Uncertain geomagnetic disturbance small resistance configuration method and system containing wind power system

Abstract

The application discloses a small-resistor configuration method and system for uncertainty geomagnetic disturbance containing a wind power system, and belongs to the cross field of geomagnetic storm and power system stability research. The application applies transformer reactive power loss caused by induced geomagnetic field sample to the power system as a load, causes node voltage change, thereby links the geomagnetic disturbance to the small disturbance stability of the system, and is used for evaluating the influence of the geomagnetic storm on the power grid safety; through constructing the joint sensitivity characteristic space of voltage sensitivity and damping ratio sensitivity, the installation position of the small resistor is optimized, and the small disturbance instability accident caused by the geomagnetic disturbance can be effectively prevented.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of geomagnetic storm and power system stability research, and in particular to a method and system for configuring small resistances to mitigate uncertain geomagnetic disturbances in wind power systems. Background Technology

[0002] When a geomagnetic disturbance (GMD) occurs, the changing geomagnetic field induces an electric field on the Earth's surface. Potential differences exist between the grounding points of transformers in different geographical locations, forming a path through transmission lines and generating a geomagnetically induced current (GIC). As a quasi-DC current, the GIC flowing through the transformer causes half-wave saturation, resulting in reactive power loss Q. GIC Increase. The large number of transformers in the power grid increases Q. GIC The total amount is very large, and applying it as a reactive load to the system will cause changes in the power flow distribution of the system.

[0003] Q GIC The most direct impact on the power system is the resulting fluctuation in node voltage. However, for power grids in low- and mid-latitude regions with weaker geomagnetic disturbances, more complex grid structures, and under heavy load stability limits, active power / power angle and reactive power / voltage have a coupling effect, and the small signal stability (SSS) of the power system is affected by the active / reactive power flow before the disturbance. GIC Linking GMDs to system SSS. Therefore, Q caused by geomagnetic storms GIC It has become a potential threat to induce small disturbance instability, but the impact of GMD on system SSS and disaster prevention and control have not yet been studied.

[0004] With the construction of new power systems themed around new energy sources, the proportion of new energy sources, primarily wind power, is rapidly increasing. However, whether the ability of hybrid systems containing wind power to resist geomagnetic disturbances will change during such disturbances remains to be studied. Furthermore, whether the addition of wind power will affect the installation location of low-resistance control devices also requires further investigation. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for configuring small resistances to mitigate uncertain geomagnetic disturbances in wind power systems, by using Q GIC As a bridge, it links geomagnetic disturbances with the small disturbance stability of the system, and is used to assess the impact of geomagnetic storms on power grid safety. Based on the voltage / damping ratio joint sensitivity scenario, it studies the optimal configuration of small resistance control devices, which can effectively prevent the occurrence of small disturbance instability accidents when geomagnetic disturbances occur.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for configuring small resistors to handle uncertain geomagnetic disturbances in a wind power system includes:

[0008] Based on geomagnetic disturbance data, a stochastic fuzzy model of the induced geoelectric field is constructed;

[0009] Based on the aforementioned random fuzzy model, induced ground electric field samples are obtained through random fuzzy simulation and inverse transformation methods.

[0010] The reactive power loss of the transformer caused by the induced ground electric field sample is applied to the power system as a load, causing node voltage changes, thereby constructing a joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity;

[0011] Multiple joint sensitivity scenarios are clustered in the joint sensitivity feature space, and each joint sensitivity scenario is mapped to the induced ground electric field space to obtain multiple induced ground electric field sensitivity scenarios; multiple induced ground electric field sensitivity scenarios correspond to multiple substations with different installation locations of small resistors;

[0012] Pre-screening of substations with small resistors by using the combined sensitivity of the induced ground electric field sensitivity scenario.

[0013] Establish an objective function for optimizing the installation location of small resistors;

[0014] Based on multiple induced ground electric field sensitivity scenarios and pre-screened substations, a binary-coded genetic algorithm is used to solve the objective function and obtain the optimal small resistor installation location.

[0015] A low-resistance configuration system for uncertain geomagnetic disturbances incorporating a wind power system includes:

[0016] The random fuzzy model building module is used to build a random fuzzy model of the induced geoelectric field based on geomagnetic disturbance data.

[0017] The sample acquisition module is used to obtain induced ground electric field samples based on the random fuzzy model through random fuzzy simulation and inverse transformation methods.

[0018] The joint sensitivity feature space construction module is used to apply the transformer reactive power loss caused by the induced ground electric field sample as a load to the power system, causing node voltage changes, thereby constructing a joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity.

[0019] The scene acquisition module is used to cluster multiple joint sensitivity scenes in the joint sensitivity feature space and map each joint sensitivity scene to the induced ground electric field space to obtain multiple induced ground electric field sensitivity scenes; the multiple induced ground electric field sensitivity scenes correspond to multiple substations with different installation locations of small resistors;

[0020] The pre-screening module is used to pre-screen substations with small resistors by utilizing the joint sensitivity of the induced ground electric field sensitivity scenario.

[0021] The objective function creation module establishes an objective function for optimizing the installation location of small resistors.

[0022] The optimization module is used to solve the objective function based on multiple induced ground electric field sensitivity scenarios and pre-screened substations, and obtain the optimal small resistor installation location.

