High-proportion new energy power grid interaction characterization method based on source network disturbance boundary

Abstract

The invention provides a high-proportion new energy power grid interaction characterization method based on a source network disturbance boundary, and the method comprises the following steps: building a full-system dynamic matrix of a power system, and building a transfer function between power equipment voltage disturbance and power supply voltage variation in the power system according to the full-system dynamic matrix. Obtaining a source network disturbance boundary index based on the transfer function and a matrix perturbation method, and analyzing the influence of the interaction of different devices on the system stability according to the source network disturbance boundary. According to the method, the influence degree of a transfer function between voltage disturbances of different devices on the devices is obtained based on the whole system dynamic matrix, the source network disturbance boundary index reflecting the interaction effect of the devices is determined, and the defect that a traditional impedance method only judges the overall stability of the system and cannot analyze which devices are strongly correlated to oscillation is overcome; and a basis is provided for researching the system stability and the interaction between different devices.

Description

Technical Field

[0001] The present invention relates to the technical field of power system stability control, and in particular to a method for characterizing the interaction of a high-proportion new energy power grid based on a source-grid disturbance boundary. Background Art

[0002] Building a new power system with new energy as the main body has become an important measure to achieve carbon reduction goals. Against the backdrop of large-scale access of new energy to the power grid, the dominant position of synchronous motors in the power system is gradually being replaced by power electronic equipment represented by converters.

[0003] However, oscillation problems caused by the grid connection of power electronic equipment have occurred in some areas. Compared with the traditional power system dominated by synchronous motors, the large-scale access of power electronic equipment makes the dynamic characteristics of the system more complex, and the oscillation phenomenon caused by it shows the characteristics of multi-type equipment interaction and multi-time scale mutual coupling. It can be seen that the stability of new energy grid connection has become an urgent and complex issue to be solved.

[0004] The state space method is an important method to describe the small signal stability of the system. The state space model is obtained by local linearization of the nonlinear power system. The eigenvalue of the system at the operating point can be obtained. By judging the positive and negative signs of the real part of the eigenvalue, it is determined whether the system maintains stability. The participation factor analysis based on the state space model gives the degree of participation of the state variable in the eigenvalue, so that it can be determined which state variables have a greater impact on the stability of the system. However, the establishment process of the state space model is essentially a simplification of the differential algebraic equations describing the dynamics of the system. It is necessary to obtain all the coefficients of the differential algebraic equations to obtain the eigenvalues ​​of the system, that is, the state space method needs to obtain the complete parameters of the system. Power electronic equipment manufacturers usually do not provide complete equipment parameters, and it is difficult to unify the equipment parameter standards of different manufacturers. When a large number of power electronic equipment are connected to the power grid, the number of state quantities increases sharply, which makes the solution of the state space model face the problem of "dimensionality curse". Therefore, the application of the state space method in power grids with a high proportion of power electronics is more difficult.

[0005] The impedance model is an important method for analyzing the grid-connected stability of power electronic equipment. It simplifies the system model in the complex frequency domain, compresses all dynamic behaviors into the transfer function relationship between the device port voltage and current, and gives the system stability conclusion by analyzing the interactive relationship between the grid-connected device impedance and the grid impedance. In practical applications, the device impedance model can be obtained by measuring methods such as frequency sweeping, so it is a "black box" model that does not require the complete system parameters. The dq impedance model of the grid-connected converter can be obtained by converting the three-phase circuit to the dq axis through Park transformation for small signal modeling. The system stability can be judged by using the generalized Nyquist criterion for the ratio of the dq impedance model and the grid impedance. The dq impedance model was first used only in the stability analysis of a single converter connected to an infinite system. When it was applied to a multi-machine system, there was a problem of misalignment of the dq coordinates of multiple devices. The full system dynamic matrix model uses the dynamic embedding method to achieve the alignment of the coordinate system of the dq impedance model of multiple devices, and uses a closed-loop formula to associate the device impedance model with the network node admittance matrix, expanding the application scope of the impedance model to multi-machine systems.

[0006] The traditional impedance analysis method uses the source-grid impedance ratio to determine system stability. This processing method can usually only give a system stability judgment result, but cannot analyze the impact of different devices on stability, let alone the strength of the interaction between different devices.

