Equivalent flux inertia characterization method and device based on voltage deviation and frequency deviation

Abstract

The application discloses an equivalent magnetic flux inertia characterization method and device based on voltage deviation and frequency deviation, and relates to the technical field of power grids. The method comprises the following steps: constructing a power topology structure of a hybrid grid-connected system of a grid-constructed new energy station and an SVG; determining energy storage changes of the hybrid grid-connected system under unit frequency changes and under unit voltage changes based on the power topology structure; obtaining a magnetic flux inertia expression based on frequency deviation based on the energy storage changes under unit frequency changes and a derivative of current with respect to time; and obtaining a magnetic flux inertia expression based on voltage deviation based on the energy storage changes under unit voltage changes and the derivative of current with respect to time. The application deduces the magnetic flux inertia of the hybrid grid-connected system of the grid-constructed new energy station and the SVG based on frequency deviation and voltage deviation, clearly defines the physical connotation of the magnetic flux inertia and the quantitative expression based on frequency and voltage deviation, and provides a theoretical basis for analyzing frequency disturbance resistance and voltage disturbance resistance of the system.

Description

Technical Field

[0001] This invention relates to the field of power grid technology, and in particular to a method and apparatus for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation. Background Technology

[0002] Traditional renewable energy power plants employ grid-following converters (GFLs). Grid-following control uses a phase-locked loop (PLL) to lock the amplitude and phase of the voltage at the grid connection point, achieving frequency and phase synchronization. However, with the development trend of "high-voltage and high-efficiency" power systems, the equivalent electrical distance between power generation and the grid side is increasing, the equivalent electrical strength of the grid is gradually weakening, and the system's short-circuit ratio (SCR) is decreasing. When the SCR is low, the converter under grid-following control is prone to instability and oscillation due to its inherent structure. Therefore, a single grid-following renewable energy power plant cannot safely and stably transmit power. Currently, grid-based retrofitting of renewable energy power plants and the addition of static var generators (SVG) are effective means to solve this problem. By transforming grid-following control into grid-forming converter (GFM) control, the static stability capability of power plants under weak grid conditions is improved. Currently, renewable energy power plants often use virtual synchronous generator (VSG) technology and grid-forming control algorithms to retrofit grid-following control equipment. Simultaneously, the use of static var generators (SVG) provides more reactive power injection, which helps stabilize the voltage level at the grid connection point. However, the quantitative evaluation method for the resistance to frequency and voltage disturbances under transient conditions in hybrid grid-connected systems using VSG and SVG is still imperfect. Furthermore, the approach to modifying parameters to improve the resistance to frequency and voltage disturbances in hybrid grid-connected systems is not yet clear. Therefore, how to analyze and estimate the transient immunity capability of hybrid grid-connected systems using grid-forming renewable energy power plants and SVG has become a key challenge in this research.

[0003] Currently, industry standards do not specify inertia standards for voltage deviation during transient processes, and existing technologies rarely focus on quantitative assessment methods for transient voltage deviation. Furthermore, the impact of which core parameters on transient voltage deviation is unknown. The analytical methods for estimating the transient stability immunity of grid-connected renewable energy power plants and SVG hybrid systems have the following shortcomings: first, a quantitative assessment method with mathematical derivation has not yet been developed for hybrid systems; second, the correlation and changing trends of which core parameters this quantitative assessment method is clearly related to are unclear.

[0004] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0005] To address at least one of the technical problems in the background section, this application provides a method and apparatus for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation, clarifying the physical connotation of magnetic flux inertia and its quantitative expression based on frequency and voltage deviation, thus providing a theoretical basis for analyzing the frequency and voltage immunity of the system.

[0006] In a first aspect, embodiments of the present invention provide a method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation, the method comprising: Constructing a power topology for a hybrid grid-connected system of grid-connected new energy power plants and SVG; Based on the power topology, the energy storage changes of the hybrid grid-connected system under unit frequency change and under unit voltage change are determined. Based on the changes in stored energy and the derivative of current with respect to time under unit frequency variation, an expression for magnetic flux inertia based on frequency deviation is obtained. Based on the energy storage change under the unit voltage change and the derivative of current with respect to time, the expression for magnetic flux inertia based on voltage deviation is obtained.

[0007] In some optional embodiments of this example, the power topology includes SVG branches, VSG branches, and grid branches, wherein the SVG branches and VSG branches are connected to the grid branches through a grid connection point; The SVG branch includes an SVG DC-side capacitor, a transistor, a filter inductor, a filter capacitor, the line inductance of the SVG branch, and the line resistance. The VSG branch includes a new energy power station, a transistor, a filter inductor and a filter capacitor, and the line inductance and line resistance of the VSG branch. The power grid branch includes the line inductance and line resistance of the power grid branch.

[0008] In some optional embodiments of this example, determining the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change includes: The frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch and power grid branch are determined respectively. Based on the current sensitivity based on frequency deviation and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under unit frequency change is determined. Based on the voltage deviation-based current sensitivity and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under a unit voltage change is determined.

[0009] In some optional embodiments of this example, determining the frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch, and power grid branch includes: Determine the equivalent admittance of the SVG branch, VSG branch, and power grid branch respectively; The equivalent admittance of the hybrid grid-connected system is determined based on the equivalent admittance of the SVG branch, VSG branch and power grid branch. Based on the equivalent admittance of the SVG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the SVG branch are determined. Based on the equivalent admittance of the VSG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the VSG branch are determined. Based on the equivalent admittance of the power grid branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the power grid branch are determined.

[0010] In some optional embodiments of this example, the step of determining the equivalent admittance of the VSG branch includes: Determine the physical filter impedance and total control equivalent impedance of the VSG branch; The equivalent admittance of the VSG branch is determined based on the physical filter impedance and the total control equivalent impedance of the VSG branch.

[0011] In some optional embodiments of this example, the step of determining the equivalent admittance of the SVG branch includes: Determine the physical filter impedance and total control equivalent impedance of the SVG branch; The equivalent admittance of the SVG branch is determined based on the physical filter impedance and the total control equivalent impedance of the SVG branch.

