Energy storage type intelligent soft switch based weak grid online impedance measurement device and method

Abstract

This invention provides an online impedance measurement device and method for weak grids based on an energy storage-type intelligent soft switch. The device includes an energy storage-type intelligent soft switch, a measuring device, and auxiliary equipment for injecting multi-sinusoidal voltage signals into the equipment-side inverter. The energy storage-type intelligent soft switch includes an equipment-side inverter and a grid-side inverter symmetrically connected on both sides of a DC bus, and an energy storage module connected to the DC bus. The measuring device is used to obtain a control signal based on grid-side connection point data and the fundamental frequency, and to obtain a first harmonic impedance amplitude by combining the energy storage module and the grid-side inverter. It is also used to obtain a disturbance voltage signal based on the multi-sinusoidal voltage signal, the fundamental frequency, and equipment-side connection point data, and to obtain a second harmonic impedance amplitude by combining the energy storage-type intelligent soft switch and the first harmonic impedance amplitude. This device has dual-mode measurement capability for parallel current and series voltage, and can simultaneously identify the broadband coupling impedance characteristics on both sides of the source-load, realizing real-time monitoring and identification of broadband disturbance response.

Description

Technical Field

[0001] This invention relates to the field of online monitoring and control technology for power systems, specifically to an online impedance measurement device and method for weak power grids based on energy storage-type intelligent soft switches. Background Technology

[0002] With the large-scale integration of new power electronic devices such as distributed generation units, photovoltaic inverters, and electric vehicle charging stations, the harmonic components in power systems have increased significantly. These harmonics not only degrade the power quality of the system but may also couple with other devices in the system, inducing broadband oscillations and thus threatening the system's operational stability. Especially in weak grid environments, due to the high grid impedance, harmonic currents can have a significant amplification effect in the system, exacerbating system oscillations. To obtain the harmonic impedance characteristics of the system in a timely manner, a great deal of research has been conducted on system impedance measurement techniques in recent years.

[0003] Existing harmonic impedance measurement methods can be broadly categorized into two types: non-injection methods and injection methods. Non-injection methods do not require injecting any disturbance signal into the system; they rely solely on the inherent harmonics of the system under its current operating conditions, estimating the system impedance through data estimation, Kalman filters, and fluctuation quantity algorithms. While these methods do not interfere with system operation, they are highly dependent on the harmonic components within the system, especially in weak power grids where the background harmonic components are small, making it difficult for fluctuation quantity algorithms and other methods to effectively capture the system's characteristic impedance. Furthermore, data estimation methods require a large amount of historical data for modeling; incomplete data or uneven node distribution can lead to significant deviations in impedance estimation results. Injection methods, on the other hand, measure system impedance by injecting a small-amplitude disturbance signal into the system. The injected signal typically uses a sine wave, pseudo-random sequence, or multiple sine wave signals. Based on the injection method, they can be further divided into parallel current injection methods and series voltage injection methods. Parallel current injection methods inject a current signal into the system through a parallel disturbance source, effectively capturing the current response characteristics of the inverter ports. However, since most of the current in the parallel current disturbance source flows to the low-impedance grid side, the high-frequency impedance measurement results in the system are often severely affected, and the high-frequency impedance characteristics on the equipment side are difficult to obtain accurately. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing an online impedance measurement device for weak power grids based on an energy storage-type intelligent soft switch. This device has dual-mode measurement capabilities for parallel current and series voltage, can simultaneously identify wideband coupling impedance characteristics on both sides of the source-load, and can monitor and identify wideband disturbance response in real time. It provides feedforward basis for preventing hard-to-detect frequency domain instability, and achieves high-precision and high-speed frequency domain measurement, overcoming the limitations of traditional frequency sweeping methods in terms of time efficiency and spectrum control.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, embodiments of the present invention propose an online impedance measurement device for weak grids based on an energy storage-type intelligent soft switch, comprising an energy storage-type intelligent soft switch, an energy storage module, a measuring device, and auxiliary equipment; the energy storage-type intelligent soft switch comprises an equipment-side inverter, a grid-side inverter, and an energy storage module, wherein the equipment-side inverter and the grid-side inverter are respectively connected to both sides of a DC bus in a symmetrical wiring manner, and the energy storage module is connected to the DC bus;

[0007] The measuring device is used to measure the fundamental frequency, collect first and second electrical energy data, obtain a control signal based on the first electrical energy data and the fundamental frequency, obtain a first harmonic impedance amplitude based on the control signal, the first electrical energy data, the energy storage module, and the grid-side inverter, obtain a disturbance voltage signal based on a multi-sine voltage signal, the fundamental frequency, and the second electrical energy data, and obtain a second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical energy data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude; the first electrical energy data is the electrical energy data at the grid-side connection point, the second electrical energy data is the electrical energy data at the equipment-side connection point, the first harmonic impedance amplitude is the harmonic impedance amplitude of the grid, and the second harmonic impedance amplitude is the harmonic impedance amplitude of the new energy equipment;

[0008] The auxiliary equipment is used to inject the multi-sine voltage signal into the inverter on the equipment side.

[0009] In some embodiments, when the second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second energy data, and the first harmonic impedance amplitude, the charging and discharging control strategy of the energy storage module is VDCM grid-type control.

[0010] In some embodiments, the measuring device includes a first measuring device and a second measuring device; the first measuring device is integrated on the grid-side inverter, and the second measuring device is integrated on the device-side inverter;

[0011] The first measuring device is used to measure the fundamental wave, to collect the first power data, to obtain a control signal based on the first power data and the fundamental wave, and to obtain the first harmonic impedance amplitude based on the control signal, the first power data, the energy storage module and the grid-side inverter.

[0012] The second measuring device is used to collect the second electrical energy data, to obtain the first harmonic impedance amplitude, to obtain a disturbance voltage signal based on the multi-sine voltage signal, the fundamental wave and the second electrical energy data, and to obtain a second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical energy data, the energy storage intelligent soft switch and the first harmonic impedance amplitude.

[0013] In some embodiments, the first measuring device includes a first acquisition unit, a first calculation unit, a proportional-integral controller, a pulse width modulation module, and a second calculation unit;

[0014] The first acquisition unit is used to acquire or update the first power data;

[0015] The first calculation unit is used to perform Clark transformation on the first electrical quantity data to obtain first intermediate data, to perform Fast Fourier Transform on the first intermediate data to obtain second intermediate data, to set the resistance of each harmonic, to obtain reference values ​​of each harmonic current based on the voltage of each harmonic and the resistance of each harmonic, to obtain the difference of each harmonic current based on the current of each harmonic and the reference values ​​of each harmonic current, and to perform inverse Park transform on each harmonic phase and intermediate control quantity to obtain each harmonic control quantity; the second intermediate data includes the voltage of each harmonic, the current of each harmonic, and the phase of each harmonic.

[0016] The proportional-integral controller is used to obtain intermediate control quantities based on the differences in harmonic currents.

[0017] The pulse width modulation module is used to obtain the control signal based on the control quantities of each harmonic and the fundamental frequency, and to apply the control signal to the grid-side inverter based on the energy storage module.