[0023] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0024] This invention discloses a method and system for configuring small resistors to handle uncertain geomagnetic disturbances in wind power systems. The method applies the reactive power loss of transformers caused by induced geoelectric field samples as a load to the power system, causing changes in node voltage. This links geomagnetic disturbances with the system's small disturbance stability, enabling the assessment of the impact of geomagnetic storms on power grid safety. By constructing a joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity to optimize the installation location of the small resistors, the method can effectively prevent small disturbance instability accidents during geomagnetic disturbances. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A flowchart of a method for configuring small resistors to handle uncertain geomagnetic disturbances in a wind power system, provided by an embodiment of the present invention;

[0027] Figure 2 The east-west component E of the induced ground electric field provided in the embodiments of the present invention x Schematic diagram of probability density function;

[0028] Figure 3 The north-south component E of the induced ground electric field provided in the embodiments of the present invention y Schematic diagram of probability density function;

[0029] Figure 4 The east-west component E of the induced ground electric field provided in the embodiments of the present invention x Schematic diagram of probability density function parameter distribution; Figure 4 In the figure, (a) represents the east-west component of the induced ground electric field, E. x A schematic diagram of the location parameter distribution of the probability density function. Figure 4 In the diagram, (b) represents the east-west component of the induced ground electric field, E. x A schematic diagram of the scale parameter distribution of the probability density function. Figure 4 (c) represents the east-west component of the induced ground electric field E. x A schematic diagram of the shape parameter distribution of the probability density function;

[0030] Figure 5 The north-south component E of the induced ground electric field provided in the embodiments of the present invention y Schematic diagram of probability density function parameter distribution; Figure 5 In the figure, (a) represents the north-south component of the induced ground electric field, E. x A schematic diagram of the location parameter distribution of the probability density function. Figure 5 (b) represents the north-south component of the induced ground electric field, E. x A schematic diagram of the scale parameter distribution of the probability density function. Figure 5 (c) represents the north-south component of the induced ground electric field, E. x A schematic diagram of the shape parameter distribution of the probability density function. Detailed Implementation

[0031] 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 embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] The purpose of this invention is to provide a method and system for configuring small resistances to mitigate uncertain geomagnetic disturbances in wind power systems, by using Q GIC As a bridge, it links geomagnetic disturbances with the small disturbance stability of the system, and is used to assess the impact of geomagnetic storms on power grid safety. Based on the voltage / damping ratio joint sensitivity scenario, it studies the optimal configuration of small resistance control devices, which can effectively prevent the occurrence of small disturbance instability accidents when geomagnetic disturbances occur.

[0033] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] like Figure 1As shown in the figure, an embodiment of the present invention provides a method for configuring small resistance to uncertain geomagnetic disturbances in a wind power system, comprising:

[0035] Step S1: Based on geomagnetic disturbance data, construct a stochastic fuzzy model of the induced geoelectric field.

[0036] Based on geomagnetic disturbance data recorded by geomagnetic observatories, the induced geoelectric field is calculated and a stochastic fuzzy model of the induced geoelectric field is constructed. The specific process is as follows:

[0037] Calculate the induced geoelectric field corresponding to the geomagnetic disturbance data for each geomagnetic disturbance event;

[0038] Analyzing the probability density distribution characteristics of each induced ground electric field, the probability density distribution function of the induced ground electric field is obtained as follows:

[0039]

[0040] In the formula, f(a) is the probability density distribution function of the a-th induced ground electric field, Γ(·) is the gamma function, μ is the location parameter, σ is the scale parameter, and υ is the shape parameter; this step uses a three-parameter t-distribution function for fitting.

[0041] A fuzzy uncertainty analysis was performed on the distribution parameters of all induced ground electric fields to determine the membership function of the distribution parameters.

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048] In the formula, μ x σ x and υ x These represent the location, scale, and shape parameters of the east-west component of the induced ground electric field, μ. y σ y and υ y These represent the location, scale, and shape parameters of the north-south components of the induced ground electric field, respectively, f(μ x ), f(σ x ) and f(υ) x ) are respectively μ x σ x and υ xThe membership function, f(μ) y ), f(σ y ) and f(υ) y ) are respectively μ y σ y and υ y Membership function; μ x σ x υ x μ y σ y and υ y These are all distribution parameters of the induced ground electric field. In fuzzy uncertainty analysis, shape parameters, scale parameters, and location parameters are defined as fuzzy variables.

[0049] Step S2: Based on the random fuzzy model, obtain the induced ground electric field sample through random fuzzy simulation and inverse transformation method.

[0050] For example, the detailed process of step S2 is as follows:

[0051] 1) In μ x σ x υ x μ y σ y and υ y M P values ​​are drawn from each confidence interval. os The parameter {·}≥ε; where P os {·} represents the probability measure, and ε is a positive number; ε is a sufficiently small positive number.

[0052] 2) Extract the M μ x σ x υ x Arbitrary matching combinations, and simulate the generation of P for each combination of east and west parameters within the interval [0,1]. os {μ xi ,σ xi ,υ xi}, and simultaneously extract M μ y σ y and υ y Arbitrary matching combinations, and simulate the generation of P for each north-south parameter combination within the interval [0,1]. os {μ yi ,σ yi ,υ yi}; where μ xi ,σ xi ,υ xi Let μ be the position parameter, scale parameter, and shape parameter of the east-west component of the induced ground electric field in the i-th combination of east-west parameters. yi ,σ yi ,υ yiThese are the location parameters, scale parameters, and shape parameters of the north-south component of the induced geoelectric field in the i-th north-south combination, respectively.

