Optimal configuration method, device and medium for network-following network-constructing hybrid system considering uncertainty

Abstract

The present application relates to a kind of network configuration type hybrid system optimization configuration method, equipment and medium considering uncertainty, comprising: with minimum reconstruction times as optimization goal, hybrid system robust stability as constraint condition, converter optimization configuration model is built, and hybrid system optimization configuration process includes: S1, current hybrid system is divided into equivalent follow network / network subsystem, respectively calculate generalized short-circuit ratio, determine the critical value of corresponding nominal system small disturbance stability, solve the critical robust generalized short-circuit ratio and robust stability margin in subsynchronous frequency band based on small gain theorem;S2, judge whether to meet constraint condition, if meet, then end current optimization process, otherwise, turn to S3;S3, the weakest feed-in point in current hybrid system is identified using participation factor method, after the station corresponding to the weakest feed-in point is reconstructed into network type control, turn to S1.Compared with prior art, the present application reduces the input cost in system reconstruction process on the basis of ensuring system robust stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy power system converter configuration, in particular to a grid-following and grid-forming hybrid system optimization configuration method considering uncertainty, equipment and medium. BACKGROUND

[0002] With the increasing penetration of wind power, photovoltaic and other new energy, the power system is changing into a new type of power system dominated by power electronic devices. The new energy grid-connected equipment with power electronic interface (i.e. converter) usually adopts two typical control modes of grid-following (GFL) and grid-forming (GFM). With the gradual replacement of synchronous machines, the voltage support strength of the power system dominated by grid-following converters decreases, and the sub-synchronous oscillation instability phenomenon is easily triggered under the condition of weak power grid with low short circuit ratio (SCR). In contrast, grid-forming converters can actively establish and support grid voltage and frequency, and have good adaptability to weak power grids, which has attracted widespread attention in the industry.

[0003] With the gradual investment of grid-forming converters to replace the support of synchronous machines, a power system with grid-following and grid-forming hybrid networking (hereinafter referred to as "hybrid system") will be formed. The comprehensive use of grid-following / grid-forming converters is equivalent to matching the appropriate short circuit ratio for the converter, thereby ensuring the small disturbance stability of the converter in weak and strong power grids. However, most of the existing researches on hybrid systems ignore the influence of uncertainty, and the theory is based on the assumption that the external characteristics of grid-following (grid-forming) converters are similar. In actual hybrid systems, not only are there differences in external characteristics between converters with different control modes (strong heterogeneity), but also converters with the same control mode are usually "heterogeneous" (weak heterogeneity). The robust stability boundary and margin under the perspective of grid strength can be quantified by combining the dynamic division method of the converter and the small gain theorem.

[0004] The quantification of the robust stability boundary of the hybrid system can provide theoretical guidance for the grid-following station grid-forming transformation. Since the configuration of grid-forming converters can effectively improve the strength of the AC power grid, increase the risk of low-frequency oscillation instability while improving the sub-synchronous frequency band stability. Considering the suppression of low-frequency oscillation and the reduction of investment cost, in the process of grid-forming transformation of existing grid-following stations, the problem of how to configure the proportion and position of grid-following / grid-forming devices to ensure robust stability and minimize the number of transformations needs to be answered. SUMMARY

[0005] The purpose of the present application is to overcome the defects of the prior art and provide a grid-following and grid-forming hybrid system optimization configuration method considering uncertainty, equipment and medium, which reduces the investment cost in the system transformation process while ensuring the robust stability of the system.

[0006] The object of the present application can be achieved by the following technical solutions:

[0007] According to a first aspect of the present application, a follow-network and build-network hybrid system optimization configuration method considering uncertainty is provided, with the minimum number of modifications as the optimization objective, and the robust stability of the modified hybrid system as the constraint condition, a converter optimization configuration model is constructed, and the hybrid system optimization configuration process comprises:

[0008] S1, the current hybrid system is dynamically divided into an equivalent follow-network subsystem and an equivalent build-network subsystem, the generalized short-circuit ratio of the equivalent subsystems is calculated respectively, the generalized short-circuit ratio is taken as a power grid strength quantitative index, the critical value of small disturbance stability of the corresponding nominal system is determined through the dominant eigenvalue trajectory, and the generalized short-circuit ratio of the critical robustness in the subsynchronous frequency band and the robust stability margin are solved based on the small gain theorem;

