Self-adaptive adjustment method for network construction type energy storage parameters based on buffer function and damping switching

Abstract

The invention relates to the technical field of new energy storage, and discloses a network construction type energy storage parameter adaptive adjustment method based on a buffer function and damping switching, and the method comprises the steps: firstly, employing the buffer function in inertia adjustment to increase the adjustment smoothness of a system; secondly, a steady-state / transient-state damping switching link is introduced into damping adjustment, and active output steady-state errors during frequency reduction are reduced; and finally, introducing a correction amount for inertia damping through fuzzy control, and carrying out stability analysis on the proposed method. The method is simple to control, has a better effect of improving small interference stability and power response dynamic performance compared with a traditional method, and has a very high 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] In order to cope with the growing power demand and environmental pressure, the "double high" characteristics of the new power system with a high proportion of new energy and a high proportion of power electronic equipment are becoming more and more obvious. Among them, the new energy grid connection generally adopts grid-following control, which lacks inertia support and frequency control capabilities, weakens the system AC synchronization mechanism, reduces the small signal anti-interference ability of the weak power grid, and makes the system more prone to instability.

[0003] The grid-forming control technology directly controls the output voltage amplitude and phase by simulating the rotor motion equation of the synchronous generator set, presenting voltage source control and self-synchronous grid characteristics to the outside world. Compared with the grid-following control, it has stronger inertial support capability and can provide frequency support for low-inertia grids.

[0004] However, the network control should reasonably increase the system inertia and damping to enhance the system's small disturbance stability. Excessive damping will lead to slow response speed, and excessive inertia will increase active overshoot. Therefore, how to adjust the inertia damping parameters to optimize power dynamic performance and improve the system's small disturbance stability has become a technical challenge faced by the network control. Summary of the invention

[0005] The purpose of this application is to provide a method for adaptively adjusting 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 great 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] Conduct stability analysis on the oscillation process of the system output active power and frequency.

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

[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. The upper and lower limits of the function value and the smoothness of the function are fixed to make the inertia adaptive adjustment 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 angular frequency change; 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 the active power is 0, 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 grid-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 of the VSG power angle characteristic curve, the power changes from the first power value P 0 Sudden change to the second power value P 1 Afterwards, the system undergoes four stages of decay oscillation, namely the first stage, the second stage, the third stage and the fourth stage;

[0026] For the first stage, increase inertia and damping to reduce 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 of the present invention are reflected in: alleviating the problem that the inertia may change too quickly or too much during the adaptive adjustment process; reducing the active output steady-state error when the system frequency decreases; the inertia damping adaptive adjustment strategy improves the system frequency stability and power dynamic regulation performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of the principle of adaptive inertia adjustment 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 A system pole distribution diagram under the adaptive change of inertia damping provided in an embodiment of the present application; wherein, (a) is a pole distribution diagram under the adaptive change of inertia; (b) is a pole distribution diagram under the adaptive change of damping;

[0036] Figure 5 A comparison diagram of power-frequency characteristics of the parameter adaptive adjustment method under different working conditions provided in the embodiment of the present application; wherein, (a) is a comparison of frequency characteristics under changes in scheduling instructions; (b) is a comparison of power characteristics under changes in scheduling instructions; (c) is a comparison of frequency characteristics under a decrease in system frequency; (d) is a 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, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways 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 without conflict.

[0038] The specific implementation of the present application is further described in detail below in conjunction with the 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: J 0 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 angular velocity change rate amplitude change threshold.

[0043] like Figure 1 As shown, it is a schematic diagram of the inertia adaptive adjustment principle provided by the embodiment of the present application. In step 1, the specific implementation process is:

[0044] Adaptive regulation is achieved by refining the inertia interval division; the 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 damping adjustment. The calculation process is expressed as:

[0046]

[0047] Where: D 0 is the damping rating; K d1 , K d2 , K d3 is the adjustment coefficient of virtual damping; T d1 、T d2 、Td3 is the change threshold.

[0048] like Figure 2 The schematic diagram of the damping adaptive adjustment principle of the embodiment of the present application is shown in FIG. 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 value T d1 Steady-state damping is used when the first threshold T d1 With the second threshold T d2 When between, the damping increases linearly; when exceeding T d2 Switch to transient damping to improve active power tracking accuracy.

[0049] Specifically, a damping strategy is set according to the angular frequency change; wherein the damping strategy includes: when the angular frequency change 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 the exponential function is used to slowly adapt to the change; d1 and the second threshold T d2 When the angular frequency change exceeds the second threshold value T, steady-state damping is used and the damping is increased linearly; when the angular frequency change exceeds the second threshold value T d2 When the active power is 0, 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 is a schematic diagram of the fuzzy control correction inertia damping principle of the embodiment of the present application. The specific implementation process of step 3 is: e and the rate of change K ec The input is transformed into fuzzy variables by fuzzy processing and membership function, and then defuzzified by fuzzy reasoning and centroid method 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, it is a system pole distribution diagram under the adaptive change of inertia damping provided in the embodiment of the present application, and the specific implementation process of step 4 is:

[0056] During the transition of the VSG power angle characteristic curve, the power changes from P 0 Mutation to P 1 After that, the system undergoes four stages of decay 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 angular velocity change rate; for the fourth stage, the inertia is reduced and the damping is increased to accelerate the angular frequency recovery. Adaptive adjustment ensures that the system characteristic roots remain in the left half plane to ensure asymptotic stability.

[0057] The grid-type energy storage parameter adaptive adjustment method 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 devices in the front stage of the grid-forming inverter.

[0058] like Figure 5 As shown in (a), after adopting the photovoltaic energy storage VSG adaptive adjustment method, the frequency fluctuation when the dispatching 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 dispatching 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 dispatching 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 7kW in conventional VSG adaptive control, verifying the effectiveness of photovoltaic energy storage and parameter coordinated control; 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 7kW in conventional VSG control, greatly 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 3.62s in conventional VSG control, and the dynamic response performance is further improved.

[0060] like Figure 5 As 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 the conventional VSG adaptive control is 5.7kW higher than the primary frequency regulation increment, and the active power increase after adopting the VSG adaptive adjustment method proposed in this paper gradually equals the primary frequency regulation increment, which is consistent with the above analysis results, mainly because when the system frequency decreases, the damping coefficient switches to transient damping, which reduces the active 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 belong to the scope of the present application, and the scope of patent protection of the present application shall be limited 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: Use buffer function in inertia adjustment to increase the smoothness of system adjustment; Introducing steady-state and / or transient damping switching links in damping adjustment; Introducing corrections for inertia and damping through fuzzy control; Conduct 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 the 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. The upper and lower limits of the function value and the smoothness of the function are fixed to make the inertia adaptive adjustment 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: Introduce steady-state / transient damping switching link in damping adjustment, including: The damping strategy is set according to the angular frequency change; 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 value T d2 When the active power is 0, 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 attenuation oscillation, namely the first stage, the second stage, the third stage and the fourth stage; For the first stage, increase inertia and damping to reduce 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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