Reactive power optimization method and system for power distribution network based on magnetic control transformer

Abstract

The application relates to the technical field of power distribution network dispatching, and discloses a power distribution network reactive power optimization method and system based on magnetic control transformers. The method constructs a power distribution network reactive power optimization model by taking the lowest input cost of the magnetic control transformer as a target condition and taking the compensation node and compensation capacity of the magnetic control transformer as decision variables, optimizes the power distribution network reactive power optimization model, determines the compensation node with the lowest input cost of the magnetic control transformer and the corresponding compensation capacity of the magnetic control transformer according to the optimal solution, replaces the original transformer on the corresponding compensation node of the magnetic control transformer with the magnetic control transformer with the determined compensation capacity, compensates and optimizes the voltage and reactive power in the power distribution network, and thus the voltage and reactive power in the power distribution network are compensated at the optimal compensation node with the lowest input cost, additional reactive power compensation devices are not needed, and the load and system loss of the system are reduced.

Description

Technical Field

[0001] This invention relates to the field of power distribution network dispatching technology, and in particular to a method and system for reactive power optimization in power distribution networks based on magnetically controlled transformers. Background Technology

[0002] With the increasing use of power electronic devices in power distribution networks and the grid connection of new energy sources, primarily photovoltaic and wind power, the power quality of the power system has been severely impacted, causing problems such as voltage and reactive power fluctuations. The high proportion of cables in urban distribution networks also leads to significant reactive power deficits and low voltage issues; simultaneously, the integration of photovoltaic systems at the end of lines can cause voltage exceeding limits. When these problems are severe, the distribution network may experience both high and low voltage exceeding limits, leading to numerous issues such as power supply reliability and customer complaints. Voltage stability is a crucial indicator of power quality. Voltage fluctuations can cause electrical equipment to malfunction, resulting in abnormal equipment operation, equipment failures, and even electrical accidents.

[0003] A magnetically controlled transformer is a new type of transformer that combines a magnetically controlled reactor and a power transformer into one unit, possessing both arc-free, stepless, continuous voltage regulation and capacitive reactive power compensation functions. Currently, in traditional power systems, power transformers and magnetically controlled reactors often operate separately, which not only occupies a large area but also has high manufacturing costs and high no-load and load losses.

[0004] Chinese invention patent CN116362141A discloses a method and apparatus for reactive power optimization in distribution networks based on quantum genetic algorithms, which uses inverters to compensate for active and reactive power in the system. Chinese invention patent CN116362061A discloses a method and apparatus for reactive power optimization in distribution networks, which adopts different reactive power optimization methods according to the type of distribution network and uses parallel capacitor banks and static var generators to compensate for system reactive power.

[0005] The aforementioned patents all use separate reactive power compensation devices, which optimize the reactive power of the power distribution network, but also increase the load on the system and significantly increase system losses. Summary of the Invention

[0006] This invention provides a method and system for reactive power optimization in power distribution networks based on magnetically controlled transformers, which solves the technical problem that the use of separate reactive power compensation devices in the prior art increases the load on the system and significantly increases system losses.

[0007] In view of this, the first aspect of the present invention provides a reactive power optimization method for a distribution network based on a magnetically controlled transformer, wherein the distribution network includes multiple distribution transformer nodes located on a transmission bus, each distribution transformer node being connected to a user-side load via a transformer, and the transmission bus being connected to a power station. The method includes the following steps:

[0008] With the goal of minimizing the investment cost of the magnetically controlled transformer, and with the compensation node and compensation capacity of the magnetically controlled transformer as decision variables, a reactive power optimization model for the distribution network is constructed. The compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer.

[0009] The reactive power optimization model of the power distribution network is optimized and solved. Based on the optimal solution, the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined.

[0010] The magnetically controlled transformer replaces the original transformer at the corresponding compensation node according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the compensation of voltage and reactive power in the distribution network.