[0012] In some optional embodiments of this example, the step of determining the equivalent admittance of the power grid branch includes: The equivalent admittance of the power grid branch is determined based on the line inductance and line resistance of the power grid branch.

[0013] Secondly, embodiments of the present invention also provide an equivalent magnetic flux inertia characterization device based on voltage deviation and frequency deviation, the device comprising: The power topology construction module is configured to construct the power topology of a hybrid grid-connected system of grid-connected new energy power plants and SVG. The energy storage change determination module is configured to determine the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change based on the power topology. The first magnetic flux inertia characterization module is configured to obtain a magnetic flux inertia expression based on frequency deviation, based on the energy storage change and the derivative of current with respect to time under unit frequency change. The second magnetic flux inertia characterization module is configured to obtain a magnetic flux inertia expression based on voltage deviation, based on the energy storage change under the unit voltage change and the derivative of current with respect to time.

[0014] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation.

[0015] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations.

[0016] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation.

[0017] This invention provides a method and apparatus for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations. It derives the magnetic flux inertia based on frequency and voltage deviations for a hybrid grid-connected system of grid-connected new energy power stations and SVG, clarifies the physical connotation of magnetic flux inertia and its quantitative expression based on frequency and voltage deviations, and provides a theoretical basis for analyzing the frequency and voltage immunity of the system. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a flowchart illustrating an equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation in an embodiment of the present invention. Figure 2 This is a schematic diagram of the power topology of a grid-type new energy power station and an SVG hybrid grid-connected system in an embodiment of the present invention; Figure 3 This is a flowchart of the method for analyzing equivalent magnetic flux inertia under parameter differences in an embodiment of the present invention; Figure 4 For different VSG under strong and weak power grids in the embodiments of the present invention J eq of J Ψ，ω and J Ψ，U A schematic diagram; Figure 5a and Figure 5b For different VSGs under strong and weak power grids in embodiments of the present invention L v and R v of J Ψ，ω and J Ψ，U A schematic diagram; Figure 6a and Figure 6b Different SVG under strong and weak power grids in embodiments of the present invention L s and R s of J Ψ，ω and J Ψ，U A schematic diagram; Figure 7a and Figure 7b Different feeder lines for strong and weak power grids in embodiments of the present invention L G and R G of J Ψ，ω and J Ψ，U A schematic diagram; Figure 8a and Figure 8b This is a schematic diagram of magnetic flux inertia based on voltage and frequency deviation under different VSG and SVG line inductances in a strong power grid scenario according to an embodiment of the present invention; Figure 9a and Figure 9b This is a schematic diagram of magnetic flux inertia based on voltage and frequency deviation under different VSG and SVG line inductances in a weak power grid scenario according to an embodiment of the present invention; Figure 10a and Figure 10bThis is a schematic diagram illustrating the relative sensitivity of different parameters of the hybrid system to magnetic flux inertia based on voltage and frequency deviation in an embodiment of the present invention. Figure 11 This is a schematic diagram of the structure of an equivalent magnetic flux inertia characterization device based on voltage deviation and frequency deviation in an embodiment of the present invention. Figure 12 This is a schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0020] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation portals are provided for users to choose to authorize or refuse.

[0021] The acquisition, transmission, storage, use, and processing of data in this application comply with relevant national laws and regulations. It should be noted that certain software, components, models, and other existing industry solutions may be mentioned in the embodiments of this application. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0022] Current research on transient immunity quantification indices for hybrid systems is as follows: Existing technology one analyzes the active power-frequency response characteristics of each component in the system and proposes a node instantaneous equivalent inertia index that can reflect the spatiotemporal distribution law of system frequency transients. Simultaneously, based on feasibility, it establishes a membership function of the current state to the system's transient instability state, effectively solving the problem that probabilistic methods are insufficient to assess the system's instability status under different operating conditions from a system perspective. However, this method's model does not consider the influence of reactive power loops. Existing technology two takes systems with large-scale wind power integration as the research object, comprehensively considering the transient voltage response characteristics of multiple heterogeneous power sources and loads, and studies a voltage stability assessment method for wind power grid-connected systems under grid short-circuit faults. It proposes an improved Thevenin equivalent method suitable for transient voltage stability analysis of wind turbine units. Existing technology three, based on electromagnetic transient theory, defines the stator flux inertia as a core parameter and derives an analytical expression for the stator flux inertia that includes variables such as motor parameters and rotor current control gain. The influence mechanism of flux linkage inertia on the dynamic characteristics of stator voltage and rotor induced electromotive force through electromagnetic coupling was analyzed in depth. Existing technology four analyzed the disturbance characteristics of virtual inertia in doubly-fed induction generators, simplified the linearized equation of rotor flux linkage-current loop based on the stator flux linkage orientation principle, and established a fifth-order closed-loop transfer function of the wind turbine considering rotor flux linkage-current loop control using state equations. The frequency domain response of rotor flux linkage under the current loop effect was quantified using the frequency domain method. Existing technology five proposed a robust fault ride-through strategy for GFMCs based on reactive power synchronization (Q-Syn) under voltage dips. The Q-Syn method guarantees the transient response of GFMCs. Voltage stability is unaffected by the duration of faults. Existing technology six establishes a simplified mathematical model of a doubly-fed inertial generator (DFIG) with inertia control. By calculating the equivalent inertia time constant, it quantitatively characterizes the inertia response capability of the DFIG and proposes an inertia control method for DFIGs based on slip feedback, applying slip control to a vector control framework. Existing technology seven establishes a low-dimensional voltage stability analysis model for high-penetration photovoltaic power fed into the receiving-end grid. Considering branch decoupling based on active power shunting, it derives the load limit expression for transient voltage stability of the receiving-end grid to achieve rapid quantitative assessment of transient voltage stability. Existing technology eight proposes a transient power flow section PV curve analysis method based on the technical route of dynamically tracking system characteristic changes, and provides calculation methods for transient voltage stability quantification indicators and corresponding stability criteria.

[0023] However, existing research on reactive power support has not fully considered the electromagnetic induction nature of voltage surges and flux linkage inertia, and has not yet constructed a method to analyze voltage and frequency support capabilities from the perspective of the entire transient process of stator flux linkage. Existing technology provides a method for analyzing transient voltage processes from stator flux linkage, but does not consider frequency. Therefore, it is necessary to propose a comprehensive method that can analyze both the frequency and voltage of transient processes, while also exploring the influence of relevant line parameters.

