Temporary overvoltage calculation method and device for new energy direct current delivery system

Abstract

The invention discloses a temporary overvoltage calculation method and device for a new energy direct current delivery system. The method comprises the following steps: screening influence parameters of an overvoltage peak value of a new energy direct current delivery system in electromagnetic transient simulation based on a Sobol global sensitivity analysis method, and determining key influence factors; according to the value range of the key influence factor and a preset constraint condition, determining multiple groups of sample data of the key influence factor and a sample data set formed by a temporary overvoltage peak value of each group of data; fitting the sample data set by adopting a ridge regression method of QR decomposition to obtain a fitting relationship between the key influence factors and the transient overvoltage peak value; and calculating a simulation transient overvoltage peak value of the new energy alternating current delivery system according to the simulation key influence factor value of the new energy direct current delivery system by adopting the fitting relationship.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and more specifically, to a method and device for calculating temporary overvoltage of a new energy direct current transmission system. Background Art

[0002] As the proportion of renewable energy power generation increases, the establishment of large renewable energy stations gradually extends to areas far away from the load center. In order to make full use of the generated electricity, laying large-capacity cross-regional ultra-high voltage AC and DC long-distance transmission channels is an important trend in my country's current power grid construction. However, the disturbance caused by DC faults will cause system voltage fluctuations, resulting in an increase in temporary overvoltage, which makes it easy for renewable energy units to be disconnected from the grid on a large scale. Therefore, the ability to quickly and accurately characterize temporary overvoltage is an important indicator for judging system safety.

[0003] Electromagnetic transient simulation technology and electromechanical transient simulation technology are currently advantageous tools for judging whether transient stability is within the safety margin. For electromagnetic transient simulation research, the voltage instantaneous value characteristics can be analyzed, and the voltage harmonic components can be more accurately characterized. However, in the calculation of power system mode, it is usually limited by computing resources and computing efficiency, and has the characteristics of high precision and slow simulation speed. For electromechanical transient simulation research, based on the phasor model, some differential equations are simplified into algebraic equations, which can only be used to analyze the power frequency component. However, due to its high computing efficiency, it is widely used in power system mode calculation, and has the characteristics of fast simulation speed and low precision. In order to take into account the advantages of high electromagnetic simulation accuracy and fast electromechanical simulation speed, it is urgent to propose a method for analyzing the electromagnetic-electromechanical mapping relationship of temporary overvoltage in new energy DC transmission systems, which can ensure that the voltage value is quickly obtained while also meeting the accuracy of the results. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and device for calculating temporary overvoltage in a new energy direct current transmission system.

[0005] According to one aspect of the present invention, a method for calculating temporary overvoltage of a new energy direct current transmission system is provided, comprising:

[0006] Based on the Sobol global sensitivity analysis method, the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation are screened to determine the key influencing factors;

[0007] According to the value range of the key influencing factors and the preset constraint conditions, a plurality of groups of sample data of the key influencing factors and a sample data set consisting of the temporary overvoltage peak value of each group of data are determined;

[0008] The QR decomposition ridge regression method is used to fit the sample data set to obtain the fitting relationship between the key influencing factors and the transient overvoltage peak value;

[0009] The simulated transient overvoltage peak of the new energy AC transmission system is calculated based on the simulation key influencing factor values ​​of the new energy DC transmission system using the fitting relationship.

[0010] Optionally, the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation are screened based on the Sobol global sensitivity analysis method to determine the key influencing factors, including:

[0011] Determine the value range of the influencing parameters;

[0012] Map the value range to the preset value range,

[0013] Using the Sobol sequence generator, 2N quasi-random sample points are randomly generated according to the number of sampling samples N and the number of image parameters n;

[0014] The first N sample points form the basis matrix A N×n , the last N sample points form the matrix B N×n , and based on the base matrix A, repeatedly change i from 1 to n, replace the value of the i-th column with the value of the i-th column in the matrix B, and obtain n difference matrices AB i ;

[0015] The electromagnetic model is used to calculate the basis matrix A N×n , Matrix B N×n And n difference matrices AB i Perform simulation calculations to obtain the first matrix, the second matrix and the third matrix of the temporary overvoltage peak value of the corresponding new energy direct current transmission system;

[0016] According to the basis matrix A N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, and calculate the influence degree of each influencing parameter;

[0017] The influence degrees of all influencing parameters are arranged in descending order, and the influencing parameters whose image degrees exceed the preset threshold are selected as key influencing factors.