[0011] Preferably, the reactive power optimization model for the distribution network includes an objective function and constraints; wherein the objective function is:

[0012]

[0013] In the formula, G(S) i Q i ) is about the compensation node N i Apparent power S of the installed magnetically controlled transformer i and reactive power Q i The input cost is α, which is the cost coefficient of the magnetically controlled transformer and apparent power, β, which is the cost coefficient of the magnetically controlled transformer and reactive power, and n is the number of distribution transformer nodes.

[0014] The constraints include:

[0015] U imin ≤U i ≤U imax ,

[0016] 0≤S i ≤S imax ,0≤Q i ≤Q imax

[0017] In the formula, U i To compensate node N i Voltage at point, cosφ i To compensate node N i The power factor at point U imin U imax The compensation nodes are N respectively. i Minimum voltage limit and maximum voltage limit at the location. The compensation nodes are N respectively. iMinimum power factor limit, maximum power factor limit, S imax Q represents the maximum apparent power limit of a magnetically controlled transformer. imax This represents the maximum reactive power limit of a magnetically controlled transformer, where...

[0018] f i (N i ,S i Q i )=(U i ,cosφ i ) i＝1,…,n

[0019] In the formula, f i (N i ,S i Q i ) is the compensation node N i Apparent power S of the installed magnetically controlled transformer i and reactive power Q i With compensation node N i Voltage U at the point i and power factor cosφ i The corresponding functional relationship.

[0020] Preferably, the step of finding the optimal solution for the reactive power optimization model of the distribution network and determining the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution specifically includes:

[0021] The reactive power optimization model of the power distribution network is optimized using a genetic algorithm. Based on the optimal solution, the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined.

[0022] Preferably, the step of optimizing the reactive power optimization model of the distribution network based on a genetic algorithm, and determining the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution, specifically includes:

[0023] Initialize the population parameters, and encode the compensation nodes and their corresponding magnetically controlled transformers using real number encoding.

[0024] The fitness value of an individual is calculated using the objective function of the reactive power optimization model of the power distribution network as the fitness function.

[0025] The initial population is selected using a roulette wheel selection method to generate the first generation population, where individual G... k The probability of being selected is:

[0026]

[0027] In the formula, P n Let f be the probability. k For individual G k fitness value, f m Individual G m The fitness value, where M is the number of individuals in the initial population;

[0028] The first generation population is subjected to hybridization and mutation operations to generate the next generation population;

[0029] Using the next generation population as the current population, the current population is reselected using a roulette wheel method to generate the next generation population, and this process is repeated iteratively.

[0030] Determine if the number of iterations has reached the preset maximum number of iterations. If the number of iterations has not reached the preset maximum number of iterations, proceed to the step of selecting two parent populations using the roulette wheel method on the initial population. If the number of iterations has reached the preset maximum number of iterations, the iteration stops and the corresponding population is output.

[0031] The individual with the highest fitness value is selected as the optimal solution from the output population.

[0032] The compensation node with the lowest investment cost for the magnetically controlled transformer and its corresponding compensation capacity are determined based on the optimal solution.

[0033] Secondly, the present invention also provides a reactive power optimization system for a distribution network based on a magnetically controlled transformer, wherein the distribution network includes multiple distribution transformer nodes located on a transmission bus, each distribution transformer node being connected to a user-side load via a transformer, and the transmission bus being connected to a power station. The system includes:

[0034] The optimization model construction module is used to construct a reactive power optimization model for the distribution network with the objective condition of minimizing the investment cost of the magnetically controlled transformer and the compensation node and compensation capacity of the magnetically controlled transformer as decision variables. The compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer.

[0035] The optimization solution module is used to optimize the reactive power optimization model of the power distribution network and determine the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution.

[0036] The reactive power compensation optimization module is used to replace the original transformer at the corresponding compensation node with the magnetically controlled transformer according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the voltage and reactive power compensation in the distribution network.