[0009] S2, whether the current hybrid system meets the robust stability constraint condition is judged according to the generalized short-circuit ratio of the equivalent subsystems, and the generalized short-circuit ratio of the critical robustness in the subsynchronous frequency band and the robust stability margin, if the robust stability constraint condition is met or the maximum number of modifications is reached, the current optimization process is ended and the number of modifications and the configuration result of the optimized hybrid system are output, otherwise, S3 is converted;

[0010] S3, the weakest feed-in point in the current hybrid system is identified by using the participation factor method, the station corresponding to the weakest feed-in point is modified into a build-network type control, and S1 is converted.

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

[0012] The nominal system device side:

[0013]

[0014] Wherein: Y GFL (s) represents the follow-network type device dynamics, Y PLL (s) is the nominal follow-network type converter admittance, Y GFM (s) represents the build-network type device dynamics, Y GF (s) is the nominal build-network type converter admittance, S1 and S2 are diagonal matrices composed of the capacity ratio of the follow-network type converter and the build-network type converter, e Jθ and e -Jθ are the coordinate transformation matrices 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] The nominal system network side:

[0016]

[0017] Y multi_grid (s) represents the network side dynamics, B is the 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] where, is the device admittance matrix of the i-th 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) includes two block diagonal matrices Δ PLL (s) and Δ GF (s), corresponding to the grid-following device and the grid-forming device respectively:

[0022]

[0023] Preferably, the closed-loop dynamics of the equivalent grid-forming subsystem is:

[0024]

[0025] where: is the grid-forming converter admittance matrix considering device-side uncertainty, B redv is the equivalent network node admittance matrix after kron order reduction;

[0026] The closed-loop dynamics of the equivalent grid-following subsystem is:

[0027]

[0028] B redp = B 11

[0029] where: is the grid-following converter admittance matrix considering device-side uncertainty, B redp is a sub-matrix deleting the rows and columns corresponding to the grid-forming converter nodes in the matrix B.

[0030] Preferably, the mathematical expression of the converter optimization configuration model is:

[0031] min(K)

[0032]

[0033] where K is the number of modifications; gSCR p and gSCR v are the generalized short circuit ratio of the equivalent follow network system and the equivalent build network system, respectively, for quantifying the strength of the sub-synchronous frequency band / low frequency band power grid; CgSCR p and CgSCR v are the critical generalized short circuit ratio of the small signal stability of the equivalent follow network system and the equivalent build network system, respectively; CRgSCR p is the critical robust generalized short circuit ratio; η is the robust stability margin of the system sub-synchronous frequency band, η set is the minimum robust stability margin requirement considering the device uncertainty.

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

[0035]

[0036] where p 1,i is the generalized short circuit ratio gSCR p of the equivalent follow network system, L i,i is the participation factor of node i, and the i-th diagonal element of the extended admittance matrix , and respectively represent the generalized short circuit ratio gSCR p of the equivalent follow network system, and the corresponding left and right eigenvectors satisfy

[0037] Preferably, according to the equivalent network admittance matrix and the device capacity matrix, the generalized short circuit ratios of the equivalent follow network system and the equivalent build network system are calculated, and the calculation expression is specifically:

[0038]

[0039] where gSCR v is the generalized short circuit ratio of the equivalent build network system , which is used as a quantitative index of the low frequency band power grid strength of the mixed system; gSCR p is the generalized short circuit ratio of the equivalent follow network system , which is used as a quantitative index of the sub-synchronous frequency band power grid strength of the mixed system; Δλ(s) is the perturbation caused by the dynamic of the build network type converter in the equivalent network.

[0040] Preferably, the critical value of the small signal stability of the corresponding nominal system is determined by the dominant eigenvalue trajectory, and specifically includes:

[0041] The nominal system model is selected, and the critical value CgSCR of small disturbance stability of the nominal network-forming system is determined by the dominant eigenvalue trajectory in the low frequency band p The critical value CgSCR of small disturbance stability of the nominal network-forming system is determined by the dominant eigenvalue trajectory in the sub-synchronous frequency band v .

