Adaptive adjustment method of grid-type energy storage parameters based on buffer function and damping switching

Abstract

The present application relates to the field of new energy storage technology, and discloses a method for adaptively adjusting parameters of a grid-type energy storage system based on a buffer function and damping switching. The method first uses a buffer function in the inertia adjustment to increase the adjustment smoothness of the system. Secondly, a steady-state / transient damping switching link is introduced in the damping adjustment to reduce the steady-state error of the active output when the frequency drops. Finally, a correction amount is introduced for the inertia damping through fuzzy control and a stability analysis of the proposed method is performed. The above method is simple to control and is more effective than traditional methods in improving small-disturbance stability and power response dynamic performance, and has strong practical value.

Description

Technical Field

[0001] The present application relates to the field of new energy storage technology, and in particular to a method for adaptively adjusting parameters of a grid-type energy storage system based on a buffer function and damping switching. Background Art

[0002] To address growing electricity demand and environmental pressures, new power systems are increasingly characterized by a high proportion of renewable energy and power electronics. Renewable energy grid-connected systems generally employ grid-following control, which lacks inertia support and frequency control capabilities. This weakens the system's AC synchronization mechanism, reduces the weak grid's ability to resist small-signal interference, and makes the system more susceptible to instability.

[0003] Grid-forming control technology simulates the rotor motion equations of synchronous generator sets to directly control their output voltage amplitude and phase, presenting voltage source control and self-synchronizing grid characteristics. Compared to grid-following control, it has stronger inertia support capabilities and can provide frequency support for low-inertia grids.

[0004] However, networked control requires a reasonable increase in system inertia and damping to enhance small-disturbance stability. Excessive damping can lead to slow response, while excessive inertia can increase active power overshoot. Therefore, adjusting inertia damping parameters to optimize power dynamics and improve small-disturbance stability presents a technical challenge for networked control. Summary of the Invention

[0005] The purpose of this application is to provide a method for adaptively adjusting the parameters of a grid-type energy storage device based on a buffer function and damping switching. This method can adaptively adjust the inertia and damping parameters of a grid-type energy storage converter according to working conditions, and has strong practical value.

[0006] In order to achieve the above purpose, the technical solutions adopted are as follows:

[0007] The present invention provides a method for adaptively adjusting parameters of a grid-type energy storage system based on a buffer function and damping switching, the method comprising:

[0008] Use buffer function in inertia adjustment to increase the smoothness of system adjustment;

[0009] Introducing steady-state and / or transient damping switching links in damping adjustment;

[0010] Introducing corrections for inertia and damping through fuzzy control;

[0011] Perform stability analysis on the oscillation process of the system output active power and frequency.

[0012] Preferably, in the above-mentioned adaptive adjustment method of network-type energy storage parameters based on buffer function and damping switching, using the buffer function in inertia adjustment to increase the adjustment smoothness of the system includes:

[0013] Divide the inertia into intervals so that the divided inertia intervals can be adaptively adjusted according to different situations;

[0014] An activation function is introduced as a buffer function in each inertia interval to increase the nonlinearity of the system. By fixing the upper and lower limits of the function value and the smoothness characteristics of the function, the inertia adaptive adjustment is made smooth and stable.

[0015] Preferably, in the above-mentioned adaptive adjustment method of grid-type energy storage parameters based on buffer function and damping switching, a steady-state / transient damping switching link is introduced in the damping adjustment, including:

[0016] The damping strategy is set according to the change in angular frequency; wherein the damping strategy includes:

[0017] When the angular frequency change is lower than the first threshold T d1 When , steady-state damping is used and the adaptive change is slow through the exponential function;

[0018] When the angular frequency change is within the first threshold T d1 and the second threshold T d2 When the value is between , steady-state damping is used and the damping is increased linearly;

[0019] When the angular frequency variation exceeds the second threshold value T d2 When , it switches to transient damping to improve the steady-state error, thereby improving the active power tracking accuracy.

[0020] Preferably, in the above-mentioned adaptive adjustment method of network-type energy storage parameters based on buffer function and damping switching, a correction amount is introduced into inertia and damping through fuzzy control, including:

[0021] Select the frequency change K e and frequency change rate K ec As the input variable of the fuzzy self-adaptive link, the input variable is fuzzified and the corresponding fuzzy subset is set;

[0022] The input and output variables are transformed into fuzzy variables using triangular and Gaussian membership functions, and the results are obtained through fuzzy reasoning;

[0023] The results are defuzzified by the center of gravity method to obtain the inertia and damping values ​​of the system.