[0024] Currently, there is a lack of in-depth research on comprehensive analysis and evaluation methods for voltage and frequency deviations during transient processes in grid-connected renewable energy power plants and SVG hybrid systems. How to use inherent equivalent quantities to evaluate the resistance capability under voltage and frequency disturbances deserves attention. Therefore, this invention patent introduces a standard method for magnetic flux inertia based on frequency and voltage deviations. Analogous to the standard method for machine inertia, it can evaluate the suppression level of transient voltage and frequency deviation change rates in grid-connected renewable energy power plants and SVG hybrid systems. First, the expression and inherent physical essence of magnetic flux inertia are derived mathematically; second, the influence of line impedance and grid strength on magnetic flux inertia is explored; and third, the core parameters affecting magnetic flux inertia are summarized.

[0025] Therefore, the technical problem to be solved by this invention is to propose a method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation. The relevant expressions are derived through mathematical and physical formulas, and the influence of different line resistances and reactances on the two types of equivalent magnetic flux inertia based on voltage deviation and frequency deviation is investigated using a single variable. Based on relative sensitivity, the core parameters affecting magnetic flux inertia are summarized, and the idea is organized into a flowchart of the equivalent magnetic flux inertia and parameter sensitivity analysis method.

[0026] In view of this, this application proposes a method for characterizing the equivalent magnetic flux inertia based on voltage deviation and frequency deviation, such as... Figure 1 As shown, the method includes: Step 10: Construct the power topology of the hybrid grid-connected system of grid-connected new energy power plants and SVG.

[0027] In some optional embodiments of this example, the power topology includes SVG branches, VSG branches, and grid branches, wherein the SVG branches and VSG branches are connected to the grid branches through a grid connection point; The SVG branch includes an SVG DC-side capacitor, a transistor, a filter inductor, a filter capacitor, the line inductance of the SVG branch, and the line resistance. The VSG branch includes a new energy power station, a transistor, a filter inductor and a filter capacitor, and the line inductance and line resistance of the VSG branch. The power grid branch includes the line inductance and line resistance of the power grid branch.

[0028] Specifically, with Figure 2 The power topology shown is used to illustrate this application: In power electronic systems, many power electronic devices (such as virtual synchronous machines (VSGs) and static var generators (SVGs) have no mechanical rotating parts, but they can exhibit dynamic characteristics similar to "inertia" through the magnetic flux storage of electromagnetic components, namely equivalent magnetic flux inertia.

[0029] The power topology of a grid-connected renewable energy power plant and an SVG hybrid grid-connected system is given below. Figure 2 As shown. Figure 2 middle C dc For SVG DC side capacitor, L f-s and C f-s For the SVG branch, the filter inductor and filter capacitor are... L s and R s For the line inductance and line resistance of the SVG branch; L f-v and C f-s For the VSG branch, the filter inductor and filter capacitor are... L v and R v For the line inductance and line resistance of the VSG branch; C G For the grounding capacitor at the grid connection point, L G and R G For the line inductance and line resistance of the power grid branch; I s , I v and I G These are the line currents for the SVG branch, VSG branch, and power grid branch, respectively.

[0030] like Figure 2 As shown, the SVG branch also includes a transistor, and the VSG branch also includes a transistor and a new energy power station.

[0031] Step 20: Based on the power topology, determine the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change.

[0032] In some optional embodiments of this example, determining the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change includes: The frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch and power grid branch are determined respectively. Based on the current sensitivity based on frequency deviation and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under unit frequency change is determined. Based on the voltage deviation-based current sensitivity and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under a unit voltage change is determined.

[0033] In some optional embodiments of this example, determining the frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch, and power grid branch includes: Determine the equivalent admittance of the SVG branch, VSG branch, and power grid branch respectively; The equivalent admittance of the hybrid grid-connected system is determined based on the equivalent admittance of the SVG branch, VSG branch and power grid branch. Based on the equivalent admittance of the SVG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the SVG branch are determined. Based on the equivalent admittance of the VSG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the VSG branch are determined. Based on the equivalent admittance of the power grid branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the power grid branch are determined.

[0034] In some optional embodiments of this example, the step of determining the equivalent admittance of the VSG branch includes: Determine the physical filter impedance and total control equivalent impedance of the VSG branch; The equivalent admittance of the VSG branch is determined based on the physical filter impedance and the total control equivalent impedance of the VSG branch.

[0035] In some optional embodiments of this example, the step of determining the equivalent admittance of the SVG branch includes: Determine the physical filter impedance and total control equivalent impedance of the SVG branch; The equivalent admittance of the SVG branch is determined based on the physical filter impedance and the total control equivalent impedance of the SVG branch.

[0036] In some optional embodiments of this example, the step of determining the equivalent admittance of the power grid branch includes: The equivalent admittance of the power grid branch is determined based on the line inductance and line resistance of the power grid branch.

[0037] In a hybrid grid-connected system, the flux linkages of branches such as VSG, SVG, and the power grid can be described by the relationship between inductance and current (in the dq rotating coordinate system): (1) In formula (1) Ψ x = [ Ψ xd , Ψ xq ] T Let dq be the branch flux linkage component, and for simplification, let VSG, SVG, and the line reactance of the power grid be respectively... L v , L s and L G The physical essence of magnetic flux linkage is that it is the energy carrier of magnetic field. Equation (1) establishes a linear mapping between current and magnetic flux linkage, providing a basis for subsequent energy analysis.

[0038] The total flux linkage energy of the system is the sum of the inductance energy stored in each branch as shown in equation (2), which is expressed in the form of dq components.

[0039] (2)

[0040] Equation (2) describes the energy storage change per unit frequency change and is the core of the energy derivation of the equivalent magnetic flux inertia, i.e., the energy storage model of the hybrid grid-connected system in this application. It should be noted that the inertia characteristics under subsequent frequency and voltage deviation disturbances are essentially the external manifestation of the law of magnetic flux energy storage changing with disturbance.