[0018] Optionally, according to the basis matrix A N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, calculate the influence degree of each influencing parameter, including:

[0019] According to the basis matrix A N×nand the first matrix calculates the expected value;

[0020] Calculate the total output variance based on the first matrix and the expected value;

[0021] Calculate the first-order sensitivity index of each influencing parameter and the total effect sensitivity index according to the expected value, the total output variance, the first matrix, the second matrix and the third matrix;

[0022] The influence degree of each influencing parameter is determined according to the first-order sensitivity index and the total effect sensitivity index of each influencing parameter.

[0023] Optionally, the expected value E[Y] is calculated as:

[0024]

[0025] The calculation formula for the output total variance Var(Y) is:

[0026]

[0027] Where Y(A) is the first matrix; N is the number of samples.

[0028] Optionally, the first-order sensitivity index S i and the total effect sensitivity index S Ti The calculation formula is:

[0029]

[0030] In the formula, Y(A) n is the output corresponding to the nth sample of the basis matrix A, Y(B) n is the output corresponding to the nth sample of matrix B, Y(AB i ) n is the difference matrix AB i The output corresponding to the nth sample.

[0031] Optionally, the preset constraints are: the electrical distance Z1 from the new energy to the DC converter station is the maximum, Z1|=0.2pu, and the proportion of new energy η=0.9.

[0032] Optionally, the objective function of the ridge regression method of QR decomposition is:

[0033]

[0034] Where Q and R are two matrices of QR decomposition, Y is the overvoltage peak difference vector, C is the unknown quantity to be fitted, and λ is the regularization strength parameter.

[0035] Optionally, the expression of the fitted relationship is:

[0036]

[0037] In the formula, X / R is the impedance ratio, SCR is the short circuit ratio, K p_PLL is the PLL control parameter, ΔU r Temporary overvoltage peak.

[0038] According to another aspect of the present invention, a temporary overvoltage calculation device for a new energy direct current transmission system is provided, comprising:

[0039] The screening module is used to screen the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation based on the Sobol global sensitivity analysis method to determine the key influencing factors;

[0040] A determination module, used to determine multiple groups of sample data of key influencing factors and a sample data set consisting of a temporary overvoltage peak value of each group of data according to a value range of the key influencing factors and preset constraints;

[0041] A fitting module is used to fit the sample data set using the ridge regression method of QR decomposition to obtain the fitting relationship between the key influencing factors and the transient overvoltage peak value;

[0042] The calculation module is used to calculate the simulated transient overvoltage peak value of the new energy AC transmission system according to the simulation key influencing factor values ​​of the new energy DC transmission system by adopting a fitting relationship.

[0043] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method described in any one of the above aspects of the present invention.

[0044] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of the above aspects of the present invention.

[0045] Therefore, the present invention proposes a method for calculating temporary overvoltage of a new energy direct current transmission system. Based on the Sobol global sensitivity analysis method, the influencing parameters of the overvoltage peak of the new energy direct current transmission system in the electromagnetic transient simulation are screened to determine the key influencing factors; according to the value range of the key influencing factors and the preset constraints, a sample data set consisting of multiple groups of sample data of the key influencing factors and the temporary overvoltage peak of each group of data is determined; the sample data set is fitted by the ridge regression method of QR decomposition to obtain the fitting relationship between the key influencing factors and the transient overvoltage peak; the fitting relationship is used to calculate the simulated transient overvoltage peak of the new energy alternating current transmission system according to the simulated key influencing factor values ​​of the new energy direct current transmission system for analyzing the safety of the power grid and ensuring the stable operation of the new energy direct current transmission system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0047] Figure 1 It is a flow chart of a temporary overvoltage calculation method of a new energy direct current transmission system provided by an exemplary embodiment of the present invention;

[0048] Figure 2 is a Thevenin equivalent circuit diagram of a new energy direct current transmission system provided by an exemplary embodiment of the present invention;

