences are generated. The mean of the Gaussian white noise sequence is 0. A set of Gaussian white noise is added to x(t) in the order of the Gaussian white noise sequence to obtain N sets of noisy signals. Empirical mode decomposition is performed on each set of noisy signals to obtain k intrinsic mode function components and one residual component.

[0047] The decomposition results of N groups are integrated, and the arithmetic mean of the eigenmode function components of the same order is calculated to obtain several final eigenmode function components. The arithmetic mean of the residual components is calculated to obtain a final residual component. Among them, the k-th eigenmode function component of different groups is of the same order. The decomposed eigenmode function components are sorted from high to low frequency. The decomposition effect is verified by Hilbert spectrum. It is required that the frequency ranges of each eigenmode function component do not overlap, and the period of the eigenmode function component with the highest frequency is ≤λ.

[0048] When using this method, please refer to steps 101 to 103:

[0049] The adaptive mode decomposition algorithm is used to accurately decompose the grid frequency regulation command. Combined with the minimum time constant of the thermal system of the thermal power unit, the decomposition parameters are dynamically set and the noise processing is optimized to effectively remove high-frequency disturbance components. This avoids the response lag problem caused by mode aliasing in traditional control and provides a non-overlapping frequency component basis for subsequent frequency division control strategies, thereby improving the unit's adaptability to the fluctuating grid of new energy sources and the stability of frequency regulation.

[0050] Step 2: Perform spectral analysis on each intrinsic mode function component, extract the dominant frequency and energy percentage, mark the component whose dominant frequency exceeds the high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculate the fluctuation amplitude and rate of change.

[0051] Step two includes the following:

[0052] Step 201: Calculate the frequency threshold of high-frequency disturbance based on the response capability of the thermal system of the thermal power unit. Select the maximum time constant τmax in the thermal system of the thermal power unit and set the frequency threshold of high-frequency disturbance to 1 / 2π times the reciprocal of the maximum time constant, that is, the frequency threshold of high-frequency disturbance = 1 / (2π×τmax).

[0053] The high-frequency disturbance frequency threshold is the lower limit of the fluctuation frequency that the thermal system of a thermal power unit cannot effectively track. The response capability of the thermal system of a thermal power unit is determined by its amplitude-frequency characteristics. When the fluctuation frequency exceeds the cutoff frequency of the thermal system of the thermal power unit, the output amplitude of the thermal system of the thermal power unit decays to less than 0.707 times the input, which is considered as an ineffective response. For different units, the time constant can be corrected through step response experiments. For example, when a step coal feed command is input to the boiler, the time when the main steam pressure reaches 63.2% of the steady-state value is recorded as the time constant to ensure the accuracy of the time constant.

[0054] Step 202: Perform spectral analysis on the intrinsic mode function components. Fast Fourier Transform (FFT) is used to perform spectral analysis on each intrinsic mode function component. Specific steps include:

[0055] Each intrinsic mode function component is zero-mean processed to remove the DC component;

[0056] A sampling window of length L=1024 is selected, and an FFT transformation is performed to obtain the frequency spectrum;

[0057] Extract the principal frequency (the frequency corresponding to the peak value in the frequency spectrum) and frequency bandwidth (the frequency range corresponding to the drop-off from the peak value to 50% of the peak value on both sides) of each intrinsic mode function component.

[0058] The energy of each intrinsic mode function component is calculated by integrating the sum of squares of the time-domain signals of the intrinsic mode function components. The calculation formula is as follows: ,in, Indicates the first k The energy of each eigenmode function component Indicates the first k There are 10 intrinsic mode function components, the integration interval is the signal acquisition period, and the energy proportion of each intrinsic mode function component is calculated, i.e., energy proportion = Total energy, Total energy = ,in, The energy of the residual component;

[0059] Step 203: Mark the intrinsic mode function components whose main frequency exceeds the high-frequency disturbance frequency threshold as high-frequency disturbance components. For the marked high-frequency disturbance components, calculate the difference between the peak and valley values ​​in the time domain signal of the intrinsic mode function component as the fluctuation amplitude. At the same time, calculate the root mean square value of the time domain signal of the intrinsic mode function component as the average fluctuation intensity. Calculate the instantaneous rate of change of the time domain signal of the intrinsic mode function component and take the maximum absolute value as the rate of change.

