A distributed photovoltaic voltage coordinated control method for distribution network based on dynamic partitioning

Abstract

The present invention provides a distributed photovoltaic voltage coordinated control method for a distribution network based on dynamic partitioning, and belongs to the technical field of distributed photovoltaic voltage coordinated control for distribution networks; the present invention realizes flexible response to the over-limit degree of different nodes through dynamic partitioning and designing consistency variables, improves the coordination and overall effect of voltage control, and solves the voltage over-limit problem of the distribution network caused by distributed photovoltaic access. The technical scheme adopted is: calculating the voltage sensitivity and electrical distance of each node according to the line parameters of the distribution network; constructing dynamic partitioning indicators; selecting a dominant node according to the influence of a certain node on other nodes in the partition; establishing a dynamic partitioning objective function, using a genetic algorithm to perform partitioning solution, partitioning once every hour, outputting the partitioning results and calculating the dominant nodes in each partition; the present invention is applied to the distributed photovoltaic voltage coordinated control of the distribution network.

Description

Technical Field

[0001] The present invention provides a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning, belonging to the technical field of coordinated control of distributed photovoltaic voltage in a distribution network. Background Art

[0002] With the establishment and use of more and more distributed photovoltaic power plants in recent years, more and more photovoltaic power generation has been connected to the distribution network. However, the randomness and intermittency of photovoltaic power generation itself will lead to frequent voltage fluctuations and frequent voltage over-limit situations, especially in low-load periods and high light intensity. The distribution network voltage is significantly high. At night, when the user load is large and the photovoltaic power generation is not working, the distribution network voltage will be low and it needs to be adjusted and controlled.

[0003] The current voltage regulation methods include adding voltage regulators and reactive power compensation devices, but the added devices often find it difficult to respond in real time to the voltage fluctuations caused by photovoltaic power generation, and the regulation range is limited, which cannot meet the voltage requirements under a high proportion of distributed photovoltaic access. With the large-scale access of distributed photovoltaics, some nodes in the distribution network are prone to voltage over-limit phenomena. Existing control methods are difficult to effectively respond to voltage fluctuations, especially when the severity of over-limit is inconsistent at different nodes. Traditional zoning control strategies lack flexibility.

[0004] There are also methods that use the reactive and active power regulation of photovoltaic inverters to achieve the distribution network voltage management target. For this purpose, it is proposed to use clustering algorithms to partition distributed photovoltaic clusters, and then locally control the output of photovoltaic inverters based on the partitioning results, thereby adjusting the voltage at the grid connection point; however, such methods all adopt one-time partitioning, without considering the randomness of photovoltaic output and the dynamic changes of load. The voltage deviation of different nodes changes dynamically, which will cause changes in the power balance between partitions. Fixed partitioning schemes cannot adapt to the dynamically changing operating conditions of the distribution network. This method is difficult to dynamically adjust according to the voltage regulation needs of different nodes, resulting in uneven distribution of control resources. Some nodes may not be able to effectively eliminate the voltage over-limit problem due to insufficient regulation capabilities.

[0005] In addition, there are also methods that use the utilization rate of distributed photovoltaic reactive or active power to design consistency variables, specifically controlling the node voltage by adjusting the output of distributed power sources through the convergence of the consistency protocol. The purpose of this method is to make the reactive or active utilization rate of distributed photovoltaics approach consistency, but it does not take into account that different nodes have different effects on voltage, making it difficult to maximize the voltage regulation effect of photovoltaic inverters. There is a problem of insufficient coordination in the collaborative control of multiple photovoltaic inverters, and it is impossible to fully utilize the voltage regulation contribution of each inverter to reach a consensus, resulting in poor voltage control effect. Summary of the invention

[0006] The present invention achieves flexible response to the over-limit degree of different nodes through dynamic partitioning and design of consistency variables, improves the coordination and overall effect of voltage control, and solves the voltage over-limit problem of distribution network caused by distributed photovoltaic access. The technical solution adopted is: a distributed photovoltaic voltage coordinated control method of distribution network based on dynamic partitioning, including the following coordinated control steps:

