Active low-voltage power distribution network topology identification method based on voltage correlation and energy balance and computer medium

Abstract

The invention discloses an active low-voltage distribution network topology identification method based on voltage correlation and energy balance. The method comprises the following steps: S1, obtaining distribution transformer information and terminal user information; the distribution transformer information comprises basic measurement data of the distribution transformer; the terminal user information comprises position information, voltage characteristics and power characteristics of a user; s2, performing preset processing on the distribution transformer information to obtain a first data set; performing preset processing on the terminal user information to obtain a second data set; s3, dividing user ownership according to the first data set and the second data set in combination with a voltage correlation principle to obtain a first result; identifying a topological relation according to the first data set and the second data set in combination with an energy balance principle to obtain a second result; s4, comparing the first result with the second result to obtain a first difference value set; and correcting the topological relation according to the first difference value set to obtain a third result, and completing topology identification.

Description

Technical Field

[0001] The present invention relates to the field of active low-voltage distribution network topology identification, and in particular to an active low-voltage distribution network topology identification method based on voltage correlation and energy balance and a computer medium. Background Art

[0002] The topological structure of the distribution network refers to the topological connection relationship between the end-user meter and the transformer in the distribution area, and is an important part of the distribution network. Correctly identifying the topological relationship of the active low-voltage distribution network is an important guarantee for carrying out short-circuit fault location, capacity expansion and transformation of existing lines, and line loss reduction. Therefore, accurate identification of the topological structure of the active low-voltage distribution network plays a key role in achieving safe and stable operation of the distribution network.

[0003] However, with the massive access of distributed resources in the distribution network at this stage, the distribution network power flow has reversed, the operating conditions have become increasingly complex, the correlation of user voltage time series data has weakened, and the line loss has increased, resulting in an increase in the error of the traditional distribution network topology identification method using voltage and power, which has brought major challenges to the actual distribution network topology identification problem.

[0004] Therefore, a new technical solution is urgently needed to solve the technical problem of how to accurately identify the topology structure of an active low-voltage distribution network that is connected to a large number of distributed resources. Summary of the invention

[0005] The present invention provides an active low-voltage distribution network topology identification method and computer medium based on voltage correlation and energy balance, which are used to solve the technical problem of how to accurately identify the topology structure of an active low-voltage distribution network that is connected to a large number of distributed resources.

[0006] To achieve the above object, the present invention provides an active low-voltage distribution network topology identification method based on voltage correlation and energy balance, comprising the following steps:

[0007] S1. Obtain distribution transformer information and terminal user information; the distribution transformer information includes basic measurement data of the distribution transformer; the terminal user information includes the user's location information, voltage characteristics and power characteristics.

[0008] S2. Preset processing is performed on the distribution transformer information to obtain a first data set; and preset processing is performed on the terminal user information to obtain a second data set.

[0009] S3. Divide the user affiliation according to the first data set and the second data set in combination with the voltage correlation principle to obtain a first result; identify the topological relationship according to the first data set and the second data set in combination with the energy balance principle to obtain a second result.

[0010] S4. Compare the first result with the second result to obtain a first difference set; modify the topological relationship according to the first difference set to obtain a third result, and complete the topological identification.

[0011] Preferably, S2 comprises:

[0012] Assume that there are a distribution transformers and b end users in the area to be identified. The set A of distribution transformers and the set B of end users are:

[0013] A={1,2,...,a}

[0014] B = {1, 2, ..., b}

[0015] The distribution transformer information is sorted to obtain the first data set. The voltage time series data U of the αth distribution transformer in the first data set is Aα And power timing data P Aα for:

[0016] U Aα =[u Aα1 ,u Aα2 ,…,u Aαt , ..., u AαW ] T

[0017] P Aα =[p Aα1 , p Aα2 , ..., p Aαt , ..., p AαW ] T

[0018] Among them, u Aαt is the voltage of the αth distribution transformer at time t; p Aαt is the power of the αth distribution transformer at time t; W is the data length; t and α are positive integers, t=1,2,...W,α=1,2,...a; T is the transposition operator symbol.

[0019] The terminal user information is sorted to obtain a second data set, and the voltage time series data U of the βth terminal user in the second data set is Bβ And power timing data P Bβ for:

[0020] U Bβ =[u Bβ1 ,u Bβ2 , ..., u Bβt , ..., u BβW ] T

[0021] P Bβ =[pBβ1 , p Bβ2 , ..., p Bβt , ..., p BβW ] T

[0022] Among them, u Bβt is the voltage of the βth terminal user at time t; p Bβt is the power of the βth terminal user at time t; β is a positive integer, β = 1, 2, ...b.

