Networking type converter performance detection device suitable for new energy and energy storage

Abstract

The invention discloses a performance detection device for a network construction type converter suitable for new energy and energy storage, and relates to the field of power conversion equipment testing. The automatic test unit comprises a frequency adjustment test module, a phase jump test module, a short circuit ratio adjustment test module, a broadband harmonic injection test module, an island simulation test module, a source load switching test module and a damping test module. Compared with an existing test platform, the precision in the aspects of frequency, phase, short-circuit ratio adjustment and the like is improved, and the precision of a test result is ensured; testing of various complex working conditions such as isolated island operation, source load switching and broadband harmonic injection is supported, and all key working conditions possibly encountered by the power conversion system in practical application can be simulated; the system has an automatic testing function, various tests are automatically carried out through preset working conditions, a detailed analysis report is generated, and manual intervention is reduced.

Description

Technical Field

[0001] The present invention relates to the field of power conversion equipment testing, and in particular to a performance testing device for a grid-type converter suitable for new energy and energy storage. Background Art

[0002] In today's power systems, power conversion systems (PCSs) are key components that play an indispensable role in microgrid and smart grid applications. As energy systems evolve toward decentralization, decarbonization, and intelligentization, PCS equipment plays a crucial role in integrating, dispatching, and managing distributed energy resources.

[0003] However, existing technologies still have shortcomings in PCS testing methods, particularly in the ability to accurately test key functions such as islanding operation, frequency dynamic response, short-circuit ratio adjustment, and harmonic injection. Current test systems struggle to accurately simulate complex grid conditions, especially those with rapid frequency and phase changes. This makes it difficult to fully evaluate the dynamic response and performance of the PCS, resulting in a mismatch between test results and actual grid operation.

[0004] Currently, no effective solutions have been proposed for the problems in related technologies. Summary of the Invention

[0005] To address the challenges of related technologies, this invention proposes a performance testing device for grid-connected converters suitable for renewable energy and energy storage applications. This device addresses the existing challenge of insufficient simulation of complex grid operating conditions. This device enables high-precision simulation of actual grid operation and comprehensive testing of the dynamic response and stability of PCSs under various operating conditions. This device provides precise test results, particularly under complex conditions such as islanding, frequency hopping, short-circuit ratio adjustment, and broadband harmonic injection.

[0006] To this end, the specific technical solutions adopted in the present invention are as follows:

[0007] A performance testing device for a grid-connected converter suitable for new energy and energy storage, the device comprising an automated testing unit for automatically performing a frequency regulation test, a phase jump test, a short-circuit ratio adjustment test, a broadband harmonic injection test, an islanding simulation test, a source-load switching test, and a damping test according to preset test conditions. The automated testing unit comprises a frequency regulation test module, a phase jump test module, a short-circuit ratio adjustment test module, a broadband harmonic injection test module, an islanding simulation test module, a source-load switching test module, and a damping test module.

[0008] The frequency regulation test module is used to simulate the grid voltage frequency based on piecewise linear change control and joint software and hardware control, combined with cascade delay filtering technology and differential operation detection frequency method. The simulated grid voltage frequency is input into the grid-type converter to evaluate the frequency response characteristics of the grid-type converter.

[0009] Phase jump test module, used to simulate grid phase jump parameters using phase angle control technology, and input the simulated grid phase jump parameters into the grid-forming converter to test the dynamic response capability of the grid-forming converter under phase jump conditions;

[0010] The short-circuit ratio adjustment test module is used to simulate the voltage characteristics of the output port of the grid performance evaluation platform through power electronics. It combines virtual impedance control technology and pulse width modulation drive control technology to adjust the short-circuit ratio parameter. The short-circuit ratio parameter is input into the grid-type converter to evaluate the dynamic response and stability of the grid-type converter under different grid strengths.

[0011] The broadband harmonic injection test module is used to generate harmonic signals through a digital frequency synthesizer, adjust the harmonic parameters in combination with the pulse width modulation strategy, and test the harmonic anti-disturbance performance of the grid-type converter through the harmonic parameters;

[0012] The island operation simulation module is used to physically isolate the main grid from the grid-connected converter using a physical isolation device, and to verify the stability of the grid-connected converter in island mode.

[0013] The source-load switching test module is used to select the optimal control method based on the five-loop control strategy to perform seamless switching between the source and the load, and to evaluate the dynamic response characteristics during the seamless switching between the source and the load;

[0014] The damping test module is used to adjust damping parameters and perform frequency sweep tests. It also uses a grid-type control strategy to simulate the dynamic behavior of the power grid under different damping conditions and evaluate the dynamic response characteristics and stability of the grid-type converter.

[0015] Furthermore, the frequency regulation test module includes a piecewise linear change control module, a joint regulation module, a differential frequency detection module and a cascade delay filtering module;

[0016] The segmented linear change control module is used to control the rate of change of the grid voltage and frequency using a ramp control method;

[0017] The joint control module is used to control the accuracy of the grid voltage and frequency by using a digital-to-analog converter, combined with digital operation and digital signal processing technology;

[0018] The differential frequency detection module is used to calculate the real-time voltage frequency based on the differential frequency detection method and the three-phase ideal voltage signal of the power grid as input;

[0019] The cascade delay filtering module is used to eliminate high-order harmonic components in the grid voltage by using the cascade delay filtering technology.

[0020] Furthermore, according to the differential frequency detection method, the three-phase ideal voltage signal of the power grid is used as input, and the real-time voltage frequency is calculated to include:

[0021] Obtain the grid voltage signal and decompose it to obtain a symmetrical, balanced and harmonically distorted three-phase voltage;

[0022] The three-phase voltage is subjected to Clarke transformation, amplitude normalization, and differential processing, i.e., filtering, in sequence, and when the voltage amplitude reaches a preset value, the voltage real-time frequency is obtained.

[0023] Furthermore, the cascade delay filtering technology is used to eliminate the high-order harmonic components in the grid voltage, including:

[0024] Several delay elimination filter modules are combined in a cascade manner, and the current value, rotation factor and the value before the delay are used to calculate the frequency component elimination in the relevant coordinate system.

[0025] Furthermore, the phase jump test module includes a main program module, a full comparison unit interrupt module, a capture unit interrupt module, a first digital signal processing module, a first sensor module and a suppression circuit module;

[0026] The main program module is used to initialize system parameters, start the pulse width modulation control module, and enter the real-time control mode. The system parameters include duty cycle and phase reference value.

[0027] The full comparison unit interrupt module is used to trigger the interrupt service subroutine when the value of the comparison register matches the counter; the duty cycle is adjusted according to the previous three-phase duty cycle control signal, and the grid phase is regulated by adjusting the duty cycle;

[0028] The capture unit interrupt module is used to detect the rising edge of the synchronization signal of the input phase voltage and the output voltage, and calculate the phase difference of the synchronization signal; according to the comparison result of the phase difference and the reference phase angle, the control parameters are dynamically adjusted;

[0029] The first digital signal processing module is used to update the phase difference according to the change of the input phase voltage signal, and ensure the regulation of the output voltage amplitude and phase by adjusting the duty cycle of the front stage and the rear stage;

[0030] A first sensor module is used to monitor the state of the output signal and feed back the state data to the first digital signal processing module;

[0031] The suppression circuit module is used to ensure the waveform quality of the output voltage by passing the filter and harmonic suppression circuit in both the front stage and the back stage.

[0032] Furthermore, the short circuit ratio adjustment test module includes a second sensor module and a second digital signal processing module;

[0033] The second sensor module is used to collect parameters of the meshed converter, including voltage data and current data of the meshed converter.

[0034] The second digital signal processing module is used to calculate the short-circuit ratio of the current power grid in real time based on the collected grid-type converter parameters, and compare the short-circuit ratio of the current grid-type converter with the target short-circuit ratio; when it is detected that the short-circuit ratio of the current grid-type converter deviates from the target short-circuit ratio, it dynamically outputs a pulse width modulation signal to control the impedance adjustment device to adjust the short-circuit ratio of the current grid-type converter to the target short-circuit ratio.

[0035] Furthermore, the broadband harmonic injection test module includes a harmonic signal output module and a harmonic injection module;

[0036] Among them, the harmonic signal output module is used to transmit the harmonic table data, fundamental wave parameters, and amplitude gain configuration data to the programmable logic device based on the digital frequency synthesizer to calculate and generate the digital harmonic signal;

[0037] The harmonic injection module is used to control the frequency and amplitude of the harmonics using a pulse width modulation strategy, and dynamically adjust the pulse width modulation strategy using the monitoring output signals of the voltage and current sensors.

[0038] Furthermore, the island operation simulation module includes an island state identification module and an island simulation module;

[0039] The islanding state identification module is used to identify the islanding state and initiate the islanding control strategy using a multi-parameter joint analysis method, and the multi-parameter joint analysis method includes frequency change rate and voltage phase drift detection technology;

[0040] The island simulation module is used to simulate the island operation mode of the grid-connected converter using AC circuit breakers, output circuit breakers, inverters and filter circuits.

[0041] Furthermore, based on the five-loop control strategy, the optimal control method is selected to perform seamless switching between sources and loads, including:

[0042] Obtaining a first set, where the elements of the first set include the control quantity output value of the source current loop and the control quantity output value of the source power loop; obtaining a minimum value of the first set by comparing the elements of the first set;

[0043] Obtain a second set, where the elements of the second set include the control quantity output value of the load current loop and the control quantity output value of the load power loop; obtain the maximum value of the second set by comparing all elements in the second set;

[0044] The voltage loop control quantity is obtained, and the optimal control quantity is selected from the minimum value of the first set, the maximum value of the second set, and the voltage loop control quantity by comparison, and seamless switching between the source and the load is performed based on the selected optimal control quantity.

[0045] Furthermore, obtaining a voltage loop control quantity, selecting an optimal control quantity from the minimum value of the first set, the maximum value of the second set, and the voltage loop control quantity by comparing the values, and performing seamless switching between the source and the load based on the selected optimal control quantity includes:

[0046] If the minimum value of the first set > the voltage loop control value > the maximum value of the second set, the voltage loop control value is selected as the optimal control value;

[0047] If the minimum value of the first set ≤ the maximum value of the second set > the voltage loop control variable, the maximum value of the second set is selected as the optimal control variable;

[0048] If the voltage loop control quantity is greater than or equal to the minimum value of the first set and the maximum value of the second set, the minimum value of the first set is selected as the optimal control quantity;

[0049] If the voltage loop control quantity ≤ the maximum value of the second set ≥ the minimum value of the first set, then the minimum value of the first set is selected as the optimal control quantity; if the maximum value of the second set ≥ the minimum value of the first set ≥ the voltage loop control quantity, then the maximum value of the second set is selected as the optimal control quantity;

[0050] When the comparison result satisfies the condition that the maximum value of the second set > the voltage loop control amount > the minimum value of the first set, an alarm signal is generated.

[0051] Furthermore, the frequency response characteristics of the grid-connected converter are evaluated including:

[0052] Acquire frequency response evaluation data of a grid-connected converter simulating grid voltage and frequency input within a preset time interval, wherein the frequency response evaluation data includes converter output voltage amplitude, converter input voltage amplitude, converter maximum frequency response time, converter output phase, and converter input phase;

[0053] Combining the frequency response evaluation data with a frequency response reference value obtained from a preset database to obtain a converter frequency response parameter, wherein the converter frequency response parameter is used to quantitatively evaluate the degree of compliance of the frequency response characteristics of the grid-type converter, and the frequency response reference value includes a reference maximum phase response deviation and a reference maximum frequency response time;

[0054] comparing the frequency response parameter of the converter with a preset frequency response threshold range obtained from a preset database, and not performing frequency response characteristic optimization if the frequency response parameter of the converter is within the preset frequency response threshold range;

[0055] If the converter frequency response parameter exceeds the preset frequency response threshold range, frequency response characteristic optimization is performed, and the converter frequency optimization parameter after the frequency response characteristic optimization is obtained. The converter frequency optimization parameter is used to quantitatively evaluate the effect of the frequency response characteristic optimization.

[0056] Furthermore, obtaining the converter frequency optimization parameters after performing frequency response characteristic optimization includes:

[0057] Acquiring frequency optimization evaluation related data after performing frequency response characteristic optimization, wherein the frequency optimization evaluation related data includes optimized converter frequency response parameters, converter output power, converter input power, and maximum optimized frequency deviation;

[0058] The converter frequency optimization parameters are obtained based on the maximum initial frequency deviation, frequency optimization evaluation related data and the optimal reference frequency response parameters obtained from a preset database.