[0053] 3) Input the east-west parameter combination and the north-south parameter combination into the probability density distribution function of the induced ground electric field, respectively, and calculate the probability density distribution of the east-west component and the probability density distribution of the north-south component of the induced ground electric field.

[0054] 4) The cumulative probability density function F is obtained by accumulating the probability density distributions of the east-west components of all induced ground electric fields. x (), and simultaneously, the probability density distributions of all induced ground electric fields (north and south components) are accumulated to obtain the cumulative probability density function F. y ();

[0055] 5) Based on the cumulative probability density function F x ( ), cumulative probability density function F y ( ) Each east-west parameter combination and each north-south parameter combination, based on the inverse transformation method, uses the formula Calculate the induced ground electric field components corresponding to each combination of east and west parameters. And the induced ground electric field components corresponding to each north-south parameter combination In the formula, Ch(·) is the chance measurement operator, and E x / y For the east-west / north-south components of the induced ground electric field;

[0056] 6) The induced ground electric field component and Randomly combined to form induced ground electric field samples

[0057] Step S3: The reactive power loss of the transformer caused by the induced ground electric field sample is applied to the power system as a load, causing changes in node voltage, thereby constructing a joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity.

[0058] The construction of the joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity mainly includes three parts: the construction of voltage sensitivity, the construction of damping ratio sensitivity, and the construction of the joint sensitivity feature space.

[0059] The process of constructing voltage sensitivity is as follows:

[0060] The equivalent geomagnetic induced voltage source can be obtained by integrating the induced ground electric field along the transmission line, thus transforming the GIC bias calculation into a simple circuit problem:

[0061]

[0062] In the formula: E represents the induced electric field on the ground; R represents the route of the line; dl represents a small element of the line. Assuming the induced ground electric field remains constant, the induced voltage source of the line can be expressed as:

[0063] U = E N L N +E E L E (9)

[0064] In the formula: E E and E N L represents the electric field amplitude in the east and north directions, respectively; E and L N These represent the equivalent transmission line lengths for eastward and northward directions, respectively.

[0065] Models of transformers and transmission lines are established to construct a calculation model for geomagnetic induced current. The geomagnetic induced current is calculated using a full-node admittance matrix model. Based on the equivalent model, the expression for the total network node voltage can be derived as follows:

[0066] V = Y -1 I (10)

[0067] In the formula, Y represents the n×n order real symmetric augmented admittance matrix, and I is the matrix derived from U in formula (9). ij The equivalent injected DC current source is obtained.

[0068] I = [I1,...,I n ] T =Σy ij U ij =PE (11)

[0069] In the formula, U ij Let P be the voltage source between node i and node j. The node injection current I is linearly related to the ground electric field E, where P is an n×2 matrix. The calculated voltages of all nodes in the entire network are as follows:

[0070] V = [V1,...,V] n ] T =Y -1 PE (12)

[0071] Finally, the neutral point GIC of each branch of the power grid and the transformer is solved according to equation (13).

[0072] I GIC =Y r Y -1 PE (13)

[0073] In the formula, Y r Y is the admittance matrix of the entire system, and Y is the admittance matrix between lines (excluding grounding branches).

[0074] A transformer GIC-Q loss algorithm based on the proportionality coefficient K. The single-phase GIC-Q loss model of a transformer can be expressed as:

[0075] Q Loss =V pu KI GIC (14)

[0076] In the formula: Q Loss I represents the transformer GIC loss (Mvar); K represents the transformer reactive power loss coefficient (Mvar / A). GIC This represents a single-phase GIC(A) flowing through the neutral point of the transformer; V pu This represents the actual voltage per unit value.

[0077] Q Loss When reactive power is applied to the system, it causes changes in node voltages, thus linking geomagnetic disturbances to system stability. Voltage sensitivity refers to the node voltage change caused by reactive power. For a system with N... B For a system with nodes, the power flow equations expressed in polar coordinates can be linearized, as shown in (15).

[0078]

[0079] In the formula, J Pθ J PV J Qθ and J QV This is a block matrix in the augmented Jacobian matrix. ΔV represents the node voltage change. Δθ represents the power angle change.

[0080] Since there is a weak coupling relationship between voltage amplitude and active power increment, the influence of active power is ignored, as shown in equation (16).

[0081] ΔV=S VQ ΔQ (16)

[0082] In the formula, S VQ This is the voltage / reactive power sensitivity matrix.

[0083] S VQ This reflects the linear incremental relationship between system node voltage and reactive power, with each column of the matrix reflecting the impact of each node on the system voltage. Therefore, summing the elements in each column yields a set of 1×(N)... B -1) dimension vector, called sensitivity vector, is used to measure the effect of reactive power injection at each node on the system voltage, as shown in (17).

[0084]

[0085] The larger the element in S1, the greater the impact of the node's reactive power on the system voltage. VQ,Nj Let be the voltage sensitivity of node N under the j-th set of induced ground electric field samples. The induced ground electric field does not appear directly in the system, but affects the power flow and thus the node voltage through QLOSS.

[0086] The process of constructing and calculating the damping ratio sensitivity is as follows:

[0087] The dynamic system described by differential algebraic equations is shown in (18).