[0041] For the VSG branch, the voltage balance relationship between the VSG output terminal and the point of common coupling (PCC) is shown in the following equation (3): (3) In equation (3), E v =[ E vd , E vq ] T The dq component of the output electromotive force of the VSG inverter. V pcc =[ V pccd , V pccq ] T The dq component of the grid connection point voltage. i v =[ i vd , i vq ] T Let dq be the current component of the VSG branch. ω This is the actual angular frequency of the power grid. Rv and L v These are the line resistance and line inductance of the VSG branch.

[0042] Taking the Laplace transform of the physical filter equation, we obtain the VSG physical filter impedance. Z v (s) is shown in equation (4) below: (4) The VSG affects the d-axis control impedance through the active-frequency loop and the q-axis control impedance through the reactive-voltage loop. Ignoring coupling, the total control equivalent impedance of the VSG is... Z cv (s) is the diagonal matrix shown in equation (5) below, where Z cvd (s) and Z cvq (s) represent the equivalent dq-axis component impedances of the VSG control loop: (5) The core of the active frequency loop of VSG is to simulate the rotor motion of a synchronous generator to achieve dynamic coupling between active power and frequency, as shown in equation (6) below: (6) in, P e-v =1.5 E vd i vd To output active power to VSG, ω v For VSG virtual angular velocity, ω 0 is the rated angular frequency. P ref-v This is the reference value for active power.

[0043] Virtual angle deviation Δ θ v The relationship with angular velocity is shown in the following equation (7): (7) Correction amount Δ for shaft electromotive force E vd Due to virtual angular deviation Δ θ v The decision is expressed as shown in the following formula (8): (8) In formula (8) K θ Angle-voltage gain describes the effect of virtual angle changes on voltage gain. The ability to adjust the shaft electromotive force.

[0044] The Laplace transform of equation (6) yields the following expression (9): (9) When the DC component is ignored, the active power deviation is approximately linearly related to the change in active current as shown in equation (10): (10) Combining the relationship between virtual angle and angular velocity Δ θ v (s)=Δ ω v (s) / s and electromotive force correction Δ E vd (s) Eliminate Δ ω v (s) then we can obtain: (11) The control equivalent impedance is defined as the ratio of the electromotive force regulation to the current deviation. The VSG equivalent d-axis impedance... Z cvd (s) is as follows (12): (12) make K ω =2K θ / 3 E vd0， Then the equivalent d-axis impedance of VSG (12) can be further modified as follows: (13) The VSG reactive power loop adopts an unbiased voltage reactive excitation equation and uses reactive power. Q e-v Compared with reference value Q ref-v The deviation is driven by a PI controller, and the expression is as follows: (14) In equation (14) K pq-v and K iq-v For the proportional and integral coefficients of the VSG reactive power loop PI controller, V pcc and V ref-v These are the PCC voltage value and the VSG voltage reference value, respectively.

[0045] The correction amount of the q-axis electromotive force is determined by the output of the PI controller, as expressed in the following equation (15): (15) Where, Δ V pcc = V ref - V pcc This refers to the voltage deviation. It is approximated that the voltage deviation is linearly related to the reactive current change, i.e., Δ... V pcc = K q-v Δ Q v , K q-v For voltage-reactive power sensitivity, and Δ Q v =1.5 E vq0 Δ i vq Substituting the values, we get: (16) Define the q-axis control equivalent impedance as the ratio of the electromotive force correction to the q-axis current deviation, and let the combined voltage-reactive power sensitivity be... K qv =3 / 2 E vq0 K q-v Then equation (16) is further transformed into equation (17): (17) According to equation (17) and the current-voltage relationship, the equivalent q-axis impedance of VSG is... Z cvq (s) is as follows (18): (18) Combining equations (4), (13) and (18), the equivalent impedance and corresponding admittance of the VSG branch are shown in equations (19) and (20).

[0046] (19) (20) For the SVG branch, the voltage balance relationship between the SVG output and the point of common coupling (PCC) is shown in equation (21): (twenty one) In equation (21), E s =[ E sd , E sq] T The dq component of the output electromotive force of the VSG inverter. i s =[ i sd , i sq ] T Let dq be the current component of the VSG branch. ω This is the actual angular frequency of the power grid. R s and L s These are the line resistance and line inductance of the SVG branch.

[0047] Similar to VSG, SVG physical filter impedance Z s (s) See equation (22) below: (twenty two) The SVG affects the d-axis control impedance through the active-frequency loop and the q-axis control impedance through the reactive-voltage loop; coupling is not considered. The total control equivalent impedance of the SVG is... Z cs (s) is the diagonal matrix shown in equation (23) below, where Z csd (s) and Z csq (s) represent the equivalent dq-axis component impedances of the SVG control loop: (twenty three) The SVG regulates reactive power and supports PCC voltage solely through q-axis current regulation; therefore, only the q-axis control equivalent impedance needs to be derived. Z csq (s), d-axis controlled equivalent impedance Z csd (s) can be set to 0 by default.

[0048] The reactive power loop of SVG is similar to that of VSG, and the reactive power-voltage equation is shown in equation (24): (twenty four) in, K pq-s and K iq-s These are the proportional and integral coefficients of the SVG reactive power loop PI controller. V ref-s This is the reference value for SVG voltage. Q e-s and Q ref-s These represent the reactive power output by the SVG and the command value, respectively. Meanwhile, it can be approximated as... Qe-s =1.5 V pccd i sq ,in V pccd The d-axis component of the grid connection point voltage. i sq This represents the q-axis component of the SVG output current.

[0049] The q-axis electromotive force correction of the SVG is determined by the output of the PI controller, as shown in equation (25): (25) In equation (25), the voltage deviation can be approximated as linearly related to the change in reactive current of SVG, i.e., Δ V pcc = K q-s Δ Q e-s , K q-s (Voltage-Reactive Power Sensitivity of SVG), and Δ Q e-s =1.5 V pccd0 Δ i sq , V pccd0 Let d be the rated component of the grid connection point voltage. Substituting this into the equation, we get the following formula (26): (26) The q-axis of the SVG controls the equivalent impedance, which is 1.5. V pccd0 K q-s Combined into a comprehensive voltage-reactive power sensitivity K qs Then equation (26) can be further transformed into equation (27): (27) According to equation (27) and the current-voltage relationship, the equivalent q-axis impedance of SVG is... Z csq (s) is as follows (28): (28) Combining equations (22) and (28), the equivalent impedance of the SVG branch is... Z SVG (s) and corresponding admittance Y SVG (s) See equations (29) and (30) below.