[0007] Step 1: Calculate the voltage sensitivity and electrical distance of each node based on the distribution network line parameters;

[0008] Step 2: Construct dynamic partition index;

[0009] Step 3: Select the dominant node based on the impact of a node on other nodes in the partition;

[0010] Step 4: Set up the dynamic partition objective function, the expression is:

[0011] ;

[0012] In the formula, λ 1 and λ 2 are weight factors, satisfying λ 1 +λ 2 =1, to adjust the partitioning results, α and β are the intra-region coupling degree and interval dispersion respectively;

[0013] Then, the genetic algorithm is used to solve the partitioning problem, partitioning once every hour, outputting the partitioning results and calculating the dominant nodes in each partition;

[0014] Step 5: After the voltage exceeds the limit, the voltage deviation value of each node that exceeds the limit is counted, and then the reactive regulation power of each distributed photovoltaic in the distribution network and the weight coefficient of the photovoltaic node in the partition are calculated according to the partition result in step 4;

[0015] Step 6: Distributed photovoltaics in each zone respond to reactive power regulation through the consistency algorithm results;

[0016] Step 7: If the reactive power regulation resources of the distributed photovoltaics in each partition are exhausted, the active power regulation method is adopted, and the distributed photovoltaics respond according to the consistency regulation method in step 6.

[0017] The method for calculating the voltage sensitivity of each node in step 1 is:

[0018] The active and reactive-voltage sensitivity matrices are used for expression:

[0019] ;

[0020] Where V 0 is the node voltage at the beginning of the line; S P,ijis the active power-voltage sensitivity between the i-th node and the j-th node; S Q,ij is the reactive power-voltage sensitivity between the i-th grid connection point and the j-th grid connection point; R i and X i are the resistance and reactance values ​​of the i-th line respectively;

[0021] The method for calculating the electrical distance is:

[0022] The electrical distance is calculated using voltage sensitivity. The electrical distance between nodes i and j is calculated as:

[0023] ;

[0024] In the formula, S P,im is the active power-voltage sensitivity between the ith node and the mth node; S P,jm is the active power-voltage sensitivity between the jth node and the mth node; S Q,im is the reactive power-voltage sensitivity between the ith node and the mth node; S Q,jm is the reactive power-voltage sensitivity between the jth node and the mth node.

[0025] The specific method for constructing the dynamic partition index in step 2 is:

[0026] The intra-region coupling degree α and interval dispersion β of distributed photovoltaic nodes are calculated respectively, and the calculation formula is:

[0027] ;

[0028] ;

[0029] Where N is the number of partitions; A is the node set of partition x; L ave,x is the average distance of partition x.

[0030] The specific method of selecting the dominant node in step 3 is:

[0031] Select the leading nodeδ based on the impact of the node on other nodes in the partition x , the selection basis satisfies the following calculation formula:

[0032] ;

[0033] In the formula, S P,jj is the active power-voltage sensitivity of the jth node to itself; S Q,jj is the reactive power-voltage sensitivity of the jth node to itself.

[0034] The specific method for dynamic partitioning in step 4 is:

[0035] Step 4.1: Draw a network topology diagram based on the actual power distribution network;

[0036] Step 4.2: Convert each node and branch of the network topology into genetic algorithm chromosome code:

[0037] The length of the chromosome encoding vector is equal to the total number of branches in the distribution topology. 0 and 1 elements are used to represent the partition relationship between branches and nodes. 0 means that the nodes at both ends of the branch are not in the same partition, and 1 means that the nodes at both ends of the branch are in the same partition.

[0038] Step 4.3: Input the number of individuals, maximum genetic generation, generation gap coefficient, crossover probability, mutation probability, and partition index weight coefficient required by the genetic algorithm;

[0039] Step 4.4: Randomly encode chromosomes and generate the initial population:

[0040] The partitioning scheme is obtained by decoding the chromosome, and the individual fitness is calculated by the partitioning evaluation index;

[0041] Step 4.5: Perform selection, crossover, and mutation operations to obtain the offspring population, calculate the fitness of the offspring population, insert the offspring into the parent generation to obtain a new population, and output the partition result after reaching the maximum genetic generation number;

[0042] Step 4.6: After obtaining the partition results, select the dominant node of each partition using the calculation formula in step 2.

