Virtual impedance self-adaptive control method of network construction type energy storage converter

Abstract

The invention relates to the technical field of virtual impedance self-adaptive control of energy storage converters, in particular to a virtual impedance self-adaptive control method of a grid-forming type energy storage converter, which comprises the following steps of: acquiring three-phase voltage and current of a grid-connected point in real time; performing phase-locked loop processing and coordinate transformation to obtain a d-axis voltage, a q-axis voltage and a current under a synchronous rotating coordinate system; calculating instantaneous power, and obtaining active power and reactive power; virtual resistance and virtual inductance are calculated according to power fluctuation through an adaptive algorithm; the virtual impedance equation generates a voltage drop compensation signal; and superposing the compensation signal and the reference voltage to generate a new modulation wave, and inputting the new modulation wave into the pulse width modulation module to realize power oscillation suppression and stable operation. According to the method, the problems between damping enhancement and loss reduction in network construction type control are solved, the dynamic and steady-state performance of the converter is improved, and a key technical support is provided for large-scale and high-reliability application of the network construction type energy storage converter in a novel power system.

Description

Technical Field

[0001] This invention relates to the field of virtual impedance adaptive control technology for energy storage converters, specifically a virtual impedance adaptive control method for grid-type energy storage converters. Background Art

[0002] The penetration rate of renewable energy sources, such as wind and solar power, in the power system is continuously increasing. However, the inherent intermittency and volatility of these energy sources pose significant challenges to the stable operation of the power grid. Grid-connected converter technology, capable of autonomously constructing grid voltage and frequency, provides the necessary inertia and damping support for high-proportion renewable energy grids, and is becoming a key technology for building new power systems.

[0003] The combination of energy storage systems and grid-based control forms a grid-based energy storage converter, which not only smooths power fluctuations but also actively supports the power grid, earning it the reputation of a "multi-functional intelligent node" for the grid. In grid-based control, virtual synchronous generators and their derivative technologies are one of the mainstream solutions. By simulating the rotor motion equations and electromechanical transient characteristics of a synchronous generator, the converter possesses inertial response and primary frequency and voltage regulation functions.

[0004] However, when grid-connected converters operate in weak or high-impedance-ratio grid environments, their output impedance characteristics differ significantly from those of traditional synchronous generators. This makes them prone to complex power oscillations with the grid impedance or other converters, which can lead to system instability in severe cases. To enhance system damping and suppress power oscillations, the introduction of virtual impedance control has become an effective solution. Virtual impedance, by introducing an additional impedance element into the control loop, can reshape the converter's output impedance characteristics, thereby effectively attenuating power coupling and low-frequency oscillations.

[0005] However, traditional fixed-parameter virtual impedance control methods have significant limitations: First, to ensure stability under the worst operating conditions, fixed-parameter virtual impedance typically requires a large value, which can cause unnecessary voltage drops and power losses during steady-state operation, reducing system efficiency. Second, the operating conditions of the power grid are complex and variable, and fixed impedance parameters cannot provide optimal damping effects under all conditions. When the system operating point or grid strength changes, fixed virtual parameters may fail to provide sufficient damping and may even trigger new oscillation problems. No solutions have yet been proposed to address these technical issues. Summary of the Invention

[0006] To address the problems in related technologies, this invention proposes a virtual impedance adaptive control method for grid-type energy storage converters to overcome the aforementioned technical issues in existing related technologies. The purpose of this invention is to solve the problem of balancing enhanced damping and reduced losses in grid-type control, improve the dynamic and steady-state performance of the converter, and provide key technical support for the large-scale, high-reliability application of grid-type energy storage converters in new power systems.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a virtual impedance adaptive control method for grid-type energy storage converters, comprising the following steps:

[0008] Step S01: Real-time acquisition of three-phase voltage and three-phase current at the grid connection point of the grid-connected energy storage converter;

[0009] Step S02: Perform phase-locked loop processing and coordinate transformation on the three-phase voltage and three-phase current to obtain the d-axis voltage, q-axis voltage, d-axis current and q-axis current in the synchronous rotating coordinate system;

[0010] Step S03: Calculate the instantaneous power at the grid connection point based on the d-axis voltage, q-axis voltage, d-axis current, and q-axis current to obtain the active power and reactive power.

[0011] Step S04: Based on the fluctuations in active and reactive power, calculate the required virtual resistance and virtual inductance values ​​in real time using an adaptive algorithm.

[0012] Step S05: Substitute the calculated virtual resistance and virtual inductance values ​​into the virtual impedance equation to generate a virtual impedance voltage drop compensation signal.

[0013] Step S06: The virtual impedance voltage drop compensation signal is superimposed with the reference voltage signal output by the front-end voltage loop to generate a new modulation wave signal, which is then input to the pulse width modulation module to drive the power switching device of the grid-type energy storage converter, thereby achieving power oscillation suppression and stable operation at the grid connection point.