[0049] Figure 3 It is a schematic diagram of the structure of a VSC grid-connected system of a PSCAD electromagnetic model provided by an exemplary embodiment of the present invention;

[0050] Figure 4 is a PLL control block diagram provided by an exemplary embodiment of the present invention;

[0051] Figure 5 is a block diagram of a building system provided by an exemplary embodiment of the present invention;

[0052] Figure 6 It is a structural schematic diagram of a temporary overvoltage calculation device for a new energy direct current transmission system provided by an exemplary embodiment of the present invention;

[0053] Figure 7 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0054] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0055] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0056] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0057] It should also be understood that, in the embodiments of the present invention, “plurality” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0058] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0059] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0060] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0061] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0062] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0063] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0064] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0065] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc.

[0066] Electronic devices such as terminal devices, computer systems, servers, etc. can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0067] Exemplary Methods

[0068] Figure 1 FIG. 1 is a flow chart of a method for calculating a temporary overvoltage of a new energy DC transmission system provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the temporary overvoltage calculation method 100 of the new energy direct current transmission system includes the following steps:

[0069] Step 101, screening the influencing parameters of the overvoltage peak of the new energy direct current transmission system in the electromagnetic transient simulation based on the Sobol global sensitivity analysis method, and determining the key influencing factors;

[0070] Step 102, determining multiple groups of sample data of key influencing factors and a sample data set consisting of a temporary overvoltage peak value of each group of data according to the value range of the key influencing factors and preset constraints;

[0071] Step 103, using the ridge regression method of QR decomposition to fit the sample data set, to obtain the fitting relationship between the key influencing factors and the transient overvoltage peak value;

[0072] Step 104 , using a fitting relationship to calculate the simulated transient overvoltage peak value of the new energy AC transmission system according to the simulated key influencing factor values ​​of the new energy DC transmission system.

[0073] Specifically, in view of the technical problems existing in the prior art, the present invention proposes a temporary overvoltage calculation method for a new energy DC transmission system, comprising the following steps: 1. Based on the Sobol global sensitivity analysis method, the key influencing factors of the overvoltage peak value of the new energy AC transmission system in the electromagnetic transient simulation are screened out; 2. Based on the ridge regression method of QR decomposition, a fitting method is obtained; 3. Samples are generated according to the constraint conditions to establish a mapping relationship between the electromagnetic-electromechanical temporary overvoltage peak values;

[0074] Step 1: Based on the Sobol sensitivity analysis method, key influencing factors of the overvoltage peak of the new energy DC transmission system in electromagnetic transient simulation are screened out;

[0075] (1) Select influencing parameters and determine the value range;

[0076] (2) Select the indicators to be evaluated and analyzed, and perform sampling according to the Sobol test principle, map the value range of each parameter to [0,1], determine the number of samples N and the number of parameters n, and use the Sobol sequence generator to generate 2N quasi-random sample points;

[0077] Generate difference matrix AB i , the first N sample points form the basis matrix A N×n , the last N sample points form the matrix B N×n , and based on matrix A, replace the values ​​in the i-th column with the values ​​in the i-th column in matrix B to obtain the difference matrix AB i Repeat the above steps, making i range from 1 to n, and obtain n difference matrices;

[0078] (3) Simulation of the maximum voltage of the electromagnetic model. Substitute the sample parameter matrices A and B and the difference matrix AB into the electromagnetic transient model for simulation, and obtain the corresponding temporary overvoltage peak matrices Y(A), Y(B) and Y(AB) of the new energy DC transmission system. i );

[0079] (4) Sensitivity calculation: First, the expected value is calculated from the basis matrix A and its output matrix Y(A):

[0080]

[0081] Where: N is the number of samples, Y(A) n is the output corresponding to the nth sample of matrix A;

[0082] In order to calculate the sensitivity index of the Sobol method, the total output variance must also be calculated:

[0083]

[0084] According to the expected value and the total output variance, the first-order sensitivity index S of the i-th parameter is obtained. i and the total effect sensitivity index S Ti for:

[0085]

[0086] Where: Y(A) n is the output corresponding to the nth sample of matrix A, Y(B) n is the output corresponding to the nth sample of matrix B, Y(AB i ) n is the difference matrix AB i The output corresponding to the nth sample;

[0087] The first-order sensitivity index S of the i-th parameter i The larger the value, the greater the direct impact of the parameter on the target output; the total effect sensitivity index S Ti The larger it is, the greater the interaction between this parameter and other parameters.