[0043] In step 5, after the voltage exceeds the limit, the voltage deviation value of each exceeding-limit node is counted, and the calculation formula is:

[0044] ;

[0045] Where U ref is the reference voltage, K is the set of nodes that exceed the limit, U k is the real-time voltage value of the voltage-exceeding-limit node;

[0046] According to the partition results in step 4, calculate the reactive regulation power ΔQ of each distributed photovoltaic i (t), the calculation formula is:

[0047] ;

[0048] In the formula, w i is the weight coefficient of the distributed photovoltaic leading node and other nodes; η i (t) is the voltage regulation contribution of photovoltaic node i at time t; Q i,max is the maximum reactive output of distributed photovoltaic i;

[0049] Calculate the weight coefficient of the photovoltaic nodes in the partition using the following formula:

[0050] ;

[0051] In the formula, S PV,i is the grid-connected capacity of the ith distributed photovoltaic; m is the number of distributed photovoltaic nodes in the partition.

[0052] The consistency algorithm used in step 6 is specifically:

[0053] Each node bears the voltage fluctuation according to its voltage regulation contribution, and finally reaches the following consistency:

[0054] ;

[0055] Where η dom (t) and η i (t) are the voltage regulation contributions of the dominant node and other nodes at time t; ΔU dom (t) and ΔU i (t) are the voltage deviations of the dominant node and other nodes at time t; ΔQ dom (t) and ΔQ i (t) are the reactive regulation powers of the dominant node and other nodes at time t; w dom and w i are the weight coefficients of the dominant node and other nodes respectively; Q dom,max and Q i,max are the maximum reactive power regulation margins of the dominant node and other nodes respectively.

[0056] The specific method of responding to reactive power regulation in step 6 is:

[0057] Step 6.1: Determine the adjacency matrix in each partition according to the network topology of the distribution network. The expression is:

[0058] ;

[0059] Where, d ij represents the communication weight between nodes i and j; the n×n matrix is ​​a square matrix with n elements in both rows and columns, where n is the number of nodes in the distribution network;

[0060] Step 6.2: Calculate the communication weight d between nodes i and j ij , the calculation formula is:

[0061] ;

[0062] In the formula, if there is communication between nodes i and j, then s ij =1, otherwise s ij =0,Ni is the number of nodes i;

[0063] Step 6.3: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula:

[0064] ;

[0065] Where η i (k) represents the reactive voltage regulation contribution of PV node i, and k is the sampling time.

[0066] The specific steps of the active power regulation method adopted in step seven are:

[0067] Step 7.1: Calculate the active regulation power of each distributed photovoltaic:

[0068] ;

[0069] In the formula, w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes; ρ i (t) is the voltage regulation contribution; ΔP i (t) Each distributed photovoltaic participating in voltage management should respond to the active power regulation amount;

[0070] Step 7.2: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula:

[0071] ;

[0072] In the formula, ρ i (k) represents the reactive voltage regulation contribution of PV node i, k is the sampling time;

[0073] Step 7.3: The distributed photovoltaics in each partition respond to active regulation through the consistency algorithm results. Each node bears the voltage fluctuation according to the voltage regulation contribution, and finally reaches consistency. The consistency expression is:

[0074] ;

[0075] In the formula, ρ dom (t) and ρ i (t) are the voltage regulation contributions of the dominant node and other nodes respectively; ΔU dom (t) and ΔU i (t) are the voltage deviations of the dominant node and other nodes at time t, ΔP dom (t) and ΔP i (t) are the active regulation power of the dominant node and other nodes at time t; w domis the weight coefficient of the dominant node, P dom,max and P i,max are the maximum active regulation margins of the dominant node and other nodes respectively.

