CN108683180A - A kind of three-phase low-voltage power distribution network topology rebuilding method - Google Patents

Abstract

A method for topology reconstruction of a three-phase low-voltage distribution network. Based on the sequential voltage data of the low-voltage distribution network, the present invention obtains the sequential voltage from the smart meter on the user side. Firstly, the correlation coefficient between the bus voltage data and the reference voltage is obtained by using the method of correlation analysis, and the phase with the largest correlation coefficient is identified. Complete the phase identification process to obtain the phase connection information of each bus. Divide all buses into three groups of phase A, phase B, and phase C according to their phases, and use the Chow-Liu algorithm to obtain the cross-correlation information among the above three groups of buses Matrix, and then use the cross-correlation information to complete the topology reconstruction of the three groups of undirected networks, and finally integrate the three groups of reconstructed undirected networks to obtain a complete topological network structure.

Description

A three-phase low-voltage distribution network topology reconstruction method

technical field

The invention belongs to the technical field of electric power system power distribution, and in particular relates to a technology for reconstructing the topology of end users of a three-phase low-voltage power distribution network by using time series voltage data of a power distribution network.

Background technique

With the development of technology, intelligent monitoring equipment has been able to accurately monitor the information of high-voltage and medium-voltage power grids. Unauthorized modification of lines and other issues, the phase information on the user side of the three-phase low-voltage distribution network is often incomplete or wrong. However, the network topology information of the three-phase low-voltage distribution network is essential for the safe and stable operation of the network, and the accurate phase information at the user level is also of great significance to improve the operation performance of the three-phase low-voltage distribution network, for example, by adjusting the three-phase Balancing reduces system losses, etc.

At present, in the topology research of power system, most of them study the topology error identification and topology change of the high-voltage or medium-voltage power grid. They mainly use the knife switch remote signal matrix to reconstruct the network, but this method has the error of pseudo-measurement equipment. As a result, the accuracy of the results is not high, and because the low-voltage distribution network has not yet fully installed monitoring equipment, it is impossible to use the method of topology research on the high- and medium-voltage distribution network. For the identification method of the grid phase, the existing μPMU-based power line transmission phase data is used to monitor the phase of the distribution network, but the power line transmission signal has disadvantages such as a high bit error rate. In addition, this method also requires the installation of a large number of μPMU devices on the user side. However, the low-voltage distribution network has not yet been fully deployed and installed. Moreover, the existing technology fails to process the identification of the phase of the distribution network and the identification of the topology synchronously. With the large number of smart meters connected to the user side of the low-voltage distribution network, the voltage and power consumption data of the three-phase low-voltage distribution network can be monitored. The generation of a large amount of data provides the possibility for data-driven topological network structure reconstruction.

It can be seen that in the prior art, the following problems exist in the reconstruction of distribution network topology:

1. At present, the phase is not distinguished in the topological network reconstruction problem based on the time-series voltage data of the distribution network;

2. The research on power system topology is mostly limited to the identification of transmission network topology errors and the detection of topology changes. However, at present, the distribution network is frequently updated and the wiring is complicated. Massive data make it difficult to realize distribution network topology identification.

Contents of the invention

In order to solve the above problems in the prior art, the present invention proposes a three-phase low-voltage distribution network topology reconstruction method. The technical solution disclosed in the present invention first identifies the phases of the three-phase low-voltage distribution network, and then reconstructs different The data-driven method of the network topology under the phase, the data-driven method does not require prior knowledge such as the topology connection relationship of the low-voltage distribution network, switch deployment and status, and only uses the data of the smart meter to realize the phase identification and topology of the distribution network as a whole. reconstruction.

In order to realize the purpose of the above invention, the present invention specifically adopts the following technical solutions.