[0088]

[0089] In the formula, x and y are the state variable and algebraic variable, respectively. f and g are nonlinear vector-valued functions.

[0090] When a geomagnetic downdraft (GMD) occurs, the change in the Earth's magnetic field generates a geoelectric field on the Earth's surface, resulting in a quasi-DC geomagnetically induced current (GIC) flowing through long-haul power transmission lines, neutral transformer grounding, and the Earth itself. At frequencies well below 1 Hz, GIC can cause half-cycle transformer saturation, leading to increased transformer reactive power losses, which may cause system stability and reliability issues. (Q...) GIC Adding reactive load to the system will cause changes in power flow and node voltages; therefore, when describing the dynamic system using differential-algebraic equations, E is added as a parameter. By linearizing the state equations, the sensitivity of the eigenvalue λ to E is transformed into the state matrix A. sys Sensitivity to E. The damping ratio sensitivity is obtained based on the relationship between the damping ratio and the eigenvalue.

[0091] For ease of analysis, the output characteristics of the fan and Q are compared. GIC The equivalent ground admittance model is used instead, as shown in equations (19) and (20).

[0092]

[0093] In the formula, P DFIG and Q DFIG These represent the active power and reactive power output of the doubly-fed wind turbine, respectively; g DFIG and b DFIG U represents the equivalent ground conductance and susceptance; j is the imaginary part; U DFIG This is the voltage at the node where the doubly fed wind turbine is connected.

[0094]

[0095] In the formula, Q GIC This refers to the reactive power loss generated when GIC flows through the transformer; This refers to the voltage at the substation nodes.

[0096] The system state equations are linearized using Taylor expansion. The linearized synchronous generator-related state equations and DFIG state equations are then combined, and the connection nodes are eliminated to obtain the state matrix. A structure-preserving model as shown in equation (21) is established, and the eigenvalues ​​λ of the system state matrix are correlated with E. x / y The sensitivity is converted into a state matrix A sys For E x / y Sensitivity.

[0097]

[0098] In the formula, ψ and These are the left and right eigenvectors of the state matrix. ψ T This is the transpose of ψ. ψ' and A is an augmented matrix. A, B, C, and D are state matrices. sys The block matrix. Based on the relationship between damping ratio and eigenvalues. Where σ is the real part of the eigenvalue and ω is the imaginary part of the eigenvalue, the damping ratio sensitivity S2 is obtained as shown in equation (22).

[0099]

[0100] The system's equilibrium point is determined by the power flow, i.e., the injected power at each generator node and load node; in other words, it is determined by the system's operating mode. Under a given operating mode, the active / reactive power injected into all nodes is represented by the vector s. sp Indicate. Q GIC As a load applied to the node, the node power is as shown in (23).

[0101] s = s sp +s Q (E x E y ) (twenty three)

[0102] In the formula, s Q The power change caused by GMD, i.e., Q GIC , which is E x and E y The function.

[0103] If we separate the power flow equations from all the algebraic equations, the voltage and phase of each node can be represented as y. N The other part is represented as y R Then equation (23) can be divided into generator stator voltage balance equation (24) and power flow equation (25).

[0104] g R (x,y R ,y N)=0 (24)

[0105] g N (y N ) = s sp +s Q (25)

[0106] steady-state equilibrium point y N y R The calculation of x and the matrices A, B, C and D in (21) is exactly the same as that of traditional SSS analysis, that is, firstly using the given s sp Perform power flow calculations to obtain the steady-state values ​​of node voltages and phases. Use x, y R and y N To obtain their steady-state values ​​x, we need to understand the relationship between them. 0 and Then, the corresponding matrices A, B, C, and D are formed to obtain A. sys The eigenvalues ​​and corresponding left and right eigenvectors of A, B, C, and D are then used. Therefore, the remaining question is how to compute the eigenvalues ​​of each element in A, B, C, and D for E. x and E y The partial derivatives of .

[0107] The power flow equation (25) for E x Take the partial derivatives to obtain the node voltage and phase angle (or voltage components in Cartesian coordinates) with respect to E. x The partial derivatives are shown in equation (26).

[0108]

[0109] In the formula, To calculate the power flow g using the Newton-Raphson method N (y N ) = s sp The augmented matrix of the Jacobian matrix at convergence contains all nodes.

[0110] Node current versus E x The partial derivatives can be directly obtained from the voltage power equation. For example, if the node voltage and current are expressed in rectangular coordinates, the power equation for node i is shown in (27). The partial derivatives of E on both sides... x Taking the partial derivatives yields equation (28).

[0111]

[0112] In the formula, P spi and Q spi For s sp The power value related to node i. For s Q Q related to node iGIC .

[0113]

[0114] and The result has already been obtained in equation (26), and can be calculated by substituting it into equation (28). and

[0115] Voltage components U along the generator power angle δ, d-axis, and q-axis d and U q For example, it illustrates the effect of each state variable of the generator on E. x The methods for calculating the partial derivatives are shown in (29) and (30).

[0116]

[0117] In the formula, X q This is a synchronization reactance. R a This is the stator resistance.

[0118]

[0119] Both sides of equations (29) and (30) with respect to E x Taking the partial derivatives, we get equations (31) and (32).

[0120]

[0121]

[0122] Generator node voltage and current versus E x The partial derivatives of have been obtained in (26) and (28), therefore and δ 0 For E x The partial derivatives can be obtained from (31) and (32). Transform the rectangular coordinates into dq coordinates and apply E... x Taking the partial derivative, we get equation (33).

