Optimal configuration method, device and medium for network-following-and-network-constructing type series-parallel system considering uncertainty

Abstract

The invention relates to an optimization configuration method, equipment and medium for a network-following construction type series-parallel system considering uncertainty, and the method comprises the steps: constructing a converter optimization configuration model by taking the minimum number of reconstruction times as an optimization target and taking the robust stability of the series-parallel system as a constraint condition; the optimized configuration process of the series-parallel system comprises the following steps: S1, segmenting the current series-parallel system into equivalent network following / network constructing subsystems, respectively calculating a generalized short-circuit ratio, determining a critical value of small interference stability of a corresponding nominal system, and solving a generalized short-circuit ratio and a robust stability margin of critical robustness of a subsynchronous frequency band based on a small gain theorem; s2, judging whether constraint conditions are met or not, if yes, ending the current optimization process, and otherwise, turning to S3; and S3, identifying the weakest feed-in point in the current series-parallel system by adopting a participation factor method, transforming the station corresponding to the weakest feed-in point into network construction type control, and turning to S1. Compared with the prior art, the input cost in the system transformation process is reduced on the basis of ensuring the robust stability of the system.

Description

Technical Field

[0001] The present invention relates to the field of converter configuration of a new energy power system, and in particular to an optimization configuration method, equipment and medium for a grid-connected hybrid system taking uncertainty into account. Background Art

[0002] With the increasing penetration of new energy sources such as wind power and photovoltaic power, the power system is transforming into a new power system dominated by power electronic equipment. New energy grid-connected equipment (i.e., converters) with power electronics as interfaces usually adopt two typical control methods: grid-following (GFL) and grid-forming (GFM). As synchronous machines are gradually replaced, the voltage support strength of the power system dominated by grid-following converters decreases, and subsynchronous oscillation instability is easily caused under weak grid conditions with low short circuit ratio (SCR). In contrast, grid-forming converters can actively establish and support grid voltage and frequency, have good adaptability to weak grids, and have received widespread attention in the industry.

[0003] As grid-connected converters that replace the supporting role of synchronous machines are gradually put into use, a power system with a hybrid network of grid-connected and grid-connected (hereinafter referred to as a "hybrid system") will be formed. The comprehensive use of grid-connected / grid-connected converters is equivalent to re-matching the converter with a suitable short-circuit ratio, thereby ensuring the converter's stability in weak and strong grids with small disturbances. However, most of the existing research on hybrid systems ignores the impact of uncertainty, and its theory is based on the assumption that the external characteristics of grid-connected (grid-connected) converters are similar. In actual hybrid systems, not only do converters with different control methods have different external characteristics (strong heterogeneity), but converters using the same control method are also usually "heterogeneous" (weak heterogeneity). The robust stability boundary and margin from the perspective of grid strength can be quantified by combining the converter dynamic partitioning method and the small gain theorem.

[0004] The quantification of the robust stability boundary of the hybrid system can provide theoretical guidance for the networking transformation of the grid-following type station. Since the configuration of the grid-following type converter can effectively improve the strength of the AC power grid, improve the stability of the subsynchronous frequency band, and increase the risk of low-frequency oscillation instability. In order to suppress low-frequency oscillations and reduce investment costs, in the process of networking transformation of existing grid-following type stations, it is necessary to answer the question of how to configure the proportion and location of the grid-following / grid-following type equipment to minimize the number of transformations on the basis of ensuring robust stability. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method, device and medium for optimizing the configuration of a grid-connected hybrid system taking into account uncertainty, thereby reducing the investment cost in the system transformation process while ensuring the robustness and stability of the system.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] According to a first aspect of the present invention, a method for optimizing the configuration of a hybrid system with a grid-connected network taking uncertainty into account is provided. The optimization objective is to minimize the number of transformations, and the robust stability of the hybrid system after the transformation is used as a constraint condition to construct a converter optimization configuration model. The optimization configuration process of the hybrid system includes:

[0008] S1. Dynamically divide the current hybrid system into an equivalent grid-following subsystem and an equivalent grid-forming subsystem, calculate the generalized short-circuit ratio of the equivalent subsystem respectively, use the generalized short-circuit ratio as a quantitative indicator of grid strength, determine the critical value of the small disturbance stability of the corresponding nominal system through the dominant characteristic root locus, and solve the generalized short-circuit ratio and robust stability margin of the critical robustness of the subsynchronous frequency band based on the small gain theorem;

[0009] S2. According to the generalized short-circuit ratio of the equivalent subsystem, the generalized short-circuit ratio of the critical robustness of the subsynchronous frequency band, and the robust stability margin, determine whether the current hybrid system meets the robust stability constraint condition. If the robust stability constraint condition is met or the maximum number of transformations is reached, the current optimization process is terminated and the number of transformations and the configuration result of the hybrid system after optimization are output. Otherwise, go to S3.

[0010] S3. Use the participation factor method to identify the weakest feeding point in the current hybrid system, transform the station corresponding to the weakest feeding point into a grid-type control, and go to S1.

[0011] Preferably, the multiplicative perturbation model of the hybrid system includes:

[0012] Nominal system equipment side:

[0013]

[0014] Where: Y GFL (s) indicates the dynamics of network-based devices, Y PLL (s) is the nominal grid-type converter admittance, Y GFM (s) represents the dynamics of networking equipment, Y GF (s) is the nominal grid-type converter admittance, S1 and S2 are the diagonal matrices consisting of the capacity ratios of the grid-type converter and the grid-type converter, respectively, e Jθ and e -Jθ is the coordinate transformation matrix between the global coordinate system and the local coordinate system, and θ represents the steady-state phase angle difference between the two coordinate systems;

[0015] Nominal system network side:

[0016]

[0017] Where: Y multi_grid (s) represents the network side dynamics, the B matrix is ​​the node admittance matrix of the AC network, ω0 is the nominal frequency of the system, and τ is the R / L ratio of the line;

[0018] Uncertainty perturbation:

[0019]

[0020] in, is the device admittance matrix of the ith converter in the global coordinate system of the actual hybrid system, e Jθ Y C (s)e -Jθ is the device admittance matrix in the global coordinate system of the nominal grid-following system or the nominal grid-forming system;

[0021] The uncertainty perturbation Δ(s) consists of two block diagonal matrices Δ PLL (s) and Δ GF (s), corresponding to network-following devices and network-building devices respectively:

[0022]

[0023] Preferably, the equivalent network subsystem The closed-loop dynamics are:

[0024]

[0025] in: is the admittance matrix of the grid-connected converter considering the uncertainty on the equipment side, B redv is the equivalent network node admittance matrix after kron reduction;

[0026] The equivalent network subsystem The closed-loop dynamics are:

[0027]

[0028] B redp =B 11

[0029] in: is the admittance matrix of the grid-connected converter considering the uncertainty on the equipment side, B redp To delete the sub-matrices corresponding to the rows and columns of the grid-type converter nodes in matrix B.

[0030] Preferably, the converter optimization configuration model has a mathematical expression as follows:

[0031] min(K)

[0032]

[0033] Where: K is the number of transformations; gSCR p and gSCR v CgSCR is the generalized short-circuit ratio of the equivalent grid-following subsystem and the equivalent grid-forming subsystem, which is used to quantify the subsynchronous frequency band / low frequency band power grid strength; p and CgSCR v are the critical generalized short-circuit ratios for small-disturbance stability of the equivalent grid-following subsystem and the equivalent grid-building subsystem, respectively; CRgSCR p is the critical robust generalized short-circuit ratio; η is the robust stability margin of the subsynchronous frequency band of the system, η set Minimum robust stability margin requirement to account for equipment uncertainties.