A three-phase low-voltage distribution network topology reconstruction method, characterized in that: firstly, based on the time-series voltage data association analysis to identify the specific phase of the bus, for three groups of different phases, respectively use the Chow-Liu Algorithms are used to reconstruct the topological structure of the three-phase low-voltage power distribution network, and finally the three obtained networks are integrated to obtain a complete topological network structure.

The three-phase low-voltage distribution network topology reconstruction method includes the following steps:

Step 1: Obtain time series voltage data from the smart meter on the user side;

Step 2: In each station area, the power distribution network is abstracted into a graph model G=(M,S), and the busbar is represented by the nodes of the graph model, that is, M={i,i=1,2,…,N} , the branches are represented by the edges of the graph model, that is, S={l _i,j ,i,j∈M}; where, G is the graph model of the distribution network, M is the node set of the distribution network, and N is the maximum number of nodes , S is the branch set of the distribution network, l _i,j is the branch connecting node i and node j;

Step 3: Given a time window T _p and a time interval T, obtain a voltage value of a smart meter every time interval T, a total of D voltage values are collected to form a voltage vector U _i , where D=T _p /T, U _i represents The vector composed of the voltage of bus i in the whole time window, select the timing voltages of the bus bars closest to the transformer that belong to phase A, phase B and phase C respectively as the reference, respectively recorded as:

U _ph = {u _ph ; ph = A, B, C};

Step 4: Calculate the correlation coefficient between the sequence voltage U _i of bus i and U _A , U _B , U _C , denoted as ρ _i,A , ρ _i,B , ρ _i,C respectively; for bus i, select ρ _{i , A} , ρ _{i, B} , ρ _{i, C} is the largest one, its corresponding phase is the identified phase of the bus, and all the buses in the distribution network are calculated cyclically;

Step 5: Add all buses in step 4 to the three categories of phase A, phase B and phase C;

Step 6: Obtain the three sets of cross-correlation information of the three sets of buses in step 5 respectively cross-correlation information is the weight value obtained according to the Chow-Liu algorithm, according to the cross-correlation information Carry out topology network reconstruction respectively;

Step 7: Find the correlation coefficient between the sequential voltages of the busbars belonging to phase A, phase B and phase C as the reference, and integrate the reconstructed topological network of phase A, phase B and phase C to form a complete topological network structure .

The present invention further includes the following preferred solutions.

In step 4, the correlation coefficient between the sequence voltage U _i of other buses and the reference sequence voltage U _ph of the corresponding phase is calculated according to the following formula:

Where Cov(U _i , U _ph ) is the covariance of U _i , U _ph variables, is the standard deviation of the two voltage variables.

In step 6, the cross-correlation information between different groups of buses Calculated according to the following formula:

where f _uv (i, j) is the maximum likelihood estimate of P(u _i =u, u _j =v), f _u (i) is the maximum likelihood estimate of P(u _i =u), f _v (j ) is the maximum likelihood estimate of P(u _j =v), P(u _i =u, u _j =v) refers to the joint probability when u _i =u, u _j =v, P(u _i =u) is the probability when u _i =u, and P(u _j =v) is the probability when u _j =v.

In step 6, according to the cross-correlation information The topology network reconstruction respectively includes the following contents:

6.1 For each phase, select the bus a with the largest correlation coefficient between the bus voltage and the reference voltage;

6.2 Based on cross-correlation information Select bus b with the highest cross-correlation information with bus a;

6.3 Repeat step 6.2 until all buses belonging to the phase are connected.

In step 7, specifically include the following:

7.1 Calculate the correlation coefficient between the three reference voltages of the three phases;

7.2 According to the obtained results, connect three groups of voltages, that is, connect the reference bus with a large correlation coefficient between the voltages of the reference bus. The present invention has the following beneficial technical effects:

The invention uses the Chow-Liu algorithm to obtain the mutual correlation information between the busbars to complete the topology reconstruction of the network, and obtain the network connection relationship of the low-voltage user side of the distribution network, which is helpful for repairing and locating, analyzing and judging distribution network faults, and optimizing power outage plans. . In addition, the process of phase identification is introduced when rebuilding the network structure, which solves the problem of incomplete phase information on the low-voltage user side of the distribution network, and then can use the phase information to detect network imbalance problems to solve system line loss and energy consumption problems, and at the same time facilitate the introduction of The regenerative energy enters the user network.