[0037] Thirdly, the present invention also provides an electronic device, the electronic device including a memory and a processor;

[0038] The memory is used to store programs;

[0039] The processor executes the program to implement the above-described method.

[0040] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0041] As can be seen from the above technical solutions, the present invention has the following advantages:

[0042] This invention constructs a reactive power optimization model for a distribution network, using the lowest possible investment cost of the magnetically controlled transformer as the objective condition and the compensation node and compensation capacity of the magnetically controlled transformer as decision variables. The model is then optimized, and the optimal solution determines the compensation node with the lowest investment cost and its corresponding compensation capacity. The original transformer at the corresponding compensation node is replaced with the magnetically controlled transformer according to the determined compensation capacity. This optimizes voltage and reactive power compensation in the distribution network, achieving voltage and reactive power compensation at the optimal compensation node with the lowest investment cost. This eliminates the need for additional reactive power compensation devices; only one magnetically controlled transformer is required to replace the traditional transformer, reducing system load and losses. Attached Figure Description

[0043] Figure 1 This is a structural diagram of an application scenario of a power distribution network provided in an embodiment of the present invention;

[0044] Figure 2 A flowchart illustrating a reactive power optimization method for a distribution network based on a magnetically controlled transformer, provided as an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of a power distribution network reactive power optimization system based on a magnetically controlled transformer, provided as an embodiment of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] like Figure 1 As shown, Figure 1 The diagram illustrates the structure of a power distribution network application scenario. In order to address the reactive power hazards to the power grid caused by a large number of power electronic devices and the voltage fluctuations in the power distribution network caused by the grid connection of new energy sources, this invention provides a reactive power optimization method for power distribution networks based on magnetically controlled transformers. The power distribution network includes multiple distribution transformer nodes located on the transmission bus. Each distribution transformer node is connected to the user-side load through a transformer, and the transmission bus is connected to the power station.

[0048] The photovoltaic power station is connected to the distribution network via a 10kV transmission bus, N1~N n This indicates the power consumption area connected to the transmission line. Each power consumption area uses a power transformer to convert the 10kV line voltage to the voltage level required by the area. N1~N n The capacity of the transformer to be installed is known. To balance the reactive power generated by the grid connection of the photovoltaic power station, it is planned to initially install one magnetically controlled transformer to N1~N2. n A distribution transformer node is used to replace the traditional transformer. The magnetically controlled transformer has both voltage transformation and reactive power compensation functions.

[0049] For easier understanding, please refer to Figure 2 The present invention provides a reactive power optimization method for distribution networks based on magnetically controlled transformers, comprising the following steps:

[0050] Step 1: With the goal of minimizing the investment cost of the magnetically controlled transformer, and with the compensation node and compensation capacity of the magnetically controlled transformer as decision variables, construct a reactive power optimization model for the distribution network. Here, the compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer.

[0051] Since the magnetically controlled transformer has both voltage transformation and reactive power compensation functions, the compensation capacity includes two components: apparent power and reactive power.

[0052] The cost of investing in the magnetically controlled transformer is calculated based on the cost coefficients corresponding to the apparent power and reactive power of the magnetically controlled transformer. This cost is then added to the costs of transformers at other nodes to obtain the total cost. Since the transformer capacities at other nodes are known, the objective condition is simply to minimize the investment cost of the magnetically controlled transformer. The distribution transformer node with the lowest investment cost and its corresponding magnetically controlled transformer compensation capacity are selected from the magnetically controlled transformers at each distribution transformer node. The transformer at that node is then replaced with a magnetically controlled transformer, thereby compensating for the voltage and reactive power of the distribution network.

