A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy

Abstract

The present invention discloses a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy, which relates to the technical field of distribution network parameter identification and estimation. First, each node and branch of the distribution network are numbered according to depth-first search, and the number of the first node is 0; a consistency deviation index is established to distinguish available measurement values and unavailable measurement values, and the unavailable measurement values are eliminated; the measured voltage of each node of the distribution network is used as the initial value of the voltage amplitude, and the initial value of the voltage amplitude of the node without measurement value is 1. The power is pushed forward and the deviation from the measured power is calculated. If it is greater than the set threshold, the branch is set as the line to be corrected; the voltage is back-substituted from the first node to obtain the voltage phase angles at the beginning and end of the line to be corrected, the parameters of the line to be corrected are set as state variables, and the corrected parameters are obtained; the corrected parameters are brought into the forward-backward substitution for state estimation of the distribution network, and the branch parameters of the measurement points of the distribution network are further corrected based on the forgetting factor least squares recursive method.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network parameter identification and estimation, and specifically to a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy. Background Art

[0002] With the development of the Supervisory Control And Data Acquisition (SCADA) system, the Remote Terminal Units (RTUs) in this system can obtain on-site measurement data. However, the SCADA system has poor data synchronization and only provides voltage and current amplitudes, active power, and reactive power, and cannot provide phase angle information. The Wide-Area Measurement System (WAMS) based on the Phasor Measurement Unit (PMU) can provide phase angle information, but the price of PMU devices is much higher than that of RTU devices. Currently, PMU devices are mainly installed in important substations of 500 kV and 220 kV. Using advanced measurement equipment for power system state estimation can effectively judge the operating state of the power grid in real time and improve the stability of the power grid.

[0003] Accurate measurement data provides a new way to obtain line parameters. Parameter accuracy is closely related to the operation and control of the power system, such as protection setting, fault location, and state estimation. Incorrect parameters will affect the safe and stable operation of the power grid. Generally, line parameters are mainly obtained through theoretical calculation or off-line measurement. The theory is an approximate estimate, while off-line measurement is under specific working conditions, and neither can reflect the true situation of line parameters under actual working conditions and factors such as climate, temperature, and geography. In addition, ensuring the accuracy of various component parameters in the power grid is also the basis for the power grid to arrange dispatching operation plans. In short, improving the accuracy of power grid parameter calculation is a basic requirement for building a smart grid and is of great significance for maintaining the safe, stable, and economic operation of the power grid.

[0004] The distribution network directly faces a large number of users and belongs to basic power consumption facilities. The quality of its operation will have a great impact on the final power supply quality. Therefore, it is extremely important to study its parameter identification. At present, the construction of the intelligent distribution network is still in its infancy, and the amount of measurement is relatively small. The most urgent task at present is to make the completely unmonitorable distribution network basically observable, allowing a certain error to exist at this time. In the actual system, there are errors in the measurement data and the error level is unknown. Inappropriate data may lead to non-convergence in the identification process. Therefore, before parameter identification, bad measurement values should be screened and eliminated. Compared with the main grid, the network structure of the distribution network is much more complex and has numerous nodes. The resistance and reactance on the entire line are basically similar, and in some special environments, the former will exceed the latter. Therefore, the ratio of branch parameters in the distribution network is relatively large. Therefore, for state estimation and parameter identification, traditional Newton-Raphson method and PQ decomposition method will have problems such as difficult convergence and low calculation efficiency. The operation of a large number of short branches and the complex situation of multiple branches in the distribution network also bring difficulties to the numerical calculation of some algorithms. If the branch parameters are augmented as state variables into the state estimation (SE) for calculation, since the derivative component of the measurement with respect to the parameter easily leads to a jump in the condition number of the Jacobian matrix, the numerical stability of the state estimation after augmenting the parameters deteriorates significantly. Summary of the Invention

[0005] To solve the deficiencies mentioned in the above background technology, the purpose of the present invention is to provide a method for correcting distribution network parameters based on forward-backward sweep and measurement redundancy, which can correct the line parameters of the distribution network.