[0050] (29) (30) For a power grid branch, the equivalent impedance Z G (s) and corresponding admittance Y G (s) See equations (31) and (32) below, where R G and L G These represent the line resistance and line inductance of the power grid branch.

[0051] (31) (32) Meanwhile, the grounding capacitor at the grid connection point PCC C p Frequency domain admittance Y C (s) is shown in equation (33) below. I c This represents the current flowing through the capacitor.

[0052] (33)

[0053] Finally, calculate the total current at point PCC. I total and the total admittance Y of the system sys (s) See equations (34) and (35) below: (34) (35) The response of magnetic flux energy storage to disturbances (frequency / voltage) needs to be derived by impedance to determine the current sensitivity. Equations (1) to (35) have already derived the equivalent impedance and equivalent admittance of the system. Now, the current sensitivity will be analyzed.

[0054] Furthermore, the sensitivity analysis of current to frequency is as follows: From the KCL relation (34), the sensitivity to frequency is the current to frequency (angular velocity). ω Find the partial derivative, expressed as in equation (36), the essence of which is... ω The rotating electromotive force term affecting impedance ωL, Note the formula V pcc Including phase.

[0055] (36)

[0056] In equation (36) Y sxs / ω For the impedance of each branch ω The partial derivative, V PCC / ω For voltage pair ω The partial derivatives can be used to determine the frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch and power grid branch according to formula (36).

[0057] Substituting the current sensitivity based on frequency deviation into the energy storage formula (2), the following equation (37) is retained, retaining the differential term: (37) Equation (37) represents the energy storage change of a hybrid grid-connected system under unit frequency variation.

[0058] Furthermore, the sensitivity analysis of current to grid connection point voltage is as follows: Taking the partial derivative of KCL equation (34), the sensitivity to voltage is the current-to-voltage ratio (voltage amplitude at grid connection point). U pcc Find the partial derivative, which is expressed as follows (38): (38) In formula (38) Y sxs / U PCC For the impedance of each branch U PCC The partial derivative, V PCC / U PCC voltage vector pair U PCC Partial derivative.

[0059] Substituting the current sensitivity based on voltage deviation into the energy storage formula (2), we obtain the following equation (39) with the differential term retained: (39) Equation (39) represents the energy storage change of a hybrid grid-connected system under a unit voltage change.

[0060] Step 30: Based on the changes in stored energy and the derivative of current with respect to time under unit frequency variation, obtain the expression for magnetic flux inertia based on frequency deviation.

[0061] Step 40: Based on the energy storage change under the unit voltage change and the derivative of current with respect to time, obtain the expression for magnetic flux inertia based on voltage deviation.

[0062] Specifically, the characterization of magnetic flux inertia is as follows: Inertia is essentially "resistance to changes in the rate of change", as shown in equation (40).

[0063] (40)

[0064] Machine inertia is typically characterized as... J d ω / dt= T Therefore, the magnetic flux inertia under frequency deviation can be expressed as the following equation (41): (41) In equation (41) J eq d( is the equivalent inertia of the converter) W Ψ / ω ) / dt is the time derivative of the current with respect to frequency, reflecting the influence of the "time variation of the rate of frequency change" on the inertia. Meanwhile, the derivative of the current with respect to time is given by equation (42): (42) Substituting equation (42) into equation (37), and further deriving equation (41), we obtain the expression for magnetic flux inertia based on frequency deviation (43): (43) The magnetic flux inertia based on voltage deviation is the time derivative of the current sensitivity to voltage as shown in equation (44): (44) In equation (44), d( W Ψ / U PCC ) / dt is the time derivative of the current in response to voltage, reflecting the effect of the "time variation of the voltage change rate" on the inertia.

[0065] Substituting equation (42) into equation (39), and further deriving equation (44), we obtain the expression for magnetic flux inertia based on voltage deviation (45): (45) Equations (42) and (45) are the equivalent magnetic flux inertia expressions based on frequency deviation and voltage deviation.

[0066] Furthermore, this application also employs the single-variable method to analyze the effects of different control parameters and line impedance variations on the hybrid system. J Ψ，ω and J Ψ，U The impact. By establishing x- J Ψ，ω / J Ψ，U The relationship between parameter variations and equivalent magnetic flux inertia is shown in the figure. Simultaneously, the influence of coupling between line parameters on equivalent magnetic flux inertia is investigated, and relative sensitivity analysis is used to analyze the core parameters affecting equivalent magnetic flux inertia. The flowchart of the analysis method for equivalent magnetic flux inertia under parameter differences is shown below. Figure 3 As shown, the formula is derived for the equivalent magnetic flux inertia of the hybrid system; the control and line parameters of the hybrid system with a single variable are analyzed; two-dimensional curves of the changing parameters and magnetic flux inertia are constructed to analyze the relationship and trend; based on the three-dimensional graph, the influence of the coupling between line parameters on the change of magnetic flux inertia is analyzed; and the core parameters affecting the equivalent magnetic flux inertia are analyzed using relative sensitivity analysis.

[0067] Specifically, a brief analysis of the different parameters is as follows: ① The impact of different grid strengths (SCR) In a weak grid (low SCR, resulting in a large equivalent inductance of the grid), the PCC voltage is more easily disturbed, the branch current fluctuates more, the magnetic flux energy is more sensitive to disturbances, and the equivalent magnetic flux inertia increases.

[0068] In a strong grid (high SCR), the grid is highly rigid, disturbances are quickly absorbed, and the inertia index is relatively reduced.

[0069] ② Virtual inertia J v

[0070] It is directly added to the inertia formula in the frequency dimension, so it increases. J v , J ψ,ω It will increase significantly. However, virtual inertia J v Active power loop parameters, for J ψ,U The impact is relatively small.

