Self-adaptive control method and system for network construction type energy storage converter

Abstract

The invention relates to the technical field of power electronics, and discloses a self-adaptive control method for a network construction type energy storage converter, which comprises the following steps of: acquiring voltage data and current data to obtain network-side real-time active power data and reactive power data; obtaining angular frequency data and voltage data by using a self-adaptive virtual synchronous machine control method, and processing the angular frequency data and the voltage data by using a voltage and current double-closed-loop control method to obtain a final modulation voltage signal; and processing the final modulation voltage signal by using a dq coordinate transformation method to obtain an SPWM wave, and taking the SPWM wave as a switch tube trigger signal to provide proper inertia support for a power grid system. Transient frequency response can be improved, active power oscillation can be suppressed, virtual inertia and virtual damping can be dynamically adjusted according to power grid disturbance intensity and system working conditions, service life loss caused by frequent and large-amplitude charging and discharging of energy storage is reduced, energy utilization efficiency is improved, and maintenance cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and more specifically, to an adaptive control method and system for a grid-type energy storage converter. Background Technology

[0002] Currently, China possesses abundant wind and solar energy resources, and the installed capacity of distributed and field-type renewable energy sources, such as wind turbines and solar power plants, continues to grow. These new energy power generation units are connected to the public power grid through power electronic devices such as inverters, transmitting DC or frequency-converted AC energy from the generation end to the load side. With the large-scale application of grid-connected technologies centered on power electronics and energy storage converters, the rotating mechanical inertia contributed by traditional synchronous generators in the system has significantly decreased, weakening the first-order inertial response capability of the overall power system. The reduction in inertia makes the system more susceptible to accelerated frequency rate changes, short-term frequency deviations, and amplified oscillations when subjected to large-scale disturbances (such as sudden loss of generation units, sudden load changes, or line switching), thereby threatening the safe and stable operation of the power grid and power quality. To mitigate the impact of inertia loss, grid-based energy storage systems are widely deployed as an important support method. Virtual Synchronous Generator (VSG) control has become one of the mainstream solutions because it can simulate the inertia and damping characteristics of a rotating machine. By introducing equivalent inertia and damping terms into the inverter control layer, VSG enables energy storage units to provide active / reactive support when frequency deviation occurs, thereby improving short-time frequency response and voltage stability.

[0003] However, traditional fixed-parameter VSG control has limitations under complex real-world grid conditions: on the one hand, fixed virtual inertia / damping designs are often based on a specific operating condition or small disturbance, making it difficult to balance response speed and system damping when faced with external disturbances of different amplitudes and frequencies, easily leading to over- or under-regulation of active power; on the other hand, impedance coupling between the inverter and the grid, control loop delays, and the interaction of multiple units in grid connection can cause VSG output oscillations or unstable transient power waveforms, resulting in frequency fluctuations and grid connection point voltage disturbances. These problems are further amplified by multi-point coordinated control, communication delays, and operating condition uncertainties, especially in grid-connected energy storage systems.

[0004] No effective solutions have yet been proposed to address the problems in the relevant technologies. Summary of the Invention

[0005] To address the problems in related technologies, this invention proposes an adaptive control method and system for grid-type energy storage converters to overcome the aforementioned technical problems in existing related technologies.

[0006] Therefore, the specific technical solution adopted by the present invention is as follows:

[0007] According to one aspect of the present invention, an adaptive control method for a grid-type energy storage converter is provided, comprising the following steps:

[0008] S1. Collect the three-phase voltage data and three-phase current signal data of the energy storage converter, and process the three-phase voltage data and three-phase current signal data using the dq coordinate transformation method to obtain the real-time active power data and real-time reactive power data of the grid side.

[0009] S2. Using the adaptive virtual synchronous machine control method, the real-time active power data, real-time reactive power data and battery exchange power data of the grid side are processed to obtain angular frequency data and voltage data. The voltage and current dual closed-loop control method is then used to process the angular frequency data and voltage data to obtain the final modulated voltage signal.

[0010] S3. The final modulated voltage signal is processed using the dq coordinate transformation method to obtain the SPWM wave, and the SPWM wave is used as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

[0011] Preferably, the acquisition of three-phase voltage data and three-phase current signal data from the energy storage converter, and the processing of the three-phase voltage data and three-phase current signal data using the dq coordinate transformation method to obtain grid-side active power data and grid-side real-time reactive power data, includes:

[0012] S11. Real-time acquisition of three-phase voltage data on the capacitor and three-phase current data on the inductor on the output side of the energy storage converter;

[0013] S12. Use the dq coordinate transformation method to convert the three-phase voltage data and three-phase current signal data, and convert the three-phase voltage data and three-phase current data of the abc axis into voltage data and current data of the dq axis.