[0059] Furthermore, the evaluation of the dynamic response and stability of the grid-connected converter under different grid strengths includes:

[0060] Acquiring short-circuit ratio test-related data after inputting the short-circuit ratio parameter into the grid-type converter, wherein the short-circuit ratio test-related data includes short-circuit ratio, output voltage stability, phase angle deviation, and power factor;

[0061] The converter short-circuit ratio test parameters are obtained by combining the short-circuit ratio related data and the test reference data obtained from the preset database. The converter short-circuit ratio test parameters are used to quantitatively evaluate the dynamic response and stability compliance of the grid-type converter under different grid strengths. The test reference data includes the test reference optimal data and the test evaluation weight.

[0062] The test reference optimal data includes reference optimal output stability, reference optimal phase angle deviation and reference optimal power factor;

[0063] The test evaluation weights include a voltage fluctuation evaluation weight, a phase deviation evaluation weight, and a power factor evaluation weight.

[0064] The beneficial effects of the present invention are:

[0065] (1) The present invention has high precision and high reliability: compared with the existing test platform, it improves the accuracy of frequency, phase, short-circuit ratio adjustment, etc., ensuring the accuracy of the test results.

[0066] (2) The present invention has comprehensive testing functions: it supports testing of various complex working conditions such as island operation, source-load switching, and broadband harmonic injection, and can simulate all key working conditions that the power conversion system may encounter in actual applications.

[0067] (3) The present invention is automated and intelligent: the detection device has an automated testing function, automatically performs various tests through preset working conditions, and generates detailed analysis reports, reducing manual intervention.

[0068] (4) The present invention has a numerical evaluation of the degree of compliance of the frequency response characteristics of the grid-type converter: by obtaining the frequency response evaluation data of the grid-type converter input by simulating the grid voltage and frequency within a preset time interval, and then combining the frequency response evaluation data with the frequency response reference value obtained from a preset database to obtain the converter frequency response parameters, a more accurate evaluation of the degree of compliance of the frequency response characteristics of the grid-type converter is achieved.

[0069] (5) The present invention has a numerical evaluation of the frequency response characteristic optimization effect: by obtaining frequency optimization evaluation related data after performing frequency response characteristic optimization, and then obtaining the converter frequency optimization parameters based on the maximum initial frequency deviation, the frequency optimization evaluation related data and the optimal reference frequency response parameters obtained from the preset database, a more accurate evaluation of the frequency response characteristic optimization effect is achieved.

[0070] (6) The present invention has a numerical evaluation of the dynamic response and stability of the grid-type converter under different grid strengths: obtaining short-circuit ratio test related data after the grid-type converter is input through the short-circuit ratio parameter, and then obtaining the converter short-circuit ratio test parameters based on the short-circuit ratio related data and the test reference data obtained from the preset database, thereby achieving an improvement in the accuracy of the dynamic response and stability evaluation of the grid-type converter under different grid strengths. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0072] Figure 1This is a principle block diagram of a performance detection device for a grid-connected converter suitable for new energy and energy storage according to an embodiment of the present invention;

[0073] Figure 2 It is the voltage space vector αβDSCn operation diagram;

[0074] Figure 3 is the frequency response graph of αβDSC4;

[0075] Figure 4 is a flow chart of the cascade αβDSC;

[0076] Figure 5 It is the frequency detection block diagram;

[0077] Figure 6 This is a flow chart for judging whether to interrupt when the full comparison unit is interrupted;

[0078] Figure 7 It is a schematic diagram of node voltage variation;

[0079] Figure 8 It is the control system block diagram.

[0080] In the picture:

[0081] 1. Frequency adjustment test module; 2. Phase jump test module; 3. Short-circuit ratio adjustment test module; 4. Broadband harmonic injection test module; 5. Island simulation test module; 6. Source-load switching test module; 7. Damping test module. DETAILED DESCRIPTION

[0082] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They 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. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0083] According to an embodiment of the present invention, a performance testing device for a grid-connected converter suitable for renewable energy and energy storage is provided. This device relates to a device for testing power conversion systems (PCSs) in power systems, and more particularly, to a test system for evaluating the performance of grid-connected PCSs. This device can be applied to performance verification and dynamic response analysis in scenarios such as microgrids, energy storage systems, and islanded grid operations.

[0084] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Figure 1As shown, according to an embodiment of the present invention, a grid-type converter performance detection device suitable for new energy and energy storage includes an automated testing unit for automatically performing a frequency regulation test, a phase jump test, a short-circuit ratio adjustment test, a broadband harmonic injection test, an islanding simulation test, a source-load switching test, and a damping test according to preset test conditions. The automated testing unit includes: a frequency regulation test module 1, a phase jump test module 2, a short-circuit ratio adjustment test module 3, a broadband harmonic injection test module 4, an islanding simulation test module 5, a source-load switching test module 6, and a damping test module 7;

[0085] The frequency regulation test module 1 is used to simulate the grid voltage frequency based on piecewise linear change control and software and hardware joint control, combined with cascade delay filtering technology and differential operation detection frequency method. The simulated grid voltage frequency is input into the grid-type converter to evaluate the frequency response characteristics of the grid-type converter.

[0086] Phase jump test module 2 is used to simulate the grid phase jump parameters by using phase angle control technology, and input the simulated grid phase jump parameters into the grid-forming converter to test the dynamic response capability of the grid-forming converter under phase jump conditions;

[0087] The short-circuit ratio adjustment test module 3 is used to simulate the voltage characteristics of the output port of the grid performance evaluation platform through power electronics. It combines virtual impedance control technology and pulse width modulation drive control technology to adjust the short-circuit ratio parameter. The short-circuit ratio parameter is input into the grid-type converter to evaluate the dynamic response and stability of the grid-type converter under different grid strengths.

[0088] The broadband harmonic injection test module 4 is used to generate harmonic signals through a digital frequency synthesizer, adjust the harmonic parameters in combination with a pulse width modulation strategy, and test the harmonic anti-disturbance performance of the grid-type converter through the harmonic parameters;

[0089] The island operation simulation module 5 is used to physically isolate the main grid from the grid-connected converter using a physical isolation device, and to verify the stability of the grid-connected converter in the island mode;

[0090] The source-load switching test module 6 is used to select the optimal control method to perform seamless switching between the source and the load based on the five-loop control strategy, and to evaluate the dynamic response characteristics during the seamless switching between the source and the load;

[0091] The damping test module 7 is used to adjust the damping parameters and perform frequency sweep tests, and use the grid-type control strategy to simulate the dynamic behavior of the power grid under different damping conditions to evaluate the dynamic response characteristics and stability of the grid-type converter.

[0092] In order to facilitate understanding of the above technical solutions of the present invention, the above technical solutions of the present invention are further explained below from the perspectives of architecture and principle.

[0093] This invention provides high-precision testing of PCSs under a variety of complex grid conditions (such as frequency variations, phase jumps, islanding, short-circuit ratio adjustment, and broadband harmonic injection), ensuring that test results accurately reflect the device's performance in actual operation. It also simulates seamless source-load switching and islanding operation, realistically reproducing the dynamic response and stability of PCSs during grid switching, thus providing technical support for reliability and safety assessments of PCS devices in practical applications. The modules of this invention include the following.

[0094] 1. Frequency Regulation Module

[0095] It can simulate grid frequency variations, supporting a frequency range of 40-60Hz with an accuracy adjustable to 0.001Hz, enabling precise control of the frequency rate of change. This method is used to test the inertia and damping of PCS equipment. This invention proposes a high-precision voltage-frequency control method that combines αβCDSC filtering technology with a differential frequency detection method, enabling high-precision frequency testing of PCS equipment. Using a high-precision digital signal processor (DSP) control coupled with a digital-to-analog converter (DAC), precise frequency rate of change control is achieved through piecewise linear variation control. Tests demonstrated a simulated frequency range of 40-60Hz, a frequency error of ±0.001Hz, and a simulation compliance of 99.98%. These results demonstrate that the system's frequency regulation is within the required accuracy of 0.001Hz, and the simulation results highly meet expected standards. Multi-stage filtering is performed on the voltage-frequency feedback signal to enhance the stability and accuracy of frequency control. Its accuracy is adjustable to 0.001Hz, with a stability of ±0.001Hz, ensuring that the entire loop remains stable during frequency testing.

[0096] In the frequency adjustment module, high-precision frequency testing methods include:

[0097] Multi-stage αβCDSC filtering algorithm technology is used: after multi-stage filtering of the voltage frequency feedback, the voltage frequency value is more stable and accurate, which can make the loop more stable.

[0098] High-precision frequency control algorithm: adopts piecewise linear change control and ramp control method to accurately control the frequency change rate. This method is particularly suitable for simulating gradual changes in grid frequency, thereby controlling with a precise frequency change rate (such as 0.001Hz / s).

[0099] Joint control of software and hardware: Using high-precision DAC hardware, combined with digital computing methods and high-speed DSP computing resources and its CPLD (CPLD is a digital integrated circuit with logic functions constructed by users according to their own needs) for control, the detected frequency delay can be extremely small and the accuracy is extremely high; and the frequency change can be accurately controlled within the expected change rate.

[0100] Specific implementation method: High-precision frequency control is achieved through high-precision detection algorithm feedback, and accurate sine wave signals are synthesized through digital signal processing (DSP) technology. A digital-to-analog converter (DAC) outputs a high-resolution frequency signal, enabling frequency adjustment to an accuracy of 0.001Hz.

[0101] This paper proposes a high-precision voltage-frequency method that combines αβCDSC filtering technology with differential frequency detection. This method, implemented on a DSP28335 processor and combining digital computation with high-speed computing resources, minimizes the detected frequency delay and achieves high accuracy. The method first utilizes differential frequency detection under ideal three-phase grid voltage conditions. Then, using the filter principle of a single-stage delay filter to eliminate interference in a two-phase stationary coordinate system and the multi-stage αβCDSC frequency response, a clean and precise frequency is derived.

[0102] This module first uses the differential frequency detection method. Under ideal grid voltage conditions, the symmetrical, balanced and harmonic-free three-phase voltage is:

[0103]

[0104] Among them, V +1 is the amplitude of the positive sequence component of the fundamental wave, is the primary phase, ω is the fundamental angular frequency, and t is time. Clark transformation is performed on Equation (1) to obtain the components of the three-phase voltage in the two-phase stationary coordinate system αβ:

[0105]

[0106] Equation (2) can be regarded as a space vector of voltage, which rotates counterclockwise with ω. Perform amplitude normalization:

[0107]

[0108] Then, differentiate both ends of equation (3):

[0109]

[0110] Compared with the phase, the grid frequency fluctuates around the power frequency and changes slowly, which can be approximately considered as a DC component. A first-order low-pass filter is used to filter out the AC component in equation (6):

[0111]

[0112] Among them, ω p is the cutoff frequency, and its value must take into account both filtering capability and speed. s is the Laplace operator. is the normalized value of the α-axis voltage at time t+1, is the normalized value of the β-axis voltage at time t+1, is the α-axis voltage measured at time t-1, It represents the β-axis voltage measured at time t-1.

[0113] In summary, the above calculation process can be used as a real-time frequency detector when the three-phase ideal voltage signal is used as input, which is symmetrical, balanced, has no harmonic distortion and has an amplitude of 1pu.

[0114] Then, the fundamental positive sequence component is separated by cascade delay filtering. In reality, the power grid is often not an ideal sine wave under various influences. The grid voltage has a lot of high-order harmonic components, and the two phases also contain a lot of high-order clutter. Therefore, before accurately detecting the grid voltage, it is necessary to use cascade delay filtering technology to eliminate these high-order harmonic components, that is, from V αβ Separate The delay elimination filter DSC technology uses the current value, rotation factor and the value before the delay moment to perform simple mathematical operations in a two-phase stationary coordinate system to selectively eliminate specific frequency components. n The expression is:

[0115]

[0116] Where: v αβ (t) is the current voltage value; is the voltage vector rotation factor; v αβ (tT / n) is the value at the moment T / n before, and T is the power frequency cycle of the power grid. Figure 2 , if the voltage in the αβ system is taken as a rotating space vector, Equation (8) converts the space vector V before T / n into αβ (tT / n) rotates 2π / n clockwise, when n is 4, αβDSC n Eliminate certain frequency components. Figure 2 middle, The voltage vector at time t is usually represented in the α-β stationary coordinate system.

[0117] The frequency domain transfer function corresponding to formula (8) is:

[0118]

[0119] When T=0.02s, n=4, αβDSC n Frequency response, such as Figure 3 As shown, αβDSC n At (4k-1) times the fundamental frequency, there is a notch point with a cancellation effect, while at (4k+1) times the fundamental frequency, its size is retained, that is, the holding point (k is a positive or negative integer). Different values ​​of n will result in different positions of the notch point and the holding point. It should be noted that h is a negative value, which represents the negative sequence component of the harmonic, corresponding to V α Hysteresis V β The phase is 90°. is a transfer function with time-delay characteristics. Harmonic order is the harmonic order, |IGDSC4(ω)|pu is the amplitude-normalized dynamic signal compensator, and φ(ω)° is the phase angle.

