Network frequency disturbance-based network construction performance quantitative evaluation method for network construction type energy storage converter

Abstract

The invention relates to a network frequency disturbance-based network construction performance quantitative evaluation method and device for a network construction type energy storage converter. The method comprises the following steps: applying low-frequency sine type frequency disturbance with preset disturbance frequency and amplitude to grid-connected voltage of a grid-forming type energy storage converter; based on the grid-connected active power response function of the energy storage converter under the frequency disturbance, generating a Bode diagram of the output power and the disturbance frequency of the network construction type energy storage converter; based on a Pode diagram, network construction performance quantitative evaluation of the energy storage converter is established, and an equivalent inertia constant, a damping coefficient and an active frequency modulation droop coefficient of the network construction type energy storage converter are fitted by using asymptote characteristics and resonance point characteristics in an amplitude-frequency characteristic curve and a phase-frequency characteristic curve. And quantitative evaluation of the equivalent inertia constant, the damping coefficient and the active frequency modulation droop coefficient is completed. According to the experimental method for evaluating the GFM-PCS dynamic response based on the network frequency disturbance (NFP) method, quantitative evaluation of the network construction performance of the network construction type energy storage converter can be achieved.

Description

Technical Field

[0001] This disclosure relates to the field of quantitative evaluation of the network performance of grid-type energy storage converters, and more specifically, to a method and apparatus for quantitative evaluation of the network performance of grid-type energy storage converters based on network frequency disturbances. Background Technology

[0002] With rapid global economic development, energy demand continues to rise, and fossil fuels are gradually being depleted, leading to environmental pollution problems. To promote a cleaner energy structure, the proportion of new energy sources in the global energy system is significantly increasing. The International Renewable Energy Agency (IRENA), in its 2018 report "Global Energy Transition: Roadmap to 2050," clearly states that to achieve global carbon reduction targets, the share of renewable energy generation needs to increase from 26% to 55% by 2050. However, due to the physical limitations of the current-carrying capacity of power electronic devices, new energy converters struggle to provide fault current support capabilities comparable to traditional synchronous machines. This technological bottleneck directly leads to a dual challenge for modern power systems with increasing asynchronous power source penetration: the system's short-circuit capacity and equivalent inertia level exhibit exponential decay, and the overall grid electrical strength shows a significant weakening trend.

[0003] Especially in countries and regions such as the UK, Ireland, Australia, and the Hawaiian Islands, the penetration rate of new energy sources in the power system is constantly increasing, leading to a decrease in system frequency stability and voltage stability. Compared with traditional grid-following IBRs, GFM-IBRs exhibit voltage source characteristics. By simulating the external characteristics of synchronous converters, they can not only autonomously construct grid voltage and frequency references, but also effectively enhance the short-circuit capacity and system strength at the grid connection point through virtual inertia control and autonomous voltage regulation functions.

[0004] Despite extensive work in understanding and evaluating the dynamic performance and capabilities of GFM-IBRs in supporting grid operation, studies have shown that even with the same theoretical constants, the dynamic behavior of GFM-IBRs can differ significantly from that of SC and SG. Research has found that the measurement error of inertial power can reach 54%, which may pose a significant challenge to network operators in evaluating the performance of GFM-IBRs, making it impossible for them to assess them based on expected or required inertial behavior. This could hinder the wider adoption of this technology in systems.

[0005] Therefore, one or more methods are needed to solve the above problems.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this disclosure is to provide a method and apparatus for quantitatively evaluating the network performance of grid-type energy storage converters based on network frequency disturbances, thereby overcoming, to at least to some extent, one or more problems caused by the limitations and defects of related technologies.

[0008] According to one aspect of this disclosure, a method for quantitatively evaluating the grid performance of a grid-connected energy storage converter based on network frequency disturbances is provided, comprising: A low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude is applied to the grid-connected voltage of the grid-type energy storage converter to generate a Bode plot of the output power of the grid-type energy storage converter with respect to the disturbance frequency. Based on the grid-connected power closed-loop control model of energy storage converter under frequency disturbance, a decoupling method for droop coefficient and damping coefficient is proposed, and the response dominance regions of droop coefficient, inertia coefficient and damping coefficient in the Bode plot are obtained. Based on the Bode plot, a quantitative evaluation of the grid-connected performance of the energy storage converter is established. By utilizing the asymptote characteristics and resonant point characteristics in the amplitude-frequency response curve and phase-frequency response curve, the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter are fitted, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

[0009] In one exemplary embodiment of this disclosure, the method further includes: Based on the preset power loop control block diagram, the formula for simulating the rotor motion equation of the synchronous generator is as follows:

[0010] In the formula, J The moment of inertia coefficient; D The damping coefficient; ω The rotor angular frequency; ω PCC The angular frequency at the grid connection point; P m This is the comprehensive setpoint for active power; P e The inverter outputs active power; damping power. P d It can be represented as: ; Based on the power loop control block diagram, an inertia time constant is introduced. T jThat is, the rotor at its rated power P N Starting from a standstill and reaching rated speed ω Time required to reach 0, inertia time constant T j The formula is: ; Based on the power loop control block diagram, the active power droop coefficient m It can be represented as: , In the formula, the first-order frequency modulation droop coefficient k f Definition: ; Based on the power loop control block diagram, the equations for simulating the synchronous generator excitation regulator are as follows: ; in, Q m This is the comprehensive setpoint for reactive power; Q ref The reactive power setpoint is issued externally; n This refers to the reactive power voltage droop coefficient. U ref and U m These are the given value and the actual value of the inverter output voltage amplitude, respectively.

[0011] In one exemplary embodiment of this disclosure, the grid-connected active power response function of the energy storage converter based on the network frequency disturbance further includes: Utilizing the second-order function characteristics of the active-frequency response transfer function, the active power closed-loop transfer function of the grid-connected energy storage converter affected by grid frequency disturbances can be generated as follows: In the formula, Δ P e Δ is the active power disturbance at the inverter output. ω G This refers to the voltage angular frequency disturbance of the power grid. F ( s )and F δ ( s ) is a low-pass filter, parameters K It can be represented as: , In the formula, E This refers to the inverter output voltage amplitude. U G The voltage amplitude of the power grid. XFor inverter filter impedance, X G Let be the impedance of the power grid line, where E and U G Per-unit processing should be performed according to the rated voltage of the power grid. X and X G The rated impedance is determined by the inverter's rated power and rated voltage and then processed in per-unit format.

[0012] In one exemplary embodiment of this disclosure, the method further includes: Under bandwidth conditions much smaller than 50Hz, the denominator of the closed-loop transfer function is transformed to include the oscillation frequency. ω n Damping coefficient ζ The second-order transfer function type, the second-order function is represented as:

[0013] In the formula, .

