A power station multi-time scale frequency control method with adaptive switching

Abstract

The application discloses a power station multi-time scale frequency control method of self-adaptive switching, S1: extracting power grid frequency fluctuation component; S2: quantifying short-time scale frequency deviation amplitude; S3: accumulating short-time scale oscillation unstable state; S4: calculating short-time scale oscillation change rate and performing state reset; S5: generating short-time scale primary frequency modulation weakening coefficient; S6: quantifying long-time scale frequency deviation amplitude; S7: accumulating long-time scale oscillation unstable state; S8: calculating long-time scale oscillation change rate and performing state reset; S9: generating long-time scale primary frequency modulation weakening coefficient; S10: calculating total primary frequency modulation weakening coefficient; S11: self-adaptive switching of primary frequency modulation control input signal; the control method extracts power grid frequency fluctuation component, respectively constructs short-time and long-time oscillation state quantification and evaluation logic, automatically identifies power grid operation condition, and is self-adaptive to switch, so that stable operation of a power system is realized.

Description

Technical Field

[0001] This invention relates to the field of primary frequency control technology for power plants, and in particular to a multi-timescale frequency control method for power plants with adaptive switching. Background Technology

[0002] With the accelerated construction of new power systems, my country's power system power structure is undergoing profound changes, with the installed capacity of new energy sources such as wind and solar power continuously increasing, and the power grid operation characteristics exhibiting significant power electronics features. As a crucial component of the large power grid, regional power grids bear the core responsibility of ensuring the electricity demand for local economic and social development. Constrained by multiple factors such as geographical environment, grid architecture, and power source layout, the connection between power grids in some remote areas, industrial load concentration areas, and new energy-rich areas and the main grid is relatively weak. Under the influence of sudden events such as extreme weather, transmission line faults, and abnormal equipment tripping, they are highly susceptible to disconnection from the main grid, resulting in isolated grid operation. In isolated grid operation, the grid capacity is small, the rotational inertia is low, and the anti-interference capability is poor. Even a slight imbalance between power output and load demand can cause large frequency fluctuations, which in severe cases can lead to unit tripping, large-scale load shedding, or even the collapse of the entire grid, posing a significant threat to the safe and stable operation of the power system.

[0003] Current control technologies for islanded grid frequency stabilization mainly focus on three areas: power source side modification, load side control, and energy storage-assisted frequency regulation. Existing technologies generally suffer from high investment costs, poor adaptability, and insufficient control precision. Most solutions require the addition of independent control devices or the construction of dedicated islanded grid operation control systems, involving extensive hardware procurement, installation, commissioning, and system integration work. This results in long modification cycles, high investment costs, and makes large-scale application in existing generating units difficult. Some technologies use fixed-parameter control logic, which cannot dynamically adjust control parameters according to islanded grid operating conditions and frequency fluctuation characteristics. Parameter tuning relies on manual experience, making it difficult to balance frequency response speed and stability under different disturbance intensities. Furthermore, after the grid resumes parallel operation with the main grid, it cannot automatically switch to normal control mode, potentially adversely affecting the main grid's frequency regulation. Other technologies achieve islanded grid stability by limiting the active power regulation range of generating units and forcibly changing the unit's operating mode, severely impacting the unit's normal active power output increase / decrease capabilities. This creates coupling conflicts with the original primary frequency regulation control loop, reducing the frequency regulation performance during normal grid operation. In addition, most existing control technologies are designed for single-type power sources, making it difficult to adapt to the complex power structure of multi-energy complementarity of wind, solar, hydro, thermal and energy storage. This makes it impossible to fully utilize the frequency regulation potential of various power sources, thus restricting the improvement of system frequency stability under islanded grid operation.