[0060] When using this method, refer to steps 201 to 203:

[0061] Precisely set the high-frequency disturbance frequency threshold through the maximum time constant of the thermal system of the thermal power unit, and combine spectral analysis to extract the main frequency and energy proportion of each component, so as to identify and mark the high-frequency disturbance components, accurately quantify the fluctuation amplitude and change rate of the high-frequency disturbance, provide key parameter inputs for subsequent fuzzy control, ensure that the high-frequency components are accurately separated and directed to the fast response channel of the steam turbine governing valve, avoid equipment losses caused by response lag or misoperation of the thermal system, and at the same time improve the processing accuracy of the high-frequency components in the frequency modulation command.

[0062] Step 3: For the intrinsic mode function components and residual components whose main frequencies do not exceed the high-frequency disturbance frequency threshold, generate thermal system control commands through the PID control algorithm to adjust the coal feeding amount and the main steam pressure. For the high-frequency disturbance components, generate auxiliary compensation control commands through the fuzzy control algorithm;

[0063] The said Step 3 includes the following contents:

[0064] Step 301: Mark the intrinsic mode function components whose main frequencies do not exceed the high-frequency disturbance frequency threshold as low-frequency components. For the residual components and low-frequency components, generate thermal system control commands through the PID control algorithm to adjust the coal feeding amount and the main steam pressure, specifically including:

[0065] Superimpose the residual components and the low-frequency components as the total low-frequency target value;

[0066] Set the PID parameters, including the proportional coefficient, integral time, and differential time. Among them, the proportional coefficient Kp = 0.5 - 2.0, the integral time Ti = 60 - 120 seconds, and the differential time Td = 10 - 30 seconds, which are tuned by the critical proportion method;

[0067] Adjust the coal feeding amount. According to the control deviation signal output by the PID, change the coal feeding amount by adjusting the speed of the coal feeder. The adjustment range is ±10% of the rated coal feeding amount, and the adjustment rate ≤ 1% of the rated coal feeding amount per second;

[0068] Control the pre-opening degree of the steam turbine admission valve through the PID to maintain the main steam pressure Psteam within the set value Pset ± 0.2 MPa. When Psteam > Pset + 0.2 MPa, reduce the pre-opening degree of the admission valve to lower the pressure. When Psteam < Pset - 0.2 MPa, increase the pre-opening degree of the admission valve to raise the pressure;

[0069] Step 302: For the high-frequency disturbance components, utilize the fast response characteristic of the steam turbine governing valve to generate auxiliary compensation control commands through the fuzzy control algorithm to finely adjust the opening degree of the governing valve, specifically including:

[0070] The fluctuation amplitude and rate of change of high-frequency components are selected as input variables of the fuzzy controller. The fuzzy subset of fluctuation amplitude is "small, medium, large" with a universe of discourse of [0,10]. For example, [0,3] is small, (3,7] is medium, and (7,10] is large. The fuzzy subset of rate of change is "slow, medium, fast" with a universe of discourse of [0,5]. For example, [0,2] is small, (2,3] is medium, and (3,5] is large. The fuzzy subsets are fuzzified using a triangular membership function.

[0071] The output variable is the valve opening fine-tuning amount, and the fuzzy subset of the valve opening fine-tuning amount is "negative large, negative small, zero, positive small, positive large", with a universe of discourse of [-3,3].

[0072] Control rules are constructed based on the "IF-THEN" rule. If the fluctuation amplitude is small and the rate of change is slow, the valve opening fine-tuning amount is zero; if the fluctuation amplitude is small and the rate of change is medium, the valve opening fine-tuning amount is positive small; if the fluctuation amplitude is small and the rate of change is fast, the valve opening fine-tuning amount is positive small; if the fluctuation amplitude is medium and the rate of change is slow, the valve opening fine-tuning amount is positive small; if the fluctuation amplitude is medium and the rate of change is medium, the valve opening fine-tuning amount is positive small; if the fluctuation amplitude is medium and the rate of change is fast, the valve opening fine-tuning amount is positive large; if the fluctuation amplitude is large and the rate of change is slow, the valve opening fine-tuning amount is positive small; if the fluctuation amplitude is large and the rate of change is medium, the valve opening fine-tuning amount is positive large; if the fluctuation amplitude is large and the rate of change is fast, the valve opening fine-tuning amount is positive large.

[0073] The rate of change of the valve opening is limited to ≤0.5% / second, that is, the difference in the fine adjustment of the valve opening between adjacent moments does not exceed 0.5% × control period, and the control period is usually 1 second;

[0074] Step 303: When both the thermal system control command and the auxiliary compensation control command point to an increase in load, or both point to a decrease in load, it is determined that there is no conflict, and the two are executed in parallel; when the command directions are opposite, such as the thermal system control command requiring a decrease in load and the auxiliary compensation control command requiring an increase in load, the total energy percentage of the high-frequency disturbance component is calculated, that is, the sum of the energy percentages of all high-frequency disturbance components. If the total energy percentage of the high-frequency disturbance component is ≤30%, the thermal system control command is executed, and the auxiliary compensation control command is paused; if the total energy percentage of the high-frequency disturbance component is >30%, the auxiliary compensation control command is executed first, and the thermal system control command is delayed for 5 seconds.