[0024] Preferably, in the above-mentioned grid-type energy storage parameter adaptive adjustment method based on buffer function and damping switching, the stability analysis of the oscillation process of the system output active power and frequency includes:

[0025] During the transition process of the VSG power angle characteristic curve, after the power suddenly changes from the first power value P0 to the second power value P1, the system undergoes four stages of attenuated oscillation, namely the first stage, the second stage, the third stage and the fourth stage;

[0026] For the first stage, the inertia and damping are increased to reduce the angular frequency deviation;

[0027] For the second stage, the damping is increased and the inertia is reduced to restore the angular velocity;

[0028] For the third stage, the inertia and damping are adaptively increased to reduce the rate of change of angular velocity;

[0029] For the fourth stage, the inertia is reduced and the damping is increased so that the acceleration angular frequency is restored.

[0030] The beneficial effects of this application are:

[0031] The effects of the grid-type energy storage parameter adaptive adjustment method based on buffer function and damping switching in the present invention are reflected in: alleviating the problem of excessively fast or excessive changes in inertia during adaptive adjustment; reducing the active output steady-state error when the system frequency decreases; and improving the system frequency stability and power dynamic regulation performance through the inertia damping adaptive adjustment strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of the inertia adaptive adjustment principle provided in an embodiment of the present application;

[0033] Figure 2 A schematic diagram of the damping adaptive adjustment principle provided in an embodiment of the present application;

[0034] Figure 3 A schematic diagram of the fuzzy control corrected inertia damping principle provided in an embodiment of the present application;

[0035] Figure 4 The pole distribution diagram of the system under the adaptive change of inertia and damping provided in the embodiment of the present application; wherein, (a) is the pole distribution diagram under the adaptive change of inertia; (b) is the pole distribution diagram under the adaptive change of damping;

[0036] Figure 5 A comparison diagram of the power-frequency characteristics of the parameter adaptive adjustment method under different working conditions provided in the embodiment of the present application; among them, (a) comparison of frequency characteristics under changes in scheduling instructions; (b) comparison of power characteristics under changes in scheduling instructions; (c) comparison of frequency characteristics under a decrease in system frequency; (d) comparison of power characteristics under a decrease in system frequency. DETAILED DESCRIPTION

[0037] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0038] The specific implementation of the present application is further described in detail below with reference to the accompanying drawings and examples.

[0039] An embodiment of the present application provides a method for adaptively adjusting parameters of a grid-type energy storage system based on a buffer function and damping switching, the method comprising the following steps 1 to 4.

[0040] Step 1: Use the buffer function in inertia adjustment to increase the smoothness of the system adjustment. The buffer function is expressed as:

[0041]

[0042] Where: J0 is the rated value of inertia; J A is the adjusted inertia value; Δω is the angular velocity change; dω / dt is the angular velocity change rate; K j1 , K j2 , K j3 is the adjustment coefficient of virtual inertia; T j is the threshold value of the angular velocity change rate amplitude.

[0043] like Figure 1 The figure shows the principle diagram of inertia adaptive adjustment provided by the embodiment of the present application. In step 1, the specific implementation process is as follows:

[0044] Adaptive regulation is achieved by refining the inertia interval division; an activation function is introduced to increase nonlinearity, and the upper and lower limits of the function value are fixed and smoothed to avoid excessive inertia changes and improve regulation stability.

[0045] Step 2: Introduce steady-state and / or transient damping switching links in the damping adjustment. The calculation process is expressed as:

[0046]

[0047] Where: D0 is the damping rating; K d1 , K d2 , K d3 is the adjustment coefficient of virtual damping; T d1 、T d2 、T d3 is the change threshold.

[0048] like Figure 2 The following is a schematic diagram of the damping adaptive adjustment principle of the embodiment of the present application. The specific implementation process of step 2 is: setting the damping strategy according to the angular frequency change: the change is lower than the first threshold T d1 Steady-state damping is used when the first threshold T d1 With the second threshold T d2 Increase damping linearly between T d2 Switch to transient damping to improve active power tracking accuracy.

