Power distribution network line parameter automatic identification method based on augmented state estimation
By using the augmented state estimation method and the residual information of conductance, susceptance and current amplitude, the parameters of the distribution network line are iteratively corrected, which solves the parameter drift problem caused by environmental and physical factors and achieves fast and accurate parameter identification.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY
- Filing Date
- 2026-04-13
- Publication Date
- 2026-05-12
AI Technical Summary
Over long-term operation, the parameters of power distribution lines become inaccurate due to changes in environmental and physical factors, and existing technologies are unable to effectively correct them.
An augmented state estimation-based method is adopted. By constructing an augmented state vector and a Jacobian matrix, and utilizing the residual information of conductance, susceptance, active power, reactive power, and current amplitude, the line parameters are iteratively corrected to improve parameter accuracy.
It enables rapid and accurate identification of line resistance, reactance, and susceptance even with small voltage phase angle differences, improving the accuracy and robustness of parameters and solving the problem of parameter drift.
Smart Images
Figure CN122019947A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power distribution network technology, specifically to an automatic identification method for power distribution network line parameters based on augmented state estimation. Background Technology
[0002] A distribution network refers to a power grid that receives electrical energy from the transmission network or regional power plants and distributes it locally or tiered according to voltage to various users through distribution facilities. A distribution network consists of lines (usually overhead or underground), cables, poles, distribution transformers, disconnect switches, reactive power compensators, and some ancillary facilities. Distribution lines are the power lines or circuits that transmit electricity from substations to homes, businesses, and other buildings. They are an important component of the power grid because they transmit electricity at a lower voltage than long-distance transmission lines.
[0003] The resistance, reactance, and other parameters of distribution network lines are the only language for quantifying and mapping the electrical characteristics (heating, magnetic field, electric field effects) of physical entities into digital systems. Therefore, distribution network line parameters (mainly including resistance, reactance, and susceptance) are the cornerstone of constructing a distribution network physical model.
[0004] However, the parameters of power distribution lines usually rely solely on the factory-specified data. These data may drift due to environmental factors such as temperature, aging, or corrosion during long-term operation, resulting in inaccurate parameters. Summary of the Invention
[0005] To address the technical problem of potentially inaccurate determination of distribution network line parameters, this invention provides an automatic identification method for distribution network line parameters based on augmented state estimation. This method corrects line parameters when solving for the operating state of the power grid, thereby obtaining the true parameters after changes due to environmental or physical factors, thus improving the accuracy of the parameters.
[0006] The technical solution adopted in this invention is: an automatic identification method for distribution network line parameters based on augmented state estimation, which includes: obtaining a parameter including a state vector. x s and preset line parameter vector x p augmented state vector x The state vector x s Includes: voltage amplitude subvector V and voltage phase angle sub-vector i Voltage amplitude subvector V The i The dimension is the first i Voltage amplitude output by each node, voltage phase angle sub-vector i The i The dimension is the first iThe voltage phase angle output by each node; the line parameter vector includes: resistor vector. R Electron vector X and electron susceptor vector B resistance vector R Electron vector X and electron susceptor vector B The i All dimensions are related to the first i The node and the first i The physical parameters of the line between +1 nodes are related. i Represent the index; construct the nonlinear measurement function, and based on the nonlinear measurement function and the state vector... x s and line parameter vector x p Calculate the estimated conductance / susceptance values for each line and the estimated active power / reactive power / current amplitude values for each node; obtain the measured conductance / susceptance values for each line and the measured active power / reactive power / current amplitude values for each node; calculate the conductance / susceptance residuals for each line and the active power / reactive power / current amplitude residuals for each node; construct the augmented Jacobian matrix; calculate the correction vector based on the conductance / susceptance residuals for each line, the active power / reactive power / current amplitude residuals for each node, and the augmented Jacobian matrix; and apply the correction vector to the augmented state vector. x Make corrections and iterate until the result converges; then convert the converged augmented state vector. x Output.
