Power distribution network voltage control region division method and device and electronic equipment

Abstract

The invention discloses a power distribution network voltage control region division method and device and electronic equipment. The method comprises the following steps: acquiring power flow information of each node in the power distribution network, and determining a system admittance matrix of the power distribution network according to the power flow information; determining a cut set corresponding to each region in the power distribution network according to the system admittance matrix, wherein the cut set is used for determining a preliminary partitioning result of the power distribution network; a voltage increment matrix corresponding to each node in the power distribution network is determined, and the voltage increment matrix is used for reflecting the voltage change condition of each node after the power change preset value of any node in each node; the cut set serves as clustering prior information, the voltage increment matrix is clustered, a target partitioning result of the power distribution network is obtained, and the target partitioning result comprises regions to which the nodes belong; and performing voltage partition control on the power distribution network according to the target partition result. According to the method and the device, the technical problem of relatively high partition control loss caused by adoption of a static partition mode of the power distribution network in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of electrical engineering, and in particular to a method, device and electronic equipment for dividing voltage control areas in a distribution network. Background Art

[0002] In the related art, when the distribution network system is partitioned, the method of static partitioning followed by partition scheduling is often adopted. The problem with this method is that the partition result will not be changed after the partition, but the working state of the distribution network system is dynamically changing, resulting in the partition scheduling result sometimes not matching the actual situation, causing more regulation losses.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method, device and electronic device for dividing voltage control areas in a distribution network, so as to at least solve the technical problem of large zoning control losses caused by the static zoning of the distribution network adopted in the related art.

[0005] According to one aspect of an embodiment of the present application, a method for dividing a distribution network voltage control area is provided, comprising: obtaining power flow information of each node in the distribution network, and determining a system admittance matrix of the distribution network based on the power flow information, wherein the node includes a generator node and a load node; determining a cut set corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut set is used to determine a preliminary partitioning result of the distribution network; determining a voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; using the cut set as clustering prior information, clustering the voltage increment matrix, and obtaining a target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; and performing voltage partitioning control on the distribution network based on the target partitioning result.

[0006] Optionally, determining the cut sets corresponding to each area in the distribution network based on the system admittance matrix includes: determining the inverse matrix of the system admittance matrix; performing item-by-item product operation on the system admittance matrix and the inverse matrix to obtain a coupling matrix of the distribution network, wherein the elements in the coupling matrix are coupling strength indicators between two nodes in the distribution network; determining a preset coupling coefficient; comparing each element in the coupling matrix with the preset coupling coefficient, and retaining elements greater than the preset coupling coefficient; and determining the cut sets based on the retained elements.

[0007] Optionally, determining the cut set based on the retained elements includes: determining an edge between two nodes corresponding to the retained elements as a key edge; and determining the cut set based on the key edge.

[0008] Optionally, determining the voltage increment matrix corresponding to each node in the distribution network includes: determining a sensitivity matrix of each node in the distribution network, wherein the sensitivity matrix is ​​used to reflect the correlation between the voltage change of each node and the power change of the distribution network; sequentially changing the power of each node from a first power to a second power, and determining the voltage change of each node after the power is changed based on the sensitivity matrix, thereby obtaining a voltage increment matrix, wherein the power change of each node is the same, and when changing the power of any node among the nodes, the power of nodes other than the arbitrary node remains at the first power.

[0009] Optionally, clustering each node in the distribution network based on the cut set and the voltage increment matrix includes: a first step, determining each row element in the voltage increment matrix as a sample, and determining each sample as a sample category; a second step, determining the distance between each sample category; a third step, merging the two sample categories with the closest distance into one sample category, and jumping to the second step when the number of remaining sample categories is greater than the preset number of sample categories.

[0010] Optionally, determining the distance between each sample category includes: when there are multiple samples in the sample category, for each first sample in the first sample category, determining the distance between the first sample and each second sample in the second sample category, wherein the first sample category is any sample category in the sample categories, and the second sample category is any sample category in the sample categories except the first sample category; determining that the minimum value of the distance between the first sample and the second sample is the distance between the first sample category and the second sample category.

[0011] Optionally, determining the distance between each sample category includes: when there are multiple samples in the sample category, determining the average square distance of all sample pairs between the first sample category and the second sample category as the distance between the first sample category and the second sample category, wherein the sample pairs include a first sample in the first sample category and a second sample in the second sample category, the first sample category is any sample category in each sample category, and the second sample category is any sample category in each sample category except the first sample category.

[0012] Optionally, determining the distance between each sample category includes: determining the incremental sum of squared deviations between any two sample categories in each sample category, wherein the incremental sum of squared deviations is obtained by subtracting the sum of squared deviations of the sample category obtained after merging any two sample categories from the sum of squared deviations of the two sample categories before the merging; and using the incremental sum of squared deviations as the distance between any two sample categories.