[0076] The beneficial effects of the present invention compared with the prior art are as follows: the distributed photovoltaic voltage coordinated control method of the distribution network provided by the present invention dynamically partitions nodes with different voltage sensitivities, so that the control resources of the photovoltaic inverter can be allocated in a targeted manner, thereby improving the response capability to voltage fluctuations in different regions, avoiding the ineffective response of the global control strategy to local problems, and improving the flexibility of voltage control; and by using the voltage regulation contribution to construct a consistency variable, reasonably allocate the regulation capability of each inverter, optimize the allocation of control resources, maximize the voltage regulation effect, avoid the problem of over-regulation or under-regulation of some nodes, and improve the control efficiency; at the same time, the present invention adopts a consistency control strategy to realize the coordinated work of multiple photovoltaic inverters, enhance the coordination between the nodes within the system, improve the overall effect of voltage regulation, and ensure the voltage stability of the distribution network under large-scale photovoltaic access. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] The present invention will be further described below in conjunction with the accompanying drawings:

[0078] Figure 1 The present invention is a flowchart of the steps of the method for coordinated control of distributed photovoltaic voltage in a power distribution network. DETAILED DESCRIPTION

[0079] like Figure 1 As shown, the present invention provides a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning. The method is based on a method for dynamic partitioning of distributed photovoltaics and uses the consistency principle to achieve coordinated control of active and reactive voltages of distributed photovoltaics. The present invention can dynamically partition according to the severity of over-limit of different nodes, use voltage regulation contribution to construct consistency variables, optimize and adjust active and reactive power distribution in real time, achieve effective suppression of voltage over-limit, ensure safe and stable operation of the distribution network, and at the same time improve the quality of electric energy, providing technical support for the sustainable development of the power system.

[0080] The distributed photovoltaic voltage coordinated control method of the distribution network based on dynamic partitioning provided by the present invention specifically includes the following control steps:

[0081] Step 1: Calculate the voltage sensitivity of each node according to the distribution network line parameters. The active and reactive-voltage sensitivity matrix expressions are as follows:

[0082] (1);

[0083] Where V 0 is the node voltage at the beginning of the line; SP,ij is the active power-voltage sensitivity between the i-th node and the j-th node; S Q,ij is the reactive power-voltage sensitivity between the i-th grid connection point and the j-th grid connection point; R i and X i are the resistance and reactance values ​​of the i-th line respectively.

[0084] Using voltage sensitivity to calculate electrical distance, the electrical distance between nodes i and j is:

[0085] (2);

[0086] In the formula, S P,im is the active power-voltage sensitivity between the ith node and the mth node; S P,jm is the active power-voltage sensitivity between the jth node and the mth node; S Q,im is the reactive power-voltage sensitivity between the ith node and the mth node; S Q,jm is the reactive power-voltage sensitivity between the jth node and the mth node;

[0087] Step 2: Construct dynamic partitioning indicators. Calculate the intra-region coupling degree α and interval dispersion β of distributed photovoltaic nodes. The calculation formulas are shown in formula (3) and formula (4) respectively:

[0088] (3);

[0089] (4);

[0090] Where N is the number of partitions; A is the node set of partition x; L ave,x is the average distance of partition x, which is calculated as .

[0091] Step 3: Define the dominant node and select the dominant node based on the impact of the node on other nodes in the partition. x , the selection is based on the following formula:

[0092] (5);

[0093] In the formula, S P,jj is the active power-voltage sensitivity of the jth node to itself; S Q,jj is the reactive power-voltage sensitivity of the jth node to itself;

[0094] Step 4: Set up dynamic partition objective function:

[0095] ;

[0096] Where:1 and λ 2 are weight factors, satisfying λ 1 +λ 2 =1, the partition result can be adjusted.

[0097] Genetic algorithm is used to solve the partition problem, partitioning once every hour, outputting the partition results and calculating the dominant nodes in each partition.

[0098] The specific method of dynamic partitioning is as follows:

[0099] Step 4.1: Draw a network topology diagram based on the actual power distribution network.

[0100] Step 4.2: Convert each node and branch of the network topology into the encoding of the genetic algorithm chromosome. The length of the chromosome encoding vector is equal to the total number of branches in the distribution topology. 0 and 1 elements are used to represent the partition relationship between branches and nodes. 0 means that the nodes at both ends of the branch are not in the same partition, and 1 means that the nodes at both ends of the branch are in the same partition.