[0042] Preferably, the small gain theorem is used to solve the critical robustness generalized short-circuit ratio and the robust stability margin in the sub-synchronous frequency band, and 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 drawn, and the upper bound of the H ∞ norm of the uncertainty perturbation Δ(s) is determined by the peak value of the frequency domain characteristic curve, Wherein, sup represents the maximum value, σ max [·] is the maximum singular value of the matrix ·;

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

[0045]

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

[0047] The small gain theorem is used to solve the critical robustness generalized short-circuit ratio and the robust stability margin in the sub-synchronous frequency band, and the calculation expression is:

[0048]

[0049] Wherein: δ is the reciprocal of the upper bound value of the uncertainty perturbation, that is

[0050] The robust stability margin of the system in the sub-synchronous frequency band is calculated as:

[0051] η = gSCR p -CRgSCR p

[0052] According to the second aspect of the present application, an electronic device is provided, comprising a memory and a processor, the memory stores a computer program, and the processor executes the program to realize the method of any one of the aspects.

[0053] According to the third aspect of the present application, a computer readable storage medium is provided, which stores a computer program, and the program is executed by a processor to realize the method of any one of the aspects.

[0054] Compared with the prior art, the present application has the following beneficial effects:

[0055] (1) The follow-network-construct-network type hybrid system optimization configuration scheme proposed in the present application takes the minimum network construction times as the optimization target, reduces the input cost while suppressing low-frequency oscillation, and fully considers the influence of the uncertainty factors on the equipment side, quantifies the robust stability by taking the generalized short-circuit ratio as the power grid strength index, optimizes the hybrid system under the constraint of the robust stability of the hybrid system, and reduces the input cost in the system reconstruction process to the maximum extent on the basis of ensuring the robust stability of the system.

[0056] (2) The present application uses the critical stability short-circuit ratio value of the weakest single-feed-in follow-network / construct-network type system considering uncertainty to represent the robust stability critical value, and the calculation only involves 2x2 matrix operation, avoiding the "dimension disaster" problem caused by high-order matrix operation.

[0057] (3) The present application uses the participation factor method to identify the weakest feed-in point in the hybrid system, and preferentially transforms the corresponding converter station into a construct-network type control mode, avoiding the problem that the increase in the number of configured construct-network type converters causes the increase in the generalized short-circuit ratio of the equivalent follow-network subsystem, thereby increasing the risk of low-frequency oscillation instability, and the system has higher robust stability. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 It is a flowchart of the follow-network-construct-network type hybrid multi-feed-in system optimization configuration considering uncertainty in the embodiments of the present application;

[0059] Figure 2 It is a flowchart of a specific embodiment in the embodiments of the present application;

[0060] Figure 3 It is a two-area-four-machine system schematic diagram in the embodiments of the present application;

[0061] Figure 4 It is a hybrid multi-feed-in system model decomposition schematic diagram in the embodiments of the present application;

[0062] Figure 5 It is a frequency domain characteristic curve schematic diagram of the uncertainty perturbation in the embodiments of the present application;

[0063] Figure 6 It is a relationship diagram between the complementary sensitivity peak value and gSCRp in the embodiments of the present application;

[0064] Figure 7 It is a two-area-four-machine system time domain simulation result diagram in the embodiments of the present application. DETAILED DESCRIPTION

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0066] Example

[0067] like Figure 1 As shown, this embodiment provides an optimization configuration method for a grid-connected hybrid system that takes uncertainty into account. The optimization objective is to minimize the number of modifications, and the robust stability of the modified hybrid system is used as a constraint. An optimal converter configuration model is constructed, and the hybrid system optimization configuration process includes:

[0068] S1. Dynamically divide the current hybrid system into an equivalent grid subsystem and an equivalent network subsystem. Calculate the generalized short-circuit ratio of the equivalent subsystems respectively. Use the generalized short-circuit ratio as a quantitative index of power grid strength. Determine the critical value of small disturbance stability of the corresponding nominal system through the dominant eigenvalue locus. Solve the generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band based on the small gain theorem.

[0069] S2. Based on the generalized short-circuit ratio of the equivalent subsystem, the critical robust generalized short-circuit ratio and robust stability margin of the subsynchronous frequency band, determine whether the current hybrid system meets the robust stability constraint conditions. If the robust stability constraint conditions are met or the maximum number of modifications is reached, end the current optimization process and output the number of modifications and the configuration result of the optimized hybrid system; otherwise, go to S3.