Description of drawings

Figure 1 is a schematic diagram of a three-phase low-voltage distribution network entering a household;

Figure 2 is a schematic diagram of three-phase low-voltage distribution network topology reconstruction;

Fig. 3 is a schematic flow chart of the method for reconstructing the topology of the three-phase low-voltage distribution network according to the present invention.

Detailed ways

The technical solutions of the present invention will be further introduced in detail below in conjunction with the accompanying drawings and specific embodiments.

The invention proposes a method of first identifying and distinguishing the phases of the busbars, and then performing the topology reconstruction of the distribution network.

As shown in Figure 1 and Figure 2, in the distribution network, electric energy enters the distribution box of the end user after passing through the general power distribution room, the first-level power distribution equipment and the second-level power distribution equipment. The task of the first-level power distribution equipment here is to transform the medium voltage of 10kV into a low voltage (system voltage) of 400V/230V, where 400V is the voltage between the three phases (that is, three phases A, B, and C) Value, 230V is the phase voltage of the three phase lines relative to the neutral line. Due to the large number of end users, only relying on the first-level power distribution equipment to distribute electric energy will cause the equipment to be too large and complex, so the second-level power distribution equipment is used to carry out second-level distribution of electric energy. After passing through the second-level power distribution equipment, the output voltage drops to 380V/220V (Standard Voltage). The home power distribution cable of the secondary equipment transmits electric energy to the meter box of the end user, among which the home power distribution cable has three phase lines, and the meter box of the end user is single-phase electricity, in order not to cause waste , the neutral wire N will be split into two more, and thus connected to the three-phase live wires, that is, "live wire a+neutral wire", "live wire b+ neutral wire", "live wire c+neutral wire" three groups, and then the obtained three groups of electricity according The actual situation is allocated to each end user, and the architecture of the three-phase home access is shown in Figure 1.

As shown in Figure 3, it is a schematic flow chart of the three-phase low-voltage distribution network topology reconstruction method of the present invention. The three-phase low-voltage distribution network topology reconstruction method disclosed by the present invention includes the following steps:

Step 1: Obtain time series voltage data from the smart meter on the user side;

Since each end user is connected to the transmission line in a single-phase manner, and the connection information of the end users on the low-voltage feeder is mostly incomplete or missing, so which one we use for most end users The phase lines are unknown. To solve this problem, we obtain the time-series voltage data of the user's smart meter, and use correlation analysis to identify the phase information of the end user.

Step 2: Abstract the distribution network into a graph model

In order to describe the network and parameters of the distribution network in the process of phase identification and topology reconstruction, the following definitions are made. In each station area, the power distribution network consists of several buses and branches. It is abstracted as a graph model G=(M,S), the bus is represented by the nodes of the graph model, that is, M={i,i=1,2,...,N}, and the branches are represented by the edges of the graph model, that is, S= {l _i,j ,i,j∈M}.

Step 3: Choose a reference voltage

Since the variation trends of the voltage curves of different phases over time are different, the correlation between voltage curves with the same phase over time is stronger than that between voltage curves with different phases over time. Therefore, according to the correlation between the voltages, the correlation coefficients between the bus bars and the time-series voltage data belonging to the A phase, B phase and C phase can be obtained through the correlation analysis method. The larger the correlation coefficient is, the higher the degree of correlation is. By selecting Maximum correlation coefficient for phase identification.