[0018] The second calculation unit is used to measure the fundamental wave, to collect the updated first electrical quantity data, and to obtain the first harmonic impedance amplitude based on the updated first electrical quantity data using the least squares method.

[0019] In some embodiments, the second measuring device includes a second acquisition unit, a signal execution unit, a third calculation unit, and a fourth calculation unit;

[0020] The second acquisition unit is used to acquire or update the second power data, and to obtain the amplitude of the first harmonic impedance;

[0021] The signal execution unit is used to apply the updated disturbance signal to the equipment-side inverter in a series injection manner;

[0022] The third calculation unit is used to obtain the Parker transform input angle based on the fundamental frequency, to obtain a first voltage reference value based on the fundamental frequency and the multi-sine voltage signal, to obtain a first voltage reference value based on the fundamental frequency and the disturbance voltage signal, to perform a Parker transform on the second electrical data based on the Parker transform input angle to obtain third intermediate data, to obtain an intermediate voltage reference value based on the first voltage reference value and the third intermediate data, and to perform an inverse Parker transform on the intermediate voltage reference value based on the Parker transform input angle to obtain the disturbance voltage signal; the first voltage reference value is the output voltage reference value at the next sampling time of the grid connection point on the equipment side;

[0023] The fourth calculation unit is used to perform a Fourier transform on the second power data to obtain fourth intermediate data, and to obtain the second harmonic impedance amplitude based on the fourth intermediate data, the energy storage intelligent soft switch and the first harmonic impedance amplitude.

[0024] A method for online impedance measurement of weak grids based on energy storage-type intelligent soft switches, implemented using the aforementioned online impedance measurement device for weak grids based on energy storage-type intelligent soft switches, includes:

[0025] Collect the first power data and the second power data; measure the fundamental frequency;

[0026] The control signal is obtained based on the first power data and the fundamental frequency.

[0027] The first harmonic impedance amplitude is obtained based on the control signal, the first power data, the energy storage module, and the grid-side inverter;

[0028] Inject the multi-sine voltage signal into the inverter on the device side;

[0029] The disturbance voltage signal is obtained based on the multi-sine voltage signal, the fundamental wave, and the second electrical quantity data;

[0030] The second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second power data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

[0031] In some embodiments, obtaining the control signal based on the first power data and the fundamental frequency includes:

[0032] The first power data is subjected to Clark transformation to obtain the first intermediate data;

[0033] The first intermediate data is subjected to a fast Fourier transform to obtain the second intermediate data; the second intermediate data includes the voltage, current and phase of each harmonic.

[0034] Set the resistance values ​​for each harmonic;

[0035] The reference values ​​of each harmonic current are obtained based on the voltage and resistance of each harmonic.

[0036] The difference between each harmonic current is obtained based on the amount of each harmonic current and the reference value of each harmonic current.

[0037] The intermediate control quantity is obtained based on the difference between the harmonic currents of each order.

[0038] The harmonic control quantities are obtained by performing Park inverse transform based on the phase of each harmonic and the intermediate control quantity.

[0039] The control signal is obtained based on the control quantities of each harmonic and the fundamental frequency.

[0040] In some embodiments, obtaining the first harmonic impedance amplitude based on the control signal, the first energy data, the energy storage module, and the grid-side inverter includes:

[0041] Step S11: Based on the energy storage module, apply the control signal to the grid-side inverter;

[0042] Step S12: Update the first power data, and obtain the control signal again based on the updated first power data and the fundamental wave, and repeat steps S11-S12;

[0043] Step S13: Based on the least squares method, obtain the first harmonic impedance amplitude according to the updated first electrical charge data.

[0044] In some embodiments, obtaining the disturbance voltage signal based on the multisine voltage signal, the fundamental frequency, and the second electrical quantity data includes:

[0045] Step S21: Let the multi-sinusoidal voltage signal be the current disturbance signal; obtain the Parker transform input angle based on the fundamental wave;

[0046] Step S22: Obtain a first voltage reference value based on the current disturbance signal and the fundamental frequency. The first voltage reference value is the output voltage reference value at the next sampling moment of the grid connection point on the equipment side.

[0047] Step S23: Perform a Parker transformation on the second electrical quantity data based on the Parker transformation input angle to obtain the third intermediate data;

[0048] Step S24: Obtain an intermediate voltage reference value based on the first voltage reference value and the third intermediate data;

[0049] Step S25: Based on the Parker transform input angle, perform an inverse Parker transform on the intermediate voltage reference value to obtain the disturbance voltage signal;

[0050] Step S26: Set the disturbance voltage signal to the current disturbance signal, and repeat steps S22-S25.

[0051] In some embodiments, obtaining the second harmonic impedance amplitude based on the disturbance voltage signal, the second energy data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude includes:

[0052] The disturbance voltage signal is applied to the device-side inverter in a series injection manner;

[0053] Update the second battery level data;

[0054] The updated second power data is subjected to Fourier transform to obtain the fourth intermediate data;

[0055] The second harmonic impedance amplitude is obtained based on the fourth intermediate data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The online impedance measurement device for weak power grids proposed in this invention has dual-mode measurement capability for parallel current and series voltage, and can simultaneously identify the wideband coupling impedance characteristics on both sides of the source and load. It breaks through the limitations of traditional impedance measurement devices that have single function and cannot adapt to real-time changes in system harmonic impedance, and realizes online dynamic measurement capability.

[0058] This invention deeply integrates dynamic impedance sensing with power support, oscillation and harmonic suppression functions. It not only provides support under steady-state conditions, but also enables real-time monitoring and identification of wideband disturbance response in complex operating states where system parameters change over time. This provides feedforward basis for preventing hard-to-detect frequency domain instability, thereby effectively enhancing the power system's ability to identify and suppress time-varying oscillations. At the same time, it integrates harmonic current reshaping, model predictive control and multi-sine wideband injection methods to achieve high-precision and high-speed frequency domain measurement, overcoming the limitations of traditional frequency sweeping methods in terms of time efficiency and spectrum control. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of the online impedance measurement device for weak grids based on energy storage intelligent soft switches in this invention;

[0060] Figure 2 This is a schematic diagram of a converter impedance measurement device based on SOP in the existing technology;

[0061] Figure 3 This is a flowchart of the online impedance measurement method for weak power grids based on energy storage intelligent soft switches in this invention;

[0062] Figure 4 This is a schematic diagram of the power grid impedance measurement and harmonic suppression principle based on SOP;

[0063] Figure 5 This is an MPC block diagram for measuring the harmonic impedance amplitude of the new energy equipment of the present invention;

[0064] Figure 6 This is a block diagram of a virtual DC motor control.

[0065] Figure 7 It is an equivalent diagram of energy storage and converter;

[0066] Figure 8 This is a low-frequency oscillation waveform diagram under the mesh control strategy;

[0067] Figure 9 This is a waveform diagram showing no oscillation under a network-type control strategy.