[0014] S13. Perform power calculations on the converted voltage and current data of the dq axis to obtain real-time active power data and real-time reactive power data on the grid side.

[0015] Preferably, the step of processing the active power data and reactive power data using the adaptive virtual synchronous machine control method to obtain angular frequency data and voltage data, and then processing the angular frequency data and voltage data using the voltage-current dual closed-loop control method to obtain the final modulated voltage signal includes:

[0016] S21. The reactive power droop control is used as a virtual voltage regulator to participate in the primary voltage regulation and suppress voltage fluctuations. The active power droop control is used as a virtual rotor to generate simulated mechanical torque input into the swing equation, providing virtual inertia and virtual damping for the power grid system.

[0017] S22. The adaptive virtual synchronous machine control method includes adaptive virtual inertial control mode and adaptive virtual damping control mode, which are used to enhance the controllability of the external control power loop, suppress rapid frequency fluctuations, and obtain reference voltage data and reference angular frequency data.

[0018] S23. Based on the real-time active power data and real-time reactive power data of the grid side, and combined with the pre-acquired reference power data, battery exchange power data and battery SOC data, the angular frequency data and voltage data are calculated.

[0019] S24. Collect battery SOC data and exchange power data, participate in adaptive control, process the battery SOC data and exchange power data to obtain battery exchange power data, comprehensively evaluate the battery SOC data and the inertia requirements of the power grid system, limit the battery exchange power, and prevent the battery from being overcharged or over-discharged.

[0020] S25. The angular frequency data and voltage data are processed using the inner current loop control and the outer voltage loop control to generate the final modulated voltage signal.

[0021] Preferably, the adaptive virtual synchronous machine control method includes an adaptive virtual inertial control mode and an adaptive virtual damping control mode, used to enhance the controllability of the external control power loop to suppress rapid frequency fluctuations, including:

[0022] S221. Calculate the frequency deviation value to obtain the difference between the current frequency and the reference frequency; calculate the frequency change rate value to obtain the current power grid system oscillation intensity value.

[0023] S222. If the absolute value of the frequency change rate is less than and / or equal to the change threshold, the virtual inertia output is the basic virtual inertia; if the frequency deviation difference is less than and / or equal to the deviation threshold, the virtual damping output is the basic virtual damping.

[0024] S223. If the absolute value of the frequency change rate is greater than and / or equal to the change threshold range, enter the adaptive virtual inertial control mode; if the frequency deviation value is greater than and / or equal to the deviation threshold range, enter the adaptive virtual damping control mode.

[0025] Preferably, the step of entering the adaptive virtual inertial control mode if the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and entering the adaptive virtual damping control mode if the frequency deviation value is greater than and / or equal to the threshold range, includes:

[0026] S2231. When the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and the adaptive virtual inertia control mode is entered, if the frequency deviation increases, the virtual inertia is increased to slow down the frequency fluctuation of the power grid system and increase the stability of the power grid system. If the frequency change rate of the power grid system is large, the virtual inertia is increased to maintain the stability of the power grid system.

[0027] S2232. When the frequency deviation is greater than and / or equal to the threshold range, and the adaptive virtual damping control mode is entered, if the rate of change of the power angle increases, the virtual damping is increased to suppress the oscillation of the power grid system and improve the stability of the power grid system. When the frequency deviation is large, the virtual damping is increased to reduce the frequency fluctuation of the power grid system and help the power grid system restore a stable state.

[0028] Preferably, the virtual inertia and the virtual damping have a lower limit to meet the minimum requirements for maintaining the operation of the energy storage system. When the power grid system is disturbed, the virtual inertia and virtual damping will be strengthened for a short time to keep the frequency change of the power grid system within a safe range. When the frequency change rate exceeds the range of angular frequency change, the virtual inertia and virtual damping will slowly increase to keep the frequency of the power grid system within a safe range.

[0029] Preferably, the formula for calculating the battery SOC is:

[0030] ;

[0031] In the formula, Minimum SOC for the battery For battery charging and discharging efficiency, This refers to the battery's nominal rating. For battery power exchange, This is the integral of the battery's power exchange over time, representing energy.

[0032] Preferably, the virtual rotor equation is:

[0033] ;

[0034] ;

[0035] In the formula, The reference angular frequency of the power grid. The nominal virtual angular frequency, Nominal frequency, for, For power angle, For electrical torque, For mechanical torque, Where J is mechanical power, J is virtual inertia, and D is virtual damping. The rate of change of angular frequency, This represents the angular frequency deviation.

