A method for quantifying maximum wind power penetration rate under frequency stability constraint in low penetration scenarios

Abstract

The application discloses a kind of low frequency stability constraint scene under wind power maximum penetration rate quantification method, comprising, according to wind power grid-connected multi-machine power system, set for quantitatively calculating the frequency stability index of key frequency characteristics in low voltage ride through process;Determine the relationship between frequency stability index and wind power capacity proportion;Based on frequency stability index and the limit of lowest point and rate of change key frequency characteristics of system, determine common constraint, establish the optimization model of system wind power maximum penetration rate under quantitatively calculating low voltage ride through scene, by solving the optimization model obtains the wind power maximum of this scene satisfying frequency stability constraint.Based on frequency stability index and its critical value constraint, the upper limit of wind power penetration rate can be calculated;By relatively accurate model solution, wind power maximum penetration rate is obtained, avoids time domain simulation analysis;Wind power maximum penetration rate is evaluated for low voltage ride through scene, more suitable for future high proportion wind power system, more conducive to the development of wind turbine in power grid.

Description

Technical Field

[0001] This invention relates to the technical field of assessing the wind power absorption capacity of power systems, and particularly to a method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-voltage scenarios. Background Technology

[0002] As the penetration rate of new energy sources gradually increases and a large number of new energy units replace the original synchronous units in the system, the system's frequency regulation capability will decrease, and frequency instability may occur under power disturbances. Therefore, it is necessary to study the maximum penetration rate of new energy sources in the system under frequency stability constraints, i.e., the carrying capacity, to provide theoretical support for actual operation.

[0003] Studies on renewable energy carrying capacity from the perspective of frequency stability constraints typically use key frequency characteristics such as the minimum point and rate of change as indicators of frequency stability. Many studies have already quantitatively analyzed the frequency characteristics of systems subjected to active power step disturbances. However, in future high-proportion renewable energy power systems, compared to unit disconnection, it is more common for units to enter low-voltage transmission after a fault. For example, the "Technical Regulations for Wind Farm Connection to Power Systems Part 1: Onshore Wind Power" has clearly stipulated requirements for the low-voltage transmission capability of wind farms after a fault. Furthermore, because active power recovers slowly after a fault is cleared, the resulting active power disturbance is not the power step disturbance typically used in studies. If the impact of the recovery process on frequency is ignored, and indicators under step disturbances are still used to evaluate the system's frequency minimum point and rate of change, the evaluation results will inevitably be overly conservative. Using such results to constrain the renewable energy access capacity is detrimental to the further development of renewable energy in the system.

[0004] To further integrate new energy sources, most studies have qualitatively analyzed whether adding frequency regulation control to new energy sources can improve carrying capacity or whether improving the system's frequency regulation capability is necessary to improve carrying capacity. However, they lack quantitative analysis and calculation, which is not conducive to practical power system applications.

[0005] Therefore, it is necessary to study a quantitative calculation method for the maximum wind power penetration rate that takes into account the frequency stability index constraints of low voltage ride-through scenarios. Summary of the Invention

[0006] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0007] In view of the problems existing in the current methods for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios, this invention is proposed.

[0008] Therefore, the purpose of this invention is to provide a method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios.

[0009] To solve the above-mentioned technical problems, the present invention provides the following technical solution: Based on a multi-machine power system including wind power grid connection, a frequency stability index is set for quantitatively calculating key frequency characteristics during low voltage ride-through; The frequency stability index includes the lowest point. and rate of change ; Determine the relationship between the frequency stability index and the proportion of wind power capacity; and, Based on the frequency stability index and the system's restrictions on the key frequency characteristics of the minimum point and rate of change, common constraints are determined, and an optimization model is established to quantitatively calculate the maximum wind power penetration rate of the system under the low voltage ride-through scenario. By solving the optimization model, the maximum wind power that satisfies the frequency stability constraints under this scenario is obtained, and a two-layer cyclic optimization method is used to solve the wind power carrying capacity.

[0010] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in the low-penetration scenario described in this invention, the power generation equipment in the multi-machine power system with wind power grid connection includes synchronous machines and wind turbine generators, and the maximum active power disturbance in the system is caused by the low-penetration of the wind turbine generators. The active power disturbance includes power disturbance, and the power disturbance caused to the system during the low voltage ride-through process is as follows: in, At the moment the fault occurs, it can be set , This is the time to clear the fault. This refers to the power deficit caused by the low-frequency operation of the fan during a momentary malfunction. , This represents the active power output value of the wind turbine unit when it was operating normally before the fault. This refers to the recovery rate of active power fixed value of the wind turbine after the fault is cleared.