[0120] Single αβDSC n The amplification factor of each frequency component is less than or equal to 1, which can eliminate some redundant frequency components without amplifying other harmonic components. Therefore, multiple αβDSC modules can be combined in a cascade manner to form an αβCDSC, which eliminates harmonics layer by layer. Only the original fundamental wave is left, such as Figure 4 As shown, It is the voltage prediction value after passing through the multi-stage dynamic compensation module.

[0121] Finally, the voltage frequency detection method using delay elimination filtering is based on the principle of combining the advantages of αβCDSC filtering and differential operation, including the frequency detection scheme of the pre-stage delay elimination filtering, such as Figure 5 As shown in the figure, after the three-phase voltage is transformed by Clark, the two-phase grid voltage signal is subjected to αβCDSC pre-stage filtering in the αβ system to separate the fundamental positive sequence component. After the amplitude is normalized, the frequency signal is obtained by applying equations (4)-(7). Figure 5 In, v abc is the three-phase voltage, v α is the shaft voltage, v β is the shaft voltage, v apu is the normalized α-axis voltage, v βpu is the normalized β-axis voltage, ω p is the cutoff frequency, s is the Laplace operator, is the angular velocity.

[0122] It should be added that the specific steps for evaluating the frequency response characteristics of the grid-type converter are as follows: obtaining frequency response evaluation data of the grid-type converter simulating the grid voltage and frequency input within a preset time interval, the frequency response evaluation data including the converter output voltage amplitude, converter input voltage amplitude, converter output phase, converter maximum frequency response time and converter input phase; combining the frequency response evaluation data with the frequency response reference value obtained from the preset database to obtain the converter frequency response parameters, the converter frequency response parameters are used to quantitatively evaluate the degree of compliance of the grid-type converter frequency response characteristics, the frequency response reference value includes the reference maximum phase response deviation and the reference maximum frequency response time; comparing the converter frequency response parameters with the preset frequency response threshold range obtained from the preset database, if the converter frequency response parameters are within the preset frequency response threshold range, the frequency response feature optimization is not performed; if the converter frequency response parameters exceed the preset frequency response threshold range, the frequency response feature optimization is performed, and at the same time, the converter frequency optimization parameters after the frequency response feature optimization are obtained, and the converter frequency optimization parameters are used to quantitatively evaluate the effect of the frequency response feature optimization.

[0123] The method to obtain the frequency response parameters of the converter is as follows:

[0124]

[0125] Where Gf represents the frequency response parameter of the converter, m represents the number of times the grid voltage and frequency are input to the grid-forming converter within a preset time interval, m = 1, 2, ..., M, M represents the total number of times the grid voltage and frequency are input to the grid-forming converter within a preset time interval, V out (f) m It represents the output voltage amplitude of the converter of the mth simulated grid voltage and frequency input grid-type converter within the preset time interval, V in (f) m It represents the input voltage amplitude of the converter of the grid-type converter for the mth simulated grid voltage and frequency input within the preset time interval, It represents the output phase of the converter of the grid-connected converter for the mth simulated grid voltage and frequency input within the preset time interval. It represents the input phase of the converter of the grid-type converter for the mth simulated grid voltage and frequency input within the preset time interval, represents the reference maximum phase response deviation obtained from the preset database, T res represents the maximum frequency response time of the converter, and T′ represents the reference maximum frequency response time obtained from the preset database.

[0126] It should be understood that the converter output voltage amplitude, converter input voltage amplitude, converter output phase and converter input phase are obtained through the built-in voltage sensor and phase detector of the grid-type converter; the converter maximum frequency response time is obtained through simulation software such as MATLAB, and the maximum value of the difference between the historical converter output phase and the converter input phase collected is used to represent the reference maximum phase response deviation, and the maximum value of the historical converter maximum frequency response times collected is used to represent the reference maximum frequency response time.

[0127] Among them, the preset frequency response threshold range is set by professionals according to standards in the field, for example, the preset frequency response threshold range is set to 0.65 to 0.90; the frequency response characteristics are optimized through adaptive control algorithms (such as the minimum mean square error method to automatically adjust the gain parameters) and phase compensation technology (such as a lag compensator or a feedforward compensator to adjust the phase response), for example, by minimizing the mean square value of the error and updating the gain parameters according to the gradient descent method.

[0128] The frequency response parameters of the converter are used to quantitatively evaluate the degree of compliance of the frequency response characteristics of the grid-type converter. Specifically, the frequency response parameters of the converter include parameters from multiple aspects, and the various parameters are related to each other and do not exist independently. For example, as the maximum frequency response time of the converter increases, it indicates that the converter responds slowly to the input frequency and the amplitude adjustment process is relatively delayed, which leads to a decrease in the output voltage amplitude of the converter, and then causes the frequency response parameters of the converter to decrease accordingly; in addition, the increase in the maximum frequency response time of the converter also leads to a lag in the output phase of the converter, that is, the output phase of the converter is lagging behind the input phase of the converter. The difference increases, which leads to a decrease in the frequency response parameters of the converter. At the same time, as the maximum frequency response time of the converter decreases, the compliance degree of the frequency response characteristics of the grid-type converter increases, that is, the frequency response parameters of the converter increase accordingly. Therefore, considering the correlation and mutual influence between various factors, the frequency response parameters of the converter are obtained through comprehensive analysis, and the numerical evaluation of the compliance degree of the frequency response characteristics of the grid-type converter is realized. The compliance degree of the frequency response characteristics of the grid-type converter is judged through numerical evaluation, thereby achieving an improvement in the accuracy of the evaluation of the compliance degree of the frequency response characteristics of the grid-type converter.

[0129] Specifically, the specific steps for obtaining the frequency optimization parameters of the converter after executing the frequency response characteristic optimization are as follows: obtaining the frequency optimization evaluation related data after executing the frequency response characteristic optimization, the frequency optimization evaluation related data including the optimized converter frequency response parameters, converter output power, converter input power and maximum optimized frequency deviation; obtaining the converter frequency optimization parameters based on the maximum initial frequency deviation, the frequency optimization evaluation related data and the optimal reference frequency response parameters obtained from the preset database.

[0130] The method for obtaining the converter frequency optimization parameters is as follows:

[0131]

[0132] Where Gy represents the converter frequency optimization parameter, Gf' represents the optimized converter frequency response parameter, Gf y Represents the optimal reference frequency response parameter obtained from the preset database, P out Indicates the converter output power, P in represents the converter input power, Δf max,px Indicates the maximum initial frequency deviation, Δf max,py Indicates the maximum optimized frequency deviation.

[0133] It should be understood that the optimized converter frequency response parameters refer to the converter frequency response parameters after the frequency response characteristics are optimized, and the converter output power and converter input power are obtained through a power meter; the maximum optimized frequency deviation refers to the maximum value of the frequency deviation after the frequency response characteristics are optimized, and the maximum initial frequency deviation refers to the maximum value of the frequency deviation before the frequency response characteristics are optimized. The deviation between the input frequency and the output frequency obtained by the frequency monitor represents the frequency deviation, and the maximum value corresponding to the frequency deviation before and after the frequency response characteristics are optimized is obtained through the max function in the python library to obtain the maximum value of the frequency deviation. The optimal reference frequency response parameter is generally set to the middle value of the preset frequency response threshold range.

[0134] Specific assumptions: the optimal reference frequency response parameter is 0.8, and the maximum initial frequency deviation is 0.1 Hz. The converter frequency optimization parameters can be calculated using the above method. The statistical table of converter frequency optimization parameters changes is shown in Table 1:

[0135] Table 1 Statistics of changes in converter frequency optimization parameters

[0136]

[0137]

[0138] It can be seen from the data in the table that as the optimized converter frequency response parameters increase, the converter frequency optimization parameters also increase. At the same time, as the ratio of converter output power to converter input power increases, the converter frequency optimization parameters also increase. In addition, the maximum optimized frequency deviation also affects the converter frequency optimization parameters. Specifically, when the maximum initial frequency deviation is a fixed value (0.1 Hz), as the maximum optimized frequency deviation decreases, the converter frequency optimization parameters increase.

[0139] The converter frequency optimization parameters are used to quantitatively evaluate the effect of frequency response characteristic optimization. Among them, the changes in the optimized converter frequency response parameters, converter output power, converter input power and maximum optimized frequency deviation all have an impact on the converter frequency optimization parameters. Specifically, for example, as the optimized converter frequency response parameters increase, the converter frequency optimization parameters also increase. In addition, the converter frequency optimization parameters include parameters from multiple aspects, and the various parameters are related and do not exist independently. For example, as the optimized converter frequency response parameters increase, it indicates that the speed at which the converter responds to input power changes increases, thereby increasing the converter efficiency. As the ratio of the converter output power to the converter input power increases, the converter frequency optimization parameters also increase. At the same time, as the ratio of the converter output power to the converter input power decreases, it indicates that the converter efficiency decreases, which leads to an increase in the maximum optimized frequency deviation, and then the converter frequency optimization parameters decrease. Therefore, through quantitative means, the correlation and mutual influence between various factors are taken into account, and the converter frequency optimization parameters are obtained through comprehensive analysis, which realizes the numerical evaluation of the frequency response characteristic optimization effect. The frequency response characteristic optimization effect is judged through numerical evaluation, thereby achieving a more accurate evaluation of the frequency response characteristic optimization effect.

[0140] In practical applications, high-precision sampling and filtering algorithms enable high-precision closed-loop control of the frequency. Frequency detection under different power grid conditions is achieved. Results show that compared with traditional frequency detection and regulation methods, the regulation method of the present invention can improve system stability and reliability, with greater accuracy and faster response speed.

[0141] 2. Phase jump module

[0142] The phase jump module in the present invention is designed to simulate the phase change in the power grid, supporting a phase jump range of -60° to +60°, and an adjustment accuracy of up to 3°, so as to test the dynamic response capability of the power conversion system (PCS) under load changes, faults or other disturbance conditions, and achieve precise adjustment and rapid response to the phase under grid disturbance conditions. After testing, in the set phase angle range: -60° to +60°, the actual output phase angle deviation: ±0.8°, the phase control accuracy: within 0.8°, and the simulation compliance: 99.85%. The phase control achieved high-precision continuous adjustment in the test, and the phase simulation effect was good. The high-precision phase jump of this module is achieved through the following core features.

[0143] 2.1. ACCPA Technology Application

[0144] The module uses three-phase ACCPA (AC Constant Current Power Amplifier) ​​phase angle control technology to achieve phase angle jump control. This module uses three-phase ACCPA to ensure high-precision phase adjustment and jump control under various complex grid conditions. By independently controlling each phase and combining the duty cycle adjustment of the upstream and downstream stages, the three-phase ACCPA enables rapid and precise phase jump control within the set range.

[0145] The core of three-phase ACCPA technology lies in the independent and synchronized control of each phase. By precisely controlling each single-phase ACCPA within the three-phase system, the output waveform of each phase can be independently adjusted in phase angle and amplitude, thereby ensuring the symmetry and stability of the entire three-phase system. In practical applications, this independent control capability is crucial for responding to various grid disturbances, as each phase can be dynamically adjusted according to grid conditions to ensure overall system balance and stability.

[0146] 2.2 High-precision software control

[0147] The control system uses the TMS320F28335 chip as its core. A closed-loop control program for the three-phase AC / DC phase angle is developed using C language, and a high-performance control board is fabricated to precisely manage phase transitions. Precise software control enables rapid and accurate phase transitions, ensuring dynamic response speed and control accuracy during phase changes. Through real-time calculation and closed-loop adjustment, the control system responds to input signal changes in a fraction of a second and maintains a stable output voltage phase.

[0148] 2.3 Specific implementation of high-precision phase jump

[0149] Three single-phase ACCPAs can form a three-phase ACCPA group. Since each phase is independent and unrelated to each other, the three-phase ACCPA group can adjust the duty cycle d of the front and rear stages of each phase ACCPA. y1x 、D y2x (x = a, b, c, the same below), a three-phase AC voltage source with asymmetric amplitude and phase can be converted into a three-phase AC voltage source with completely symmetrical amplitude and phase, and the amplitude and phase can be adjusted independently and continuously. To simplify the analysis, it is assumed that the circuit components are ideal and consistent in each phase, the low-frequency voltage drop of Lf1 and Lf2 and the fundamental voltage drop of the third harmonic trap are ignored, and the input phase voltage u is assumed to be ia 、u ib 、u ic The three-phase ideal positive sequence sinusoidal symmetry is shown.