[0068] The attached figures are labeled as follows: 10, disturbance source; 101, grid-side inverter; 11, series voltage disturbance module; 12, parallel current disturbance module; 13, SOP series voltage disturbance impedance measurement; 2, power grid; 3, new energy equipment; 4, first acquisition unit; 5, first calculation unit; 51, Fourier transform module; 52, intermediate processing module; 53, proportional-integral controller; 54, pulse width modulation module; 55, control signal; 61, disturbance voltage signal; 62, Parker transform module; 63, model predictive control module; 64, inverse Parker transform module; 65, integrator; 7, fundamental frequency; 81, voltage loop; 82, JD loop; 83, VDCM; 84, current loop. Detailed implementation methods.

[0069] To address the shortcomings of the prior art, researchers have proposed a dual-mode measurement method combining series voltage disturbance sources and parallel current disturbance sources, thereby improving the comprehensiveness of system impedance measurements. However, there is still a lack of efficient equipment containing both disturbance sources capable of simultaneously and accurately measuring the harmonic impedance characteristics of the system and converter. While broadband measurement with single-injection is highly efficient, frequency coupling effects caused by characteristics such as converter control system asymmetry can interfere with the accuracy of broadband impedance measurements. Therefore, it is necessary to study measures to avoid impedance measurement errors caused by frequency coupling and switching frequency sideband effects. Furthermore, both broadband and frequency-sweep impedance measurement methods require a power source to generate harmonic injection energy, increasing equipment management and maintenance costs.

[0070] With the increasing integration of power electronic devices, the demand for frequency domain stability analysis in systems is constantly rising, making impedance measurement technology a key means of evaluating the interaction characteristics between grid-connected equipment and the power grid. In existing research, the point-by-point frequency sweep injection method has gradually revealed its application limitations due to problems such as long measurement time and poor real-time performance, thus giving rise to a research boom in wideband injection methods. Among these, a study proposed a fast impedance measurement method based on wideband excitation, which is currently a relatively complete scheme in terms of both theory and implementation. This scheme targets single-phase four-quadrant converters (4QC) in high-speed railway power supply systems. By designing multi-tone disturbance signals, it covers multiple frequency points in a single injection process, effectively avoiding the efficiency bottleneck of traditional frequency sweep injection. In terms of measurement strategy, this scheme adopts αβ coordinate transformation, Hilbert transform, and αβ value exchange technology (αβ-VEM) to accurately extract the effective response from multi-frequency signals, thereby improving the accuracy and robustness of impedance calculation. To comprehensively obtain the frequency domain behavior of the power grid and the converter, a combined injection method of series voltage disturbance sources and parallel current disturbance sources was designed to excite the dynamic responses on the grid side and the equipment side, respectively. Compared to a single injection scheme, this dual-path perturbation method is more conducive to distinguishing the frequency coupling characteristics and impedance interaction between the source and the load, and theoretically it has the ability to simultaneously measure the impedance characteristics of the system and the equipment.

[0071] However, this scheme mainly focuses on proposing control strategies and modeling methods, and verifying their effectiveness through simulation and real-time hardware-in-the-loop testing. Although its dual disturbance injection path logically achieves independent identification of grid-side and device-side impedances, it has not yet proposed a unified injection platform or actual equipment with synchronous measurement capabilities. The related disturbance source control, power support, and real-time adjustment mechanisms still rely on external modules for collaborative completion.

[0072] Based on the above background, this invention proposes an online impedance measurement device for weak grids based on an energy storage-type intelligent soft switch (E-SOP). While achieving active power mutual assistance and reactive power support, it also possesses the function of measuring system harmonic impedance. The E-SOP includes a parallel current disturbance module 12 and a series voltage disturbance module 11 as dual disturbance sources, respectively measuring the harmonic impedance of the grid and the harmonic impedance of the renewable energy grid-connected converter, enabling online dynamic measurement of grid-load harmonic impedance.

[0073] To clearly illustrate the technical features of this solution, the implementation methods of this application will be described in detail below with reference to the accompanying drawings and embodiments. This will allow for a full understanding and implementation of how this application uses technical means to solve technical problems and achieve corresponding technical effects. The embodiments of this application and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this application.

[0074] Firstly, see [the following] Figure 1 This invention proposes an online impedance measurement device for weak grids based on an energy storage-type intelligent soft switch, comprising an energy storage-type intelligent soft switch, an energy storage module, a measuring device, and auxiliary equipment. The energy storage-type intelligent soft switch is an Energy Storage Integrated Soft Open Point, abbreviated as E-SOP. The energy storage-type intelligent soft switch includes an equipment-side inverter, a grid-side inverter 101, and an energy storage module. The equipment-side inverter and the grid-side inverter 101 are respectively connected to both sides of the DC bus in a symmetrical wiring manner. The energy storage module is connected to the DC bus. The equipment-side inverter and the grid-side inverter 101 are both three-phase voltage source type PWM converters.

[0075] Measuring equipment: used to measure the fundamental frequency, to collect first and second electrical energy data, to obtain control signals based on the first electrical energy data and the fundamental frequency, to obtain the first harmonic impedance amplitude based on the control signals, the first electrical energy data, the energy storage module and the grid-side inverter 101, to obtain disturbance voltage signals based on the multi-sine voltage signal, the fundamental frequency and the second electrical energy data, and to obtain the second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical energy data, the energy storage intelligent soft switch and the first harmonic impedance amplitude; the first electrical energy data is the electrical energy data of the grid-side grid connection point, including the voltage and current of the grid-side grid connection point; the second electrical energy data is the electrical energy data of the equipment-side grid connection point, including the voltage and current of the equipment-side grid connection point; the first harmonic impedance amplitude is the harmonic impedance amplitude of the grid 2; the second harmonic impedance amplitude is the harmonic impedance amplitude of the new energy equipment 3.

[0076] Auxiliary equipment is used to acquire the fundamental frequency and to inject multi-sine voltage signals into the inverter on the equipment side.

[0077] Considering that E-SOP is a flexible power electronic device, its core function lies not only in power dispatch and power support, but also in achieving efficient measurement of harmonic impedance of online impedance measurement devices for weak power grids. Traditional harmonic impedance measurement methods mostly employ frequency sweeping, which, although covering a wide frequency range, suffers from low measurement efficiency due to point-by-point frequency scanning, especially in the wide-frequency oscillation band, where measurement accuracy is also limited. (See attached...) Figure 2The diagram shows a traditional wind-solar inverter impedance measurement device with SOP as the series voltage disturbance source (10), also known as SOP series voltage disturbance impedance measurement (13). SOP stands for Soft Open Point, indicating a flexible tie switch. Because the current from the parallel current disturbance module 12 flows primarily to the low-impedance grid side 2, it cannot measure the high-frequency impedance characteristics of the new energy equipment 3. To address this issue, the dual-disturbance-source E-SOP measurement model effectively combines series voltage injection and parallel current injection to achieve grid-load harmonic impedance measurement, such as... Figure 1 As shown, the system deploys two independent disturbance source modules on the new energy equipment 3 side and the grid 2 side, respectively. These modules can perform online monitoring of harmonic impedance for the grid 2 and the inverter, respectively. The parallel current disturbance module 12 is used to extract the low-frequency harmonic impedance characteristics of the new energy equipment 3 side, while the series voltage disturbance module 11 can be used to obtain the high-frequency harmonic impedance information of the grid 2. This dual disturbance source configuration not only effectively avoids the measurement blind zone caused by a single disturbance source, but also improves the detection accuracy of harmonic impedance through joint measurement. At the same time, the energy storage module inside the E-SOP provides reliable support for the energy injection of the disturbance source, enabling the system to maintain the stability of the disturbance source output for a long time, thereby ensuring the accuracy of the measurement data.