[0004] Based on the above-mentioned problems, frequency stability of isolated regional grids has become a key technical bottleneck restricting the safe and reliable operation of new power systems, and cannot meet the safety requirements of regional power grids to cope with extreme faults under the background of high proportion of new energy access. Summary of the Invention

[0005] To overcome the above problems, the purpose of this invention is to provide an adaptive switching multi-timescale frequency control method for power plants. This control method is used for switching between large-scale, isolated, and small-scale power grid operation modes. By extracting the frequency fluctuation components of the power grid, it constructs oscillation state quantification and evaluation logic for short-term and long-term timescales, automatically identifies low-frequency oscillations in the power grid and isolated / small-scale grid operation conditions, adaptively generates a primary frequency regulation weakening coefficient, rapidly suppresses oscillation propagation when the power grid experiences small-cycle low-frequency oscillations, weakens the frequency regulation effect over a long period when the power grid is in a weak connection state for a long time, and flexibly restores the full frequency regulation capability after the power grid resumes large-scale operation. This achieves precise matching between the power plant's frequency regulation characteristics and the power grid's operating state, improving the grid-source coordination level and the stability of the power system operation.

[0006] The technical solution adopted in this invention is:

[0007] An adaptive switching multi-timescale frequency control method for power plants includes the following steps:

[0008] S1: Extract the power grid frequency fluctuation component;

[0009] S2: Quantization of short-timescale frequency out-of-tolerance amplitude;

[0010] S3: Accumulate short-timescale oscillatory instability states. Add the output of S2 to the output of the previous calculation cycle switching module 2 algebraically to obtain the short-timescale oscillatory instability state quantity, thereby realizing the cumulative quantification of continuous frequency out-of-tolerance events.

[0011] S4: Calculate the short-timescale oscillation rate of change, set its lower limit by taking the maximum value of the result (0), and then perform a state reset.

[0012] S5: Generate short-timescale primary frequency modulation weakening coefficients;

[0013] S6: Quantizes the frequency out-of-tolerance amplitude over a long time scale;

[0014] S7: Accumulate long-term oscillatory instability states. Add the output of S6 to the output of the previous calculation cycle switching module 4 algebraically to obtain the long-term oscillatory instability state quantity, thereby realizing the cumulative quantification of long-term frequent frequency out-of-range events.

[0015] S8: Calculate the long-time scale oscillation rate of change, take the maximum value of it with 0 to limit the lower limit, and then perform a state reset;

[0016] S9: Generate long-time scale primary frequency modulation attenuation coefficients;

[0017] S10: Calculate the overall primary frequency modulation weakening coefficient, multiply the short-timescale weakening coefficient with the long-timescale weakening coefficient to obtain the overall primary frequency modulation weakening coefficient that integrates the oscillation characteristics of multiple timescales.

[0018] S11: Adaptive switching of primary frequency modulation control input signal.

[0019] As a further description of the present invention, the specific process of S1 is as follows:

[0020] S1-1: Real-time acquisition of power grid frequency signals;

[0021] S1-2: The power grid frequency signal is filtered by passing it through three cascaded first-order inertial elements, respectively;

[0022] S1-3: Subtract the filtered signal from the original grid frequency signal to obtain the pure fluctuation component of the grid frequency without DC offset.

[0023] As a further description of the present invention, the specific process of S2 is as follows: the frequency fluctuation component in S1 is input into the high and low tolerance alarm module, and it is determined whether the fluctuation amplitude exceeds the set short time scale alarm value. If it exceeds the set value, the product of the absolute value of the frequency fluctuation component and the proportional coefficient is output. If it does not exceed the set value, the output is 0.

[0024] As a further description of the present invention, the specific process of S4 is as follows:

[0025] S4-1: Smooth the first-order inertial element obtained in S3;

[0026] S4-2: The rate of change of oscillation is obtained by subtracting the smoothed signal from the oscillation signal;

[0027] S4-3: Take the maximum value of the result with 0 to limit the lower limit;

[0028] S4-4: Determine whether the maximum value in S43 is less than the fixed value C;

[0029] If so, a short pulse signal is triggered to make the output of switching module 2 0, completing the clearing and reset of the short-timescale oscillation state.

[0030] Otherwise, the switching module 2 will continue to output the value of the previous cycle and continue to accumulate the oscillation state.

[0031] As a further description of the present invention, the specific process of S5 is as follows:

[0032] S5-1: The signal from S4, after taking the maximum value of 0, is smoothed by passing it through a first-order inertial circuit;

[0033] S5-2: Subtract the smoothed signal from the fixed value D;

[0034] S5-3: Multiply the difference by the proportionality coefficient and then input it into the exponential function;

[0035] S5-4: Minimize the output value of the exponential function with 1 to limit the upper limit, and obtain the short-timescale primary frequency modulation attenuation coefficient.