Since the sequential voltage data of the bus takes into account the voltage drop along the line, for different buses along the line, the voltage amplitude is different at different positions from the transformer, and the bus with the closest electrical distance to the transformer has a higher sequential voltage amplitude. Given a time window _Tp and a time interval T, select the sequential voltages of the busbars that belong to phase A, phase B, and phase C that are closest to the transformer as references, which are denoted as

U _ph = {u _ph ; ph=A, B, C},

Step 4: Obtain the voltage of each bus node, and calculate the correlation coefficient between each bus and the reference voltage for phase identification

Select the same time window T _p and time interval T to obtain the time-series voltage data of the remaining buses, recorded as U _i ={u _i ; i=1,2,...,N}, where N is the number of all buses.

According to the principle of cross-correlation, that is, for two variables X, Y, calculate the correlation coefficient of X, Y, as follows:

Among them, Cov(X,Y)=E[(X-μ _X )(X-μ _Y )] is the covariance of X and Y variables; μ _X and μ _Y are the mean value of variable X and the mean value of variable Y respectively ;σ _X , σ _Y are the standard deviation of the variable X and the standard deviation of the variable Y respectively. The larger the correlation coefficient, the stronger the correlation between the two variables, and the smaller the correlation coefficient, the smaller the correlation between the two variables. Therefore, the correlation coefficient between the sequential voltage U _i of each bus and U _A , U _B , and U _C can be calculated separately They are respectively denoted as ρ _i,A , ρ _i,B , ρ _i,C . For each bus i, select the largest one among ρ _i,A , ρ _i,B , and ρ _i,C , and the corresponding phase is the identified phase of the bus.

Step 5: Identify phases into three groups A, B, and C

According to the method of correlation analysis above, add all buses into the three categories of phase A, phase B and phase C respectively, and then reconstruct the network topology for the buses belonging to the three phases respectively. Taking the busbar belonging to phase A as an example to illustrate the rebuilding process, the rebuilding principles of the busbars belonging to phase B and C are the same as that of phase A.

Step 6: Use the Chow-Liu algorithm to obtain three sets of cross-correlation information matrices, and then perform topology reconstruction on the three sets of buses

Based on the Chow-Liu algorithm, the topology structure reconstruction of the three-phase low-voltage power distribution network is carried out.

Chow-Liu algorithm based on cross-correlation information Construct a maximum weight spanning tree using Kruskal's algorithm. In descending order of weights, edges are built one at a time, and if all weights are greater than 0, a connected result is obtained.

The specific process is as follows: The Chow-Liu algorithm is a finite sample in a given data set, and uses a tree model to estimate an n-dimensional discrete probability distribution. For n-dimensional vectors Each _xi is a variable, P(x) is the joint probability distribution of n discrete variables x ₁ , x ₂ ,…,x _n , we want to approximate the true joint probability distribution with a tree model of the following form:

x _π(i) is the parent node of variable i, if i is the root node, P( _xi |x _π(i) )=P( _xi ), the tree model considers the relationship between variables in the data set. For variables x _i and x _j , define the cross-correlation information between the two variables as which is

where P( _xi , x _j ) is the joint probability distribution of variables _xi and x _j , for a limited sample set, we use the maximum likelihood method to estimate the probability distribution function, and use which is

where f _uv (i,j) is the maximum likelihood estimate of P( _xi =u, x _j =v), n is the number of samples, namely

f _u (i) is the maximum likelihood estimate of P( _xi = u), namely

f _u (i) = ∑ _v f _uv (i,j) (6)

cross-correlation information The cross-correlation matrix can be established, and then the establishment of the tree model can be completed.

For the topology reconstruction of our three-phase low-voltage distribution network, the Chow-Liu algorithm can be applied to obtain the reconstructed undirected network. First, the sequential voltages of a limited number of buses belonging to three different phases can be obtained, and then the cross-correlation information between buses of the same phase can be obtained Because the voltage fluctuation curves between buses with close electrical distances are relatively similar, that is, the correlation degree is high; the similarity degree of voltage fluctuation curves between buses with long electrical distances is low, that is, the correlation degree is low. The degree of correlation between two continuously changing voltage values is measured by the cross-correlation information of the sequential voltages between each bus. Next, the Kruskal algorithm is used to construct the maximum weight spanning tree, and the topological network structure with the largest correlation coefficient between the busbars connected to each other can be obtained.