[0078] In the dual-disturbance-source system, the energy storage module can flexibly switch between two disturbance modes: single-module parallel current injection and dual-module series voltage injection, to adapt to the needs of different testing scenarios. This dual-mode switching function not only improves the flexibility of system measurement but also provides an effective way to solve the problem of limited power injection capability in traditional impedance measurement equipment. Furthermore, the control strategy within the E-SOP achieves dynamic allocation of measurement frequency points through comprehensive and coordinated control of the parallel current disturbance module 12 and the series voltage disturbance module 11, enabling it to comprehensively cover both low-frequency and high-frequency harmonic impedance.

[0079] Integrating an energy storage-type intelligent soft switch (E-SOP) into an existing system not only enables real-time harmonic impedance measurement but also provides multi-functional optimized control, including voltage support and frequency support for weak nodes. Traditional impedance measurement methods largely rely on frequency sweep measurements, which require point-by-point frequency scanning, resulting in low measurement efficiency and the potential to overlook rapidly changing harmonic components in the system. However, the online impedance measurement device for weak grids incorporating an E-SOP achieves synchronous harmonic impedance measurement based on a dual-module architecture by utilizing dynamic disturbance signals provided by the energy storage module. The two modules operate synchronously, adapting to real-time changes in system harmonic impedance, thus improving the coverage of the measurement frequency range and ensuring measurement efficiency. Regarding frequency support, the E-SOP can adjust the discharge rate of the energy storage module to suppress system frequency fluctuations in real time. This frequency support function not only enhances the system's ability to suppress low-frequency oscillations but also further optimizes the stability of harmonic impedance measurement data through frequency coordination control when multiple modules work together. Therefore, by introducing impedance measurement and harmonic suppression control, the multi-functional E-SOP device achieves dynamic measurement and control of harmonic impedance, effectively improving the system's adaptability to changes in harmonic impedance.

[0080] This invention, through the design of an online impedance measurement device for weak power grids containing an E-SOP, utilizes the E-SOP as a dual disturbance source. This not only effectively improves the frequency coverage of harmonic impedance measurement but also provides multi-functional optimized control, such as voltage support and frequency support for weak nodes. This provides strong support for the implementation of harmonic detection and subsequent suppression control strategies for weak power grids.

[0081] When measuring the harmonic impedance amplitude of the grid 2 by obtaining the first harmonic impedance amplitude based on the control signal, the first power data, the energy storage module, and the grid-side inverter 101, the energy storage module is equivalent to a virtual resistor. The grid-side inverter 101, based on its constant power generation function, is equivalent to a virtual harmonic resistor under each harmonic. At this time, the energy storage module acts as a broadband harmonic load impedance, forming a loop with the broadband background harmonic voltage source of the weak grid. The disturbance energy generated by the energy storage module in E-SOP can operate in the single-module parallel current injection mode. Then, by adjusting the control strategy of the grid-side inverter 101, the measurement of the first harmonic impedance amplitude is achieved. Preferably, the change in harmonic voltage amplitude at the grid connection point is measured by changing the value of the equivalent virtual harmonic resistance, and the harmonic impedance amplitude of the grid 2 is estimated based on the least squares method, and the control is not affected by the interference from the new energy equipment 3.

[0082] When measuring the harmonic impedance amplitude of the new energy device 3 by obtaining the second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical data, and the first harmonic impedance amplitude, the energy storage module is equivalent to a voltage source. At this time, the disturbance energy generated by the energy storage module in the E-SOP can operate in the dual-module series voltage injection mode. By setting the charging control strategy of the energy storage module, the control strategy of the inverter on the device side can be adjusted, thereby achieving the measurement of the second harmonic impedance amplitude. Advantageously, the energy storage-type intelligent soft switch can realize both parallel current injection mode and series voltage injection mode, accommodating the needs of both disturbance sources and simultaneously measuring the harmonic impedance amplitudes of the power grid 2 and the new energy device 3. Compared with existing technologies, this online impedance measurement device for weak grids based on an energy storage-type intelligent soft switch achieves a systematic breakthrough in terms of structural integration, functional complexity, and measurement efficiency. Traditional impedance measurement devices only have a single disturbance source and cannot simultaneously sense the harmonic impedance characteristics of the power grid on two sides and the new energy equipment on three sides. Furthermore, they lack power support and dynamic vibration suppression capabilities, making it difficult to meet the requirements of real-time measurement and online stability analysis. The online impedance measurement device for weak power grids proposed in this invention has dual-mode measurement capabilities for parallel current and series voltage, and can simultaneously identify the broadband coupling impedance characteristics on both the source and load sides. It overcomes the limitations of traditional impedance measurement devices, which have a single function and cannot adapt to real-time changes in system harmonic impedance, and achieves online dynamic measurement capabilities. Furthermore, by deeply integrating dynamic impedance sensing with power support, oscillation and harmonic suppression functions, this invention not only provides support under steady-state conditions but also enables real-time monitoring and identification of wideband disturbance responses in complex operating states where system parameters change over time. This provides a feedforward basis for preventing difficult-to-detect frequency domain instability, thereby effectively enhancing the power system's ability to identify and suppress time-varying oscillations. Simultaneously, by integrating harmonic current reshaping, model predictive control, and multi-sine wideband injection methods, it achieves high-precision and high-speed frequency domain measurement, overcoming the limitations of traditional frequency sweeping methods in terms of time efficiency and spectrum control.

[0083] In some embodiments, when the second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second energy data and the first harmonic impedance amplitude, the charging and discharging control strategy of the energy storage module is VDCM grid-type control.

[0084] VDCM stands for Virtual DC Motor. VDCM grid-type control can maintain the DC bus voltage without large disturbances and effectively suppress low-frequency oscillations. By adding VDCM-controlled energy storage at the DC bus, the damping is adaptively adjusted according to the voltage deviation and rate of change to smooth the DC bus voltage fluctuations of the rectifier converter, successfully suppressing oscillations.

[0085] In traditional DC bus voltage control, power electronic converters have a fast response speed but lack physical inertia, making the DC voltage very sensitive to power fluctuations. To improve the stability of the DC side voltage, a "virtual DC motor (VDCM)" is introduced. By embedding a mathematical model of a DC motor into the controller, "inertia and damping" are artificially constructed, allowing the DC bus voltage to have buffering characteristics like a mechanical system.