[0075] When using this method, refer to the content of steps 301 to 303:

[0076] By employing a frequency division control strategy, PID control is used to generate thermal system control commands for low-frequency components, stabilizing and regulating coal feed and main steam pressure. Fuzzy control is used to generate auxiliary compensation commands for high-frequency components, enabling rapid response to high-frequency disturbances. This fully leverages the synergistic advantages of the turbine control valve's speed and the thermal system's large inertia, significantly improving frequency regulation response speed and accuracy. Simultaneously, a conflict coordination mechanism is introduced to dynamically adjust command priority based on the energy proportion of high-frequency components, avoiding power oscillations caused by regulation conflicts and ensuring unit operation stability and equipment safety.

[0077] Step 4: Convert the thermal system control commands and auxiliary compensation control commands into operating parameters of the target thermal power unit control mechanism and issue them for execution. Monitor the operating status of the target thermal power unit and the grid frequency response in real time. When the control effect deviation continues to exceed the deviation threshold, trigger the optimization process.

[0078] Step four includes the following:

[0079] Step 401: Convert the generated thermal system control commands and auxiliary compensation control commands into specific operating parameters for each control mechanism of the target thermal power unit. For the coal feed command, convert the speed command output by the PID controller into a frequency converter signal for the coal feeder motor, a 4~20mA analog signal, where 4mA corresponds to the minimum coal feed and 20mA corresponds to the maximum coal feed. The conversion formula is as follows: ,in, I For output current, n For the target speed, The rated speed is used for the main steam pressure command. The pressure setpoint is converted into a control signal for the boiler drum pressure transmitter, which is 4~20mA and corresponds to a pressure range of 0~20MPa. For the valve opening command, the total opening is equal to the pre-opening of the thermal system control plus the valve opening fine adjustment, which is converted into a position signal for the servo mechanism. The 4~20mA corresponds to 0~100% opening, and the single adjustment range is limited to no more than 1%. The converted parameters are sent to the coal feeder control cabinet, the boiler control system, and the turbine valve servo mechanism in real time.

[0080] Step 402: Monitor the operating status and grid frequency response of the target thermal power unit in real time, and comprehensively collect the action data and frequency change data of the control mechanism. The monitoring parameters include: actual unit load, main steam pressure, coal feed rate, valve opening, boiler outlet temperature and other operating status parameters; real-time grid frequency; control mechanism action data, including coal feeder speed feedback, valve opening feedback, and actuator fault signals, such as jamming and overcurrent.

[0081] Step 403: Calculate the control effect deviation based on the monitoring data. ,in, This is the actual power grid frequency. For the target frequency, when the control effect deviation exceeds the deviation threshold (e.g., 0.05) for 10 consecutive seconds, the optimization process is triggered: The spectrum of the current high-frequency disturbance component is analyzed using Fast Fourier Transform (FFT). If there are undecomposed components with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 5%, indicating that the high-frequency disturbance has not been fully extracted, the decomposition scale parameter is adjusted to the original value × 0.8. If the low-frequency components contain components with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 3%, the decomposition scale parameter is adjusted to the original value × 1.2, and step one of the decomposition is re-executed. The maximum time constant is updated every 3 months, and the high-frequency disturbance frequency threshold is recalculated. If the unit is modified by adding a heat storage device, the maximum time constant is corrected in real time. The proportional coefficient Kp is reduced to 0.9 times the original value, and the integral time Ti is increased to 1.1 times the original value.

[0082] When using this method, please refer to the content of steps 401 to 403:

[0083] By accurately converting control commands into operating parameters of the actuators, closed-loop execution of commands is achieved. The unit load, main steam pressure, and grid frequency response are monitored in real time, and a dynamic feedback mechanism is constructed. When the control deviation continues to exceed the limit, the parameter optimization process is automatically triggered to solve the problem of decreased control effect caused by high-frequency disturbance identification deviation or changes in operating conditions, and significantly improves the adaptability and stability of the system in long-term operation.

[0084] Please see Figure 3 The present invention also provides a frequency regulation control system for thermal power units, comprising: a signal decomposition module, a spectrum analysis module, a control command generation module, and an optimization module, wherein:

[0085] The signal decomposition module acquires the frequency modulation command signal from the power grid and uses an adaptive mode decomposition algorithm to decompose the frequency modulation command signal to obtain multiple intrinsic mode function components and residual components.