[0150] In the three-phase ACCPA group, the front stage duty cycle d y1xAdding the double frequency AC component and considering the three-phase phase relationship, we can know that d y1a d y1b d y1c The initial phase angle of is 120° in reverse order, that is:

[0151]

[0152] Among them, the coefficients k0 and k2 are non-negative real numbers, and β2 is d y1a The initial phase angle of u ix and d y1x The corresponding multiplication is to obtain the output phase voltage u of the three-phase front-stage Buck AC converter o1x (u o1x Contains the third harmonic voltage component u 3x and fundamental voltage component u 1x , and u 3x After being filtered out by the third harmonic trap, u is obtained across the front-stage output capacitor Cf1. 1x ), whose expression is:

[0153]

[0154] Where U 1m 、U 3m u 1x 、u 3x The amplitude of u 1a 、u 3a The phase angle, U 1m 、 U 3m 、 The relationship with the control parameters k0, k2, and β2 is:

[0155]

[0156] The three-phase fundamental voltage component u of the front stage 1a 、u 1b 、u 1c The amplitude is equal, and the phase angle difference is 120°; the third harmonic voltage component u 3a 、u 3b 、u 3c Equal, that is, u 3a =u 3b =u 3c Therefore, the output line voltage u of the three-phase front-stage Buck AC converter is o1ab 、u o1bc 、u o1ca , the voltage between points A2, B2, and C2 is:

[0157]

[0158] Among them, a, b, and c represent three transformation modules. o1ab 、u o1bc 、u o1ca There is no third harmonic voltage component in the circuit, only the fundamental voltage component, and the three-phase positive sequence sine is symmetrical, which is equal to the voltage between A3, B3 and C3 respectively. Therefore, the three-phase ACCPA group does not need a third harmonic trap. If there is no third harmonic trap, when the duty cycle D y2a =D y2b =D y2c , then the output line voltage of the subsequent stage is also three-phase positive sequence sinusoidal symmetry, but the output phase voltage of the subsequent stage contains third harmonic voltage components.

[0159] The three Boost AC converters in the rear stage are replaced by a three-phase Boost AC converter, and the three third-harmonic traps in the front stage are omitted (that is, points X2 and X3 of each phase are combined into one point, X=A, B, C), resulting in a three-phase ACCPA circuit topology without a third-harmonic trap.

[0160] If the duty cycle D of the subsequent three-phase Boost AC converter y2 is a constant, Uom is the amplitude of the output phase voltage, and o is u oa The phase angle is the phase difference between the output line voltage and the input line voltage. The output line voltage of the three-phase ACCPA circuit is:

[0161]

[0162] The amplitude gain k of the three-phase ACCPA output voltage relative to the input voltage is g and phase shift The same as single-phase ACCPA, its expression is:

[0163]

[0164] Therefore, the phase angle of the three-phase ACCPA output voltage is determined by the duty cycle d y1x Control, its amplitude is determined by the duty cycle D of the subsequent stage y2 (Combined with d y1x ) control, that is, the phase angle and amplitude of the three-phase ACCPA output voltage can be adjusted independently and continuously. om is the output voltage amplitude, U im Including U 1m 、U 2m and U 3m , U 1m 、U 2m and U 3m They are the three input voltage amplitudes.

[0165] To further improve the accuracy of phase jumps, the present invention employs a dynamic adjustment strategy based on high-frequency sampling. Specifically, the system samples the voltage of each phase at high frequency and inputs the sampled signals into the DSP for real-time analysis. By meticulously measuring and analyzing the phase difference, the DSP can dynamically adjust control parameters to minimize phase error, making the phase jump process more accurate and smoother. The ratio of the sampling frequency to the control frequency is carefully designed to ensure timely response to phase jump commands under all circumstances, thereby avoiding grid instability caused by phase changes.

[0166] 2.4 Phase jump control strategy

[0167] The front stage of the three-phase ACCPA uses three single-phase Buck AC converters to control the phase of the output voltage. By sampling the input phase voltage, a zero comparator is used to generate positive and negative polarity signals, and the phase difference between the output voltage and the input voltage is calculated by the DSP controller. The DSP controller compares the detected phase difference with the set reference phase and adjusts the control parameters in real time to dynamically adjust the front stage duty cycle signal (d y1a d y1b d y1c ), thereby achieving precise phase jump.

[0168] Specifically, the DSP controller detects positive and negative changes in the input phase voltage, compares the preset reference phase angle with the actual measured phase angle, and then automatically adjusts the control parameters based on the comparison result, allowing the output voltage phase angle to quickly converge to the target value. This control strategy ensures that the system's output phase maintains high accuracy and stability despite load changes or grid fluctuations.

[0169] To achieve dynamic phase jump control, the DSP controller uses a predictive control algorithm (Model Predictive Control, MPC). MPC predicts future phase change trends based on historical phase data and current system status and adjusts control parameters in advance of sudden phase changes, thereby achieving seamless phase jumps. This predictive control significantly reduces the potential for transient oscillations during phase jumps, ensuring high system stability despite frequency and phase changes.

[0170] 2.5 Algorithm Implementation

[0171] The three-phase ACCPA phase closed-loop control algorithm primarily consists of a main program and five interrupt service subroutines. The main program initializes the system and sets various parameters, including duty cycle and phase reference value. After the system is powered on, the main program first initializes the system, starts the PWM control module, and enters real-time control mode.

[0172] The main function of the interrupt service subroutine is to handle phase measurement and dynamic adjustment of duty cycle, including:

[0173] Full comparison unit interrupt (CMP1, CMP2, CMP3): When the comparison register value matches the counter, the interrupt service subroutine is triggered to calculate and generate the three-phase duty cycle control signal (d y1a d y1b d y1c ) and adjust the duty cycle to achieve the purpose of phase regulation.

[0174] Capture unit interrupt (CAP1, CAP3): Captures the synchronous signals of the input phase voltage and the output voltage. By detecting the rising edge of these signals, the phase difference (such as φs = φo = φ1) is calculated and compared with the reference phase angle. The DSP controller dynamically adjusts the control parameters k0 and k2 according to the comparison result, thereby controlling the starting duty cycle d y1a d y1b d y1c .

[0175] Through these interrupt service subroutines, the system can capture the phase information of input and output in real time and dynamically adjust the control parameters so that the phase difference between the output phase voltage and the input phase voltage remains within the set range, achieving high-precision phase jump control.

[0176] In addition, the DSP controller continuously updates the phase difference based on changes in the input signal and ensures independent and continuous regulation of the output voltage amplitude and phase by adjusting the duty cycle of the upstream and downstream stages, thereby ensuring symmetry and harmonic suppression of the three-phase output. The entire control system, with a high-performance DSP at its core, achieves precise phase control of the three-phase ACCPA group through rapid calculation and feedback regulation.

[0177] like Figure 6 As shown, Figure 6 This is a flow chart for judging whether to interrupt when all comparison units are interrupted.

[0178] 2.6 System Hardware Architecture and Implementation Details

[0179] The hardware of the present invention includes the modules of the three-phase ACCPA and the related control and detection circuits. Specifically, it includes:

[0180] PWM drive circuit: drives the switch tube of each phase ACCPA through high-precision PWM signals, controls the duty cycle of the front and rear stages, and realizes independent adjustment of phase and amplitude.

[0181] Current and voltage sensors are installed at the output of each phase of the ACCPA to monitor the output signal in real time and feed the data back to the DSP controller. Sensor accuracy directly affects the effectiveness of phase control, so high-precision, low-noise current / voltage sensors are selected to ensure the accuracy of the feedback signal.

[0182] Filtering and harmonic suppression circuit: Both the front and rear stages are equipped with LC filters and harmonic suppression circuits to ensure the waveform quality of the output voltage, reduce harmonic interference, and further improve the power quality of the system.

[0183] In practical applications, the system adjusts to phase changes in a very short time through high-frequency sampling and rapid control response. The entire control process is based on real-time detection and dynamic adjustment, and through the collaborative work of hardware and software, high-precision phase jump control is achieved. Through this sophisticated design, the present invention can achieve stable and rapid control of the phase angle and amplitude of three-phase AC voltage in various complex power grid environments.

[0184] 3. Short-circuit ratio adjustment module

[0185] The short-circuit ratio adjustment module in this invention simulates the voltage characteristics of the output port of the network performance evaluation platform through power electronics to support the performance evaluation of the power conversion system (PCS) under different strong and weak grid conditions. The short-circuit ratio adjustment range is adjustable between 1.2 and 50. This module can verify the dynamic response capability and stability of the PCS in weak grid conditions. The core features of this module include the following:

[0186] 3.1 Short circuit ratio adjustment function

[0187] The short-circuit ratio adjustment module, implemented through power electronics, allows precise control of the system's short-circuit ratio. Specifically, this module allows the short-circuit ratio to be adjusted over a wide range of conditions, from strong to weak grids (for example, from a short-circuit ratio of 50 to 1.2), simulating varying grid stiffness conditions. During the adjustment process, changes in the short-circuit ratio affect the system's damping characteristics and stability, particularly in weak grid conditions, significantly impacting the PCS's voltage support capability.

[0188] 3.2 High-precision control implementation

[0189] The short-circuit ratio adjustment module uses the TMS320F28335 as its core control device. It achieves precise adjustment of the short-circuit ratio through a combination of PWM drive control and virtual impedance adjustment. The DSP controller collects system voltage and current information in real time and dynamically adjusts the system's virtual impedance parameters based on the set short-circuit ratio target. With an adjustment accuracy of 0.01, it ensures that output characteristics meet expectations under different short-circuit ratios.

[0190] To improve the accuracy of short-circuit ratio regulation, this invention employs a dynamic regulation strategy based on closed-loop feedback. By monitoring the system's current and voltage changes in real time, the DSP controller accurately determines the current short-circuit ratio state and adjusts the corresponding virtual impedance value based on the measurement results, ensuring short-circuit ratio accuracy and system stability.

[0191] 3.3 Short-circuit ratio jump control strategy

[0192] This module designs a short-circuit ratio jump control strategy that can quickly switch between different short-circuit ratio states to simulate the short-circuit ratio changes that may be encountered in actual power grids. When the system needs to jump the short-circuit ratio, the DSP controller adjusts the relevant impedances through PWM modulation based on the current system state and the target short-circuit ratio value, thereby achieving a rapid jump in the short-circuit ratio.

[0193] During short-circuit ratio changes, the DSP controller uses a predictive control algorithm to predict the system's dynamic response in advance and adjusts damping and reactive power compensation appropriately during the change, ensuring the system returns to a stable state within a short period of time. This control strategy effectively improves system stability in weak grid conditions and ensures safe operation of the power conversion system under different short-circuit ratio conditions.

[0194] 3.4 Specific implementation of short-circuit ratio adjustment through power electronics

[0195] The short-circuit ratio adjustment module in this invention uses power electronics control strategies to simulate the voltage characteristics of the output port of the network performance evaluation platform to achieve adjustment for different short-circuit ratios. The specific implementation combines multiple advanced power electronics control strategies, including virtual impedance control, PWM modulation, circulating current control, voltage feedforward, and current feedback, to achieve grid simulation under different short-circuit ratios.

[0196] 3.5 Virtual Impedance Control

[0197] Virtual impedance control (VIC) is a method that modulates the impedance characteristics of the converter output terminal by introducing a virtual impedance into the power electronics control system, thereby simulating the equivalent impedance of the power grid. This can significantly affect the converter's output voltage characteristics, thereby enabling precise adjustment of the short-circuit ratio.

[0198] In power electronics control, the implementation of virtual impedance relies on the calculation and regulation of voltage drop. By adding virtual resistance and inductance to the voltage control loop, the system can simulate grid states with different impedance characteristics. The principle formula is as follows:

[0199] The relationship between the output voltage and current is: Vout = Vref - (Rv + jωLv) Iout.

[0200] Where Vout is the converter output voltage, Vref is the reference voltage, Rv is the virtual resistance, Lv is the virtual inductance, ω is the system angular frequency, and Iout is the output current. By adjusting the values ​​of Rv and Lv, the system's equivalent output impedance can be changed, thereby achieving precise control of the short-circuit ratio.

[0201] The main advantages of virtual impedance control include:

[0202] Flexible impedance adjustment: Virtual impedance control can quickly adjust the converter's equivalent impedance through software without changing physical components. This flexibility allows the system to adapt to the needs of different grid environments. In particular, in weak grids, it can improve system stability by increasing the equivalent impedance.

[0203] Enhance the system's anti-interference ability: By properly adjusting the virtual resistance Rv, the system's oscillation can be effectively suppressed, increasing the system's damping effect, thereby enhancing the system's anti-interference ability in the face of grid disturbances. Especially in weak grid environments, the virtual impedance can play a significant role in voltage support.