[0088] By judging the degree of influence, the key parameters that affect the temporary overvoltage peak of the new energy DC transmission system can be determined;

[0089] Step 2: Get the fitting method based on the ridge regression method of QR decomposition

[0090] The peak difference vector of overvoltage between electromagnetic transient simulation and electromechanical transient simulation is Y n×1 , where n is the number of samples used for fitting. For the i-th and j-th key factors k i , k j , the constant term, power term, and cross term total m terms, expressed as X n×m . Polynomial coefficient C m×1 is the unknown quantity to be fitted. Then for n groups of samples, we have: n×1 =X n×m C m×1 .

[0091] Perform QR decomposition on X, and we have X = QR, where Q is an orthogonal matrix and R is an upper triangular matrix. The original ridge regression problem can be transformed into: Let Q T Y=D, by solving the equation (R T R+λI)C=R T D can obtain the optimal estimate solution of coefficient C.

[0092] Then the coefficient of determination R 2 (also known as goodness of fit) to evaluate the fitting effect, R 2 The expression is:

[0093] Among them, SST is the total sum of squares, SSR is the regression sum of squares, and SSE is the residual sum of squares. The expression is as follows:

[0094]

[0095] Where: y i is the experimental value, is the average value of the experimental values, is the regression value.

[0096] Step 3: Generate samples based on constraint conditions to establish a mapping relationship between electromagnetic and electromechanical overvoltage peaks

[0097] The analysis obtains the constraints of the key influencing factors of the new energy overvoltage peak in the electromagnetic transient simulation in step 1, and determines the range of key parameters. Samples are uniformly taken according to the constraints and the value range, and then the functional relationship formula is obtained by fitting these samples.

[0098] The coefficient of determination in the goodness of fit describes the variation in the response variable of the model. The fitting effect is judged based on the coefficient of determination.

[0099] In one embodiment of the present invention, the implementation process of the method proposed by the present invention is as follows:

[0100] Step 1: Based on the Sobol global sensitivity analysis method, key influencing factors of the temporary overvoltage peak of the new energy DC transmission system in electromagnetic transient simulation are screened out;

[0101] The parameters affecting the overvoltage peak of renewable energy are selected as follows: network parameter synchronous machine to DC converter station reactance X2, electrical distance from renewable energy to DC converter station |Z1|, impedance ratio m=X1 / R, renewable energy proportion η and PLL control parameter K p_PLL , K i_PLL , determine the value range as shown in Table 1;

[0102] Table 1 Value ranges of various influencing parameters

[0103]

[0104]

[0105] In the embodiment of the present invention, the Thevenin equivalent circuit diagram of the new energy DC transmission system is as follows: Figure 2 As shown, ignoring the dynamics of the renewable energy PLL link and the reactive power compensation dynamics of the DC system, there are many factors that can affect the magnitude of temporary overvoltage in the renewable energy system.

[0106] (1) Network parameters Synchronous machine to DC converter station reactance X2:

[0107]

[0108] The greater the electrical distance from the synchronous machine to the DC converter station, the greater the maximum voltage at the new energy machine terminal.

[0109] (2) Electrical distance from new energy to DC converter station |Z1|:

[0110] The electrical distance from the renewable energy source to the DC converter station can be represented by |Z1|. If m = X1 / R, then:

[0111]

[0112] When X1 / R is constant, the electrical distance from the renewable energy source to the DC converter station increases as R increases.

[0113]

[0114] To analyze the sign of the numerator of formula (3), first compare E eq and Since R is the line resistance, the value is usually not more than 0.2, and α is usually not more than 2. When the DC capacity is used as the reference, I N <1p.u., formula (2) shows that E eq >1, so Then get In addition, if m>1, it can be concluded that the numerator of formula (3) is positive.

[0115] Therefore, the maximum voltage at the terminal of the new energy source increases with the increase of the electrical distance from the new energy source to the DC converter station.