[0071] ③VSG voltage loop ratio K pq-v and points K iq-v

[0072] The higher the gain, the easier it is to "hard suppress" voltage disturbances, and the smaller the current disturbance, leading to... J ψ,VThe gain decreases. The smaller the gain, the more the voltage loop inertia is "softened," the greater the voltage disturbance energy, and the higher the inertia index.

[0073] ④SVG voltage loop ratio K pq-s and points K iq-s coefficient

[0074] Effect and VSG voltage loop ratio K pq-v and points K iq-v Consistent.

[0075] ⑤VSG line resistance R v Line reactance L v SVG line resistance R s Line reactance L s Grid line resistance R G and line reactance L G .

[0076] The line parameters need to be analyzed specifically based on the two-dimensional graph and relative sensitivity, as follows: First, write Figure 2 The magnetic flux inertia code framework for frequency and voltage deviation of grid-connected new energy power stations and SVG hybrid grid-connected systems, and the parameters used in the code are shown in Table 1 below.

[0077] Table 1

[0078] (1) The effect of different VSG control parameters and line parameters on magnetic flux inertia based on voltage deviation and frequency deviation

[0079] Using SCR as a distinction, the VSGs under strong (SCR>5) and weak (SCR<3) grid strengths are compared. J eq Presented J Ψ，ω and J Ψ，U Draw below Figure 4 In China, particularly in the context of strong power grid scenarios J Ψ，ω and J Ψ，U The weak grid scenario is described using solid orange lines and dashed orange lines. J Ψ，ω and JΨ，U Described using solid blue lines and dashed blue lines.

[0080] Figure 4 In the middle, different virtual inertia J eq Down J Ψ，ω and J Ψ，U The degree of change varies. J eq Increased power grid capacity in both strong and weak grid scenarios J Ψ，ω Both are showing an increasing trend, under strong power grids J Ψ，ω It is larger than a weak power grid, and for J Ψ，U Strong and weak power grids J Ψ，U The changes were minimal.

[0081] Figure 5a In the context of VSG, the differences L v Presented magnetic flux inertia J Ψ，ω and J Ψ，U Different, with L v When it increases J Ψ，ω Both are showing a decreasing trend, under strong power grids J Ψ，ω It is larger than a weak power grid, and for J Ψ，U Strong and weak power grids J Ψ，U The changes were minimal. Figure 5b In the context of VSG, the differences R v Presented magnetic flux inertia J Ψ，ω and J Ψ，U The changes were minimal.

[0082] (2) The influence of different SVG line parameters on magnetic flux inertia based on voltage deviation and frequency deviation

[0083] Figure 6a In China, for different SVGs L v Presented magnetic flux inertia J Ψ，ω and J Ψ，U The changes were very slight, with L v When it increasesJ Ψ，ω Basically unchanged, under strong power grid J Ψ，ω It is larger than a weak power grid, and for J Ψ，U Strong and weak power grids J Ψ，U The results were consistent. Figure 6b In the context of VSG, the differences R v Presented magnetic flux inertia J Ψ，ω and J Ψ，U and Figure 5a They are basically the same, except for the difference in the magnitude of magnetic flux correlation.

[0084] (3) The influence of differences in grid line parameters on magnetic flux inertia based on voltage deviation and frequency deviation

[0085] Figure 7a In the context of different Grids L G Presented magnetic flux inertia J Ψ，ω and J Ψ，U Significant changes, with L G When it increases J Ψ，ω Reduce, under strong power grid J Ψ，ω It is larger than a weak power grid, and for J Ψ，U along with L G Increase and J Ψ，ω Basically the same.

[0086] Figure 7b In the context of different Grids R G Presented magnetic flux inertia J Ψ，ω and J Ψ，U The changes are different, with R G Increase, under strong and weak power grids J Ψ，ω Unlike other high-voltage power grids, with R G Increase J Ψ，ω Reduce, in weak power grids as R G Increase JΨ，ω Basically unchanged. With R G Increase, under strong and weak power grids J Ψ，U All decreased.

[0087] (4) The effect of coupling between VSG and SVG parameters on magnetic flux inertia based on voltage and frequency deviations

[0088] Considering that the VSG branch may have a coupling effect with the SVG branch under different power grid strengths, and this coupling effect will also affect the equivalent magnetic flux inertia of the system to a certain extent, this invention patent takes into account the inductance of the VSG line under different power grid strengths. L v and SVG line inductance L s With respect to magnetic flux inertia J Ψ,V and J Ψ,ω The coupling effects are as follows: Figure 8a , Figure 8b , Figure 9a and Figure 9b As shown.

[0089] Figure 8a In the context of a strong power grid, L v Increase the J Ψ,V It has a reducing effect. L s Increase the J Ψ,V Its effect is minimal. Figure 8b In the context of a strong power grid, L v Increase the J Ψ,ω It has a reducing effect. L s Increase the J Ψ,V Its effect is minimal. L v and L s The coupling effect is relatively small.

[0090] Figure 9a In the context of weak power grids, L v Increase the J Ψ,V It has a reducing effect. L s Increase the J Ψ,V Its effect is minimal. Figure 9b In the context of weak power grids,L v Increase the J Ψ,ω It has a reducing effect. L s Increase the J Ψ,V Its effect is minimal. L v and L s The coupling effect is relatively small.

[0091] The changing trends are the same under both strong and weak power grids, only the magnitudes of the equivalent magnetic flux inertia differ.

[0092] Finally, the effects of the different control parameters on magnetic flux inertia based on voltage and frequency deviations are described in the following quantized sensitivity description. Figure 10a and Figure 10b As shown. Figure 10a and Figure 10b In the figure, the horizontal axis represents different parameters, and the vertical axis represents the relative sensitivity (positive and negative can reflect the trend of magnetic flux inertia under parameter changes, and the magnitude can reflect the strength of the relationship between parameter changes and magnetic flux inertia).