[0204] Optimizing dynamic response: Adjusting the virtual inductance (Lv) can be used to optimize the converter's dynamic response. When the load changes rapidly, increasing the virtual inductance can smooth the current response and reduce current overshoot, thereby improving system stability and dynamic response.

[0205] In the specific implementation, the DSP controller collects the output current of the converter in real time and calculates the corresponding voltage drop based on the set virtual impedance parameters. This voltage drop determines the final output voltage Vout through the difference with the reference voltage Vref. By continuously adjusting the values ​​of the virtual resistance and inductance, the control system can dynamically adjust the output characteristics to simulate the voltage characteristics under different short-circuit ratio conditions in the power grid, such as Figure 7 As shown, where SCR-U is the voltage stability margin.

[0206] The introduction of this virtual impedance control method not only reduces reliance on physical hardware but also improves the system's adaptability and flexibility, becoming a key means of achieving efficient short-circuit ratio regulation. This allows the power conversion system to better adapt to dynamic changes in the grid, ensuring stable operation under various grid rigidity conditions.

[0207] 3.6 PWM modulation strategy

[0208] PWM pulse width modulation regulation is the key to achieving converter output voltage control. The amplitude and phase of the output voltage are controlled by adjusting the duty cycle of the PWM signal.

[0209] Vector control method: Using the vector control method, the amplitude of the output voltage is controlled by adjusting the direct-axis component Vd and quadrature-axis component Vq of the reference voltage vector: By changing Vd and Vq, the amplitude and phase characteristics of the output voltage can be affected, thereby affecting the output virtual impedance performance and indirectly adjusting the short circuit ratio (SCR).

[0210] 3.7 Short-circuit ratio adjustment based on circulating current

[0211] In parallel converters, circulating current control can also be used to adjust the short-circuit ratio. In parallel converters, a circulating current controller is introduced to adjust the circulating current magnitude Ic, thereby affecting the equivalent output impedance and achieving flexible adjustment of the short-circuit ratio.

[0212] 3.8 Current Feedback and Voltage Feedforward Control

[0213] Voltage feedforward control: Voltage feedforward is used to enhance the system's response to grid disturbances by measuring the output voltage and introducing it into the controller for feedforward regulation:

[0214] Vff=Kff(Vref-Vout)

[0215] By adjusting the feedforward coefficient Kff, the system's dynamic response to voltage disturbances can be improved.

[0216] Current feedback control: Sample the output current and adjust the output impedance characteristics through the current loop:

[0217] Ierr=Iref-Iout

[0218] Where Iref is the reference current. By changing the current feedback coefficient, the system impedance can be effectively affected and the short-circuit ratio can be precisely adjusted.

[0219] 3.9 DSP program algorithm implementation

[0220] The control algorithm of the short-circuit ratio adjustment module mainly includes: initialization setting, interrupt service subroutine and dynamic adjustment process.

[0221] Initialization settings: After the system is powered on, the DSP controller is initialized first, including setting the initial short-circuit ratio, impedance adjustment parameters and feedback control parameters.

[0222] Interrupt Service Subroutine: When the system detects that the short-circuit ratio needs to be adjusted, the interrupt service subroutine is triggered. This subroutine dynamically calculates the required impedance adjustment by comparing the current short-circuit ratio with the set value and outputs a PWM signal to control the impedance adjustment module.

[0223] Dynamic adjustment process: During the short-circuit ratio adjustment process, the DSP controller monitors the current, voltage and impedance status in the system in real time, determines the changing trend of the short-circuit ratio, and dynamically adjusts the control signal to ensure that the system can respond to sudden changes in the power grid in a timely manner.

[0224] 3.10 System Hardware Architecture and Implementation Details

[0225] The hardware part of the short-circuit ratio adjustment module includes an adjustable impedance component (such as a controllable inductor), a current and voltage sensor, and a PWM drive circuit connected to a DSP controller.

[0226] Adjustable Impedance Components: Dynamic adjustment of the short-circuit ratio is achieved through controllable reactors or other types of impedance adjustment devices. The adjustment range of the reactor is carefully designed to cover various possible conditions in the power grid, thereby adapting to different testing requirements.

[0227] High-precision current and voltage sensors: used to monitor the current and voltage status of the system in real time. The data accuracy of the sensor is crucial to the effect of short-circuit ratio adjustment. Therefore, high-precision measurement sensors are selected to ensure the accuracy of the feedback signal.

[0228] PWM drive circuit: The adjustable impedance is controlled by PWM drive. The PWM signal output by DSP is modulated according to the adjustment requirements to achieve precise adjustment of the short-circuit ratio.

[0229] 3.11 Dynamic Feedback and Closed-Loop Control

[0230] To ensure accurate short-circuit ratio regulation, this module uses a combination of dynamic feedback and closed-loop control. The DSP controller continuously collects system voltage, current, and other grid parameters, calculates the current short-circuit ratio in real time, and compares it with the target short-circuit ratio. If a deviation is detected, the system dynamically adjusts the PWM signal to change the resistance of the controllable resistor, rapidly adjusting the short-circuit ratio to the target value.

[0231] This closed-loop feedback control strategy enables the system to respond quickly to changes in grid parameters, especially when encountering sudden load changes or grid disturbances. The system can complete adjustments in a short time to ensure the safe and stable operation of the power conversion system.

[0232] The 10MW grid performance evaluation platform, for devices under test (DUTs) with a rated capacity of less than 3.3MW, precisely controls the system's equivalent output impedance by adjusting the parameters of virtual resistance and virtual inductance. The short-circuit ratio can be adjusted between 1.2 and 50. Power electronics simulate the voltage characteristics of the platform's output port. Combining virtual impedance control technology with PWM drive control enables wide-ranging adjustment, from a minimum of 1.2 to a maximum of 50. During short-circuit ratio adjustment, damping and reactive power compensation are adjusted appropriately during transitions to achieve high stability. This allows for wide-ranging simulation of grid stability. This allows PCS performance evaluation to ensure stability under weak grid conditions. A closed-loop feedback control strategy is employed, coupled with a DSP controller to dynamically collect current and voltage information and adjust virtual impedance parameters in real time based on the set short-circuit ratio target value. This simulates grid strength.

[0233] The test was conducted under different short-circuit ratio conditions, gradually increasing the load and monitoring the voltage stability, phase angle change, power factor, response time, current harmonic content,

[0234] Short circuit ratio = 1.2, output voltage stability: ±1.5%, phase angle deviation: 1.2°, power factor: 0.95, dynamic response time: 60ms, current harmonic content (THD): 1.5%, simulation compliance: 97%.

[0235] Short circuit ratio = 5.0, output voltage stability: ±0.2%, phase angle deviation: 0.2°, power factor: 0.99, dynamic response time: 50ms, current harmonic content (THD): 1.1%, simulation compliance: 99.8%.

[0236] Short circuit ratio = 20, output voltage stability: ±0.1%, phase angle deviation: 0.05°, power factor: 0.995, dynamic response time: 30ms, current harmonic content (THD): 0.8%, simulation compliance: 99.9%.

[0237] Short-circuit ratio = 45, output voltage stability: ±0.02%, phase angle deviation: 0.01°, power factor: 0.999, dynamic response time: 10ms, current harmonic content (THD): 0.1%. Simulation compliance: 99.98%.

[0238] It should be added that the specific steps for evaluating the dynamic response and stability of the grid-type converter under different grid strengths are as follows: obtain the short-circuit ratio test related data after the short-circuit ratio parameter is input into the grid-type converter, and the short-circuit ratio test related data include short-circuit ratio, output voltage stability, phase angle deviation and power factor; obtain the converter short-circuit ratio test parameters based on the short-circuit ratio related data and the test reference data obtained from the preset database, and the converter short-circuit ratio test parameters are used to quantitatively evaluate the degree of compliance of the dynamic response and stability of the grid-type converter under different grid strengths. The test reference data include test reference optimal data and test evaluation weights; the test reference optimal data include reference optimal output stability, reference optimal phase angle deviation and reference optimal power factor; the test evaluation weights include voltage fluctuation evaluation weights, phase deviation evaluation weights and power factor evaluation weights.

[0239] The method for obtaining the converter short-circuit ratio test parameters is as follows:

[0240]

[0241] Where Gd represents the converter short-circuit ratio test parameter, SCR represents the short-circuit ratio, τ1 represents the voltage fluctuation evaluation weight, τ2 represents the phase deviation evaluation weight, τ3 represents the power factor evaluation weight, and U p Indicates output voltage stability, U′ p represents the reference optimal output stability obtained from the database, X p Indicates the phase angle deviation, X′ p represents the reference optimal phase angle deviation obtained from the database, G represents the power factor, and G′ represents the reference optimal power factor obtained from the database.

[0242] Specifically, the short-circuit ratio is obtained through a short-circuit test, the output voltage stability (i.e., the maximum percentage of voltage amplitude fluctuation) is obtained through power system simulation software (such as MATLAB / Simulink, PSCAD, etc.), the phase angle deviation is obtained through a phase measurement tool, and the power factor is obtained through a power meter.

[0243] Among them, the result of summing and averaging the collected historical output voltage stability represents the reference optimal output stability, the result of summing and averaging the collected historical phase angle deviations represents the reference optimal phase angle deviation, and the result of summing and averaging the collected historical power factors represents the reference optimal power factor.

[0244] The voltage fluctuation assessment weight, phase deviation assessment weight, and power factor assessment weight are obtained from a preset database, all ranging from [0, 1], and summing to 1. Specifically, the voltage fluctuation assessment weight, phase deviation assessment weight, and power factor assessment weight are used to reflect the degree of influence of the converter output voltage stability, phase angle deviation, and power factor on the converter short-circuit ratio test parameter. The corresponding weights are obtained by inputting the real-time converter output voltage stability, phase angle deviation, and power factor into a mapping set. The mapping relationship can be one-to-one or many-to-one.

[0245] The converter short-circuit ratio test parameters are used to quantitatively evaluate the dynamic response and stability of the grid-type converter under different grid strengths. Specifically, the converter short-circuit ratio test parameters include parameters in multiple aspects. The output voltage stability, phase angle deviation and power factor all have an impact on the converter short-circuit ratio test parameters. Specifically, as the degree of deviation between the output voltage stability, phase angle deviation and power factor and the corresponding test reference optimal data decreases, the converter short-circuit ratio test parameters increase accordingly. In addition, the various parameters are related and do not exist independently. For example, the phase angle deviation is usually caused by poor synchronization between the grid and the converter. As the phase angle deviation increases, that is, the degree of deviation between the phase angle deviation and the reference optimal phase angle deviation increases, which leads to a decrease in the power factor, that is, the degree of deviation between the power factor and the reference optimal power factor increases, which in turn leads to a decrease in the converter short-circuit ratio test parameters; therefore, through a quantitative approach, the correlation and mutual influence between various factors are taken into account, and the converter short-circuit ratio test parameters are obtained through comprehensive analysis, which realizes the numerical evaluation of the dynamic response and stability compliance of the grid-type converter under different grid strengths. Through numerical evaluation, the accuracy of the evaluation of the dynamic response and stability compliance of the grid-type converter under different grid strengths is improved.

[0246] Under various short-circuit ratio conditions, the system's voltage fluctuation and phase deviation are close to zero, and the power factor approaches 1.0, demonstrating excellent grid adaptability and interference immunity. As the short-circuit ratio increases, the system's voltage stability and phase angle accuracy significantly improve, demonstrating excellent grid simulation and interference immunity.

[0247] 4. Broadband Harmonic Injection Module

[0248] The broadband harmonic injection module of this invention accurately injects harmonic and interharmonic signals in the 2.5Hz to 2500Hz range to test the dynamic response and stability of power conversion systems (PCSs) under complex grid conditions. By integrating real-time data acquisition with high-precision voltage and current sensors and CPLD and DDS signal generation technology, the dynamic response and robustness of PCSs under complex grid conditions can be tested. This function is implemented through the following modules and steps.

[0249] 4.1. Obtaining harmonic amplitude compensation coefficient

[0250] During harmonic injection, the harmonic intensity and accuracy must be determined by calculating harmonic amplitude compensation coefficients. This is accomplished by the DSP controller. The system first collects the output signal in real time using high-precision voltage and current sensors. It then calculates compensation coefficients for each harmonic and interharmonic amplitude based on real-time load changes. These compensation coefficients ensure that the harmonic amplitudes of the output signal meet the desired targets.

