Three-phase four-wire low-voltage transformer area parameter identification method and system based on pressure drop equation

Abstract

The application discloses a three-phase four-wire low-voltage transformer area parameter identification method and system based on a voltage drop equation, and relates to the technical field of low-voltage power distribution networks.The application constructs an initial voltage and current phasor based on smart meter measurement data and superimposes noise to construct a nonlinear voltage drop equation; the nonlinear voltage drop equation is mapped to a three-dimensional real vector space through real linear projection functional mapping to construct a linear voltage drop model and obtain a node-to-node electrical parameter relationship; based on the relationship, an improved least square method combining column scale normalization and ridge regularization is used for impedance parameter estimation, and a Huber iterative reweighting mechanism is used for robust estimation; based on the converged line impedance parameters, power flow back calculation is performed, phase angle is iteratively corrected, and the linear voltage drop model construction and impedance parameter solving are repeatedly executed until the iteration stopping condition is met.The application realizes accurate identification of three-phase four-wire low-voltage transformer area line impedance parameters under low-cost conditions without synchronous phasor measurement devices.

Description

Technical Field

[0001] This invention relates to the field of low-voltage distribution network technology, specifically to a method and system for identifying parameters of three-phase four-wire low-voltage distribution areas based on voltage drop equations. Background Technology

[0002] Low-voltage distribution networks are the final link connecting distribution transformers and end users, characterized by a large number of nodes, complex line branches, strong load randomness, and prominent three-phase imbalance. Traditional methods of estimating line parameters based on drawings, conductor types, and line lengths are insufficient to reflect parameter deviations caused by line aging, changes in joint contact resistance, and differences between renovation construction and actual installation.

[0003] Meanwhile, line parameters are fundamental data for low-voltage distribution network status sensing, power flow calculation, line loss analysis, fault location, non-sudden fault early warning, and three-phase imbalance management. Inaccurate line parameters will affect subsequent voltage limit judgments, line loss allocation, fault section location, and operational optimization results. Especially in scenarios involving aging lines or poor contact, increased line impedance is often an early characteristic of fault development; therefore, parameter identification is not only a modeling problem but also has value for fault early warning.

[0004] The large-scale deployment of smart meters has provided new possibilities for parameter identification in low-voltage distribution networks. Smart meters can provide operational data such as voltage, current, active power, and reactive power on the user side. Compared with manual inspection and offline measurement, they have advantages such as wide coverage, low cost, and long-term continuous acquisition. However, due to limitations in the measurement accuracy, sampling period, and lack of phase angle information of smart meters, it is still difficult to directly solve line parameters based solely on conventional meter data. For example, conventional smart meters do not provide synchronous phase angle information for voltage and current. The phase angle needs to be indirectly calculated through the power factor angle. In scenarios with severe load fluctuations, power factor changes, or three-phase imbalance, the initial value of the phase angle based on the power factor angle assumption deviates from the actual value. This deviation will be directly coupled to the identification results of line impedance, leading to a systematic shift in parameter estimation.

[0005] To address this, the present invention proposes a method and system for identifying parameters of a three-phase four-wire low-voltage distribution area based on the voltage drop equation. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for identifying parameters of a three-phase four-wire low-voltage distribution area based on the voltage drop equation, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for parameter identification of three-phase four-wire low-voltage distribution areas based on voltage drop equations, comprising the following steps: The network topology information of the three-phase four-wire low-voltage distribution area to be identified and the measurement data of smart meters at each node are obtained. The smart meter measurement data includes at least the voltage amplitude, current amplitude, active power and reactive power of each phase at each node. Based on the network topology information, determine the line connection relationship between each node, construct the initial voltage phasor and initial current phasor corresponding to each node based on the active power and reactive power, and obtain the initial electrical quantities required for line parameter identification. Based on the line connection relationship, adjacent nodes with a common parent node are selected. Combined with the initial electrical quantities, a three-phase four-wire line voltage drop equation considering the influence of the neutral line is established. The line voltage drop equation is transformed according to the preset coordinate transformation rules to convert the complex domain line voltage drop relationship into the line voltage drop relationship in three-dimensional real space, and a line impedance parameter identification model is constructed. Based on the line impedance parameter identification model, the line impedance parameters are iteratively identified to obtain the current round of line impedance parameter estimation results. Based on the current round of line impedance parameter estimation results, perform three-phase four-wire low-voltage distribution area power flow back calculation to obtain the updated voltage phase angle and current phase angle of each node, and correct the initial electrical quantity according to the updated voltage phase angle and current phase angle to obtain the corrected electrical quantity corresponding to the next round of line impedance parameter identification. The corrected electrical quantity is re-input into the line impedance parameter identification model to identify the line impedance parameters, and a new round of line impedance parameter estimation results is obtained. Based on the line impedance parameter estimation results of the two adjacent rounds, it is determined whether the preset convergence condition is met. If the preset convergence condition is met, the final line impedance parameter identification result is output.