[0013] According to another aspect of an embodiment of the present application, there is also provided a distribution network voltage control area division device, comprising: a first processing module, used to obtain the power flow information of each node in the distribution network, and determine the system admittance matrix of the distribution network based on the power flow information, wherein the nodes include generator nodes and load nodes; a second processing module, used to determine the cut sets corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; a third processing module, used to determine the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; a fourth processing module, used to cluster the voltage increment matrix using the cut sets as clustering prior information, and obtain the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; a fifth processing module, used to perform voltage partitioning control on the distribution network based on the target partitioning result.

[0014] According to another aspect of an embodiment of the present application, a non-volatile storage medium is further provided, in which a program is stored, wherein when the program is running, a device where the non-volatile storage medium is located is controlled to execute a method for dividing a distribution network voltage control area.

[0015] According to another aspect of an embodiment of the present application, there is further provided an electronic device, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the method for dividing a voltage control area of ​​a distribution network is executed when the program is run.

[0016] According to another aspect of an embodiment of the present application, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, a method for dividing voltage control areas of a distribution network is implemented.

[0017] In an embodiment of the present application, the flow information of each node in the distribution network is obtained, and the system admittance matrix of the distribution network is determined based on the flow information, wherein the nodes include generator nodes and load nodes; the cut sets corresponding to each area in the distribution network are determined based on the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; the voltage increment matrix corresponding to each node in the distribution network is determined, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; the cut sets are used as clustering prior information to cluster the voltage increment matrix to obtain a target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; the voltage partitioning control method of the distribution network is performed based on the target partitioning result, and the target partitioning result is obtained by clustering the voltage increment matrix using the cut sets as prior information, thereby achieving the purpose of dynamically partitioning the distribution network, thereby achieving the technical effect of reducing the regulation loss of the distribution network, and further solving the technical problem of large partitioning control loss caused by the static partitioning method of the distribution network in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 is a schematic diagram of the structure of a computer terminal (mobile terminal) provided according to an embodiment of the present application;

[0020] Figure 2 It is a flow chart of a method for dividing voltage control areas of a distribution network provided in an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of a coupling node provided according to an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of a correlation coefficient and a coupling matrix provided according to an embodiment of the present application;

[0023] Figure 5 It is a flow chart of a distribution network voltage dispatching control process provided according to an embodiment of the present application;

[0024] Figure 6 It is a structural schematic diagram of a distribution network voltage control area division device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] In the scenario of high penetration and decentralized distributed power access in the distribution network, due to the large number of installed power generation devices and their non-centralized locations, the distribution network has become a complex network. The centralized optimization control method is used for all photovoltaic power generation systems. Due to the excessive number of variable dimensions, the optimization process will be complicated, the optimization time will be too long, and even the problem of dimensional disaster will occur.

[0028] In recent years, voltage partition control has provided a new idea for solving high-dimensional and complex voltage optimization control problems. The so-called "partition" is to divide the distribution network into several sub-areas according to certain rules. The nodes in different sub-areas have the characteristics of weak coupling, and the nodes in the same sub-area have the characteristics of strong coupling. Therefore, the voltage can be controlled independently in each sub-area and is not affected by other sub-areas. At present, the main partitioning methods developed in domestic and foreign literature for voltage partition optimization control include: spectral clustering method, K-means method, immune algorithm, complex network theory, etc.

[0029] In order to cope with the challenges brought by the high proportion of renewable energy generation access to the safe operation of the distribution network, a distributed optimization strategy based on cluster collaborative control is a solution. Taking advantage of the sparsity of the distribution network, it is divided into multiple sub-areas to achieve a control cluster with high node cohesion within the region and low coupling between nodes between regions. Then, a distributed control algorithm is used to coordinate the clusters formed by multiple sub-areas to achieve a distributed control pattern with self-discipline within the cluster and coordination between clusters. When zoning the distribution network, it is necessary not only to consider the geographical distribution and physical connection, but also the degree of electrical coupling between nodes. Different distribution network zoning indicators have been proposed according to different control objectives. There are those that construct electrical distance based on node voltage and reactive coupling as indicators, and use clustering algorithms for cluster division; there are also those that establish electrical distance based on the coupling degree of voltage and voltage between nodes for zoning; in addition, there are also studies on zoning based on voltage phase angle-active power sensitivity and branch impedance distance. In terms of zoning methods, clustering algorithms and community partitioning algorithms are currently the main ones. In addition, some studies use intelligent algorithms for zoning.

