CN116780557A - Power distribution network voltage control method and system based on clustering partition algorithm - Google Patents
Power distribution network voltage control method and system based on clustering partition algorithm Download PDFInfo
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Abstract
The application relates to the technical field of power system automation, and discloses a power distribution network voltage control method and system based on a clustering partition algorithm, wherein the method comprises the steps of calculating each phase voltage-reactive sensitivity matrix of a three-phase unbalanced power distribution network; according to the voltage-reactive sensitivity matrix, calculating a correlation coefficient between the nodes and the clustering clusters, and dividing a voltage control area of the power distribution network by using a rapid incremental clustering algorithm; according to the method, reactive compensation resources are called to carry out voltage correction by using a rule-based voltage control strategy, so that the problem that a large amount of computation and communication are needed in a centralized optimization-based method is avoided, and the control response speed is improved.
Description
Technical Field
The application relates to the technical field of power system automation, in particular to a power distribution network voltage control method and system based on a clustering partition algorithm.
Background
The method for voltage control by using distributed energy resources can be divided into three types, i.e., centralized, decentralized and distributed. Centralized approaches typically precondition the observability of the entire distribution network, belong to global optimization problems, and rely on monitoring and control facilities with communication capabilities. The decentralized approach aims to regulate the voltage of a given node, requiring only local measurement data. The distributed control method allows coordination between the partial devices and limited data exchange between the devices using low bandwidth communication, achieving coordinated control with all resources available at the time at minimal cost.
With the rapid development of distributed energy sources, power distribution network voltage control becomes more and more important. Traditional centralized voltage control methods have been difficult to meet the control demands of modern power distribution networks due to the large amount of communication and computing resources required. In order to solve this problem, some voltage control methods based on power distribution network partitions have appeared in recent years. These methods divide a power distribution network into a plurality of sub-areas and use local controllers to regulate reactive compensation resources within each area. These methods have faster response times and less communication requirements than traditional centralized voltage control methods.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present application has been made in view of the above-described problems occurring in the prior art.
Therefore, the application provides a power distribution network voltage control method based on a clustering partition algorithm, which can realize the distributed utilization of reactive compensation resources and keep the system voltage level in a safe range.
In order to solve the technical problems, the application provides a power distribution network voltage control method based on a clustering partition algorithm, which comprises the following steps:
calculating a voltage-reactive sensitivity matrix of each phase of the three-phase unbalanced power distribution network;
according to the voltage-reactive sensitivity matrix, calculating a correlation coefficient between the nodes and the clustering clusters, and dividing a voltage control area of the power distribution network by using a rapid incremental clustering algorithm;
and partitioning the power distribution network according to the partitioned voltage control area, detecting voltage out-of-limit nodes in the area, constructing a priority list according to the sensitivity correlation level, and sequentially calling reactive compensation resources to perform voltage correction.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the voltage-reactive sensitivity matrix comprises an influence relationship of reactive compensation resources of an analysis system on node voltage level,
wherein ,SV-Q The voltage-reactive sensitivity matrix is adopted, and N is the number of load nodes in the power distribution network;
wherein i is the ith row element, j is the jth row element, q i,j Injecting a unit reactive power into the node j to the extent that the voltage of the node i is affected,representing the voltage level of node i, ">Represents the voltage level of node i after reactive power injection, Δq j Indicating the amount of reactive power injected at node j.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the dividing the voltage control area of the distribution network comprises obtaining S based on the current load condition V-Q And calculates the mean value mu of the j-th column j Sum of variances sigma j Calculating a correlation matrix C of node sensitivity Q It is indicated that the number of the elements is,
c m,n the pearson correlation coefficients representing two columns of the voltage-reactive sensitivity matrix m, n, representing the correlation between nodes m, n when voltage regulation is performed, are calculated as,
when classifying a new load node l, the correlation with the current kth control region uses the average correlation coefficient m ccl,k The evaluation is carried out, the calculation formula is that,
wherein x represents the index of the xth load node in the control region K, K represents the total number of the control regions, m k The number of load nodes for the kth control region.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the priority list comprises, when the reactive resource in the coordination area realizes voltage control, a node sensitivity correlation coefficient according to calculationAssigning priority levels of reactive resource call to all nodes x in the region k, and arranging the nodes according to the calculated correlation coefficient in descending order;
representing the priority list of the kth control region as PL k The voltage controller presses PL k Sequentially calling reactive compensation resources on each node until the total injection amount of reactive power reaches delta Q req If the reactive power compensation device is not installed on the node, the next node is jumped to call the reactive power resource.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the sequentially calling reactive compensation resources to perform voltage correction comprises the steps that when a power distribution network is divided into a plurality of control areas, each area calls the reactive compensation resources in the jurisdiction area to perform voltage control, when a voltage out-of-limit node exists in a kth control area, a controller of the area enters a voltage correction mode, the most serious overvoltage/undervoltage node r is marked, and when the node r needs to correct the voltage deviation delta V r In order to achieve this, the first and second,
wherein ,represents the highest voltage value at overvoltage, +.>Representing the lowest voltage value at the undervoltage, vmax/Vmin is the upper and lower limits of the node voltage level, according to voltage-noneAnd calculating the required reactive compensation quantity by using the power sensitivity matrix.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the reactive compensation quantity includes,
wherein α represents a threshold value of a correlation coefficient, q r,r The voltage-reactive sensitivity of the node r, deltaQ, is taken out of the SV-Q matrix req Is reactive compensation quantity.