[0014] Preferably, in step S04, the adaptive algorithm specifically involves: establishing a fuzzy logic controller or proportional-integral controller with the power oscillation amplitude or frequency change rate as input and the virtual impedance value as output; and dynamically adjusting the virtual resistance and virtual inductance values ​​through the controller so that when the power oscillation intensifies, the virtual impedance value is automatically increased to enhance damping; and when the system tends to stabilize, the virtual impedance value is automatically decreased to reduce steady-state losses.

[0015] Preferably, in step S04, the calculation formulas for the virtual resistance value and the virtual inductance value are as follows:

[0016] R_v=R_0+K_p*ΔP+K_i*∫ΔP dt

[0017] L_v=L_0+K_p'*ΔQ+K_i'*∫ΔQ dt;

[0018] In the formula, R_v is the virtual resistance value, L_v is the virtual inductance value, R_0 and L_0 are the initial virtual impedance reference values, K_p, Ki, K_p', and Ki' are adaptive control coefficients, and ΔP and ΔQ are the deviations of active power and reactive power from their given values ​​or sliding average values, respectively.

[0019] Preferably, in step S05, the virtual impedance equation is:

[0020] [ΔU_d;ΔU_q]=-[R_v,-ω*L_v;ω*L_v,R_v]*[I_d;I_q]

[0021] In the formula, ΔU_d and ΔU_q are the virtual impedance voltage drop compensation signals of the d-axis and q-axis, respectively, and ω is the grid angular frequency.

[0022] Preferably, in step S03, the instantaneous power is calculated using a method based on instantaneous power theory, and the formula is as follows:

[0023] P = 1.5 * (U_d * I_d + U_q * I_q)

[0024] Q = 1.5 * (U_q * I_d - U_d * I_q)

[0025] In the formula, P represents active power and Q represents reactive power.

[0026] Preferably, step S04 further includes limiting the calculated virtual resistance and virtual inductance values.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) The present invention is a virtual impedance adaptive control method for grid-type energy storage converters. By monitoring the fluctuations of active power and reactive power in real time and using an adaptive algorithm to dynamically adjust the magnitude of the virtual impedance, the oscillation is quickly suppressed and prevented from expanding further, which greatly improves the stable operation capability of the converter under complex conditions such as weak power grid and sudden load changes.

[0029] (2) The present invention is a virtual impedance adaptive control method for grid-type energy storage converters. It solves the problem that the existing method of using a conservative and large set value will cause continuous and unnecessary voltage drop and power loss when the system is running smoothly. The adaptive algorithm will automatically reduce the virtual impedance value, thereby significantly reducing the active power loss of the virtual impedance in steady state and improving the operating efficiency and economy of the entire energy storage converter system.

[0030] (3) The present invention is a virtual impedance adaptive control method for grid-type energy storage converters. Through the adaptive algorithm, the impedance parameters can be continuously and smoothly adjusted according to the power deviation and its changing trend. It can automatically optimize according to the changes in operating conditions such as grid strength, load level, and power output status, and always provide the most matching damping effect at that moment. This solves the problem of the versatility of fixed parameters not being able to perform optimally under all operating conditions.

[0031] (4) The present invention is a virtual impedance adaptive control method for grid-type energy storage converters. Through the limiting processing step, it ensures that the virtual resistance value and virtual inductance value calculated adaptively are always limited within the preset reasonable safety range, effectively preventing the risk of system overvoltage, overcurrent or instability caused by abnormal parameter calculation or over-adjustment, and enhancing the reliability and engineering practicality of the control method. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating the method of the present invention. Detailed Implementation

[0033] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0034] Example

[0035] Please see Figure 1 This invention proposes a technical solution for a virtual impedance adaptive control method for grid-type energy storage converters: the virtual impedance adaptive control method for grid-type energy storage converters includes the following steps:

[0036] Step S01: Real-time acquisition of three-phase voltage and three-phase current at the grid connection point of the grid-connected energy storage converter; specifically, acquisition is performed at a sampling frequency of 10kHz using voltage Hall sensors and current Hall sensors, and the analog signals output by the sensors are converted into digital signals by the ADC module of the DSP after passing through the conditioning circuit.

[0037] Step S02: Perform phase-locked loop processing and coordinate transformation on the three-phase voltage and three-phase current to obtain the d-axis voltage, q-axis voltage, d-axis current and q-axis current in the synchronous rotating coordinate system. Specifically, the DSP performs software phase-locked loop processing on the acquired digital signal to accurately obtain the phase angle θ and angular frequency ω (rated value is 314 rad / s) of the grid voltage. Using this phase angle, the voltage and current in the three-phase stationary coordinate system (abc) are transformed to the synchronous rotating coordinate system through Park transformation (also known as dq transformation) to obtain the d-axis voltage, q-axis voltage, d-axis current and q-axis current.