[0034] Preferably, the participation factor method is used to identify the weakest feed-in point in the current parallel-parallel system, wherein the participation factor calculation expression of node i in the equivalent grid subsystem is:

[0035]

[0036] Where: p 1,i is the generalized short-circuit ratio gSCR of the equivalent grid subsystem p The participation factor for node i, L i,i To expand the admittance matrix The i-th diagonal element of and They represent the generalized short-circuit ratio gSCR of the equivalent grid subsystem. p The corresponding left and right eigenvectors satisfy

[0037] Preferably, the generalized short-circuit ratios of the equivalent grid-connected subsystem and the equivalent grid-connected subsystem are calculated respectively according to the equivalent network admittance matrix and the equipment capacity matrix. The calculation expressions are specifically as follows:

[0038]

[0039] Among them: gSCR v Equivalent Network Subsystem The generalized short-circuit ratio is used as a quantitative indicator of the low-frequency grid strength of the hybrid system; gSCR p Equivalent network subsystem The generalized short-circuit ratio is used as a quantitative indicator of the grid strength in the subsynchronous frequency band of the hybrid system; Δλ(s) is the perturbation caused by the dynamics of the grid-connected converter in the equivalent network.

[0040] Preferably, determining the critical value of the small disturbance stability of the corresponding nominal system by the dominant characteristic root locus specifically includes:

[0041] Select the nominal system model and determine the critical value CgSCR of the nominal grid-type system's small disturbance stability through the dominant characteristic root loci in the low frequency band p , the critical value CgSCR of small disturbance stability of nominal grid-following system is determined by the dominant characteristic root locus of subsynchronous frequency band v .

[0042] Preferably, the method of solving the critical robust generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band based on the small gain theorem specifically includes:

[0043] According to the maximum modulus theorem, the frequency domain characteristic curve of the singular value of the uncertainty perturbation Δ(s) is plotted, and the H of the uncertainty perturbation Δ(s) is determined by the peak value of the frequency domain characteristic curve. ∞ The upper bound of the norm, Among them, sup represents the maximum value, σ max [·] is the largest singular value of the matrix ·;

[0044] The relationship between the generalized short-circuit ratio and the complementary sensitivity peak is established as follows:

[0045]

[0046] Where: κ2(W) is the spectral condition number of the matrix W, when SB -1 When it is a symmetric matrix, κ2(W)=1; gSCR is the generalized short-circuit ratio of the equivalent subsystem;

[0047] Based on the small gain theorem, the critical robust generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band are solved, and the calculation expression is:

[0048]

[0049] Where: δ is the inverse of the upper bound of the uncertainty perturbation, that is

[0050] The robust stability margin of the subsynchronous frequency band of the system is calculated as:

[0051] η=gSCR p -CRgSCR p .

[0053] According to a second aspect of the present invention, there is provided an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, any one of the methods described above is implemented.

[0054] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, any one of the methods described above is implemented.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] (1) The proposed scheme for optimizing the configuration of the grid-connected hybrid system takes the minimum number of grid-connected transformations as the optimization goal, reduces the investment cost while suppressing low-frequency oscillations, and fully considers the influence of uncertainty factors on the equipment side. The generalized short-circuit ratio is used as a quantitative indicator of the grid strength, and robust stability quantitative calculation is performed. The hybrid system is optimized with the robust stability of the hybrid system as a constraint condition. Taking into account the uncertainty factors existing on the equipment side of the actual hybrid system, the investment cost in the system transformation process is minimized on the basis of ensuring the robust stability of the system.

[0057] (2) The present invention adopts the short-circuit ratio of the weakest single-feed grid-following / grid-forming system and the critical stability when taking uncertainty into account to characterize the critical value of robust stability. Its calculation only involves 2×2-order matrix operations, avoiding the "curse of dimensionality" problem caused by high-order matrix operations.