[0053] It should be noted that node N, which ensures the voltage and power factor of each distribution transformer node meet safety standards, is calculated based on the system data of the distribution network. iA magnetically controlled transformer can be installed at a point. That is, after the magnetically controlled transformer is installed, the voltage and power factor of each node in the distribution network must meet the safety standards (generally, the voltage fluctuation on the low-voltage side of 10kV power supply users is less than 7%, and the power factor is not less than 0.95). At the same time, the installation capacity of the magnetically controlled transformer at the compensation node must not exceed the maximum allowable access capacity of the node.

[0054] Based on this, the reactive power optimization model for the distribution network includes an objective function and constraints; the objective function is:

[0055]

[0056] In the formula, G(S) i Q i ) is about the compensation node N i Apparent power S of the installed magnetically controlled transformer i and reactive power Q i The input cost is α, which is the cost coefficient of the magnetically controlled transformer and apparent power, β, which is the cost coefficient of the magnetically controlled transformer and reactive power, and n is the number of distribution transformer nodes.

[0057] The constraints include:

[0058] U imin ≤U i ≤U imax ,

[0059] 0≤S i ≤S imax ,0≤Q i ≤Q imax

[0060] In the formula, U i To compensate node N i Voltage at point, cosφ i To compensate node N i The power factor at point U imin U imax The compensation nodes are N respectively. i Minimum voltage limit and maximum voltage limit at the location. The compensation nodes are N respectively. i Minimum power factor limit, maximum power factor limit, S imax Q represents the maximum apparent power limit of a magnetically controlled transformer. imax This represents the maximum reactive power limit of a magnetically controlled transformer, where...

[0061] f i (N i ,S i Q i )=(U i,cosφ i ) i＝1,…,n

[0062] In the formula, f i (N i ,S i Q i ) is the compensation node N i Apparent power S of the installed magnetically controlled transformer i and reactive power Q i With compensation node N i Voltage U at the point i and power factor cosφ i The corresponding functional relationship.

[0063] Step 2: Solve the reactive power optimization model of the distribution network, and determine the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution.

[0064] It should be noted that the reactive power optimization problem of this distribution network is a single-objective optimization problem. In this embodiment, the reactive power optimization model of the distribution network is optimized based on the genetic algorithm. The compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined based on the optimal solution.

[0065] Specifically, the steps of using a genetic algorithm to find the optimal solution for the reactive power optimization model of the distribution network, and determining the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution, include:

[0066] 201. Initialize the population parameters and encode the compensation nodes and their corresponding magnetically controlled transformers using real number encoding.

[0067] The population can be set to have 10 individuals. The initial population can be represented as G1 = (111…0000), G2 = (001…1010), G3 = 7(111…0100), G4 = 7(101…1011), G5 = 7(010…1100), G6 = 5(011…1100), G7 = 3(1110…011), G8 = 4(001…1110), G9 = 6(000…1101), G10 = 6(110…1001). The encoding method involves first sorting all nodes from 1 to n, corresponding to the nth position on the chromosome. If a node is directly connected to another node, its position on the chromosome corresponding to that node is set to 1; otherwise, it is set to 0. Each node's position on its own chromosome is also set to 1. For example, chromosome S1 = (111…0000) represents the node directly connected to nodes 1, 2, and 3.

[0068] 202. Using the objective function of the reactive power optimization model of the distribution network as the fitness function, calculate the fitness value of an individual.

[0069] The lower the cost, the higher the fitness value.

[0070] 203. The initial population is selected using a roulette wheel selection method to generate the first generation population, where individual G... k The probability of being selected is:

[0071]

[0072] In the formula, P n Let f be the probability. k For individual G k fitness value, f m Individual G m The fitness value, where M is the number of individuals in the initial population;

[0073] After obtaining the probability of individual selection, a uniformly random number between [0,1] is generated to determine which individual participates in mating. If an individual has a high selection probability, it has a chance to be selected multiple times, and its genetic material will expand in the population; if an individual has a low selection probability, it is more likely to be eliminated.