[0101] Step 4.3: Input the parameters required by the genetic algorithm, such as the number of individuals, maximum genetic generation, generation gap coefficient, crossover probability, mutation probability, partition index weight coefficient, etc.

[0102] Step 4.4: Randomly encode chromosomes to generate the initial population. Obtain the partitioning scheme by decoding the chromosomes, and calculate the individual fitness through the partitioning evaluation index.

[0103] Step 4.5: Perform selection, crossover, mutation and other operations to obtain the offspring population, calculate the fitness of the offspring population, insert the offspring into the parent generation to obtain a new population. After reaching the maximum genetic generation, output the partition result.

[0104] Step 4.6: After obtaining the partition results, select the dominant node of each partition using the calculation formula in step 2.

[0105] Step 5: After the voltage exceeds the limit, count the voltage deviation values ​​of each node that exceeds the limit , where U ref is the reference voltage, K is the set of nodes that exceed the limit, U k It is the real-time voltage value of the voltage-exceeding-limit node.

[0106] According to the partition results in step 4, calculate the reactive regulation power ΔQ of each distributed photovoltaic i (t):

[0107] (6);

[0108] In the formula, w i is the weight coefficient of the distributed photovoltaic leading node and other nodes; η i(t) is the voltage regulation contribution of photovoltaic node i at time t; Q i,max is the maximum reactive power output of distributed photovoltaic i.

[0109] The calculation formula of the weight coefficient of the photovoltaic node in the partition is as follows:

[0110] (7);

[0111] In the formula, S PV,i is the grid-connected capacity of the ith distributed photovoltaic; m is the number of distributed photovoltaic nodes in the partition.

[0112] Step 6: Distributed photovoltaics in each partition respond to reactive power regulation through the consistency algorithm results. Each node bears voltage fluctuations according to its contribution to voltage regulation and finally reaches consistency. The consistency expression is:

[0113] (8);

[0114] Where η dom (t) and η i (t) are the voltage regulation contributions of the dominant node and other nodes at time t; ΔU dom (t) and ΔU i (t) are the voltage deviations of the dominant node and other nodes at time t; ΔQ dom (t) and ΔQ i (t) are the reactive regulation powers of the dominant node and other nodes at time t; w dom and w i are the weight coefficients of the dominant node and other nodes respectively; Q dom,max and Q i,max are the maximum reactive power regulation margins of the dominant node and other nodes respectively.

[0115] Then reactive power regulation is performed based on consistency. The specific steps are as follows:

[0116] Step 6.1: Determine the adjacency matrix within each partition based on the distribution system network topology , d ij represents the communication weight between nodes i and j;

[0117] Step 6.2: Calculate the communication weight d between nodes i and j ij , the calculation formula is as follows:

[0118] (9);

[0119] In the formula, if there is communication between nodes i and j (i≠j), then s ij =1, otherwise s ij =0,Ni is the number of nodes i.

[0120] Step 6.3: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula:

[0121] (10);

[0122] Where η i (k) represents the reactive voltage regulation contribution of PV node i, and k is the sampling time.

[0123] Step 7: If the reactive power regulation resources of distributed photovoltaics in each partition are exhausted, the active power regulation method is adopted, and the distributed photovoltaics respond according to the above consistency regulation method.

[0124] The specific method of the above distributed photovoltaic active power regulation is:

[0125] Step 7.1: Calculate the active regulation power of each distributed photovoltaic:

[0126] (11);

[0127] In the formula, w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes; ρ i (t) is the voltage regulation contribution; ΔP i (t) Each distributed photovoltaic participating in voltage management should respond with active power regulation.

[0128] Step 7.2: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula, which is:

[0129] (12);

[0130] In the formula, ρ i (k) represents the reactive voltage regulation contribution of PV node i, and k is the sampling time.