[0036] Preferably, the formula for calculating the final modulated voltage signal is:

[0037] ;

[0038] ;

[0039] In the formula, The output d-axis component is for voltage and current dual closed-loop control. The output q-axis component is for voltage and current dual closed-loop control. This refers to the proportional coefficient of the current inner loop proportional-differential controller. The integral coefficient of the current inner loop proportional-differential controller is denoted as . The component of the current inner loop on the d-axis is given by the current inner loop value. The component on the q-axis of the current inner loop is given. Let be the d-axis component of the three-phase voltage on the grid side. Let be the q-axis component of the three-phase grid-side voltage. Let represent the d-axis components of the three-phase grid-side current. Let be the q-components of the three-phase grid-side current. It is a three-phase filter inductor. The nominal virtual angular frequency, This is for integration over time.

[0040] According to another aspect of the present invention, an adaptive control system for a grid-type energy storage converter is provided, comprising:

[0041] The power calculation module is used to collect three-phase voltage data and three-phase current signal data of the energy storage converter, and to process the three-phase voltage and three-phase current data using the dq coordinate transformation method to obtain real-time active power data and reactive power data on the grid side.

[0042] The virtual synchronization control module is used to process the real-time active power data, real-time reactive power data and battery exchange power data of the grid side using an adaptive virtual synchronous machine control method to obtain angular frequency data and voltage data. The voltage and current dual closed-loop control method is then used to process the angular frequency data and voltage data to obtain the final modulated voltage signal.

[0043] The pulse width modulation module is used to process the final modulated voltage signal using the dq coordinate transformation method to obtain the SPWM wave, and uses the SPWM wave as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

[0044] The beneficial effects of this invention are as follows:

[0045] 1. Adaptive virtual synchronous generator control significantly improves transient frequency response and suppresses active power oscillations. It can dynamically adjust virtual inertia and virtual damping according to the intensity of grid disturbances and system operating conditions. During large disturbances, it increases virtual inertia to reduce the rate of frequency change, and increases damping during the disturbance decay phase to quickly dissipate oscillation energy.

[0046] 2. Collect battery SOC and switching power to participate in adaptive control. Under the condition of meeting the minimum inertia support, limit the battery charging and discharging threshold, reduce the life loss of energy storage caused by frequent large charging and discharging, improve energy utilization efficiency, reduce maintenance costs, and make the system more adaptable to parameter uncertainty and time-varying network conditions. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in 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.

[0048] Figure 1 This invention relates to an adaptive control method and system for a grid-type energy storage converter according to an embodiment of the present invention.

[0049] Figure 2 This is a flowchart of an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram of an adaptive control system for a grid-type energy storage converter according to an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of the active-frequency control principle of an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention.

[0052] Figure 5 This is an adaptive virtual inertia formation flowchart of an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention;

[0053] Figure 6 This is a flowchart illustrating the adaptive virtual damping formation process of an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention.

[0054] Figure 7 This is a schematic diagram of the reactive power-voltage control principle of an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention.

[0055] Figure 8This is a schematic diagram of a voltage and current dual closed-loop control method for an adaptive control method of a grid-type energy storage converter according to an embodiment of the present invention.

[0056] In the picture:

[0057] 1. Power calculation module; 2. Virtual synchronization control module; 3. Pulse width modulation module. Detailed Implementation

[0058] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention. The components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0059] According to an embodiment of the present invention, an adaptive control method and system for a grid-type energy storage converter is provided.

[0060] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, an adaptive control method for a grid-type energy storage converter according to an embodiment of the present invention includes:

[0061] S1. Collect the three-phase voltage data and three-phase current signal data of the energy storage converter, and process the three-phase voltage data and three-phase current signal data using the dq coordinate transformation method to obtain the real-time active power data and real-time reactive power data of the grid side.

[0062] In a preferred embodiment, the acquisition of three-phase voltage data and three-phase current signal data from the energy storage converter, and the processing of the three-phase voltage data and three-phase current signal data using the dq coordinate transformation method to obtain grid-side active power data and grid-side real-time reactive power data, includes:

[0063] S11. Real-time acquisition of three-phase voltage data on the capacitor and three-phase current data on the inductor on the output side of the energy storage converter;

[0064] S12. Use the dq coordinate transformation method to convert the three-phase voltage data and three-phase current signal data, and convert the three-phase voltage data and three-phase current data of the abc axis into voltage data and current data of the dq axis.

[0065] S13. Perform power calculations on the converted voltage and current data of the dq axis to obtain real-time active power data and real-time reactive power data on the grid side.