[0014] In one exemplary embodiment of this disclosure, the method further includes: A low-frequency sinusoidal preset disturbance is applied to the grid-connected voltage of the grid-type energy storage converter; The frequency disturbance is ,in, f 0 is the rated frequency, Δ f The amplitude of the disturbance frequency. f NFP This is the fluctuation frequency of the disturbance frequency. Correspondingly, the active power response of the energy storage converter also includes frequencies of... f NFP The sinusoidal component: , In the formula, ΔP This represents the phase difference between the sinusoidal component of the power disturbance and the disturbance frequency; Define the perturbation output power Δ P With disturbance frequency amplitude Δ f The ratio is R NFP , where Δ P Δ is the per-unit value. f At rated frequency f Use 0 to mark per unit and define variables. R NFP :

[0015] RNFP This indicates the amplitude and phase characteristics of the active power response of the PCS caused by a unit frequency change under frequency disturbances. This can be achieved by collecting the amplitude and phase of the sinusoidal component of the grid disturbance voltage, as well as the amplitude and phase of the sinusoidal component of the PCS output active power. R NFP By performing THD analysis, the perturbation frequency can be obtained. f NFP Amplitude | R NFP | and phase ∠ R NFP , R NFP It can be transformed into: .

[0016] In one exemplary embodiment of this disclosure, the method further includes: To limit the active power output of grid-connected energy storage converters and ensure safe operation of the equipment, a disturbance power Δ is set. P The maximum value Δ P max It is 0.25 pu, Δ P The formula with limiting conditions is:

[0017] set up f NFP The range is 0.001~20Hz. Frequency disturbances are added to the grid-connected voltage and divided equally according to the logarithmic coordinate system. Ten frequency points are selected for every 10 octaves, for a total of 43 frequency disturbance points. At the same time, the voltage source amplitude is set to be stable at 1.0pu during the disturbance process. Only the interaction between active power and frequency / phase is observed.

[0018] In one exemplary embodiment of this disclosure, the droop coefficient in the method k f The evaluation formula is:

[0019] In the formula, ω 0 is the preset value. m For a given value.

[0020] In one exemplary embodiment of this disclosure, the inertia time constant in the method T j The evaluation methods also include: The inertia assessment method must meet the following requirements:

[0021] The formula provides an asymptote for the inertial response of the NPF plot, which defines the expected response of the PCS during a constant RoCoF perturbation. This asymptote can be derived from the frequency corresponding to the maximum phase angle of the NPF plot phase-frequency curve. f NFP The equivalent inertia time constant is thus obtained. T j for: .

[0022] In one exemplary embodiment of this disclosure, the damping coefficient in the method D The evaluation methods also include: The quality factor of a second-order response system can be obtained by using the shape of the resonance peak of the NFP amplitude-frequency curve. Q Thus, the damping ratio is obtained. ζ Finally obtained D The quality factor can be determined by the resonant frequency and the cutoff frequency, with the cutoff frequency being the frequency corresponding to 3dB below the resonant peak. f 1 and f 2):

[0023] ζ With quality factor Q The following relationship exists:

[0024] according to J , m Quantization parameters and known impedance parameters X , X G ,get D The estimated value is: .

[0025] In one aspect of this disclosure, a device for quantitatively evaluating the grid performance of a grid-based energy storage converter based on network frequency disturbances is provided, comprising: The frequency disturbance application module is used to apply a low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude to the grid-connected voltage of the grid-connected energy storage converter, and generate a Bode plot of the output power of the grid-connected energy storage converter with respect to the disturbance frequency. A Bode plot generation module is used for the grid-connected power closed-loop control model of energy storage converter under frequency disturbance. It proposes a decoupling method for droop coefficient and damping coefficient and obtains the response dominance regions of droop coefficient, inertia coefficient and damping coefficient in the Bode plot. The dynamic response evaluation module, based on the Bode plot, establishes a quantitative evaluation of the grid-connected performance of the energy storage converter. Utilizing the asymptotic features and resonant point features in the amplitude-frequency response curve and phase-frequency response curve, it fits the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

[0026] An exemplary embodiment of this disclosure provides a method for quantitatively evaluating the grid performance of a grid-connected energy storage converter based on network frequency perturbation. The method includes: applying a low-frequency sinusoidal frequency perturbation of preset frequency and amplitude to the grid-connected voltage of the grid-connected energy storage converter; generating a Bode plot of the output power of the grid-connected energy storage converter versus the perturbation frequency based on the grid-connected active power response function of the energy storage converter under the frequency perturbation; establishing a quantitative evaluation of the grid performance of the energy storage converter based on the Bode plot; and fitting the equivalent inertia constant, damping coefficient, and active power frequency modulation droop coefficient of the grid-connected energy storage converter using the asymptote features and resonant point features in the amplitude-frequency response curve and phase-frequency response curve, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency modulation droop coefficient. The experimental method of evaluating the dynamic response of a GFM-PCS based on the network frequency perturbation (NFP) method disclosed in this disclosure can realize the quantitative evaluation of the grid performance of a grid-connected energy storage converter.