[0023] Preferably, in S3, the user affiliation is divided according to the first data set and the second data set in combination with the voltage correlation principle, and the first result obtained includes:

[0024] S31. Analyze the voltage characteristics of the low-voltage distribution network according to the first data set and the second data set to obtain a first voltage characteristic.

[0025] S32. Calculate voltage correlations between all distribution transformers and all end users according to the first voltage characteristic.

[0026] S33. Obtain a first result.

[0027] Preferably, S31 includes:

[0028] By analyzing the relationship between voltage fluctuation and power change, the voltage relationship between the end user and the distribution transformer is obtained according to the voltage drop formula, which can be expressed by the following relationship:

[0029]

[0030] Among them, U0 is the outgoing line voltage on the low voltage side of the distribution transformer; U i is the voltage of end user i; R j and X j is the resistance and reactance of distribution branch j; P Lj and Q Lj are the active power and reactive power of distribution branch j; i = 1, 2, ... n, where n is the number of terminal users.

[0031] In the substation area, the reactive power transmitted by the line is small, and the reactive power loss of the low-voltage line is small and can be ignored. The above formula can be simplified to:

[0032]

[0033] Among them, P k is the active power injected into end user k; P kloss is the line loss of distribution branch k.

[0034] That is, for end users on the same line, the voltage variation trends are similar, and the similarity increases as the electrical distance decreases.

[0035] Preferably, S32 includes:

[0036] S321, use Pearson correlation coefficient to calculate voltage correlation, the correlation coefficient r between distribution transformer α and end user β α，β It can be expressed by the following relationship:

[0037]

[0038] Among them, u Aαt is the voltage of the αth distribution transformer at time t; u Bβt is the voltage of the βth terminal user at time t.

[0039] Calculate the voltage correlation between the βth terminal user and each element in the distribution transformer set A, and obtain the voltage correlation set R of the βth terminal user β :

[0040] R β = {r 1，β , r 2，β , ..., r a，β}

[0041] Assume R β The largest element in is r a′，β ,Right now:

[0042] r α′β =maxR β

[0043] Here, α′ is a positive integer between 1 and a.

[0044] It is considered that the βth terminal user belongs to the α′th distribution transformer.

[0045] S322 , calculating the voltage correlation of each terminal user in the terminal user set B, and obtaining the belonging relationship of each terminal user.

[0046] Preferably, in S3, the topological relationship is identified based on the first data set and the second data set in combination with the energy balance principle to obtain the second result, which includes:

[0047] Define a two-dimensional variable x α，β , used to indicate whether the βth end user belongs to the αth distribution transformer; when x α，β =1, indicating that the βth end user belongs to the αth distribution transformer; when x α，β = 0, indicating that the βth end user does not belong to the αth distribution transformer; define the vector X αRepresents the topological relationship of the αth distribution transformer, and defines the matrix X to represent the topological relationship of all distribution transformers:

[0048] X α =[x α,1 , x α，2 , ..., x α，b ] T

[0049] X=[X1,X2,...,X a ] T

[0050] Wherein, a is the number of distribution transformers in the area to be identified; b is the number of terminal users in the area to be identified; α = 1, 2, ...a; β = 1, 2, ...b.

[0051] Define Q as a matrix composed of a sub-matrices q arranged along the diagonal direction:

[0052]

[0053] The number of rows in the Q matrix is ​​a×W, and the number of columns is a×b, where W is the length of the time series data.

[0054] Define ξ as the error vector, then considering the error, the power relationship P in the distribution network is:

[0055] P=QX T +ξ

[0056] Among them, X T is the transposed matrix of matrix X.

[0057] Therefore, the problem of solving the subordinate relationship between distribution transformers and terminal users is transformed into a quadratic programming problem, and a quadratic programming model is obtained; and the second result is obtained by solving the quadratic programming model.

[0058] Preferably, the quadratic programming model includes:

[0059] The objective function can be expressed by the following relationship:

[0060] min||P-QX T || 2

[0061] The constraints can be expressed by the following relationship:

[0062]

[0063] Preferably, S4 includes:

[0064] S41, define the first result as N1, define the second result as N2; compare the topological relationship between N1 and N2, obtain the different parts as the first difference set N, and obtain the same parts as N3.

[0065] S42, constructing a target terminal user address information database based on existing terminal user data; dividing the user location information in the target terminal user address information database into a preset number of levels according to a preset location level planning.