[0011] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios described in this invention, the key frequency includes the lowest point of the system frequency. and rate of change It can be expressed by the following formula: in, To evaluate the frequency stability performance at the lowest point of the system frequency during the low-voltage ride-through process, The frequency stability index of the rate of change during low voltage ride-through. It is a natural constant. The damping ratio of the system, It is an integer, typically 3. , and These are the system's total inertia coefficient, damping coefficient, and droop coefficient, which are related to the capacity, number, and type of power generation equipment involved in frequency regulation in the system. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the synchronous machine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the wind turbine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the equivalent equipment, respectively.

[0012] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in the low-voltage ride-through scenario described in this invention, the frequency stability indices for evaluating the system's lowest frequency point and rate of change during the low-voltage ride-through process are both related to wind power penetration rate. The functions are denoted as follows: , The formula is: in, , and and All of these are wind power capacity ratios The function; When the wind power penetration rate When the value increases, the frequency stability index under the same disturbance deteriorates; When the wind power penetration rate When it is too large, the system frequency reaches its lowest point. and the rate of change This will exceed the limits of the frequency stability index, and there is a risk of frequency instability.

[0013] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios described in this invention, wherein: and The critical value for frequency stability is given by the following formula: Where, Δ ω nadir,max and These represent the minimum allowable frequency point of the power grid and the maximum amplitude of the average rate of change, respectively.

[0014] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios described in this invention, the model for the maximum wind power penetration rate is as follows: in, and This is the critical value for frequency stability indicators.

[0015] As a preferred embodiment of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in the low-penetration scenario described in this invention, the dual-layer circulation includes an inner circulation and an outer circulation.

[0016] The inner loop includes solving the system strength index under any given percentage, while the outer loop is for solving the maximum wind power penetration rate.

[0017] As a preferred embodiment of the wind power maximum penetration rate quantification method under frequency stability constraints in low-penetration scenarios described in this invention, the operation steps of the inner and outer loops are as follows: Given the initial wind power penetration rate and power generation equipment parameters of the system, solve for the frequency stability index under this wind power penetration rate; Determine whether the indicators obtained from the above steps meet the constraints in the wind power maximum penetration rate assessment model. If they do, increase the wind power penetration rate and update the initial wind power penetration rate in step A1. To speed up the solution process, a sequential quadratic programming algorithm can be used to search for the next wind power capacity percentage. Repeat the above two steps until the wind power penetration rate is too high to meet the constraints in the evaluation model. At this point, the wind power penetration rate is the maximum wind power penetration rate that satisfies the system frequency stability constraint.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements a method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios.

[0019] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements a method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios.

[0020] The beneficial effects of the present invention are as follows: (1) The present invention establishes an evaluation model for the maximum penetration rate of wind power. Based on the frequency stability index and its critical value constraint, the upper limit of wind power penetration rate can be calculated. The maximum penetration rate of wind power can be obtained by solving the model more accurately, avoiding time-domain simulation analysis, and having a stronger theoretical basis.

[0021] (2) For low-penetration scenarios, the maximum penetration rate of wind power was evaluated, which is more suitable for future high-proportion wind power systems and is also more conducive to the further development of wind turbine units in the power grid. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is an overall flowchart of the method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios according to the present invention.

[0023] Figure 2 This is a flowchart of the optimization model for the maximum penetration rate described in the wind power maximum penetration rate quantification method under frequency stability constraints in the low-penetration scenario of the present invention.

[0024] Figure 3 This is a schematic diagram of 10 machines and 39 nodes in the simulation verification of Example 2.

[0025] Figure 4 This is a model diagram of the turbine governor system in the simulation verification of Example 2.

[0026] Figure 5 This is a diagram of the integrated inertia frequency modulation control structure of the wind turbine in the simulation verification of Example 2.

[0027] Figure 6 This is a comparison chart of the frequency waveform at the maximum wind power penetration rate obtained from the theoretical calculation in the simulation verification of Example 2, and the frequency waveform at other wind power penetration rates. Detailed Implementation

[0028] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0029] 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.

[0030] 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.