[0066] Specifically, such as Figure 3As shown, a battery module is used as a stable DC power supply. The battery module is connected to the DC side of the inverter. The positive terminal is connected to the filter inductor via a protection device, and then connected to the positive terminal of the H-bridge DC side. The negative terminal is connected to the support capacitor via a protection device, and then connected to the negative terminal of the H-bridge DC side. The three-phase H-bridge circuit converts DC power into three-phase AC power at industrial frequency. The AC side circuit includes an AC bypass switch and a three-phase filter inductor. and three-phase filter capacitors The grid-side circuitry includes grid impedance and grid inductive reactance.

[0067] In the diagram, PCC is the common connection point, i L For network current acquisition, u c For grid-side voltage acquisition, I sa Let I be the phase A current. sb For phase B current, I sc This represents the C-phase current; 12, 34, and 56 represent the three-phase H-bridge circuits. Where E is the power angle and E is the voltage amplitude. For battery power exchange, For line impedance, u cdq Let i be the voltage parameter after dq conversion. Ldq These are the current parameters after dq conversion. Where is the grid reference angular frequency, P is the real-time active power on the grid side, and Q is the real-time reactive power on the grid side. As the reference angular frequency, For reference reactive power, For reference active power, This is the final modulated voltage signal in the dq coordinate system. It is a three-phase modulated wave signal in the abc stationary coordinate system.

[0068] Specifically, real-time three-phase voltage and current data of the energy storage converter are collected from the grid side, and dq coordinate transformation is performed to convert the abc coordinate to the dq coordinate. Power calculation is then performed on the voltage and current data of the transformed dq axis to obtain real-time active power and reactive power data of the grid side.

[0069] S2. Using the adaptive virtual synchronous machine control method, the real-time active power data, real-time reactive power data and battery exchange power data of the grid side are processed to obtain angular frequency data and voltage data. The voltage and current dual closed-loop control method is then used to process the angular frequency data and voltage data to obtain the final modulated voltage signal.

[0070] In a preferred embodiment, an adaptive virtual synchronous machine control method is used to process real-time grid-side active power data, real-time grid-side reactive power data, and battery exchange power data to obtain angular frequency data and voltage data. Then, a voltage-current dual closed-loop control method is used to process the angular frequency data and voltage data to obtain the final modulated voltage signal, including:

[0071] S21. The reactive power droop control is used as a virtual voltage regulator to participate in the primary voltage regulation and suppress voltage fluctuations. The active power droop control is used as a virtual rotor to generate simulated mechanical torque input into the swing equation, providing virtual inertia and virtual damping for the power grid system.

[0072] In a preferred embodiment, the virtual inertia and the virtual damping have a lower limit to meet the minimum requirements for maintaining the operation of the energy storage system. When the power grid system is disturbed, the virtual inertia and virtual damping will be strengthened for a short time to keep the frequency change of the power grid system within a safe range. When the rate of frequency change exceeds the range of angular frequency change, the virtual inertia and virtual damping will slowly increase to keep the frequency of the power grid system within a safe range.

[0073] Specifically, such as Figure 4 As shown, the angular frequency is obtained by collecting the grid-side voltage and current. Combined with the reference angular frequency and reference active power, the active power droop control equation is obtained:

[0074] ;

[0075] In the formula, For virtual mechanical torque, To control the output mechanical power of the active droop control, For reference active power, This is the active power droop coefficient. As the reference angular frequency, The nominal virtual angular frequency, This represents the rate of change of frequency.

[0076] Furthermore, it should be noted that the reference active power and reference reactive power are obtained by extending the active and reactive power equations, wherein the expression for the reference active power is:

[0077] ;

[0078] The expression for reference reactive power is:

[0079] ;

[0080] In the formula, Where E is the line impedance and E is the voltage amplitude at the far end starting point. This represents the voltage amplitude at the local node. It is the phase angle.

[0081] Next, the transmitted power is calculated using the active power equation and the reactive power equation, and its expression is:

[0082] ;

[0083] In the formula, The phase angle (i.e., E lags V by one angle) ), is the apparent power, Q is the reference reactive power, and P is the reference active power.

[0084] Among them, such as Figure 7 As shown, the expression for the reactive power-voltage control equation is:

[0085] ;

[0086] In the formula, Real-time reactive power on the grid side; For reference reactive power; This refers to the grid-side voltage. For virtual synchronous machine voltage; K is the reactive power droop factor; K is the gain factor.