[0116] The schematic diagram of the electromagnetic transient model structure of the VSC grid-connected system is as follows: Figure 3 As shown, PLL control has a greater impact on the new energy overvoltage of the electromagnetic model.

[0117] (1)PLL

[0118] PLL control block diagram Figure 4 As shown, the PLL control equation is:

[0119]

[0120] Where: K p_PLL is the proportional coefficient of the PLL, K i_PLL is the integral coefficient of the PLL

[0121] The new energy overvoltage peak value obtained by electromagnetic transient simulation after the lockout fault after DC commutation failure is cleared is selected as the evaluation index Y, and sampling is performed according to the Sobol test principle, the value range of the above 6 parameters is mapped to [0,1], the sample number is determined to be 5, and 10 quasi-random sample points are generated using the Sobol sequence generator;

[0122] Generate difference matrix AB i , the first 5 sample points form the basis matrix A 5×6 , the last 5 sample points form the matrix B 5×6 , and based on matrix A, replace the values ​​in the i-th column with the values ​​in the i-th column in matrix B to obtain the difference matrix AB i Repeat the above steps, changing i from 1 to 6, and obtain 6 difference matrices;

[0123] The electromagnetic model voltage maximum value simulation is performed by substituting the sample parameter matrices A, B and the difference matrix AB into the electromagnetic transient model for simulation, and the corresponding new energy DC transmission system temporary overvoltage peak matrices Y(A), Y(B) and Y(AB i );

[0124] Sensitivity calculation, first find the expected value from the basis matrix A and its output matrix Y(A):

[0125]

[0126] In order to calculate the sensitivity index of the Sobol method, the total output variance must also be calculated:

[0127]

[0128] According to the expected value and the total output variance, the first-order sensitivity index S of the i-th parameter is obtained. i and the total effect sensitivity index S Ti for:

[0129]

[0130] By judging the degree of influence, we can determine m, X2, and K. p_PLL are the key parameters of the temporary overvoltage peak of the new energy DC transmission system. Three key parameters are selected, among which m and X2 are related to the grid structure, and K p_PLL Related to new energy control. Since |Z1| and η are positively correlated with the maximum voltage, the maximum value |Z1|=0.2pu, η=0.9 is selected, and K p_PLL The other control parameters of K are at the boundary values ​​that can stabilize the system and make the overvoltage level higher. p_PLL Uniform sampling is performed to obtain samples.

[0131] Step 2: Based on the ridge regression method of QR decomposition, a fitting method for electromagnetic-electromechanical mapping is obtained.

[0132] The peak difference vector of overvoltage between electromagnetic transient simulation and electromechanical transient simulation is Y n×1 , where n is the number of samples used for fitting. For the i-th and j-th key factors k i , k j , the constant term, power term, and cross term total m terms, expressed as X n×m . Polynomial coefficient C m×1 is the unknown quantity to be fitted. Then for n groups of samples, we have: n×1 =X n×m C m×1

[0133] Perform QR decomposition on X, and we have X = QR, where Q is an orthogonal matrix and R is an upper triangular matrix. The original ridge regression problem can be transformed into: Let Q T Y=D, by solving the equation (R T R+λI)C=R T D can obtain the optimal estimate solution of coefficient C.

[0134] Analysis of m, X2, K p_PLL Relationship with the maximum difference between electromagnetic and electromechanical voltages.

[0135] The three key factors are uniformly valued to generate 125 groups of samples for functional relationship fitting, and the functional relationship formula is obtained:

[0136]

[0137] Then the coefficient of determination R 2 (also known as goodness of fit) to evaluate the fitting effect, R 2 The expression is

[0138] Among them, SST is the total sum of squares, SSR is the regression sum of squares, and SSE is the residual sum of squares. The expression is as follows:

[0139]

[0140] Where: y i is the experimental value, is the average value of the experimental values, is the regression value.

[0141] Coefficient of determination R in goodness of fit 2 It is 0.915, indicating that the model explains about 91.5% of the variation in the response variable, and the fitting effect is ideal.