[0066] S43. Compare the first difference set N with the elements in the target terminal user address information database, retain the part corresponding to the topological connection relationship match as the first part, conduct field verification on the part that cannot be matched with the topological connection relationship to obtain the second part, and splice the first part, the second part and N3 to obtain the third result, thereby completing the topology identification.

[0067] The present invention also provides a computer medium, comprising a processor, a memory and a computer program for implementing the method of the present invention.

[0068] The present invention has the following beneficial effects:

[0069] The active low-voltage distribution network topology identification method based on voltage correlation and energy balance of the present invention analyzes the user affiliation and the distribution network topology relationship based on the voltage correlation principle and the energy balance principle respectively, and then compares and analyzes the analysis results of the two schemes and corrects them, so that the present invention integrates the advantages of the two schemes, overcomes the defects that the affiliation cannot be determined due to single voltage characteristics being too similar or the flow being reversed, optimizes the identification process, and further improves the identification accuracy; through the mutual verification of the two schemes, the method of the present invention can realize the accurate topology structure identification of the active low-voltage distribution network that is connected to a large number of distributed resources.

[0070] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0072] Figure 1 It is a flow chart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0073] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims.

[0074] See also Figure 1 In a preferred embodiment of the present invention, a method for identifying topology of an active low-voltage distribution network based on voltage correlation and energy balance is provided, comprising the following steps:

[0075] S1. Obtain distribution transformer information and terminal user information; the distribution transformer information includes basic measurement data of the distribution transformer; the terminal user information includes the user's location information, voltage characteristics and power characteristics.

[0076] S2, pre-processing the distribution transformer information to obtain a first data set; pre-processing the terminal user information to obtain a second data set. S2 specifically includes:

[0077] Assume that there are a distribution transformers and b end users in the area to be identified. The set A of distribution transformers and the set B of end users are:

[0078] A={1,2,...,a}

[0079] B = {1, 2, ..., b}

[0080] The distribution transformer information is sorted to obtain the first data set. The voltage time series data U of the αth distribution transformer in the first data set is Aα And power timing data P Aα for:

[0081] U Aα =[u Aα1 ,u Aα2 , ..., u Aαt , ..., u AαW ] T

[0082] P Aα =[p Aα1 , p Aα2 , ..., p Aαt , ..., p AαW ] T

[0083] Among them, u Aαt is the voltage of the αth distribution transformer at time t; p Aαt is the power of the αth distribution transformer at time t; W is the data length; t and α are positive integers, t=1,2,...W, α=1,2,...a; T is the transposition operator symbol;

[0084] The terminal user information is sorted to obtain a second data set, and the voltage time series data U of the βth terminal user in the second data set is Bβ And power timing data P Bβ for:

[0085] U Bβ =[u Bβ1 ,u Bβ2 , ..., u Bβt , ..., u BβW ] T

[0086] P Bβ =[p Bβ1 , p Bβ2 , ..., p Bβt , ..., p BβW ] T

[0087] Among them, u Bβt is the voltage of the βth terminal user at time t; p Bβt is the power of the βth terminal user at time t; β is a positive integer, β = 1, 2, ...b.

[0088] S3. Divide the user affiliation according to the first data set and the second data set in combination with the voltage correlation principle to obtain a first result; identify the topological relationship according to the first data set and the second data set in combination with the energy balance principle to obtain a second result.

[0089] (1) In S3, the user affiliation is divided according to the first data set and the second data set in combination with the voltage correlation principle, and the first result obtained specifically includes:

[0090] S31. Analyze the voltage characteristics of the low-voltage distribution network according to the first data set and the second data set to obtain a first voltage characteristic. S31 specifically includes:

[0091] By analyzing the relationship between voltage fluctuation and power change, the voltage relationship between the end user and the distribution transformer is obtained according to the voltage drop formula, which can be expressed by the following relationship:

[0092]

[0093] Among them, U0 is the outgoing line voltage on the low voltage side of the distribution transformer; U i is the voltage of end user i; R j and X j is the resistance and reactance of distribution branch j; P Lj and Q Lj is the active power and reactive power of distribution branch j; i = 1, 2, ... n, n is the number of terminal users;

[0094] In the substation area, the reactive power transmitted by the line is small, and the reactive power loss of the low-voltage line is small and can be ignored. The above formula can be simplified to:

[0095]

[0096] Among them, P k is the active power injected into end user k; P kloss is the line loss of distribution branch k;

[0097] In low-voltage distribution networks, the voltage of end users gradually decreases along the line, and end users with similar electrical distances have similar voltage change trends. That is, the voltage change trends of end users on the same line are similar, and the similarity increases as the electrical distance decreases.