[0007] In summary, for engineering problems such as system planning and parameter optimization, it is often desirable to evaluate the impact of local system components on the overall stability. Therefore, a method for characterizing the interaction of a high-proportion renewable energy grid based on the source-grid disturbance boundary is needed to analyze the impact of the interaction between different devices on the stability of the power system. Summary of the invention

[0008] In view of the problems existing in the prior art, the present invention provides a method for quantifying the interaction between different devices in a high-proportion new energy power grid in a new power system with a large number of power electronic devices connected, thereby studying the relationship between system stability and the interaction between different devices, and providing quantitative indicators of the interaction between different devices.

[0009] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0010] The present invention provides a method for characterizing the interaction of a high-proportion new energy power grid based on a source-grid disturbance boundary, which comprises the following steps:

[0011] Establish the full system dynamic matrix of the power system;

[0012] Establishing a transfer function between the voltage disturbance of the power equipment and the voltage variation of the power supply in the power system according to the full system dynamic matrix;

[0013] Based on the transfer function and matrix perturbation method, a source network disturbance boundary index is obtained to characterize the interaction.

[0014] Optionally, the power system is a multi-machine system consisting of multiple power sources and supporting network components;

[0015] The method for establishing the whole system dynamic matrix comprises the following steps:

[0016] Establishing impedance models of multiple power sources and network elements in the power system;

[0017] Based on the impedance model, the admittance matrix of the entire system under the condition of a complex frequency domain multi-machine system is obtained.

[0018] Optionally, the method for establishing the whole system admittance matrix further includes the following steps:

[0019] Establish power admittance model and power network small signal model;

[0020] Based on the power supply admittance model and the power network small signal model, construct a relationship between a voltage disturbance and a corresponding current variation;

[0021] The whole system admittance matrix is ​​obtained by solving the relationship.

[0022] Optionally, the power supply admittance model is obtained by transforming a power supply state space model or by a measurement method.

[0023] Optionally, in the power admittance model, the small signal models of each power supply are aligned in coordinate system by a dynamic embedding method.

[0024] Optionally, the method for establishing the transfer function comprises the following steps:

[0025] The transfer function is obtained based on the full system dynamic matrix and the voltage and current variation relationship.

[0026] Optionally, the method for obtaining the source network disturbance boundary indicator comprises the following steps:

[0027] Assume that the determinant of the whole system dynamic matrix at the eigenvalue is 0, and obtain the sensitivity relationship between the eigenvalue and the transfer function by matrix perturbation method;

[0028] The sensitivity value is solved by the sensitivity relationship.

[0029] Optionally, the method for obtaining the source network disturbance boundary indicator further includes the following steps:

[0030] The sensitivity relationship is normalized.

[0031] Optionally, the method for obtaining the source network disturbance boundary indicator further includes the following steps:

[0032] Based on the normed result of the sensitivity relation, the variation of the maximum eigenvalue is substituted and the maximum variation of the transfer function is solved.

[0033] Optionally, based on the source-grid disturbance boundary index corresponding to the power source, the voltage variation margin between any device and the power grid bus node caused by the disturbance of the power source is obtained to characterize the interaction.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention obtains the degree of influence of the transfer function between voltage disturbances of different devices on the devices based on the dynamic matrix of the whole system, determines the source-grid disturbance boundary index reflecting the interaction of the devices, and makes up for the deficiency that the traditional impedance method only judges the overall stability of the system but cannot analyze which devices are strongly correlated with the oscillation, thus providing a basis for studying the system stability and the interaction between different devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0037] Figure 1 is a flow chart of the method of the present invention;

[0038] Figure 2 This is a structural diagram of a three-grid-type and one-grid-type converter system in Example 1;

[0039] Figure 3 It is the pole diagram of the three-grid type and one-grid type converter system in Example 1;

[0040] Figure 4 It is a spectrum diagram of the admittance matrix elements of the whole system of the three-grid type and one-grid type converter system in Example 1;

[0041] FIG5( a ) is a frequency response diagram of the grid-type converter after the active load of the bus connected to each grid-type converter in Example 1 increases by 0.5 pu;

[0042] FIG5( b ) is a voltage response diagram of the grid-type converter after the active load of the bus connected to each grid-type converter in Example 1 increases by 0.5 pu;

[0043] FIG6( a ) is a voltage response diagram of a bus voltage connected to each grid-type converter in Example 1, in which an oscillation source with a frequency of 12.26 Hz and an amplitude of 0.01 pu is applied followed by a grid-type converter;

[0044] FIG6( b ) is a frequency response diagram of the grid-type converter in Example 1 when the bus voltage connected to each grid-type converter is applied with a frequency of 12.26 Hz and an amplitude of 0.01 pu and then followed by an oscillation source;