[0038] Step S03: Based on the d-axis voltage, q-axis voltage, d-axis current, and q-axis current, calculate the instantaneous power at the grid connection point to obtain the active power and reactive power; specifically, in the DSP, based on instantaneous power theory, use the d-axis voltage, q-axis voltage, d-axis current, and q-axis current obtained in step S02.

[0039] Step S04: Based on the fluctuations in active and reactive power, the required virtual resistance and virtual inductance values ​​are calculated in real time using an adaptive algorithm. Specifically, the DSP program calculates the active power deviation and reactive power deviation in real time. The active power deviation is the deviation between the current active power value and the value filtered by the first-order low-pass filter (i.e., ΔP = P - P_fil). The reactive power deviation is calculated in the same way, effectively extracting the oscillation and AC components in the power.

[0040] Step S05: Substitute the calculated virtual resistance and virtual inductance values ​​into the virtual impedance equation to generate a virtual impedance voltage drop compensation signal.

[0041] Step S06: The virtual impedance voltage drop compensation signal is superimposed with the reference voltage signal output by the preceding voltage loop to generate a new modulation wave signal, which is then input to the pulse width modulation module to drive the power switching devices of the grid-type energy storage converter, thereby achieving power oscillation suppression and stable operation at the grid connection point. Specifically, the reference voltage signals U_d_ref and U_q_ref output by the preceding voltage loop (in this embodiment, the voltage loop of the VSG control algorithm) are superimposed with the compensation signals ΔU_d and ΔU_q generated in step S05 to generate new d-axis and q-axis reference voltage signals.

[0042] U_d_ref_new=U_d_ref+ΔU_d

[0043] U_q_ref_new=U_q_ref+ΔU_q

[0044] Then, U_d_ref_new and U_q_ref_new are converted back to three-phase modulated wave signals in the three-phase stationary coordinate system through inverse Park transform. This modulated wave signal is input to the DSP's ePWM module, compared with a triangular carrier wave, and a variable duty cycle SVPWM wave is generated. This wave ultimately drives the IGBT power switching devices to turn on and off, thereby controlling the converter's output voltage and achieving adaptive suppression of power oscillations and stable system operation.

[0045] Furthermore, in step S04, the adaptive algorithm specifically involves: establishing a fuzzy logic controller or proportional-integral controller with the power oscillation amplitude or frequency change rate as input and the virtual impedance value as output; and dynamically adjusting the virtual resistance and virtual inductance values ​​through the controller so that when the power oscillation intensifies, the virtual impedance value is automatically increased to enhance damping; and when the system tends to stabilize, the virtual impedance value is automatically decreased to reduce steady-state losses.

[0046] Furthermore, in step S04, the calculation formulas for the virtual resistance value and the virtual inductance value are as follows:

[0047] R_v=R_0+K_p*ΔP+K_i*∫ΔP dt

[0048] L_v=L_0+K_p'*ΔQ+K_i'*∫ΔQ dt;

[0049] In the formula, R_v is the virtual resistance value, L_v is the virtual inductance value, R_0 and L_0 are the initial virtual impedance reference values, K_p, Ki, K_p', and Ki' are adaptive control coefficients, and ΔP and ΔQ are the deviations of active power and reactive power from their given values ​​or sliding average values, respectively.

[0050] In this embodiment, the parameter settings are as follows:

[0051] The initial virtual resistance reference value R_0 = 0.1Ω;

[0052] The initial virtual inductance reference value L_0 = 0.3mH;

[0053] The active power proportional coefficient K_p = 0.05, and the active power integral coefficient Ki = 2;

[0054] The reactive power proportional coefficient K_p' = 0.001, and the reactive power integral coefficient Ki' = 0.05.

[0055] When the system experiences active power oscillations due to load switching or grid disturbances (ΔP increases), this algorithm rapidly increases the value of R_v, thereby enhancing system damping and suppressing oscillations. After the oscillations subside (ΔP tends to 0), R_v automatically falls back to near R_0, reducing steady-state losses. The control principle for L_v is similar, mainly used to suppress reactive power loop oscillations.

[0056] Finally, the calculated R_v and L_v are limited to prevent numerical overflow or excessive extreme values ​​that could lead to system instability. In this embodiment, the range of R_v is set to [0Ω, 1.0Ω], and the range of L_v is set to [0mH, 5.0mH].

[0057] Furthermore, in step S05, the virtual impedance equation is:

[0058] [ΔU_d;ΔU_q]=-[R_v,-ω*L_v;ω*L_v,R_v]*[I_d;I_q]

[0059] In the formula, ΔU_d and ΔU_q are the virtual impedance voltage drop compensation signals of the d-axis and q-axis, respectively, and ω is the grid angular frequency.