[0251] 4.2 Determining harmonic formula and signal generation

[0252] Next, based on the output bit identifier and amplitude compensation coefficient of the current harmonic, the DSP controller determines the specific generation formula for the harmonic or interharmonic to be injected. The harmonic formula includes parameters such as the amplitude, frequency, and phase of the fundamental wave and each harmonic. Harmonics are sinusoidal waves, and a standard sinusoidal wave signal can be expressed as follows:

[0253] f(t)=Asin(2πf0t+θ0)

[0254] Among them, A is the amplitude information of the sinusoidal signal, f0 is the frequency information, and θ0 is the phase information. When multiple sinusoidal signals are superimposed:

[0255] f(t)=A0sin(2πf0t+θ0)+A1sin(2πf1t+θ1)+...+A n sin(2πf n t+θ n )

[0256] Compensate for high-frequency harmonics, and the waveform formula obtained by compensation is as follows:

[0257] f(t)=Kf0A0sin(2πf0t+θ0)+...+K n A n sin(2πf0t+θ n )

[0258] Where K n is the coefficient of the nth harmonic.

[0259] The system will refer to the harmonic formula and parameters to calculate the waveform data table for subsequent harmonic signal generation. Since multiple harmonics are superimposed, the required nth harmonic can be directly selected from the system. Assuming that the system supports the output of up to 10 harmonics, each harmonic is superimposed and output, and the output bit mark can be externally controlled, the harmonic measurement formula is as follows:

[0260] f(t)=Kf0A0sin(2πf0t+θ0)+Kf1A1sin(2πf1t+θ1)+...+K 10 A 10 sin(2πf 10 t+θ 10 )

[0261] 4.3. Waveform data calculation and gain coefficient configuration

[0262] According to the harmonic formula and amplitude compensation coefficient, the system generates the wave table data of the current harmonic inside the DSP. The data contains the frequency, amplitude and phase information of the signal to guide subsequent signal generation.

[0263] Frequency control word calculation: Ki = 2N*fi / fs.

[0264] Among them, Ki is the frequency control word of the th harmonic, N is the bit width of the phase accumulation module, fi is the frequency of the th harmonic, and fs is the clock frequency of the CPLD.

[0265] Initial phase word calculation: Pi = 2M*θi / 360.

[0266] Wherein, Pi is the initial phase word of the i-th harmonic in the harmonic signal, M is the bit width of the phase addition module, and θi is the initial phase of the i-th harmonic in the harmonic signal.

[0267] The system obtains the appropriate amplitude configuration gain factor, which is used to adjust the overall signal amplitude to meet the harmonic output requirements. The gain factor is calculated based on the amplitude of the fundamental waveform and the system's grid interference conditions to ensure the accuracy of harmonic injection.

[0268] 4.4 Data configuration to CPLD and DDS signal generation

[0269] The harmonic table data, fundamental wave parameters, and amplitude gain configuration data obtained from the above calculations are transferred to a programmable logic device (CPLD), which is responsible for combining and processing these data.

[0270] CPLD internal module specific implementation:

[0271] Phase accumulation module: used to accumulate the frequency control word on the rising edge of the clock pulse to generate a phase code, which is used to determine the reading position of the wave table data.

[0272] Phase addition module: adds the phase code of the phase accumulation module to the initial phase word to generate the read address of the wave table storage module in order to obtain the corresponding wave table data.

[0273] Wave table storage module: obtains the wave table data in the waveform memory according to the read address. The data represents the original waveform of the fundamental wave and each harmonic.

[0274] Amplitude multiplication module: multiplies the wave table data by the amplitude gain coefficient to generate each harmonic component.

[0275] Harmonic synthesis module: superimposes each harmonic component and finally synthesizes the harmonic signal.

[0276] The CPLD generates the final digital harmonic signal output through a direct digital synthesizer (DDS). The DDS's run flag and output flag ensure smooth signal output.

[0277] 4.5 PWM modulation strategy and inverter control

[0278] In order to achieve accurate harmonic injection, the system adopts PWM (pulse width modulation) strategy to control the frequency and amplitude of the harmonics.

[0279] PWM signal conditioning: DSP-generated PWM signals drive high-frequency switching devices such as IGBTs and MOSFETs. The PWM duty cycle is used to adjust the amplitude of harmonics and interharmonics. The system adjusts the PWM duty cycle and frequency in real time based on feedback, enabling rapid harmonic frequency switching within the 2.5Hz to 2500Hz frequency range.

[0280] Inverter control: Using a three-phase inverter structure, the CPLD controls the IGBT switches of each phase, achieving independent and precise control of each harmonic and interharmonic. The IGBT (Insulated Gate Bipolar Transistor) is a three-terminal semiconductor switching device.

[0281] 4.6 Real-time feedback and closed-loop control

[0282] During the harmonic injection process, the control system uses closed-loop control to maintain signal stability and accuracy.

[0283] Real-time monitoring and feedback: Use voltage and current sensors to monitor the output signal and feed the monitoring data back to the DSP to dynamically adjust the PWM frequency and duty cycle.

[0284] Closed-loop control algorithm: The DSP controller adjusts the harmonic generation parameters based on the feedback value to ensure that the output signal amplitude meets the target value.

[0285] 4.7. Filter Usage and Signal Quality Control

[0286] To remove high-frequency switching noise and ensure signal quality, the system adds an LC filter after the harmonic injection module. The filter uses adjustable inductance and capacitance to adapt to the needs of different frequency harmonics, thereby improving the clarity and quality of the harmonic output signal.

[0287] 4.8 System Integration and Optimization

[0288] The harmonic injection module of this invention is integrated with other regulation modules (such as the short-circuit ratio adjustment module and the virtual impedance module), and is uniformly coordinated and controlled by a DSP program to ensure overall system performance and accurate harmonic injection. During operation, PWM control parameters, filter characteristics, and harmonic generation strategies are continuously optimized to ensure stable operation under complex grid conditions.

[0289] Through this implementation, the harmonic injection module accurately generates harmonics and interharmonics in the 2.5Hz to 2500Hz range, enabling testing of the power system's response and robustness under complex conditions. The injection range for single harmonics is 0-8%, the total harmonics 0-15%, the single interharmonics 0-2%, and the total interharmonics 0-5%. Closed-loop control ensures harmonic injection stability and output signal quality. CPLD parallel computing and real-time data processing ensure system efficiency and responsiveness.

[0290] 5. Island simulation module

[0291] The present invention relates to an islanding operation simulation function module in a grid-type converter performance detection device suitable for new energy and energy storage, which is intended to test the anti-islanding capability and dynamic response characteristics of the power conversion system (PCS) in islanding mode. In islanding operation mode, after the system is disconnected from the main power grid, the converter needs to be independently powered to ensure the normal operation of the local load. This module uses a variety of technical means to achieve accurate simulation of the islanding mode, ensuring that the test of PCS equipment by the grid performance evaluation platform meets the conditions of actual grid islanding operation, as follows:

[0292] 5.1 Physical Implementation of Island Mode

[0293] The detection device uses a physical isolation device to completely separate the main grid from the system, thereby simulating the island mode. Specifically, a high-performance relay or circuit breaker is used to disconnect the main grid from the converter, so that the system only supplies power to the load through the internal power supply or inverter. The device integrates controllable loads and adjustable impedance (such as resistive loads and inductive loads) to accurately adjust electrical parameters to ensure stable power output after the main grid is disconnected. The physical isolation process monitors its operating status through a closed-loop control system and combines it with power electronic modules to ensure seamless transition and efficient operation of island switching.

[0294] 5.2. Dynamic response in simulated island mode

[0295] The island simulation module combines a DSP (digital signal processor) controller with a high-frequency inverter to achieve real-time, precise control of the system. During island operation, the DSP controller collects output voltage and frequency in real time and adjusts the inverter output using a pulse-width modulation (PWM) strategy to accommodate varying loads and electrical disturbances. In the event of sudden load changes or system failures, the DSP controller dynamically adjusts output parameters to ensure output voltage and frequency stability, accurately simulating the dynamic operating characteristics of island conditions.

[0296] 5.3 Virtual Impedance Control Technology

[0297] To better simulate islanding operation, the detection device incorporates virtual impedance control technology. This technology adjusts the converter's equivalent impedance to improve system stability in islanding mode. Virtual impedance control dynamically adjusts the system's equivalent impedance based on operating conditions by adding virtual resistance and inductance components to the control loop. This technology allows the system to better adapt to load changes while accurately simulating frequency and voltage fluctuations in islanding mode, ensuring that simulation results align with actual islanding conditions.

[0298] 5.4 Island Detection and Switching Mechanism

[0299] To ensure the accuracy of island simulation, the present invention integrates a variety of island detection technologies and automatic switching functions. When the main power grid is disconnected, the system quickly identifies the island state and initiates the island control strategy through technologies such as the rate of change of frequency (ROCOF) and voltage phase drift detection. The island detection module adopts a multi-parameter joint analysis method to improve the accuracy and rapid response capability of island detection. When the main power grid is reconnected, the system uses a synchronous control strategy to enable smooth switching between island mode and grid-connected mode, thereby ensuring system stability and operational continuity.

[0300] The present invention has highly flexible island simulation capabilities and supports testing under a variety of different load conditions (such as resistive loads, inductive loads, and mixed loads). By integrating multiple load modules, the system can simulate different types of island operation scenarios, including island mode startup and operation under unstable grid conditions. The system also supports online adjustment of operating parameters. Users can change the load parameters during island operation in real time according to experimental requirements, thereby comprehensively evaluating the PCS's island protection performance and ensuring its safe and stable operation under various complex grid conditions.

[0301] 5.5. Island Mode Hardware Principle

[0302] The device includes the following main components:

[0303] AC circuit breakers QF1 and QF2: used to connect the main grid and distributed power inverter respectively, and play the role of switching power supply.

[0304] Output circuit breakers KM1 and KM2: used to switch outputs in different test scenarios, ensuring that the device can be flexibly configured and adjusted for test connections according to experimental requirements.

[0305] Inverter and filter circuit:

[0306] Inverter Structure: Contains three bridge inverters consisting of 12 IGBTs, achieving DC to AC conversion through a three-phase bridge inverter. Filtering and Rectification Module: The inverter output is filtered through an LC filter to ensure that the output voltage waveform meets grid operating standards. A transformer is used for voltage adjustment and phase matching, ultimately forming a three-phase AC output (A1, B1, C1). Adjustable Load Module: Through controllable adjustable loads, such as RLC simulated loads, different types of grid operating environments are simulated, ensuring that the system can accurately evaluate its performance under different load conditions.

[0307] 5.6 Input Power Conversion

[0308] The input is a DC power source, which is first converted to AC by a bridge inverter. The inverted AC power then passes through an LC filter to remove high-frequency components and harmonics, resulting in a pure AC output. The filtered AC power is then isolated and converted by a transformer to achieve voltage level matching and ensure the safety of the system's ground voltage.

[0309] 5.7 Output and Load Regulation

[0310] After filtering and voltage transformation, AC power passes through circuit breaker KM2 and is connected to the test output terminals (A1, B1, and C1), providing a three-phase test voltage. The load section consists of a controllable RLC circuit. By adjusting the load resistance (R), inductance (L), and capacitance (C), the load characteristics of the power grid under different operating conditions can be simulated. This effectively tests the response characteristics of the distributed power supply to various loads in island mode.

[0311] 5.8 Conclusion

[0312] By integrating these multiple functions, the present invention's grid-connected converter performance testing device for renewable energy and energy storage can comprehensively and accurately simulate islanded operation, fully evaluating the dynamic response characteristics, stability, and anti-islanding capabilities of a PCS under grid islanding conditions. This precise simulation of islanded operation provides reliable technical support for power system security testing, particularly in microgrids and distributed power systems, providing a crucial testing method and tool for assessing system stability and security under islanding conditions.

[0313] 6. Source-load switching module

[0314] This module is a source-load seamless switching technology applicable to grid-type converter performance testing devices for renewable energy and energy storage, including methods, devices, systems, and media. Combining multi-loop control technology for the source current loop, source power loop, load current loop, load power loop, and voltage loop, it enables smooth current transitions and faster dynamic response during the system's switching between source and load power supply. This effectively addresses existing issues such as discontinuous current changes, control blind spots, and slow switching response speeds, thereby improving the converter's adaptability and reliability in complex application scenarios.

[0315] 6.1 Source-load seamless switching method

[0316] This invention proposes a method for achieving seamless source-load switching. The converter's control system includes five closed-loop control loops: voltage loop, source current loop, source power loop, load current loop, and load power loop. The unique feature of this invention is the use of an intelligent multi-loop selection algorithm to achieve seamless source-load switching in an optimal control manner. The specific implementation steps include:

[0317] Obtaining the First Set S: First, obtain the first set S, which consists of the control variable output values ​​of the source current loop and the source power loop. By comparing the elements of the set, the minimum value in the set is selected, denoted as Smin. This process determines the minimum control requirements for the source energy supply to ensure minimal power loss and maximum energy supply efficiency.