[0049] Specifically, the damping strategy is set according to the angular frequency variation; wherein the damping strategy includes: when the angular frequency variation is lower than the first threshold value T d1 When the angular frequency changes within the first threshold T, steady-state damping is used and adaptive changes are made slowly through the exponential function. d1 and the second threshold T d2 When the angular frequency variation exceeds the second threshold value T, steady-state damping is used and the damping is increased linearly; when the angular frequency variation exceeds the second threshold value T d2 When , it switches to transient damping to improve the steady-state error, thereby improving the active power tracking accuracy.

[0050] Step 3: Introduce corrections for inertia and damping through fuzzy control. The calculation process is expressed as:

[0051]

[0052] Where: J A 、D A are the inertia and damping adaptive terms respectively; ΔJ and ΔD are the fuzzy adjustment quantities of inertia and damping respectively; J Σ 、D Σ It is obtained by superimposing the adaptive terms of inertia and damping and the fuzzy variation.

[0053] like Figure 3 The figure shows the principle diagram of fuzzy control correction inertia damping in this embodiment of the present application. The specific implementation process of step 3 is: take the frequency change K e and the rate of change K ec As input, fuzzy processing and membership function are used to transform it into fuzzy variables, and fuzzy reasoning and centroid method are used to defuzzify it to obtain the system inertia and damping values.

[0054] Step 4: Perform stability analysis on the oscillation process of the system output active power and frequency.

[0055] like Figure 4 As shown in FIG, the pole distribution diagram of the system under the adaptive change of inertia damping provided in the embodiment of the present application is shown. The specific implementation process of step 4 is:

[0056] During the transition of the VSG power-angle characteristic curve, after the power suddenly changes from P0 to P1, the system undergoes four stages of attenuated oscillation: the first, second, third, and fourth stages. In the first stage, inertia and damping are increased to reduce angular frequency deviation; in the second stage, damping is increased and inertia is reduced to restore angular velocity; in the third stage, inertia and damping are adaptively increased to reduce the rate of change of angular velocity; in the fourth stage, inertia is reduced and damping is increased to restore the acceleration angular frequency. Adaptive adjustment ensures that the system's characteristic roots remain in the left half plane, guaranteeing asymptotic stability.

[0057] The adaptive adjustment method of grid-type energy storage parameters based on buffer function and damping switching provided in the embodiment of the present application is compared with the traditional virtual synchronous machine control method. The results are as follows: Figure 5 shown. Figure 5 In the conventional VSG control, the inverter configuration used is based on a DC voltage source as the front stage, while the photovoltaic energy storage VSG control integrates photovoltaic and energy storage equipment in the front stage of the grid-forming inverter.

[0058] like Figure 5 As shown in (a), after adopting the photovoltaic storage VSG adaptive adjustment method, the frequency fluctuation when the dispatch instruction changes is 0.1Hz, which is 23% less than the 0.13Hz of conventional VSG adaptive control, verifying the effectiveness of the coordinated control of photovoltaic energy storage and parameters; after adopting the inertia damping coordinated adaptive adjustment method proposed in this paper, the frequency fluctuation when the dispatch instruction changes is 0.09Hz, which is 30% less than the 0.13Hz of conventional VSG adaptive control, further reducing the frequency fluctuation amplitude; after adopting the VSG adaptive adjustment method proposed in this paper, the frequency adjustment time when the dispatch instruction changes is 3.2s, which is 14% faster than the 3.7s of conventional VSG control, further accelerating the dynamic response performance.

[0059] like Figure 5 As shown in (b), after adopting the photovoltaic energy storage VSG control, the power overshoot when the dispatch instruction changes is 4kW, which is 42.8% less than the 7kW under conventional VSG adaptive control, verifying the effectiveness of the coordinated control of photovoltaic energy storage and parameters; after adopting the adaptive adjustment method proposed in this paper, the active power overshoot when the dispatch instruction changes is 0.8kW, which is 88.5% less than the 7kW under conventional VSG control, significantly reducing the active power overshoot; after adopting the adaptive adjustment method proposed in this paper, the active power adjustment time when the dispatch instruction changes is 3.22s, which is 11% higher than the 3.62s under conventional VSG control, and the dynamic response performance is further improved.

[0060] like Figure 5As shown in (c) and (d), after adopting the photovoltaic energy storage VSG adaptive adjustment method, the frequency fluctuation amplitude and adjustment time when the system frequency decreases are further improved compared with the conventional VSG adaptive control under the DC voltage source; the active power increase using conventional VSG adaptive control increases by 5.7kW compared with the primary frequency regulation increment. After adopting the VSG adaptive adjustment method proposed in this paper, the active power increase gradually equals the primary frequency regulation increment, which is consistent with the above analysis results. This is mainly because the damping coefficient switches to transient damping when the system frequency decreases, reducing the active power output steady-state error.