As a preferable scheme of the power distribution network voltage control method based on the clustering and partitioning algorithm, the application comprises the following steps: the fast incremental clustering algorithm comprises mcc calculated if K control areas exist l,k All lower than the correlation coefficient threshold alpha, the node l is classified as a new control region K+1, if the mcc calculated by the existing K control regions l,k All above the correlation coefficient threshold α, classifying the node as the control region with the largest average correlation coefficient.
Another object of the present application is to provide a system for controlling voltage of a power distribution network based on a clustering partitioning algorithm, which divides a power distribution line into a plurality of weakly coupled areas, so that voltage can be independently adjusted in each area, thereby improving control accuracy and efficiency.
As a preferable scheme of the power distribution network voltage control system based on the clustering and partitioning algorithm, the application comprises the following steps: the system comprises a data acquisition module, a clustering partition module, a reactive power control module and a system monitoring module;
the data acquisition module acquires data of the power distribution network;
the clustering partition module performs clustering analysis on the collected data and partitions the power distribution network into areas;
the reactive power control module is used for controlling reactive power in each partition according to the clustering partition result;
and the system monitoring module is used for carrying out state detection and fault diagnosis on the whole system.
A computer device comprising a memory and a processor, said memory storing a computer program, characterized in that the processor, when executing said computer program, implements the steps of a method for controlling the voltage of a distribution network based on a clustering partitioning algorithm.
A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of a method for controlling the voltage of a power distribution network based on a clustering partitioning algorithm.
The application has the beneficial effects that: the method uses the voltage control strategy based on the rule to call the reactive compensation resource to carry out voltage correction, thereby avoiding the problem that a large amount of calculation and communication are required in the centralized optimization-based method and improving the control response speed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
fig. 1 is a schematic flow chart of a power distribution network voltage control method based on a clustering partition algorithm according to an embodiment of the present application;
fig. 2 is a schematic diagram of a fern partitioning result of a power distribution network voltage control method based on a clustering partitioning algorithm according to an embodiment of the present application;
fig. 3 is a schematic diagram of a sensitivity calculation result under different proportions of photovoltaic permeability of a power distribution network voltage control method based on a clustering partition algorithm according to an embodiment of the present application;
fig. 4 is a schematic diagram of cluster numbers under different phase relation number threshold settings of a power distribution network voltage control method based on a clustering partition algorithm according to an embodiment of the present application;
fig. 5 is a schematic diagram of node voltage comparison results under different voltage control strategies in a power distribution network voltage control method based on a clustering partition algorithm according to an embodiment of the present application;
fig. 6 is a schematic flow chart of a power distribution network voltage control system based on a clustering partition algorithm according to an embodiment of the present application.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1-2, a first embodiment of the present application provides a power distribution network voltage control method based on a clustering partitioning algorithm, including:
s1: calculating a voltage-reactive sensitivity matrix of each phase of the three-phase unbalanced power distribution network;
further, the voltage-reactive sensitivity matrix comprises an analysis system reactive compensation resource influence relationship on node voltage level,
wherein ,SV-Q The voltage-reactive sensitivity matrix is adopted, and N is the number of load nodes in the power distribution network;
wherein i is the ith row element, j is the jth row element, q i,j Injecting a unit reactive power into node j versus node i voltageThe degree of influence is such that,representing the voltage level of node i, ">Represents the voltage level of node i after reactive power injection, Δq j Indicating the amount of reactive power injected at node j.