[0086] The spectrum analysis module performs spectrum analysis on each intrinsic mode function component, extracts the dominant frequency and energy percentage, marks the components whose dominant frequency exceeds the high-frequency disturbance frequency threshold as high-frequency disturbance components, and calculates the fluctuation amplitude and rate of change.

[0087] The control command generation module generates thermal system control commands through a PID control algorithm for intrinsic mode function components and residual components whose main frequency does not exceed the high-frequency disturbance frequency threshold, thereby adjusting the coal feed rate and main steam pressure. For high-frequency disturbance components, it generates auxiliary compensation control commands through a fuzzy control algorithm.

[0088] The optimization module converts thermal system control commands and auxiliary compensation control commands into operating parameters for the target thermal power unit's control mechanism and issues them for execution. It monitors the target thermal power unit's operating status and grid frequency response in real time. When the control effect deviation continues to exceed the deviation threshold, the optimization process is triggered.

[0089] In the application, the various formulas mentioned are all calculated by removing dimensions and taking their numerical values. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The coefficients in the formulas are set by those skilled in the art according to the actual situation.

[0090] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, and combinations thereof. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A frequency regulation control method for thermal power units, characterized in that: include: The frequency regulation command signal from the power grid is acquired, and an adaptive mode decomposition algorithm is used to decompose the frequency regulation command signal. This includes: setting the decomposition scale parameter λ to 1 / 5 to 1 / 2 of the minimum time constant in the target thermal power unit's thermal system as a benchmark; introducing an adaptive noise amplitude, dynamically adjusting the white noise amplitude according to 0.1 times the standard deviation σ of the original signal; generating eigenmode function components through 100 ensemble averages, with the period of the highest frequency component ≤ λ; denoting the frequency regulation command signal as x(t), generating N sets of Gaussian white noise sequences, adding a set of Gaussian white noise to x(t) in sequence to obtain N sets of noisy signals, performing empirical mode decomposition on each set of noisy signals to obtain multiple eigenmode function components and one residual component; integrating the N sets of decomposition results, calculating the arithmetic mean of the eigenmode function components of the same order to obtain several final eigenmode function components, and calculating the arithmetic mean of the residual components to obtain a final residual component. Spectral analysis is performed on each intrinsic mode function component to extract the dominant frequency and energy percentage. Components whose dominant frequency exceeds the high-frequency disturbance frequency threshold are marked as high-frequency disturbance components, and the fluctuation amplitude and rate of change are calculated. For the intrinsic mode function components and residual components whose main frequency does not exceed the high-frequency disturbance frequency threshold, the thermal system control command is generated by the PID control algorithm to adjust the coal feed rate and main steam pressure. For the high-frequency disturbance components, the auxiliary compensation control command is generated by the fuzzy control algorithm. The thermal system control commands and auxiliary compensation control commands are converted into operating parameters of the target thermal power unit control mechanism and issued for execution. The operating status of the target thermal power unit and the grid frequency response are monitored in real time. When the control effect deviation continues to exceed the deviation threshold, the optimization process is triggered.

2. The frequency regulation control method for a thermal power unit according to claim 1, characterized in that: The maximum time constant in the thermal system of the target thermal power unit is selected, and the high-frequency disturbance frequency threshold is set to 1 / 2π times the reciprocal of the maximum time constant. Fast Fourier transform is performed on each intrinsic mode function component to extract the dominant frequency and energy proportion. Intrinsic mode function components whose dominant frequency exceeds the high-frequency disturbance frequency threshold are marked as high-frequency disturbance components, and their fluctuation amplitude and rate of change are calculated. Among them, the fluctuation amplitude is the peak-valley difference of the time domain signal of the intrinsic mode function component, and the rate of change is the absolute maximum value of the instantaneous rate of change of the time domain signal of the intrinsic mode function component.

3. The frequency regulation control method for a thermal power unit according to claim 1, characterized in that: The generated thermal system control commands include: The residual component is superimposed with the intrinsic mode function component whose main frequency does not exceed the high-frequency disturbance frequency threshold to form the total low-frequency target value; PID parameters are set, including proportional coefficient, integral time, and derivative time; control commands are output through the PID control algorithm to adjust the coal feed rate; based on the control deviation signal output by the PID, the coal feed rate is changed by adjusting the speed of the coal feeder, with the adjustment range being ±10% of the rated coal feed rate, while maintaining the main steam pressure at ±0.2MPa of the set value.