[0087] The equation for the virtual rotor is:

[0088] ;

[0089] ;

[0090] In the formula, The reference angular frequency of the power grid. The nominal virtual angular frequency, Nominal frequency, for, For power angle, For electrical torque, For mechanical torque, Where J is mechanical power, J is virtual inertia, and D is virtual damping. The rate of change of angular frequency, This represents the angular frequency deviation.

[0091] The equation for adaptive virtual inertia is:

[0092] ;

[0093] The equation for adaptive virtual damping is:

[0094] ;

[0095] In the formula, Based on inertia, Basic damping; The inertia gain coefficient, This is the coefficient representing the influence of the rate of change of frequency on the moment of inertia. This is the coefficient representing the effect of frequency deviation on damping. This is the damping gain coefficient; This is for frequency deviation; This represents the rate of change of frequency.

[0096] S22. The adaptive virtual synchronous machine control method includes adaptive virtual inertial control mode and adaptive virtual damping control mode, which are used to enhance the controllability of the external control power loop, suppress rapid frequency fluctuations, and obtain reference voltage data and reference angular frequency data.

[0097] In a preferred embodiment, the adaptive virtual synchronous machine control method includes an adaptive virtual inertial control mode and an adaptive virtual damping control mode, used to enhance the controllability of the external control power loop and suppress rapid frequency fluctuations, including:

[0098] S221. Calculate the frequency deviation value to obtain the difference between the current frequency and the reference frequency; calculate the frequency change rate value to obtain the current power grid system oscillation intensity value.

[0099] S222. If the absolute value of the frequency change rate is less than and / or equal to the change threshold, the virtual inertia output is the basic virtual inertia; if the frequency deviation difference is less than and / or equal to the deviation threshold, the virtual damping output is the basic virtual damping.

[0100] S223. If the absolute value of the frequency change rate is greater than and / or equal to the change threshold range, enter the adaptive virtual inertial control mode; if the frequency deviation value is greater than and / or equal to the deviation threshold range, enter the adaptive virtual damping control mode.

[0101] It should be noted that the reference voltage data and reference angular frequency data are obtained by collecting grid-side voltage and current data and then performing power calculations. In this process, the voltage data and angular frequency data collected and calculated for the first time are used as reference values ​​for the voltage and angular frequency collected and calculated for the second time, and so on.

[0102] Specifically, the expression for the change in work angle is:

[0103] ;

[0104] In the formula, This represents the change in power. J is the change in angular frequency; J is the virtual inertia; D is the virtual damping. is the damping coefficient.

[0105] As can be seen from the above expression, the output power and frequency of the virtual synchronizer depend entirely on the virtual inertia J, the virtual damping D, and the damping coefficient. Based on the dynamic response characteristics of the system, and combined with the angular frequency deviation, the rate of change of angular frequency and the state feedback of the system, an adaptive virtual damping and virtual inertia control is proposed.

[0106] In a preferred embodiment, the step of entering the adaptive virtual inertial control mode if the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and entering the adaptive virtual damping control mode if the frequency deviation value is greater than and / or equal to the threshold range, includes:

[0107] S2231. When the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and the adaptive virtual inertia control mode is entered, if the frequency deviation increases, the virtual inertia is increased to slow down the frequency fluctuation of the power grid system and increase the stability of the power grid system. If the frequency change rate of the power grid system is large, the virtual inertia is increased to maintain the stability of the power grid system.

[0108] S2232. When the frequency deviation is greater than and / or equal to the threshold range, and the adaptive virtual damping control mode is entered, if the rate of change of the power angle increases, the virtual damping is increased to suppress the oscillation of the power grid system and improve the stability of the power grid system. When the frequency deviation is large, the virtual damping is increased to reduce the frequency fluctuation of the power grid system and help the power grid system restore a stable state.

[0109] Specifically, such as Figure 5 As shown, the adaptive virtual synchronous generator control method can adjust the inertia J in real time, so that the power grid system has the optimal dynamic inertia adjustment response in different oscillation stages.

[0110] First, calculate the frequency deviation value. To obtain the current frequency With reference frequency Differences; Calculate the absolute value of the rate of change of frequency. To obtain the current system oscillation intensity, if the absolute value of the rate of frequency change... Less than and / or equal to the change threshold Inside, the virtual inertial output is based on the virtual inertial. If the absolute value of the rate of change of frequency Greater than and / or equal to the change threshold It then enters the adaptive virtual inertial control mode.

[0111] When frequency deviation With the rate of change of frequency product When it is less than 0, the virtual inertia is:

[0112] ;

[0113] When frequency deviation With the rate of change of frequency product When the virtual inertia is greater than or equal to 0, it is:

[0114] ;

[0115] In the formula, The inertia gain coefficient, This is the coefficient representing the influence of the rate of change of frequency on the moment of inertia. This represents the absolute value of the angular frequency deviation.