Define each bus, the corresponding U _i , U _j represent the sequential voltage of bus i and bus j, and i,j∈{1,2,…,n}, n is the total number of all buses connected to phase A . Assuming that there are 6 busbars connected to phase A, a 6*6 symmetrical square matrix can be obtained according to the voltage correlation coefficients of the 6 busbars. Here, And a _i,j =a _j,i , because these two values are correlation coefficients between the sequential voltages of bus i and bus j. The resulting correlation coefficient matrix representing the timing voltages of each bus is as follows:

Select the bus i with the closest electrical distance from the transformer as the starting point, and then select the bus with the largest correlation coefficient with i from the correlation coefficient matrix, assuming that j is the downstream bus directly connected to i, similarly, continue from the correlation coefficient matrix Select the bus with the largest correlation coefficient with j as the downstream bus directly connected to j, until all 6 buses are connected to the line, and the network topology of users belonging to phase A is obtained.

When the number of busbars is n, the above process still holds true. Similarly, the network topology structures of users belonging to phase B and phase C can be obtained.

Step 7: Find the correlation coefficient between the reference voltages, integrate the three groups of networks, and obtain a complete network structure

Find the correlation coefficient between the sequential voltages of the busbars belonging to phase A, phase B and phase C respectively as a reference, and integrate the reconstructed topological network of phase A, phase B and phase C to form a complete topological network structure. It specifically includes the following content: Calculate the correlation coefficient between the three reference voltages of the three phases, the specific calculation formula has been given in step 4; according to the obtained results, connect the three sets of voltages, that is, the correlation coefficient between the voltages of the bus as the reference is large connected to the reference bus.

Based on the above analysis, according to the correlation analysis between the voltages, the busbars are divided into three categories: A phase, B phase and C phase. Next, the three-phase low-voltage distribution is performed on the busbars belonging to each phase according to the Chow-Liu algorithm. The topology structure of the power network is reconstructed, and finally the reconstruction network of the three phases is integrated to obtain the complete topology structure of the three-phase low-voltage distribution network. Figure 2 is a schematic diagram of the simple low-voltage distribution network topology generated by the three-phase distribution network topology reconstruction method . The figure contains 13 user topological diagrams that are connected to the three-phase low-voltage side of A, B, and C through a transformer, where user 1, user 2, and user 3 are connected to phase A; user 4, user 5, and user 6 , User 7 and User 8 are connected in Phase B; User 9, User 10, User 11, User 12, and User 13 are connected in Phase C. .

The applicant has made a detailed illustration and description of the embodiments of the present invention in conjunction with the accompanying drawings, but those skilled in the art should understand that the above embodiments are only preferred embodiments of the present invention, and the detailed description is only to help readers better understand The spirit of the present invention does not limit the protection scope of the present invention. On the contrary, any improvement or modification made based on the spirit of the present invention should fall within the protection scope of the present invention.

Claims (6)

1. a kind of three-phase low-voltage power distribution network topology rebuilding method, it is characterised in that：It is primarily based on time-sequential voltage data relation analysis It identifies the specific phase of busbar, for three groups of different phases, the busbar for belonging to three phases is utilized respectively Chow- Liu algorithms are rebuild to carry out the topological structure of three-phase low-voltage distribution network, and three obtained network is finally carried out integration acquisition Complete topology network architecture.