[0030] However, the distribution network partitioning in the related art is mostly carried out according to the dispatching partitioning, so that the order of each sub-block is roughly equal so that the computer can perform parallel processing. This partitioning method is called structural partitioning or static partitioning. It reflects the characteristics of the network structure. The power grid structure is static, and the parameters in the structure determine the network characteristics, which reflects the dynamic behavior. However, the existing methods do not deal with the problem from the perspective of the dynamic operation characteristics of the network. At the same time, the coordination between regions is not considered, which leads to a higher cost of voltage regulation. Therefore, after the distribution network is partitioned, it is necessary to realize parallel calculations in each sub-region and coordinate optimization between regions at the same time, so as to truly realize the partitioning of the distribution network and ensure that the voltage of the nodes in the divided voltage region has a centralized distribution law.

[0031] In order to solve the above problems, relevant solutions are provided in the embodiments of the present application, which are described in detail below.

[0032] According to an embodiment of the present application, a method embodiment of a method for dividing voltage control areas in a distribution network is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for dividing a distribution network voltage control area is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0034] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0035] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the distribution network voltage control area division method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the above-mentioned distribution network voltage control area division method is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0036] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0037] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0038] Under the above operating environment, the embodiment of the present application provides a method for dividing the voltage control area of ​​the distribution network, such as Figure 2 As shown, the method comprises the following steps:

[0039] Step S202, acquiring power flow information of each node in the distribution network, and determining a system admittance matrix of the distribution network according to the power flow information, wherein the nodes include generator nodes and load nodes;

[0040] It should be noted that the power flow information of each node changes in real time, so the admittance matrix and partition results based on the power flow information also change in real time.

[0041] In some embodiments of the present application, in order to systematically form a coupling matrix in an operational manner, the term-by-term product of two vectors is first defined, and the symbol is denoted by ⊙.

[0042] Assume that the row vector a and column vector b are:

[0043] a=[a1 a2 … a n ] (1)

[0044] b=[b1 b2 … b n ] T (2)

[0045] Then the term-by-term product of vector a and vector b is defined as:

[0046] a☉b=[a1b1 a2b2 … a n b n ] (3)

[0047] In linear algebra, the scalar product (inner product) of two vectors is:

[0048] a·b=a1b1+a2b2+…+a n bn (4)

[0049] It expresses the overall correlation between two vectors.

[0050] If the canonical form is:

[0051] μ=(a·b) / |a||b| (5)

[0052] Then μ can be used to quantitatively describe the degree of correlation between two vectors. When μ is close to 1, vectors a and b are said to be strongly linearly correlated, and when μ is close to 0, vectors a and b are said to be weakly linearly correlated.

[0053] The term-by-term product further understands the correlation between the two vectors from the corresponding elements. If one term among the terms of a1b1, a2b2, ..., anbn has a large proportion in absolute value, it indicates that the term plays a major role in the correlation between the vectors a and b2.

[0054] Take the system admittance matrix as an example to illustrate the generation of the correlation matrix:

[0055] For the admittance matrix Y and its inverse matrix Y-1:

[0056]

[0057] In the formula, y1, y2…yn are row vectors, and y1-1, y2-1…an-1 are column vectors.

[0058] Then there exists:

[0059]

[0060]

[0061] Write the row vector as:

[0062]

[0063] As the i-th row of matrix G, and record G matrix as:

[0064] G=Y☉Y -1 (9)

[0065] Define the matrix G as the product of the Y and Y-1 matrices. The G matrix can be used as the coupling matrix between the admittances of each branch. Define G as the coupling matrix of the Y matrix.

[0066] Step S204, determining the cut sets corresponding to each area in the distribution network according to the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network;

[0067] The above cut sets can be regarded as the partition results obtained based on the dynamic segmentation theory in this application, which is partitioned from the perspective of network parameters. Since a single partitioning method is restricted by the real-time grid changes and power flow factors in the actual power grid, the voltage sensitivity method is combined with the real-time power flow information to make up for this shortcoming.

[0068] In the technical solution provided in step S204, the step of determining the cut sets corresponding to each area in the distribution network based on the system admittance matrix includes: determining the inverse matrix of the system admittance matrix; performing item-by-item product operation on the system admittance matrix and the inverse matrix to obtain a coupling matrix of the distribution network, wherein the elements in the coupling matrix are coupling strength indicators between two nodes in the distribution network; determining a preset coupling coefficient; comparing each element in the coupling matrix with the preset coupling coefficient, and retaining elements greater than the preset coupling coefficient; and determining the cut sets based on the retained elements.

[0069] Specifically, the above-mentioned preset coupling coefficient is used to determine the number of divided areas. The smaller the coefficient value, the more areas are divided; the larger the coefficient value, the fewer areas are divided; the coefficient is an empirically selected parameter, and generally the parameter selection range is between 0.001-0.005. In addition, the preset coupling coefficient can also be dynamically adjusted according to preset rules.

[0070] As an optional implementation, the step of determining a cut set based on the retained elements includes: determining an edge between two nodes corresponding to the retained elements as a key edge; and determining a cut set based on the key edge.