[0116] In addition, such as Figure 6 As shown, adaptive virtual synchronous generator control can also adjust the inertia D in real time, enabling the power grid system to have optimal dynamic damping regulation response in different oscillation stages:

[0117] First, calculate the frequency deviation value. To obtain the current frequency With reference frequency Differences; Calculate the absolute value of the rate of change of frequency. To obtain the current system oscillation intensity, if the frequency deviation value... Less than and / or equal to the deviation threshold Within the range, the virtual damping output is based on the virtual damping. If the frequency deviation value Greater than and / or equal to the deviation threshold Then it enters the adaptive virtual damping control mode.

[0118] When the absolute value of the rate of change of frequency Greater than or equal to the threshold At that time, the virtual inertia is:

[0119] ;

[0120] When the absolute value of the rate of change of frequency Less than the threshold At that time, the virtual inertia is:

[0121] ;

[0122] In the formula, This is the coefficient representing the effect of frequency deviation on damping. This is the damping gain coefficient.

[0123] S23. Based on the real-time active power data and reactive power data of the grid side, and combined with the pre-acquired reference power data, battery exchange power data and battery SOC data, the angular frequency data and voltage data are calculated.

[0124] S24. Collect battery SOC data and exchange power data, participate in adaptive control, process the battery SOC data and exchange power data to obtain battery exchange power data, comprehensively evaluate the battery SOC data and the inertia requirements of the power grid system, limit the battery exchange power, and prevent the battery from being overcharged or over-discharged.

[0125] It should be noted that processing the SOC data prevents battery overcharging or over-discharging, thus protecting the battery. Exchanging power data participates in power comparison in the adaptive virtual synchronizer, which in turn affects virtual inertia and virtual damping.

[0126] Specifically, the formula for calculating battery SOC is:

[0127] ;

[0128] In the formula, in the formula, Minimum SOC for the battery For battery charging and discharging efficiency, This refers to the battery's nominal rating. For battery power exchange, This is the integral of the battery's power exchange over time, representing energy.

[0129] S25. The angular frequency data and voltage data are processed using the inner current loop control and the outer voltage loop control to generate the final modulated voltage signal.

[0130] Specifically, such as Figure 8 As shown, the overvoltage outer loop and the current inner loop form a dual closed-loop control to generate the final modulated voltage signal. For grid-connected energy storage converter systems, the hardware typically adopts a voltage source converter model. Based on the power order, the adaptive virtual synchronous generator control serves as the main controller for generating converter threshold limits. When the main controller issues a command, the current inner loop and the voltage outer loop control follow the given command, thereby achieving precise control of the target by adjusting the current.

[0131] According to the voltage outer loop control equation:

[0132] ;

[0133] In the formula, and The output is controlled by a dual closed-loop system for voltage and current. The proportional parameter for the inner current loop control. These are the integral parameters for the inner current loop control. and These are the outer loop voltage setpoints. and These are the current inner loop setpoints, and This refers to the grid-side voltage transformed from the abc coordinate system to the dq coordinate system. and This refers to the quantity of the converter output current transformed from the abc coordinate system to the dq coordinate system.

[0134] Combining the inner current control equations:

[0135] ;

[0136] In the formula, The proportional parameter for the inner current loop control. These are the integral parameters for the inner current loop control. and The given value for the outer voltage loop; and This represents the grid-side current transformed from the abc coordinate system to the dq coordinate system.

[0137] The final formula for calculating the modulated voltage signal is obtained as follows:

[0138] ;

[0139] ;

[0140] In the formula, The output d-axis component is for voltage and current dual closed-loop control. The output q-axis component is for voltage and current dual closed-loop control. This refers to the proportional coefficient of the current inner loop proportional-differential controller. The integral coefficient of the current inner loop proportional-differential controller is denoted as . The component of the current inner loop on the d-axis is given by the current inner loop value. The component on the q-axis of the current inner loop is given. Let represent the d-axis components of the three-phase grid-side voltage. Let be the q-axis component of the three-phase grid-side voltage. Let represent the d-axis components of the three-phase grid-side current. Let be the q-components of the three-phase grid-side current. To integrate over time, It is a three-phase filter inductor. This refers to the nominal virtual angular frequency.

[0141] S4. The final modulated voltage signal is processed using the dq coordinate transformation method to obtain the SPWM wave, and the SPWM wave is used as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

[0142] According to another embodiment of the invention, such as Figure 2 As shown, an adaptive control system for a grid-type energy storage converter is provided, comprising:

[0143] Power calculation module 1 is used to collect three-phase voltage data and three-phase current signal data of the energy storage converter, and process the three-phase voltage and three-phase current data using the dq coordinate transformation method to obtain real-time active power data and reactive power data on the grid side.