[0036] As a further description of the present invention, the specific process of S6 is as follows: the oscillation rate of change in S4 and the result of taking the maximum value of 0 are input into another set of high and low error alarm modules to determine whether the set long-term scale alarm value is exceeded. If it is exceeded, the product of the absolute value of the frequency fluctuation component and the proportional coefficient is output. If it is not exceeded, the output is 0.

[0037] As a further description of the present invention, the specific process of S8 is as follows:

[0038] S8-1: Perform deep smoothing on the five cascaded first-order inertial elements obtained in S7.

[0039] S8-2: The long-time scale oscillation rate of change is obtained by subtracting the deep-smoothed signal from the oscillatory signal.

[0040] S8-3: Take the maximum value of the result with 0 to limit the lower limit;

[0041] S8-4: Determine whether the maximum value in S83 is less than the fixed value E;

[0042] If so, a short pulse signal is triggered to make the output of switching module 4 0, completing the clearing and reset of the long-term scale oscillation state. At the same time, this pulse signal serves as the global reset signal of the system.

[0043] Otherwise, the switching module 4 will continue to output the value of the previous cycle, and the long-term oscillation state will continue to accumulate.

[0044] As a further description of the present invention, the specific process of S9 is as follows:

[0045] S9-1: The signal in S8 after taking the maximum value of 0 is smoothed by passing it through a first-order inertial element;

[0046] S9-2: Subtract the smoothed signal from the fixed value F;

[0047] S9-3: Multiply the difference by the proportionality coefficient and then input it into the exponential function;

[0048] S9-4: The minimum value of the exponential function output value and 1 is taken to limit the upper limit, thus obtaining the long-time scale primary frequency modulation attenuation coefficient.

[0049] As a further description of the present invention, the specific switching process in S11 is as follows:

[0050] The original power grid frequency deviation signal is multiplied by the total weakening coefficient to obtain the optimized frequency modulation deviation signal. The output state of the switching module 5 is controlled by the RS flip-flop: when the signal after taking the maximum value of 0 in S4 is greater than the set value A, the RS flip-flop is set, and the switching module 5 outputs the optimized frequency modulation deviation signal to the primary frequency controller; when the global reset signal is triggered in S8, the RS flip-flop is reset, and the switching module 5 outputs the original power grid frequency deviation signal, thus ending one calculation cycle.

[0051] As a further description of the present invention, the total primary frequency modulation weakening coefficient in S10 is calculated by multiplying multiple time scale coefficients, thereby realizing the superposition of the adjustment effects at different time scales;

[0052] When only short-term low-frequency oscillations occur, the value is close to 1, and the total weakening effect is mainly provided by the component;

[0053] When the power grid is in a weak connection state for a long time, the continuous reduction and the combined effect achieve deep weakening;

[0054] Once the power grid resumes full operation, both will flexibly recover to 1 within a short period of time to avoid the impact of sudden frequency regulation on the power grid.

[0055] The beneficial effects of this invention are:

[0056] 1. By constructing oscillation detection and control loops that operate in parallel on both short and long time scales, accurate identification and differentiated control of different types of unstable operating conditions of the power grid are achieved. This can quickly suppress low-frequency oscillations with small cycles and weaken the frequency regulation effect over long periods during islanded / small grid operation, thus solving the problem that traditional primary frequency regulation control strategies cannot adapt to changes in the operating state of the power grid.

[0057] 2. This control method extracts the frequency fluctuation component by subtracting the original frequency signal from its third-order inertial filter signal. This effectively eliminates the influence of DC offset of the power grid frequency on oscillation detection, improves the accuracy and robustness of oscillation identification, and can still reliably detect the frequency oscillation component even when the overall power grid frequency deviates from the rated value.

[0058] 3. This control method uses a recursive accumulation approach to quantify the oscillation state, replacing the traditional integrator and simplifying the control system implementation. Simultaneously, the state clearing logic effectively prevents data overflow. The oscillation state quantity is coupled with both the oscillation amplitude and frequency, comprehensively reflecting the instability of the power grid and providing an accurate basis for adaptive adjustment of frequency regulation.