[0008] Furthermore, based on the active and reactive power, the initial voltage phasors and initial current phasors corresponding to each node are constructed to obtain the initial electrical quantities required for line parameter identification, specifically including: Calculate the power factor angle of each phase based on the active and reactive power of each phase at each node; Set the initial voltage phase angle of phase A to 0°, the initial voltage phase angle of phase B to 120° lags behind phase A, and the initial voltage phase angle of phase C to 120° lead phase A, and construct the initial voltage phasor of each phase at each node. The initial electrical quantities are obtained by constructing the initial current phasor of each phase at each node based on the current amplitude of each phase at each node, the corresponding power factor angle, and the initial voltage phasor of each phase, and by calculating the corresponding neutral line current phasor based on the three-phase initial current phasor.

[0009] Furthermore, it also includes applying relative Gaussian noise to the voltage amplitude, specifically as follows: in Indicator box At discrete time The measured voltage, Represents the relative noise standard deviation, taken as... , This represents a noise variable randomly drawn from a standard normal distribution.

[0010] Furthermore, based on the aforementioned line connection relationships, adjacent nodes with a common parent node are selected, and a voltage drop equation for a three-phase four-wire line, taking into account the influence of the neutral wire, is established in conjunction with the initial electrical quantities. Specifically, this includes: For two adjacent nodes with a common parent node, the parent node is used as a common reference node, and the voltage drop relationship of each phase conductor is established according to Kirchhoff's voltage law. Establish separate terms for the impedance voltage drop of each phase conductor and the impedance voltage drop of the neutral conductor; The voltage drop of each phase conductor impedance and the voltage drop of the neutral conductor together constitute the voltage drop equation for a three-phase four-wire system that takes into account the influence of the neutral conductor.

[0011] Furthermore, the line voltage drop equation is transformed according to a preset coordinate transformation rule, converting the complex domain line voltage drop relationship into a three-dimensional real space line voltage drop relationship, and constructing a line impedance parameter identification model, specifically including: Establish a linear projection mapping from complex phasor space to three-dimensional real space; Project the voltage phasor, current phasor, and impedance phasor in the line voltage drop equation along the reference directions of phase A, phase B, and phase C, respectively. The line voltage drop relationship in the complex domain is transformed into a linear constraint relationship in three-dimensional real space to construct a line impedance parameter identification model.

[0012] Furthermore, based on the aforementioned line impedance parameter identification model, the line impedance parameters are iteratively identified to obtain the current round of line impedance parameter estimation results, specifically including: The coefficient matrix corresponding to the line impedance parameter identification model is subjected to column scaling normalization. Construct an objective function containing ridge regularization terms based on the normalized coefficient matrix; The ridge regression method is used to solve for the initial estimates of the line impedance parameters; Calculate the prediction residuals corresponding to each sampling point based on the current estimated line impedance parameters, and calculate the residual scale based on the current round of prediction residuals; The Huber loss function is constructed based on the residual scale. The weights corresponding to each sampling point are updated using the iterative reweighted least squares method. The current round line impedance parameter estimation result is then recalculated based on the updated weights.

[0013] Furthermore, based on the current line impedance parameter estimation results, a three-phase four-wire low-voltage distribution area power flow back calculation is performed to obtain the updated voltage phase angle and current phase angle of each node, specifically including: A three-phase four-wire power flow calculation model is established based on the current line impedance parameter estimation results. Based on the three-phase four-wire power flow calculation model, power flow calculation is performed to obtain the updated voltage phase angle and current phase angle of each node; The voltage phasors and current phasors of each node are reconstructed based on the updated voltage phase angle and current phase angle.

[0014] Furthermore, the initial electrical quantities are corrected based on the updated voltage phase angle and current phase angle to obtain the corrected electrical quantities corresponding to the next round of line impedance parameter identification, specifically including: A damping update strategy is used to correct the voltage phase angle and current phase angle obtained from the current power flow recalculation. The voltage phase angle and current phase angle of the previous round are weighted and fused with those of the current round based on the preset damping factor; By updating the corresponding voltage phasors and current phasors using the fused voltage phase angle and current phase angle, the corrected electrical quantities corresponding to the next round of line impedance parameter identification are obtained.

[0015] Furthermore, the corrected electrical quantity is re-input into the line impedance parameter identification model to identify the line impedance parameters, obtaining a new round of line impedance parameter estimation results. The results of the two adjacent rounds of line impedance parameter estimation are then used to determine whether a preset convergence condition is met. If the preset convergence condition is met, the final line impedance parameter identification result is output, as follows: Calculate the parameter variation between the estimated impedance parameters of two adjacent circuits; The change in the parameter is compared with a preset convergence threshold. If the change in the parameter is less than the preset convergence threshold, or if the preset maximum number of iterations is reached, then the preset convergence condition is satisfied, and the final line impedance parameter identification result is output.