[0045] FIG7( a ) is a voltage response FFT result of a bus voltage connected to each grid-type converter in Example 1 with an oscillation source having an applied frequency of 12.26 Hz and an amplitude of 0.01 pu followed by a grid-type converter;

[0046] FIG7( b ) is a frequency response FFT result of the grid-type converter in Example 1 when the bus voltage connected to each grid-type converter is applied with a frequency of 12.26 Hz and an amplitude of 0.01 pu and then followed by an oscillation source;

[0047] Figure 8 This is a structural diagram of a one-grid three-grid converter system in Example 1;

[0048] Fig. 9 It is the pole diagram of the one-grid three-grid converter system in Example 1;

[0049] Fig.10 It is a spectrum diagram of the admittance matrix elements of the whole system of the one-grid three-grid converter system in Example 1;

[0050] FIG11( a ) is a voltage response diagram of the grid-type converter after applying an oscillation source with a frequency of 23.42 Hz and an amplitude of 0.01 pu to the bus voltage connected to each grid-type converter in Example 1;

[0051] FIG11( b ) is a frequency response diagram of the grid-type converter after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 23.42 Hz and an amplitude of 0.01 pu;

[0052] FIG12( a ) is the FFT result of the voltage response of the grid-type converter after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 23.42 Hz and an amplitude of 0.01 pu;

[0053] FIG12( b ) is the frequency response FFT result of the grid-type converter after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 23.42 Hz and an amplitude of 0.01 pu;

[0054] Fig.13 The busbar system 14 in Example 1 is modified;

[0055] Fig.14 The pole diagram of the bus system 14 transformed in Example 1;

[0056] Fig.15 This is the spectrum diagram of the admittance element of the whole system of the 14-bus system transformed in Example 1;

[0057] FIG. 16( a ) is a voltage response diagram of the grid-type converter GFMA6 after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 30.06 Hz and an amplitude of 0.01 pu;

[0058] FIG. 16( b ) is a frequency response diagram of the grid-type converter GFMA6 after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 30.06 Hz and an amplitude of 0.01 pu;

[0059] FIG. 17( a ) is a voltage response FFT result of the grid-type converter GFMA6 after applying an oscillation source with a frequency of 30.06 Hz and an amplitude of 0.01 pu to the bus voltage connected to each grid-type converter in Example 1;

[0060] FIG. 17( b ) is the frequency response FFT result of the grid-type converter GFMA6 after the bus voltage connected to each grid-type converter in Example 1 is applied with an oscillation source having a frequency of 30.06 Hz and an amplitude of 0.01 pu. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0063] It is worth noting that the methods used in the present invention are all conventional methods unless otherwise specified; the raw materials and devices used are all conventional commercially available products, and their sources are not specifically limited unless otherwise specified.

[0064] It should be noted that in order to facilitate understanding in the specific embodiments of the present invention, the method steps are described in a certain order, but those skilled in the art can change the order of the steps according to actual needs, and therefore this cannot be used as a limiting condition.

[0065] like Figure 1 As shown, this embodiment provides a method for characterizing the interaction of a high proportion of new energy grids based on a source-grid disturbance boundary, comprising the following steps:

[0066] Step 1: Establishing a full system dynamic matrix of the power system. The method includes: First, the power system to which the present invention is applicable is a multi-machine system composed of multiple power sources and supporting network elements, so an impedance model including all power sources and network elements is established.

[0067] Furthermore, the admittance matrix model of the whole system is obtained under the condition of establishing a multi-machine system in the complex frequency domain.

[0068] Optionally, a power supply admittance model and a power network small signal model are established, wherein the power supply admittance model can be simplified by a state space model or obtained by measurement, namely:

[0069]

[0070] Among them, Y Gi and Z Gi They represent the admittance and impedance of the power source connected to bus i in the complex frequency domain, and are the corresponding elements of the device admittance in the dq rotating coordinate system. If there is no power at bus i, then Y Gi =0.

[0071] It should be noted that the small signal model of each power supply in the multi-machine system is established in its own reference coordinate system, so it is necessary to align the coordinate system through the dynamic embedding method. The power admittance matrix Y of the system can be obtained from the admittance models of each power supply after the coordinate system is aligned. G :

[0072]

[0073] Among them, Y G ∈2n×2n represents the admittance matrix of the system power supply, and n is the number of system nodes.