[0071] Specifically, a matrix describing the static performance of a system (admittance matrix) or a matrix describing its dynamic behavior (state matrix and its inverse matrix) has corresponding elements, and their connections usually express the connection between certain physical or engineering quantities.

[0072] If Y -1 Array element uses y -1 Indicates that the Y array element y ji With Y -1 Array element y ij -1 This is a pair of corresponding elements. To briefly explain the relationship between the two, we use the flow graph in graph theory to explain it accordingly. To facilitate the expression of the "causal" relationship between quantities, we use directed edges to represent this relationship. According to the flow graph convention, the direction of a directed edge always points from the second subscript to the first subscript.

[0073] First observe Y -1 The i-th element y of the j-th array ij -1 The graph theoretical implication is: it is equal to (-1) i+j Δ ji / Δ, where Δ is the determinant of the Y matrix, and Δji is Δ removing the j rows (i j1 ,i j2 ,…,i jn ) and column i (i 1i ,i 2i ,…,i ni ) T In the corresponding network graph, node j has no incoming edges but only outgoing edges; node i has no outgoing edges but only incoming edges. Therefore, there is a directed edge from node j to node i with an edge weight of y. ij -1 ,See Figure 3 Left side.

[0074] Consider the Y array element y ji : In the corresponding network graph, it is a directed edge from node i to node j, with edge weight y ji , and the above y ij -1 That directed edge forms a first-order loop, which makes the physical quantities on the two nodes feedback each other, thus coupling the two nodes with each other. ji =y ji y ij -1 , which can be used to measure the coupling degree between nodes i and j, and can be defined as the coupling coefficient between nodes i and j, see Figure 3 Shown on the right.

[0075] If g ji Put it into the jth row and ith column of matrix G, such as Figure 4 As shown, g is given ji Directionality from i to j. Let i, j = 1, 2, ..., n, so the elements of G matrix are formed one by one, and the resulting G matrix is ​​defined as the correlation matrix of Y matrix.

[0076] After obtaining the system admittance matrix Y, we can then find Y -1 array, forming a coupled array G = Y⊙Y -1 Then, a critical coupling coefficient g is set c , in the G matrix, discard all coupling coefficients with an absolute value less than g c The corresponding coupling edge of the G matrix is ​​discarded, and the corresponding edge of the Y matrix is ​​also cancelled, which means that the edge has little effect on the voltage static characteristics of the system. At this time, the system is divided into sub-blocks, and the node connectivity is used to search for nodes connected to each sub-block, and the nodes are marked. Therefore, after the division, the nodes on the same sub-block are connected, and the nodes on the boundaries of different sub-blocks can be regarded as unconnected.

[0077] Step S206, determining a voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value;

[0078] In the technical solution provided in step S206, the step of determining the voltage increment matrix corresponding to each node in the distribution network includes: determining the sensitivity matrix of each node in the distribution network, wherein the sensitivity matrix is ​​used to reflect the correlation between the voltage change of each node and the power change of the distribution network; changing the power of each node from the first power to the second power in turn, and determining the voltage change of each node after the power is changed based on the sensitivity matrix, thereby obtaining a voltage increment matrix, wherein the power change of each node is the same, and when changing the power of any node among the nodes, the power of the nodes other than the arbitrary node remains at the first power.

[0079] Specifically, any method for determining the voltage sensitivity matrix can be used when determining the voltage sensitivity matrix, and the present application has no restrictions on this. In addition, the voltage sensitivity matrix includes the sensitivity of each node in the distribution network. Sensitivity can reflect the sensitivity of the voltage value of each node to the power change. When the voltage value of a node changes greatly, it indicates that this node is sensitive to power changes; if the voltage change value of a node is small, it means that the voltage of this node is relatively stable and is less affected by the power changes of other nodes. It should also be noted that voltage sensitivity includes active voltage sensitivity and reactive voltage sensitivity.

[0080] In order to more effectively regulate the voltage of each node in the distribution network, this application pays more attention to the impact of changes in the power system structure on each node of the system. When the system structure changes and causes the power injected into a certain node to increase, the voltage change generated at other nodes is a positive value. When the power injected into a certain node decreases, the voltage change value at other nodes will become smaller accordingly. At this time, the absolute value of the voltage change is used to describe it. In order to obtain the voltage increment matrix of the entire distribution network, the grid structure of the distribution network is first changed. When the power injected into a certain node changes, the voltage of other nodes in the system will change. When the balancing node is not considered, an n-1-dimensional voltage change vector will be generated. When the same power injection is changed to n-1 nodes in turn, a voltage change matrix with a dimension of (n-1)×(n-1) is generated. This matrix is ​​called a voltage increment matrix.