[0016] According to a second aspect of the present invention, the present invention provides a three-phase four-wire low-voltage distribution area parameter identification system based on voltage drop equations, for implementing the three-phase four-wire low-voltage distribution area parameter identification method based on voltage drop equations described in the first aspect, comprising: The data acquisition module is used to acquire the network topology information of the three-phase four-wire low-voltage distribution area to be identified and the smart meter measurement data of each node. The smart meter measurement data includes at least the voltage amplitude, current amplitude, active power and reactive power of each phase of each node. The initial electrical quantity calculation module is used to determine the line connection relationship between each node based on the network topology information, construct the initial voltage phasor and initial current phasor corresponding to each node based on the active power and reactive power, and obtain the initial electrical quantities required for line parameter identification. The model building module is used to select adjacent nodes with a common parent node according to the line connection relationship, establish a three-phase four-wire line voltage drop equation that takes into account the influence of the neutral line in combination with the initial electrical quantities, perform coordinate transformation on the line voltage drop equation according to the preset coordinate transformation rules, convert the line voltage drop relationship in the complex domain into the line voltage drop relationship in the three-dimensional real space, and build a line impedance parameter identification model. The iterative identification module is used to iteratively identify the line impedance parameters based on the line impedance parameter identification model to obtain the current round of line impedance parameter estimation results. The update and correction module is used to perform power flow back calculation of the three-phase four-wire low-voltage distribution area based on the current round line impedance parameter estimation results, obtain the updated voltage phase angle and current phase angle of each node, and correct the initial electrical quantity according to the updated voltage phase angle and current phase angle to obtain the corrected electrical quantity corresponding to the next round line impedance parameter identification. The result output module is used to re-input the corrected electrical quantity into the line impedance parameter identification model to identify the line impedance parameters, obtain a new round of line impedance parameter estimation results, and determine whether the preset convergence condition is met based on the line impedance parameter estimation results of the two adjacent rounds; if the preset convergence condition is met, the final line impedance parameter identification result is output.

[0017] According to a third aspect of the present invention, the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor. When the processor loads and executes the computer program, it employs the three-phase four-wire low-voltage distribution area parameter identification method based on the voltage drop equation described in the first aspect.

[0018] According to a fourth aspect of the present invention, the present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform a three-phase four-wire low-voltage distribution area parameter identification method based on voltage drop equations as described in the first aspect.

[0019] The present invention has at least the following beneficial effects: 1. This invention incorporates neutral line impedance into the modeling framework when establishing the voltage drop equation. Through the coupling relationship between neutral current and three-phase current, it comprehensively describes the electrical constraints of a three-phase four-wire network. This modeling method avoids structural modeling errors introduced by neglecting neutral current, ensuring that the parameter identification results accurately reflect the actual operating state of three-phase load imbalance in low-voltage distribution areas, and improving the fit between the identification model and the actual physical system.

[0020] 2. Measurement data from smart meters in low-voltage distribution networks contain inherent noise and occasional outliers. Ordinary least squares methods, when the coefficient matrix column scales differ significantly or exhibit ill-conditioned behavior, can easily amplify measurement noise into impedance parameter estimation. This invention introduces an improved least squares framework combining column scale normalization and ridge regularization in the solution process. Adaptive regularization coefficients suppress parameter oscillations when the matrix condition number is too large. Furthermore, a Huber iterative reweighting mechanism is employed to dynamically adjust weights based on the residuals of each sampling point, reducing the interference of outlier sampling points on parameter estimation. This dual robustness mechanism ensures that the identification method maintains the stability and consistency of parameter estimation even in the presence of measurement noise.

[0021] 3. Smart meters do not directly provide voltage and current phase angles. The initial phase angle value depends on the power factor angle assumption. This assumption deviates from the true value under load fluctuation scenarios. After completing one round of impedance identification, this invention uses the current impedance estimate to perform power flow back calculation to obtain phase angle information that is closer to the actual operating state. Furthermore, through a damping update strategy, the phase angle correction is smoothly absorbed round by round, avoiding the mutual amplification of phase angle error and impedance error in the closed-loop iteration. This iterative correction mechanism gradually approaches the true phase angle value under low-cost conditions without the need to add a synchronous phasor measurement device, thereby improving the identification accuracy of line impedance parameters.

[0022] 4. This invention superimposes relative Gaussian noise into voltage amplitude data to simulate actual measurement errors, and performs model training and parameter fitting in a noisy data environment. This noise injection strategy exposes the identification model to measurement disturbances during the training phase, enhancing the method's adaptability to fluctuations in actual field data quality and reducing the performance gap between the ideal simulation environment and the real measurement environment.

[0023] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the overall process of the method described in this invention. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Example 1: This embodiment, considering the three-phase imbalance problem and including the neutral wire, establishes a method for identifying line parameters in a three-phase four-wire low-voltage distribution network with a known topology. Since the information provided by smart meters is insufficient and the phase angle is unknown, Kirchhoff's voltage law equation is first established sequentially for the two meter boxes under ideal conditions. A linear voltage drop model is constructed to fit the impedance parameters as initial values ​​for the line impedance. Next, power flow iteration yields new voltage and current phase angles, forming new electrical quantities. Finally, the line impedance value is iteratively solved based on the linear voltage drop equation until convergence. Noise is added to simulate measurement errors and improve the robustness of the method.