[0144] Virtual synchronization control module 2 is used to process the real-time active power data, real-time reactive power data and battery exchange power data of the grid side using an adaptive virtual synchronous machine control method to obtain angular frequency data and voltage data. The angular frequency data and voltage data are then processed using a voltage and current dual closed-loop control method to obtain the final modulated voltage signal.

[0145] The pulse width modulation module 3 is used to process the final modulated voltage signal using the dq coordinate transformation method to obtain the SPWM wave, and uses the SPWM wave as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

[0146] In summary, by utilizing the above-mentioned technical solution of this invention, adaptive virtual synchronous generator control significantly improves transient frequency response and suppresses active power oscillations. It can dynamically adjust virtual inertia and virtual damping according to the intensity of grid disturbances and system operating conditions. During large disturbances, virtual inertia is increased to reduce the rate of frequency change, and damping is increased during the disturbance decay phase to quickly dissipate oscillation energy. It collects battery and switching power and participates in adaptive control. While meeting the minimum inertia support, it limits the battery charging and discharging thresholds, reduces the lifespan loss of energy storage caused by frequent large-scale charging and discharging, improves energy utilization efficiency, reduces maintenance costs, and makes the system more adaptable to parameter uncertainties and time-varying network conditions.

[0147] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive control method for a grid-type energy storage converter, characterized in that, include: S1. Collect the three-phase voltage data and three-phase current signal data of the energy storage converter, and process the three-phase voltage data and three-phase current signal data using the dq coordinate transformation method to obtain the real-time active power data and real-time reactive power data of the grid side. S2. Using the adaptive virtual synchronous machine control method, the real-time active power data, real-time reactive power data and battery exchange power data of the grid side are processed to obtain angular frequency data and voltage data. The voltage and current dual closed-loop control method is then used to process the angular frequency data and voltage data to obtain the final modulated voltage signal. S3. The final modulated voltage signal is processed using the dq coordinate transformation method to obtain the SPWM wave, and the SPWM wave is used as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

2. The adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, The process involves acquiring three-phase voltage and current signal data from the energy storage converter, and then processing this data using the dq coordinate transformation method to obtain grid-side active power data and grid-side real-time reactive power data, including: S11. Real-time acquisition of three-phase voltage data on the capacitor and three-phase current data on the inductor on the output side of the energy storage converter; S12. Use the dq coordinate transformation method to convert the three-phase voltage data and three-phase current signal data, and convert the three-phase voltage data and three-phase current data of the abc axis into voltage data and current data of the dq axis. S13. Perform power calculations on the converted voltage and current data of the dq axis to obtain real-time active power data and real-time reactive power data on the grid side.

3. The adaptive control method for a grid-type energy storage converter according to claim 1, characterized in that, The process of using an adaptive virtual synchronous machine control method to process active and reactive power data to obtain angular frequency and voltage data, and then using a voltage-current dual closed-loop control method to process the angular frequency and voltage data to obtain the final modulated voltage signal, includes: S21. The reactive power droop control is used as a virtual voltage regulator to participate in the primary voltage regulation and suppress voltage fluctuations. The active power droop control is used as a virtual rotor to generate simulated mechanical torque input into the swing equation, providing virtual inertia and virtual damping for the power grid system. S22. The adaptive virtual synchronous machine control method includes adaptive virtual inertial control mode and adaptive virtual damping control mode, which are used to enhance the controllability of the external control power loop, suppress rapid frequency fluctuations, and obtain reference voltage data and reference angular frequency data. S23. Based on the real-time active power data and real-time reactive power data of the grid side, and combined with the pre-acquired reference power data, battery exchange power data and battery SOC data, the angular frequency data and voltage data are calculated. S24. Collect battery SOC data and exchange power data, participate in adaptive control, process the battery SOC data and exchange power data to obtain battery exchange power data, comprehensively evaluate the battery SOC data and the inertia requirements of the power grid system, limit the battery exchange power, and prevent the battery from being overcharged or over-discharged. S25. The angular frequency data and voltage data are processed using the inner current loop control and the outer voltage loop control to generate the final modulated voltage signal.