[0074] Furthermore, the power network small signal model Y N It is the node admittance matrix established in the complex frequency domain dq coordinate system:

[0075]

[0076] Among them, Y Nij represents the mutual admittance element between buses i and j, Y Nii represents the self-admittance element of bus i.

[0077] Considering the disturbance value of the voltage injected at each busbar of the network as input, the following formula is obtained:

[0078] Δu=ΔU=[ΔU1…ΔU i …ΔU n ] T (4)

[0079] Among them, Δu is equivalent to ΔU, which represents the voltage change on the device, ΔU i is the injected voltage disturbance value of bus i, which has two components, dq, namely ΔU i =[ΔU id ,ΔU iq ] T , T represents matrix transpose.

[0080] The current change caused at each busbar is output as:

[0081] Δy=ΔI=[ΔI1…ΔI i …ΔI n ] T (5)

[0082] Among them, Δy is equivalent to ΔI, which represents the change in current, and ΔI i =[ΔI id ,ΔI iq ] T .

[0083] When there is an injected voltage disturbance at the bus, it can be known from Kirchhoff's voltage law that the sum of the power supply voltage change and the injected voltage change is equal to the grid connection point voltage change, and the grid connection point voltage change and the injected current change satisfy the constraints of the node admittance matrix. Therefore, by constructing the relationship between the voltage disturbance and the corresponding current change, the relationship between the injected voltage disturbance and the corresponding current change can be established, as shown in the following formula:

[0084]

[0085] Where E is the unit matrix, Y and Z are the full system dynamic matrices that reflect the response transfer function of the injected disturbance to the bus; Z is the full system impedance matrix; Y is the full system admittance matrix, which is the full system dynamic matrix obtained under the background of voltage disturbance as input and current disturbance as output; Z N is the impedance associated with the small signal model of the power network, Z G is the impedance of the power source; Δx is equivalent to the aforementioned Δu, which represents the disturbance value of the voltage injected at each bus of the network as input.

[0086] Step 2: Establish the transfer function between the voltage disturbance of power equipment and the change of power supply voltage in the power system based on the dynamic matrix of the whole system.

[0087] Specifically, a transfer function of the power grid bus voltage to the power supply voltage is constructed, and the construction method includes the following steps:

[0088] The voltage change and current change on the device meet the following conditions:

[0089] ΔU G =(Y G ) -1 ΔI G (7)

[0090] Combining equations (6) and (7), we can obtain the transfer function relationship from the voltage change on the device to the network series disturbance voltage source:

[0091] ΔU=(Z N +Z G )ΔI=(Z N +Z G )Y G ΔU s (8)

[0092] Among them, ΔU s is the voltage disturbance value on the power supply.

[0093] Equation (8) reflects the impact of power supply voltage disturbance on network injection disturbance. Obviously, each element of the transfer function matrix represents the interaction between a specific power supply and the bus connected to another device, that is:

[0094] ΔU k =[(Z N +Z G )Y G ] kj ΔU sj (9)

[0095] Among them, ΔU k is the disturbance magnitude of the voltage source connected in series with the kth bus, ΔU sj is the voltage disturbance value on the jth power supply.

[0096] Step 3: Obtain source network disturbance boundary indicators based on transfer function and matrix perturbation method.

[0097] Further, a source network disturbance boundary indicator is constructed, and the method includes the following steps:

[0098] Assume that the determinant of the dynamic matrix of the whole system at the eigenvalue is 0, that is, the i-th eigenvalue of the system satisfies:

[0099] Z N (λ i )+Z G (λ i )|=0 (10)

[0100] So we have:

[0101]

[0102] Among them, λ i is the i-th eigenvalue of the system.

[0103] The state space participation analysis locates the key state of the system by solving the sensitivity of the eigenvalue to the state matrix, while the impedance model participation analysis locates the key components of the system by solving the sensitivity of the eigenvalue to the component admittance. By analogy with the state space participation analysis method and the component impedance participation analysis method, according to the matrix perturbation system, there is the following sensitivity relationship:

[0104]

[0105] Among them, Res λi () represents the matrix at eigenvalue λ i The residue at , and it should be considered that the oscillation mode under investigation is caused by the interaction between the power source and the network, that is, the power source and the grid remain stable when not connected to the grid. This assumption is reasonable in analyzing the grid stability problem.