4. The frequency regulation control method for a thermal power unit according to claim 3, characterized in that: The generation of auxiliary compensation control commands includes: Using the fluctuation amplitude and rate of change of the high-frequency disturbance component as input, a fuzzy control algorithm is used to output the fine adjustment amount of the turbine control valve. Among them, the fuzzy subset of fluctuation amplitude is {small, medium, large}, with a universe of discourse [0, 10]; the fuzzy subset of rate of change is {slow, medium, fast}, with a universe of discourse [0, 5]; the fuzzy subset of control valve fine adjustment amount is {negative large, negative small, zero, positive small, positive large}, with a universe of discourse [-3, 3]. The fine adjustment amount is dynamically calculated according to the control rules, and the rate of change of control valve opening is limited to ≤0.5% / second.

5. The frequency regulation control method for a thermal power unit according to claim 4, characterized in that: When the directions of the thermal system control command and the auxiliary compensation control command conflict, calculate the total energy percentage of all high-frequency disturbance components; if the total energy percentage is ≤30%, execute the thermal system control command and suspend the auxiliary compensation control command; if the total energy percentage is >30%, prioritize the execution of the auxiliary compensation control command and delay the execution of the thermal system control command for 5 seconds.

6. The frequency regulation control method for a thermal power unit according to claim 1, characterized in that: For coal feed command, the speed command output by the PID controller is converted into a frequency converter signal for the coal feeder motor, with 4~20mA corresponding to the minimum to maximum coal feed. For main steam pressure command, the pressure setpoint is converted into a control signal for the boiler drum pressure transmitter, with 4~20mA corresponding to 0~20MPa. For valve opening command, it is converted into a position signal for the servo mechanism, with 4~20mA corresponding to 0~100% opening. The total opening is the sum of the pre-opening and the fine adjustment, and the single adjustment amplitude is ≤1%. The converted signals are sent to the coal feeder control cabinet, the boiler control system, and the turbine valve servo mechanism in real time.

7. The frequency regulation control method for a thermal power unit according to claim 6, characterized in that: Collect data on the actual load, main steam pressure, valve opening, and grid frequency of the target thermal power unit; calculate the grid frequency deviation, which is the absolute value of the difference between the actual grid frequency and the target frequency; and trigger the optimization process when the control effect deviation exceeds the deviation threshold for 10 seconds. The optimization process includes: analyzing the spectrum of the current high-frequency disturbance component through Fast Fourier Transform; if there is a component with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 5%, the decomposition scale parameter is adjusted to the original value × 0.8; if the low-frequency component contains a component with a dominant frequency > high-frequency disturbance frequency threshold and an energy percentage ≥ 3%, the decomposition scale parameter is adjusted to the original value × 1.

2.

8. A frequency regulation control system for a thermal power unit, used to implement the method described in any one of claims 1 to 7, characterized in that: include: The signal decomposition module acquires the frequency regulation command signal from the power grid and decomposes it using an adaptive mode decomposition algorithm. This includes: setting the decomposition scale parameter λ to 1 / 5 to 1 / 2 of the minimum time constant in the target thermal power unit's thermal system as a benchmark; introducing an adaptive noise amplitude, dynamically adjusting the white noise amplitude by 0.1 times the original signal standard deviation σ; generating eigenmode function components through 100 ensemble averages, with the period of the highest frequency component ≤ λ; denoting the frequency regulation command signal as x(t), generating N sets of Gaussian white noise sequences, adding a set of Gaussian white noise to x(t) in sequence to obtain N sets of noisy signals; performing empirical mode decomposition on each set of noisy signals to obtain multiple eigenmode function components and one residual component; integrating the N sets of decomposition results, calculating the arithmetic mean of the eigenmode function components of the same order to obtain several final eigenmode function components, and calculating the arithmetic mean of the residual components to obtain a final residual component. The spectrum analysis module performs spectrum analysis on each intrinsic mode function component, extracts the dominant frequency and energy percentage, marks the components whose dominant frequency exceeds the high-frequency disturbance frequency threshold as high-frequency disturbance components, and calculates the fluctuation amplitude and rate of change. The control command generation module generates thermal system control commands through a PID control algorithm for intrinsic mode function components and residual components whose main frequency does not exceed the high-frequency disturbance frequency threshold, thereby adjusting the coal feed rate and main steam pressure. For high-frequency disturbance components, it generates auxiliary compensation control commands through a fuzzy control algorithm. The optimization module converts thermal system control commands and auxiliary compensation control commands into operating parameters for the target thermal power unit's control mechanism and issues them for execution. It monitors the target thermal power unit's operating status and grid frequency response in real time. When the control effect deviation continues to exceed the deviation threshold, the optimization process is triggered.

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