[0028] Please see Figure 1 This invention provides a technical solution: a method for parameter identification of three-phase four-wire low-voltage distribution areas based on voltage drop equations, comprising the following steps: S1. Obtain the network topology information of the three-phase four-wire low-voltage distribution area to be identified and the smart meter measurement data of each node. The smart meter measurement data shall include at least the voltage amplitude, current amplitude, active power and reactive power of each phase of each node. right Phase meter box At discrete time The measurement data includes: voltage amplitude Current amplitude Meritorious / Ineffective ; S2. Determine the line connection relationships between nodes based on the network topology information. Construct the initial voltage phasor and initial current phasor for each node based on active power and reactive power to obtain the initial electrical quantities required for line parameter identification, as follows: S21. Calculate the power factor angle of each phase based on the active and reactive power of each phase at each node: (1) In the formula: for Phase power supply The power factor angle at that point, for Phase meter box Power factor angle at S22. Set the initial voltage phase angle of phase A to 0°, the initial voltage phase angle of phase B to 120° lag behind phase A, and the initial voltage phase angle of phase C to 120° lead phase A. Construct the initial voltage phasors for each phase at each node, as follows: Assume that the initial values ​​of the phase angles of the voltage phasors at all terminals of phase A are all The initial values ​​of the phase angles of the three-phase voltage phasors differ. Substituting into equation (1), the initial three-phase current phasors are calculated, and the corresponding neutral line current phasors are calculated based on the initial three-phase current phasors to obtain the initial electrical quantities, as follows: (2) In the formula, for Phase meter box The power factor angle at that point, These are the three-phase current vector values. This represents the neutral line current vector value. S23. Apply relative Gaussian noise to the voltage amplitude: (3) in Indicator box At discrete time The measured voltage, Represents the relative noise standard deviation, taken as... , This represents a noise variable randomly drawn from a standard normal distribution; S3. Based on the line connection relationship, select adjacent nodes with a common parent node, and establish a three-phase four-wire line voltage drop equation considering the influence of the neutral wire, combined with the initial electrical quantities. Perform coordinate transformation on the line voltage drop equation according to the preset coordinate transformation rules, converting the complex domain line voltage drop relationship into a three-dimensional real space line voltage drop relationship, and constructing a line impedance parameter identification model, specifically including: S31. For two adjacent nodes with a common parent node, using the parent node as a common reference node, establish the voltage drop relationship of each phase conductor according to Kirchhoff's voltage law, and establish the impedance voltage drop term of each phase conductor and the neutral line impedance voltage drop term respectively. Then, the impedance voltage drop of each phase conductor and the neutral line impedance voltage drop together constitute the voltage drop equation of a three-phase four-wire line considering the influence of the neutral line: Select two meter boxes under the same branch box. For the meter box and watch box If two meter boxes are connected in parallel and share a common parent node 0, then the nonlinear voltage drop equation considering the influence of the neutral line can be established as follows: (4) in, They represent the watch case. , watch box and the voltage value of the common parent node, box 0. These represent the meter box nodes respectively. , The vector value of a certain phase current, Representing nodes respectively of Phase impedance value, Representing nodes respectively The neutral line impedance value, where Represents resistance and reactance, respectively; S32. Perform coordinate transformation on the line voltage drop equation according to the preset coordinate transformation rules, converting the complex domain line voltage drop relationship into a three-dimensional real space line voltage drop relationship, and constructing a line impedance parameter identification model, specifically including: S32.1 Establish a linear projection mapping from complex phasor space to three-dimensional real space; In low-voltage distribution networks, due to the short lines and relatively small transmission power, the voltage phase angle difference between nodes is usually very small, therefore the transverse component of voltage drop... It can be ignored; Let there be a phasor space on the complex plane, and define a family of real linear projective functionals on it. : (5) in, In the formula For the product of complex numbers, The unit metric basis vectors for each phase projection direction; This functional maps the two-dimensional complex phasor space to a one-dimensional real eigenspace with normality preservation, forming a structure from... arrive Linear embedding: (6) This embedding represents each phasor as a triplet of instantaneous active components in a three-phase synchronous reference coordinate system, providing a tensor representation in coordinate basis for subsequent three-phase decoupling modeling; S32.2 Project the voltage phasor, current phasor, and impedance phasor in the line voltage drop equation along the reference directions of phase A, phase B, and phase C, respectively, as follows: By the definition of the projection operator To verify its consistency with the direct algebraic expansion, the impedance-current product term is expanded. Let the current phasor be... ,impedance ,but: (7) in, and Represents current phasor Expanding the real and imaginary parts; for The product term, when the projection direction is taken When the reference direction is A, equation (7) simplifies to: Similarly, the product of zero-line impedance and current can be simplified to: Substituting into equation (4), we obtain the linear voltage drop equation in the A-phase projection system: (8) Will Substituting the values ​​into the equations, we obtain the complete system of equations for the three-axis projection system, phase B projection system: (9) (10) (11) C-phase projection system: (12) (13) (13) In the formula, They represent Phase meter box The real and imaginary parts of the live wire current obtained by the projection operator. Let represent the real and imaginary parts of the zero-line current obtained by the projection operator, respectively. These represent the resistance and reactance values ​​of the live wire and neutral wire, respectively. S32.3 transforms the complex domain line voltage drop relationship into a linear constraint relationship in three-dimensional real space, constructing a line impedance parameter identification model, specifically including: Equations (6) to (14) together constitute the voltage drop equation for a three-phase four-wire system. Tensor representation in coordinates can extend the original complex domain single equation into a linear constraint system in three-dimensional real vector space (taking phase A as an example for illustration): (14) In equation (14), subtracting the two equations yields the table box node. and The electrical parameter relationship is as follows: (15) in, (16) S4. Based on the line impedance parameter identification model, the line impedance parameters are iteratively identified to obtain the current round of line impedance parameter estimation results, as follows: S41. Perform column scaling normalization on the coefficient matrix corresponding to the line impedance parameter identification model, and construct an objective function containing ridge regularization terms based on the normalized coefficient matrix: In actual measurements, the amplitude and phase changes of the current in each branch are not completely uniform, and the local regression matrix may exhibit column scaling differences and ill-conditioned behavior. If ordinary least squares or pseudo-inverse is used directly for solving, small random disturbances in the voltage amplitude may be amplified in the impedance parameters. Therefore, this embodiment first performs column scaling normalization on the coefficient matrix: (17) in The number of sampling points. The number of parameters to be estimated. For column scaling matrix, This is the normalized coefficient matrix. A ridge regularization term is further introduced into the normalized space, with the regularization coefficients adaptively given according to matrix energy: (18) In the formula, This is the relative regularization coefficient.