[0131] Step 7.3: The distributed photovoltaics in each partition respond to active regulation through the consistency algorithm results. Each node bears the voltage fluctuation according to the voltage regulation contribution, and finally reaches consistency. The consistency expression is:

[0132] (13);

[0133] In the formula, ρ dom (t) and ρ i (t) are the voltage regulation contributions of the dominant node and other nodes respectively; ΔU dom (t) and ΔU i(t) are the voltage deviations of the dominant node and other nodes at time t, ΔP dom (t) and ΔP i (t) are the active regulation power of the dominant node and other nodes at time t; w dom is the weight coefficient of the dominant node, P dom,max and P i,max are the maximum active regulation margins of the dominant node and other nodes respectively.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning, characterized in that: The collaborative control steps include the following: Step 1: Calculate the voltage sensitivity and electrical distance of each node based on the distribution network line parameters; Step 2: Construct dynamic partition index; Step 3: Select the dominant node based on the impact of a node on other nodes in the partition; Step 4: Set up the dynamic partition objective function, the expression is: ； In the formula, λ1 and λ2 are weight factors, respectively, satisfying λ1+λ2=1, to adjust the partitioning results, α and β are the intra-region coupling degree and interval dispersion, respectively; Then, the genetic algorithm is used to solve the partitioning problem, partitioning once every hour, outputting the partitioning results and calculating the dominant nodes in each partition; Step 5: After the voltage exceeds the limit, the voltage deviation value of each node that exceeds the limit is counted, and then the reactive regulation power of each distributed photovoltaic in the distribution network and the weight coefficient of the photovoltaic node in the partition are calculated according to the partition result in step 4; Step 6: Distributed photovoltaics in each zone respond to reactive power regulation through the consistency algorithm results; Step 7: If the reactive power regulation resources of the distributed photovoltaics in each partition are exhausted, the active power regulation method is adopted, and the distributed photovoltaics respond according to the consistency regulation method in step 6.

2. According to claim 1, a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning is characterized in that: The method for calculating the voltage sensitivity of each node in step 1 is: The active and reactive-voltage sensitivity matrices are used for expression: ； Where V0 is the voltage at the node at the beginning of the line; S P,ij is the active power-voltage sensitivity between the i-th node and the j-th node; S Q,ij is the reactive power-voltage sensitivity between the i-th grid connection point and the j-th grid connection point; R i and X i are the resistance and reactance values ​​of the i-th line respectively; The method for calculating the electrical distance is: The electrical distance is calculated using voltage sensitivity. The electrical distance between nodes i and j is calculated as: ； In the formula, S P,im is the active power-voltage sensitivity between the ith node and the mth node; S P,jm is the active power-voltage sensitivity between the jth node and the mth node; S Q,im is the reactive power-voltage sensitivity between the ith node and the mth node; S Q,jm is the reactive power-voltage sensitivity between the jth node and the mth node.

3. According to claim 2, a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning is characterized in that: The specific method for constructing the dynamic partition index in step 2 is: The intra-region coupling degree α and interval dispersion β of distributed photovoltaic nodes are calculated respectively, and the calculation formula is: ； ； Where N is the number of partitions; A is the node set of partition x; L ave,x is the average distance of partition x.

4. According to claim 2, a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning is characterized in that: The specific method of selecting the dominant node in step 3 is: Select the leading nodeδ based on the impact of the node on other nodes in the partition x , the selection basis satisfies the following calculation formula: ； In the formula, S P,jj is the active power-voltage sensitivity of the jth node to itself; S Q,jj is the reactive power-voltage sensitivity of the jth node to itself.

5. According to claim 3, a method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning is characterized in that: The specific method for dynamic partitioning in step 4 is: Step 4.1: Draw a network topology diagram based on the actual power distribution network; Step 4.2: Convert each node and branch of the network topology into genetic algorithm chromosome code: The length of the chromosome encoding vector is equal to the total number of branches in the distribution topology. 0 and 1 elements are used to represent the partition relationship between branches and nodes. 0 means that the nodes at both ends of the branch are not in the same partition, and 1 means that the nodes at both ends of the branch are in the same partition. Step 4.3: Input the number of individuals, maximum genetic generation, generation gap coefficient, crossover probability, mutation probability, and partition index weight coefficient required by the genetic algorithm; Step 4.4: Randomly encode chromosomes and generate the initial population: The partitioning scheme is obtained by decoding the chromosome, and the individual fitness is calculated by the partitioning evaluation index; Step 4.5: Perform selection, crossover, and mutation operations to obtain the offspring population, calculate the fitness of the offspring population, insert the offspring into the parent generation to obtain a new population, and output the partition result after reaching the maximum genetic generation number; Step 4.6: After obtaining the partition results, select the dominant node of each partition using the calculation formula in step 2.