[0098] S32, calculating the voltage correlation between all distribution transformers and all end users according to the first voltage characteristic. S32 specifically includes:

[0099] S321. Use the Pearson correlation coefficient to calculate the voltage correlation. The Pearson correlation coefficient is a method to measure the similarity between two variables. Its value is between -1 and 1, where 0 represents no correlation between the two variables, 1 represents a perfect positive correlation between the two variables, and -1 represents a perfect negative correlation between the two variables. The correlation between the two variables can be determined based on the absolute value of the Pearson correlation coefficient. The larger the absolute value, the stronger the correlation.

[0100] Correlation coefficient r between distribution transformer α and end user β α，β It can be expressed by the following relationship:

[0101]

[0102] Among them, u Aαt is the voltage of the αth distribution transformer at time t; u Bβt is the voltage of the βth terminal user at time t;

[0103] Calculate the voltage correlation between the βth terminal user and each element in the distribution transformer set A, and obtain the voltage correlation set R of the βth terminal user β :

[0104] R β = {r 1，β , r 2，β , ..., r a， β}

[0105] Assume R β The largest element in is r a′，β ,Right now:

[0106] r α′β =maxR β

[0107] Among them, α′ is a positive integer between 1 and a;

[0108] It is considered that the βth terminal user belongs to the α′th distribution transformer;

[0109] S322 , calculating the voltage correlation of each terminal user in the terminal user set B, and obtaining the belonging relationship of each terminal user.

[0110] S33. Obtain a first result.

[0111] In a preferred embodiment of the present invention, the user affiliation is divided according to the voltage correlation principle, so that the corresponding part of the method is simple and convenient to calculate.

[0112] (2) In S3, the topological relationship is identified based on the first data set and the second data set in combination with the energy balance principle, and the second result obtained specifically includes:

[0113] Define a two-dimensional variable x α，β , used to indicate whether the βth end user belongs to the αth distribution transformer; when x α，β =1, indicating that the βth end user belongs to the αth distribution transformer; when x α，β = 0, indicating that the βth end user does not belong to the αth distribution transformer; define the vector X α Represents the topological relationship of the αth distribution transformer, and defines the matrix X to represent the topological relationship of all distribution transformers:

[0114] X α =[x α,1 , x α，2 , ..., x α，b ] T

[0115] X=[X1,X2,...,X a ] T

[0116] Where a is the number of distribution transformers in the area to be identified; b is the number of end users in the area to be identified; α = 1, 2, ... a; β = 1, 2, ... b;

[0117] Define Q as a matrix composed of a sub-matrices q arranged along the diagonal direction:

[0118]

[0119] Among them, the number of rows of the Q matrix is ​​a×W, and the number of columns is a×b, where W is the length of the time series data;

[0120] Define ξ as the error vector, then considering the error, the power relationship P in the distribution network is:

[0121] P=QX T +ξ

[0122] Among them, X T is the transposed matrix of matrix X;

[0123] Therefore, the problem of solving the subordinate relationship between distribution transformers and terminal users is transformed into a quadratic programming problem, and a quadratic programming model is obtained; and the second result is obtained by solving the quadratic programming model.

[0124] In a preferred embodiment of the present invention, the quadratic programming model includes:

[0125] The objective function can be expressed by the following relationship:

[0126] min||P-QX T || 2

[0127] The constraints can be expressed by the following relationship:

[0128]

[0129] S4, comparing the first result with the second result to obtain a first difference set; modifying the topological relationship based on the first difference set combined with a fuzzy identification method to obtain a third result, and completing topological identification. S4 specifically includes:

[0130] S41, define the first result as N1, define the second result as N2; compare the topological relationship between N1 and N2, obtain the different parts as the first difference set N, and obtain the same parts as N3.

[0131] S42, constructing a target terminal user address information database based on existing terminal user data; dividing the user location information in the target terminal user address information database into a preset number of levels according to a preset location level planning.