[0070] S3. Use the participation factor method to identify the weakest feed point in the current hybrid system, and transform the station corresponding to the weakest feed point into a grid-type control system, then go to S1.

[0071] Next, combined Figure 2 The method of this embodiment will be described in detail below.

[0072] (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;

[0073] (2) Construct the equivalent network subsystem of the current system and equivalent network subsystem Calculate the generalized short-circuit ratio gSCR of the equivalent subsystem v and gSCR p ;

[0074] (3) Select an appropriate nominal model and determine the critical value CgSCR for small disturbance stability by using the dominant eigenvalue locus in the low-frequency / subsynchronous frequency band. v / CgSCR p ;

[0075] (4) Analysis of the uncertainty perturbation Δ PLL (s) of the singular value in the frequency domain, determine the upper bound δ of the H ∞ norm of the perturbation -1 ;

[0076] (5) Draw the complementary sensitivity peak curve of the nominal grid-following type system connected to the AC system with different gSCR p , solve the critical robustness of the generalized short-circuit ratio CRgSCR p and the robust stability margin η in the subsynchronous frequency band.

[0077] (6) Determine whether the system meets the constraint condition, if it does, end the process, count the number of modifications K, and output the optimized system grid-following / construction network type equipment ratio and position; otherwise, go to the next step.

[0078] (7) Calculate the participation factor of the multi-infeed system, determine the weakest infeed point i, and modify the station corresponding to the infeed point i to the construction network type control, and then return to (2).

[0079] This embodiment builds a two-area-four-machine system as shown in Figure 3 in the Matlab / Simulink environment, and the initial system is of grid-following type control mode. First, the initial system model considering equipment uncertainty is established. Since the initial system is a heterogeneous multi-infeed grid-following system, the construction of its model can ignore the construction network type equipment part on the basis of the multiplicative perturbation model of the hybrid system:

[0080] 1) Nominal system equipment side:

[0081]

[0082] where Y GFL (s) represents the grid-following type equipment dynamic, Y PLL (s) is the nominal grid-following type converter admittance, and S1 is a diagonal matrix composed of the capacity ratio of the grid-following type converter.

[0083] 2) Nominal system network side:

[0084]

[0085] where Y multi_grid (s) represents the network side dynamic, ω0 is the nominal frequency of the system, 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:

[0086]

[0087] 3) Uncertainty perturbation:

[0088]

[0089] where, Y Jθ Y PLL (s) e -Jθ is the nominal grid-forming system admittance matrix in the global coordinate system.

[0090] Then, the grid-forming converter dynamics are merged into the equivalent network as shown in Figure 4 The hybrid system is decomposed into two subsystems dominated by single-type converters at the device 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 is the initial system itself. According to the original data of the initial system, the admittance matrix of the compressed AC network is derived:

[0091]

[0092] The minimum eigenvalue of gSCR P ≈ 3.52.

[0093] To reduce the conservatism of the robust stability criterion, the grid-following device with the smallest perturbation is selected as the nominal model. According to the explicit relationship between the characteristic equation of the "weakest" single-infeed grid-following system after decoupling of the nominal grid-following system and gSCR p , we have:

[0094] c(s) = det(Y PLL (s) + gSCR p *F(s))

[0095] The dominant eigenvalue trajectory of the nominal grid-following system in the subsynchronous frequency band is plotted on MATLAB, and it can be seen that when CgSCR p is 3.72, the nominal grid-following system is approximately in a critical stable state in the subsynchronous frequency band.

[0096] Then, the frequency domain characteristic curve of the singular value of the uncertainty perturbation Δ PLL (s) is analyzed to determine the upper bound of the H ∞ norm of the perturbation. The expression of the device uncertainty perturbation Δ PLL (s) is:

[0097]

[0098] where, Equivalent grid-following subsystem The device admittance matrix in the global coordinate system of the i-th converter, e Jθ Y PLL (s)e -Jθ The device admittance matrix in the global coordinate system of the nominal grid-following system.