[0006] The purpose of the present invention can be achieved through the following technical solutions: 1. A method for correcting distribution network parameters based on forward-backward sweep and measurement redundancy, characterized in that the method includes the following steps:

[0007] Number each node and branch of the distribution network according to depth-first search, and the number of the first node is 0;

[0008] Collect measurement values at each measurement point, including branch active power P m , branch reactive power Q m , node voltage amplitude U m , branch current amplitude I m and node active load node reactive load

[0009] According to branch power balance and node power balance, establish branch power consistency deviation index ξ 1 and node power consistency deviation index ξ 2 , and set the index threshold to ε 1 and ε 2, distinguish available measurement values from unavailable measurement values. If the consistency deviation index value is less than the index threshold, it is an available measurement value; otherwise, it is an unavailable measurement value, and the unavailable measurement values are excluded;

[0010] Take the measured voltage of each node in the distribution network as the initial voltage value, the initial voltage amplitude value of the node without a measurement value is 1, forward the power and calculate the deviation from the measured power. If it is greater than the set deviation threshold ε 3 , then set the branch as the line to be corrected. If it is less, then obtain the correction parameter using the branch parameters and perform the correction;

[0011] Back-substitute the voltage from the head node to obtain the voltage phase angles at the head and end of the line to be corrected. Set the parameters of the line to be corrected as state variables, obtain the correction parameter, and return to the previous step to correct the branch parameters again;

[0012] Substitute the correction parameter into the forward-back substitution for the state estimation of the distribution network, and further correct the branch parameters of the distribution network based on the forgetting factor least squares recursive method.

[0013] Preferably, the process of distinguishing available measurement values from unavailable measurement values and excluding unavailable measurement values includes the following steps:

[0014] For the active power P of the branch collected m , reactive power Q m , node active load node voltage amplitude U m and branch current amplitude I m , use Equation (1) to calculate the branch power consistency deviation index ξ 1 and the node power consistency deviation index ξ 2 :

[0015]

[0016] In Equation (1), k is the k-th node of the distribution network, C j is the set of all nodes connected to node j except node i, is the active power measurement value of the branch from node j to node k, is the active power measurement value of the branch from node i to node j, is the reactive power measurement value of the load at node j;

[0017]

[0018] In Equation (2), and are the voltage and current measurement values of node i respectively, is the reactive power measurement value of the branch from node i to node j;

[0019] When ξ 1Less than the set threshold ε 1 and ξ 2 Less than the set threshold ε 2 when all of the above measurement values are available;

[0020] When ξ 1 Less than the set threshold ε 1 and ξ 2 Greater than the set threshold ε 2 at this time, the active power P of the branch m and reactive power Q m and the active power load of the node are available, and the node voltage amplitude U m and the branch current amplitude I m are not available;

[0021] When ξ 1 Greater than the set threshold ε 1 and ξ 2 Less than the set threshold ε 2 at this time, the active power P of the branch m and reactive power Q m and the node voltage amplitude U m and the branch current amplitude I m are available, and the node active power load is not available;

[0022] When ξ 1 Greater than the set threshold ε 1 and ξ 2 Greater than the set threshold ε 2 at this time, all of the above measurement values are not available.

[0023] Preferably, the process of determining whether a branch is a line to be corrected is as follows:

[0024] Forward power from the end nodes of each branch of the distribution network, k ij is the transformer turns ratio, S is the apparent power, y is the equivalent shunt admittance of the branch, and C is the set of all nodes connected to node j except node i; use equations (3)-(6) to calculate the deviation between the branch power and the branch measured power:

[0025]

[0026] In equation (3), is the voltage vector of node j;

[0027]

[0028] In equation (4), is the apparent power vector of node j, is the apparent power measurement value vector of the branch from node i to node k, is the vector of measured apparent power of load at node j, is the vector of measured voltage at node k, is the conjugate value of the admittance of node j;

[0029]

[0030] In formula (5), is the apparent power of the branch from node i to node j, Z ij is the branch impedance from node i to node j;

[0031]

[0032] If formula (6) does not hold, set the branch as the line to be corrected, otherwise obtain the correction parameters using the branch parameters and perform the correction.

[0033] Preferably, the calculation process of the voltages at the beginning and end of the line to be corrected is as follows:

[0034] Back-substitute the voltage from the head node, and use formula (7) and formula (8) to obtain the voltage vectors at the beginning and end of the line to be corrected:

[0035]

[0036] In formula (7), is the voltage vector of node i;

[0037]

[0038] In formula (8), is the current vector of the branch from node i to node j.

[0039] Preferably, the process of obtaining the correction parameters is as follows:

[0040] Obtain its correction parameters from the measured values using formula (9)-(12) as follows:

[0041]

[0042]

[0043]

[0044]

[0045] where g ij and b ij are the conductance and susceptance of the branch from node i to node j, θ i and θ j are the voltage phase angles of node i and node j respectively, θ ijis the difference in voltage phase angle between node i and node j, is the measured voltage value of node j, is the measured current value of the branch from node i to node j, and A is an intermediate variable; the line parameters g to be corrected ij , b ij , y j0 are set as state variables.