[0059] 4. This control method achieves nonlinear generation of the weakening coefficient through an exponential function, so that the degree of weakening of the frequency regulation effect matches the intensity of the power grid oscillation. It can quickly and deeply weaken the frequency regulation when the oscillation is severe, and can basically maintain the original frequency regulation capability when the oscillation is slight, thus achieving the optimal balance between frequency regulation support and oscillation suppression.

[0060] 5. This control method is entirely based on the existing control system of the power plant, requiring no additional hardware. Deployment can be completed simply by modifying the control logic, resulting in low implementation costs and a short cycle. The control logic adopts a modular design, facilitating parameter tuning and allowing for flexible adjustment based on the characteristics of different power plants and power grids, thus possessing broad applicability and promotional value. Furthermore, self-regulation eliminates the need for manual intervention by operators, enabling real-time adjustment of frequency regulation characteristics based on changes in the power grid's operating status. This truly achieves coordinated operation between the power grid and the grid, significantly improving the stability and reliability of the power system under various operating conditions. Attached Figure Description

[0061] Figure 1 This is the logic diagram of the main control of a power plant multi-timescale frequency control method with adaptive switching proposed in this invention.

[0062] Figure 2 This is a functional switching control logic diagram of an adaptive switching power plant multi-timescale frequency control method proposed in this invention. Detailed Implementation

[0063] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0064] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0065] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0066] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0067] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0068] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0069] like Figures 1-2 As shown, it illustrates a specific embodiment of the present invention:

[0070] Example 1:

[0071] An adaptive switching multi-timescale frequency control method for power plants includes the following steps:

[0072] Step 1: Extract the grid frequency fluctuation component. The real-time acquired grid frequency signal is filtered by three cascaded first-order inertial elements. The difference between the filtered signal and the original grid frequency signal is calculated to obtain the pure grid frequency fluctuation component without DC offset.

[0073] In this embodiment, the frequency fluctuation component is extracted by subtracting the original power grid frequency signal from its third-order inertial filter signal, instead of the traditional method of subtracting the frequency setpoint from the actual value. This effectively eliminates the impact of DC offset of the power grid frequency on the subsequent over-tolerance alarm logic, ensuring that even if the overall power grid frequency deviates from the rated value, the AC fluctuation component superimposed on the DC component can still be accurately extracted, thus guaranteeing the accuracy and reliability of oscillation detection.

[0074] Step 2: Quantify the short-time scale frequency out-of-tolerance amplitude. Input the frequency fluctuation component obtained in Step 1 into the high and low out-of-tolerance alarm module to determine whether the fluctuation amplitude exceeds the set short-time scale alarm values ​​h1 and l1. If it exceeds, output the product of the absolute value of the frequency fluctuation component and the proportional coefficient. If it does not exceed, output 0.

[0075] In this embodiment, the frequency fluctuation component is processed in parallel through two paths. The specific process is as follows:

[0076] 1. One of the input high / low tolerance alarm modules is set to a high value alarm setpoint and a low value alarm setpoint. When the frequency fluctuation component is greater than or less than the setpoint, the high / low tolerance alarm module outputs a true value; otherwise, it outputs a false value. The true value output by the alarm module is converted into a short pulse signal with a fixed width by a monostable multivibrator and input to the control selection port of the switching module 1.

[0077] 2. The absolute value of the frequency fluctuation component is obtained through the absolute value calculation module, multiplied by the scaling factor, and then input to port 1 of switching module 1. The input to port 2 of switching module 1 is 0.

[0078] 3. The control logic of the switching module 1 is as follows: when the control selection port is high, the analog value of the output port 1 is output; when the control selection port is low, the analog value of the output port 2 is output. That is, only when the frequency fluctuation amplitude exceeds the set threshold will the value proportional to the fluctuation amplitude be included in the oscillation state accumulation.

[0079] Step 3: Accumulate short-timescale oscillatory instability states. Add the output of Step 2 algebraically to the output value of the previous calculation cycle switching module 2 to obtain the short-timescale oscillatory instability state quantity, thereby realizing the cumulative quantification of continuous frequency out-of-tolerance events.