[0058] (3) The present invention adopts the participation factor method to identify the weakest feeding point in the hybrid system, and preferentially transforms the corresponding converter station into a grid-type control mode, thereby avoiding the problem of increased risk of low-frequency oscillation instability caused by an increase in the generalized short-circuit ratio of the equivalent grid-type subsystem due to an increase in the number of configured grid-type converters, and the system has higher robust stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a schematic diagram of a flow chart of optimizing configuration of a grid-connected hybrid multi-feed system taking uncertainty into account in an embodiment of the present invention;

[0060] Figure 2 It is a flowchart of a specific embodiment of the present invention;

[0061] Figure 3 Schematic diagram of a two-zone-four-machine system in an embodiment of the present invention;

[0062] Figure 4 It is a schematic diagram of deconstructing a hybrid multi-feed system model in an embodiment of the present invention;

[0063] Figure 5 is a schematic diagram of a frequency domain characteristic curve of uncertainty perturbation in an embodiment of the present invention;

[0064] Figure 6 is a relationship diagram between the complementary sensitivity peak and gSCRp in an embodiment of the present invention;

[0065] Figure 7 4 is a time domain simulation result diagram of a two-zone, four-machine system in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 should fall within the scope of protection of the present invention.

[0067] Example

[0068] like Figure 1 As shown, this embodiment provides an optimization configuration method for a hybrid system of a grid-connected type taking uncertainty into account, takes the minimum number of transformations as the optimization goal, takes the robust stability of the hybrid system after the transformation as the constraint condition, and constructs a converter optimization configuration model. The hybrid system optimization configuration process includes:

[0069] S1. Dynamically divide the current hybrid system into an equivalent grid-following subsystem and an equivalent grid-forming subsystem, calculate the generalized short-circuit ratio of the equivalent subsystem respectively, use the generalized short-circuit ratio as a quantitative indicator of grid strength, determine the critical value of the small disturbance stability of the corresponding nominal system through the dominant characteristic root locus, and solve the generalized short-circuit ratio and robust stability margin of the critical robustness of the subsynchronous frequency band based on the small gain theorem;

[0070] S2. According to the generalized short-circuit ratio of the equivalent subsystem, the generalized short-circuit ratio of the critical robustness of the subsynchronous frequency band, and the robust stability margin, determine whether the current hybrid system meets the robust stability constraint condition. If the robust stability constraint condition is met or the maximum number of transformations is reached, the current optimization process is terminated and the number of transformations and the configuration result of the hybrid system after optimization are output. Otherwise, go to S3.

[0071] S3. Use the participation factor method to identify the weakest feeding point in the current hybrid system, transform the station corresponding to the weakest feeding point into a grid-type control, and go to S1.

[0072] Next, combine Figure 2 , the method of this embodiment is introduced in detail.

[0073] (1) Input the initial value of the rated capacity of the hybrid system and the original data such as the equivalent AC network line impedance;

[0074] (2) Constructing an equivalent networking subsystem of the current system and equivalent network subsystem Calculate the generalized short-circuit ratio gSCR of the equivalent subsystem v and gSCR p ;

[0075] (3) Select an appropriate nominal model and determine the critical value of small disturbance stability CgSCR through the dominant characteristic root locus of the low frequency band / subsynchronous frequency band v / CgSCR p ;

[0076] (4) Analysis of uncertainty perturbation Δ PLL (s) Frequency domain characteristic curve of singular value, determine the perturbation H ∞ Norm upper bound δ -1 ;

[0077] (5) Plotting the nominal grid-type system after decoupling and connecting to different gSCRs p The complementary sensitivity peak curve of the AC system is used to solve the critical robust generalized short-circuit ratio CRgSCR in the subsynchronous frequency band. p and the robust stability margin η.

[0078] (6) Determine whether the system meets the constraints. If so, end the process, count the number of transformations K, and output the ratio and location of the optimized system and network / network-type equipment. Otherwise, proceed to the next step.