[0123]

[0124] Similarly, calculation and For E x Partial derivatives. Steady-state values ​​of other generator variables. and For E x Partial derivatives are obtained using similar methods and will not be repeated. The calculation of each state variable x and algebraic variable y (including yi) is performed using the same method. Rand y N The steady-state value of E x After the partial derivatives, each element in matrices A, B, C, and D with respect to E x The partial derivatives can be directly derived from the relationships between them and the steady-state values ​​of these variables with respect to E. x It is derived from the partial derivatives. Then, the eigenvalue pairs E x The sensitivity can be obtained from (11). Eigenvalues ​​for E y The sensitivity calculation method is the same. Finally, the damping ratio sensitivity is calculated using equation (22).

[0125] The reactive power loss generated by the geomagnetic induced current is calculated using the induced geoelectric field (IGF) sample and applied as a load to the power flow calculation of the power system. The voltage stability sensitivity S1 and damping ratio sensitivity S2 are then calculated.

[0126] The process of constructing the joint sensitivity feature space is as follows:

[0127] The voltage sensitivity and damping ratio sensitivity are combined to form the total sensitivity vector sample [S1, S2];

[0128] Principal component analysis (PCA) is used to select the first s principal components with a contribution rate greater than 98% from the total sensitivity vector sample. The first s principal components constitute the joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity.

[0129] Step S4: Cluster multiple joint sensitivity scenarios in the joint sensitivity feature space, and map each joint sensitivity scenario to the induced ground electric field space to obtain multiple induced ground electric field sensitivity scenarios; multiple induced ground electric field sensitivity scenarios correspond to multiple substations with different installation locations of small resistors.

[0130] Based on the clustering index K DBI The optimal number of clusters for each sensitivity scenario is obtained. Based on the optimal number of clusters, K joint sensitivity scenarios are obtained by clustering in the joint sensitivity feature space using the K-means clustering method.

[0131] Step S5: Use the combined sensitivity of the induced ground electric field sensitivity scenario to pre-screen substations with small resistors installed.

[0132] A preset threshold value is set, and the induced ground electric field sensitivity scenarios with joint sensitivity greater than the sensitivity threshold value are selected. The number of substations corresponding to the selected induced ground electric field sensitivity scenarios is determined as the chromosome length in the binary encoding genetic algorithm (non-dominated sorting genetic algorithm).

[0133] Step S6: Establish an objective function for optimizing the installation location of small resistors.

[0134] The objective functions include: a first objective function that minimizes the reactive power loss of the transformer, a second objective function that minimizes the sum of the resistance values ​​of the small resistors in the system, and a third objective function that minimizes the expected value of voltage fluctuation.

[0135] The first objective function is: In the formula, I Q Let T be the number of scenes, and p be the first objective function. k f represents the probability of scenario k occurring; 1k Let be the resistance value of the small resistor in scenario k. Q GICn Let n be the reactive power loss of substation n;

[0136] The second objective function is: In the formula, I R The second objective function is f; 2k This represents the sum of the resistance values ​​of the small resistors in scenario k. N s R represents the number of small resistors already installed. g The resistance value of the small resistor installed in node g;

[0137] The third objective function is: In the formula, I V The third objective function; f 3k For the node voltage fluctuation in scenario k. U g U0 and U0 are the actual voltage and rated voltage of node g, respectively, and ΔU max This represents the maximum deviation of the node voltage;

[0138] The constraints for the first, second, and third objective functions are as follows:

[0139]

[0140] The constraints include the following equations: the first equation is the voltage constraint, the second equation is the maximum value constraint of node GIC, the third equation is the average value constraint of node GIC, the fourth equation is the damping ratio constraint, the fifth equation is the grounding resistance constraint, the sixth equation is the active power balance constraint, and the seventh equation is the reactive power balance constraint.

[0141] in, V gmin and V gmax These represent the random fuzzy voltage value of node g, and the upper and lower limits of the allowable voltage for node g, respectively. For random fuzzy geomagnetic induced current values, I GIC,maxThe threshold value for the geomagnetic induced current; I GIC,ave The threshold value is the average geomagnetic induced current of all transformers in the system. The average GIC value for all transformers; Let ΔQ be the initial value of the damping ratio. GICn Let be the change in reactive power loss of substation n. To determine the sensitivity of the damping ratio to the reactive power loss of the transformer, ζ T R is the damping ratio threshold; T It is the threshold of the small resistance; N T N represents the number of transformers. G and N L These represent the number of generator nodes and the number of load nodes, respectively. This represents the random fuzzy active power of generator node r. This represents the random fuzzy active power at generator node t. This represents the random fuzzy reactive power of generator node r. This represents the random fuzzy reactive power of generator node t.

[0142] To ensure the effectiveness of evenly distributing GIC, the current of all 500kV transformers in the system must not exceed 50A, and the voltage of all 220kV transformers must not exceed 20A. T R is the damping ratio threshold, which is set to 0.05 in this embodiment of the invention. T This is the threshold value for low resistance. According to DL / T 621-1997 "Grounding of AC Electrical Installations," to ensure the reliability of transformer grounding, the R value of a 500kV transformer... g Less than 3Ω, R of a 220kV transformer g Less than 4Ω.