[0106] Formula (12) represents the transfer function between the specific characteristic value and the device voltage change [(Z G (λ i )+Z N (λ i ))·Y G (λ i )], whose magnitude represents the degree of correlation between the transfer function and the eigenvalue. If the sensitivity is large, it means that a small Δ[(Z G (λ i )+Z N (λ i ))·Y G (λ i )], a large eigenvalue change Δλ will occur i , that is, the system's anti-interference ability is low and the system stability is poor.

[0107] The elements of the matrix in formula (12) represent the sensitivity of the eigenvalue to the voltage change transfer function between specific devices, that is:

[0108]

[0109] Since the device impedance is established in the dq coordinate system, equation (13) is in the form of a second-order matrix. Therefore, the sensitivity relationship is quantified using the Frobenius norm:

[0110]

[0111] Among them, ||F means taking the Frobenius norm of the matrix.

[0112] If the change of the eigenvalue in the left half of the complex plane is greater than the absolute value of its real part, then the changed eigenvalue may be in the right half of the complex plane, and the system is unstable. Therefore, the maximum change of the eigenvalue that maintains the stability of the system is substituted into the above formula to determine the maximum change of the transfer function corresponding to the maximum change of the eigenvalue, and thus define the source-to-grid perturbation propagation boundaries (SGB):

[0113]

[0114] Among them, SGB kj (λ i ) represents the source network disturbance boundary, which represents the voltage variation margin on the grid bus connected to device k caused by the disturbance of power source i; -σ i The maximum eigenvalue change required to maintain system stability.

[0115] Based on the SGB index corresponding to the specific power source, the voltage change margin of the grid bus node connected to any device caused by the disturbance of the corresponding power source is obtained to characterize the interaction. kj (λ i ) is large, indicating that the eigenvalue is less sensitive to the interaction between the two devices, the range of the eigenvalue change is larger, and the system stability is stronger. In practical applications, by calculating the source network disturbance boundary of a certain device to different devices, it is possible to directly determine which devices are strongly related to the oscillation at the device, thereby making the solution to enhance system stability more targeted.

[0116] Embodiment 1;

[0117] The method of the present invention is described in detail below in conjunction with specific examples:

[0118] like Figure 2 As shown, this embodiment takes a three-grid-type and one-grid-type converter system as an example, wherein all line impedances are 0.1+0.3jp.u., and the system control parameters are shown in Table 1 below:

[0119]

[0120] Table 1

[0121] from Figure 3 The pole distribution diagram of the system shows that there is a weakly damped oscillation mode 2π·(-0.06+12.26j). Figure 4The total system admittance element spectrum is reflected as a peak at 12.26Hz. The source-grid disturbance boundaries of the grid-type converter and the grid-type converter with different configurations are calculated as SGB and 1-2 =2.7373, SGB 1-3 =6.3741, SGB 1-4 =35.6476, which means that the eigenvalue is most sensitive to the interaction between bus 1 and bus 2, that is, the order of disturbances caused by the grid-type converters at bus 2, 3, and 4 is GFM2>GFM3>GFM4. Figure 5(a) and Figure 5(b) show the voltage and frequency changes of the grid-type converters after adding 0.5pu active load to bus 2, 3, and 4 respectively; it can be seen that under the same disturbance size, the oscillation at GFL1 caused by GFM2 is the most violent, followed by GFM3, and the oscillation amplitude caused by GFM4 is the smallest, which is consistent with the theoretical analysis conclusion. Figure 6(a), Figure 6(b) and Figure 7(a), Figure 7(b) respectively show the voltage, frequency response and FFT (Fast Fourier Transform) results of GFL1 after applying the oscillation source at bus 2, 3, and 4, which are consistent with the theoretical results, indicating the effectiveness of the source-grid disturbance boundary index.

[0122] Figure 8 As shown, in a three-grid inverter system, all line impedances are 0.1+0.3jp.u. The system control parameters are shown in Table 2 below:

[0123]

[0124] Table 2

[0125] Fig. 9 The system pole diagram shown shows that there is a weakly damped oscillation mode in the system, reflected in Fig.10 There is a resonance peak of 23.42Hz in the system admittance matrix element spectrum diagram shown in the figure. The source grid disturbance boundary indicators between the grid-type converter and the grid-type converter are calculated as SGB and 1-2 =0.0349, SGB 1-3 =0.0401, SGB 1-4 =0.0425, indicating that the disturbances at bus 2, 3, and 4 cause the oscillation of the grid-type converter connected to bus 1 to be ranked as GFL2>GFL3>GFL4. Figures 11(a), 11(b) and 12(a), 12(b) respectively show the voltage and frequency response and FFT results at GFM1 after the oscillations are applied to bus 2, 3, and 4. The simulation results show that GFL2 has the greatest impact on the oscillation at GFM1, followed by GFL3, and GFL4 has the least impact, which is consistent with the judgment results of the source network disturbance boundary index.