[0086] The control block diagram of VDCM can be obtained from the following two agendas:

[0087] ;

[0088] In the formula, For virtual inertia coefficient, For virtual angular velocity, For mechanical torque, For electromagnetic torque, This is the virtual damping coefficient. As the reference angular velocity, Electromagnetic power, Terminal voltage, This is the equivalent electromotive force. Equivalent resistance For virtual armature current, Let f be the motor flux linkage constant;

[0089] Figure 6 The diagram illustrates the VDCM network control block diagram. In this diagram, the main function of the virtual DC motor mechanical torque is to allow the DC / DC converter to adjust the virtual angular velocity ω in real time when low-frequency oscillations occur on the DC side. This allows the DC / DC converter to dynamically adjust the armature induced electromotive force through the electromagnetic balance equation, thereby responding to low-frequency power fluctuations and maintaining a constant DC side voltage.

[0090] The control process of VDCM network control is as follows:

[0091] Voltage loop 81 compares DC side voltage reference value With DC bus voltage via voltage loop PI controller Adjust to obtain the power compensation amount of the voltage loop output. ;

[0092] Power compensation amount of voltage loop 81 output Entering the virtual DC motor model, i.e., JD ring 82, VDCM83 includes JD ring 82, through the virtual inertia coefficient and virtual damping coefficient Generate an equivalent angular velocity deviation ;

[0093] Equivalent electromotive force generated from virtual angular velocity ω Combined with equivalent resistance Obtain the virtual armature current ;

[0094] Current loop 84 with virtual armature current As an instruction, via the current loop Pl controller The pulse width modulator (PWM) is used to regulate the DC / DC converter, thereby achieving DC bus voltage regulation.

[0095] In this way, the DC bus exhibits a buffering effect similar to "motor inertia" when power fluctuates.

[0096] like Figure 7 The diagram shows the equivalent circuit of the VDCM (Virtual DC-DC Converter) network control in the energy storage module. From the perspective of the DC bus voltage port, the energy storage and converter under VDCM network control can be equivalent to a virtual capacitor. DC-side power exchange is mainly achieved through the supporting capacitor C. Therefore, when low-frequency oscillations occur, the fluctuation of unbalanced power needs to be maintained by adjusting the supporting capacitor C to keep the system stable; the larger the capacitance, the greater the system inertia. Therefore, compared to the very small supporting capacitor in the actual converter, VDCM network control, without changing the original converter topology, only needs to adjust the moment of inertia and damping coefficient to create an equivalent large capacitor with adjustable capacitance on the DC side. This effectively reduces the rate of change of the DC-side voltage, providing a certain inertial support for system regulation. That is, when power oscillation disturbances occur, the reverse charging and discharging resistance can dampen the DC bus voltage fluctuations to suppress AC-side oscillations. Figure 8 The diagram illustrates a simulation of low-frequency oscillations in a single-phase traction power supply system. This invention designs an energy storage module controlled by a VDCM (Voltage Diversion Module) at the DC bus. This module adaptively adjusts the damping based on voltage deviation and rate of change to smooth out DC bus voltage fluctuations in the rectifier converter, successfully suppressing the oscillations. (See attached diagram.) Figure 9 As shown.

[0097] The energy storage module is directly connected in parallel to the DC bus and its charging and discharging are controlled by a DC / DC converter. The controller monitors the DC bus voltage in real time. When the DC bus voltage deviates from the set value, the VDCM control strategy calculates the voltage deviation and its rate of change to determine the charging and discharging power of the energy storage module, thereby actively adjusting the DC bus voltage. Compared to traditional PI control, the VDCM network control used in this invention can quickly intervene in the early stages of voltage fluctuations. By introducing virtual inertia, it provides additional energy storage support, thereby effectively suppressing the voltage fluctuation amplitude and ensuring the stability of the DC bus voltage.

[0098] The advantages are: setting the charging and discharging control strategy of the energy storage module to VDCM grid-type control smooths the DC bus voltage. With the support of VDCM grid-type energy storage, the device maintains the stability of the bus voltage while injecting disturbances. It has three functions: online dynamic measurement, oscillation early warning and system support, which significantly improves the practicality and engineering adaptability of the online impedance measurement device for weak grids based on energy storage-type intelligent soft switch.

[0099] In some embodiments, the measuring device includes a first measuring device and a second measuring device; the first measuring device is integrated on the grid-side inverter 101, and the second measuring device is integrated on the equipment-side inverter, without the need to add additional measuring devices;

[0100] The first measuring device is used to measure the fundamental wave, to collect the first electrical energy data, to obtain a control signal based on the first electrical energy data and the fundamental wave, and to obtain the first harmonic impedance amplitude based on the control signal, the first electrical energy data, the energy storage module and the grid-side inverter 101.

[0101] The second measuring device is used to collect second electrical quantity data, to obtain the first harmonic impedance amplitude, to obtain a disturbance voltage signal based on the multi-sine voltage signal, the fundamental wave, and the second electrical quantity data, and to obtain the second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical quantity data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

[0102] In some embodiments, the first measuring device includes a first acquisition unit 4, a first calculation unit, a proportional-integral controller, a pulse width modulation module, and a second calculation unit;

[0103] The first acquisition unit 4 is used to measure the fundamental frequency and to acquire or update the first power data;

[0104] See Figure 4 The first calculation unit 5 is used to perform Clark transformation (α and β transformation) on the first electrical quantity data to obtain first intermediate data, which consists of the α-axis and β-axis components of the first electrical quantity data. The first intermediate data is then used to perform a Fast Fourier Transform (FFT) on the first intermediate data in the Fourier Transform module to obtain second intermediate data. The FFT takes the real and imaginary parts of the α-axis and β-axis components of the first electrical quantity data, respectively, to obtain the positive and negative sequence components of the harmonics. These components are used to set the resistance of each harmonic, to obtain reference values ​​for each harmonic current based on the harmonic voltage and resistance, to obtain the harmonic current difference based on the harmonic current and its reference value, and to perform an inverse Park transformation based on the harmonic phase and intermediate control quantity to obtain the harmonic control quantity. The second intermediate data includes the harmonic voltage, harmonic current, and harmonic phase.

[0105] The proportional-integral controller 53 is used to obtain intermediate control quantities based on the differences between harmonic currents, wherein the differences between harmonic currents are obtained by the intermediate processing module 52 in the first calculation unit 5.

[0106] The pulse width modulation module 54 is used to obtain control signals based on each harmonic control quantity and the fundamental frequency. Specifically, it superimposes each harmonic control quantity and the fundamental frequency control quantity and sends them to the pulse width modulation module to generate control signal 55, and applies control signal 55 to the grid-side inverter 101 based on the energy storage module.

[0107] The second calculation unit is used to collect the updated first power data and to obtain the first harmonic impedance amplitude based on the updated first power data using the least squares method.

[0108] The above transformation generates an h-th harmonic current that is in the same direction as the h-th harmonic voltage but differs in amplitude by a factor of rh. This makes the grid-side inverter 101 equivalent to a controlled current source, controlled by the harmonic voltages at the grid connection point. Therefore, the grid-side inverter 101 can be considered a virtual resistor, i.e., a reshaped harmonic current. The amplitude change of the harmonic voltage at the grid connection point is then measured by repeatedly reshaping the harmonic current values, and the harmonic impedance amplitude of grid 2 is estimated based on the least squares method.