2. a kind of three-phase low-voltage power distribution network topology rebuilding method, which is characterized in that three-phase low-voltage power distribution network topology rebuilding side Method includes the following steps：

Step 1：Time-sequential voltage data are obtained from the intelligent electric meter of user side；

Step 2：In each taiwan area, distribution network is abstracted as graph model G=(M, S), the node of busbar graph model indicates, That is M={ i, i=1,2 ..., N }, branch route the side expression of graph model, i.e. S={ l_i,j,i,j∈M}；Wherein, G is power distribution network Graph model, M are the set of node of power distribution network, and N is maximum node number, and S is the branch collection of power distribution network, l_i,jFor connecting node i and node The branch of j；

Step 3：Given time window T_pWith time interval T, an intelligent electric meter voltage value is obtained every time interval T, is acquired altogether D voltage value constitutes a voltage vector U_i, wherein D=T_p/ T, U_iIndicate what busbar i was constituted in the voltage of entire time window Vector, the time-sequential voltage for choosing the busbar that is belonging respectively to A phase, B phase and C phase nearest from transformer are denoted as respectively as benchmark

U_ph={ u_ph；Ph=A, B, C }；

Step 4：Calculate the time-sequential voltage U of busbar i_iAnd U_A, U_B, U_CBetween related coefficient, be denoted as ρ respectively_i,A, ρ_i,B, ρ_i,C；For Busbar i chooses ρ_i,A, ρ_i,B, ρ_i,CIn maximum one, the phase corresponding to it is the phase that the busbar is identified to, cycle Calculate all busbares in power distribution network；

Step 5：All busbares in step 4 are added in three classifications of A phase, B phase, C phase；

Step 6：Respectively obtain three groups of cross-correlation information of three groups of busbares in step 5Wherein cross-correlation informationFor the weighted value obtained according to Chow-Liu algorithms, according to cross-correlation informationTopological network is carried out respectively It rebuilds；

Step 7：The related coefficient between the time-sequential voltage as the busbar for being belonging respectively to A phases, B phases and C phases of benchmark is sought, A is integrated Phase, the three groups of reconstructions of B phases and C phases topological network, formed a complete topology network architecture.

3. three-phase low-voltage power distribution network topology rebuilding method according to claim 2, it is characterised in that：

In step 4, in addition to as benchmark time-sequential voltage other busbares time-sequential voltage U_iWith the benchmark time-sequential voltage of corresponding phase U_phRelated coefficient calculate as follows：

Wherein Cov (U_i,U_ph) it is U_i,U_phThe covariance of variable,For the standard deviation of two voltage quantities.

4. three-phase low-voltage power distribution network topology rebuilding method according to claim 2 or 3, it is characterised in that：

In step 6, the cross-correlation information between different group busbaresIt calculates as follows：

Wherein f_uv(i, j) is P (u_i=u, u_j=v) maximal possibility estimation, f_u(i) it is P (u_i=u) maximal possibility estimation, f_v (j) it is P (u_j=v) maximal possibility estimation, P (u_i=u, u_j=v) refer to u_i=u, u_jJoint probability when=v, P (u_i=u) Refer to u_iProbability when=u, P (u_j=v) refer to u_jProbability when=v.

5. three-phase low-voltage power distribution network topology rebuilding method according to claim 4, it is characterised in that：In step 6, according to Cross-correlation informationIt includes the following contents to carry out topological network reconstruction respectively：

6.1 are directed to each phase, choose busbar voltage and the maximum busbar a of reference voltage related coefficient；

6.2 according to cross-correlation informationIt chooses and the highest busbar b of busbar a cross-correlation information；

6.3 repeat step 6.2, until all busbares for belonging to the phase are completed to connect.

6. three-phase low-voltage power distribution network topology rebuilding method according to claim 2, it is characterised in that：

In step 7, the following contents is specifically included：

7.1 calculate the related coefficient between three reference voltages of three phases；

7.2, according to acquired results, connect three groups of voltages, i.e., benchmark big as related coefficient between the voltage of the busbar of benchmark is female Line is connected.