[0080] In this embodiment, in step 3, the short-timescale oscillation instability state quantity is calculated by recursive accumulation, which replaces the traditional integrator structure and simplifies the implementation complexity of the control system. This state quantity is coupled with the amplitude and frequency of frequency oscillation, and can comprehensively reflect the degree of instability of the power grid frequency in a short period of time.

[0081] Step 4: Calculate the short-timescale oscillation rate of change and perform state reset. The signal obtained in Step 3, after passing through the first-order inertial element, is smoothed. The difference between the smoothed signal and the oscillation rate of change is obtained. The maximum value of the difference between the smoothed signal and 0 is used to limit the lower limit. It is determined whether the maximum value is less than a fixed value. If so, a short pulse signal is triggered to make the output of switching module 2 0, thus completing the clearing and reset of the short-timescale oscillation state. Otherwise, the output of switching module 2 is kept at the value of the previous cycle, and the oscillation state continues to accumulate.

[0082] In this embodiment, in step 4, the oscillation rate of change obtained by subtracting it from the first-order inertial filter signal can reflect the changing trend of the oscillation state. When it continues to increase, it indicates that the amplitude of the grid frequency oscillation is increasing or the oscillation frequency is increasing, and the instability of the system is aggravated. The logic of taking the maximum value of 0 can shield the influence of the negative rate of change and avoid negative differential overshoot during reset.

[0083] Step 5: Generate short-time-scale primary frequency modulation attenuation coefficients. The signal obtained in Step 4 after taking the maximum value of 0 is smoothed through a first-order inertial circuit. The difference between the smoothed signal and a fixed value is calculated. The difference is multiplied by a proportional coefficient and then input into an exponential function. The minimum value of the exponential function output is taken by taking the minimum value of 1 to limit the upper limit, thus obtaining the short-time-scale primary frequency modulation attenuation coefficients.

[0084] In this embodiment, step 5 utilizes an exponential function and a minimum value constraint to achieve nonlinear generation and upper limit constraint of the primary frequency regulation weakening coefficient. The generated short-timescale primary frequency regulation weakening coefficient primarily targets low-frequency grid oscillations with a duration of 10 seconds to 3 minutes and a frequency range of 0.2 to 2 Hz. When the short-timescale oscillation is weak, the coefficient is close to 1, and the primary frequency regulation effect is essentially unaffected. When the oscillation intensifies, the coefficient decreases rapidly in an exponential manner, effectively weakening the primary frequency regulation effect and suppressing the spread of oscillations caused by excessive unit regulation.

[0085] Step 6: Quantify the frequency deviation amplitude on a long time scale. Input the result of the oscillation rate of change in S4 and the maximum value of 0 into another set of high and low deviation alarm modules to determine whether the fluctuation amplitude exceeds the set long time scale alarm values ​​h2 and l2. If it exceeds, output the product of the absolute value of the frequency fluctuation component and the proportional coefficient. If it does not exceed, output 0.

[0086] Step 7: Accumulate long-term oscillatory instability states. Add the output of Step 6 to the output of the previous calculation cycle switching module 4 algebraically to obtain the long-term oscillatory instability state quantity, thereby realizing the cumulative quantification of long-term frequent frequency out-of-range events.

[0087] Step 8: Calculate the long-time scale oscillation rate of change and perform state reset. The first-order inertial element obtained in step 7 through five series-connected inertial elements is deeply smoothed. The difference between the smoothed signal and the long-time scale oscillation rate of change is obtained. The maximum value of the difference between the smoothed signal and the value of the element is taken to limit the lower limit. It is determined whether the maximum value is less than a certain value. If it is, a short pulse signal is triggered to make the output of switching module 4 0, thus completing the clearing and reset of the long-time scale oscillation state. At the same time, the pulse signal serves as the global reset signal of the system. Otherwise, the output of switching module 4 is kept at the value of the previous cycle, and the long-term oscillation state continues to accumulate.

[0088] Step 9: Generate long-time scale primary frequency modulation attenuation coefficients. The signal obtained in Step 8 after taking the maximum value of 0 is smoothed through a first-order inertial element. The difference between the smoothed signal and a fixed value is calculated. The difference is multiplied by a proportional coefficient and then input into an exponential function. The minimum value of the exponential function output is taken by taking the minimum value of 1 to limit the upper limit, thus obtaining the long-time scale primary frequency modulation attenuation coefficients.