[0027] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0028] The above and other features and advantages of this disclosure will become more apparent from the detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0029] Figure 1 A flowchart is shown for a method for quantitative evaluation of the network performance of a grid-type energy storage converter based on network frequency perturbation, according to an exemplary embodiment of the present disclosure. Figure 2 A schematic diagram of an equivalent model of a GFM-IBR grid-connected system is shown, illustrating a quantitative evaluation method for the grid-connected performance of a grid-connected energy storage converter based on network frequency disturbances, according to an exemplary embodiment of this disclosure. Figure 3 A schematic diagram of the GFM-IBR active power control model is shown in an exemplary embodiment of the present disclosure, illustrating a quantitative evaluation method for the network performance of a grid-type energy storage converter based on network frequency disturbances. Figure 4 A schematic diagram of the small-signal frequency control block of a GFM-PCS for a quantitative evaluation method of the network performance of a grid-type energy storage converter based on network frequency perturbation, according to an exemplary embodiment of the present disclosure, is shown. Figure 5The diagram illustrates the influence of Tj and ζ on the inertia curve of a network performance quantitative evaluation method for a network-based energy storage converter based on network frequency perturbation, according to an exemplary embodiment of the present disclosure. Figure 6 The diagram illustrates the damping effect of Tj and ζ on the NFP curve of a quantitative evaluation method for the network performance of a grid-type energy storage converter based on network frequency disturbance according to an exemplary embodiment of the present disclosure. Figure 7 The present invention illustrates a PCS grid-connected system and a control block diagram of a method for quantitatively evaluating the grid performance of a grid-connected energy storage converter based on network frequency disturbances, according to an exemplary embodiment of the present disclosure. Figure 8 The diagram illustrates the NFP perturbation frequency and output power response waveforms of a network-based energy storage converter network performance quantitative evaluation method based on network frequency perturbation according to an exemplary embodiment of this disclosure. Figure 9 The diagram illustrates an NFP disturbance analysis of a method for quantitatively evaluating the network performance of a grid-type energy storage converter based on network frequency disturbances, according to an exemplary embodiment of this disclosure. Figure 10 It shows Figure 9 Enlarged view of a local region of the inertial response asymptote; Figure 11 It shows Figure 9 A magnified view of a local area at the resonance point; Figure 12 The diagram illustrates the output power and output frequency waveforms under a -5° phase jump disturbance, according to an exemplary embodiment of the present disclosure, of a method for quantitatively evaluating the network performance of a grid-type energy storage converter based on network frequency disturbance. Figure 13 The diagram illustrates the output power and output frequency waveforms under a RoCoF = -0.5Hz / s disturbance when droop control is ineffective, according to an exemplary embodiment of the present disclosure, for a quantitative evaluation method of the grid performance of a grid-type energy storage converter based on network frequency disturbance. Figure 14 The diagram illustrates the output power and output frequency waveforms under a RoCoF = -0.5Hz / s disturbance when droop control is effective, according to an exemplary embodiment of the present disclosure, for a quantitative evaluation method of the grid performance of a grid-type energy storage converter based on network frequency disturbance. Figure 15 The diagram illustrates the output power and output frequency waveforms under a -5° phase jump disturbance and a RoCoF = -0.5Hz / s disturbance, when droop control is ineffective, according to an exemplary embodiment of this disclosure. Figure 16The diagram illustrates the output power and output frequency waveforms under -5° phase jump disturbance and RoCoF = -0.5Hz / s disturbance when droop control is effective, according to an exemplary embodiment of the present disclosure, for a quantitative evaluation method of grid-type energy storage converter grid performance based on network frequency disturbance. Figure 17 A schematic block diagram of a network performance quantification evaluation device for a grid-type energy storage converter based on network frequency perturbation, according to an exemplary embodiment of the present disclosure, is shown. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0031] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, materials, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, materials, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0032] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0033] In this example embodiment, a method for quantitatively evaluating the network performance of grid-type energy storage converters based on network frequency perturbations is first provided; refer to Figure 1 As shown, the method for quantitatively evaluating the grid performance of a grid-based energy storage converter based on network frequency perturbation may include the following steps: Step S110: Apply a low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude to the grid-connected voltage of the grid-type energy storage converter to generate a Bode plot of the output power of the grid-type energy storage converter with respect to the disturbance frequency. Step S120: Based on the closed-loop control model of grid-connected power of energy storage converter under frequency disturbance, a decoupling method for droop coefficient and damping coefficient is proposed, and the response dominance regions of droop coefficient, inertia coefficient and damping coefficient in the Bode plot are obtained. Step S130: Based on the Bode plot, establish a quantitative evaluation of the grid-connected performance of the energy storage converter. Using the asymptote features and resonant point features in the amplitude-frequency characteristic curve and phase-frequency characteristic curve, fit the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter to complete the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

[0034] An exemplary embodiment of this disclosure provides a method for quantitatively evaluating the grid performance of a grid-connected energy storage converter based on network frequency perturbation. The method includes: applying a low-frequency sinusoidal frequency perturbation of preset frequency and amplitude to the grid-connected voltage of the grid-connected energy storage converter; generating a Bode plot of the output power of the grid-connected energy storage converter versus the perturbation frequency based on the grid-connected active power response function of the energy storage converter under the frequency perturbation; establishing a quantitative evaluation of the grid performance of the energy storage converter based on the Bode plot; and fitting the equivalent inertia constant, damping coefficient, and active power frequency modulation droop coefficient of the grid-connected energy storage converter using the asymptote features and resonant point features in the amplitude-frequency response curve and phase-frequency response curve, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency modulation droop coefficient. The experimental method of evaluating the dynamic response of a GFM-PCS based on the network frequency perturbation (NFP) method disclosed in this disclosure can realize the quantitative evaluation of the grid performance of a grid-connected energy storage converter.

[0035] The following will further explain a method for quantitative evaluation of the network performance of a grid-type energy storage converter based on network frequency perturbation in this example embodiment.

[0036] Example 1: In step S110, a low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude is applied to the grid-connected voltage of the grid-type energy storage converter to generate a Bode plot of the output power of the grid-type energy storage converter with respect to the disturbance frequency.

[0037] In this example embodiment, the method further includes: Based on the preset power loop control block diagram, the formula for simulating the rotor motion equation of the synchronous generator is as follows:

[0038] In the formula, damping power P d It can be represented as: ; Based on the power loop control block diagram, an inertia time constant is introduced. Tj That is, the rotor at its rated power P N Starting from a standstill and reaching rated speed ω Time required to reach 0, inertia time constant T j The formula is: ; Based on the power loop control block diagram, the active power droop coefficient m It can be represented as: , In the formula, the first-order frequency modulation droop coefficient k f Definition: ; Based on the power loop control block diagram, the equations for simulating the synchronous generator excitation regulator are as follows: ; in, ω The rotor angular frequency; ω 0 is the rated electrical angular frequency; ω PCC The angular frequency at the grid connection point; P m This is the comprehensive setpoint for active power; P e and Q e These represent the active power and reactive power output by the inverter, respectively. P d Damping power; J The moment of inertia coefficient; D The damping coefficient; P ref and Q ref These are the active power setpoint and reactive power setpoint issued externally, respectively. m This is the active frequency modulation droop factor; n This refers to the reactive power voltage droop coefficient. U ref and U m These are the given and actual values ​​of the inverter output voltage amplitude, respectively. θ and U PCC These are the phase angle and amplitude reference values ​​for the inverter output voltage, respectively.

[0039] In this example embodiment, the grid-connected active power response function of the energy storage converter based on the network frequency disturbance further includes: Utilizing the second-order function characteristics of the active-frequency response transfer function, the active power closed-loop transfer function of the grid-connected energy storage converter affected by grid frequency disturbances can be generated as follows: , In the formula, Δ P e Δ is the active power disturbance at the inverter output. ω G This refers to the voltage angular frequency disturbance of the power grid. F ( s )and F δ ( s ) is a low-pass filter, parameters K It can be represented as: , In the formula, E This refers to the inverter output voltage amplitude. U G The voltage amplitude of the power grid. X For inverter filter impedance, X G Let be the impedance of the power grid line, where E and U G Per-unit processing should be performed according to the rated voltage of the power grid. X and X G The rated impedance is determined by the inverter's rated power and rated voltage and then processed in per-unit format.

[0040] In this example embodiment, the method further includes: Under bandwidth conditions much smaller than 50Hz, the denominator of the closed-loop transfer function is transformed to include the oscillation frequency. ω n Damping coefficient ζ The second-order transfer function type, the second-order function is represented as:

[0041] In the formula, .

[0042] In step S120, based on the closed-loop control model of the grid-connected power of the energy storage converter under frequency disturbance, a decoupling method for the droop coefficient and the damping coefficient is proposed, and the response dominance regions of the droop coefficient, inertia coefficient and damping coefficient in the Bode plot are obtained.