[0046] Preferably, the process of estimating the state of the distribution network by substituting the correction parameters into the forward-backward substitution and further correcting the branch parameters of the distribution network based on the forgetting factor least squares recursive method is as follows:

[0047] Substitute the correction parameters into the forward-backward substitution for state estimation of the distribution network:

[0048] h = xΦ (13)

[0049]

[0050]

[0051] In equation (13), h is the state estimation quantity, x is the branch parameter matrix, Φ I is the current data matrix, Φ P is the active power data matrix, Φ Q is the reactive power data matrix, and B is an intermediate variable.

[0052] Real-time correction of parameters based on the forgetting factor least squares recursive method:

[0053]

[0054] In equation (16), t is the iteration number, λ is the forgetting factor, x t and x t-1 are the branch parameter matrices at the t-th and (t-1)-th times, K t is the gain matrix at the t-th time, P t and P k-1 are the covariance matrices at the t-th and (t-1)-th times, Φ t and Φ t T are the data matrix at the t-th time and the transpose of the data matrix, and E is the identity matrix.

[0055] Preferably, a device includes:

[0056] One or more processors;

[0057] A memory for storing one or more programs;

[0058] When one or more of the said programs are executed by one or more of the said processors, the one or more processors implement a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy as described above.

[0059] Preferably, a storage medium containing computer-executable instructions, the computer-executable instructions being used to execute a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy as described above when executed by a computer processor.

[0060] Advantages of the present invention:

[0061] 1. The present invention takes into account the characteristics of a large number of nodes and complex branches in the distribution network. By using deep numbering, it is simple and rapid to find the line with incorrect parameters based on the forward-backward substitution method. The corrected parameters are then used as the line base value for state estimation, and the deviation from the measured value is small. Further correcting the parameters based on this is more accurate than directly correcting the parameters.

[0062] 2. The present invention defines a consistency deviation index. By calculating the branch active power balance relationship and establishing the node power balance relationship, available measurement data can be screened out.

[0063] 3. The present invention is applicable to the situation of insufficient measurements in the distribution network. Based on limited measured values, forward-backward substitution and distribution network state estimation can still be carried out.

[0064] 4. The present invention adopts the least squares recursive method based on genetic factors, which can correct the line parameters of the measurement points according to the screened available measured values, gradually weakening the historical data, having real-time performance, and requiring less memory and shorter calculation time than traditional methods. Description of the Drawings

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings;

[0066] Figure 1 is the flowchart of the method of the present invention;

[0067] Figure 2 is the equivalent network of the radial distribution network of the present invention. Detailed Embodiments

[0068] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0069] As Figure 1 shown, a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy includes the following steps:

[0070] S1. Number each node and branch of the distribution network according to the depth of the tree, and the number of the first node is 0. For Figure 2 the shown schematic diagram of the distribution network, measure values are collected at each measurement point, including branch active power P m , branch reactive power Q m , node voltage amplitude U m , branch current amplitude I m and node load and other data;

[0071] S2. Define a consistency deviation index ξ to evaluate the error of the measured values, including branch power deviation and node power deviation. For the branch active power P m , reactive power Q m , node active load node voltage amplitude U m and branch current amplitude I m collected in S1, use Equation (1) to calculate the branch power consistency deviation index ξ1, and use Equation (2) for the node power consistency deviation index ξ 2 :

[0072]

[0073]

[0074] When ξ 1 is less than the set threshold ε 1 and ξ 2 is less than the set threshold ε 2 , all the above measured values are available;

[0075] When ξ 1 is less than the set threshold ε 1 and ξ 2 is greater than the set threshold ε 2 , the branch active power P m , reactive power Q m and node active load are available, and the node voltage amplitude U m and branch current amplitude Im Unavailable;

[0076] When ξ 1 is greater than the set threshold ε 1 and ξ 2 is less than the set threshold ε 2 the active power P of the branch m , reactive power Q m , the node voltage amplitude U m and the branch current amplitude I m are available, and the node active load is unavailable;

[0077] When ξ 1 is greater than the set threshold ε 1 and ξ 2 is greater than the set threshold ε 2 all of the above measurement values are unavailable;

[0078] S3. Using the measured voltage of each node in the distribution network as the initial value of the voltage amplitude, the initial value of the voltage amplitude of the node without measurement value is 1, and the voltage phase angles are all 0. Push forward the power from the end nodes of each branch in the distribution network and calculate the deviation from the measured power of the branch. If it is greater than the set threshold ε 3 , then set this branch as the line to be corrected, otherwise go to S5;