It should be noted that SV-Q describes the sensitivity of a single-phase load node, and for a three-phase distribution network in real scenarios, a voltage-reactive sensitivity matrix may be calculated for each phase separately.
S2: according to the voltage-reactive sensitivity matrix, calculating a correlation coefficient between the nodes and the clustering clusters, and dividing a voltage control area of the power distribution network by using a rapid incremental clustering algorithm;
it should be noted that the voltage-reactive sensitivity matrix includes, analyzing the influence relationship of reactive compensation resources on node voltage level,
wherein ,SV-Q The voltage-reactive sensitivity matrix is adopted, and N is the number of load nodes in the power distribution network;
wherein i is the ith row element, j is the jth row element, q i,j Injecting a unit reactive power into the node j to the extent that the voltage of the node i is affected,representing the voltage level of node i, ">Represents the voltage level of node i after reactive power injection, Δq j Indicating the amount of reactive power injected at node j.
S3: and partitioning the power distribution network according to the partitioned voltage control area, detecting voltage out-of-limit nodes in the area, constructing a priority list according to the sensitivity correlation level, and sequentially calling reactive compensation resources to perform voltage correction.
Furthermore, due to factors such as uneven load distribution, the actual power distribution network has the problem of three-phase unbalance. Therefore, when voltage regulation is performed, each phase of load needs to be clustered separately to realize partition control.
It should be noted that, in theory, each voltage control region is composed of load nodes of high correlation voltage sensitivity. To determine the number of control areas in the distribution feeder and the number of load nodes in each control area, the load nodes are clustered using a fast delta clustering (FIC, fast incremental clustering) method using a voltage-reactive sensitivity matrix calculated under different load conditions. The FIC is a non-iterative algorithm that sorts the data one by one in a sequential manner. Thus, each load node is considered only once, and its class, which is clustered, does not change all the time after classification of all load nodes is completed.
Further, since FIC depends on the order of data processing and voltage sensitivity varies in proportion to distribution distance, load nodes need to be sorted in ascending order according to the distance between each node and the substation before FIC is applied.
Further, the dividing the voltage control area of the distribution network includes, in each time interval, obtaining S based on the current load condition V-Q And calculates the mean value mu of the j-th column j Sum of variances sigma j Calculating a correlation matrix C of node sensitivity Q It is indicated that the number of the elements is,
c m,n the pearson correlation coefficients representing two columns of the voltage-reactive sensitivity matrix m, n, representing the correlation between nodes m, n when voltage regulation is performed, are calculated as,
the values of the correlation coefficients are transformed within-1 to 1, the closer 1 is to the stronger the correlation between the nodes m, n, "-1" is to the negative correlation, "0" is to the uncorrelation, and "1" is to the positive correlation.
When classifying a new load node l, the correlation with the current kth control region uses the average correlation coefficient m ccl,k The evaluation is carried out, the calculation formula is that,
wherein x represents the index of the xth load node in the control region K, K represents the total number of the control regions, m k The number of load nodes for the kth control region.
It should be noted that the fast incremental clustering algorithm includes mcc calculated if there are K control regions available l,k All lower than the correlation coefficient threshold alpha, the node l is classified as a new control region K+1, if the mcc calculated by the existing K control regions l,k All above the correlation coefficient threshold α, classifying the node as the control region with the largest average correlation coefficient.
Furthermore, the sequentially calling reactive compensation resources to perform voltage correction includes that when the power distribution network is divided into a plurality of control areas, each area calls reactive compensation resources in the jurisdiction area to perform voltage control, when a voltage out-of-limit node exists in a kth control area, a controller of the area enters a voltage correction mode, the most serious overvoltage/undervoltage node r is marked, and when the node r needs to correct a voltage deviation delta V r In order to achieve this, the first and second,
wherein ,representing the most significant over-voltageHigh voltage value>The lowest voltage value in undervoltage is represented, vmax/Vmin is the upper limit and the lower limit of the node voltage level, and the required reactive compensation quantity is calculated according to the voltage-reactive sensitivity matrix.