[0081] Step S208, using the cut set as clustering prior information, clustering the voltage increment matrix to obtain a target partition result of the distribution network, wherein the target partition result includes the area to which each node belongs;

[0082] In the technical solution provided in step S208, the step of clustering each node in the distribution network based on the cut set and the voltage increment matrix includes: a first step, determining each row element in the voltage increment matrix as a sample, and determining each sample as a sample category; a second step, determining the distance between each sample category; a third step, merging the two sample categories with the closest distance into one sample category, and jumping to the second step when the number of remaining sample categories is greater than the preset number of sample categories.

[0083] As an optional implementation, the step of determining the distance between each sample category includes: when there are multiple samples in the sample category, for each first sample in the first sample category, determining the distance between the first sample and each second sample in the second sample category, wherein the first sample category is any sample category in the sample categories, and the second sample category is any sample category in the sample categories except the first sample category; determining the minimum value of the distance between the first sample and the second sample is the distance between the first sample category and the second sample category.

[0084] In some embodiments of the present application, the step of determining the distance between each sample category includes: when there are multiple samples in the sample category, determining the average square distance of all sample pairs between the first sample category and the second sample category as the distance between the first sample category and the second sample category, wherein the sample pairs include a first sample in the first sample category and a second sample in the second sample category, the first sample category is any sample category among the sample categories, and the second sample category is any sample category among the sample categories except the first sample category.

[0085] As an optional implementation, the step of determining the distance between each sample category includes: determining the incremental sum of squared deviations between any two sample categories in each sample category, wherein the incremental sum of squared deviations is obtained by subtracting the sum of squared deviations of the sample category obtained after merging any two sample categories from the sum of squared deviations of the two sample categories before merging; and using the incremental sum of squared deviations as the distance between any two sample categories.

[0086] Specifically, in the embodiment of the present application, a system clustering algorithm can be used to cluster the voltage increment matrix. System clustering is also called hierarchical clustering. This clustering method is to continuously aggregate or split samples to form a hierarchical tree-like structure. The algorithm is divided according to the nature of the research object, which helps to classify according to local conditions. Nowadays, the commonly used system clustering methods mainly include the intra-group link method, the inter-group link method, the sum of squared deviations method (Ward method), etc. Clustering statistics mainly include Euclidean distance, Euclidean square distance, Minkowski distance (Minkowski), Manhattan distance, Person correlation coefficient and other metrics. Taking the agglomeration method as an example, the steps of the system clustering algorithm are:

[0087] In the first step, we first calculate the distance between different categories and express it in a distance matrix;

[0088] The second step is to compare the distances between different classes and merge the two closest classes into a new class;

[0089] The third step is to update the distance matrix, continue to compare the distances between different classes, and synthesize a new class;

[0090] In the fourth step, the second and third steps are repeated until the number of required termination classes is synthesized.

[0091] The embodiment of the present application intends to cluster the voltage increment matrix using the intra-group link method, the inter-group link method, and the deviation square sum method (Ward method). The intra-group link method refers to the distance between points with the smallest average square distance in two categories representing the inter-class distance. The inter-group link method refers to the use of the average of the squared distances between each pair of data points in two categories to represent the inter-class distance. The deviation square sum method is an extended algorithm of variance analysis. When the system samples are properly classified, the deviation square sum between each class of samples should be small, and the deviation square sum between different classes should be relatively large. Therefore, this method can achieve a small distance within the group and a large distance between different groups, thereby realizing the voltage partitioning of the distribution network. The specific idea of ​​the deviation square sum method is as follows:

[0092] The first step is to divide the n types of sample data into k categories, G1, G2, G3, ..., G k , then the sum of squares of the deviations of the t-th class of samples is:

[0093]

[0094] In the formula, It's G t The center of gravity, X it (m-dimensional vector) represents G t The i-th sample in n t Represents G t The number of samples in .

[0095] In the second step, when class G p and class G q Merge into new class G r When , there are three types of sum of squares of deviations S p , S q and S r , then the increased sum of squares of deviations is D pq 2 =S r -S p -S q .

[0096] Step 3: When G p and G q The two categories are close to each other. should be smaller, this classification is reasonable; when D pq 2 When it is larger, it is classified as unreasonable.

[0097] The fourth step is to regard the sum of squared deviations caused by the combination of the two categories as the squared distance, then we have the distance formula, see formula (11), and the recursive formula is shown in formula (12).

[0098]

[0099]

[0100] In the formula, G q The center of gravity, X p G p The samples in n p 、n q 、n r 、n k is the corresponding number of samples.

[0101] When calculating the distance between samples, the Euclidean distance method, the Euclidean square distance method, the Minkowski distance method, and the Manhattan distance method can be used as classification statistics. For any two samples, the Euclidean distance is:

[0102]

[0103] For any two samples, the Euclidean square distance is:

[0104]

[0105] For any two samples, the Minkowski distance is:

[0106]

[0107] In the formula, p is the power of the distance between samples, which is usually 2.