[0089] In this embodiment, steps 6 to 9 construct a long-term control loop that runs parallel to the short-term logic. The core difference lies in using a fifth-order series inertial element instead of a first-order inertial element to calculate the oscillation rate of change, significantly increasing the system's time constant. This enables the system to respond to frequent frequency oscillation events over several hours, thereby accurately identifying long-term operating conditions where the power plant is in isolated or weak grid conditions. This loop can maintain the primary frequency regulation action in a weakened state for a long period (approximately 5 hours) when the grid is chronically unstable, preventing frequent unit adjustments from exacerbating grid fluctuations.

[0090] Step 10: Calculate the overall primary frequency modulation weakening coefficient. Multiply the short-timescale weakening coefficient with the long-timescale weakening coefficient to obtain the overall primary frequency modulation weakening coefficient that integrates the oscillation characteristics of multiple timescales.

[0091] In this embodiment, in step 10, the total weakening coefficient is calculated by multiplying multiple time-scale coefficients, achieving the superposition of adjustment effects at different time scales. When only short-term low-frequency oscillations occur, the coefficient is close to 1, and the total weakening effect is mainly provided by [factor name missing]. When the power grid is in a weak connection state for a long time, the coefficient continuously decreases, and [factor name missing] and [factor name missing] work together to achieve deep weakening. When the power grid resumes full operation, [factor name missing] and [factor name missing] will flexibly recover to 1 within a few minutes and about one day, respectively, avoiding the impact of abrupt frequency regulation on the power grid. This control logic can add multiple time-scale k-functions to the two time scales (long and short) and multiply the outputs to obtain the weakening coefficient for managing different power grid frequency fluctuations.

[0092] Step 11: Adaptively switch the primary frequency regulation control input signal. Multiply the original grid frequency deviation signal by the total weakening coefficient to obtain the optimized frequency regulation deviation signal. Control the output state of the switching module 5 through the RS flip-flop: when the signal after taking the maximum value of 0 in step 4 is greater than a set value, the RS flip-flop is set, and the switching module 5 outputs the optimized frequency regulation deviation signal to the primary frequency regulation controller; when the global reset signal is triggered in step 8, the RS flip-flop is reset, and the switching module 5 outputs the original grid frequency deviation signal. At this point, one calculation cycle ends. This method cyclically executes the above steps to realize online monitoring of the grid status and adaptive adjustment of the primary frequency regulation function.

[0093] In this embodiment, in step 11, the RS trigger implements automatic switching control of the primary frequency modulation weakening function. When the short-timescale oscillation rate exceeds a set value, the weakening function is automatically activated; when the long-timescale oscillation rate is less than a set value and persists for a certain period of time, the weakening function is automatically reset and deactivated. This design avoids frequent function switching and ensures the stability of the control system. The switching module 5 also retains a manual switching interface, which allows manual deactivation of the weakening function and restoration of the original primary frequency modulation control logic in abnormal situations.

[0094] In summary, this method is based entirely on the existing control system of the power plant, without the need for additional hardware equipment. Deployment can be completed simply by modifying the control logic. The control parameters can be flexibly adjusted according to different power plant types such as thermal power, hydropower, wind power, and photovoltaic power, as well as the characteristics of the power grid.

[0095] Example 2:

[0096] In a real power plant setting, taking a 350MW thermal power unit as an example, when the grid frequency is selected as the data source for this method, the above parameters are set as follows:

[0097] ,

[0098] ,

[0099] ,

[0100] ,

[0101] ,

[0102] ,

[0103] ,

[0104] ,

[0105] ,

[0106] ,

[0107] ,

[0108] ,

[0109] ,

[0110] ,

[0111] ,

[0112] ,

[0113] ,

[0114] ,

[0115] .

[0116] If the grid frequency is replaced with the synchronous machine speed, the speed should be converted into the grid frequency based on the number of magnetic pole pairs, and then the control logic should be executed with the above parameters.

[0117] Example 3:

[0118] In an actual power plant site, let's take a 200MW hydropower unit as an example.