[0007] Preferably, the resistive sub-vector R The i The dimension is the first i The node and the first i +1 node line resistance, the reactance subvector X The i The dimension is the first i The node and the first i +1 node line reactance, the susceptance subvector B The i The dimension is the first i The node and the first i +1 ampere between nodes.
[0008] Preferably, the nonlinear measurement function includes an admittance parameter conversion function, an active power measurement function, a reactive power measurement function, and a current amplitude measurement function.
[0009] Preferably, calculating the conductance / susceptance estimate of each line includes: calculating the conductance / susceptance estimate of each line according to the admittance parameter transformation function, wherein the calculation of the first... i The node and the firsti The formula for estimating the conductance / susceptance of the line between +1 nodes is: .
[0010] in, R i For the resistive vector R The i One dimension, X i The reactive vector X The i The dimension, the first i The node and the first i +1 node connection, g i This is an estimate of the conductivity. b i This is an estimated value for susceptance.
[0011] Preferably, calculating the estimated active power / reactive power of each node includes: calculating the estimated active power of each node based on the active power measurement function, wherein the calculation of the first... i The formula for estimating the active power of each node is: .
[0012] in, P mean ( i ) is the first i The estimated active power of each node. V i For the first i The voltage amplitude at each node, V i+1 For the first i +1 node voltage amplitude, i i For the first i The voltage phase angle of each node, i i+1 For the first i +1 node voltage phase angle, N The number of all nodes; calculate the estimated reactive power value of each node according to the reactive power measurement function, where the calculation of the first... i The formula for estimating the reactive power of each node is: .
[0013] in, Q mean ( i ) is the first i The estimated reactive power of each node.
[0014] Preferably, calculating the estimated current amplitude of each node includes: calculating the estimated current amplitude of each node based on the current amplitude measurement function, wherein the calculation of the first... i The formula for estimating the current magnitude at each node is: .
[0015] in, I ( i ) is the first i Estimated current amplitude at each node.
[0016] Preferably, calculating the residuals of conductance / susceptance and the residuals of active power / reactive power / current amplitude includes: calculating the difference between the measured value of conductance and the estimated value of conductance, denoted as the conductance residual; calculating the difference between the measured value of susceptance and the estimated value of susceptance, denoted as the susceptance residual; calculating the difference between the measured value of reactive power and the estimated value of reactive power, denoted as the reactive power residual; calculating the difference between the measured value of active power and the estimated value of active power, denoted as the active power residual; and calculating the difference between the measured value of current amplitude and the estimated value of current amplitude, denoted as the current amplitude residual.
[0017] Preferably, calculate the first k The correction vector in the nth iteration includes: (in the...) k In the next iteration, the residual vector Δ is constructed. z ( k ), of which k The residual vector Δ in the next iteration z ( k )satisfy: Conductivity residual subvector The i-th dimension is the i The node and the first i +1 nodes' conductance residuals, susceptance residual subvectors The i The dimension is the first i The node and the first i The susceptance residual of the line between +1 nodes, and the active power residual subvector. The i The dimension is the first i Active power residuals and reactive power residual subvectors at each node The i The dimension is the first i The reactive power residuals and current amplitude residual subvectors at each node The i The dimension is the first i The residual current amplitude at the nth node; calculate the residual current amplitude at the nth node. k The correction vector Δ in the next iteration x ( k The calculation formula is as follows: .
[0018] in, W The preset weight matrix, H k For the first k The augmented Jacobian matrix in the next iteration.
[0019] Preferably, constructing the augmented Jacobian matrix includes: constructing the variables to be determined. and measurement vector Among them, the active power sub-vector P The i The dimension is the first i Active power and reactive power subvectors of each node Q The i The dimension is the first i Reactive power and current amplitude subvectors at each node I The i The dimension is the first i The current amplitude at each node; construct the augmented Jacobian matrix, wherein the augmented Jacobian matrix... H satisfy: .