[0074] 204. Perform hybridization and mutation operations on the first-generation population to generate the next generation population;

[0075] Hybridization involves performing hybridization operations on the first-generation population. The hybridization operation is performed as follows: if two parent chromosomes have the same part (both of the same position are 1 or 0), then other chromosomes containing this same part are added to the population; otherwise, no operation is performed.

[0076] The mutation operation sets the inheritance probability to 0.05. At this probability, certain coding positions on the offspring chromosome mutate, resulting in a different chromosome with a high degree of similarity to it.

[0077] 205. Using the next generation population as the current population, the current population is reselected using the roulette wheel method to generate the next generation population, and this process is repeated iteratively.

[0078] 206. Determine whether the number of iterations has reached the preset maximum number of iterations. If the number of iterations has not reached the preset maximum number of iterations, proceed to the step of selecting two parent populations using the roulette wheel method on the initial population. If the number of iterations has reached the preset maximum number of iterations, the iteration stops and the corresponding population is output.

[0079] 207. Select the individual with the highest fitness value from the output population as the optimal solution;

[0080] 208. Based on the optimal solution, determine the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity.

[0081] Step 3: Replace the original transformer at the corresponding compensation node with the magnetically controlled transformer according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the voltage and reactive power compensation in the distribution network.

[0082] It should be noted that this invention constructs a reactive power optimization model for the distribution network by taking the lowest possible investment cost of the magnetically controlled transformer as the objective condition and using the compensation node and compensation capacity of the magnetically controlled transformer as decision variables. The model is then optimized and solved. Based on the optimal solution, the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined. The original transformer at the corresponding compensation node is replaced with the magnetically controlled transformer according to the determined compensation capacity. This optimizes voltage and reactive power compensation in the distribution network, achieving voltage and reactive power compensation at the optimal compensation node with the lowest investment cost. Therefore, no additional reactive power compensation device is required; only one magnetically controlled transformer is needed to replace the traditional transformer, reducing the system load and system losses.

[0083] The above is a detailed description of an embodiment of a reactive power optimization method for a distribution network based on a magnetically controlled transformer provided by the present invention. The following is a detailed description of an embodiment of a reactive power optimization system for a distribution network based on a magnetically controlled transformer provided by the present invention.

[0084] This invention also provides a reactive power optimization system for a distribution network based on a magnetically controlled transformer. The distribution network includes multiple distribution transformer nodes located on the transmission busbar. Each distribution transformer node is connected to the user-side load via a transformer. The transmission busbar is connected to the power station. For easier understanding, please refer to [link to relevant documentation]. Figure 3 This system includes:

[0085] The optimization model construction module 100 is used to construct a reactive power optimization model for the distribution network with the objective condition of minimizing the investment cost of the magnetically controlled transformer and the compensation node and compensation capacity of the magnetically controlled transformer as decision variables. The compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer.

[0086] The optimization solution module 200 is used to optimize the reactive power optimization model of the distribution network and determine the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution.

[0087] The reactive power compensation optimization module 300 is used to replace the original transformer at the corresponding compensation node with the magnetically controlled transformer according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the voltage and reactive power compensation in the distribution network.

[0088] The present invention also provides an electronic device, which includes a memory and a processor;

[0089] Memory is used to store programs;

[0090] The processor executes the program to implement the above method.

[0091] The present invention also provides a computer-readable storage medium storing a computer program, characterized in that the computer program implements the above-described method when executed by a processor.