4. The adaptive control method for a grid-type energy storage converter according to claim 3, characterized in that, The adaptive virtual synchronous machine control method includes an adaptive virtual inertial control mode and an adaptive virtual damping control mode, used to enhance the controllability of the external control power loop and suppress rapid frequency fluctuations, including: S221. Calculate the system frequency deviation value to obtain the difference between the current frequency and the reference frequency; calculate the frequency change rate value to obtain the current power grid system oscillation intensity value. S222. If the absolute value of the frequency change rate is less than and / or equal to the change threshold, the virtual inertia output is the basic virtual inertia; if the frequency deviation difference is less than and / or equal to the deviation threshold, the virtual damping output is the basic virtual damping. S223. If the absolute value of the frequency change rate is greater than and / or equal to the change threshold range, enter the adaptive virtual inertial control mode; if the frequency deviation value is greater than and / or equal to the deviation threshold range, enter the adaptive virtual damping control mode.

5. The adaptive control method for a grid-type energy storage converter according to claim 4, characterized in that, The step of entering adaptive virtual inertial control mode if the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and entering adaptive virtual damping control mode if the frequency deviation value is greater than and / or equal to the threshold range, includes: S2231. When the absolute value of the frequency change rate is greater than and / or equal to the threshold range, and the adaptive virtual inertia control mode is entered, if the frequency deviation increases, the virtual inertia is increased to slow down the frequency fluctuation of the power grid system and increase the stability of the power grid system. If the frequency change rate of the power grid system is large, the virtual inertia is increased to maintain the stability of the power grid system. S2232. When the frequency deviation is greater than and / or equal to the threshold range, and the adaptive virtual damping control mode is entered, if the rate of change of the power angle increases, the virtual damping is increased to suppress the oscillation of the power grid system and improve the stability of the power grid system. When the frequency deviation is large, the virtual damping is increased to reduce the frequency fluctuation of the power grid system and help the power grid system restore a stable state.

6. The adaptive control method for a grid-type energy storage converter according to claim 3, characterized in that, The virtual inertia and virtual damping have lower limits to meet the minimum requirements for maintaining the operation of the energy storage system. When the power grid system is disturbed, the virtual inertia and virtual damping will increase for a short time to keep the frequency change of the power grid system within a safe range. When the rate of frequency change exceeds the range of angular frequency change, the virtual inertia and virtual damping will slowly increase to keep the frequency of the power grid system within a safe range.

7. The adaptive control method for a grid-type energy storage converter according to claim 3, characterized in that, The formula for calculating the battery's SOC is: ； In the formula, Minimum SOC for the battery For battery charging and discharging efficiency, This refers to the battery's nominal rating. For battery power exchange, This is the integral of the battery's power exchange over time, representing energy.

8. The adaptive control method for a grid-type energy storage converter according to claim 3, characterized in that, The virtual rotor equation is: ； ； In the formula, The reference angular frequency of the power grid. The nominal virtual angular frequency, Nominal frequency, for, For power angle, For electrical torque, For mechanical torque, Where J is mechanical power, J is virtual inertia, and D is virtual damping. The rate of change of angular frequency, This represents the angular frequency deviation.

9. The adaptive control method for a grid-type energy storage converter according to claim 3, characterized in that, The formula for calculating the final modulated voltage signal is: ； ； In the formula, The output d-axis component is for voltage and current dual closed-loop control. The output q-axis component is for voltage and current dual closed-loop control. This refers to the proportional coefficient of the current inner loop proportional-differential controller. The integral coefficient of the current inner loop proportional-differential controller is denoted as . The component on the d-axis of the current inner loop is given. The component on the q-axis of the current inner loop is given. Let be the d-axis component of the three-phase voltage on the grid side. Let be the q-axis component of the three-phase grid-side voltage. Let represent the d-axis components of the three-phase grid-side current. Let be the q-components of the three-phase grid-side current. To integrate over time, It is a three-phase filter inductor. This refers to the nominal virtual angular frequency.

10. An adaptive control system for a grid-type energy storage converter, used to implement the adaptive control method for a grid-type energy storage converter according to any one of claims 1-9, characterized in that, include: The power calculation module is used to collect three-phase voltage data and three-phase current signal data of the energy storage converter, and to process the three-phase voltage and three-phase current data using the dq coordinate transformation method to obtain real-time active power data and reactive power data on the grid side. The virtual synchronization control module is used to process the real-time active power data, real-time reactive power data and battery exchange power data of the grid side using an adaptive virtual synchronous machine control method to obtain angular frequency data and voltage data. The voltage and current dual closed-loop control method is then used to process the angular frequency data and voltage data to obtain the final modulated voltage signal. The pulse width modulation module is used to process the final modulated voltage signal using the dq coordinate transformation method to obtain the SPWM wave, and uses the SPWM wave as the trigger signal for the switching transistor to control the switching of power electronic components, providing suitable inertia support for the power grid system.

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