[0108] For any two samples, the Manhattan distance is:

[0109]

[0110] In formulas (13) to (16), X in represents the value of the nth variable in the ith sample, X jn Represents the nth vector value in the jth sample.

[0111] Step S210: performing voltage partition control on the distribution network according to the target partition result.

[0112] In some embodiments of the present application, in summary, the process of dispatching and controlling the voltage of the distribution network is as follows: Figure 5 As shown in the figure, it is divided into two parts: dynamic segmentation based on network structure and auxiliary decision-making based on reactive power and voltage sensitivity, including the following steps:

[0113] The first step is to record the power flow information of the generator nodes and load nodes in the distribution network, convert the power of the corresponding nodes into admittance and incorporate it into the system admittance matrix.

[0114] The second step is to calculate the coupling matrix G corresponding to the admittance array Y and give the coupling coefficient g c .

[0115] The third step is to determine the element y ij Is it greater than g? c If y ij Greater than g c , determine the branches corresponding to the key edges and form the cut sets corresponding to each region; if y ij Less than g c Then discard irrelevant edges.

[0116] The fourth step is to make auxiliary decisions based on voltage sensitivity, obtain the system Jacobian matrix and invert it to obtain the sensitivity matrix [J aco ] -1 .

[0117] Step 5: Calculate the voltage increment ΔV i , and obtain the voltage increment matrix.

[0118] The sixth step is to use the system clustering algorithm to partition the voltage of the distribution network. The clustering methods include the intra-group link method, the inter-group link method, the sum of squared deviations method (Ward method), and the clustering methods include Euclidean distance, Euclidean square distance, and Minkowski distance. The partition results are obtained to accurately control the distribution network voltage.

[0119] The invention adopts the method of obtaining the flow information of each node in the distribution network, and determining the system admittance matrix of the distribution network according to the flow information, wherein the nodes include generator nodes and load nodes; determining the cut sets corresponding to each area in the distribution network according to the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; determining the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; clustering the voltage increment matrix using the cut sets as clustering prior information to obtain the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; and controlling the voltage partitioning of the distribution network according to the target partitioning result, and obtaining the target partitioning result by clustering the voltage increment matrix using the cut sets as prior information, thereby achieving the purpose of dynamically partitioning the distribution network, thereby realizing the technical effect of reducing the regulation loss of the distribution network, and further solving the technical problem of large partitioning control loss caused by the static partitioning method of the distribution network in the related technology.

[0120] In addition, the embodiment of the present application also provides a dynamic segmentation theory applicable to the distribution network. The regional segmentation theory can achieve a balance between global optimization and local control. Traditional voltage control methods often rely on centralized control or decentralized control, and it is difficult to balance global optimization and local control. The regional segmentation theory divides the distribution network into several relatively independent voltage regions by segmenting network parameters, which can achieve global optimization and improve the response speed of local control. Each region can be independently adjusted according to its own voltage requirements, thereby achieving voltage stability and optimization.

[0121] In addition, in the embodiment of the present application, the voltage increment matrix is ​​obtained to perform system cluster analysis, and the entire distribution network can be partitioned for auxiliary voltage. The clustering method adopts the sum of squares of deviations method, the inter-group link method and the intra-group link method, and the clustering methods mainly include Euclidean distance, Minkowski distance and Manhattan distance. By observing the obtained dendrogram and icicle diagram, the distribution network is partitioned and classified. After obtaining the classified areas, the voltage characteristics of the nodes in different areas are studied, and the boundary node ownership problem is further judged according to the size of the voltage increment.

[0122] The present application provides a device for dividing voltage control areas in a power distribution network. Figure 6 is a schematic diagram of the structure of the device. Figure 6It can be seen that the device includes: a first processing module 60, which is used to obtain the flow information of each node in the distribution network, and determine the system admittance matrix of the distribution network based on the flow information, wherein the nodes include generator nodes and load nodes; a second processing module 62, which is used to determine the cut sets corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; a third processing module 64, which is used to determine the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; a fourth processing module 66, which is used to cluster the voltage increment matrix using the cut sets as clustering prior information, and obtain the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; a fifth processing module 68, which is used to perform voltage partitioning control on the distribution network based on the target partitioning result.

[0123] In some embodiments of the present application, the step of the second processing module 62 determining the cut sets corresponding to each area in the distribution network based on the system admittance matrix includes: determining the inverse matrix of the system admittance matrix; performing item-by-item product operation on the system admittance matrix and the inverse matrix to obtain a coupling matrix of the distribution network, wherein the elements in the coupling matrix are coupling strength indicators between two nodes in the distribution network; determining a preset coupling coefficient; comparing each element in the coupling matrix with the preset coupling coefficient, and retaining elements greater than the preset coupling coefficient; and determining the cut sets based on the retained elements.