[0099] The above uncertainty perturbation is analyzed, and the distribution curve of σ max [Δ PLL,i (jω)] with frequency is plotted on MATLAB (as shown in FIG. 2), and the peak value of the perturbation and its reciprocal δ are determined. Figure 5

[0100] The uncertainty perturbation Δ PLL (s) of the device side affects the critical value CgSCR p of small signal stability of the nominal grid-following system. By inversely solving the following equation, an explicit expression of the critical robust generalized short-circuit ratio CRgSCR p can be obtained:

[0101]

[0102] The above solving process is equivalent to plotting the peak value curve of the complementary sensitivity of the "weakest" single-infeed system of the nominal grid-following system when connected to an AC system with different gSCR p on MATLAB (as shown in FIG. 3), and CRgSCR p corresponds to the gSCR p value when the ordinate is δ / κ2(W). Figure 6

[0103] The equivalent grid-following subsystem robust stability and its critical value quantitative evaluation index can be defined as the robust stability margin of the subsynchronous frequency band of the system:

[0104] η=gSCR p -CRgSCR p

[0105] Then, the sensitivity of each infeed point to gSCR p is calculated, and the initial system weak point position is found out from it. Table 1 shows the participation factors of each infeed point of the initial system.

[0106] Table 1 Participation factors of the initial system

[0107] feed-in point 1 2 3 4 participation factor 0.0410 0.0254 0.6705 0.2631

[0108] Table 1 shows that the participation factor of infeed point 3 is the largest. Therefore, the grid-following station of infeed point 3 is preferentially transformed into a grid-forming station. Then, the equivalent subsystem of the system after the first transformation is constructed​​ and And calculate gSCR v . The equivalent network admittance matrix B redp This can be represented as the AC network admittance matrix B with the row and column corresponding to feed point 3 removed:

[0109]

[0110] Simultaneously, it can be obtained The minimum eigenvalue gSCR p .

[0111] Repeat the above steps, set up the nominal model, and calculate the critical value CgSCR for small-interference stability of the nominal and mesh-type system in the subsynchronous frequency band. p Equivalent network subsystem Critically robust generalized short-circuit ratio CRgSCR p And the robust stability margin η, then the weak points of the equivalent network are re-identified and the corresponding stations are transformed into grid-type control systems until the constraints are met or the maximum number of transformations is reached. Finally, based on the minimum robust stability margin requirement, the scheme with the fewest transformations and the corresponding ratio and location of grid-type and grid-type converters are determined.

[0112] Table 2 System Modification various indicators

[0113] retrofit node gSCR v ]] CgSCR v ]]> low-frequency band 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

[0114] Table 3. System after modification various indicators

[0115] retrofit node nominal model gSCR p ]]> CgSCR p ]]> 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

[0116] Since this optimized configuration scheme aims to minimize the number of modifications, it does not consider the scenario where all converter stations are converted to grid-connected configurations. Table 3 shows that when all converter stations in the two-zone-four-unit system adopt grid-connected control, the system does not meet the robust stability requirements. As more stations are modified, the quantitative indicator gSCR of the grid-connected support capability of the two-zone-four-unit system decreases. p As it increases, if the nominal model remains unchanged, the critical generalized short-circuit ratio CRgSCR for robust stability increases. p This will decrease or remain unchanged, therefore the corresponding robust stability margin η increases with the number of modifications. If the minimum robust stability margin η is required... set If the number of modifications is greater than 2, the solution with the fewest modifications should be to modify nodes 3 and 4.

[0117] The effectiveness of the grid-connected / grid-based converter optimization configuration scheme is verified using time-domain simulation. Assuming t = 0.2s, Figure 4The infinite bus in the system experiences a voltage drop of 0.02s duration and 0.5pu. The figure below shows the time-domain response curves of the system output active power within 1.5s under different control methods and parameters.

[0118] Case 1: All stations adopt a grid-based control method;

[0119] Case 2: Stations 1 and 2 are changed to network-type control, while stations 3 and 4 maintain network-type control, with phase-locked loop bandwidths of 40 and 60 respectively;

[0120] Case 3: Stations 3 and 4 are changed to network-type control, while stations 1 and 2 maintain network-type control, with phase-locked loop bandwidths of 40 and 60 respectively.