[0043] In this example embodiment, the method further includes: A low-frequency sinusoidal preset disturbance is applied to the grid-connected voltage of the grid-type energy storage converter; The frequency disturbance is ,in, f 0 is the rated frequency, Δ f The amplitude of the disturbance frequency. f NFP This is the fluctuation frequency of the disturbance frequency. Correspondingly, the active power response of the energy storage converter also includes frequencies of... f NFP The sinusoidal component: , In the formula, ΔP This represents the phase difference between the sinusoidal component of the power disturbance and the disturbance frequency; Define the perturbation output power Δ P With disturbance frequency amplitude Δ f The ratio is R NFP , where Δ P Δ is the per-unit value. f At rated frequency f Use 0 to mark per unit and define variables. R NFP：

[0044] R NFP This indicates the amplitude and phase characteristics of the active power response of the PCS caused by a unit frequency change under frequency disturbances. This can be achieved by collecting the amplitude and phase of the sinusoidal component of the grid disturbance voltage, as well as the amplitude and phase of the sinusoidal component of the PCS output active power. R NFP By performing THD analysis, the perturbation frequency can be obtained. f NFP Amplitude | R NFP | and phase ∠ R NFP , R NFP It can be transformed into: .

[0045] In this example embodiment, the method further includes: To limit the active power output of grid-connected energy storage converters and ensure safe operation of the equipment, a disturbance power Δ is set. P The maximum value Δ P max It is 0.25 pu, Δ P The formula with limiting conditions is:

[0046] set upf NFP The range is 0.001~20Hz. Frequency disturbances are added to the grid-connected voltage and divided equally according to the logarithmic coordinate system. Ten frequency points are selected for every 10 octaves, for a total of 43 frequency disturbance points. At the same time, the voltage source amplitude is set to be stable at 1.0pu during the disturbance process. Only the interaction between active power and frequency / phase is observed.

[0047] In step S130, based on the Bode plot, a quantitative evaluation of the grid-connected performance of the energy storage converter is established. Using the asymptote features and resonant point features in the amplitude-frequency characteristic curve and phase-frequency characteristic curve, the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter are fitted, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

[0048] In this example embodiment, the droop coefficient in the method k f The evaluation formula is:

[0049] In the formula, ω 0 is the preset value. m For a given value.

[0050] In this example embodiment, the inertia time constant in the method T j The evaluation methods also include: The inertia assessment method must meet the following requirements:

[0051] The formula provides an asymptote for the inertial response of the NPF plot, which defines the expected response of the PCS during a constant RoCoF perturbation. This asymptote can be derived from the frequency corresponding to the maximum phase angle of the NPF plot phase-frequency curve. f NFP The equivalent inertia time constant is thus obtained. T j for: .

[0052] In this example embodiment, the damping coefficient in the method D The evaluation methods also include: The quality factor of a second-order response system can be obtained by using the shape of the resonance peak of the NFP amplitude-frequency curve. Q Thus, the damping ratio is obtained. ζ Finally obtained D The quality factor can be determined by the resonant frequency and the cutoff frequency, with the cutoff frequency being the frequency corresponding to 3dB below the resonant peak. f1 and f 2):

[0053] ζ With quality factor Q The following relationship exists:

[0054] according to J , m Quantization parameters and known impedance parameters X , X G ,get D The estimated value is: .

[0055] Example 2: With the large-scale grid connection of power converter systems (PCS), the synchronous inertia support capability of traditional power systems has weakened, leading to reduced system strength and increased challenges in frequency and voltage regulation. Grid-forming PCS (GFM-PCS), which simulates the characteristics of rotating machinery to provide virtual inertia support, is considered an effective solution to address system inertia decline. However, the response characteristics of GFM-PCS differ from those of synchronous generators and synchronous condensers, and there is currently no authoritative technical method to evaluate its dynamic performance. To accurately quantify and evaluate the active-frequency droop performance, inertia constant, and damping performance of GFM-PCS, this embodiment presents an experimental method for evaluating the dynamic response of GFM-PCS based on the Network Frequency Disturbance (NFP) method. The inertia constant and damping coefficient of a 1.725MW PCS prototype, as well as the impact of parameters such as grid disturbances on the output power response of GFM-PCS, were verified on a hardware-in-the-loop (HIL) simulation platform.

[0056] In this example embodiment, the inertia response and damping response of the GFM-IBR are analyzed as follows, wherein the inertia and damping control strategies of the GFM-IBR include: Equivalent model of GFM-IBR grid-connected system, such as Figure 2 As shown. The IBR's bridge arm corresponds to the rotor end of the synchronous generator, and the VSG's output end corresponds to the stator end. The connection between the rotor and stator ends is an impedance. X The impedance in X′ This refers to the damping winding of the synchronous generator. This damping is a real, external damping, whereas the VSG does not have this external damping; it only has the filter reactance of the inverter. XThe connection between the VSG output and the remote power grid includes transformers and transmission line impedance. The voltage phases of the off-grid power grid, VSG output, and VSG arm in the model are as follows: G , S , R The phase difference between the two ends of the filter reactance is δ RS The phase difference between the bridge arm voltage and the grid voltage is δ RG .

[0057] The inertia and damping control of the GFM-IBR mainly simulates the rotor motion equations and active power-frequency droop control of the synchronous generator. The complete control equation, combined with the secondary frequency regulation power, is shown in equation (1). P ref The active power given for secondary frequency regulation is Pm, where Pm is the given active power. P e For output power, ω For the output angular frequency, D It is the damping coefficient. J It is the moment of inertia of the rotor.

[0058] (1) (2) Taking the Laplace transform of equation (1), we get equation (2), which shows that k f and D Together, they provide comprehensive damping. Considering that the output frequency of the PCS changes little under small disturbances, to simplify the calculation, the denominator in (2) is positioned... ω Change to a fixed value ω 0. However, k f and D There are subtle differences: natural damping power to Figure 2 shown δ RS The deviation responds instantaneously without delay, while the droop response depends on δ. RS The frequency deviation from the static frequency reference value is used to calculate the response power through a control algorithm, thus exhibiting a certain hysteresis effect.

[0059] To transform the rotor motion equations into electrical equations, an inertial time constant is introduced. T j (Unit: seconds), defined as the time required for the rotor to rise from rest to its rated speed under rated torque. Synchronous generators in... Tj Doing work at all times W k As shown in equation (3). Assume the kinetic energy of the rotor is equal to... W k You can get J and T j The relationship is shown in equation (4).

[0060] (3) (4) In this example embodiment, the analysis of the impact of the inertia and damping control of the GFM-IBR on the output power includes: Based on the above analysis, the active power control model of the GFM-IBR after connection to the power grid can be reorganized, as follows: Figure 3 As shown in the figure. In the figure, voltage and frequency are both per unit of 1 pu, and the inertia constant is... J The damping coefficient is D The droop coefficient is k f Given angular frequency ω 0, the actual output angular frequency of the VSG is ω , X For inverter filter reactor, X G For the impedance of the power grid line, P ref Given the power, P m_pu To simulate rotor output power, P e_pu To simulate stator output power (i.e. PCS output power). P S_pu For damping output power, P ( s To simulate the response delay of the prime mover, F S ( s ) is a boxcar filter for noise reduction, which is a low-pass filter with a delay. This is to introduce computational delay in the digital control system.