[0124] In some embodiments of the present application, the step of the second processing module 62 determining the cut set according to the retained elements includes: determining the edge between two nodes corresponding to the retained elements as a key edge; and determining the cut set according to the key edge.

[0125] In some embodiments of the present application, the step of the third processing module 64 determining the voltage increment matrix corresponding to each node in the distribution network includes: determining the sensitivity matrix of each node in the distribution network, wherein the sensitivity matrix is ​​used to reflect the correlation between the voltage change of each node and the power change of the distribution network; changing the power of each node from the first power to the second power in turn, and determining the voltage change of each node after the power is changed based on the sensitivity matrix, thereby obtaining a voltage increment matrix, wherein the power change of each node is the same, and when changing the power of any node among the nodes, the power of the nodes other than the arbitrary node remains at the first power.

[0126] In some embodiments of the present application, the step of clustering each node in the distribution network according to the cut set and the voltage increment matrix by the fourth processing module 66 includes: a first step of determining each row element in the voltage increment matrix as a sample, and determining each sample as a sample category; a second step of determining the distance between each sample category; a third step of merging the two sample categories with the closest distance into one sample category, and jumping to the second step when the number of remaining sample categories is greater than the preset number of sample categories.

[0127] In some embodiments of the present application, the step of the fourth processing module 66 determining the distance between each sample category includes: in the case where there are multiple samples in the sample category, for each first sample in the first sample category, determining the distance between the first sample and each second sample in the second sample category, wherein the first sample category is any sample category in the sample categories, and the second sample category is any sample category in the sample categories except the first sample category; determining that the minimum value of the distance between the first sample and the second sample is the distance between the first sample category and the second sample category.

[0128] In some embodiments of the present application, the step of the fourth processing module 66 determining the distance between each sample category includes: when there are multiple samples in the sample category, determining the average square distance of all sample pairs between the first sample category and the second sample category as the distance between the first sample category and the second sample category, wherein the sample pairs include a first sample in the first sample category and a second sample in the second sample category, the first sample category is any sample category among the sample categories, and the second sample category is any sample category among the sample categories except the first sample category.

[0129] In some embodiments of the present application, the step of the fourth processing module 66 determining the distance between each sample category includes: determining the incremental sum of squared deviations between any two sample categories in each sample category, wherein the incremental sum of squared deviations is obtained by subtracting the sum of squared deviations of the two sample categories before the merging from the sum of squared deviations of the sample category obtained after merging any two sample categories; and using the incremental sum of squared deviations as the distance between any two sample categories.

[0130] It should be noted that the various modules in the above-mentioned distribution network voltage control area division device can be program modules (for example, a set of program instructions to implement a certain specific function) or hardware modules. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0131] According to an embodiment of the present application, a non-volatile storage medium is also provided, in which a program is stored, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the distribution network voltage control area division method as shown in the figure below: obtain the power flow information of each node in the distribution network, and determine the system admittance matrix of the distribution network based on the power flow information, wherein the node includes a generator node and a load node; determine the cut set corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut set is used to determine the preliminary partitioning result of the distribution network; determine the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; use the cut set as clustering prior information to cluster the voltage increment matrix to obtain the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; and perform voltage partitioning control on the distribution network based on the target partitioning result.

[0132] According to an embodiment of the present application, an electronic device is also provided, including: a memory and a processor, the processor is used to run a program stored in the memory, wherein the following distribution network voltage control area division method is executed when the program is running: obtaining the power flow information of each node in the distribution network, and determining the system admittance matrix of the distribution network based on the power flow information, wherein the node includes a generator node and a load node; determining the cut set corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut set is used to determine the preliminary partitioning result of the distribution network; determining the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; using the cut set as clustering prior information, clustering the voltage increment matrix, and obtaining the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; and performing voltage partitioning control on the distribution network based on the target partitioning result.

[0133] According to an embodiment of the present application, a computer program product is also provided, including a computer program, which implements the following distribution network voltage control area division method when executed by a processor: obtaining power flow information of each node in the distribution network, and determining the system admittance matrix of the distribution network based on the power flow information, wherein the node includes a generator node and a load node; determining the cut sets corresponding to each area in the distribution network based on the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; determining the voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in each node changes by a preset value; using the cut sets as clustering prior information, clustering the voltage increment matrix, and obtaining the target partitioning result of the distribution network, wherein the target partitioning result includes the area to which each node belongs; and performing voltage partitioning control on the distribution network based on the target partitioning result.

[0134] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0136] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0138] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0139] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for dividing voltage control areas of a distribution network, characterized in that: include: Acquire power flow information of each node in the distribution network, and determine the system admittance matrix of the distribution network according to the power flow information, wherein the nodes include generator nodes and load nodes; Determining a cut set corresponding to each area in the distribution network according to the system admittance matrix, wherein the cut set is used to determine a preliminary partition result of the distribution network; Determine a voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in the nodes changes by a preset value; The cut set is used as clustering prior information to cluster the voltage increment matrix to obtain a target partition result of the distribution network, wherein the target partition result includes the area to which each node belongs; The distribution network is subjected to voltage partition control according to the target partition result.