[0126] consider Fig.13 The modified IEEE14 bus system shown has a topological structure consistent with the IEEE standard 14 bus system, but the specific devices connected to the bus are different, wherein busbars 1, 2, 3 and 8 are connected to synchronous machines, busbar 6 is connected to a grid-forming converter, and busbars 11, 12 and 13 are connected to a grid-following converter. In this embodiment, the control parameters of the modified IEEE14 bus system are shown in Table 3 below:

[0127]

[0128] Table 3

[0129] Fig.14 The system pole diagram and Fig.15 The total system admittance element spectrum shown shows that there is an oscillation mode of 30.06Hz in the system. The result of calculating the source network disturbance boundary index is SGB 6-11 =0.3765, SGB 6-12 =0.2716, SGB 6-13 =0.3062, SGB results show that when GFL connected to bus 11, 12, 13 is disturbed, the oscillation magnitude of GFM6 connected to bus 6 is GFL12>GFL13>GFL11. Figures 16(a), 16(b) and 17(a), 17(b) respectively show the voltage and frequency response and FFT results of GFM6 after the bus applies the oscillation source. The simulation results show that under the premise of the same oscillation source amplitude, the oscillation at GFL12 causes the most violent oscillation at GFM6, followed by GFL13, and the smallest at GFL11, that is, the interaction between GFL11 and GFM6 has the least effect on system stability, which is consistent with the SGB index analysis results, proving that the SGB index can be used in the stability analysis of multi-machine systems.

[0130] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A method for characterizing the interaction of a high-proportion renewable energy grid based on source-grid disturbance boundaries, characterized in that: The steps include: Establish a full system dynamic matrix of the power system; Establishing a transfer function between the voltage disturbance of the power equipment and the voltage variation of the power supply in the power system according to the full system dynamic matrix; Based on the transfer function and matrix perturbation method, a source network disturbance boundary index is obtained to characterize the interaction.

2. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 1 is characterized in that: The power system is a multi-machine system consisting of multiple power sources and supporting network components; The method for establishing the whole system dynamic matrix comprises the following steps: Establishing impedance models of multiple power sources and network elements in the power system; Based on the impedance model, the admittance matrix of the entire system under the condition of a complex frequency domain multi-machine system is obtained.

3. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 2 is characterized in that: The method for establishing the whole system admittance matrix also includes the following steps: Establish power admittance model and power network small signal model; Based on the power supply admittance model and the power network small signal model, construct a relationship between a voltage disturbance and a corresponding current variation; The whole system admittance matrix is ​​obtained by solving the relationship.

4. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 3 is characterized in that: The power supply admittance model is obtained by transforming a power supply state space model or by a measurement method.

5. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 3 or 4, characterized in that: In the power admittance model, the small signal models of each power supply are aligned in coordinate system by a dynamic embedding method.

6. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 5 is characterized in that: The method for establishing the transfer function comprises the following steps: The transfer function is obtained based on the full system dynamic matrix and the voltage and current variation relationship.

7. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 6 is characterized in that: The method for obtaining the source network disturbance boundary index comprises the following steps: Assume that the determinant of the whole system dynamic matrix at the eigenvalue is 0, and obtain the sensitivity relationship between the eigenvalue and the transfer function by matrix perturbation method; The sensitivity value is solved by the sensitivity relationship.

8. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 7 is characterized in that: The method for obtaining the source network disturbance boundary index also includes the following steps: The sensitivity relationship is normalized.

9. The method for characterizing the interaction between a high proportion of new energy power grids based on source-grid disturbance boundaries according to claim 8 is characterized in that: The method for obtaining the source network disturbance boundary index also includes the following steps: Based on the normed result of the sensitivity relation, the variation of the maximum eigenvalue is substituted and the maximum variation of the transfer function is solved.

10. The method for characterizing high-proportion new energy grid interaction based on source-grid disturbance boundary according to claim 9 is characterized in that: Based on the source-grid disturbance boundary index corresponding to the power source, the voltage variation margin of the power grid bus node connected to any device caused by the disturbance of the power source is obtained to characterize the interaction.

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