[0079] (7) Calculate the participation factor of the multi-feed system, determine the weakest feed point i, transform the station corresponding to feed point i into grid-type control, and then return to (2).

[0080] This embodiment is built in Matlab / Simulink environment as follows Figure 3 In the two-zone-four-machine system shown in the figure, all converters in the initial system are controlled in a grid-following manner. First, an initial system model taking into account equipment uncertainty is established. Since the initial system is a heterogeneous multi-input grid-following system, its model can be constructed by ignoring the grid-following equipment part based on the multiplicative perturbation model of the hybrid system:

[0081] 1) Nominal system equipment side:

[0082]

[0083] Among them, Y GFL (s) indicates the dynamics of network-based devices, Y PLL (s) is the nominal grid-type converter admittance, and S1 is the diagonal matrix formed by the grid-type converter capacity ratio.

[0084] 2) Nominal system network side:

[0085]

[0086] Among them, Y multi_grid (s) represents the network side dynamics, ω0 is the nominal frequency of the system, and τ is the R / L ratio of the line. The B matrix is ​​the node admittance matrix of the AC network, which can be expressed in blocks as follows:

[0087]

[0088] 3) Uncertainty perturbation:

[0089]

[0090] in, is the device admittance matrix of the ith grid-connected converter in the global coordinate system, e Jθ Y PLL (s)e -Jθ is the device admittance matrix of the nominal grid-type system in the global coordinate system.

[0091] Then, the grid-forming converter is dynamically merged into the equivalent network, such as Figure 4 As shown in Figure 1, the hybrid system is deconstructed into two subsystems dominated by a single type of converter on the equipment side, and an equivalent heterogeneous multi-infeed grid-following / grid-forming system is constructed to approximate the dominant oscillation modes of the two subsystems Σ2 and Σ1. Since the initial system is a heterogeneous multi-infeed grid-following system, its equivalent grid-following subsystem That is the initial system itself. Based on the original data of the initial system, the admittance matrix of the AC network after node compression is derived:

[0092]

[0093] At the same time, you can obtain The minimum eigenvalue of gSCR is P ≈3.52.

[0094] In order to reduce the conservatism of the robust stability criterion, the grid-following device that can minimize the perturbation is selected as the nominal model. According to the characteristic equation of the “weakest” single-feed grid-following system after decoupling the nominal grid-following system and gSCR p Explicit relationship between:

[0095] c(s)=det(Y PLL (s)+gSCR p *F(s))

[0096] By plotting the dominant characteristic root locus of the subsynchronous frequency band of the nominal network system on MATLAB, we can know that CgSCR p When the frequency is 3.72, the nominal grid-type system is approximately in a critical stable state in the sub-synchronous frequency band.

[0097] Then analyze the uncertainty perturbation Δ PLL (s) Frequency domain characteristic curve of singular value, determine the perturbation H ∞ Norm upper bound, device uncertainty perturbation Δ PLL The expression of (s) is:

[0098]

[0099] in, Equivalent network subsystem The device admittance matrix of the i-th converter in the global coordinate system, e Jθ Y PLL (s)e -Jθ is the device admittance matrix in the global coordinate system of the nominal tracking system.

[0100] Analyze the above uncertainty perturbation and plot σ on MATLAB max [Δ PLL,i The distribution curve of (jω)] with frequency (such as Figure 5 As shown), determine the peak value of the perturbation and its inverse δ.

[0101] Uncertain perturbation Δ on the device side PLL (s) affects the critical value of small disturbance stability of the nominal grid-following system CgSCR p By inversely solving the following equation, the critical robust generalized short-circuit ratio CRgSCR can be obtained: p The explicit expression for is:

[0102]

[0103] The above solution process is equivalent to drawing the “weakest” single-feed system connected to different gSCRs after the nominal grid-type system is decoupled on MATLAB. p The complementary sensitivity peak curve of the AC system (such as Figure 6 As shown), CRgSCR p gSCR corresponding to the vertical coordinate of δ / κ2(W) p value.