[0031] Secondly, the present invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of the present invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not according to the usual scale. Furthermore, the schematic diagrams are merely examples and should not limit the scope of protection of the present invention. In addition, actual fabrication should include three-dimensional spatial dimensions of length, width, and depth.

[0032] Example 1 Reference Figure 1 and Figure 2 A method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios includes: S1: Based on multi-unit power systems with wind power grid connection, frequency stability indices are set to quantitatively calculate key frequency characteristics during low-voltage ride-through. It should be noted that: In a multi-machine power system with wind power grid connection, the generating equipment includes synchronous machines and wind turbines; the largest active power disturbance in the system is caused by the low-voltage ride-through of the wind turbines.

[0033] Active disturbances include power disturbances. The power disturbance caused to the system during the low-voltage ride-through process can be expressed in the time domain as follows: in, At the moment the fault occurs, it can be set ; This is the time to clear the fault. This refers to the power deficit caused by the low-frequency operation of the fan during a momentary malfunction. , This represents the active power output value of the wind turbine unit when it was operating normally before the fault. This refers to the recovery rate of active power fixed value of the wind turbine after the fault is cleared.

[0034] The wind turbine grid-connected system contains n power generation devices, of which the first m are synchronous machines, numbered 1 to m, and the last n are wind turbines, numbered m+1 to n.

[0035] The active power disturbance in the frequency domain of wind turbine unit m+1 in the grid-connected system is denoted as Δ. P d_LVRT ( s It can be decomposed into a first-step perturbation Δ P d_s ( s )=- P 0 / s and Δ P d_r ( s )=Δ P d_LVRT ( s )+ P 0 / s sum.

[0036] Furthermore, the key frequencies include the lowest system frequency. and rate of change It can be expressed by the following formula: in, To evaluate the frequency stability performance at the lowest point of the system frequency during the low-voltage ride-through process, The frequency stability index of the rate of change during low voltage ride-through. It is a natural constant. The damping ratio of the system, It is an integer, typically 3. , and These are the system's total inertia coefficient, damping coefficient, and droop coefficient, which are related to the capacity, number, and type of power generation equipment involved in frequency regulation in the system. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the synchronous machine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the wind turbine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the equivalent equipment, respectively.

[0037] S2: Determine the relationship between frequency stability indicators and the proportion of wind power capacity. It should be noted that: , and This is related to the capacity, number, and type of power generation equipment involved in frequency regulation within the system. When the wind power penetration rate in the system changes, i.e., when wind turbines replace the generating capacity of synchronous generators, this will lead to... , and Changes occur, which in turn cause changes in the frequency stability indicators in the above steps.

[0038] Frequency stability metrics are related to wind power penetration rate The function is given by the formula: in, , and and All of these are wind power capacity ratios The function; When wind power penetration rate When the value increases, the frequency stability index deteriorates under the same disturbance. When wind power penetration rate When it is too large, the system frequency reaches its lowest point. and rate of change This will exceed the limits of the frequency stability index and pose a risk of frequency instability.

[0039] S3: Based on frequency stability indicators and system constraints on key frequency characteristics of minimum points and rates of change, common constraints are determined, and an optimization model is established to quantitatively calculate the maximum wind power penetration rate under low voltage ride-through scenarios. By solving this optimization model, the maximum wind power penetration rate satisfying the frequency stability constraints in this scenario is obtained, and a two-layer iterative optimization method is used to solve for the wind power carrying capacity. It should be noted that: The model for the maximum penetration rate of wind power is as follows: in, and This is the critical value for frequency stability indicators.

[0040] Further: in, and These represent the minimum allowable frequency point of the power grid and the maximum amplitude of the average rate of change, respectively.

[0041] The double-loop system includes an inner loop and an outer loop.

[0042] The inner cycle involves solving the system strength index for any given percentage, while the outer cycle involves solving the maximum wind power penetration rate.

[0043] The specific steps are as follows: A1: Given the initial wind power penetration rate and power generation equipment parameters of the system, solve for the frequency stability index under this wind power penetration rate.

[0044] A2: Determine whether the index obtained in step A1 meets the constraints in the wind power maximum penetration rate assessment model. If it does, increase the wind power penetration rate and update the initial wind power penetration rate in step A1.

[0045] To accelerate the solution process, a sequential quadratic programming algorithm can be used to search for the next wind power capacity percentage.