[0061] When a grid phase disturbance occurs, the grid-connected PCS actively responds to the phase change, absorbing or injecting power to counteract the phase change. Based on the power angle relationship, the output active power of the grid-connected PCS... P e This can be expressed as shown in equation (5). In equation (5), considering the limitation of line inductance on current change, the output current in the actual system cannot achieve a step response; the current should still exhibit continuous change characteristics after a phase change. Therefore, a box-type filter is added to the digital control system.F ( s (Low-pass filtering + delay) is used to simulate and calculate the delay.

[0062] (5) like Figure 3 As shown, when the power grid experiences disturbances such as phase jumps or steady RoCoF ramp events, δ RS Deviation will affect output power P e The frequency changes due to the presence of inertial components, while the presence of the integrator ensures that the generated output power exhibits a certain degree of persistence. Since the GFM-PCS lacks an external damping winding, the control loop must introduce an additional active power component proportional to the RoCoF. P s To counteract power oscillations, ultimately manifesting as P e Damping D Insufficient oscillations will cause slow decay, while D Excessive levels can cause high-frequency noise or unstable control.

[0063] In this example embodiment, the effects of inertia and damping parameters on stability include: As can be seen from the above analysis, the frequency control of the power grid structure PCS mainly achieves relative synchronization of the phase angle difference δGS through active power control. Substituting the angle / power relationship expressed in equation (5) into... Figure 3 The small-signal control block diagram of the network PCS output voltage frequency has been reorganized as follows: Figure 4 As shown.

[0064] Figure 4 In order to obtain the active power output of the PCS, ω G The response under disturbance will ω PCC Disturbance transformed into ω G Disturbance, ignore P ref The perturbation of the PCS's own power is given. Considering the perturbation frequency is less than 50Hz, the filter function can be simplified to... F δ ( s )≈1, F drp ( s )≈1. According to Figure 4 The active power output of the PCS can be obtained. ωG Closed-loop transfer function of influence G PωG ( s ): (6) Under bandwidth conditions much smaller than 50Hz, it can be considered in small-signal analysis that F δ ( s )≈1, F S ( s )≈1, k f →0, the denominator can be transformed into a second-order transfer function type as shown in Equation 7, where... ω n The oscillation frequency is... ζ is the damping coefficient.

[0065] (7) exist J , ζ and X G In adjustable scenarios, considering that synchronous generators are typically... ζ Operating at around 0.25, the GFM-PCS, limited by hardware and efficiency requirements, can be configured to be critical or even overdamped to mitigate the risk of subsynchronous oscillations caused by coupling with other devices.

[0066] In this example embodiment, the NFP evaluation principle in the network performance quantification analysis includes: Since the dynamic characteristics of the GFM-IBR can be approximated by the second-order system of Equation (7), the inertia, damping, and droop coefficients of the GFM-IBR can be identified by analyzing the dynamic response of active power under frequency disturbances. Therefore, the NFP diagram is a tool for analyzing and understanding the response of equipment in a power system to changes in grid frequency. This method simulates the dynamic changes in grid frequency by artificially injecting frequency disturbance signals (such as sine waves, step signals, or sweep signals) into the grid, and generates a Bode diagram of output power versus disturbance frequency. Using the amplitude-frequency characteristic curve and phase-frequency characteristic curve, the equivalent inertia, damping, and droop coefficients of the IBR are fitted.

[0067] A small-amplitude frequency disturbance, typically a sinusoidal waveform, is applied to the power grid or equipment to simulate frequency variations in the power grid. As shown in equation (8), where Δ f The amplitude of the disturbance frequency. f NFP The frequency of the disturbance is the fluctuation frequency.

[0068] (8) The active power response of the IBR to the disturbance frequency will also include frequencies of . f NFP The sinusoidal component, as shown in Formula 9, has a phase deviation from the disturbance frequency. ΔP .

[0069] (9) According to equation (9), the disturbance output power Δ is defined. P With disturbance frequency amplitude Δ f The ratio is R NFP , where Δ P Δ is the per-unit value. f At rated frequency f 0 is used for per-unit marking to ensure consistency in the drawing.

[0070] (10) right R NFP By performing THD analysis, the perturbation frequency can be obtained. f NFP Amplitude | R NFP | and phase ∠ R NFP Here is the setting. f NFP The selected range is (0.001~20Hz) because (0.001~1Hz) corresponds to the slow dynamic processes of the system, such as inertial response and primary frequency regulation, while (1~20Hz) may involve damping control and the response of power electronic devices. Furthermore, subsynchronous resonance affecting the power system typically occurs below 20Hz, therefore, disturbances to higher frequencies are not permitted.

[0071] In this example embodiment, the parameter evaluation is based on the following criteria: First of all k f Based on the evaluation, when the disturbance frequency is very small (approaching 0.001Hz), it can be approximately considered that there is a nearly stable RoCoF. At this time, the output power satisfies the active droop relationship of Equation 2, and Δ P = k f (Δ f / f 0), and due to the inverse relationship between power and frequency, at this time ΔP = 180°. Therefore, the droop coefficient is evaluated as shown in equation (11).

[0072] (11) Next is J The evaluation of inertia control is a relatively slow and continuous process. At a constant RoCoF, the output power can be approximately expressed as Equation (12).

[0073] (12) According to (6) and Figure 3 From this, we can derive (13), which reveals the influence of the inertial constant on the frequency characteristics.

[0074] (13) Further analysis T j and ζ The effect of the parameters on the NFP curve validated the effectiveness of the quantitative method. The NFP plots under different parameters are shown below. Figure 5 , Figure 6 As shown.

[0075] exist Figure 5 middle, T j The values ​​are 2, 4, 6, 8, and 10 respectively. From the graph, we can see that: (i) with... T j As the value increases, the oscillation frequency of the NFP amplitude-frequency curve increases. ω n Decrease, which is consistent with the analysis in equation (7); (ii) as T j As the value increases, the oscillation peak value increases, indicating that the inertial response power provided by the PCS increases. (iii) With the increase of the value, the oscillation peak value increases, indicating that the inertial response power provided by the PCS increases. T j As the inertial response power increases, the phase frequency curve of the NFP plot gets closer to the inertial asymptote (270°), indicating that the increase in inertial response power leads to a decrease in damped response. (iv) k f Since the parameters are the same, the intersection points of the five curves with the Y-axis coincide, which is consistent with the above analysis.

[0076] exist Figure 6 middle, ζ The values ​​are 0.5, 0.6, 0.7, 0.8, and 0.9, respectively. As can be seen from the graph: (i) with... ζ As the value increases, the power oscillations and phase fluctuations of the NFP plot decrease, indicating that the damping response power increases; (ii) the oscillation frequency of the NFP amplitude-frequency curve. ω n The fact that it remains unchanged indicates that the oscillation frequency is the same as that of the oscillation frequency. ζ Irrelevant.

[0077] Secondly, it is DQuantitative evaluation. According to the UK ESO standard, the damping provided by GFM should be greater than 0.2, which helps to reduce subsynchronous oscillations in the power system. According to equation (9), in Figure 6 The influence of the damping coefficient on the frequency response can be observed, showing that the damping coefficient affects the peak characteristics. Based on the characteristics of the second-order transfer function, the active power response under frequency disturbance exhibits a resonant spike. Given... k f The resonant frequency can be obtained from the NFP diagram. ω n And the damping ratio is derived using equation (14). ζ It has two cutoff frequencies ( f 1 and f 2 is defined as the frequency at -3dB below the resonance peak. Subsequently, equation (6) can be used to calculate... D The estimated value.