[0029] S43. Use the ridge regression method to solve for the initial estimates of the line impedance parameters: Each local identification problem can be written as a weighted ridge regression: (19) in for The OK, For the first The robust weights for each sampling point, with the ridge regularization term not altering the physical meaning of the linear voltage drop model, serve to suppress parameter oscillations when the matrix condition number is large, thereby improving the stability of impedance estimation under noisy conditions. In this embodiment, the weights are... To achieve a trade-off between regularization stability and parameter bias; S44. Calculate the prediction residuals corresponding to each sampling point based on the current estimated line impedance parameters. Calculate the residual scale based on the current round's prediction residuals. Construct the Huber loss function based on the residual scale. Update the weights corresponding to each sampling point using the iterative reweighted least squares method. Recalculate the current round's line impedance parameter estimation results based on the updated weights, as detailed below: Ridge regularization alone is insufficient to completely eliminate the influence of individual outlier sampling points. To further improve robustness against measurement noise and local outliers, this embodiment employs the iterative reweighted least squares method corresponding to Huber loss: Given the first The weight matrix of the next iteration Normalized parameters The update is as follows: (20) (twenty one) After completing a parameter update, the current model prediction error is used as the residual, and the residual scale is estimated accordingly. To avoid a few large residuals from inflating the scaling estimate, this embodiment uses the median absolute deviation as the scaling estimator: (twenty two) The weights of each sampling point are then updated according to the Huber weight function: (twenty three) in This is the Huber threshold coefficient. To minimize the weight, when the residual is small, the observation points maintain a unit weight; after the residual exceeds the threshold, its influence decreases as the residual amplitude increases. In this embodiment, we take... The maximum number of iterations is set to 8, and when the relative change in weight between two adjacent rounds is less than 8, the maximum number of iterations is 8. When the weight distribution is considered stable, the iteration stops. S5. Based on the current round of line impedance parameter estimation results, perform a three-phase four-wire low-voltage distribution area power flow back calculation to obtain the updated voltage phase angle and current phase angle of each node. Then, correct the initial electrical quantities based on the updated voltage and current phase angles to obtain the corrected electrical quantities corresponding to the next round of line impedance parameter identification. Specifically, this includes: A three-phase four-wire power flow calculation model is established based on the current line impedance parameter estimation results. Based on the three-phase four-wire power flow calculation model, power flow calculation is performed to obtain the updated voltage phase angle and current phase angle of each node. A damping update strategy is used to correct the voltage phase angle and current phase angle obtained from the current power flow back calculation. The voltage phase angle and current phase angle of the previous round are weighted and fused with those of the current round based on the preset damping factor; By using the fused voltage phase angle and current phase angle to update the corresponding voltage phasor and current phasor, the corrected electrical quantities corresponding to the next round of line impedance parameter identification are obtained. Specifically: In smart meter measurement scenarios, voltage and current phase angles are not directly available. The initial phase angle is approximated by the power factor angle and the three-phase symmetry assumption mentioned above. To reduce the impact of phase angle approximation on impedance identification, after completing one impedance identification, a power flow back calculation is performed, and the back-calculated phase angle is used to correct the next round of impedance estimation. Phase angle damping update Since the phase angle in the backflow calculation is still affected by the current impedance estimation error, if the new phase angle is used completely in the iteration process, it may lead to excessive phase angle correction and cause parameter oscillation. Therefore, this embodiment adopts a damped update strategy to make the phase angle corrected smoothly in each iteration: (twenty four) (25) In the formula, The outer iteration number, Calculate the phase angle for the current return. As the damping factor, this embodiment takes... By absorbing only a portion of the phase angle correction in each round, this strategy can reduce the amplification effect between "impedance error - phase angle error - impedance error of the next round", thereby improving the closed-loop iteration stability. S6. Re-input the corrected electrical quantities into the line impedance parameter identification model to identify the line impedance parameters and obtain a new round of line impedance parameter estimation results. Determine whether the preset convergence condition is met based on the line impedance parameter estimation results of the two adjacent rounds. If the preset convergence condition is met, output the final line impedance parameter identification result. During the simulation verification phase, using a preset line impedance as a reference value, error evaluation is performed on the identification results of each round, and for any line... Identified resistance Reactance and real resistance Reactance The relative error is defined as: (26) To simultaneously reflect both the maximum error and the overall error level, this embodiment constructs the following comprehensive score, with each item in the comprehensive score having a weight. Adjustments based on the target being identified: (27) If the current round's overall score does not significantly deteriorate compared to the historical best result, then the phase angle and impedance updates for this round are accepted; otherwise, the closed-loop iteration is considered to have entered an unstable state and the current parameter identification results are no longer accepted.