[0109] In some embodiments, the second measuring device includes a second acquisition unit, a signal execution unit, a third calculation unit, and a fourth calculation unit;

[0110] The second acquisition unit is used to measure the fundamental wave, to acquire or update the second electrical data, and to obtain the amplitude of the first harmonic impedance.

[0111] The signal execution unit is used to apply the updated disturbance voltage signal 61 to the inverter on the equipment side in a series injection manner. It adopts a control strategy based on MPC (Model Predictive Control) and multi-sine signal injection. The MPC control strategy ensures that the spectrum of the injected signal is controllable, and the multi-sine signal injection avoids frequency coupling interference. Moreover, the control is not affected by the interference from the two sides of the power grid, so as to realize the accurate measurement of the impedance of the new energy equipment.

[0112] The entire control process is implemented in the dq domain. The third calculation unit is used to obtain the Parker transform input angle based on the fundamental frequency 7. The Parker transform input angle is obtained by integrating the fundamental frequency angular velocity with the integrator 65. It is used to obtain the first voltage reference value based on the fundamental frequency 7 and the multi-sinusoidal voltage signal. Specifically, when the multi-sinusoidal voltage signal is injected for the first time, the first voltage reference value is obtained by adding the fundamental frequency rated voltage and the multi-sinusoidal voltage signal. After that, the first voltage reference value is obtained by adding the fundamental frequency rated voltage and the disturbance voltage signal. It is used to perform Parker transform on the second electrical data based on the Parker transform input angle to obtain the third intermediate data. The Parker transform is completed in the Parker transform module 62. The third intermediate data is the d-axis component and q-axis component of the second electrical data. It is used to obtain the intermediate voltage reference value based on the first voltage reference value and the third intermediate data. It is also used to perform inverse Parker transform on the intermediate voltage reference value based on the Parker transform input angle to obtain the disturbance voltage signal 61. The inverse Parker transform is completed in the inverse Parker transform module 64. The first voltage reference value is the output voltage reference value at the next sampling time of the grid connection point on the equipment side.

[0113] The fourth calculation unit is used to perform a Fourier transform on the second electrical data to obtain the fourth intermediate data, and to obtain the second harmonic impedance amplitude based on the fourth intermediate data, the energy storage intelligent soft switch and the first harmonic impedance amplitude.

[0114] A disturbance voltage signal with multiple frequency components is generated through an MPC control strategy and applied to the inverter on the equipment side via series injection. The reference value of the output voltage at the next sampling moment of the grid-connected point on the equipment side is calculated in real time to ensure that the amplitude, frequency, and phase of the injected signal are generated strictly according to preset values, thereby enabling impedance measurement at different frequency points. During the measurement process, a LC filter is used to suppress high-frequency noise and maintain the output impedance of the inverter on the equipment side much smaller than the impedance of the inverter of the new energy equipment under test, thus reducing measurement errors. For the measurement of the harmonic impedance of the new energy equipment 3, since the amplitude of the first harmonic impedance (i.e., the amplitude of the grid harmonic impedance) has been obtained through the first measuring device, the positive and negative sequence voltage components and positive and negative sequence current components at each frequency point can be extracted by collecting the second power data response and performing a Fourier transform during the injection of the disturbance voltage signal. Since the amplitude of the grid harmonic impedance is known, the harmonic impedance amplitude of the new energy equipment 3 can be obtained by analyzing the voltage and current response at the grid-connected point on the equipment side based on the series impedance voltage division principle.

[0115] The online impedance measurement device for weak grids based on energy storage intelligent soft switch proposed in this invention is equipped with an E-SOP containing dual disturbance sources. Through the synergistic effect of the virtual harmonic resistance regulation of the grid-side inverter 101 and the MPC control strategy of the equipment-side inverter, comprehensive measurement of harmonic impedance of new energy equipment and grid harmonic impedance is realized.

[0116] See Figure 3 A method for online impedance measurement of weak grids based on energy storage intelligent soft switches is proposed, which is implemented using an online impedance measurement device for weak grids based on energy storage intelligent soft switches, including:

[0117] Collect first and second battery power data; measure fundamental frequency.

[0118] The control signal is obtained based on the first power data and the fundamental frequency.

[0119] The first harmonic impedance amplitude is obtained based on the control signal, the first power data, the energy storage module, and the grid-side inverter 101.

[0120] Inject multiple sinusoidal voltage signals into the inverter on the equipment side;

[0121] The disturbance voltage signal is obtained based on the multi-sine voltage signal, the fundamental frequency, and the second electrical quantity data.

[0122] The second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second power data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

[0123] The proposed online impedance measurement method for weak grids based on energy storage-type intelligent soft switches utilizes an E-SOP with dual disturbance sources. Through the synergistic effect of virtual harmonic resistance regulation of the grid-side inverter 101 and the MPC control strategy of the equipment-side inverter, comprehensive measurement of harmonic impedance of both new energy equipment and the grid is achieved. This method effectively overcomes the response lag problem in traditional frequency sweep measurements. Dynamic adjustment of the virtual harmonic resistance not only improves measurement accuracy but also enhances the system's adaptability to rapid changes in harmonic impedance. Furthermore, the disturbance signal injection under MPC control not only ensures the spectral independence of each harmonic component but also suppresses the interference of frequency coupling effects on the measurement results, providing more accurate data support for the analysis of the harmonic impedance amplitudes of new energy equipment 3 and the grid 2.

[0124] See Figure 4 In some embodiments, obtaining the control signal based on the first power data and the fundamental frequency includes:

[0125] The first battery data is transformed using Clark transformation to obtain the first intermediate data;

[0126] The first intermediate data is subjected to a fast Fourier transform to obtain the second intermediate data; the second intermediate data includes the voltage, current and phase of each harmonic.

[0127] Set the resistance values ​​for each harmonic;

[0128] The reference values ​​of each harmonic current are obtained based on the voltage and resistance of each harmonic.

[0129] The difference of each harmonic current is obtained based on the quantity of each harmonic current and the reference value of each harmonic current.

[0130] The intermediate control quantity is obtained based on the difference between each harmonic current;

[0131] The control quantities of each harmonic are obtained by performing the Park inverse transform based on the phase of each harmonic and the intermediate control quantity.

[0132] The control signal is obtained based on the control quantities of each harmonic and the fundamental frequency.

[0133] In some embodiments, obtaining the first harmonic impedance amplitude based on the control signal, first energy data, energy storage module, and grid-side inverter 101 includes:

[0134] Step S11: Based on the energy storage module, apply the control signal to the grid-side inverter 101;

[0135] Step S12: Update the first power data, and obtain the control signal repeatedly based on the updated first power data and the fundamental frequency, and repeat steps S11-S12.

[0136] Step S13: Based on the least squares method, obtain the first harmonic impedance amplitude according to the updated first electrical charge data.