[0318] Obtaining the Second Set L: Next, obtain the second set L, which includes the control variable output values ​​of the load current loop and the load power loop. Compare all elements in the second set and find the maximum value, denoted as Lmax. This process aims to estimate the maximum demand when supplying energy to the load, ensuring optimal system stability and performance when supplying energy to the load.

[0319] Obtaining the voltage loop control variable Vloop: Then, the voltage loop control variable output value Vloop is obtained. The main function of the voltage loop is to maintain the stability of the converter output voltage and prevent voltage fluctuations from affecting the power supply quality.

[0320] Selecting the control variable: Smin, Lmax, and Vloop are compared, and based on the loop control selection algorithm, the optimal control variable is selected as the actual control variable output of the bidirectional DC-DC converter. This selection logic ensures smooth and seamless control variable conversion during source-load switching.

[0321] 6.2 Loop Control Selection Algorithm

[0322] In this invention, the loop control selection algorithm is the core of seamless source-load switching and determines the specific control loop selection to ensure the system outputs stable and accurate current and power during source-load switching. The selection logic is as follows:

[0323] If Smin>Vloop>Lmax, the output value of the voltage loop, Vloop, is selected as the actual control variable. In this case, the voltage loop provides a stable output voltage for the system.

[0324] If Smin≤Lmax>Vloop, the maximum value Lmax in the second set is selected to ensure stable energy supply of the system under maximum power demand.

[0325] If Vloop≥Smin>Lmax, the minimum value Smin in the first set is selected to meet the minimum control requirement of power supply and ensure stable operation of the system.

[0326] If Vloop≤Lmax≥Smin, then Smin is also selected to ensure the normal operation of the system under lower control quantity requirements.

[0327] If Lmax ≥ Smin ≥ Vloop, Lmax is selected to cope with high load demand and achieve stable energy supply.

[0328] 6.3 Abnormal alarm mechanism and response strategy

[0329] To further ensure system safety during source-load switching, the present invention also designs an abnormal state detection and alarm mechanism. When the comparison result meets the condition of Lmax>Vloop>Smin, the system will generate an alarm signal to inform the user of potential operational risks.

[0330] When an alarm signal is generated, the system enters protection mode, immediately stopping the bidirectional DC-DC converter to prevent equipment damage or load failure caused by inappropriate control switching. This design provides an additional layer of protection in high-risk scenarios, ensuring the safety and reliability of equipment and loads.

[0331] 6.4. Steps for obtaining the output value of the control quantity

[0332] The present invention describes in detail the process of obtaining the output value of each loop control variable, especially the specific steps in the source current loop, source power loop, load current loop, load power loop and voltage loop:

[0333] The control quantities of the source current loop and the source power loop are obtained.

[0334] Obtain the set value and feedback value of the source current or power: the control quantity is calculated through the error signal.

[0335] Perform PI (proportional-integral) operation on the error signal to obtain the initial control quantity.

[0336] The initial control quantity is limited and normalized: finally the output control quantity is obtained to ensure the accuracy and efficiency of the control.

[0337] Obtaining the control quantity of the load current loop and load power loop:

[0338] Obtain the set value and feedback value of the load current or power: obtain the initial control quantity through error calculation and PI operation.

[0339] Perform limiting and normalization processing to ensure that the output signal is stable within an appropriate range and ultimately obtain effective control output.

[0340] Voltage loop control quantity acquisition:

[0341] Obtain voltage set value and feedback value: After error calculation, the initial control value is obtained through PI operation.

[0342] Finally, limiting and normalization processing are performed to ensure the stability of the output voltage and avoid affecting the power supply quality due to voltage fluctuations.

[0343] 6.5 System Application and Innovation Value

[0344] The aforementioned technical approach enables efficient and seamless switching between source and load power supply, avoiding the control blind spots caused by sudden current changes in traditional control methods while effectively improving the system's response speed and stability. The source-load switching module of the present invention offers significant technical advantages and application value, particularly in scenarios requiring frequent switching of power supply modes, such as microgrids, electric vehicle charging stations, and distributed power systems.

[0345] This invention utilizes a multi-loop parallel control algorithm, operating five loops in parallel and alternately: the voltage loop, the source current loop, the source power loop, the load current loop, and the load power loop. These loops complement each other and create a synergistic effect. By directly comparing and selecting the controlled variables, this solution is independent of current direction judgment, effectively avoiding interference issues during peak current switching. The switching control process is smooth, responsive, and highly precise.

[0346] Source-load switching has been tested, with a switching time of less than 10 milliseconds, a fluctuation range of ±1 millisecond, and a simulation accuracy of 99.2%. Current surge is 7.5%, with a fluctuation range of ±2%, while the measured switching efficiency reaches 98.3%, with a simulation accuracy of 99.5%. Furthermore, harmonic distortion (THD) does not exceed 3.8%, with a simulation accuracy of 99.4%. Based on the high accuracy of these indicators, the overall simulation accuracy of the system reaches 99.3%. The system demonstrates excellent stability, fast response, and strong anti-interference capabilities.

[0347] 6.6. Expansion of Source-Load Switching Function

[0348] The source-load switching function is particularly suitable for islanded operation of a PCS system. By simulating the switching on and off of loads during islanded operation, the PCS's ability to maintain grid voltage and frequency stability and transient characteristics as a voltage source is assessed, thereby evaluating its networking capabilities. The network performance evaluation platform equipped with this function can function as both a voltage source and a load with adjustable load factors, with seamless switching between the two modes. It can simulate conditions where a large load is switched on simultaneously with a grid power outage, as well as the high-frequency switching of large loads during islanded operation, to test the PCS's networking capabilities.

[0349] 7. Damping control test module

[0350] A method and apparatus for testing the damping control performance of a grid-type power conversion system (PCS). The present invention evaluates the dynamic response characteristics and damping effect of the system by adjusting the damping coefficient and performing a sweep frequency test. An input quantity is given to the control module of the black box, the output quantity is examined, and the transfer function is inversely deduced, thereby giving different disturbances to verify the damping. This implements a damping control test, which is used to adjust the damping control parameters of the grid-type PCS. The dynamic response characteristics and damping effect of the system are evaluated through a sweep frequency test. Combined with the virtual synchronous machine (VSG) control strategy, the dynamic behavior of the power grid under different damping conditions is simulated, thereby testing the dynamic response and stability of the system under various working conditions. The specific implementation steps are as follows.

[0351] 7.1 Damping coefficient adjustment and frequency sweep test

[0352] First, the damping control parameters of the grid-type PCS are adjusted to optimize the system's damping characteristics. This process, similar to adjusting the damping winding of a synchronous generator, simulates the dynamic behavior of the power grid under different damping conditions, thereby testing the system's dynamic response under various operating conditions. Specifically, by gradually adjusting the damping coefficient of the grid-type PCS, the system's response characteristics under different damping conditions can be effectively observed, including dynamic parameters such as the system's transient process, steady-state error, and oscillation frequency.

[0353] In a grid-based test system, by adjusting the system's damping coefficient and voltage droop coefficient, stable grid operation can be achieved under various dynamic conditions. Based on harmonic balance and small-signal linearization methods, the relationship between positive and negative sequence harmonic voltage and current harmonic components is established.

[0354] Based on harmonic balance and small signal derivation, the current response corresponding to the injection of a small voltage signal of a specific frequency is obtained through the system circuit parameters, control structure and its rated working state, and the relationship between the positive and negative sequence harmonic voltages and the corresponding current harmonic components is established. The system harmonic linearization model that only considers small disturbance components is obtained, and then the voltage and current in the linearization model are divided to obtain the analytical expression of the positive and negative sequence impedance of the grid-connected inverter, thereby realizing the analysis of the system's small disturbance stability. It is suitable for deriving the influence of secondary coupling harmonics (double frequency coupling response) and establishing a mechanism model of equipment with harmonic coupling characteristics.

[0355] Qref-Q+(∣Vref∣-∣V∣)Dq=KsEm

[0356] According to the instantaneous power theory, the instantaneous output active power P and reactive power Q of the VSG can be calculated as:

[0357] P=1.5(vdid+vqiq)Q=1.5(vqid-vdiq)

[0358] Q=1.5(vqid-vdiq)Q=1.5(vdid-vdiq)

[0359] Qref is the reference value of reactive power, P and Q are active power and reactive power, respectively; |Vref|, |V|, and Em are the amplitudes of rated voltage, output voltage, and internal potential, respectively; Ks is the proportional gain in the system; vdid is the product of d-axis voltage and d-axis current; vqiq is the product of q-axis voltage and q-axis current; and Dq is the reactive power regulation gain.

[0360] The core of grid-based control lies in power synchronization. Grid-based control strategies primarily include droop control and virtual synchronous generator (VSG) control. Droop control achieves grid-based control by simulating the damping characteristics of synchronous generators. In practical applications, a low-pass filter (LPF) is often added to the front end to filter out high-order terms in the instantaneous power. The addition of the LPF imbues droop control with inertia characteristics. VSG control simulates the second-order motion equations of synchronous power devices, enabling more accurate simulation of synchronous generator operating characteristics. Based on the mathematical equations for the active and reactive power loops, VSG is equivalent to traditional droop control without considering inertia.

[0361] 7.2. Frequency Sweep Test and Transfer Function Solution

[0362] A swept frequency test records the PCS output response while gradually varying the input signal frequency (typically from low to high frequencies). The purpose of a swept frequency test is to evaluate the system's gain and phase response at different frequencies. To do this, first select a frequency range (for example, from 0.1 Hz to 1 kHz), then gradually increase the frequency in fixed increments (for example, 0.1 Hz) to obtain the system's magnitude-frequency response and phase-frequency response data.

[0363] During measurement, the system's input signal is typically a sinusoidal wave with adjustable amplitude and frequency. At each frequency point, the system's output voltage and current are recorded, and the system's dynamic characteristics are described using amplitude-frequency curves. Finally, a transfer function is used to describe the system's dynamic behavior in the frequency domain.

[0364] 7.3 Disturbance Signal Injection and System Response Analysis

[0365] To deeply analyze the system's dynamic performance and damping control effectiveness, known disturbance signals are applied to the black box control module. These disturbance signals can be unit step signals, sine waves, square waves, or random noise. The purpose is to stimulate the system's dynamic characteristics and test its stability and anti-disturbance capabilities.

[0366] The system's output signal time series is recorded in detail by the DSP. By comparing the input and output data, system identification techniques are used to derive the system's transfer function, describing the system's gain and phase variations at various frequencies. This transfer function not only reflects the system's dynamic behavior but can also be used to further evaluate the effectiveness of damping control. For example, the step response can reveal characteristics such as the system's transition time, overshoot, and steady-state error.

[0367] 7.4 Data Analysis and Parameter Optimization

[0368] The system's dynamic stability region and optimal damping coefficient are evaluated under different damping coefficients and disturbance conditions. Specifically, the system's damping control performance in complex power grid environments is evaluated by observing its dynamic characteristics, such as overshoot, oscillation decay rate, steady-state error, and frequency deviation.

[0369] Based on an in-depth analysis of these dynamic parameters, damping control parameters are optimized. By minimizing system overshoot and maximizing the damping ratio, the system controller's damping gain is adjusted to improve the dynamic response speed and overall stability of the networked PCS. Furthermore, by comparing different damping coefficients and the system's response characteristics, the optimal control parameter combination is determined, enabling the system to quickly recover and maintain stability under various sudden disturbances, ensuring system safety and reliability.

[0370] also, Figure 8 is the control system block diagram, Figure 8 in, urefdqq is the reference voltage signal, G2(s) is the compensation link, G1(s) is the current regulator, K pwm is the gain, i Ldq is the inductor current, i odq is the output current, u odq is the output voltage, ωL v is the inductor's counter electromotive force, R f is the filter resistor, L f s is the filter inductor, G f s is the filter transfer function.

[0371] The application areas of the present invention include:

[0372] Microgrid and Smart Grid: Used to test the operational stability of PCS equipment in a microgrid environment to ensure continued operation under conditions such as grid disconnection and load changes.

[0373] Energy storage system: used to test the interaction between the PCS and battery management system in the energy storage system, as well as the charging and discharging performance under grid frequency fluctuations and harmonics.

[0374] Power electronics and renewable energy power generation systems: In photovoltaic, wind power, and other systems, evaluate the dynamic response performance of PCS to ensure safe and stable operation under grid fluctuations or islanding conditions.

[0375] In summary, this invention proposes a systematic approach for effectively evaluating the damping control performance of a grid-based PCS. This approach ensures that the system exhibits excellent damping characteristics under complex grid conditions, thereby improving the overall system stability and operational reliability. The method and apparatus of this invention can effectively address dynamic stability issues in complex grid environments, providing strong technical support for the safe and reliable operation of power systems.