[0060] In this embodiment, the voltage drop signals ΔU_d and ΔU_q that need to be compensated on the d-axis and q-axis are calculated in real time through matrix operations. These signals simulate the voltage drop generated by the actual impedances R_v and L_v when current flows through them.

[0061] Furthermore, in step S03, the instantaneous power is calculated using a method based on instantaneous power theory, and the formula is as follows:

[0062] P = 1.5 * (U_d * I_d + U_q * I_q)

[0063] Q = 1.5 * (U_q * I_d - U_d * I_q)

[0064] In the formula, P represents active power and Q represents reactive power.

[0065] In this embodiment, the calculation results are updated every 0.1ms to quickly capture power fluctuations.

[0066] Furthermore, step S04 also includes limiting the calculated virtual resistance and virtual inductance values.

[0067] Without this adaptive control method, simulating the application of a 50kW resistive load at 0.5s results in an active power oscillation lasting approximately 0.4s with an amplitude exceeding 15kW. With this control method enabled, under the same disturbance, the active power oscillation is rapidly suppressed within 0.1s, with the oscillation amplitude kept below 5kW. Furthermore, after the system enters steady state, the virtual impedance automatically decreases, and the output voltage drop is significantly smaller than when using a fixed large virtual impedance. This verifies the superiority of this invention in both dynamically suppressing oscillations and improving steady-state performance.

[0068] In the description of this invention, it should be understood that the terms "coaxial," "bottom," "one end," "top," "middle," "other end," "upper," "side," "top," "inner," "front," "center," "both ends," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and 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 limiting this invention.

[0069] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "setting," "connection," "fixing," "screw connection," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal connection of two components or the interaction between two components. Unless otherwise explicitly limited, those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0070] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A virtual impedance adaptive control method for grid-type energy storage converters, characterized in that, The following steps are involved: Step S01: Real-time acquisition of three-phase voltage and three-phase current at the grid connection point of the grid-connected energy storage converter; Step S02: Perform phase-locked loop processing and coordinate transformation on the three-phase voltage and three-phase current to obtain the d-axis voltage, q-axis voltage, d-axis current and q-axis current in the synchronous rotating coordinate system; Step S03: Calculate the instantaneous power at the grid connection point based on the d-axis voltage, q-axis voltage, d-axis current, and q-axis current to obtain the active power and reactive power. Step S04: Based on the fluctuations in active and reactive power, calculate the required virtual resistance and virtual inductance values ​​in real time using an adaptive algorithm. Step S05: Substitute the calculated virtual resistance and virtual inductance values ​​into the virtual impedance equation to generate a virtual impedance voltage drop compensation signal. Step S06: The virtual impedance voltage drop compensation signal is superimposed with the reference voltage signal output by the front-end voltage loop to generate a new modulation wave signal, which is then input to the pulse width modulation module to drive the power switching device of the grid-type energy storage converter, thereby achieving power oscillation suppression and stable operation at the grid connection point.

2. The virtual impedance adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, In step S04, the adaptive algorithm specifically involves: establishing a fuzzy logic controller or proportional-integral controller with the power oscillation amplitude or frequency change rate as input and the virtual impedance value as output; and dynamically adjusting the virtual resistance and virtual inductance values ​​through the controller so that when the power oscillation intensifies, the virtual impedance value is automatically increased to enhance damping; and when the system tends to stabilize, the virtual impedance value is automatically decreased to reduce steady-state losses.

3. The virtual impedance adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, In step S04, the formulas for calculating the virtual resistance value and the virtual inductance value are as follows: R_v=R_0+K_p*ΔP+K_i*∫ΔP dt L_v=L_0+K_p'*ΔQ+K_i'*∫ΔQ dt; In the formula, R_v is the virtual resistance value, L_v is the virtual inductance value, R_0 and L_0 are the initial virtual impedance reference values, K_p, Ki, K_p', and Ki' are adaptive control coefficients, and ΔP and ΔQ are the deviations of active power and reactive power from their given values ​​or sliding average values, respectively.

4. The virtual impedance adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, In step S05, the virtual impedance equation is: [ΔU_d;ΔU_q]=-[R_v,-ω*L_v;ω*L_v,R_v]*[I_d;I_q] In the formula, ΔU_d and ΔU_q are the virtual impedance voltage drop compensation signals of the d-axis and q-axis, respectively, and ω is the grid angular frequency.

5. The virtual impedance adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, In step S03, the instantaneous power is calculated using a method based on instantaneous power theory, and the formula is as follows: P = 1.5 * (U_d * I_d + U_q * I_q) Q = 1.5 * (U_q * I_d - U_d * I_q) In the formula, P represents active power and Q represents reactive power.

6. The virtual impedance adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, Step S04 further includes limiting the calculated virtual resistance and virtual inductance values.

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