[0132] In a preferred embodiment of the present invention, a terminal user address information database is constructed based on terminal user data obtained from a power distribution system, a metering system, and a geographic information system (GIS). According to the "Place Name Address Data Specification", the electricity address is grammatically segmented. The electricity address is divided into 10 levels (Level 1-Level 10), and the meanings are as follows: Level 1 represents provinces, autonomous regions, etc., Level 2 represents cities, etc., Level 3 represents counties, districts, etc., Level 4 represents towns, townships, etc., Level 5 represents streets, roads, avenues, etc., Level 6 represents communities, gardens, flower gardens, etc., Level 7 represents buildings, buildings, etc., Level 8 represents unit numbers, etc., Level 9 represents floor numbers, etc., and Level 10 represents numbers, rooms, rooms, etc. From Level 1 to Level 10, the address jurisdiction of each level gradually shrinks.

[0133] S43. Compare the first difference set N with the elements in the target terminal user address information database, retain the part corresponding to the topological connection relationship match as the first part, conduct field verification on the part that cannot be matched with the topological connection relationship to obtain the second part, and splice the first part, the second part and N3 to obtain the third result, thereby completing the topology identification.

[0134] In a preferred embodiment of the present invention, the recognition accuracy of the method of the present invention is further improved by comparing the first result and the second result, checking the different parts against the constructed database, and conducting field verification on the unmatched parts of the check results.

[0135] In a preferred embodiment of the present invention, a computer medium is also provided, including a processor, a memory, and a computer program for implementing the method of the present invention.

[0136] In summary, the active low-voltage distribution network topology identification method based on voltage correlation and energy balance of the present invention analyzes the user affiliation and distribution network topology relationship based on the voltage correlation principle and the energy balance principle, respectively, and then compares and analyzes the analysis results of the two schemes and corrects them, so that the present invention integrates the advantages of the two schemes, overcomes the defects that the affiliation cannot be determined due to the single voltage characteristics being too similar or the flow being reversed, optimizes the identification process, and further improves the identification accuracy; through the mutual verification of the two schemes, the method of the present invention can realize the accurate topology structure identification of the active low-voltage distribution network that is connected to a large number of distributed resources.

[0137] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for identifying active low-voltage distribution network topology based on voltage correlation and energy balance, characterized in that: The following steps are involved: S1. Obtain distribution transformer information and terminal user information; the distribution transformer information includes basic measurement data of the distribution transformer; the terminal user information includes user location information, voltage characteristics and power characteristics; S2, pre-processing the distribution transformer information to obtain a first data set; pre-processing the terminal user information to obtain a second data set; S3, dividing the user affiliation according to the first data set and the second data set in combination with the voltage correlation principle to obtain a first result; Identify the topological relationship based on the first data set and the second data set in combination with the energy balance principle to obtain a second result; S4. Compare the first result with the second result to obtain a first difference value set; The topological relationship is corrected according to the first difference set to obtain a third result, thereby completing the topological identification.

2. The active low-voltage distribution network topology identification method based on voltage correlation and energy balance according to claim 1 is characterized in that: The S4 includes: S41, define the first result as N1, define the second result as N2; compare the topological relationship between N1 and N2, obtain the different parts as the first difference set N, and obtain the same parts as N3; S42, constructing a target terminal user address information database based on existing terminal user data; dividing the user location information in the target terminal user address information database into a preset number of levels according to a preset location level plan; S43. Compare the first difference set N with the elements in the target terminal user address information database, retain the part corresponding to the topological connection relationship match as the first part, conduct field verification on the part that cannot match the topological connection relationship to obtain the second part, splice the first part, the second part and N3 to obtain the third result, and complete the topology identification.

3. The active low-voltage distribution network topology identification method based on voltage correlation and energy balance according to claim 2 is characterized in that: The S2 includes: Assume that there are a distribution transformers and b end users in the area to be identified. The set A of distribution transformers and the set B of end users are: A={1,2,...,a} B = {1, 2, ..., b} The distribution transformer information is sorted to obtain a first data set, in which the voltage time series data U of the αth distribution transformer in the first data set is Aα And power timing data P Aα for: IN Aα =[in Aα1 ,in Aα2 ,...,in Aαt ,...,in AαW ] T P Aα =[p Aα1 ,p Aα2 ,...,p Aαt ,...,p AαW ] T Among them, u Aαt is the voltage of the αth distribution transformer at time t; p Aαt is the power of the αth distribution transformer at time t; W is the data length; t and α are positive integers, t=1,2,...W, α=1,2,...a; T is the transposition operator symbol; The terminal user information is sorted to obtain a second data set, and the voltage time series data U of the βth terminal user in the second data set is Bβ And power timing data P Bβ for: IN Bβ =[in Bβ1 ,in Bβ2 ,...,in Bβt ,...,in BβW ] T P Bβ =[p Bβ1 ,p Bβ2 ,...,p Bβt ,...,p BβW ] T Among them, u Bβt is the voltage of the βth terminal user at time t; p Bβt is the power of the βth terminal user at time t; β is a positive integer, β = 1, 2, ...b.