6. A method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning according to claim 5, characterized in that: In step 5, after the voltage exceeds the limit, the voltage deviation value of each exceeding-limit node is counted, and the calculation formula is: ； Where U ref is the reference voltage, K is the set of nodes that exceed the limit, U k is the real-time voltage value of the voltage-exceeding-limit node; According to the partition results in step 4, calculate the reactive regulation power ΔQ of each distributed photovoltaic i (t), the calculation formula is: ； In the formula, w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes; η i (t) is the voltage regulation contribution of photovoltaic node i at time t; Q i,max is the maximum reactive output of distributed photovoltaic i; Calculate the weight coefficient of the photovoltaic nodes in the partition using the following formula: ； In the formula, S PV,i is the grid-connected capacity of the ith distributed photovoltaic; m is the number of distributed photovoltaic nodes in the partition.

7. The method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning according to claim 1, characterized in that: The consistency algorithm used in step 6 is specifically: Each node bears the voltage fluctuation according to its voltage regulation contribution, and finally reaches the following consistency: ； Where η dom (t) and η i (t) are the voltage regulation contributions of the dominant node and other nodes at time t; ΔU dom (t) and ΔU i (t) are the voltage deviations of the dominant node and other nodes at time t; ΔQ dom (t) and ΔQ i (t) are the reactive regulation powers of the dominant node and other nodes at time t; w dom and w i are the weight coefficients of the dominant node and other nodes respectively; Q dom,max and Q i,max are the maximum reactive power regulation margins of the dominant node and other nodes respectively.

8. The method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning according to claim 1, characterized in that: The specific method of responding to reactive power regulation in step 6 is: Step 6.1: Determine the adjacency matrix in each partition according to the network topology of the distribution network. The expression is: ； Where, d ij represents the communication weight between nodes i and j; the n×n matrix is ​​a square matrix with n elements in both rows and columns, where n is the number of nodes in the distribution network; Step 6.2: Calculate the communication weight d between nodes i and j ij , the calculation formula is: ； In the formula, if there is communication between nodes i and j, then s ij =1, otherwise s ij =0,N i is the number of nodes i; Step 6.3: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula: ； Where η i (k) represents the reactive voltage regulation contribution of PV node i, and k is the sampling time.

9. The method for coordinated control of distributed photovoltaic voltage in a distribution network based on dynamic partitioning according to claim 1, characterized in that: The specific steps of the active power regulation method adopted in step seven are: Step 7.1: Calculate the active regulation power of each distributed photovoltaic: ； In the formula, w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes; ρ i (t) is the voltage regulation contribution; ΔP i (t) Each distributed photovoltaic participating in voltage management should respond to the active power regulation amount; Step 7.2: According to the consistency protocol, the voltage regulation contribution of distributed photovoltaics in the partition is iteratively updated according to the following formula: ； In the formula, ρ i (k) represents the reactive voltage regulation contribution of PV node i, k is the sampling time; Step 7.3: The distributed photovoltaics in each partition respond to active regulation through the consistency algorithm results. Each node bears the voltage fluctuation according to the voltage regulation contribution, and finally reaches consistency. The consistency expression is: ； In the formula, ρ dom (t) and ρ i (t) are the voltage regulation contributions of the dominant node and other nodes respectively; ΔU dom (t) and ΔU i (t) are the voltage deviations of the dominant node and other nodes at time t, ΔP dom (t) and ΔP i (t) are the active regulation power of the leading node and other nodes at time t respectively; w dom is the weight coefficient of the dominant node, P dom,max and P i,max are the maximum active regulation margins of the dominant node and other nodes respectively.

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