[0142] As built system Figure 5 The control parameters of the system are shown in Table 2. It is known that m = 2, X2 = 0.05 and K p_PLL =41rad / (kV·s), and these parameters are substituted into formula (8) to fit the difference between electromechanical and electromagnetic simulation ΔU r1 =-0.0110pu, and the system simulates and finds that the difference between electromechanical and electromagnetic is ΔU r2 =-0.0150pu, which is close to and lower than the calculated result, and meets the requirement of conservatism of the calculated result.

[0143] Table 2 System control parameters

[0144]

[0145] Therefore, the present invention proposes a method for calculating temporary overvoltage of a new energy direct current transmission system. Based on the Sobol global sensitivity analysis method, the influencing parameters of the overvoltage peak of the new energy direct current transmission system in the electromagnetic transient simulation are screened to determine the key influencing factors; according to the value range of the key influencing factors and the preset constraints, a sample data set consisting of multiple groups of sample data of the key influencing factors and the temporary overvoltage peak of each group of data is determined; the sample data set is fitted by the ridge regression method of QR decomposition to obtain the fitting relationship between the key influencing factors and the transient overvoltage peak; the fitting relationship is used to calculate the simulated transient overvoltage peak of the new energy alternating current transmission system according to the simulated key influencing factor values ​​of the new energy direct current transmission system for analyzing the safety of the power grid and ensuring the stable operation of the new energy direct current transmission system.

[0146] Exemplary Devices

[0147] Figure 6 FIG. 1 is a schematic diagram of a temporary overvoltage calculation device for a new energy DC transmission system provided by an exemplary embodiment of the present invention. Figure 6 As shown, the device 600 includes:

[0148] A screening module 610 is used to screen the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation based on the Sobol global sensitivity analysis method to determine the key influencing factors;

[0149] A determination module 620, for determining a plurality of groups of sample data of key influencing factors and a sample data set consisting of a temporary overvoltage peak value of each group of data according to a value range of the key influencing factors and preset constraints;

[0150] A fitting module 630 is used to fit the sample data set using a ridge regression method of QR decomposition to obtain a fitting relationship between key influencing factors and transient overvoltage peak values;

[0151] The calculation module 640 is used to calculate the simulated transient overvoltage peak value of the new energy AC transmission system according to the simulated key influencing factor values ​​of the new energy DC transmission system by using a fitting relationship.

[0152] Optionally, the screening module 610 includes:

[0153] A determination submodule is used to determine the value range of the influencing parameter;

[0154] The mapping submodule is used to map the value range to the preset value range.

[0155] The generation submodule is used to use the Sobol sequence generator to randomly generate 2N quasi-random sample points according to the number of sampling samples N and the number of image parameters n;

[0156] The submodule is used to form the basis matrix A from the first N sample points N×n , the last N sample points form the matrix B N×n , and based on the base matrix A, repeatedly change i from 1 to n, replace the value of the i-th column with the value of the i-th column in the matrix B, and obtain n difference matrices AB i ;

[0157] The simulation submodule is used to simulate the basis matrix A using the electromagnetic model. N×n , Matrix B N×n And n difference matrices AB i Perform simulation calculations to obtain the first matrix, the second matrix and the third matrix of the temporary overvoltage peak value of the corresponding new energy direct current transmission system;

[0158] The calculation submodule is used to calculate the N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, and calculate the influence degree of each influencing parameter;

[0159] A submodule is selected to arrange the influence degrees of all influencing parameters in descending order, and the influencing parameters whose image degrees exceed a preset threshold are selected as key influencing factors.

[0160] Optionally, the computing submodule includes:

[0161] The first calculation unit is used to calculate the N×n and the first matrix calculates the expected value;

[0162] A second calculation unit, used for calculating the output total variance according to the first matrix and the expected value;

[0163] A third calculation unit is used to calculate the first-order sensitivity index of each influencing parameter and the total effect sensitivity index according to the expected value, the output total variance, the first matrix, the second matrix and the third matrix;

[0164] The determination unit is used to determine the influence degree of each influencing parameter according to the first-order sensitivity index and the total effect sensitivity index of each influencing parameter.

[0165] Optionally, the expected value E[Y] is calculated as:

[0166]

[0167] The calculation formula for the output total variance Var(Y) is:

[0168]

[0169] Where Y(A) is the first matrix; N is the number of samples.