4. The active low-voltage distribution network topology identification method based on voltage correlation and energy balance according to claim 3 is characterized in that: In S3, the user affiliation is divided according to the first data set and the second data set in combination with the voltage correlation principle to obtain the first result, which includes: S3 1. Analyze the voltage characteristics of the low-voltage distribution network according to the first data set and the second data set to obtain a first voltage characteristic; S32. Calculating the voltage correlation between all distribution transformers and all end users according to the first voltage characteristic; S33. Obtain the first result.

5. The method for identifying topology of active low-voltage distribution network based on voltage correlation and energy balance according to claim 4 is characterized in that: The S31 includes: By analyzing the relationship between voltage fluctuation and power change, the voltage relationship between the end user and the distribution transformer is obtained according to the voltage drop formula, which can be expressed by the following relationship: Among them, U0 is the outgoing line voltage on the low voltage side of the distribution transformer; U i is the voltage of end user i; R j and X j is the resistance and reactance of distribution branch j; P Lj and Q Lj is the active power and reactive power of distribution branch j; i = 1, 2, ... n, n is the number of terminal users; In the substation area, the reactive power transmitted by the line is small, and the reactive power loss of the low-voltage line is small and can be ignored. The above formula can be simplified to: Among them, P k is the active power injected into end user k; P kloss is the line loss of distribution branch k; That is, for end users on the same line, the voltage variation trends are similar, and the similarity increases as the electrical distance decreases.

6. The method for identifying topology of active low-voltage distribution network based on voltage correlation and energy balance according to claim 5, characterized in that: The S32 includes: S321, use Pearson correlation coefficient to calculate voltage correlation, the correlation coefficient r between distribution transformer θ and end user β α，β It can be expressed by the following relationship: Among them, u Aαt is the voltage of the αth distribution transformer at time t; u Bβt is the voltage of the βth terminal user at time t; Calculate the voltage correlation between the βth end user and each element in the distribution transformer set A, and obtain the voltage correlation set R of the βth end user β : R β ＝{r 1，β ，r 2，β ，...，r a，β} Assume R β The largest element in is r a′，β ,Right now: r α′β =max R β Among them, α′ is a positive integer between 1 and a; It is considered that the βth terminal user belongs to the α′th distribution transformer; S322 , calculating the voltage correlation of each terminal user in the terminal user set B, and obtaining the belonging relationship of each terminal user.

7. The method for identifying topology of active low-voltage distribution network based on voltage correlation and energy balance according to claim 6, characterized in that: In S3, the topological relationship is identified based on the first data set and the second data set in combination with the energy balance principle to obtain the second result, which includes: Define a two-dimensional variable xα, β to indicate whether the βth terminal user belongs to the αth distribution transformer; when xα, β = 1, it means that the βth terminal user belongs to the αth distribution transformer; when x α，β = 0, indicating that the βth end user does not belong to the αth distribution transformer; define the vector X α Represents the topological relationship of the αth distribution transformer, and defines the matrix X to represent the topological relationship of all distribution transformers: X α =[x α,1 ,x α，2 ,...,x α，b ] T X=[X1,X2,...,X α ] T Wherein, a is the number of distribution transformers in the area to be identified; b is the number of end users in the area to be identified; α = 1, 2, ...a; β = 1, 2, ...b; Define Q as a matrix composed of a sub-matrices q arranged along the diagonal direction: Among them, the number of rows of the Q matrix is ​​a×W, and the number of columns is a×b, where W is the length of the time series data; Define ξ as the error vector, then considering the error, the power relationship P in the distribution network is: P=QX T +ξ Among them, X T is the transposed matrix of matrix X; Therefore, the problem of solving the subordinate relationship between the distribution transformer and the terminal user is transformed into a quadratic programming problem to obtain a quadratic programming model; and the second result is obtained by solving the quadratic programming model.

8. The method for identifying topology of active low-voltage distribution network based on voltage correlation and energy balance according to claim 7, characterized in that: The quadratic programming model includes: The objective function can be expressed by the following relationship: min||P-QX T ||2 The constraints can be expressed by the following relationship:

9. A computer medium, characterized in that The invention comprises a processor, a memory and a computer program for implementing the method according to any one of claims 1 to 8.

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