[0376] By integrating multiple high-precision test modules, the present invention provides a comprehensive, flexible, and accurate testing platform that can evaluate the dynamic response, stability, and anti-disturbance capability of power conversion systems (PCSs) under various complex grid conditions. Through automated and intelligent testing functions, this device reduces manual intervention, improves test efficiency, and increases the repeatability of results. This platform has important practical value in multiple application areas, including microgrids, energy storage systems, and smart grids. It can effectively improve the safety, stability, and operational efficiency of power systems, providing strong technical support for the reliable operation of future smart power systems.

[0377] In addition, the present invention also provides an evaluation platform for evaluating the dynamic response and grid adaptability of PCS equipment, as well as its anti-interference capability and frequency stability under grid disconnection, load changes, harmonic interference, and other complex working conditions. The evaluation steps include the following aspects:

[0378] Input parameters: including the frequency, phase, short-circuit ratio, harmonic injection intensity, etc. of the input grid; the test platform can be configured with specific input parameters, such as frequency range, phase jump amplitude, short-circuit ratio adjustment range, etc., to simulate the grid environment under different working conditions.

[0379] Evaluation Process: Based on the set test conditions, the platform conducts tests step by step through various modules, such as frequency adjustment, phase jump, short-circuit ratio adjustment, and harmonic injection. During each test, the platform collects real-time operating parameters such as voltage, current, and phase angle of PCS equipment. Combined with virtual impedance and synchronous control algorithms, it analyzes the system's dynamic response characteristics.

[0380] Output Results: Test results include key performance indicators such as frequency stability, phase angle deviation, output voltage stability, harmonic content (THD), and power factor. By comparing the actual and target values ​​for each indicator, the adaptability and stability of the device under various operating conditions can be determined.

[0381] The platform also includes: a human-computer interaction interface for users to configure test parameters, monitor test progress and view test results. The interface is friendly and intuitive.

[0382] 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 in the scope of protection of the present invention.

Claims

1. A performance detection device for grid-type converters suitable for new energy and energy storage, characterized in that: include: The frequency regulation test module is used to simulate the control of the grid voltage frequency based on piecewise linear variation control and joint software and hardware control, combined with cascade delay filtering technology and differential operation frequency detection method. The simulated grid voltage frequency is input into the grid-type converter to evaluate the frequency response characteristics of the grid-type converter. Phase jump test module, used to simulate grid phase jump parameters using phase angle control technology, and input the simulated grid phase jump parameters into the grid-forming converter to test the dynamic response capability of the grid-forming converter under phase jump conditions; The short-circuit ratio adjustment test module is used to simulate the voltage characteristics of the output port of the grid performance evaluation platform through power electronics. It combines virtual impedance control technology and pulse width modulation drive control technology to adjust the short-circuit ratio parameter. The short-circuit ratio parameter is input into the grid-type converter to evaluate the dynamic response and stability of the grid-type converter under different grid strengths. The broadband harmonic injection test module is used to generate harmonic signals through a digital frequency synthesizer, adjust the harmonic parameters in combination with the pulse width modulation strategy, and test the harmonic anti-disturbance performance of the grid-type converter through the harmonic parameters; The island operation simulation module is used to physically isolate the main grid from the grid-connected converter using a physical isolation device, and to verify the stability of the grid-connected converter in island mode.

2. A grid-type converter performance detection device suitable for new energy and energy storage according to claim 1, characterized in that: The frequency adjustment test module includes a piecewise linear change control module, a joint control module, a differential frequency detection module and a cascade delay filter module; The piecewise linear change control module is used to control the rate of change of the grid voltage and frequency using a ramp control method; The joint control module is used to control the accuracy of the grid voltage and frequency by using a digital-to-analog converter combined with a digital operation method and digital signal processing technology; The differential frequency detection module is used to calculate the real-time voltage frequency based on the differential frequency detection method and taking the three-phase ideal voltage signal of the power grid as input; The cascade delay filtering module is used to eliminate high-order harmonic components in the grid voltage by using the cascade delay filtering technology.

3. A grid-type converter performance detection device suitable for new energy and energy storage according to claim 2, characterized in that: The method of calculating the real-time voltage frequency based on the differential frequency detection method and taking the three-phase ideal voltage signal of the power grid as input includes: Obtain the grid voltage signal and decompose it to obtain a symmetrical, balanced and harmonically distorted three-phase voltage; The three-phase voltage is subjected to Clarke transformation, amplitude normalization, and differential processing, i.e., filtering, in sequence, and when the voltage amplitude reaches a preset value, the voltage real-time frequency is obtained.

4. A performance detection device for a grid-type converter suitable for new energy and energy storage according to claim 2, characterized in that: The method of eliminating high-order harmonic components in the grid voltage by using the cascade delay filtering technology includes: Several delay elimination filter modules are combined in a cascade manner, and the current value, rotation factor and the value before the delay are used to calculate the frequency component elimination in the relevant coordinate system.

5. A grid-type converter performance detection device suitable for new energy and energy storage according to claim 1, characterized in that: The phase jump test module includes a main program module, a full comparison unit interrupt module, a capture unit interrupt module, a first digital signal processing module, a first sensor module and a suppression circuit module; The main program module is used to initialize system parameters, start the pulse width modulation control module, and enter the real-time control mode, and the system parameters include duty cycle and phase reference value; The full comparison unit interrupt module is used to trigger the interrupt service subroutine when the value of the comparison register matches the counter; adjust the duty cycle according to the previous three-phase duty cycle control signal, and complete the grid phase adjustment by adjusting the duty cycle; The capture unit interrupt module is used to detect the rising edge of the synchronization signal of the input phase voltage and the output voltage, and calculate the phase difference of the synchronization signal; dynamically adjust the control parameters according to the comparison result of the phase difference and the reference phase angle; The first digital signal processing module is used to update the phase difference according to the change of the input phase voltage signal, and ensure the regulation of the output voltage amplitude and phase by adjusting the duty cycle of the front stage and the rear stage; The first sensor module is used to monitor the status of the output signal and feed back the status data to the first digital signal processing module; The suppression circuit module is used to ensure the waveform quality of the output voltage through filters and harmonic suppression circuits at both the front stage and the back stage.

6. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: The short-circuit ratio adjustment test module includes a second sensor module and a second digital signal processing module; The second sensor module is used to collect parameters of the meshed converter, including voltage data and current data of the meshed converter. The second digital signal processing module is used to calculate the short-circuit ratio of the current power grid in real time based on the collected grid-type converter parameters, and compare the short-circuit ratio of the current grid-type converter with the target short-circuit ratio; when it is detected that the short-circuit ratio of the current grid-type converter deviates from the target short-circuit ratio, it dynamically outputs a pulse width modulation signal to control the impedance adjustment device to adjust the short-circuit ratio of the current grid-type converter to the target short-circuit ratio.

7. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: The broadband harmonic injection test module includes a harmonic signal output module and a harmonic injection module: The harmonic signal output module is used to transfer the harmonic table data, fundamental wave parameters, and amplitude gain configuration data to the programmable logic device based on the digital frequency synthesizer to calculate and generate the digital harmonic signal; The harmonic injection module is used to control the frequency and amplitude of the harmonics using a pulse width modulation strategy, and dynamically adjust the pulse width modulation strategy using monitoring output signals of voltage and current sensors.

8. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: The island operation simulation module includes an island state identification module and an island simulation module; The islanding state identification module is used to identify the islanding state and initiate the islanding control strategy by adopting a multi-parameter joint analysis method, and the multi-parameter joint analysis method includes frequency change rate and voltage phase drift detection technology; The island simulation module is used to simulate the island operation mode of the grid-type converter by using an AC circuit breaker, an output circuit breaker, an inverter and a filter circuit.

9. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: The method of selecting the optimal control method to perform seamless switching between sources and loads based on the five-loop control strategy includes: Obtaining a first set, where the elements of the first set include the control quantity output value of the source current loop and the control quantity output value of the source power loop; obtaining a minimum value of the first set by comparing the elements of the first set; Obtain a second set, where the elements of the second set include the control quantity output value of the load current loop and the control quantity output value of the load power loop; obtain the maximum value of the second set by comparing all elements in the second set; The voltage loop control quantity is obtained, and the optimal control quantity is selected from the minimum value of the first set, the maximum value of the second set, and the voltage loop control quantity by comparison, and seamless switching between the source and the load is performed based on the selected optimal control quantity.

10. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 9, characterized in that: The step of obtaining the voltage loop control quantity, selecting the optimal control quantity from the first set minimum value, the second set maximum value, and the voltage loop control quantity by comparing the values, and performing seamless switching between the source and the load based on the selected optimal control quantity includes: If the minimum value of the first set > the voltage loop control value > the maximum value of the second set, the voltage loop control value is selected as the optimal control value; If the minimum value of the first set ≤ the maximum value of the second set > the voltage loop control variable, the maximum value of the second set is selected as the optimal control variable; If the voltage loop control quantity is greater than or equal to the minimum value of the first set and the maximum value of the second set, the minimum value of the first set is selected as the optimal control quantity; If the voltage loop control quantity ≤ the maximum value of the second set ≥ the minimum value of the first set, then the minimum value of the first set is selected as the optimal control quantity; if the maximum value of the second set ≥ the minimum value of the first set ≥ the voltage loop control quantity, then the maximum value of the second set is selected as the optimal control quantity; When the comparison result satisfies the condition that the maximum value of the second set > the voltage loop control amount > the minimum value of the first set, an alarm signal is generated.

11. A grid-type converter performance detection device suitable for new energy and energy storage according to claim 1, characterized in that: The evaluation of the frequency response characteristics of the grid-connected converter includes: Acquire frequency response evaluation data of a grid-connected converter simulating grid voltage and frequency input within a preset time interval, wherein the frequency response evaluation data includes converter output voltage amplitude, converter input voltage amplitude, converter maximum frequency response time, converter output phase, and converter input phase; Combining the frequency response evaluation data with a frequency response reference value obtained from a preset database to obtain a converter frequency response parameter, wherein the converter frequency response parameter is used to quantitatively evaluate the degree of compliance of the frequency response characteristics of the grid-type converter, and the frequency response reference value includes a reference maximum phase response deviation and a reference maximum frequency response time; comparing the frequency response parameter of the converter with a preset frequency response threshold range obtained from a preset database, and not performing frequency response characteristic optimization if the frequency response parameter of the converter is within the preset frequency response threshold range; If the converter frequency response parameter exceeds the preset frequency response threshold range, frequency response characteristic optimization is performed, and the converter frequency optimization parameter after the frequency response characteristic optimization is obtained. The converter frequency optimization parameter is used to quantitatively evaluate the effect of the frequency response characteristic optimization.

12. A grid-type converter performance detection device suitable for new energy and energy storage according to claim 11, characterized in that: The obtaining of the converter frequency optimization parameters after the frequency response characteristic optimization is performed includes: Acquiring frequency optimization evaluation related data after performing frequency response characteristic optimization, wherein the frequency optimization evaluation related data includes optimized converter frequency response parameters, converter output power, converter input power, and maximum optimized frequency deviation; The converter frequency optimization parameters are obtained based on the maximum initial frequency deviation, frequency optimization evaluation related data and the optimal reference frequency response parameters obtained from a preset database.

13. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: The evaluation of the dynamic response and stability of the grid-connected converter under different grid strengths includes: Acquiring short-circuit ratio test-related data after inputting the short-circuit ratio parameter into the grid-type converter, wherein the short-circuit ratio test-related data includes short-circuit ratio, output voltage stability, phase angle deviation, and power factor; The converter short-circuit ratio test parameters are obtained by combining the short-circuit ratio related data and the test reference data obtained from the preset database. The converter short-circuit ratio test parameters are used to quantitatively evaluate the dynamic response and stability compliance of the grid-type converter under different grid strengths. The test reference data includes the test reference optimal data and the test evaluation weight. The test reference optimal data includes reference optimal output stability, reference optimal phase angle deviation and reference optimal power factor; The test evaluation weights include a voltage fluctuation evaluation weight, a phase deviation evaluation weight, and a power factor evaluation weight.

14. A performance detection device for a grid-connected converter suitable for new energy and energy storage according to claim 1, characterized in that: Also includes: The source-load switching test module is used to select the optimal control method based on the five-loop control strategy to perform seamless switching between the source and the load, and to evaluate the dynamic response characteristics during the seamless switching between the source and the load; The damping test module is used to adjust damping parameters and perform frequency sweep tests. It also uses a grid-type control strategy to simulate the dynamic behavior of the power grid under different damping conditions and evaluate the dynamic response characteristics and stability of the grid-type converter.

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