[0079] Using the measured voltage of each node in the distribution network as the initial value of the voltage amplitude, the initial value of the voltage amplitude of the node without measurement value is 1, and the voltage phase angles are all 0. Push forward the power from the end nodes of each branch in the distribution network. k is the transformer turns ratio. Distinguish between transformer branches and ordinary branches. The voltages of transformer branches and ordinary branches are converted using Equation (3):

[0080]

[0081] S is the apparent power, y is the equivalent shunt admittance of the branch to the ground, and C is the set of all nodes connected to node j except node i. The equivalent apparent power flowing through node j is equal to the apparent power flowing through the nodes included in C, the power of the branch to the ground, and the node load power, and is calculated using Equation (4):

[0082]

[0083] Z ij is the branch impedance from node i to node j. Considering the branch power loss, the power of this branch is calculated using Equation (5):

[0084] S ij = S j +(S j / U j ) 2 Z ij (5)

[0085] Calculate the deviation between the branch power and the measured branch power using Equation (6):

[0086]

[0087] If Equation (6) does not hold, set this branch as the line to be corrected; otherwise, go to S5;

[0088] S4. Back-substitute the voltage from the head node to obtain the voltage phase angles at the head and end of the line to be corrected. Set the parameters of the line to be corrected as state variables, obtain their correction parameters, and return to S3;

[0089] S4.1. Back-substitute the voltage from the head node, distinguish between ordinary branches and transformer branches, and use Equation (7) and Equation (8) to obtain the voltage vectors at the head and end of the line to be corrected:

[0090]

[0091]

[0092] S4.2. Set the parameters g ij , b ij , y j0 of the line to be corrected as state variables. With the measured values known, use Equation (9)-(11) to obtain the correction parameters. Equation (12) is the intermediate variable of Equation (9):

[0093]

[0094]

[0095]

[0096]

[0097] S5. Substitute the correction parameters into the forward-backward substitution for the state estimation of the distribution network. h is the calculated value after the forward-backward substitution converges, including I, P, and Q. x is the branch parameter matrix, Φ is the data matrix, and B is the intermediate variable. The branch constraints are expressed by Equation (12)-(14):

[0098] h = xΦ (13)

[0099]

[0100]

[0101] To minimize the residual, further correct the branch parameters of the distribution network based on the forgetting factor least squares recursive method through Equation (15):

[0102]

[0103] where λ is the forgetting factor, K is the gain matrix, P is the covariance matrix, E represents the identity matrix, and t and t-1 represent the data corresponding to the current measurement and the previous measurement respectively.

[0104] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions, specifically to load and execute one or more instructions in the computer storage medium to implement the above method.

[0105] It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and the computer program, when run by a processor, executes the above method. The storage medium may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or combined with an instruction execution system, apparatus, or device.

[0106] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0107] The above has shown and described the basic principles, main features and advantages of the present disclosure. Those skilled in the art of this industry should understand that the present disclosure is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure will have various changes and improvements, and these changes and improvements all fall within the scope of the present disclosure claimed.

Claims

1. A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy, characterized in that, the method comprises the following steps: Number each node and branch of the distribution network according to depth-first search, with the number of the first node being 0; Collect measurement values at each measurement point, including the active power P of the branch m , the reactive power Q of the branch m , the amplitude U of the node voltage m , the amplitude I of the branch current m and the active power load of the node the reactive power load of the node Based on the branch power balance and node power balance, a branch power consistency deviation index ξ is established. 1 and a node power consistency deviation index ξ 2 , and the index thresholds are set as ε 1 and ε 2 . The available and unavailable measured values are distinguished. If the consistency deviation index value is less than the index threshold, it is an available measured value; otherwise, it is an unavailable measured value, and the unavailable measured values are eliminated. Taking the measured voltage of each node in the distribution network as the initial voltage value, the initial voltage amplitude value of the node without measured value is 1, pushing forward the power and calculating the deviation from the measured power. If it is greater than the set deviation threshold ε 3 , then set the branch as the line to be corrected. If it is less than, obtain the correction parameter using the branch parameters and perform the correction; Back-substitute the voltage from the first node to obtain the voltage phase angles at the beginning and end of the line to be corrected. Set the parameters of the line to be corrected as state variables, obtain the correction parameters, and return to the previous step to correct the branch parameters again; The process of obtaining the correction parameters is as follows: Use equations (9)-(12) from the measured values to obtain its correction parameters, as follows: where g ij and b ij are the branch conductance and susceptance from node i to node j, θ i and θ j are the voltage phase angles of nodes i and j respectively, θ ij is the difference in voltage phase angles between nodes i and j, is the measured value of the voltage at node j, is the measured value of the current in the branch from node i to node j, and A is an intermediate variable; the line parameters to be corrected, g ij , b ij , y j0 are set as state variables; Substitute the correction parameters into the forward-backward substitution for state estimation of the distribution network, and further correct the branch parameters of the distribution network based on the forgetting factor least squares recursive method.