[0046] A3: Repeat steps A1-A2 until the wind power penetration rate is too high and does not meet the constraints in the evaluation model. At this point, the wind power penetration rate is the maximum wind power penetration rate that satisfies the system frequency stability constraint.

[0047] Example 2 This embodiment is the second embodiment of the present invention. Unlike the first embodiment, this embodiment provides a verification test of a method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios, and verifies and explains the technical effects used in this method.

[0048] The method of this invention is used to process power generation equipment in a multi-machine power system, including synchronous generators and wind turbines.

[0049] First, a frequency stability index is established to quantitatively calculate key frequency characteristics such as the system's lowest point and rate of change during low-voltage ride-through. Further analysis reveals that this index is a function of wind power capacity ratio. Finally, based on the index and system constraints on key frequency characteristics, an optimization model is established to quantitatively calculate the maximum wind power penetration rate under low-voltage ride-through scenarios. Solving this model yields the maximum wind power penetration rate that satisfies the frequency stability constraints.

[0050] Specific embodiments of the present invention are as follows: Build a 10-machine, 39-node power system in the Matlab / Simulink platform, such as Figure 3 As shown in the figure; G1~G10 represent power generation equipment, and the total system capacity is 10500MVA; the initial per-unit capacity values ​​of the wind turbine and synchronous generator set (base value 1000MVA, which is used as the base value to standardize all parameters in the example) are 1.5pu and 1p.u., respectively.

[0051] Among them, G5 is a wind turbine (equipped with low voltage ride-through control, with initial frequency regulation parameters set to...). , The remaining units are synchronous units, with an initial wind power penetration rate of 14%; the load is a constant power load; the line impedance and inductance are shown in Table 1; the system's given minimum frequency and critical stable value of average rate of change are -1Hz and -1.2Hz / s, respectively.

[0052] Table 1. Line parameter values ​​in simulation verification of the embodiment.

[0053] Frequency-active power transfer function of synchronous machine for In the formula, and These are the inertia and damping coefficient of the synchronous machine, respectively. The transfer function of the turbine speed control system (input is frequency) The output is mechanical power. ), model such Figure 4 As shown.

[0054] Wind turbines using the DFIG model, such as Figure 5 As shown, the frequency-active power transfer function in the electromechanical scale. for In the formula, and These are virtual inertia and damping coefficient, respectively. The time constant of the filter, The time constant of the low-pass filter. and These are the proportional and integral parameters of the PI controller in the phase-locked loop. and These are the proportional and integral parameters of the PI controller in the active power outer loop.

[0055] The parameter values ​​for the synchronous machine and the wind turbine are shown in Table 2.

[0056] Table 2. Parameter values ​​of the equipment in the simulation verification of the embodiment.

[0057] when A three-phase short-circuit fault occurred at time point 23, and the low voltage of the wind turbine G5 was applied. The fault was located in... After the cutoff, wind turbine G5 switched from low-frequency cutoff control to active power recovery control. The critical values ​​for the frequency stability index were calculated based on the given limits for the lowest frequency point and the average rate of change. , =40.

[0058] According to the method of this invention, the maximum wind power penetration rate in the system is calculated to be 43.82%; and in the simulation, the corresponding synchronizer is replaced according to this calculation result, and the resulting system frequency trajectory is as follows. Figure 6 As shown.

[0059] Depend on Figure 6 It can be seen that at this wind power penetration rate, the lowest frequency point is almost close to the critical value of -1Hz, indicating that the lowest frequency point of the system at this wind power penetration rate is just in the critical stable state.

[0060] If the wind power penetration rate is further increased to 52% and 61%, the system frequency trajectory will be as follows: Figure 6 As shown, when the wind power penetration rate reaches 52%, the system satisfies the frequency change rate constraint, but the lowest frequency point is greater than -1Hz, which does not satisfy the lowest frequency point constraint. When the wind power penetration rate reaches 61%, neither the frequency change rate nor the lowest frequency point satisfies the constraint conditions. This further illustrates that 43.82% is the maximum wind power penetration rate that satisfies the frequency stability index constraint.