[0078] In this example embodiment, the experimental setup for performance evaluation and power response verification of the hardware-in-the-loop (HILL) method based on hardware-in-the-loop simulation includes: A hardware-in-the-loop (HIL) and rapid control prototyping (RCP) semi-physical simulation experimental platform was used for functional verification. This platform consists of a real-time simulator, an RCP system, digital and analog hardware interfaces (such as digital input / output, analog input / output, and communication ports), and a host computer. The HIL is used for high-precision simulation of the dynamic characteristics of the controlled object, while the RCP system deploys and verifies control algorithms in real time. It interacts with the simulation environment on real hardware via high-speed communication, and the host computer monitors and records data.

[0079] This disclosure uses a single-unit grid-connected energy storage converter (PCS) system with a rated power of 1.725MW as the test object. The PCS grid-connected system and control strategy are as follows: Figure 7 As shown in the diagram. The main circuit is generated by HIL (High-Intensity Logic), using a controlled voltage source with frequency perturbation added to the HIL. The control section is generated by RCP (Reactive Power Logic). The active power loop generates the angular frequency and phase of the PCS (Power Control System) output voltage, while the reactive power loop generates the amplitude of the PCS output voltage. After coordinate transformation, a reference value for the output voltage vector is obtained. Through voltage vector closed-loop control (voltage closed loop + current closed loop), the three-level IGBT is driven and controlled by SPWM modulation.

[0080] The system electrical parameters are shown in Table 1. The PCS simulates the parameters of a 1725kW rated power energy storage converter. Two sets of grid performance parameters were tested. (The remaining text appears to be incomplete and requires further context.) k f and ζ same, J and D They are different.

[0081] Table 1. Electrical Parameters of GFM-IBR

[0082] In this example embodiment, the NFP testing steps include NFP testing is conducted using the following steps: Step 1: According to Equation (5), add frequency disturbance to the controlled voltage source. The disturbance frequency range is 0.001~20Hz. Divide the disturbance into logarithmic coordinates and select 10 frequency points for every 10 octaves. A total of 43 frequency disturbance points are selected. At the same time, set the voltage source amplitude to be stable at 1.0pu during the disturbance process. Therefore, ensure that only the interaction between active power and frequency / phase is observed. Step 2: To simulate the power limitations of actual equipment, set the maximum disturbance power Δ. P max The value is 0.25 pu. According to formulas 8 and 10, the condition Δ is satisfied. P The limiting conditions are as shown in equation (15).

[0083] (15) Step 3: Perform Fourier analysis on the frequency deviation and output power. During Fourier analysis, the same window length and parameters must be used to accurately determine the disturbance power Δ. P Phase deviation can also be accurately obtained. ΔP Due to the amplitude Δ of the disturbance frequency during the disturbance process f The low voltage and frequency of the grid may lead to large errors due to the sampling accuracy of the data acquisition. Therefore, it is recommended to simultaneously collect active power and disturbance frequency phase angle. Pha NFP = 2π f NPF t to obtain Figure 8 Phase angle difference between output power and frequency disturbance ΔP .

[0084] In this example embodiment, the hardware-in-the-loop simulation-based NFP performance evaluation includes: The NFP test waveforms under the two sets of control parameters are as follows: Figure 9 As shown, based on the NFP testing steps mentioned above, the following can be estimated respectively: T j and D The parameters are shown in Table 2. First, based on the asymptote relationship of the droop response, in... Figure 9 From the overall NFP plot, we can obtain the low-frequency band of the amplitude-frequency curve. k f The estimated value of 25 is consistent with the given value, and the phase of the intersection of the asymptote of the phase frequency curve and the Y-axis is 180°, which is consistent with the theoretical analysis; subsequently, based on the asymptote relationship of the inertial response, the inertial response asymptote is locally magnified in the NFP diagram. Figure 10 The phase-frequency curves show that the maximum phase angles of PCS1 and PCS2 correspond to frequencies of 0.63Hz and 0.4Hz, respectively. Based on this, [further information is needed]. Figure 10 From the amplitude-frequency curves, the center points of the inertia asymptotes of PCS1 and PCS2 are obtained as (0.63, 30.64) and (0.4, 42), respectively. Further, the values ​​of PCS1 and PCS2 are... T j The estimated values ​​were 7.74s and 15.92s, respectively. Compared with the given values ​​of 8s and 16s, the estimation errors were -3.2% and -0.5%, respectively. This is in contrast to existing literature using the NFP method. T j The estimated values ​​were 7.47s and 14.8s, with estimation errors of -6.6% and -7.5%, respectively, indicating improved estimation accuracy. The resonant point was magnified locally in the NFP plot. Figure 11 From the amplitude-frequency curves, the resonant frequencies of PCS1 and PCS2 are found to be 1.4Hz and 1.0Hz, respectively. The two frequencies -3dB below the resonant points of PCS1 and PCS2 are (0.75Hz, 2.6Hz) and (0.63Hz, 1.6Hz), respectively. The values ​​of PCS1 and PCS2 are also obtained. ζ The estimated values ​​were 0.66 and 0.485, respectively. Compared with the given values ​​of 0.7 and 0.5, the estimation errors were -5.6% and -3%, respectively. Further, the values ​​for PCS1 and PCS2 were obtained. D The estimated values ​​were 5486 and 6099, respectively, with estimation errors of -9.9% and -3% compared to the given values. This is in contrast to existing literature using the NFP method. D The estimated values ​​were 7913 and 8745, with estimation errors of 30% and 41.7%, respectively, demonstrating a significant improvement in estimation accuracy. This is due to the method proposed in the paper regarding... D The estimation incorporates a droop coefficient. m If ignored m The method proposed in the paper is used to estimate D The values ​​were 7839 and 8455 respectively, with errors increasing to 28.7% and 36.9% respectively, thus proving that in the estimation... D It is necessary to consider the influence of the droop coefficient.

[0085] Table 2 Comparison of NFP Test Estimation Results

[0086] In this example embodiment, the quantitative evaluation and testing analysis of the active power response performance of the grid-type PCS under three grid disturbances—phase jump disturbance, RoCoF disturbance, and phase jump + RoCoF disturbance—includes the following: To avoid the impact of different voltage and power levels on the active power of the PCS, the power and frequency are standardized per unit. J = T j Four PCS sets with different inertia and damping coefficients were set up, and the output power and frequency response results of the PCS were verified under phase jump disturbance, RoCoF disturbance, and phase jump + RoCoF disturbance, respectively. Considering that the phase jump range is approximately ±60° and the RoCoF disturbance range is approximately ±2Hz / s according to various national standards, a -5° phase jump disturbance and a RoCoF = -0.5Hz / s disturbance were used for general verification. The PCS output power and frequency waveforms under the above three disturbances are shown below. Figure 12 , Figure 13 and Figure 14 .