[0170] Optionally, the first-order sensitivity index S i and the total effect sensitivity index S Ti The calculation formula is:

[0171]

[0172] In the formula, Y(A) n is the output corresponding to the nth sample of the basis matrix A, Y(B) n is the output corresponding to the nth sample of matrix B, Y(AB i ) n is the difference matrix AB i The output corresponding to the nth sample.

[0173] Optionally, the preset constraints are: the electrical distance Z1 from the new energy to the DC converter station is the maximum, Z1|=0.2pu, and the proportion of new energy η=0.9.

[0174] Optionally, the objective function of the ridge regression method of QR decomposition is:

[0175]

[0176] Where Q and R are two matrices of QR decomposition, Y is the overvoltage peak difference vector, C is the unknown quantity to be fitted, and λ is the regularization strength parameter.

[0177] Optionally, the expression of the fitted relationship is:

[0178]

[0179] In the formula, X / R is the impedance ratio, SCR is the short circuit ratio, K p_PLLis the PLL control parameter, ΔU r Temporary overvoltage peak.

[0180] Exemplary Electronic Devices

[0181] Figure 7 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 7 As shown, the electronic device 70 includes one or more processors 71 and a memory 72 .

[0182] The processor 71 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0183] The memory 72 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 71 may run the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may also include: an input device 73 and an output device 74, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0184] In addition, the input device 73 may also include, for example, a keyboard, a mouse, and the like.

[0185] The output device 74 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0186] Of course, to simplify, Figure 7 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0187] Exemplary computer program products and computer-readable storage media

[0188] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above-mentioned "Exemplary Method" section of this specification.

[0189] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0190] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0191] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0192] The basic principle of the present invention is described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. must be possessed by each embodiment of the present invention. In addition, the specific details disclosed above are only for the purpose of illustration and facilitation of understanding, rather than limitation, and the above details do not limit the present invention to being implemented by adopting the above specific details.

[0193] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0194] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0195] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware or any combination of software, hardware, firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present invention are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0196] It should also be noted that in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but in accordance with the widest range consistent with the principles and novel features disclosed here.

[0197] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for calculating temporary overvoltage of a new energy direct current transmission system, characterized in that: include: Based on the Sobol global sensitivity analysis method, the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation are screened to determine the key influencing factors; According to the value range of the key influencing factor and the preset constraint conditions, determine a plurality of groups of sample data of the key influencing factor and a sample data set consisting of a temporary overvoltage peak value of each group of data; The sample data set is fitted using a ridge regression method of QR decomposition to obtain a fitting relationship between the key influencing factors and the transient overvoltage peak value; The fitting relationship is used to calculate the simulated transient overvoltage peak value of the new energy AC transmission system according to the simulated key influencing factor values ​​of the new energy DC transmission system.

2. The method according to claim 1, characterized in that Based on the Sobol global sensitivity analysis method, the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation are screened and the key influencing factors are determined, including: Determining a value range of the influencing parameter; Mapping the value range to a preset value range, Using a Sobol sequence generator, 2N quasi-random sample points are randomly generated according to the number of sampling samples N and the number of image parameters n; The first N sample points form the basis matrix A N×n , the last N sample points form the matrix B N×n , and based on the base matrix A, repeatedly change i from 1 to n, replace the value of the i-th column with the value of the i-th column in the matrix B, and obtain n difference matrices AB i ; The electromagnetic model is used to analyze the basis matrix A N×n , Matrix B N×n And n difference matrices AB i Perform simulation calculations to obtain the first matrix, the second matrix and the third matrix of the temporary overvoltage peak value of the corresponding new energy direct current transmission system; According to the basis matrix A N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, and calculating the influence degree of each influencing parameter; The influence degrees of all influencing parameters are arranged in descending order, and the influencing parameters whose image degrees exceed a preset threshold are selected as the key influencing factors.