[0104] The equivalent grid subsystem based on the generalized short-circuit ratio is obtained The robust stability and its critical value quantitative evaluation index can define the robust stability margin of the subsynchronous frequency band of the system as:

[0105] η=gSCR p -CRgSCR p

[0106] Then, calculate the gSCR for each feed point p The sensitivity of the initial system is used to find the weak point of the initial system. The participation factors of each feeding point of the initial system are given in Table 1 below.

[0107] Table 1 Participation factors of the initial system

[0108] Feed point 1 2 3 4 Participation Factor 0.0410 0.0254 0.6705 0.2631

[0109] Table 1 shows that the participation factor of feed point 3 is the largest. Therefore, it is preferred to transform the grid-type station at feed point 3 into a grid-type station. Next, construct an equivalent subsystem of the transformed system. and And calculate gSCR v . The equivalent network admittance matrix B redp Expressed as the AC network admittance matrix B with the rows and columns corresponding to the feed point 3 deleted:

[0110]

[0111] At the same time, you can obtain The minimum eigenvalue gSCR p .

[0112] Repeat the above steps, set the nominal model, and calculate the critical value CgSCR of the small interference stability in the sub-synchronous frequency band of the nominal network-following system p , Equivalent Network Subsystem Critical robust generalized short circuit ratio CRgSCR p and robust stability margin η, then re-determine the weak points of the equivalent network and transform the corresponding stations into grid-forming control until the constraints are met or the maximum number of transformations is reached. Finally, according to the minimum robust stability margin requirement, determine the scheme with the least number of transformations and the corresponding ratio and position of grid-following converters and grid-forming converters.

[0113] Table 2 After system transformation Various indicators

[0114] Transformation Node <![CDATA[gSCR v ]]> <![CDATA[CgSCR v ]]> Low frequency stability margin 3 3.66 13.87 10.21 3、4 5.85 13.87 8.02 1、3、4 6.95 13.87 6.92

[0115] Table 3 After system transformation Various indicators

[0116] Transformation Node Nominal Model <![CDATA[gSCR p ]]> <![CDATA[CgSCR p ]]> <![CDATA[CRgSCR p ]]> η GFL2 3.52 3.72 5.28 -1.76 3 GFL2 5.07 3.72 5.28 -0.21 3、4 GFL2 6.59 3.72 4.58 2.01 1、3、4 GFL2 13.24 3.72 3.72 9.52

[0117] Since the optimization configuration scheme aims at the minimum number of transformations, the situation where all converter stations are transformed into grid-type is not considered. As shown in Table 3, when the converter stations of the two-area-four-machine system all adopt the grid-type control method, the system does not meet the robust stability conditions. As more stations are transformed, the quantitative index of the grid-type support capacity of the two-area-four-machine system, gSCR, is p As it increases, if the nominal model remains unchanged, the critical generalized short-circuit ratio CRgSCR for robust stability p will decrease or remain unchanged, so the corresponding robust stability margin η increases with the number of transformations. If the minimum robust stability margin η is required set If it is greater than 2, the solution with the least number of transformations should be to transform nodes 3 and 4.

[0118] The following time domain simulation is used to verify the effectiveness of the optimal configuration scheme of the grid-following / grid-building converter. Assuming that t = 0.2s, Figure 4The infinite bus in the system has a voltage drop of 0.02s and an amplitude of 0.5pu. The figure below shows the time domain response curve of the system output active power within 1.5s when the converter adopts different control methods and control parameters.

[0119] Case 1: All stations adopt the grid-following control method;

[0120] Case 2: Stations 1 and 2 are changed to network-building control, while stations 3 and 4 maintain network-following control, with the PLL bandwidths of 40 and 60.

[0121] Case 3: Stations 3 and 4 are changed to network-building control, while stations 1 and 2 maintain network-following control, with the phase-locked loop bandwidths of 40 and 60.