[0061] To further illustrate the limitations of existing wind power carrying capacity analyses that only consider power step disturbances, the results obtained using existing methods will be compared with those calculated using the method proposed in this paper. Figure 6 As shown. Specifically: If existing wind power carrying capacity analysis methods are used, and the maximum power disturbance is considered as a step disturbance caused by wind turbine tripping or grid disconnection, the calculated wind power carrying capacity of the system is 18.11%. Simulations are performed under this wind power capacity percentage, and the system's frequency response curve is shown. Figure 6 As shown by the dotted line, at this point, both the system's lowest frequency and average rate of change are greater than the critical value, indicating that more wind turbines can be connected to the system. This means that using existing capacity assessment methods in the literature would lead to overly conservative results, which is not conducive to the further integration of new energy sources.

[0062] The examples of this invention demonstrate the effectiveness of the quantitative calculation method for maximum wind power penetration rate that takes into account the frequency stability index constraint of low voltage ride-through scenarios.

[0063] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios, characterized in that: include, Based on a multi-machine power system including wind power grid connection, frequency stability indicators are set for quantitatively calculating key frequency characteristics during low voltage ride-through. The frequency stability index includes the lowest point. and rate of change ; Determine the relationship between the frequency stability index and the proportion of wind power capacity; and, Based on the frequency stability index and the system's restrictions on the key frequency characteristics of the minimum point and rate of change, common constraints are determined, and an optimization model is established to quantitatively calculate the maximum wind power penetration rate of the system under the low voltage ride-through scenario. By solving the optimization model, the maximum wind power that meets the frequency stability constraints under this scenario is obtained, and a two-layer cyclic optimization method is used to solve the wind power carrying capacity. The power generation equipment in the multi-machine power system with wind power grid connection includes synchronous machines and wind turbines. The maximum active power disturbance in the system is caused by the low-voltage ride-through of the wind turbines. The active power disturbance includes power disturbance, and the power disturbance caused to the system during the low voltage ride-through process is as follows: in, At the moment the fault occurs, it can be set , This is the time to clear the fault. This refers to the power deficit caused by the fan's low-frequency operation during a momentary malfunction. , This represents the active power output value of the wind turbine unit when it was operating normally before the fault. The recovery rate of active power fixed value of the wind turbine after the fault is cleared; The frequency stability indices used to assess the system's lowest frequency point and rate of change during the low-voltage ride-through process are related to wind power penetration. The functions are denoted as follows: , The formula is: in, , and and All of these are wind power capacity ratios The function; When the wind power penetration rate When the value increases, the frequency stability index under the same disturbance deteriorates; When the wind power penetration rate When it is too large, the system frequency reaches its lowest point. and the rate of change This will exceed the limits of the frequency stability index, posing a risk of frequency instability; The dual-layer loop includes an inner loop and an outer loop; The inner cycle includes solving the system strength index under any proportion, and the outer cycle is to solve the maximum wind power penetration rate. The key frequency includes the lowest system frequency. and rate of change It can be expressed by the following formula: in, To evaluate the frequency stability performance at the lowest point of the system frequency during the low-voltage ride-through process, The frequency stability index of the rate of change during low voltage ride-through. It is a natural constant. The damping ratio of the system, It is an integer, with a value of 3. , and These are the system's total inertia coefficient, damping coefficient, and droop coefficient, which are related to the capacity, number, and type of power generation equipment involved in frequency regulation in the system. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the synchronous machine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the wind turbine, respectively. , and These are the inertia coefficient, damping coefficient, and droop coefficient of the equivalent equipment, respectively. The model for the maximum penetration rate of wind power is as follows: in, and This is the critical value for frequency stability indicators; The operation steps of the inner loop and the outer loop are as follows: Given the initial wind power penetration rate and power generation equipment parameters of the system, solve for the frequency stability index under this wind power penetration rate; Determine whether the indicators obtained from the above steps meet the constraints in the wind power maximum penetration rate assessment model. If they do, increase the wind power penetration rate and update the initial wind power penetration rate in step A1. To speed up the solution process, a sequential quadratic programming algorithm can be used to search for the next wind power capacity percentage. Repeat the above two steps until the wind power penetration rate is too high to meet the constraints in the evaluation model. At this point, the wind power penetration rate is the maximum wind power penetration rate that satisfies the system frequency stability constraint.

2. The method for quantifying the maximum wind power penetration rate under frequency stability constraints in low-penetration scenarios as described in claim 1, characterized in that: The and The critical value for frequency stability is given by the following formula: in, and These represent the minimum allowable frequency point of the power grid and the maximum amplitude of the average rate of change, respectively.

3. A computer device, comprising a memory and a processor, wherein the memory stores a computer program. Its features are, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 2.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 2.

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