[0020] in, This is the partial derivative of active power with respect to the voltage phase angle. This is the partial derivative of active power with respect to voltage amplitude. This is the partial derivative of the active power with respect to the resistance. This is the partial derivative of active power with respect to reactance; This is the partial derivative of reactive power with respect to the voltage phase angle. This is the partial derivative of reactive power with respect to voltage amplitude. This is the partial derivative of reactive power with respect to resistance. This is the partial derivative of reactive power with respect to reactance; This is the partial derivative of the current amplitude with respect to the voltage phase angle. This is the partial derivative of the current amplitude with respect to the voltage amplitude. The partial derivative of the current amplitude with respect to the resistance is given. This is the partial derivative of the current amplitude with respect to the reactance.
[0021] Preferably, the convergence of the result is determined in response to the magnitude of the correction vector being less than a preset threshold or the number of iterations reaching a preset value.
[0022] The beneficial effects of this invention are as follows: This invention employs an augmented state estimation method, introducing the resistance, reactance, and susceptance of the line as state variables to be solved, constructing a unified state vector that includes voltage state and branch parameters. When solving for the power grid operating state, this invention corrects the line parameters, thereby obtaining the true parameters after changes due to environmental or physical factors, thus improving parameter accuracy.
[0023] This invention constructs an augmented Jacobian matrix, in which partial derivative terms precisely establish the relationship between measurement residuals and line parameter errors. By calculating and iteratively updating the correction vector, even when the voltage phase angle difference is small, leading to a decrease in the sensitivity of the power equation, the effective gradient information provided by the current amplitude can still be used to accelerate the convergence process of resistance and reactance, achieving rapid and accurate parameter identification. Attached Figure Description
[0024] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein: Figure 1 This is a schematic flowchart illustrating the steps of an automatic identification method for distribution network line parameters based on augmented state estimation according to an embodiment of the present invention. Detailed Implementation
[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0026] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
[0027] Figure 1 This is a schematic flowchart illustrating the steps of an automatic identification method for distribution network line parameters based on augmented state estimation according to an embodiment of the present invention.
[0028] like Figure 1 As shown, an automatic identification method for distribution network line parameters based on augmented state estimation includes steps S1 to S6.
[0029] Step S1: Obtain the state vector and the preset line parameter vector.
[0030] Wherein, the state vector x s Includes: voltage amplitude subvector Vand voltage phase angle sub-vector i Voltage amplitude subvector V The i The dimension is the first i Voltage amplitude output by each node, voltage phase angle sub-vector i The i The dimension is the first i The voltage phase angle output by each node; the line parameter vector includes: resistor vector. R Electron vector X and electron susceptor vector B resistance vector R Electron vector X and electron susceptor vector B The i All dimensions are related to the first i The node and the first i The physical parameters of the line between +1 nodes are related. i Represents an index.
[0031] It should be noted that in actual power distribution network operation, line parameters may change, and there may be deviations in topology information. This invention introduces the line parameters as state variables to be solved, and through augmented state estimation, enables subsequent nonlinear estimation to correct the line parameters while solving for the power grid operating state, thereby obtaining more accurate line parameters.
[0032] In one embodiment, the resistive subvector R The i The dimension is the first i The node and the first i +1 node line resistance, the reactance subvector X The i The dimension is the first i The node and the first i +1 node line reactance, the susceptance subvector B The i The dimension is the first i The node and the first i +1 ampere between nodes.
[0033] It should be noted that the resistance of a line mainly depends on the material properties of the conductor (such as aluminum or copper), its cross-sectional area, and the line length, reflecting the line's ability to dissipate active power; the reactance of the line reflects its resistance to changes in current and its ability to exchange magnetic field energy; and the susceptance of the line reflects its charging power characteristics. These parameters typically have factory-specified data, i.e., theoretical design values, during the initial construction of the distribution network. However, with long-term operation of the power grid, these parameters will drift due to the influence of multiple environmental and physical factors (such as temperature effects, mechanical deformation, and aging and corrosion).