2. The method for dividing the voltage control area of ​​the distribution network according to claim 1, characterized in that: Determining the cut sets corresponding to each area in the distribution network according to the system admittance matrix includes: determining an inverse matrix of the system admittance matrix; Performing an item-by-item product operation on the system admittance matrix and the inverse matrix to obtain a coupling matrix of the distribution network, wherein an element in the coupling matrix is ​​a coupling strength index between two nodes in the distribution network; determining a preset coupling coefficient; Comparing each element in the coupling matrix with the preset coupling coefficient, and retaining elements greater than the preset coupling coefficient; The cut set is determined according to the retained elements.

3. The method for dividing the voltage control area of ​​the distribution network according to claim 2, characterized in that: Determining the cut set according to the retained elements includes: Determine the edge between the two nodes corresponding to the retained elements as the key edge; The cut set is determined according to the key edge.

4. The method for dividing the voltage control area of ​​the distribution network according to claim 1, characterized in that: Determining the voltage increment matrix corresponding to each node in the distribution network includes: Determine a sensitivity matrix of each node in the distribution network, wherein the sensitivity matrix is ​​used to reflect the correlation between the voltage change of each node and the power change of the distribution network; The power of each node is changed from the first power to the second power in turn, and the voltage change of each node after the power is changed is determined according to the sensitivity matrix, so as to obtain the voltage increment matrix, wherein the power change of each node is the same, and when the power of any node among the nodes is changed, the power of nodes other than the arbitrary node is maintained at the first power.

5. The method for dividing the voltage control area of ​​the distribution network according to claim 1, characterized in that: Clustering each node in the distribution network according to the cut set and the voltage increment matrix includes: The first step is to determine each row element in the voltage increment matrix as a sample, and determine each sample as a sample category; The second step is to determine the distance between each sample category; In the third step, the two sample categories with the closest distance are merged into one sample category, and when the number of remaining sample categories is greater than the preset number of sample categories, jump to the second step.

6. The method for dividing the voltage control area of ​​the distribution network according to claim 5, characterized in that: Determining the distance between each sample category includes: In the case where there are multiple samples in a sample category, for each first sample in a first sample category, determining the distance between the first sample and each second sample in a second sample category, wherein the first sample category is any sample category among the sample categories, and the second sample category is any sample category among the sample categories except the first sample category; The minimum value of the distance between the first sample and the second sample is determined as the distance between the first sample category and the second sample category.

7. The method for dividing the voltage control area of ​​the distribution network according to claim 5, characterized in that: Determining the distance between each sample category includes: In the case where there are multiple samples in a sample category, the average square distance of all sample pairs between a first sample category and a second sample category is determined to be the distance between the first sample category and the second sample category, wherein the sample pairs include a first sample in the first sample category and a second sample in the second sample category, the first sample category is any sample category among the sample categories, and the second sample category is any sample category among the sample categories except the first sample category.

8. The method for dividing the voltage control area of ​​the distribution network according to claim 5, characterized in that: Determining the distance between each sample category includes: Determine the increment of the sum of squared deviations between any two sample categories in each sample category, wherein the increment of the sum of squared deviations is obtained by subtracting the sum of squared deviations of the two sample categories before merging from the sum of squared deviations of the sample category obtained after merging the any two sample categories; The increment of the sum of squared deviations is taken as the distance between any two sample categories.

9. A distribution network dispatching device, characterized in that: include: A first processing module is used to obtain power flow information of each node in the distribution network, and determine a system admittance matrix of the distribution network according to the power flow information, wherein the nodes include generator nodes and load nodes; A second processing module is used to determine the cut sets corresponding to each area in the distribution network according to the system admittance matrix, wherein the cut sets are used to determine the preliminary partitioning result of the distribution network; A third processing module is used to determine a voltage increment matrix corresponding to each node in the distribution network, wherein the voltage increment matrix is ​​used to reflect the voltage change of each node after the power of any node in the nodes changes by a preset value; A fourth processing module is used to cluster the voltage increment matrix by using the cut set as clustering prior information to obtain a target partition result of the distribution network, wherein the target partition result includes the area to which each node belongs; A fifth processing module is used to perform voltage partitioning control on the distribution network according to the target partitioning result.

10. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the method for dividing the voltage control area of ​​the distribution network according to any one of claims 1 to 8.

11. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the method for dividing the voltage control area of ​​the distribution network according to any one of claims 1 to 8 is executed when the program is run.

12. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, implements the method for dividing the voltage control area of ​​the power distribution network according to any one of claims 1 to 8.

Images