[0122] Attached Figure 7 The time domain simulation results show that when Case 1 is adopted, the system does not meet the robust stability criterion, and the output active power of each converter station continues to oscillate. When Case 2 is adopted, the system meets the robust stability criterion, the output active power can converge after a certain period of time after the disturbance, and the system damping ratio increases. When Case 3 is adopted, the disturbance decays quickly, and the system damping ratio is improved compared with Case 2, with sufficient robust stability margin, which is consistent with the conclusion of the optimal configuration scheme.

[0123] The simulation results show that the grid-following / grid-forming converter optimization configuration model constructed by the present invention is based on the quantitative evaluation index of robust stability from the perspective of grid strength. It can ensure that the system has sufficient robust stability margin after transformation and reduce the investment cost of the grid-forming transformation process, and has application value in actual engineering.

[0124] The electronic device of the present invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0125] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0126] The processing unit performs the various methods and processes described above, such as methods S1 to S3. For example, in some embodiments, methods S1 to S3 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into the RAM and executed by the CPU, one or more steps of methods S1 to S3 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute methods S1 to S3 in any other appropriate manner (e.g., by means of firmware).

[0127] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip systems (SOCs), load programmable logic devices (CPLDs), and the like.

[0128] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0129] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0130] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for optimizing the configuration of a hybrid system with a network structure taking into account uncertainty, characterized in that: Taking the minimum number of transformations as the optimization goal and the robust stability of the hybrid system after transformation as the constraint condition, the converter optimization configuration model is constructed. The hybrid system optimization configuration process includes: S1. Dynamically divide the current hybrid system into an equivalent grid-following subsystem and an equivalent grid-forming subsystem, calculate the generalized short-circuit ratio of the equivalent subsystem respectively, use the generalized short-circuit ratio as a quantitative indicator of grid strength, determine the critical value of the small disturbance stability of the corresponding nominal system through the dominant characteristic root locus, and solve the generalized short-circuit ratio and robust stability margin of the critical robustness of the subsynchronous frequency band based on the small gain theorem; S2. According to the generalized short-circuit ratio of the equivalent subsystem, the generalized short-circuit ratio of the critical robustness of the subsynchronous frequency band, and the robust stability margin, determine whether the current hybrid system meets the robust stability constraint condition. If the robust stability constraint condition is met or the maximum number of transformations is reached, the current optimization process is terminated and the number of transformations and the configuration result of the hybrid system after optimization are output. Otherwise, go to S3. S3. Use the participation factor method to identify the weakest feeding point in the current hybrid system, transform the station corresponding to the weakest feeding point into a grid-type control, and go to S1.

2. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 1 is characterized in that: The multiplicative perturbation model of the hybrid system includes: Nominal system equipment side: Where: Y GFL (s) indicates the dynamics of network-based devices, Y PLL (s) is the nominal grid-type converter admittance, Y GFM (s) represents the dynamics of networking equipment, Y GF (s) is the nominal grid-type converter admittance, S1 and S2 are the diagonal matrices consisting of the capacity ratios of the grid-type converter and the grid-type converter, respectively, e Jθ and e -Jθ is the coordinate transformation matrix between the global coordinate system and the local coordinate system, and θ represents the steady-state phase angle difference between the two coordinate systems; Nominal system network side: Where: Y multi_grid (s) represents the network side dynamics, the B matrix is ​​the node admittance matrix of the AC network, ω0 is the nominal frequency of the system, and τ is the R / L ratio of the line; Uncertainty perturbation: in, is the device admittance matrix of the ith converter in the global coordinate system of the actual hybrid system, e Jθ Y C (s)e -Jθ is the device admittance matrix in the global coordinate system of the nominal grid-following system or the nominal grid-forming system; The uncertainty perturbation Δ(s) consists of two block diagonal matrices Δ PLL (s) and Δ GF (s), corresponding to network-following devices and network-building devices respectively:

3. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 2 is characterized in that: The equivalent network subsystem The closed-loop dynamics are: in: is the admittance matrix of the grid-connected converter considering the uncertainty on the equipment side, B redv is the equivalent network node admittance matrix after kron reduction; The equivalent network subsystem The closed-loop dynamics are: B redp =B 11 in, is the admittance matrix of the grid-connected converter considering the uncertainty on the equipment side, B redp To delete the sub-matrices corresponding to the rows and columns of the grid-type converter nodes in matrix B.

4. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 3 is characterized in that: The converter optimization configuration model has the following mathematical expression: min(K) Where: K is the number of transformations; gSCR p and gSCR v CgSCR is the generalized short-circuit ratio of the equivalent grid-following subsystem and the equivalent grid-forming subsystem, which is used to quantify the subsynchronous frequency band / low frequency band power grid strength; p and CgSCR v are the critical generalized short-circuit ratios for small-disturbance stability of the equivalent grid-following subsystem and the equivalent grid-building subsystem, respectively; CRgSCR p is the critical robust generalized short-circuit ratio; η is the robust stability margin of the subsynchronous frequency band of the system, η set Minimum robust stability margin requirement to account for equipment uncertainties.

5. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 4 is characterized in that: The participation factor method is used to identify the weakest feed-in point in the current hybrid system, where the participation factor calculation expression of node i in the equivalent grid subsystem is: Where: p 1,i is the generalized short-circuit ratio gSCR of the equivalent grid subsystem p The participation factor for node i, L i,i To expand the admittance matrix The i-th diagonal element of and They represent the generalized short-circuit ratio gSCR of the equivalent grid subsystem. p The corresponding left and right eigenvectors satisfy 6. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 3 is characterized in that: According to the equivalent network admittance matrix and the equipment capacity matrix, the generalized short-circuit ratio of the equivalent grid-following subsystem and the equivalent grid-forming subsystem are calculated respectively. The specific calculation expressions are as follows: Among them: gSCR v Equivalent Network Subsystem The generalized short-circuit ratio is used as a quantitative indicator of the low-frequency grid strength of the hybrid system; gSCR p Equivalent network subsystem The generalized short-circuit ratio is used as a quantitative indicator of the grid strength in the subsynchronous frequency band of the hybrid system; Δλ(s) is the perturbation caused by the dynamics of the grid-connected converter in the equivalent network.

7. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 3 is characterized in that: The determining of the critical value of the small disturbance stability of the corresponding nominal system by the dominant characteristic root locus specifically includes: Select the nominal system model and determine the critical value CgSCR of the nominal grid-type system's small disturbance stability through the dominant characteristic root loci in the low frequency band p , the critical value CgSCR of small disturbance stability of nominal grid-following system is determined by the dominant characteristic root locus of subsynchronous frequency band v .

8. The method for optimizing the configuration of a hybrid system taking uncertainty into account according to claim 7 is characterized in that: The method of solving the critical robust generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band based on the small gain theorem specifically includes: According to the maximum modulus theorem, the frequency domain characteristic curve of the singular value of the uncertainty perturbation Δ(s) is plotted, and the H of the uncertainty perturbation Δ(s) is determined by the peak value of the frequency domain characteristic curve. ∞ The upper bound of the norm, Among them, sup represents the maximum value, σ max [·] is the largest singular value of the matrix ·; The relationship between the generalized short-circuit ratio and the complementary sensitivity peak is established as follows: Where: κ2(W) is the spectral condition number of the matrix W, when SB -1 When it is a symmetric matrix, κ2(W)=1; gSCR is the generalized short-circuit ratio of the equivalent subsystem; Based on the small gain theorem, the critical robust generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band are solved, and the calculation expression is: Where: δ is the inverse of the upper bound of the uncertainty perturbation, that is The robust stability margin of the subsynchronous frequency band of the system is calculated as: η=gSCR p -CRgSCR p 。 9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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