[0034] Step S2: Construct a nonlinear measurement function and calculate the estimated values of conductance / susceptance for each line and the estimated values of active power / reactive power / current amplitude for each node.
[0035] In one embodiment, the nonlinear measurement function includes an admittance parameter conversion function, an active power measurement function, a reactive power measurement function, and a current amplitude measurement function.
[0036] In one embodiment, calculating the conductance / susceptance estimate of each line includes: calculating the conductance / susceptance estimate of each line according to the admittance parameter transformation function, wherein the calculation of the first... i The node and the first i The formula for estimating the conductance / susceptance of the line between +1 nodes is: .
[0037] in, R i For the resistive vector R The i One dimension, X i The reactive vector X The i The dimension, the first i The node and the first i +1 node connection, g i This is an estimate of the conductivity. b i This is an estimated value for susceptance.
[0038] It should be noted that the admittance parameter transformation function (i.e., the transformation formula) is designed to fit the standard mathematical model for power flow calculation and state estimation in power systems. The admittance parameter transformation function maps the physical parameters to be identified to the intermediate variables required by the nonlinear measurement function.
[0039] In one embodiment, calculating the active power / reactive power estimate for each node includes: calculating the active power estimate for each node based on the active power measurement function, wherein the calculation of the first... i The formula for estimating the active power of each node is: .
[0040] in, P mean ( i ) is the first i The estimated active power of each node. V i For the first i The voltage amplitude at each node,V i+1 For the first i +1 node voltage amplitude, i i For the first i The voltage phase angle of each node, i i+1 For the first i +1 node voltage phase angle, N The number of all nodes; calculate the estimated reactive power value of each node according to the reactive power measurement function, where the calculation of the first... i The formula for estimating the reactive power of each node is: .
[0041] in, Q mean ( i ) is the first i The estimated reactive power of each node.
[0042] It should be noted that this invention relates to the construction of active power measurement functions and reactive power measurement functions based on Kirchhoff's current law.
[0043] item (In the active power measurement function) or (In reactive power measurement functions) it usually represents the parallel line loss or charging power contribution of the node itself.
[0044] item This describes the active power transfer between node i and its neighboring node i+1. (Product of voltage magnitudes) The upper limit of transmission capacity has been determined, while the phase difference... The distribution ratio of active power to reactive power was determined.
[0045] item This describes the reactive power transfer between node i and its neighboring node i+1. (The product of voltage magnitudes) The upper limit of transmission capacity has been determined, while the phase difference... The distribution ratio of active power to reactive power was determined.
[0046] These two functions act as a way to map estimated internal states (voltage, resistance, reactance, etc.) to measurable external properties (power).
[0047] In one embodiment, calculating the estimated current amplitude of each node includes: calculating the estimated current amplitude of each node based on the current amplitude measurement function, wherein the calculation of the first... i The formula for estimating the current magnitude at each node is: .
[0048] in, I ( i ) is the first i Estimated current amplitude at each node.
[0049] It should be noted that in traditional methods that only use active power and reactive power as measurements, especially when the R / X ratio of the distribution network is high or under light load, problems such as non-uniqueness of the solution are often encountered.
[0050] This invention determines the current amplitude measurement function based on the complex form of Ohm's law for line current. This function has the functions of regularization and enhanced observability. Furthermore, the current is very sensitive to changes in line impedance. Introducing the current residual can accelerate the convergence process of resistance and reactance. In particular, when the voltage phase angle difference is very small, the sensitivity of the power equation to the parameters may decrease, while the current amplitude can still provide effective gradient information.
[0051] Step S3: Obtain the measured values of the line's conductance / susceptance, and obtain the measured values of the active power / reactive power / current amplitude at each node.