[0121] Appendix Figure 7 The time-domain simulation results show that, in Case 1, the system does not meet the robust stability criterion, and the active power output of each converter station continues to oscillate. In Case 2, the system meets the robust stability criterion, and the active power output converges after a certain period of time after the disturbance, and the system damping ratio increases. In Case 3, the disturbance decays rapidly, the system damping ratio is improved compared to Case 2, and it has sufficient robust stability margin, consistent with the conclusions of the optimized configuration scheme.

[0122] Simulation results show that the grid-connected / grid-connected converter optimization configuration model constructed in this invention, based on the quantitative evaluation index of robust stability from the perspective of grid strength, can ensure that the system after the transformation has sufficient robust stability margin and reduce the investment cost of the grid transformation process, and has application value in practical engineering.

[0123] The electronic device of this invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0124] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0125] The processing units perform the various methods and processes described above, such as methods S1-S3. For example, in some embodiments, methods S1-S3 can be implemented as a computer software program tangibly embodied in a machine readable medium, such as a storage unit. In some embodiments, portions or all of the computer program can be loaded and / or installed onto the device via the ROM and / or the communication unit. When the computer program is loaded onto the RAM and executed by the CPU, one or more of the steps of methods S1-S3 described above can be performed. Alternatively, in other embodiments, the CPU can be configured to perform methods S1-S3 by any other suitable means, such as by way of firmware.

[0126] The functionality described above in this document can be performed, at least in part, by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (ASICs), Application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

[0127] Program code for carrying out methods of the present application can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, causes the machine to perform the functions / acts specified in the flowcharts and / or block diagrams. The program code can be embodied in whole or in part within a machine readable medium, which can be any medium for storing or transmitting the program code. The program code can be transmitted in the form of signals over a transmission medium via a data signal or carrier wave, or it can be provided on a machine readable medium.

[0128] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of a computer program code, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0129] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any skilled person in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements shall be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for optimal configuration of a cyber-physical system with uncertain cyber network, comprising: The converter optimization configuration model is constructed with the minimum number of transformations as an optimization objective and the robust stability of the transformed hybrid system as a constraint condition, and the hybrid system optimization configuration process includes: S1, the current hybrid system is dynamically divided into an equivalent follow-network subsystem and an equivalent network-constructing subsystem, the generalized short-circuit ratio of the equivalent subsystem is calculated, the generalized short-circuit ratio is taken as a power grid strength quantification index, the critical value of small disturbance stability of the corresponding nominal system is determined through a dominant eigenvalue trajectory, and the critical robust generalized short-circuit ratio and the robust stability margin of the subsynchronous frequency band are solved based on a small gain theorem; S2, whether the current hybrid system meets the robust stability constraint condition is judged according to the generalized short-circuit ratio of the equivalent subsystem, and the critical robust generalized short-circuit ratio and the robust stability margin of the subsynchronous frequency band, if the robust stability constraint condition is met or the maximum number of transformations is reached, the current optimization process is ended and the number of transformations and the configuration result of the optimized hybrid system are output, otherwise, S3 is turned to; S3, the weakest feed-in point in the current hybrid system is identified by using a participation factor method, the field station corresponding to the weakest feed-in point is transformed into a network-constructing control, and S1 is turned to; The equivalent networking subsystem The closed loop dynamics are: ， ， ， ， The equivalent netting subsystem The closed loop dynamics are: wherein: is the Kron-reduced equivalent network node admittance matrix of the grid-side converter; denotes the grid-side converter dynamics; is the Kron-reduced equivalent network node admittance matrix of the grid-side converter; B is the node admittance matrix of the AC network, are the elements of the matrix B are the elements of the matrix is the nominal frequency of the system, is the line R / L ratio; is the Kron-reduced equivalent network node admittance matrix of the grid-side converter; denotes the grid-side converter dynamics; B redp is the submatrix of the matrix B corresponding to the grid-side converter node; , are the uncertainty perturbations comprise two block-diagonal matrices corresponding to the grid-side converter and the grid-forming converter, respectively; The converter optimization configuration model has a mathematical expression as follows: wherein: K is the number of modifications; gSCR p and gSCR v are the generalized short circuit ratio of the equivalent follow-up grid system and the equivalent grid building system, respectively, for quantifying the strength of the power grid in the subsynchronous / low frequency range; CgSCR p and CgSCR v are the critical generalized short circuit ratio of the small signal stability of the equivalent follow-up grid system and the equivalent grid building system, respectively; CRgSCR p is the critical robust generalized short circuit ratio; is the robust stability margin of the system in the subsynchronous frequency range, is the minimum robust stability margin requirement set in view of the equipment uncertainty.