2. A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy according to claim 1, characterized in that, the process of distinguishing available measurement values and unavailable measurement values and removing the unavailable measurement values comprises the following steps: For the active power P of the branch collected m , reactive power Q m , active power load P of the node L m , node voltage amplitude U m and branch current amplitude I m , use Equation (1) to calculate the branch power consistency deviation index ξ 1 and the node power consistency deviation index ξ 2 : In Equation (1), k is the k-th node of the distribution network, C j is the set of all nodes connected to node j except node i, is the active power measurement value of the branch from node j to node k, is the active power measurement value of the branch from node i to node j, is the reactive power measurement value of the load at node j; In Equation (2), and are the voltage and current measurement values of node i respectively, is the reactive power measurement value of the branch from node i to node j; When ξ 1 is less than the set threshold ε 1 and ξ 2 is less than the set threshold ε 2 all of the above measurement values are available; When ξ 1 is less than the set threshold ε 1 and ξ 2 is greater than the set threshold ε 2 at this time, the active power P of the branch m , reactive power Q m and the active power load of the node are available, while the node voltage amplitude U m and the branch current amplitude I m are not available; When ξ 1 is greater than the set threshold ε 1 and ξ 2 is less than the set threshold ε 2 at this time, the active power P of the branch m , reactive power Q m , the node voltage amplitude U m and the branch current amplitude I m are available, and the node active power load is unavailable; When ξ 1 is greater than the set threshold ε 1 and ξ 2 is greater than the set threshold ε 2 all of the above measurement values are unavailable.

3. A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy according to claim 1, characterized in that, The process of determining whether a branch is a line to be corrected is as follows: Forward the power from the end nodes of each branch of the distribution network, k ij is the transformer turns ratio, S is the apparent power, y is the equivalent shunt admittance to ground of the branch, and C is the set of all nodes connected to node j except node i; use equations (3)-(6) to calculate the deviation between the branch power and the measured branch power: In Equation (3), is the voltage vector of node j; In Equation (4), is the apparent power vector of node j, is the apparent power measurement value vector of the branch from node i to node k, is the apparent power measurement value vector of the load at node j, is the voltage measurement value vector of node k, is the conjugate value of the admittance of node j; In formula (5), is the apparent power of the branch from node i to node j, and Z ij is the branch impedance from node i to node j; If equation (6) does not hold, set the branch as the line to be corrected; otherwise, obtain the correction parameters using the branch parameters and perform the correction.

4. A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy according to claim 1, characterized in that, The calculation process of the voltage at the beginning and end of the line to be corrected is as follows: Back-substitute the voltage from the first node, and use equations (7) and (8) to obtain the voltage vectors at the beginning and end of the line to be corrected: In formula (7), is the voltage vector of node i; In Equation (8), is the current vector of the branch from node i to node j.

5. A method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy according to claim 1, characterized in that, The process of substituting the correction parameters into the forward-backward substitution for state estimation of the distribution network and further correcting the branch parameters of the distribution network based on the forgetting factor least squares recursive method is as follows: Substitute the correction parameters into the forward-backward substitution for state estimation of the distribution network: h = xΦ (13) In Equation (13), h is the state estimator, x is the branch parameter matrix, Φ I is the current data matrix, Φ P is the active power data matrix, Φ Q is the reactive power data matrix, and B is the intermediate variable; Real-time correct the parameters based on the forgetting factor least squares recursive method: In Equation (16), t is the number of iterations, λ is the forgetting factor, x t and x t-1 are the branch parameter matrices at the t-th and (t - 1)-th times, K t is the gain matrix at the t-th time, P t and P k-1 are the covariance matrices at the t-th and (t - 1)-th times, Φ t and Φ t T are the data matrix at the t-th time and the transpose of the data matrix, and E is the identity matrix.

6. A device, characterized in that, comprises: one or more processors; a memory for storing one or more programs; When one or more of the said programs are executed by one or more of the said processors, one or more of the said processors implement a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy as described in any one of claims 1-5.

7. A storage medium containing computer-executable instructions, characterized in that, the computer-executable instructions are used to execute a method for correcting distribution network parameters based on forward-backward substitution and measurement redundancy as described in any one of claims 1-5 when executed by a computer processor.

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