[0052] It should be noted that the measured values are usually the actual operating data obtained at a certain moment by physical sensors and data acquisition terminals installed at various nodes or lines of the power distribution network.
[0053] Step S4: Calculate the residual conductance / susceptance of each line and the residual active power / reactive power / current amplitude of each node.
[0054] In one embodiment, calculating the conductance / susceptance residuals and the active power / reactive power / current amplitude residuals includes: calculating the difference between the measured conductance value and the estimated conductance value, denoted as the conductance residual; calculating the difference between the measured susceptance value and the estimated susceptance value, denoted as the susceptance residual; calculating the difference between the measured reactive power value and the estimated reactive power value, denoted as the reactive power residual; calculating the difference between the measured active power value and the estimated active power value, denoted as the active power residual; and calculating the difference between the measured current amplitude value and the estimated current amplitude value, denoted as the current amplitude residual.
[0055] Step S5: Construct the augmented Jacobian matrix, calculate the correction vector, and correct the line parameter vector using the correction vector. Iterate until the result converges.
[0056] In one embodiment, the calculation of the first k The correction vector in the nth iteration includes: (in the...) k In the next iteration, the residual vector Δ is constructed. z ( k ), of which k The residual vector Δ in the next iteration z ( k)satisfy: Conductivity residual subvector The i-th dimension is the i The node and the first i +1 nodes' conductance residuals, susceptance residual subvectors The i The dimension is the first i The node and the first i The susceptance residual of the line between +1 nodes, and the active power residual subvector. The i The dimension is the first i Active power residuals and reactive power residual subvectors at each node The i The dimension is the first i The reactive power residuals and current amplitude residual subvectors at each node The i The dimension is the first i The residual current amplitude at the nth node; calculate the residual current amplitude at the nth node. k The correction vector Δ in the next iteration x ( k The calculation formula is as follows: ; in, W The preset weight matrix, H k For the first k The augmented Jacobian matrix in the next iteration.
[0057] It should be noted that the residual vector Δ z ( k ) represents the current number k The smaller the deviation between the estimated and actual measured values of the node parameters in each iteration, the closer the line parameters are to the true values in this iteration. Augmented Jacobian matrix. H k It is a sensitivity matrix that quantifies how small perturbations in state variables and parameters cause changes in measurement values.
[0058] This invention obtains the optimal correction step size of the state vector, i.e., the residual vector Δ, through the least squares method. z ( k ).
[0059] In one embodiment, constructing the augmented Jacobian matrix includes: constructing the variables to be determined. and measurement vector Among them, the active power sub-vector P The i The dimension is the first iActive power and reactive power subvectors of each node Q The i The dimension is the first i Reactive power and current amplitude subvectors at each node I The i The dimension is the first i The current amplitude at each node; construct the augmented Jacobian matrix, wherein the augmented Jacobian matrix... H satisfy: ; in, This is the partial derivative of active power with respect to the voltage phase angle. This is the partial derivative of active power with respect to voltage amplitude. This is the partial derivative of the active power with respect to the resistance. This is the partial derivative of active power with respect to reactance; This is the partial derivative of reactive power with respect to the voltage phase angle. This is the partial derivative of reactive power with respect to voltage amplitude. This is the partial derivative of reactive power with respect to resistance. This is the partial derivative of reactive power with respect to reactance; This is the partial derivative of the current amplitude with respect to the voltage phase angle. This is the partial derivative of the current amplitude with respect to the voltage amplitude. The partial derivative of the current amplitude with respect to the resistance is given. This is the partial derivative of the current amplitude with respect to the reactance.
[0060] It should be noted that the columns of the augmented Jacobian matrix correspond to the variables to be determined. The row-corresponding measurement vectors of the augmented Jacobian matrix The partial derivative terms in the augmented Jacobian matrix establish the relationship between measurement residuals and line parameter errors, such as the partial derivatives of current amplitude and resistance. This indicates the sensitivity of the current amplitude to changes in resistance.