[0030] To verify the effectiveness of this embodiment, experiments were conducted in six typical low-voltage distribution areas to test the line parameter identification performance under various scenarios: Dataset description: Experimental data include: There are 6 types of low-voltage distribution areas, including 9 meter boxes, 3 branch boxes, and 27 nodes; Each transformer substation collects 52 days of minute-level electrical data under different sampling periods, including three-phase voltage, three-phase current, and power factor.

[0031] The transformer substation types are divided into radial, herringbone, and mixed substations containing only three-phase meter boxes, and radial, herringbone, and mixed substations containing both single-phase and three-phase meter boxes. The substation type has little impact on the identification results in this embodiment. The parameter identification results for one type of substation are as follows: Table 1 Parameter Identification Results It can be seen that when the number of sampling days is sufficient, the accuracy of parameter identification is 100% under noise-free conditions. However, with the increase of noise, both the maximum error and the average error increase to a certain extent. Furthermore, in the identification of low-voltage distribution area line parameters, under the condition that the smart meters in the low-voltage distribution area do not measure phase angle, the observability of reactance parameters is weaker than that of resistance parameters. Since the voltage drop in the line is mainly determined by the active current and resistance terms, while the reactance term contributes less to the voltage drop and is easily affected by insufficient reactive power fluctuations, measurement noise, and phase angle estimation errors, therefore... The identification error is usually greater than .

[0032] Example 2: This embodiment provides a three-phase four-wire low-voltage distribution area parameter identification system based on the voltage drop equation, used to implement the three-phase four-wire low-voltage distribution area parameter identification method based on the voltage drop equation described in Embodiment 1, including: The data acquisition module is used to acquire the network topology information of the three-phase four-wire low-voltage distribution area to be identified and the smart meter measurement data of each node. The smart meter measurement data includes at least the voltage amplitude, current amplitude, active power and reactive power of each phase of each node. The initial electrical quantity calculation module is used to determine the line connection relationship between each node based on the network topology information, construct the initial voltage phasor and initial current phasor corresponding to each node based on the active power and reactive power, and obtain the initial electrical quantities required for line parameter identification. The model building module is used to select adjacent nodes with a common parent node according to the line connection relationship, establish a three-phase four-wire line voltage drop equation that takes into account the influence of the neutral line in combination with the initial electrical quantities, perform coordinate transformation on the line voltage drop equation according to the preset coordinate transformation rules, convert the line voltage drop relationship in the complex domain into the line voltage drop relationship in the three-dimensional real space, and build a line impedance parameter identification model. The iterative identification module is used to iteratively identify the line impedance parameters based on the line impedance parameter identification model to obtain the current round of line impedance parameter estimation results. The update and correction module is used to perform power flow back calculation of the three-phase four-wire low-voltage distribution area based on the current round line impedance parameter estimation results, obtain the updated voltage phase angle and current phase angle of each node, and correct the initial electrical quantity according to the updated voltage phase angle and current phase angle to obtain the corrected electrical quantity corresponding to the next round line impedance parameter identification. The result output module is used to re-input the corrected electrical quantity into the line impedance parameter identification model to identify the line impedance parameters, obtain a new round of line impedance parameter estimation results, and determine whether the preset convergence condition is met based on the line impedance parameter estimation results of the two adjacent rounds; if the preset convergence condition is met, the final line impedance parameter identification result is output.