3. The method according to claim 2, characterized in that According to the basis matrix A N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, calculating the influence degree of each influencing parameter, including: According to the basis matrix A N×n and calculating the expected value of the first matrix; Calculate the output total variance according to the first matrix and the expected value; Calculate the first-order sensitivity index of each influencing parameter and the total effect sensitivity index according to the expected value, the output total variance, the first matrix, the second matrix and the third matrix; The influence degree of each influencing parameter is determined according to the first-order sensitivity index of each influencing parameter and the total effect sensitivity index.

4. The method according to claim 3, characterized in that The calculation formula of the expected value E[Y] is: The calculation formula of the output total variance Var(Y) is: Where Y(A) is the first matrix; N is the number of samples.

5. The method according to claim 4, characterized in that The first-order sensitivity index S i And the total effect sensitivity index S Ti The calculation formula is: In the formula, Y(A) n is the output corresponding to the nth sample of the basis matrix A, Y(B) n is the output corresponding to the nth sample of matrix B, Y(AB i ) n It is the output corresponding to the nth sample of the difference matrix ABi.

6. The method according to claim 1, characterized in that The preset constraints are: the electrical distance Z1 from the new energy to the DC converter station is the largest, Z1|=0.2pu, and the proportion of new energy η=0.

9.

7. The method according to claim 1, characterized in that The objective function of the ridge regression method of QR decomposition is: Where Q and R are two matrices of QR decomposition, Y is the overvoltage peak difference vector, C is the unknown quantity to be fitted, and λ is the regularization strength parameter.

8. The method according to claim 1, characterized in that The expression of the fitting relationship is: In the formula, X / R is the impedance ratio, SCR is the short circuit ratio, K p_PLL is the PLL control parameter, ΔU r Temporary overvoltage peak.

9. A temporary overvoltage calculation device for a new energy DC transmission system, characterized in that: include: The screening module is used to screen the influencing parameters of the overvoltage peak of the new energy DC transmission system in the electromagnetic transient simulation based on the Sobol global sensitivity analysis method to determine the key influencing factors; A determination module, used to determine a plurality of groups of sample data of the key influencing factors and a sample data set consisting of a temporary overvoltage peak value of each group of data according to a value range of the key influencing factors and preset constraints; A fitting module, used for fitting the sample data set by using a ridge regression method of QR decomposition to obtain a fitting relationship between the key influencing factors and the transient overvoltage peak value; The calculation module is used to calculate the simulated transient overvoltage peak value of the new energy AC transmission system according to the simulated key influencing factor values ​​of the new energy DC transmission system by using the fitting relationship.

10. The device according to claim 9, characterized in that Screening modules include: A determination submodule, used to determine the value range of the influencing parameter; A mapping submodule, used to map the value range to a preset value range, A generating submodule, used for using a Sobol sequence generator to randomly generate 2N quasi-random sample points according to the number of sampling samples N and the number of image parameters n; The submodule is used to form the basis matrix A from the first N sample points N×n , the last N sample points form the matrix B N×n , and based on the base matrix A, repeatedly change i from 1 to n, replace the value of the i-th column with the value of the i-th column in the matrix B, and obtain n difference matrices AB i ; The simulation submodule is used to use the electromagnetic model to simulate the basis matrix A N×n , Matrix B N×n And n difference matrices AB i Perform simulation calculations to obtain the first matrix, the second matrix and the third matrix of the temporary overvoltage peak value of the corresponding new energy direct current transmission system; A calculation submodule is used to calculate the N×n , Matrix B N×n , n difference matrices AB i , the first matrix, the second matrix and the third matrix, and calculating the influence degree of each influencing parameter; The selection submodule is used to arrange the influence degrees of all influencing parameters in descending order, and select the influencing parameters whose image degrees exceed a preset threshold as the key influencing factors.

11. The device according to claim 10, characterized in that Computing submodule, including: The first calculation unit is used to calculate the basis matrix A according to the basis matrix A. N×n and calculating the expected value of the first matrix; A second calculation unit, used for calculating an output total variance according to the first matrix and the expected value; A third calculation unit, used for calculating a first-order sensitivity index of each influencing parameter and a total effect sensitivity index according to the expected value, the output total variance, the first matrix, the second matrix and the third matrix; The determination unit is used to determine the influence degree of each influencing parameter according to the first-order sensitivity index and the total effect sensitivity index of each influencing parameter.

12. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 8.

13. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 8.

Images