[0087] Figure 12 A -5° phase jump disturbance occurs at 0.5s. The main analytical conclusions are as follows: In the active power response curves, all devices achieved a fast response within 5ms, meeting the fast response standard requirements. The initial power response is mainly affected by the system stiffness, which is determined by the total line impedance. Due to the comparative experiments... X and X G Since the values ​​are the same, the initial power spikes are also the same. The first negative oscillation of the output power is affected by the damping coefficient. ζ Significant impact. ζ Smaller devices exhibit greater power oscillations. Among devices with the same damping coefficient, those with a larger inertia constant exhibit lower power oscillations. In the frequency response curve, the damping coefficient... ζ Larger devices experience greater frequency disturbances but also reach stability more quickly. For devices with the same... ζ Devices with larger inertial constants exhibit smaller frequency disturbances and are more likely to achieve stability.

[0088] In the frequency response curve, the damping coefficient ζ Larger devices experience greater frequency disturbances but also reach stability more quickly. For devices with the same... ζ Devices with larger inertial constants exhibit smaller frequency disturbances and are more likely to achieve stability.

[0089] exist Figure 13In the analysis, the grid frequency starts at 50Hz at 0.5s, maintains a RoCoF of -0.5Hz / s for 2s, and stabilizes at 49Hz at 2.5s, ignoring droop control. The main analytical conclusions are as follows: In the active power response curves, all devices respond within 5 ms. For devices with the same moment of inertia, the steady-state power value at 2.5 s is identical. The GFM-PCS is not configured with droop control; therefore, its power response is solely due to inertial response. When the initial power is 0, T j =4 and T j The steady-state output power at =8 is 0.08 pu and 0.16 pu, respectively. These values ​​match the power output at time 2.5s in the figure.

[0090] (16) Figure 14 exist Figure 13 Based on this, droop control was added. The main analytical conclusions are as follows: In the active power response curve, all devices respond within 5ms, which is consistent with... Figure 12 The analysis is the same; In the active power response curve, the response power within the 0.5~1s time range mainly depends on the total line impedance and inertial response; in the 1~2.5s range, besides... Figure 13 In addition to the inertial response, the output power exhibits a linear increasing trend due to the droop control effect. In the active power response curves, taking GFM1 and GFM2 as examples, the active power at 2.5s is from... Figure 13 The 0.08 pu and 0.16 pu increased to 0.35 pu and 0.43 pu respectively, which is equivalent to providing approximately more sag control. T j =13.5 power contribution. Therefore, the droop-related frequency response plays a much larger role in ROCOF events than in phase-jump events; In the active power response curves, taking GFM1 and GFM3 as examples, when the inertia is the same but the damping is different, the two curves do not overlap at 2.5s, indicating that increasing the damping parameter will reduce the steady-state output power value.

[0091] Figure 15 and Figure 16 In the diagram, represent the simultaneous occurrence of phase jump and constant RoCoF perturbation events when droop control is ineffective and effective, respectively. The main analytical conclusions are as follows: In the active power response curve, a phase jump and a RoCoF disturbance event occurred simultaneously at time 0.5s. Figure 15 and Figure 16The initial response power peak was 0.3 pu, and was consistent with... Figure 12 The initial peak power is similar, which is due to the influence of system rigidity. Furthermore, since the RoCoF power response at 0.5s is slower due to inertia, its effect on the initial response power peak is not significant.

[0092] In the active power response curve, only the RoCoF disturbance exists after 0.5s, so the active power is mainly composed of the inertial response power. Figure 15 and Figure 16 The active power at 2.5s is respectively compared with Figure 13 and Figure 14 same.

[0093] In the frequency response curve, the frequency response after 0.5s and Figure 12 The frequency response after 2.5s is the same, mainly due to the phase transition. Figure 13 Similarly, this is mainly affected by RoCoF disturbances.

[0094] In the embodiments of this example, grid performance evaluation is crucial to ensure that the grid-based energy storage system can effectively support the stable operation of the power system in actual operation. Although considerable work has been done to understand and evaluate the dynamic performance and capabilities of virtual synchronous machines (VSMs) in supporting grid operation, it has been observed that even with the same inertia constant, the dynamic behavior of VSMs can differ significantly from that of SC and SG in terms of inertial response provision. This can pose a significant challenge to network operators in evaluating the performance of VSMs, preventing them from assessing them based on expected or required inertial behavior, thus hindering the wider application of this technology in systems.

[0095] To address this issue, this disclosure proposes a verification method using the NFP approach to evaluate the active-frequency droop coefficient, inertia constant, and damping coefficient of a GFM-IBR. This method can accurately evaluate the active-frequency droop coefficient and inertia constant, and has been effectively verified in a 1725kW energy storage converter semi-physical simulation grid-connected system. Furthermore, response analysis of the active-frequency droop coefficient, inertia constant, and damping coefficient under grid events such as grid phase jumps and RoCoF changes was conducted. In summary, the experimental method based on the NFP approach provides a meaningful tool for evaluating inertia and damping performance, which is beneficial for promoting the practical application of GFM-IBRs.

[0096] It should be noted that although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0097] Furthermore, in this example embodiment, a device for quantitatively evaluating the network performance of a grid-type energy storage converter based on network frequency perturbations is also provided. (Refer to...) Figure 17 As shown, the network performance quantification evaluation device 200 for a grid-based energy storage converter based on network frequency disturbance may include: a frequency disturbance application module 210, a Bode plot generation module 220, and a dynamic response evaluation module 230. Wherein: The frequency disturbance application module 210 is used to apply a low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude to the grid-connected voltage of the grid-connected energy storage converter, and generate a Bode plot of the output power of the grid-connected energy storage converter with respect to the disturbance frequency. Bode plot generation module 220 is used for the grid-connected power closed-loop control model of energy storage converter under frequency disturbance, proposes a decoupling method for droop coefficient and damping coefficient, and obtains the response dominance region of droop coefficient, inertia coefficient and damping coefficient in the Bode plot. The dynamic response evaluation module 230 establishes a quantitative evaluation of the grid-connected performance of the energy storage converter based on the Bode plot. It uses the asymptote features and resonant point features in the amplitude-frequency characteristic curve and phase-frequency characteristic curve to fit the equivalent inertia constant, damping coefficient and active power frequency regulation droop coefficient of the grid-connected energy storage converter, and completes the quantitative evaluation of the equivalent inertia constant, damping coefficient and active power frequency regulation droop coefficient.

[0098] The specific details of each of the above-mentioned network frequency disturbance-based grid-type energy storage converter network performance quantitative evaluation device modules have been described in detail in the corresponding network frequency disturbance-based grid-type energy storage converter network performance quantitative evaluation method, so they will not be repeated here.