[0137] See Figure 5 In some embodiments, obtaining the disturbance voltage signal based on the multisine voltage signal, the fundamental frequency, and the second electrical quantity data includes:

[0138] Step S21: Set the multi-sinusoidal voltage signal as the current disturbance signal; obtain the Parker transform input angle based on the fundamental frequency;

[0139] Step S22: Obtain the first voltage reference value based on the current disturbance signal and the fundamental frequency. The first voltage reference value is the output voltage reference value at the next sampling moment of the grid connection point on the equipment side.

[0140] Step S23: Perform Parker transformation on the second electrical data based on the Parker transformation input angle to obtain the third intermediate data;

[0141] Step S24: Obtain the intermediate voltage reference value based on the first voltage reference value and the third intermediate data;

[0142] Step S25: Based on the Parker transform input angle, perform an inverse Parker transform on the intermediate voltage reference value to obtain the disturbance voltage signal;

[0143] Step S26: Set the disturbance voltage signal as the current disturbance signal and repeat steps S22-S25.

[0144] In some embodiments, obtaining the second harmonic impedance amplitude based on the disturbance voltage signal, the second energy data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude includes:

[0145] The disturbance voltage signal is applied to the inverter on the equipment side in a series injection manner;

[0146] Update the second battery level data;

[0147] The updated second power data is subjected to Fourier transform to obtain the fourth intermediate data;

[0148] The second harmonic impedance amplitude is obtained based on the fourth intermediate data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

[0149] The core of MPC control is to use a discrete model to predict the voltage at the grid connection point on the device side at the next sampling time, i.e., the next cycle, and then directly substitute the "error-free tracking" condition to obtain... Figure 5 The control law of the model predictive control module 63 calculates the modulated signal, enabling the inverter on the equipment side to output a precise disturbance voltage signal in each sampling cycle. In this way, the inverter on the equipment side becomes approximately an ideal voltage source, thereby ensuring the accurate measurement of harmonic impedance of the new energy equipment 3.

[0150] The goal of MPC is to ensure that the voltage at the grid connection point on the device side is within the range of the next sampling time. k The voltage at the grid connection point on the equipment side (+1) accurately tracks the first voltage reference value. This ensures that the disturbance voltage signal is completely controllable, and the inverter measurement port on the equipment side exhibits low impedance characteristics.

[0151] Consider the filter capacitor branch of the inverter on the equipment side:

[0152] (1)

[0153] In the formula, For the current of the grounding capacitor branch d Axial components, For the current of the grounding capacitor branch q Axial components, C It is a grounding capacitor. R For grounding resistance, L For filtering inductors, t For time, It is the electric angular frequency. Voltage at the grid connection point on the equipment side d Axial components, Voltage at the grid connection point on the equipment side q Axial components, For the output current of new energy equipment d Axial components, For the output current of new energy equipment q Axial components, For the output voltage of the inverter on the equipment side d Axial components, For the output voltage of the inverter on the equipment side q Axial components;

[0154] After discretizing equation (1) using the difference equation, we obtain:

[0155] (2)

[0156] (3)

[0157] In the formula, The sampling time sequence number;

[0158] To achieve MPC control, that is, to achieve error-free tracking of the first voltage reference value at the next sampling time, the following must be satisfied:

[0159] (4)

[0160] In the formula, Output voltage at the grid connection point on the equipment side d Reference values ​​for axis components. Output voltage at the grid connection point on the equipment side q Reference values ​​for axis components;

[0161] Substituting equation (4) into equations (2) and (3) yields the result that satisfies the condition of zero-error tracking of the reference voltage at the grid connection point on the equipment side. and The intermediate voltage reference values ​​are defined as follows: and ;

[0162] (5)

[0163] In the formula, for d Reference value for intermediate voltage of shaft component. for q Reference value for intermediate voltage of shaft component. For the filter inductor current d Axial components, For the filter inductor current q Axial components, For inductive coupling, This is the first intermediate expression. This is the second intermediate expression. , Used to compensate for prediction errors:

[0164] ;

[0165] In the formula, It is a negative first power, representing the unit delay operator in a discrete system. The sampling period;

[0166] In impedance measurement, the inverter on the equipment side needs to superimpose the fundamental voltage and disturbance voltage signals at the grid connection point on the equipment side to construct a controllable first voltage reference value. The fundamental phase angle is obtained through a phase-locked loop. The three-phase signals are then transformed to the dq coordinate system to obtain the first reference voltage.

[0167] ;

[0168] In the formula, The first reference voltage, The fundamental voltage, This is a disturbance voltage signal;

[0169] A discrete prediction model for the inverter on the equipment side is established based on the dynamic equations of the LC filter. In each sampling period, the grid-connected voltage on the equipment side is predicted at the next moment using the current voltage and current state, and it is required to track the first voltage reference value without error. Under this constraint, the analytical control law for the inverter modulation can be directly derived, i.e., equation (5). The calculated... , Convert back to three-phase modulation signal , , The actual voltage is output via SVPWM to achieve error-free tracking. As a result, the inverter on the equipment side exhibits low impedance characteristics over a wide frequency range, ensuring that disturbance signals are applied completely to the device under test, thus achieving high-precision impedance measurement.

[0170] The process and approach of the weak grid voltage over-limit suppression method mentioned in this invention employs the voltage sensitivity standard deviation index to assess the weak nodes of the entire distribution network, with detailed calculation procedures. Under weak grid conditions, a calculation method is used to evaluate the sensitivity of active and reactive power to voltage using active and reactive power sensitivity deviation rate indices, with detailed calculation procedures. Furthermore, the "active power first, reactive power second" grid voltage over-limit suppression approach adopted after identifying a weak grid system, and the detailed voltage support scheme of the E-SOP device, are all within the protection scope of this invention.

[0171] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A weak grid online impedance measurement device based on energy storage intelligent soft switch, characterized in that, It includes an energy storage intelligent soft switch, measuring equipment, and auxiliary equipment; the energy storage intelligent soft switch includes an equipment-side inverter, a grid-side inverter, and an energy storage module. The equipment-side inverter and the grid-side inverter are respectively connected to both sides of the DC bus in a symmetrical wiring manner, and the energy storage module is connected to the DC bus. The measuring device is used to measure the fundamental frequency, collect first and second electrical energy data, obtain a control signal based on the first electrical energy data and the fundamental frequency, obtain a first harmonic impedance amplitude based on the control signal, the first electrical energy data, the energy storage module, and the grid-side inverter, obtain a disturbance voltage signal based on a multi-sine voltage signal, the fundamental frequency, and the second electrical energy data, and obtain a second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical energy data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude. The first power data is the power data of the grid-connected point on the grid side, the second power data is the power data of the grid-connected point on the equipment side, the first harmonic impedance amplitude is the harmonic impedance amplitude of the grid, and the second harmonic impedance amplitude is the harmonic impedance amplitude of the new energy equipment. The auxiliary equipment is used to inject the multi-sine voltage signal into the inverter on the equipment side.

2. The online impedance measurement device for weak grids based on energy storage intelligent soft switching according to claim 1, characterized in that, When the second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second power data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude, the charging and discharging control strategy of the energy storage module is VDCM network control.