[0119] When the power grid frequency is selected as the data source for this method, the above parameters are set as follows:

[0120] ,

[0121] ,

[0122] ,

[0123] ,

[0124] ,

[0125] ,

[0126] ,

[0127] ,

[0128] ,

[0129] ,

[0130] ,

[0131] ,

[0132] ,

[0133] ,

[0134] ,

[0135] ,

[0136] ,

[0137] ,

[0138] .

[0139] If the grid frequency is replaced with the synchronous machine speed, the speed should be converted into the grid frequency based on the number of magnetic pole pairs, and then the control logic should be executed with the above parameters.

[0140] Example 4:

[0141] In a real power plant site, taking a 100MW photovoltaic or wind power plant with fast frequency response or primary frequency regulation as an example, and using the grid frequency as the data source for this method, the above parameters are set as follows:

[0142] ,

[0143] ,

[0144] ,

[0145] ,

[0146] ,

[0147] ,

[0148] ,

[0149] ,

[0150] ,

[0151] ,

[0152] ,

[0153] ,

[0154] ,

[0155] ,

[0156] ,

[0157] ,

[0158] ,

[0159] ,

[0160] .

[0161] The parameters for Embodiments 2, 3, and 4 above need to be set according to the on-site unit status, regional power grid frequency, inertia time, active power regulation response time, and other parameters. The parameters need to be determined after thermal engineering commissioning and electrical system tuning and verification to ensure that normal frequency regulation is not affected while possessing the characteristics described in the manual. The logic function and performance can be verified by simulating the frequency and power disturbances of oscillation.

[0162] In summary, this control method is used for switching between large-scale, isolated, and small-scale grid operation modes of the power grid. By extracting the frequency fluctuation components of the power grid, it constructs quantification and evaluation logic for oscillation states on both short-term and long-term time scales, automatically identifies low-frequency oscillations and isolated / small-scale grid operation conditions, adaptively generates a primary frequency regulation weakening coefficient, rapidly suppresses oscillation propagation when the power grid experiences small-cycle low-frequency oscillations, weakens the frequency regulation effect over a long period when the power grid is in a weak connection state for a long time, and flexibly restores full frequency regulation capability after the power grid resumes large-scale operation. This achieves precise matching between the power plant's frequency regulation characteristics and the power grid's operating state, improving the coordination level between the power grid and power sources and the stability of the power system operation.

[0163] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

[0164] Many other changes and modifications can be made without departing from the concept and scope of this invention. It should be understood that this invention is not limited to the specific embodiments, and the scope of this invention is defined by the appended claims.

Claims

1. A method for adaptive switching of multi-time-scale frequency control in a power plant, characterized in that, Includes the following steps: S1: Extract the power grid frequency fluctuation component; S2: Quantization of short-timescale frequency out-of-tolerance amplitude; S3: Accumulate short-timescale oscillatory instability states. Add the output of S2 to the output of the previous calculation cycle switching module 2 algebraically to obtain the short-timescale oscillatory instability state quantity, thereby realizing the cumulative quantification of continuous frequency out-of-tolerance events. S4: Calculate the short-timescale oscillation rate of change, set its lower limit by taking the maximum value of the result (0), and then perform a state reset. S5: Generate short-timescale primary frequency modulation weakening coefficients; S6: Quantizes the frequency out-of-tolerance amplitude over a long time scale; S7: Accumulate long-term oscillatory instability states. Add the output of S6 to the output of the previous calculation cycle switching module 4 algebraically to obtain the long-term oscillatory instability state quantity, thereby realizing the cumulative quantification of long-term frequent frequency out-of-range events. S8: Calculate the long-time scale oscillation rate of change, take the maximum value of it with 0 to limit the lower limit, and then perform a state reset; S9: Generate long-time scale primary frequency modulation attenuation coefficients; S10: Calculate the overall primary frequency modulation weakening coefficient, multiply the short-timescale weakening coefficient with the long-timescale weakening coefficient to obtain the overall primary frequency modulation weakening coefficient that integrates the oscillation characteristics of multiple timescales. S11: Adaptive switching of primary frequency modulation control input signal.

2. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S1 is as follows: S1-1: Real-time acquisition of power grid frequency signals; S1-2: The power grid frequency signal is filtered by passing it through three cascaded first-order inertial elements, respectively; S1-3: Subtract the filtered signal from the original grid frequency signal to obtain the pure fluctuation component of the grid frequency without DC offset.

3. The adaptive switching multi-timescale frequency control method for power plants according to claim 1 is characterized in that, The specific process of S2 is as follows: input the frequency fluctuation component in S1 into the high and low tolerance alarm module, determine whether the fluctuation amplitude exceeds the set short time scale alarm value, if it exceeds, output the product of the absolute value of the frequency fluctuation component and the proportional coefficient, if it does not exceed, output 0.

4. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S4 is as follows: S4-1: Smooth the first-order inertial element obtained in S3; S4-2: The rate of change of oscillation is obtained by subtracting the smoothed signal from the oscillation signal; S4-3: Take the maximum value of the result with 0 to limit the lower limit; S4-4: Determine whether the maximum value in S43 is less than the fixed value C; If so, a short pulse signal is triggered to make the output of switching module 2 0, completing the clearing and reset of the short-timescale oscillation state. Otherwise, the switching module 2 will continue to output the value of the previous cycle and continue to accumulate the oscillation state.

5. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S5 is as follows: S5-1: The signal from S4, after taking the maximum value of 0, is smoothed by passing it through a first-order inertial circuit; S5-2: Subtract the smoothed signal from the fixed value D; S5-3: Multiply the difference by the proportionality coefficient and then input it into the exponential function; S5-4: Minimize the output value of the exponential function with 1 to limit the upper limit, and obtain the short-timescale primary frequency modulation attenuation coefficient.

6. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S6 is as follows: input the result of the oscillation rate of change in S4 and the maximum value of 0 into another set of high and low error alarm modules to determine whether it exceeds the set long-term scale alarm value. If it exceeds, output the product of the absolute value of the frequency fluctuation component and the proportional coefficient. If it does not exceed, output 0.

7. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S8 is as follows: S8-1: Perform deep smoothing on the five cascaded first-order inertial elements obtained in S7. S8-2: The long-time scale oscillation rate of change is obtained by subtracting the deep-smoothed signal from the oscillatory signal. S8-3: Take the maximum value of the result with 0 to limit the lower limit; S8-4: Determine whether the maximum value in S83 is less than the fixed value E; If so, a short pulse signal is triggered to make the output of switching module 4 0, completing the clearing and reset of the long-term scale oscillation state. At the same time, this pulse signal serves as the global reset signal of the system. Otherwise, the switching module 4 will continue to output the value of the previous cycle, and the long-term oscillation state will continue to accumulate.

8. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific process of S9 is as follows: S9-1: The signal in S8 after taking the maximum value of 0 is smoothed by passing it through a first-order inertial element; S9-2: Subtract the smoothed signal from the fixed value F; S9-3: Multiply the difference by the proportionality coefficient and then input it into the exponential function; S9-4: The minimum value of the exponential function output value and 1 is taken to limit the upper limit, thus obtaining the long-time scale primary frequency modulation attenuation coefficient.

9. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The specific switching process in S11 is as follows: The original power grid frequency deviation signal is multiplied by the total weakening coefficient to obtain the optimized frequency modulation deviation signal. The output state of the switching module 5 is controlled by the RS flip-flop: when the signal after taking the maximum value of 0 in S4 is greater than the set value A, the RS flip-flop is set, and the switching module 5 outputs the optimized frequency modulation deviation signal to the primary frequency controller; when the global reset signal is triggered in S8, the RS flip-flop is reset, and the switching module 5 outputs the original power grid frequency deviation signal, thus ending one calculation cycle.

10. The adaptive switching multi-time-scale frequency control method for power plants according to claim 1, characterized in that, The total primary frequency modulation weakening coefficient in S10 is calculated by multiplying multiple time scale coefficients, thereby achieving the superposition of adjustment effects at different time scales. When only short-term low-frequency oscillations occur, the value is close to 1, and the total weakening effect is mainly provided by the factor; When the power grid is in a weak connection state for a long time, the continuous reduction and the combined effect achieve deep weakening; Once the power grid resumes full operation, both will flexibly recover to 1 within a short period of time to avoid the impact of sudden frequency regulation on the power grid.

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