[0093] Figure 10a In China, for J Ψ,ω The magnitude and trend of the influence of parameters differ under strong and weak power grids, including the short-circuit ratio (SCR) and the virtual inertia of the VSG. J eq Both strong and weak power grids J Ψ,ω The relative sensitivity is positive, showing an increasing trend. J Ψ,ω The trend. VSG line inductance. L v and grid inductance L g Both strong and weak power grids J Ψ,ω The relative sensitivity is negative, exhibiting a decreasing trend. J Ψ,ω The trend. Grid resistance in strong and weak power grids. R g right J Ψ,ω The relative sensitivity differs; it is negative in a strong power grid, exhibiting a decreasing trend. J Ψ,ω The trend has virtually no impact on weak power grids.

[0094] Figure 10b In China, for J Ψ,V The magnitude and trend of the influence of parameters differ between strong and weak power grids. The short-circuit ratio (SCR) has an impact on both strong and weak power grids.J Ψ,V The relative sensitivity is positive, showing an increasing trend. J Ψ,ω The trend. Regarding the line inductance of VSG. L v and grid inductance L g Both strong and weak power grids J Ψ,ω The relative sensitivity is negative, exhibiting a decreasing trend. J Ψ,U The trend. Grid resistance in strong and weak power grids. R g right J Ψ,U The relative sensitivity differs; it is negative in a strong power grid, exhibiting a decreasing trend. J Ψ,U The trend has virtually no impact on weak power grids.

[0095] based on Figure 10a and Figure 10b The analysis compares different parameters under different power grid intensities. J Ψ,ω and J Ψ,V The influence of these factors is shown in Table 2 below. Among them, the short-circuit ratio and inductance... L v and L g These parameters affect the magnetic flux and inertia of this system. J Ψ,ω and J Ψ,V The core parameters.

[0096] Table 2

[0097] Table 2 illustrates the impact of different control parameters and circuits on the magnetic flux inertia of the hybrid system based on voltage and frequency deviations. It provides indicators and ideas for improving the equivalent magnetic flux inertia of the hybrid system, which is conducive to increasing the stability margin of the hybrid system under transient operating conditions.

[0098] The technical solution of this invention provides a solution and analysis method for deriving the equivalent magnetic flux inertia of hybrid systems and the influence of parameters. Its core lies in deeply revealing the electromagnetic induction nature of voltage and frequency changes and magnetic flux inertia. The magnetic flux inertia can be used to evaluate the suppression level of transient voltage and frequency deviation change rate of grid-type new energy power stations and SVG hybrid systems, providing theoretical support and practical tools for the safe and stable operation of hybrid systems.

[0099] This paper's technical solution derives the expression for magnetic flux inertia from mathematical formulas for grid-connected systems of grid-connected renewable energy power plants and SVG hybrid systems. It also analyzes the core parameters affecting magnetic flux inertia using the single-variable method. The calculated magnetic flux inertia is relatively accurate, but lacks flexibility. While the calculation process and approach are provided, different hybrid structures require recalculation of the equivalent magnetic flux inertia. Considering that the physical meaning of magnetic flux inertia is its resistance to the rate of change of deviation, the same analytical effect can be achieved through experimental fitting of curves and functions.

[0100] The advantages of this invention are as follows: First, it derives the magnetic flux inertia based on frequency and voltage deviations in a hybrid grid-connected system of grid-connected renewable energy power plants and SVG from a physical perspective, clarifying the physical connotation of magnetic flux inertia and its quantitative expression based on frequency and voltage deviations, thus providing a theoretical basis for analyzing the system's frequency and voltage immunity. Second, it explores the impact of parameter changes on the equivalent magnetic flux inertia, revealing the core parameters affecting magnetic flux inertia. These core parameters can be flexibly modified according to grid conditions to improve the system's inertia, providing guidance for engineering practice.

[0101] This invention also provides an equivalent magnetic flux inertia characterization device based on voltage deviation and frequency deviation, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of an equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation, the implementation of this device can refer to the implementation of an equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation; repeated details will not be elaborated further.

[0102] like Figure 11 As shown, the device includes: The power topology construction module 801 is configured to construct the power topology of a hybrid grid-connected system of grid-connected new energy power plants and SVG. The energy storage change determination module 802 is configured to determine the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change based on the power topology. The first magnetic flux inertia characterization module 803 is configured to obtain a magnetic flux inertia expression based on frequency deviation based on the energy storage change and the derivative of current with respect to time under unit frequency change. The second magnetic flux inertia characterization module 804 is configured to obtain a magnetic flux inertia expression based on voltage deviation, based on the energy storage change under the unit voltage change and the derivative of current with respect to time.

[0103] In some optional embodiments of this example, the power topology includes SVG branches, VSG branches, and grid branches, wherein the SVG branches and VSG branches are connected to the grid branches through a grid connection point; The SVG branch includes an SVG DC-side capacitor, a transistor, a filter inductor, a filter capacitor, the line inductance of the SVG branch, and the line resistance. The VSG branch includes a new energy power station, a transistor, a filter inductor and a filter capacitor, and the line inductance and line resistance of the VSG branch. The power grid branch includes the line inductance and line resistance of the power grid branch.

[0104] In some optional embodiments of this example, determining the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change includes: The frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch and power grid branch are determined respectively. Based on the current sensitivity based on frequency deviation and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under unit frequency change is determined. Based on the voltage deviation-based current sensitivity and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under a unit voltage change is determined.

[0105] In some optional embodiments of this example, determining the frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch, and power grid branch includes: Determine the equivalent admittance of the SVG branch, VSG branch, and power grid branch respectively; The equivalent admittance of the hybrid grid-connected system is determined based on the equivalent admittance of the SVG branch, VSG branch and power grid branch. Based on the equivalent admittance of the SVG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the SVG branch are determined. Based on the equivalent admittance of the VSG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the VSG branch are determined. Based on the equivalent admittance of the power grid branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the power grid branch are determined.

[0106] In some optional embodiments of this example, the step of determining the equivalent admittance of the VSG branch includes: Determine the physical filter impedance and total control equivalent impedance of the VSG branch; The equivalent admittance of the VSG branch is determined based on the physical filter impedance and the total control equivalent impedance of the VSG branch.

[0107] In some optional embodiments of this example, the step of determining the equivalent admittance of the SVG branch includes: Determine the physical filter impedance and total control equivalent impedance of the SVG branch; The equivalent admittance of the SVG branch is determined based on the physical filter impedance and the total control equivalent impedance of the SVG branch.