[0061] In summary, when the active power command increases and the system frequency decreases, the power frequency overshoot and adjustment time are further improved by adopting the photovoltaic energy storage inertia damping coordinated adaptive adjustment method proposed in this paper, thus verifying the effectiveness of the control strategy proposed in this paper.

[0062] The above implementation modes are only used to illustrate the present application and are not intended to limit the present application. Ordinary technicians in the relevant technical field may make various changes and modifications without departing from the spirit and scope of the present application. Therefore, all equivalent technical solutions also fall within the scope of the present application, and the scope of patent protection of the present application shall be defined by the claims.

Claims

1. A method for adaptively adjusting parameters of grid-type energy storage based on buffer function and damping switching, characterized in that: The method comprises: A buffer function is used in inertia adjustment to increase the smoothness of the system adjustment; wherein the buffer function is expressed as: Where: J0 is the rated value of inertia; J A is the adjusted inertia value; Δω is the angular velocity change; dω / dt is the angular velocity change rate; K j1 , K j2 , K j3 is the adjustment coefficient of virtual inertia; T j is the threshold value of the amplitude change of the angular velocity change rate; Introducing steady-state and / or transient damping switching links into the damping adjustment, the calculation process is expressed as: Where: D0 is the damping rating; K d1 , K d2 , K d3 is the adjustment coefficient of virtual damping; T d1 、T d2 、T d3 is the change threshold; D A is the damping adaptive term; By introducing correction values ​​for inertia and damping through fuzzy control, the calculation process can be expressed as: Where: ΔJ and ΔD are the fuzzy adjustment values ​​of inertia and damping respectively; Perform stability analysis on the oscillation process of the system output active power and frequency.

2. The method for adaptively adjusting parameters of grid-type energy storage based on buffer function and damping switching according to claim 1, characterized in that: Use buffer functions in inertia adjustment to increase the smoothness of system adjustment, including: Divide the inertia into intervals so that the divided inertia intervals can be adaptively adjusted according to different situations; An activation function is introduced as a buffer function in each inertia interval to increase the nonlinearity of the system. By fixing the upper and lower limits of the function value and the function smoothness characteristics, the inertia adaptive adjustment is made smooth and stable.

3. The method for adaptively adjusting parameters of grid-type energy storage based on buffer function and damping switching according to claim 1, characterized in that: Introducing steady-state / transient damping switching link in damping adjustment, including: The damping strategy is set according to the change in angular frequency; wherein the damping strategy includes: When the angular frequency change is lower than the first threshold T d1 When , steady-state damping is used and the adaptive change is slow through the exponential function; When the angular frequency change is within the first threshold T d1 and the second threshold T d2 When the value is between , steady-state damping is used and the damping is increased linearly; When the angular frequency variation exceeds the second threshold T d2 When , it switches to transient damping to improve the steady-state error, thereby improving the active power tracking accuracy.

4. The method for adaptively adjusting parameters of grid-type energy storage based on buffer function and damping switching according to claim 1, characterized in that: Introducing corrections for inertia and damping through fuzzy control, including: Select the frequency change K e and frequency change rate K ec As the input variable of the fuzzy self-adaptive link, the input variable is fuzzified and the corresponding fuzzy subset is set; The input and output variables are transformed into fuzzy variables using triangular and Gaussian membership functions, and the results are obtained through fuzzy reasoning; The results are defuzzified by the center of gravity method to obtain the inertia and damping values ​​of the system.

5. The method for adaptively adjusting parameters of grid-type energy storage based on buffer function and damping switching according to claim 1, characterized in that: Perform stability analysis on the oscillation process of the system output active power and frequency, including: During the transition process of the VSG power angle characteristic curve, after the power suddenly changes from the first power value P0 to the second power value P1, the system undergoes four stages of attenuated oscillation, namely the first stage, the second stage, the third stage and the fourth stage; For the first stage, the inertia and damping are increased to reduce the angular frequency deviation; For the second stage, the damping is increased and the inertia is reduced to restore the angular velocity; For the third stage, the inertia and damping are adaptively increased to reduce the rate of change of angular velocity; For the fourth stage, the inertia is reduced and the damping is increased so that the acceleration angular frequency is restored.

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