It should be noted that the reactive compensation amount includes,
wherein α represents a threshold value of a correlation coefficient, q r,r The voltage-reactive sensitivity of the node r, deltaQ, is taken out of the SV-Q matrix req Is reactive compensation quantity.
It should be noted that the priority list includes, when the reactive resource in the coordination area realizes the voltage control, a correlation coefficient according to the calculated node sensitivityAssigning priority levels of reactive resource call to all nodes x in the region k, and arranging the nodes according to the calculated correlation coefficient in descending order;
representing the priority list of the kth control region as PL k The voltage controller presses PL k Sequentially calling reactive compensation resources on each node until the total injection amount of reactive power reaches delta Q req If the reactive power compensation device is not installed on the node, the next node is jumped to call the reactive power resource. Thus, a distributed partition voltage control method based on a priority list is realized.
Example 2
Referring to fig. 3-5, for one embodiment of the present application, a method for controlling voltage of a power distribution network based on a clustering partition algorithm is provided, and in order to verify the beneficial effects of the present application, scientific demonstration is performed through experiments.
The actual data of the three-phase unbalanced distribution network in a certain region of North America is adopted for analyzing the feasibility of the application. The system comprises 1388 nodes, 415 of which are load nodes. The total 1024 household loads under the distribution feeder line are 3.52MW peak load. The photovoltaic installed capacity is assumed to be 5.12MW and its reactive compensation capability can be invoked for voltage control based on the photovoltaic inverter. As can be seen from fig. 3, as the photovoltaic permeability increases, the voltage sensitivity has a tendency to gradually rise, i.e. the influence of reactive compensation on the voltage regulation increases. Fig. 4 shows the influence of the correlation coefficient threshold on the number of clusters, and it can be seen that when the value is smaller than 0.92, each phase load is a cluster, which indicates that the phase sequence is an important factor of the voltage regulation sensitivity. At the same time, with increasing size, the interior of each phase is also divided into clusters, which indicates that there is a more intimate link between certain loads under the same phase sequence.
In order to verify the voltage control effect of the method, load data of one week are selected to construct a power distribution network scene, three voltage control modes of centralized control, non-control and partition control are applied, the maximum node voltage level is recorded, and a violin diagram is drawn, as shown in fig. 5. It can be seen that there is a serious voltage out-of-limit problem in the uncontrolled mode, and centralized control can strictly guarantee that the voltage level is within the range. In contrast, the proposed partition control method can better guarantee the voltage level, only in rare cases there is a voltage out-of-limit condition, and the condition is slight. In terms of calculation speed, the solving time of the centralized control method based on mathematical optimization is within the range of 73 seconds-171 seconds, and the partition control method provided by the application only takes 2 milliseconds, so that the control response time is greatly improved.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered by the scope of the claims of the present application.
Example 3
A third embodiment of the present application, which is different from the first two embodiments, is:
the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Example 4
Referring to fig. 6, a fourth embodiment of the present application provides a system of a power distribution network voltage control method based on a clustering partitioning algorithm, including: the system comprises a data acquisition module, a clustering partition module, a reactive power control module and a system monitoring module;
the data acquisition module acquires data of the power distribution network, including information such as load data, power supply data, line data and the like. Such data may be acquired by sensors or monitoring devices.
The clustering partitioning module performs clustering analysis on the collected data, partitions the power distribution network into areas, and the clustering method is used for concentrating loads with different properties on the premise of ensuring that the power factors in the areas are close to target values, so that reactive power control is convenient to implement.
And the reactive power control module is used for controlling reactive power in each partition according to the clustering partition result, and the control method can be realized by adopting measures such as a static compensator, a capacitive compensator, a reactor and the like. At the same time, there is also a need to design control strategies such as power factor based, voltage based, current based, etc. strategies.
The system monitoring module is used for carrying out state detection and fault diagnosis on the whole system, and when a fault occurs, an alarm needs to be sent out in time and corresponding measures are taken to ensure the normal operation of the power distribution network.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered by the scope of the claims of the present application.
Claims (10)
1. A power distribution network voltage control method based on a clustering partition algorithm is characterized by comprising the following steps of: comprising the steps of (a) a step of,
calculating a voltage-reactive sensitivity matrix of each phase of the three-phase unbalanced power distribution network;
according to the voltage-reactive sensitivity matrix, calculating a correlation coefficient between the nodes and the clustering clusters, and dividing a voltage control area of the power distribution network by using a rapid incremental clustering algorithm;
and partitioning the power distribution network according to the partitioned voltage control area, detecting voltage out-of-limit nodes in the area, constructing a priority list according to the sensitivity correlation level, and sequentially calling reactive compensation resources to perform voltage correction.