[0108] In some optional embodiments of this example, the step of determining the equivalent admittance of the power grid branch includes: The equivalent admittance of the power grid branch is determined based on the line inductance and line resistance of the power grid branch.

[0109] According to embodiments of the present disclosure, the present disclosure also provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation of the foregoing embodiments.

[0110] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations.

[0111] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation.

[0112] Figure 12 A schematic block diagram of an example computer device 900 that can be used to implement embodiments of the present disclosure is shown. The computer device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The computer device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0113] like Figure 12As shown, device 900 includes a computing unit 901, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 902 or a computer program loaded from storage unit 908 into random access memory (RAM) 903. RAM 903 may also store various programs and data required for the operation of device 900. The computing unit 901, ROM 902, and RAM 903 are interconnected via bus 904. Input / output (I / O) interface 905 is also connected to bus 904.

[0114] Multiple components in device 900 are connected to I / O interface 905, including: input unit 906, such as keyboard, mouse, etc.; output unit 907, such as various types of monitors, speakers, etc.; storage unit 908, such as disk, optical disk, etc.; and communication unit 909, such as network card, modem, wireless transceiver, etc. Communication unit 909 allows device 900 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0115] The computing unit 901 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the various methods and processes described above, such as an equivalent magnetic flux inertia characterization method based on voltage and frequency deviations.

[0116] For example, in some embodiments, a method for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed on device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by computing unit 901, one or more steps of the method for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations described above can be performed. Alternatively, in other embodiments, computing unit 901 can be configured to perform a method for characterizing equivalent magnetic flux inertia based on voltage and frequency deviations by any other suitable means (e.g., by means of firmware).

[0117] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0119] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0121] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0122] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0123] It should be noted that in the description of this application, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0124] In the embodiments of this application, the singular forms "a," "the," etc., including the plural forms, should be broadly understood as "a kind" or "a class" rather than limited to the meaning of "an." Furthermore, the term "the" should be understood to include both the singular and plural forms, unless the context explicitly indicates otherwise. Additionally, the term "according to" should be understood as "at least partially based on…," and the term "based on" should be understood as "at least partially based on…," unless the context explicitly indicates otherwise.

[0125] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0126] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation, characterized in that, include: Constructing a power topology for a hybrid grid-connected system of grid-connected new energy power plants and SVG; Based on the power topology, the energy storage changes of the hybrid grid-connected system under unit frequency change and under unit voltage change are determined. Based on the changes in stored energy and the derivative of current with respect to time under unit frequency variation, an expression for magnetic flux inertia based on frequency deviation is obtained. Based on the energy storage change under the unit voltage change and the derivative of current with respect to time, the expression for magnetic flux inertia based on voltage deviation is obtained.

2. The characterization method according to claim 1, characterized in that, The power topology includes SVG branches, VSG branches, and grid branches, wherein the SVG branches and VSG branches are connected to the grid branches through grid connection points. The SVG branch includes an SVG DC-side capacitor, a transistor, a filter inductor, a filter capacitor, the line inductance of the SVG branch, and the line resistance. The VSG branch includes a new energy power station, a transistor, a filter inductor and a filter capacitor, and the line inductance and line resistance of the VSG branch. The power grid branch includes the line inductance and line resistance of the power grid branch.

3. The characterization method according to claim 2, characterized in that, Determining the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change includes: The frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch and power grid branch are determined respectively. Based on the current sensitivity based on frequency deviation and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under unit frequency change is determined. Based on the voltage deviation-based current sensitivity and the energy storage model of the hybrid grid-connected system, the energy storage change of the hybrid grid-connected system under a unit voltage change is determined.

4. The characterization method according to claim 3, characterized in that, Determining the frequency-bias-based current sensitivity and voltage-bias-based current sensitivity of the SVG branch, VSG branch, and power grid branch includes: Determine the equivalent admittance of the SVG branch, VSG branch, and power grid branch respectively; The equivalent admittance of the hybrid grid-connected system is determined based on the equivalent admittance of the SVG branch, VSG branch and power grid branch. Based on the equivalent admittance of the SVG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the SVG branch are determined. Based on the equivalent admittance of the VSG branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid-connected system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the VSG branch are determined. Based on the equivalent admittance of the power grid branch, the grid connection point voltage, and the equivalent admittance of the hybrid grid system, the current sensitivity based on frequency deviation and the current sensitivity based on voltage deviation of the power grid branch are determined.

5. The characterization method according to claim 4, characterized in that, The steps for determining the equivalent admittance of the VSG branch include: Determine the physical filter impedance and total control equivalent impedance of the VSG branch; The equivalent admittance of the VSG branch is determined based on the physical filter impedance and the total control equivalent impedance of the VSG branch.

6. The characterization method according to claim 4, characterized in that, The steps for determining the equivalent admittance of the SVG branch include: Determine the physical filter impedance and total control equivalent impedance of the SVG branch; The equivalent admittance of the SVG branch is determined based on the physical filter impedance and the total control equivalent impedance of the SVG branch.

7. The characterization method according to claim 4, characterized in that, The steps for determining the equivalent admittance of the power grid branch include: The equivalent admittance of the power grid branch is determined based on the line inductance and line resistance of the power grid branch.

8. A device for characterizing equivalent magnetic flux inertia based on voltage deviation and frequency deviation, characterized in that, include: The power topology construction module is configured to construct the power topology of a hybrid grid-connected system of grid-connected new energy power plants and SVG. The energy storage change determination module is configured to determine the energy storage change of the hybrid grid-connected system under unit frequency change and under unit voltage change based on the power topology. The first magnetic flux inertia characterization module is configured to obtain a magnetic flux inertia expression based on frequency deviation, based on the energy storage change and the derivative of current with respect to time under unit frequency change. The second magnetic flux inertia characterization module is configured to obtain a magnetic flux inertia expression based on voltage deviation, based on the energy storage change under the unit voltage change and the derivative of current with respect to time.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the equivalent magnetic flux inertia characterization method based on voltage deviation and frequency deviation as described in any one of claims 1 to 7.

Images