[0143] Step S7: Based on multiple induced ground electric field sensitivity scenarios and pre-screened substations, a binary-coded genetic algorithm is used to solve the objective function and obtain the optimal small resistor installation location.

[0144] The specific implementation process is as follows:

[0145] Based on multiple induced ground electric field sensitivity scenarios and pre-selected substations, a binary encoded genetic algorithm is used to solve the first objective function, the second objective function, and the third objective function respectively, to obtain the first Pareto optimal solution set, the second Pareto optimal solution set, and the third Pareto optimal solution set;

[0146] Using formula Solve the fuzzy membership degrees of the first, second, and third Pareto optimal solution sets respectively; where u m(x j ) represents x in the Pareto optimal solution set. j The fuzzy membership degree of the corresponding m-th objective function value, F m (x j ) represents x in the Pareto optimal solution set. j The corresponding m-th objective function value, and These are the minimum and maximum values ​​of the m-th objective function, respectively; x j This is the j-th group of induced ground electric field samples;

[0147] Based on the fuzzy membership degrees of the first, second, and third Pareto optimal solution sets, respectively, the formulas are used... Calculate the satisfaction levels of the first Pareto optimal solution set, the second Pareto optimal solution set, and the third Pareto optimal solution set; where h m (x) is x in the Pareto optimal solution set. j The corresponding compromise solution for the m-th objective function value;

[0148] The maximum value among the satisfaction levels of the first, second, and third Pareto optimal solution sets is taken as the optimal installation location for the small resistor.

[0149] In binary encoded genetic algorithms, 0 elements on chromosomes represent no small resistors installed, and 1 elements represent small resistors installed.

[0150] This invention calculates the induced geoelectric field using data from multiple geomagnetic disturbances during the 23rd solar cycle, and fits it using a three-parameter t-distribution, such as... Figure 2 and Figure 3 As shown. Frequency statistics of the parameters of the probability distribution function reveal that the frequencies of each parameter value are not uniform within a certain interval, exhibiting certain differences and lacking a specific statistical regularity. Therefore, using fuzzy variables from fuzzy theory to describe this is more appropriate, such as... Figure 4 and Figure 5 As shown. Figure 4 (a) in the diagram is a schematic diagram of the location parameter distribution of the probability density function of the east-west component of the induced ground electric field Ex. Figure 4 (b) in the diagram is a schematic diagram of the scale parameter distribution of the probability density function of the east-west component of the induced ground electric field Ex. Figure 4 (c) in the figure is a schematic diagram of the shape parameter distribution of the probability density function of the east-west component of the induced ground electric field Ex. Figure 5 (a) in the diagram is a schematic diagram of the location parameter distribution of the probability density function of the north-south component of the induced ground electric field Ex. Figure 5(b) in the diagram is a schematic diagram of the scale parameter distribution of the probability density function of the north-south component of the induced ground electric field Ex. Figure 5 (c) in the figure is a schematic diagram of the shape parameter distribution of the probability density function of the north-south component of the induced ground electric field Ex.

[0151] from Figure 2 , Figure 3 , Figure 4 and Figure 5 It can be seen that the distribution of characteristic roots of the power system changes significantly when a geomagnetic storm occurs, producing characteristic roots with positive real parts, and the power system loses stability.

[0152] This invention optimizes the installation position of small resistors, reduces current, and thus plays a role in disaster prevention.

[0153] This invention also provides a low-resistance configuration system for uncertain geomagnetic disturbances in wind power systems, comprising:

[0154] The random fuzzy model building module is used to build a random fuzzy model of the induced geoelectric field based on geomagnetic disturbance data.

[0155] The sample acquisition module is used to obtain induced ground electric field samples based on a random fuzzy model through random fuzzy simulation and inverse transform methods.

[0156] The joint sensitivity feature space construction module is used to apply the transformer reactive power loss caused by the induced ground electric field sample as a load to the power system, causing node voltage changes, thereby constructing a joint sensitivity feature space of voltage sensitivity and damping ratio sensitivity.

[0157] The scene acquisition module is used to cluster multiple joint sensitivity scenes in the joint sensitivity feature space and map each joint sensitivity scene to the induced ground electric field space to obtain multiple induced ground electric field sensitivity scenes; the multiple induced ground electric field sensitivity scenes correspond to multiple substations with different installation locations of small resistors;

[0158] The pre-screening module is used to pre-screen substations with small resistors by utilizing the joint sensitivity of the induced ground electric field sensitivity scenario.

[0159] The objective function creation module establishes an objective function for optimizing the installation location of small resistors.

[0160] The optimization module is used to solve the objective function based on multiple induced ground electric field sensitivity scenarios and pre-screened substations, and obtain the optimal small resistor installation location.

[0161] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0162] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for small resistance configuration of uncertainty geomagnetic disturbance with wind power system, characterized in that, The method comprises the following steps: constructing a random fuzzy model of induced geoelectric field based on geomagnetic disturbance data; obtaining induced geoelectric field samples by random fuzzy simulation and inverse transformation method according to the random fuzzy model; applying transformer reactive power loss caused by the induced geoelectric field samples to the power system as load to cause node voltage change, thereby constructing a joint sensitivity characteristic space of voltage sensitivity and damping ratio sensitivity; clustering a plurality of joint sensitivity scenarios in the joint sensitivity characteristic space, and mapping each joint sensitivity scenario to the induced geoelectric field space to obtain a plurality of induced geoelectric field sensitivity scenarios; the plurality of induced geoelectric field sensitivity scenarios correspond to a plurality of substation installation positions of small resistors; pre-screening the substations installed with small resistors by using the joint sensitivity of the induced geoelectric field sensitivity scenarios; establishing an objective function for optimizing the installation position of the small resistor; solving the objective function by using a binary coded genetic algorithm based on the plurality of induced geoelectric field sensitivity scenarios and the pre-screened substations, and obtaining the optimal installation position of the small resistor.

2. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 1, characterized in that, The method of constructing a random fuzzy model of induced geoelectric field based on geomagnetic disturbance data comprises the following steps: calculating the induced geoelectric field corresponding to the geomagnetic disturbance data of each geomagnetic disturbance event respectively; The probability density distribution function of the induced geoelectric field is obtained by analyzing the probability density distribution characteristics of each induced geoelectric field, and is In the formula, f(a) is the probability density distribution function of the a-th induced geoelectric field, Γ(·) is a gamma function, μ is a location parameter, σ is a scale parameter, and υ is a shape parameter. performing fuzzy uncertainty analysis on the distribution parameters of all induced geoelectric fields to determine the membership function of the distribution parameters as where μ x , σ x and υ x are the location parameter, scale parameter and shape parameter of the east-west component of the induced geo-electric field respectively, μ y , σ y and υ y are the location parameter, scale parameter and shape parameter of the north-south component of the induced geo-electric field respectively, f(μ x ), f(σ x ) and f(υ x ) are the membership functions of μ x , σ x and υ x respectively, f(μ y ), f(σ y ) and f(υ y ) are the membership functions of μ y , σ y and υ y respectively; μ x , σ x , υ x , μ y , σ y and υ y are the distribution parameters of the induced geo-electric field.

3. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 2, characterized in that, The method of obtaining induced geoelectric field samples by random fuzzy simulation and inverse transformation method according to the random fuzzy model comprises the following steps: In μ x , σ x , υ x , μ y , σ y and υ y , the confidence intervals of each are extracted M parameters P os {·}≥ε; wherein P os {·} is the likelihood measure, and ε is a positive number; extracted M μ x ,σ x ,υ x , and simulate P os {μ xi ,σ xi ,υ xi} for each east-west parameter combination in the interval [0, 1], while matching any combination of the extracted M μ y ,σ y , and υ y , and simulate P os {μ yi ,σ yi ,υ yi} for each north-south parameter combination in the interval [0, 1]; wherein μ xi ,σ xi ,υ xi are the position parameter, scale parameter and shape parameter of the east-west component of the induced geoelectric field in the i-th east-west parameter combination, and μ yi ,σ yi ,υ yi are the position parameter, scale parameter and shape parameter of the north-south component of the induced geoelectric field in the i-th north-south parameter combination; inputting the east-west parameter combination and the north-south parameter combination into the probability density distribution function of the induced geoelectric field respectively to calculate the probability density distribution of the east-west component of the induced geoelectric field and the probability density distribution of the north-south component of the induced geoelectric field; All the probability density distributions of the east component of the induced geoelectric field are cumulated to obtain the cumulative probability density function F x () while all the probability density distributions of the north component of the induced geoelectric field are cumulated to obtain the cumulative probability density function F y () According to the cumulative probability density function F x (), the cumulative probability density function F y (), each easting parameter combination and each northing parameter combination, based on the inverse transform method, using the formula The induced geoelectric field component corresponding to each easting parameter combination is calculated respectively And the induced geoelectric field component corresponding to each northing parameter combination In the formula, Ch(·) is the opportunity measurement operator, E x / y The induced geoelectric field easting / northing component; combining the induced geoelectric field components and randomly combining induced geoelectric field samples 4. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 3, characterized in that, The method of constructing a joint sensitivity characteristic space of voltage sensitivity and damping ratio sensitivity comprises the following steps: According to the induced geo-electric field samples, a voltage sensitivity S1 is obtained wherein S1 is the voltage sensitivity, S VQ,Nj is the voltage sensitivity of node N under the jth group of induced geo-electric field samples, N B is the number of nodes of the power system; Based on the inductive electric field samples, the damping ratio sensitivity is determined as where S2 is the damping ratio sensitivity, ζ is a function of the damping ratio and the eigenvalue, σ is the eigenvalue real part, and ω is the eigenvalue imaginary part. constructing a total sensitivity vector sample [S1, S2] from the voltage sensitivity and the damping ratio sensitivity; selecting the first s principal components with a contribution rate greater than 98% from the total sensitivity vector sample by principal component analysis, and the first s principal components constitute the joint sensitivity characteristic space of the voltage sensitivity and the damping ratio sensitivity.

5. The method for configuring small resistors to handle uncertain geomagnetic disturbances in a wind power system according to claim 1, characterized in that, The method of clustering a plurality of joint sensitivity scenarios in the joint sensitivity characteristic space comprises the following steps: According to the clustering index K DBI The optimal number of clusters for the sensitivity scenario is obtained; according to the optimal cluster number, K joint sensitivity scenarios are clustered in the joint sensitivity characteristic space by using the K-means clustering method.

6. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 1, characterized in that, The method of pre-screening the substations installed with small resistors by using the joint sensitivity of the induced geoelectric field sensitivity scenarios comprises the following steps: selecting the induced geoelectric field sensitivity scenarios with joint sensitivity greater than a sensitivity threshold value, and determining the number of substations corresponding to the selected induced geoelectric field sensitivity scenarios as the length of the chromosome in the binary coded genetic algorithm.

7. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 4, characterized in that, The objective function comprises a first objective function taking the minimum transformer reactive power loss as the optimization target, a second objective function taking the minimum sum of system small resistor resistance values as the optimization target, and a third objective function taking the minimum expected value of voltage fluctuation as the optimization target. The first objective function is: where I Q is the first objective function, T is the number of scenarios, p k is the probability of scenario k occurring; f 1k is the resistance value of the small resistance in scenario k, Q GICn is the reactive power loss of substation n; The second objective function is: where I R is the second objective function; f 2k is the sum of small resistance values in the scene k, N s is the number of installed small resistances, R g is the small resistance value installed in the node g; The third objective function is: where I V is the third objective function; f 3k is the node voltage fluctuation of the scene k, U g and U0 are the actual voltage and rated voltage of the node g, ΔU max is the maximum deviation of the node voltage; The constraints of the first objective function, the second objective function and the third objective function are wherein, V gmin and V gmax are the random fuzzy voltage value of node g, the lower and upper limits of the allowable voltage of node g, respectively; is the random fuzzy geomagnetic induction current value, I GIC,max is the threshold value of the geomagnetic induction current; I GIC,ave is the threshold value of the average geomagnetic induction current of all transformers in the system, is the average value of GIC of all transformers; is the initial value of the damping ratio, AQ GICn is the reactive power loss change amount of substation n, is the sensitivity of the damping ratio to the reactive power loss of the transformer, z T is the threshold value of the damping ratio; R T is the threshold value of the small resistance; N T is the number of transformers, N G and N L are the number of generator nodes and the number of load nodes, respectively; represents the random fuzzy active power of generator node r, represents the random fuzzy active power of generator node t, represents the random fuzzy reactive power of generator node r, represents the random fuzzy reactive power of generator node t.

8. The method for configuring small resistances to mitigate uncertain geomagnetic disturbances in a wind power system according to claim 7, characterized in that, The substation based on multiple induced geoelectric field sensitivity scenes and pre-screening adopts a binary coded genetic algorithm to solve the objective function and obtain an optimal small resistance installation position, and specifically includes the following steps: The substation based on multiple induced geoelectric field sensitivity scenes and pre-screening adopts a binary coded genetic algorithm to solve the objective function and obtain an optimal small resistance installation position, and specifically includes the following steps: The fuzzy membership degrees of the first, second and third Pareto optimal solution sets are solved by using the formula m = 1, 2, 3, respectively, wherein u m (x j ) is the fuzzy membership degree of the x j corresponding to the mth objective function value in the Pareto optimal solution set, F m (x j ) is the x j corresponding to the mth objective function value in the Pareto optimal solution set, and are the minimum value and the maximum value of the mth objective function value, respectively; x j is the jth group of induced geoelectric field samples; According to the fuzzy membership of the first Pareto optimal solution set, the fuzzy membership of the second Pareto optimal solution set and the fuzzy membership of the third Pareto optimal solution set, the satisfaction degrees of the first Pareto optimal solution set, the second Pareto optimal solution set and the third Pareto optimal solution set are respectively calculated by using the formula satisfaction degrees of the first Pareto optimal solution set, the second Pareto optimal solution set and the third Pareto optimal solution set; wherein, h m (x) is x in the Pareto optimal solution set j the satisfaction degree of the corresponding mth objective function value; The maximum value among the satisfaction degrees of the first, second and third Pareto optimal solution sets is taken as the optimal small resistance installation position.

9. The method for configuring small resistances to address uncertain geomagnetic disturbances in a wind power system according to claim 8, characterized in that, In the binary coded genetic algorithm, a 0 element on a chromosome represents that a small resistance is not installed, and a 1 represents that a small resistance is installed.

10. A wind power system containing an uncertain geomagnetic disturbance low resistance configuration system, characterized in that, It includes the following steps: A random fuzzy model construction module is configured to construct a random fuzzy model of an induced geoelectric field based on geomagnetic disturbance data; A sample acquisition module is configured to obtain induced geoelectric field samples through random fuzzy simulation and inverse transformation methods according to the random fuzzy model; A joint sensitivity characteristic space construction module is configured to apply transformer reactive power loss caused by induced geoelectric field samples to a power system as a load, cause node voltage changes, and thereby construct a joint sensitivity characteristic space of voltage sensitivity and damping ratio sensitivity; A scene acquisition module is configured to cluster multiple joint sensitivity scenes in the joint sensitivity characteristic space, and map each joint sensitivity scene to an induced geoelectric field space to obtain multiple induced geoelectric field sensitivity scenes; A substation with multiple small resistances installed at different positions corresponding to the multiple induced geoelectric field sensitivity scenes; A pre-screening module is configured to pre-screen substation installed with small resistors by using the joint sensitivity of the induced geoelectric field sensitivity scenes; An objective function establishment module is configured to establish an objective function for optimizing the installation position of small resistors; An optimization module is configured to adopt a binary coded genetic algorithm to solve the objective function based on multiple induced geoelectric field sensitivity scenes and pre-screened substations, and obtain an optimal small resistance installation position.

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