2. The power distribution network voltage control method based on the clustering partitioning algorithm as claimed in claim 1, wherein: the voltage-reactive sensitivity matrix comprises an influence relationship of reactive compensation resources of an analysis system on node voltage level,
wherein ,SV-Q The voltage-reactive sensitivity matrix is adopted, and N is the number of load nodes in the power distribution network;
wherein i is the ith row element, j is the jth row element, q i,j Injecting a unit reactive power into the node j to the extent that the voltage of the node i is affected,representing the voltage level of node i, ">Represents the voltage level of node i after reactive power injection, Δq j Indicating the amount of reactive power injected at node j.
3. The power distribution network voltage control method based on the clustering partitioning algorithm as claimed in claim 2, wherein: the dividing the voltage control area of the distribution network comprises obtaining S based on the current load condition V-Q And calculates the mean value mu of the j-th column j Sum of variances sigma j Calculating a correlation matrix C of node sensitivity Q It is indicated that the number of the elements is,
c m,n the pearson correlation coefficients representing two columns of the voltage-reactive sensitivity matrix m, n, representing the correlation between nodes m, n when voltage regulation is performed, are calculated as,
when classifying a new load node l, the correlation with the current kth control region uses the average correlation coefficient m ccl,k The evaluation is carried out, the calculation formula is that,
wherein x represents the index of the xth load node in the control region K, K represents the total number of the control regions, m k The number of load nodes for the kth control region.
4. A power distribution network voltage control method based on a clustering partitioning algorithm as claimed in claim 3, wherein: the priority list comprises, when the reactive resource in the coordination area realizes voltage control, a node sensitivity correlation coefficient according to calculationAssigning priority levels of reactive resource call to all nodes x in the region k, and arranging the nodes according to the calculated correlation coefficient in descending order;
representing the priority list of the kth control region as PL k The voltage controller presses PL k Sequentially calling reactive compensation resources on each node until the total injection amount of reactive power reaches delta Q req If the reactive power compensation device is not installed on the node, the next node is jumped to call the reactive power resource.
5. The power distribution network voltage control method based on the clustering partitioning algorithm as claimed in claim 4, wherein: the sequentially calling reactive compensation resources to perform voltage correction comprises the steps that when a power distribution network is divided into a plurality of control areas, each area calls the reactive compensation resources in the jurisdiction area to perform voltage control, when a voltage out-of-limit node exists in a kth control area, a controller of the area enters a voltage correction mode, the most serious overvoltage/undervoltage node r is marked, and when the node r needs to correct the voltage deviation delta V r In order to achieve this, the first and second,
wherein ,represents the highest voltage value at overvoltage, +.>The lowest voltage value in undervoltage is represented, vmax/Vmin is the upper limit and the lower limit of the node voltage level, and the required reactive compensation quantity is calculated according to the voltage-reactive sensitivity matrix.
6. The power distribution network voltage control method based on the clustering partitioning algorithm as set forth in claim 5, wherein: the reactive compensation quantity includes,
wherein α represents a threshold value of a correlation coefficient, q r,r The voltage-reactive sensitivity of the node r, deltaQ, is taken out of the SV-Q matrix req Is reactive compensation quantity.
7. The power distribution network voltage control method based on the clustering partitioning algorithm as set forth in claim 6, wherein: the fast incremental clustering algorithm comprises mcc calculated if K control areas exist l,k All lower than the correlation coefficient threshold alpha, the node l is classified as a new control region K+1, if the mcc calculated by the existing K control regions l,k All above the correlation coefficient threshold α, classifying the node as the control region with the largest average correlation coefficient.
8. A system based on the clustering partitioning algorithm-based power distribution network voltage control method as claimed in any one of claims 1 to 7, wherein: the system comprises a data acquisition module, a clustering partition module, a reactive power control module and a system monitoring module;
the data acquisition module acquires data of the power distribution network;
the clustering partition module performs clustering analysis on the collected data and partitions the power distribution network into areas;
the reactive power control module is used for controlling reactive power in each partition according to the clustering partition result;
and the system monitoring module is used for carrying out state detection and fault diagnosis on the whole system.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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