[0033] Example 3: The present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor. When the processor loads and executes the computer program, it adopts the three-phase four-wire low-voltage distribution area parameter identification method based on the voltage drop equation described in Embodiment 1.

[0034] It should be noted that the terminal device can be a computer device such as a desktop computer, a laptop computer, or a cloud server, and the terminal device includes, but is not limited to, a processor and a memory. For example, the terminal device may also include input / output devices, network access devices, and buses.

[0035] Furthermore, the processor can be a central processing unit (CPU). Of course, depending on the actual use, other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be used. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it in this regard.

[0036] Example 4: The present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the three-phase four-wire low-voltage distribution area parameter identification method based on the voltage drop equation described in Embodiment 1.

[0037] The computer program can be stored in a computer-readable medium. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or certain middleware. The computer-readable medium includes any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the computer-readable medium includes, but is not limited to, the above-mentioned components.

[0038] In the description of this specification, the references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0039] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this application. Various changes and modifications can be made to this application without departing from the spirit and scope thereof, and all such changes and modifications fall within the scope of the claims of this application.

Claims

1. A method for parameter identification of three-phase four-wire low-voltage distribution areas based on voltage drop equations, characterized in that, Includes the following steps: The network topology information of the three-phase four-wire low-voltage distribution area to be identified and the measurement data of smart meters at each node are obtained. The smart meter measurement data includes at least the voltage amplitude, current amplitude, active power and reactive power of each phase at each node. Based on the network topology information, determine the line connection relationship between each node, construct the initial voltage phasor and initial current phasor corresponding to each node based on the active power and reactive power, and obtain the initial electrical quantities required for line parameter identification. Based on the line connection relationship, adjacent nodes with a common parent node are selected. Combined with the initial electrical quantities, a three-phase four-wire line voltage drop equation considering the influence of the neutral line is established. The line voltage drop equation is transformed according to the preset coordinate transformation rules to convert the complex domain line voltage drop relationship into the line voltage drop relationship in three-dimensional real space, and a line impedance parameter identification model is constructed. Based on the line impedance parameter identification model, the line impedance parameters are iteratively identified to obtain the current round of line impedance parameter estimation results. Based on the current round of line impedance parameter estimation results, perform three-phase four-wire low-voltage distribution area power flow back calculation to obtain the updated voltage phase angle and current phase angle of each node, and correct the initial electrical quantity according to the updated voltage phase angle and current phase angle to obtain the corrected electrical quantity corresponding to the next round of line impedance parameter identification. The corrected electrical quantity is re-input into the line impedance parameter identification model to identify the line impedance parameter, and a new round of line impedance parameter estimation results are obtained. Based on the line impedance parameter estimation results of the two adjacent rounds, it is determined whether the preset convergence condition is met. If the preset convergence condition is met, the final line impedance parameter identification result will be output.

2. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: Based on the active and reactive power, the initial voltage phasors and initial current phasors corresponding to each node are constructed to obtain the initial electrical quantities required for line parameter identification, specifically including: Calculate the power factor angle of each phase based on the active and reactive power of each phase at each node; Set the initial voltage phase angle of phase A to 0°, the initial voltage phase angle of phase B to 120° lags behind phase A, and the initial voltage phase angle of phase C to 120° lead phase A, and construct the initial voltage phasor of each phase at each node. The initial electrical quantities are obtained by constructing the initial current phasor of each phase at each node based on the current amplitude of each phase at each node, the corresponding power factor angle, and the initial voltage phasor of each phase, and by calculating the corresponding neutral line current phasor based on the three-phase initial current phasor.

3. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: This also includes applying relative Gaussian noise to the voltage amplitude, as detailed below: in Indicator box At discrete time The measured voltage, Represents the relative noise standard deviation, taken as... , This represents a noise variable randomly drawn from a standard normal distribution.

4. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: Based on the line connection relationship, adjacent nodes with a common parent node are selected, and a voltage drop equation for a three-phase four-wire line considering the influence of the neutral wire is established in conjunction with the initial electrical quantities. Specifically, this includes: For two adjacent nodes with a common parent node, the parent node is used as a common reference node, and the voltage drop relationship of each phase conductor is established according to Kirchhoff's voltage law. Establish separate terms for the impedance voltage drop of each phase conductor and the impedance voltage drop of the neutral conductor; The voltage drop of each phase conductor impedance and the voltage drop of the neutral conductor together constitute the voltage drop equation for a three-phase four-wire system that takes into account the influence of the neutral conductor.

5. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 4, characterized in that: The line voltage drop equation is transformed according to a preset coordinate transformation rule, converting the complex domain line voltage drop relationship into a three-dimensional real space line voltage drop relationship, and constructing a line impedance parameter identification model, specifically including: Establish a linear projection mapping from complex phasor space to three-dimensional real space; Project the voltage phasor, current phasor, and impedance phasor in the line voltage drop equation along the reference directions of phase A, phase B, and phase C, respectively. The line voltage drop relationship in the complex domain is transformed into a linear constraint relationship in three-dimensional real space to construct a line impedance parameter identification model.

6. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 5, characterized in that: Based on the aforementioned line impedance parameter identification model, the line impedance parameters are iteratively identified to obtain the current round of line impedance parameter estimation results, specifically including: The coefficient matrix corresponding to the line impedance parameter identification model is subjected to column scaling normalization. Construct an objective function containing ridge regularization terms based on the normalized coefficient matrix; The ridge regression method is used to solve for the initial estimates of the line impedance parameters; Calculate the prediction residuals corresponding to each sampling point based on the current estimated line impedance parameters, and calculate the residual scale based on the current round of prediction residuals; The Huber loss function is constructed based on the residual scale. The weights corresponding to each sampling point are updated using the iterative reweighted least squares method. The current round line impedance parameter estimation result is then recalculated based on the updated weights.

7. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: Based on the current line impedance parameter estimation results, a three-phase four-wire low-voltage distribution area power flow back calculation is performed to obtain the updated voltage phase angle and current phase angle of each node, specifically including: A three-phase four-wire power flow calculation model is established based on the current line impedance parameter estimation results. Based on the three-phase four-wire power flow calculation model, power flow calculation is performed to obtain the updated voltage phase angle and current phase angle of each node; The voltage phasors and current phasors of each node are reconstructed based on the updated voltage phase angle and current phase angle.

8. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: The initial electrical quantities are corrected based on the updated voltage phase angle and current phase angle to obtain the corrected electrical quantities corresponding to the next round of line impedance parameter identification, specifically including: A damping update strategy is used to correct the voltage phase angle and current phase angle obtained from the current power flow recalculation. The voltage phase angle and current phase angle of the previous round are weighted and fused with those of the current round based on the preset damping factor; By updating the corresponding voltage phasors and current phasors using the fused voltage phase angle and current phase angle, the corrected electrical quantities corresponding to the next round of line impedance parameter identification are obtained.

9. The method for parameter identification of a three-phase four-wire low-voltage distribution area based on the voltage drop equation according to claim 1, characterized in that: The corrected electrical quantity is re-input into the line impedance parameter identification model to identify the line impedance parameters, obtaining a new round of line impedance parameter estimation results. The results of the two adjacent rounds of line impedance parameter estimation are then used to determine whether a preset convergence condition is met. If the preset convergence condition is met, the final line impedance parameter identification result is output, as follows: Calculate the parameter variation between the estimated impedance parameters of two adjacent circuits; The change in the parameter is compared with a preset convergence threshold. If the change in the parameter is less than the preset convergence threshold, or if the preset maximum number of iterations is reached, then the preset convergence condition is satisfied, and the final line impedance parameter identification result is output.

10. A three-phase four-wire low-voltage distribution area parameter identification system based on voltage drop equation, used to implement the three-phase four-wire low-voltage distribution area parameter identification method based on voltage drop equation as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to acquire the network topology information of the three-phase four-wire low-voltage distribution area to be identified and the smart meter measurement data of each node. The smart meter measurement data includes at least the voltage amplitude, current amplitude, active power and reactive power of each phase of each node. The initial electrical quantity calculation module is used to determine the line connection relationship between each node based on the network topology information, construct the initial voltage phasor and initial current phasor corresponding to each node based on the active power and reactive power, and obtain the initial electrical quantities required for line parameter identification. The model building module is used to select adjacent nodes with a common parent node according to the line connection relationship, establish a three-phase four-wire line voltage drop equation that takes into account the influence of the neutral line in combination with the initial electrical quantities, perform coordinate transformation on the line voltage drop equation according to the preset coordinate transformation rules, convert the line voltage drop relationship in the complex domain into the line voltage drop relationship in the three-dimensional real space, and build a line impedance parameter identification model. The iterative identification module is used to iteratively identify the line impedance parameters based on the line impedance parameter identification model to obtain the current round of line impedance parameter estimation results. The update and correction module is used to perform power flow back calculation of the three-phase four-wire low-voltage distribution area based on the current round line impedance parameter estimation results, obtain the updated voltage phase angle and current phase angle of each node, and correct the initial electrical quantity according to the updated voltage phase angle and current phase angle to obtain the corrected electrical quantity corresponding to the next round line impedance parameter identification. The result output module is used to re-input the corrected electrical quantity into the line impedance parameter identification model to identify the line impedance parameter, obtain a new round of line impedance parameter estimation results, and determine whether the preset convergence condition is met based on the line impedance parameter estimation results of two adjacent rounds. If the preset convergence condition is met, the final line impedance parameter identification result will be output.

Images