[0061] Step S6: Output the augmented state vector after the result has converged.
[0062] In one embodiment, the convergence of the result is determined in response to the magnitude of the correction vector being less than a preset threshold or the number of iterations reaching a preset value.
[0063] It should be noted that when the correction vector is less than the threshold, it indicates that the current estimated value is already near the extreme point of the objective function, and the parameter correction brought by further iteration is small, so the result is considered to have converged. At this point, the optimal augmented state vector that simultaneously satisfies the constraints of active power, reactive power, and current amplitude is obtained. After outputting the optimal augmented state vector, relevant personnel can obtain the actual parameters of each branch by referring to the optimal augmented state vector.
[0064] In summary, this invention provides an automatic identification method for distribution network line parameters based on augmented state estimation. By constructing a unified state vector containing voltage state and branch parameters, and utilizing a weighted least squares algorithm to process multi-source measurement data, it identifies the resistance, reactance, and susceptance of distribution network lines. This invention introduces current amplitude measurement and an augmented Jacobian matrix, effectively solving the algorithm convergence difficulties caused by short lines and high R / X ratios in distribution networks, thus improving the robustness of the identification.
[0065] In the description of this specification, "multiple" or "several" means at least two, such as two, three or more, unless otherwise explicitly specified.
[0066] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.
Claims
1. A method for automatic identification of distribution network line parameters based on augmented state estimation, characterized in that, include: Obtain the state vector x s and preset line parameter vector x p augmented state vector x ; The state vector x s Includes: voltage amplitude subvector V and voltage phase angle sub-vector θ Voltage amplitude subvector V The i The dimension is the first i Voltage amplitude output by each node, voltage phase angle sub-vector θ The i The dimension is the first i The voltage phase angle output by each node; the line parameter vector includes: resistor vector. R Electron vector X and electron susceptor vector B resistance vector R Electron vector X and electron susceptor vector B The i All dimensions are related to the first i The node and the first i The physical parameters of the line between +1 nodes are related. i Represents an index; Construct a nonlinear measurement function, and based on the nonlinear measurement function and the state vector... x s and line parameter vector x p Calculate the estimated conductance / susceptance values for each line and the estimated active power / reactive power / current amplitude values for each node; obtain the measured conductance / susceptance values for each line and the measured active power / reactive power / current amplitude values for each node; calculate the residual conductance / susceptance values for each line and the residual active power / reactive power / current amplitude values for each node. Construct an augmented Jacobian matrix, calculate a correction vector based on the conductance / susceptance residuals of each line, the active power / reactive power / current amplitude residuals of each node, and the augmented Jacobian matrix, and then apply the correction vector to the augmented state vector. x Make corrections and iterate until the result converges; then convert the converged augmented state vector. x Output.
2. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 1, characterized in that, The resistive vector R The i The dimension is the first i The node and the first i +1 node line resistance, the reactance subvector X The i The dimension is the first i The node and the first i +1 node line reactance, the susceptance subvector B The i The dimension is the first i The node and the first i +1 ampere between nodes.
3. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 2, characterized in that, The nonlinear measurement functions include admittance parameter conversion functions, active power measurement functions, reactive power measurement functions, and current amplitude measurement functions.
4. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 3, characterized in that, The calculation of the conductance / susceptance estimates for each line includes: The conductance / susceptance estimates for each line are calculated based on the admittance parameter conversion function, wherein the calculation of the first... i The node and the first i The formula for estimating the conductance / susceptance of the line between +1 nodes is: ； in, R i For the resistive vector R The i One dimension, X i The reactive vector X The i One dimension, g i For the first i The node and the first i +1 estimated conductance of the line between nodes b i For the first i The node and the first i +1 estimated susceptance of the line between nodes.
5. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 4, characterized in that, The calculation of the estimated active power / reactive power at each node includes: The estimated active power value of each node is calculated based on the active power measurement function, wherein the calculation of the first node is performed. i The formula for estimating the active power of each node is: ； in, P mean ( i ) is the first i The estimated active power of each node. V i For the first i The voltage amplitude at each node, V i+1 For the first i +1 node voltage amplitude, θ i For the first i The voltage phase angle of each node, θ i+1 For the first i +1 node voltage phase angle, N The total number of nodes; The reactive power estimate of each node is calculated based on the aforementioned reactive power measurement function, wherein the calculation of the first... i The formula for estimating the reactive power of each node is: ； in, Q mean ( i ) is the first i The estimated reactive power of each node.
6. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 5, characterized in that, The calculation of the estimated current amplitude at each node includes: The estimated current amplitude of each node is calculated based on the current amplitude measurement function, wherein the calculation of the first... i The formula for estimating the current magnitude at each node is: ； in, I ( i ) is the first i Estimated current amplitude at each node.
7. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 1, characterized in that, The calculation of conductance / susceptance residuals and active power / reactive power / current amplitude residuals includes: The difference between the measured conductivity value and the estimated conductivity value is calculated and denoted as the conductivity residual. The difference between the measured susceptance and the estimated susceptance is calculated and denoted as the susceptance residual. The difference between the measured reactive power value and the estimated reactive power value is recorded as the reactive power residual. The difference between the measured active power value and the estimated active power value is calculated and denoted as the active power residual. The difference between the measured current amplitude and the estimated current amplitude is calculated and denoted as the current amplitude residual.
8. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 7, characterized in that, Calculate the first k The correction vector in the next iteration includes: In the k In the next iteration, the residual vector Δ is constructed. z ( k ), of which k The residual vector Δ in the next iteration z ( k )satisfy: Conductivity residual subvector The i-th dimension is the i The node and the first i +1 nodes' conductance residuals, susceptance residual subvectors The i The dimension is the first i The node and the first i The susceptance residual of the line between +1 nodes, and the active power residual subvector. The i The dimension is the first i Active power residuals and reactive power residual subvectors at each node The i The dimension is the first i The reactive power residuals and current amplitude residual subvectors at each node The i The dimension is the first i The residual current amplitude at each node; Calculate the first k The correction vector Δ in the next iteration x ( k The calculation formula is as follows: ； in, W For the preset weight matrix, H k For the first k The augmented Jacobian matrix in the next iteration.
9. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 8, characterized in that, Constructing the augmented Jacobian matrix includes: Construct the variable to be determined and measurement vector Among them, the active power sub-vector P The i The dimension is the first i Active power and reactive power subvectors of each node Q The i The dimension is the first i Reactive power and current amplitude subvectors at each node I The i The dimension is the first i The current amplitude at each node; Construct an augmented Jacobian matrix, wherein the augmented Jacobian matrix... H satisfy: ； in, This is the partial derivative of active power with respect to the voltage phase angle. This is the partial derivative of active power with respect to voltage amplitude. This is the partial derivative of the active power with respect to the resistance. This is the partial derivative of active power with respect to reactance; This is the partial derivative of reactive power with respect to the voltage phase angle. This is the partial derivative of reactive power with respect to voltage amplitude. This is the partial derivative of reactive power with respect to resistance. This is the partial derivative of reactive power with respect to reactance; This is the partial derivative of the current amplitude with respect to the voltage phase angle. This is the partial derivative of the current amplitude with respect to the voltage amplitude. The partial derivative of the current amplitude with respect to the resistance is given. This is the partial derivative of the current amplitude with respect to the reactance.
10. The method for automatic identification of distribution network line parameters based on augmented state estimation according to claim 1, characterized in that, The convergence of the result is determined when the magnitude of the correction vector is less than a preset threshold or the number of iterations reaches a preset value.