2. The method of claim 1, wherein, The multiplicative perturbation model of the hybrid system includes: The device side of the nominal system: where: represents the grid-following equipment dynamics, is the nominal grid-following converter admittance, represents the grid-forming equipment dynamics, is the nominal grid-forming converter admittance, and are diagonal matrices composed of the grid-following converter and grid-forming converter capacity ratio, respectively, and is the coordinate transformation matrix between the global coordinate system and the local coordinate system, represents the steady-state phase angle difference between the two coordinate systems; The network side of the nominal system: wherein: represents a network side dynamic, B is the nodal admittance matrix of the ac network, is the nominal frequency of the system, is the line's R / L ratio; Uncertainty perturbation: wherein, is the device admittance matrix of the actual hybrid system in the global coordinate system of the i converter, is the device admittance matrix of the nominal grid-following system or the nominal grid-forming system in the global coordinate system; Uncertainty perturbation Comprises two block-diagonal matrices And Corresponding to the networked device and the networked device, respectively: 。 3. The method of claim 2, wherein, The participation factor method is used to identify the weakest feed point in the current hybrid system, where the nodes in the equivalent network subsystem are... i The expression for calculating the participation factor is: where is the generalized short circuit ratio of the equivalent grid-following subsystem gSCR p the participation factor of the node i , is the th diagonal element of the expanded admittance matrix , i and and denote the generalized short circuit ratio of the equivalent grid-following subsystem gSCR p the corresponding left and right eigenvectors, respectively, satisfying .

4. The method of claim 2, wherein, According to the equivalent network admittance matrix and the device capacity matrix, the generalized short-circuit ratios of the equivalent follow-network subsystem and the equivalent network-constructing subsystem are calculated, and the calculation expression is specifically as follows: in: gSCR v For equivalent network subsystems The generalized short-circuit ratio is used as a quantitative indicator of the low-frequency grid strength of hybrid systems. gSCR p For equivalent network subsystem The generalized short-circuit ratio is used as a quantitative indicator of the subsynchronous frequency band power grid strength of hybrid systems. This refers to the perturbation caused by the dynamics of the network converter in the equivalent network.

5. The method of claim 2, wherein, The critical value of small disturbance stability of the corresponding nominal system is determined through a dominant eigenvalue trajectory, and the critical value specifically includes: The nominal system model is selected, and the critical value of small disturbance stability of the nominal networked system is determined by the dominant eigenvalue trajectory in the low frequency band CgSCR p The critical value of small disturbance stability of the nominal networked system is determined by the dominant eigenvalue trajectory in the subsynchronous frequency band CgSCR v .

6. The method of claim 5, wherein, The critical robust generalized short-circuit ratio and the robust stability margin of the subsynchronous frequency band are solved based on a small gain theorem, and the solving specifically includes: According to the maximum modulus theorem, the uncertainty perturbation is drawn The frequency domain characteristic curve of singular value, the uncertainty perturbation is determined by the peak value of the frequency domain characteristic curve The upper bound of the norm, Wherein, sup represents the maximum value, The maximum singular value of the matrix;​ The relationship expression between the generalized short-circuit ratio and the peak value of the complementary sensitivity is established as follows: wherein: is the spectral condition number of the matrix W ; when is a symmetric matrix, gSCR is the generalized short circuit ratio of the equivalent subsystem; The critical robust generalized short-circuit ratio and the robust stability margin of the subsynchronous frequency band are solved based on a small gain theorem, and the calculation expression is specifically as follows: wherein: is the inverse of the upper bound of the uncertainty perturbation, i.e. ; The robust stability margin of the system in the subsynchronous frequency band is calculated as follows: 。 7.An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, characterized in that, The processor implements the method in any one of claims 1-6 when executing the program.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that The program implements the method in any one of claims 1-6 when executed by the processor.

Images