3. The online impedance measurement device for weak grids based on energy storage intelligent soft switching according to claim 1, characterized in that, The measuring equipment includes a first measuring device and a second measuring device; the first measuring device is integrated on the grid-side inverter, and the second measuring device is integrated on the equipment-side inverter. The first measuring device is used to measure the fundamental wave, to collect the first power data, to obtain a control signal based on the first power data and the fundamental wave, and to obtain the first harmonic impedance amplitude based on the control signal, the first power data, the energy storage module and the grid-side inverter. The second measuring device is used to measure the fundamental wave, to collect the second electrical energy data, to obtain the first harmonic impedance amplitude, to obtain a disturbance voltage signal based on the multi-sine voltage signal, the fundamental wave, and the second electrical energy data, and to obtain a second harmonic impedance amplitude based on the disturbance voltage signal, the second electrical energy data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

4. The online impedance measurement device for weak grids based on energy storage intelligent soft switching according to claim 3, characterized in that, The first measuring device includes a first acquisition unit, a first calculation unit, a proportional-integral controller, a pulse width modulation module, and a second calculation unit; The first acquisition unit is used to measure the fundamental frequency and to acquire or update the first power data; The first calculation unit is used to perform Clark transformation on the first electrical quantity data to obtain first intermediate data, to perform Fast Fourier Transform on the first intermediate data to obtain second intermediate data, to set the resistance of each harmonic, to obtain reference values ​​of each harmonic current based on the voltage of each harmonic and the resistance of each harmonic, to obtain the difference of each harmonic current based on the current of each harmonic and the reference values ​​of each harmonic current, and to perform inverse Park transform on each harmonic to obtain each harmonic control quantity based on the phase of each harmonic and the intermediate control quantity; the second intermediate data includes the voltage of each harmonic, the current of each harmonic, and the phase of each harmonic. The proportional-integral controller is used to obtain intermediate control quantities based on the differences in harmonic currents. The pulse width modulation module is used to obtain the control signal based on the control quantities of each harmonic and the fundamental frequency, and to apply the control signal to the grid-side inverter based on the energy storage module. The second calculation unit is used to collect the updated first power data and to obtain the first harmonic impedance amplitude based on the updated first power data using the least squares method.

5. The online impedance measurement device for weak grids based on energy storage intelligent soft switching according to claim 3, characterized in that, The second measuring device includes a second acquisition unit, a signal execution unit, a third calculation unit, and a fourth calculation unit; The second acquisition unit is used to measure the fundamental wave, to acquire or update the second electrical data, and to obtain the amplitude of the first harmonic impedance. The signal execution unit is used to apply the updated disturbance signal to the device-side inverter in a series injection manner; The third calculation unit is used to obtain the Parker transform input angle based on the fundamental frequency, to obtain a first voltage reference value based on the fundamental frequency and the multi-sine voltage signal, to obtain a first voltage reference value based on the fundamental frequency and the disturbance voltage signal, to perform a Parker transform on the second electrical data based on the Parker transform input angle to obtain third intermediate data, to obtain an intermediate voltage reference value based on the first voltage reference value and the third intermediate data, and to perform an inverse Parker transform on the intermediate voltage reference value based on the Parker transform input angle to obtain the disturbance voltage signal; the first voltage reference value is the output voltage reference value at the next sampling time of the grid connection point on the equipment side; The fourth calculation unit is used to perform a Fourier transform on the second power data to obtain fourth intermediate data, and to obtain the second harmonic impedance amplitude based on the fourth intermediate data, the energy storage intelligent soft switch and the first harmonic impedance amplitude.

6. A method for online impedance measurement of a weak grid based on an energy storage-type intelligent soft switch, implemented using the online impedance measurement device for a weak grid based on an energy storage-type intelligent soft switch as described in any one of claims 1-5, characterized in that, include: Collect the first power data and the second power data; measure the fundamental frequency; The control signal is obtained based on the first power data and the fundamental frequency. The first harmonic impedance amplitude is obtained based on the control signal, the first power data, the energy storage module, and the grid-side inverter; Inject the multi-sine voltage signal into the inverter on the device side; The disturbance voltage signal is obtained based on the multi-sine voltage signal, the fundamental wave, and the second electrical quantity data; The second harmonic impedance amplitude is obtained based on the disturbance voltage signal, the second power data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

7. The online impedance measurement method for weak grids based on energy storage intelligent soft switching according to claim 6, characterized in that, Obtaining the control signal based on the first power data and the fundamental frequency includes: The first power data is subjected to Clark transformation to obtain the first intermediate data; The first intermediate data is subjected to a fast Fourier transform to obtain the second intermediate data; the second intermediate data includes the voltage, current and phase of each harmonic. Set the resistance values ​​for each harmonic; The reference values ​​of each harmonic current are obtained based on the voltage and resistance of each harmonic. The difference between each harmonic current is obtained based on the amount of each harmonic current and the reference value of each harmonic current. The intermediate control quantity is obtained based on the difference between the harmonic currents of each order. The harmonic control quantities are obtained by performing Park inverse transform based on the phase of each harmonic and the intermediate control quantity. The control signal is obtained based on the control quantities of each harmonic and the fundamental frequency.

8. The online impedance measurement method for weak grids based on energy storage intelligent soft switching according to claim 7, characterized in that, The first harmonic impedance amplitude is obtained based on the control signal, the first power data, the energy storage module, and the grid-side inverter, including: Step S11: Based on the energy storage module, apply the control signal to the grid-side inverter; Step S12: Update the first power data, and obtain the control signal again based on the updated first power data and the fundamental wave, and repeat steps S11-S12; Step S13: Based on the least squares method, obtain the first harmonic impedance amplitude according to the updated first electrical charge data.

9. The online impedance measurement method for weak grids based on energy storage intelligent soft switching according to claim 6, characterized in that, Obtaining the disturbance voltage signal based on the multi-sine voltage signal, the fundamental frequency, and the second electrical quantity data includes: Step S21: Let the multi-sinusoidal voltage signal be the current disturbance signal; obtain the Parker transform input angle based on the fundamental wave; Step S22: Obtain a first voltage reference value based on the current disturbance signal and the fundamental frequency. The first voltage reference value is the output voltage reference value at the next sampling moment of the grid connection point on the equipment side. Step S23: Perform a Parker transformation on the second electrical quantity data based on the Parker transformation input angle to obtain the third intermediate data; Step S24: Obtain an intermediate voltage reference value based on the first voltage reference value and the third intermediate data; Step S25: Based on the Parker transform input angle, perform an inverse Parker transform on the intermediate voltage reference value to obtain the disturbance voltage signal; Step S26: Set the disturbance voltage signal to the current disturbance signal, and repeat steps S22-S25.

10. The online impedance measurement method for weak grids based on energy storage intelligent soft switching according to claim 9, characterized in that, Obtaining the second harmonic impedance amplitude based on the disturbance voltage signal, the second power data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude includes: The disturbance voltage signal is applied to the device-side inverter in a series injection manner; Update the second battery level data; The updated second power data is subjected to Fourier transform to obtain the fourth intermediate data; The second harmonic impedance amplitude is obtained based on the fourth intermediate data, the energy storage intelligent soft switch, and the first harmonic impedance amplitude.

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