[0092] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, electronic devices, and computer-readable storage media described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0093] In the embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer-readable storage media, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] If the integrated unit is implemented as 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 this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0097] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A reactive power optimization method for distribution networks based on magnetically controlled transformers, wherein, The distribution network includes multiple distribution transformer nodes located on the transmission busbar, each distribution transformer node being connected to the user-side load via a transformer. The transmission busbar is connected to the power station. The method is characterized by the following steps: With the goal of minimizing the investment cost of the magnetically controlled transformer, and with the compensation node and compensation capacity of the magnetically controlled transformer as decision variables, a reactive power optimization model for the distribution network is constructed. The compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer. The reactive power optimization model for the distribution network includes an objective function and constraints; wherein, the objective function is: In the formula, Regarding compensation nodes Apparent power of the installed magnetically controlled transformer and reactive power The input cost The cost factor for magnetically controlled transformers and apparent power. This refers to the cost coefficient of the magnetically controlled transformer and reactive power. This refers to the number of distribution transformer nodes; The constraints include: In the formula, For compensation nodes Voltage at that point For compensation nodes The power factor at that point, , Compensation nodes Minimum voltage limit and maximum voltage limit at the location. , Compensation nodes Minimum power factor limit and maximum power factor limit at the location, This represents the maximum apparent power limit of a magnetically controlled transformer. This represents the maximum reactive power limit of a magnetically controlled transformer, where... In the formula, For compensation nodes Apparent power of the installed magnetically controlled transformer and reactive power With compensation node voltage at and power factor The corresponding functional relationship; The reactive power optimization model of the distribution network is optimized and solved. Based on the optimal solution, the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined, including: The reactive power optimization model of the power distribution network is optimized and solved based on the genetic algorithm. The compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity are determined according to the optimal solution. This includes: initializing the population parameters and encoding the compensation node and its corresponding compensation capacity of the magnetically controlled transformer using real number encoding. The fitness value of an individual is calculated using the objective function of the reactive power optimization model of the power distribution network as the fitness function. The initial population is selected using a roulette wheel selection method to generate the first generation population, where the probability of individual Gk being selected is: In the formula, For probability, The fitness value of individual Gk. Gm represents the fitness value of an individual, and M is the number of individuals in the initial population. The first generation population is subjected to hybridization and mutation operations to generate the next generation population; Using the next generation population as the current population, the current population is reselected using a roulette wheel method to generate the next generation population, and this process is repeated iteratively. Determine if the number of iterations has reached the preset maximum number of iterations. If the number of iterations has not reached the preset maximum number of iterations, proceed to the step of selecting and generating a new generation of population using the roulette wheel method with the current population as the object. If the number of iterations has reached the preset maximum number of iterations, the iteration stops and the corresponding population is output. The individual with the highest fitness value is selected as the optimal solution from the output population. The compensation node with the lowest investment cost for the magnetically controlled transformer and its corresponding compensation capacity are determined based on the optimal solution. The magnetically controlled transformer replaces the original transformer at the corresponding compensation node according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the compensation of voltage and reactive power in the distribution network.

2. A power distribution network reactive power optimization system based on a magnetically controlled transformer, applied to the power distribution network reactive power optimization method based on a magnetically controlled transformer as described in claim 1, wherein, The distribution network includes multiple distribution transformer nodes located on the transmission busbar, each distribution transformer node being connected to the user-side load via a transformer. The transmission busbar is connected to the power station. The system is characterized by comprising: The optimization model construction module is used to construct a reactive power optimization model for the distribution network with the objective condition of minimizing the investment cost of the magnetically controlled transformer and the compensation node and compensation capacity of the magnetically controlled transformer as decision variables. The compensation node is the distribution node corresponding to the transformer on a certain distribution node that is replaced by the magnetically controlled transformer. The optimization solution module is used to optimize the reactive power optimization model of the power distribution network and determine the compensation node with the lowest investment cost of the magnetically controlled transformer and its corresponding compensation capacity based on the optimal solution. The reactive power compensation optimization module is used to replace the original transformer at the corresponding compensation node with the magnetically controlled transformer according to the determined compensation capacity of the magnetically controlled transformer, thereby optimizing the voltage and reactive power compensation in the distribution network.

3. An electronic device, characterized in that, The electronic device includes a memory and a processor; The memory is used to store programs; The processor executes the program to implement the method of claim 1.

4. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of claim 1.

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