[0099] It should be noted that although several modules or units of a network performance quantification evaluation device 200 for grid-based energy storage converters based on network frequency disturbances have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0100] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0101] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0102] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for quantitatively evaluating the network performance of grid-type energy storage converters based on network frequency perturbations, characterized in that, The method includes: A low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude is applied to the grid-connected voltage of the grid-type energy storage converter to generate a Bode plot of the output power of the grid-type energy storage converter with respect to the disturbance frequency. Based on the grid-connected power closed-loop control model of energy storage converter under frequency disturbance, a decoupling method for droop coefficient and damping coefficient is proposed, and the response dominance regions of droop coefficient, inertia coefficient and damping coefficient in the Bode plot are obtained. Based on the Bode plot, a quantitative evaluation of the grid-connected performance of the energy storage converter is established. By utilizing the asymptote characteristics and resonant point characteristics in the amplitude-frequency response curve and phase-frequency response curve, the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter are fitted, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

2. The method as described in claim 1, characterized in that, The method further includes: Based on the preset power loop control block diagram, the formula for simulating the rotor motion equation of the synchronous generator is as follows: In the formula, J The moment of inertia coefficient; D The damping coefficient; ω The rotor angular frequency; ω PCC The angular frequency at the grid connection point; P m This is the comprehensive setpoint for active power; P e The inverter outputs active power; damping power. P d It can be represented as: ； Based on the power loop control block diagram, an inertia time constant is introduced. T j That is, the rotor at its rated power P N Starting from a standstill and reaching rated speed ω Time required to reach 0, inertia time constant T j The formula is: ； Based on the power loop control block diagram, the active power droop coefficient m It can be represented as: ， In the formula, the first-order frequency modulation droop coefficient k f Definition: ； Based on the power loop control block diagram, the equations for simulating the synchronous generator excitation regulator are as follows: ； in, Q m This is the comprehensive setpoint for reactive power; Q ref The reactive power setpoint is issued externally; n This refers to the reactive power voltage droop coefficient. U ref and U m These are the given value and the actual value of the inverter output voltage amplitude, respectively.

3. The method as described in claim 2, characterized in that, The grid-connected power closed-loop control model based on the grid-type energy storage converter also includes: Utilizing the second-order function characteristics of the active-frequency response transfer function, the active power closed-loop transfer function of the grid-connected energy storage converter affected by grid frequency disturbances can be generated as follows: ， In the formula, Δ P e Δ is the active power disturbance at the inverter output. ω G This refers to the voltage angular frequency disturbance of the power grid. F ( s )and F δ ( s ) is a low-pass filter, parameters K It can be represented as: ， In the formula, E This refers to the inverter output voltage amplitude. U G The voltage amplitude of the power grid. X For inverter filter impedance, X G Let be the impedance of the power grid line, where E and U G Per-unit processing should be performed according to the rated voltage of the power grid. X and X G The rated impedance is determined by the inverter's rated power and rated voltage and then processed in per-unit format.

4. The method as described in claim 3, characterized in that, The method further includes: Under bandwidth conditions much smaller than 50Hz, the denominator of the closed-loop transfer function is transformed to include the oscillation frequency. ω n Damping coefficient ζ The second-order transfer function type, the second-order function is represented as: In the formula, 。 5. The method as described in claim 4, characterized in that, The method further includes: A low-frequency sinusoidal preset disturbance is applied to the grid-connected voltage of the grid-type energy storage converter; The frequency disturbance is ,in, f 0 is the rated frequency, Δ f The amplitude of the disturbance frequency. f NFP This is the fluctuation frequency of the disturbance frequency. Correspondingly, the active power response of the energy storage converter also includes frequencies of... f NFP The sinusoidal component: ， In the formula, ΔP This represents the phase difference between the sinusoidal component of the power disturbance and the disturbance frequency; Define the perturbation output power Δ P With disturbance frequency amplitude Δ f The ratio is R NFP , where Δ P Δ is the per-unit value. f At rated frequency f Use 0 to mark per unit and define variables. R NFP : R NFP This indicates the amplitude and phase characteristics of the active power response of the PCS caused by a unit frequency change under frequency disturbances. This can be achieved by collecting the amplitude and phase of the sinusoidal component of the grid disturbance voltage, as well as the amplitude and phase of the sinusoidal component of the PCS output active power. R NFP By performing THD analysis, the perturbation frequency can be obtained. f NFP Amplitude | R NFP | and phase ∠ R NFP , R NFP It can be transformed into: 。 6. The method as described in claim 5, characterized in that, The method further includes: To limit the active power output of grid-connected energy storage converters and ensure safe operation of the equipment, a disturbance power Δ is set. P The maximum value Δ P max It is 0.25 pu, Δ P The formula with limiting conditions is: set up f NFP The range is 0.001~20Hz. Frequency disturbances are added to the grid-connected voltage and divided equally according to the logarithmic coordinate system. Ten frequency points are selected for every 10 octaves, for a total of 43 frequency disturbance points. At the same time, the voltage source amplitude is set to be stable at 1.0pu during the disturbance process. Only the interaction between active power and frequency / phase is observed.

7. The method as described in claim 6, characterized in that, The droop coefficient in the method k f The evaluation formula is: In the formula, ω 0 is the preset value. m For a given value.

8. The method as described in claim 7, characterized in that, The inertia time constant in the method T j The evaluation methods also include: The inertia assessment method must meet the following requirements: The formula provides an asymptote for the inertial response of the NPF plot, which defines the expected response of the PCS during a constant RoCoF perturbation. This asymptote can be derived from the frequency corresponding to the maximum phase angle of the NPF plot phase-frequency curve. f NFP The equivalent inertia time constant is thus obtained. T j for: 。 9. The method as described in claim 8, characterized in that, The damping coefficient in the method D The evaluation methods also include: The quality factor of a second-order response system can be obtained by using the shape of the resonance peak of the NFP amplitude-frequency curve. Q Thus, the damping ratio is obtained. ζ Finally obtained D The quality factor can be determined by the resonant frequency and the cutoff frequency, with the cutoff frequency being the frequency corresponding to 3dB below the resonant peak. f 1 and f 2): ζ With quality factor Q The following relationship exists: according to J , m Quantization parameters and known impedance parameters X , X G ,get D The estimated value is: 。 10. A device for quantitatively evaluating the network performance of a grid-type energy storage converter based on network frequency perturbation, characterized in that, The device includes: The frequency disturbance application module is used to apply a low-frequency sinusoidal frequency disturbance with a preset frequency and amplitude to the grid-connected voltage of the grid-connected energy storage converter, and generate a Bode plot of the output power of the grid-connected energy storage converter with respect to the disturbance frequency. A Bode plot generation module is used for the grid-connected power closed-loop control model of energy storage converter under frequency disturbance. It proposes a decoupling method for droop coefficient and damping coefficient and obtains the response dominance regions of droop coefficient, inertia coefficient and damping coefficient in the Bode plot. The dynamic response evaluation module, based on the Bode plot, establishes a quantitative evaluation of the grid-connected performance of the energy storage converter. Utilizing the asymptotic features and resonant point features in the amplitude-frequency response curve and phase-frequency response curve, it fits the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient of the grid-connected energy storage converter, thus completing the quantitative evaluation of the equivalent inertia constant, damping coefficient, and active power frequency regulation droop coefficient.

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