A power distribution zone topology optimization method, system, device and medium

Abstract

The application belongs to the technical field of power systems, and discloses a power distribution area topology optimization method, which comprises the following steps: adopting a real number coding mode based on a sequential loop matrix to code and process basic loop circuits in a power distribution area, so as to obtain a power distribution area topology optimization model; solving the power distribution area topology optimization model according to an improved imperialist competitive algorithm, so as to obtain an optimal power distribution area topology optimization model; and optimizing each operating parameter in the power distribution area by using the optimal power distribution area topology optimization model. The application adopts the coding mode based on the sequential loop matrix to construct the power distribution area topology optimization model, and adopts the improved imperialist competitive algorithm to optimally solve the power distribution area topology optimization model, so as to obtain the optimal power distribution area topology optimization model for optimizing the power distribution area, thereby effectively improving the topology optimization speed, maximizing the safe operation margin of the power distribution area, and ensuring the safe and stable operation of the power distribution area.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, system, equipment and medium for optimizing the topology of a distribution substation. Background Technology

[0002] In 2021, the National Energy Administration officially issued the "Notice on Announcing the List of Pilot Projects for Rooftop Distributed Photovoltaic Development in Entire Counties (Cities, Districts)," vigorously promoting the development of distributed photovoltaics through policy incentives. The installed capacity and grid connection ratio of distributed photovoltaics in low-voltage distribution networks (distribution substations) will continue to increase. As a clean energy source, photovoltaics, with its high-proportion grid connection, will bring significant power generation benefits. However, due to its inherent uncertainties, it may lead to a series of problems that threaten the safe and stable operation of the network, such as voltage exceeding limits, line overload, and reduced power quality. Therefore, to avoid these problems and maximize the safety margin of distribution substations, it is urgent to establish safety operation assessment indicators for distribution substations and, based on this, develop an effective method for optimizing the topology of distribution substations.

[0003] Currently, research on topology optimization for 10kV distribution networks is relatively abundant and mature. Objective functions mostly focus on network losses, voltage deviation, and load balance, often employing single-objective or multi-objective optimization based on actual needs. Research specifically on topology optimization for distribution substations at this voltage level is scarce, and there is a lack of established evaluation indicators that can further reflect the safe operation status of distribution substations. The effectiveness of topology optimization is closely related to the encoding method. Binary encoding generates a large number of infeasible solutions, reducing solution efficiency and affecting optimization results. While decimal genetic encoding rules and their corresponding genetic operation strategies can eliminate infeasible solutions during genetic operations, this encoding method requires subsequent auxiliary operations to eliminate infeasible solutions, and the genetic algorithm has a long solution time. Therefore, there is room for further improvement in both encoding methods and solution algorithms.

[0004] To address the aforementioned shortcomings, this invention first establishes an evaluation index for the safety margin of distribution transformer substations and a topology optimization model. Then, it employs an imperialist competition algorithm based on sequential ring matrix encoding and Cauchy mutation improvement to solve for the topology optimization results of the distribution transformer substations, thereby enhancing the safety margin of the substations and ensuring their safe and stable operation. Summary of the Invention

[0005] This invention provides a method, system, device, and medium for optimizing the topology of a distribution transformer substation, thereby improving the safety margin of the substation and ensuring its safe and stable operation.

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or to describe the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0007] According to a first aspect of the present invention, a method for optimizing the topology of a distribution radio station area is provided.

[0008] In one embodiment, the distribution area topology optimization method includes:

[0009] A topology optimization model for the distribution transformer area is obtained by encoding the basic loop circuits in the distribution transformer area using a sequential ring matrix real number encoding method.

[0010] Based on the improved imperialist competition algorithm, the topology optimization model of the distribution area is solved to obtain the optimal distribution area topology optimization model;

[0011] The optimal distribution area topology optimization model is used to optimize the operating parameters of each distribution area.

[0012] In one embodiment, the operating parameters include at least one of the following: distribution area topology connection information parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

[0013] In one embodiment, the basic loop circuits in the distribution network are encoded using a sequential ring matrix real number encoding method to obtain a distribution substation topology optimization model. This includes: reordering the basic loop circuits in the distribution substation according to the connection order of each row of branches in the distribution substation topology to obtain a sequential basic ring matrix, and using the sequential basic ring matrix as the model decision variable; determining the voltage safety margin and current safety margin according to the distribution substation safety operation margin assessment index, and establishing a model fitness function based on the voltage safety margin and current safety margin; and constructing a distribution substation topology optimization model based on the model decision variables, the model fitness function, and the constraints of the distribution substation.

[0014] In one embodiment, the basic loop circuits in the distribution network are encoded using a real number encoding method based on the sequential ring matrix to obtain the distribution substation topology optimization model. This further includes: before using the sequential basic ring matrix as the model decision variable, removing duplicate branches in each matrix row of the sequential basic ring matrix, so that each branch in the sequential basic ring matrix corresponds to only one matrix row, and the segmented switches of the sequential basic ring matrix are located in the matrix row with the smallest power distance.

[0015] In one embodiment, based on the voltage safety margin and current safety margin, the formula for calculating the model fitness function is as follows:

[0016]

[0017]

[0018]

[0019] In the formula, These represent the number of nodes and branches in the distribution area, respectively. For nodes The actual operating voltage, , branch road The actual operating current, The maximum allowable current to ensure safety. As weight, , For voltage safety margin; For current safety margin, This is the model fitness function.

[0020] In one embodiment, the constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints.

[0021] In one embodiment, solving the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model includes: initializing the countries by taking the number of disconnected switches in the distribution area topology optimization model as the national solution dimension and the positions of the disconnected switches in the distribution area topology optimization model as national positions; calculating the fitness function of each initialized country according to the model fitness function of the distribution area topology optimization model; sorting the fitness functions of each initialized country and dividing each initialized country into imperialist countries and colonial countries according to the sorting results, and assigning colonial countries to the imperialist countries in batches according to their power size to form initial imperial groups; performing assimilation and revolution operations on each empire within each initial imperial group and calculating the power size of the imperial group after assimilation and revolution operations; conducting competition between imperial groups according to the power size of each imperial group and dividing the weakest empire; determining whether the iteration termination condition has been met, and if the determination result is that the iteration termination condition has been met, taking the iterated imperial group as the optimal distribution area topology optimization model.

[0022] According to a second aspect of the present invention, a distribution area topology optimization system is provided.

[0023] In one embodiment, the distribution area topology optimization system includes:

[0024] The optimization model construction module is used to encode the basic loop circuits in the distribution transformer area using a sequential ring matrix real number encoding method to obtain the distribution transformer area topology optimization model.

[0025] The optimization model solving module is used to solve the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model;

[0026] The model optimization processing module is used to optimize the operating parameters of the distribution radio station using the optimal distribution radio station topology optimization model.

[0027] In one embodiment, the operating parameters include at least one of the following: distribution area topology connection information parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

[0028] In one embodiment, the optimization model construction module includes: a variable determination submodule, a function determination submodule, and a model construction submodule. The variable determination submodule is used to reorder the basic loops in the distribution substation according to the connection order of each row of branches in the distribution substation topology, obtaining an ordered basic loop matrix, and using the ordered basic loop matrix as the model decision variable. The function determination submodule is used to determine the voltage safety margin and current safety margin based on the distribution substation safety margin assessment index, and establish a model fitness function based on the voltage safety margin and current safety margin. The model construction submodule is used to construct a distribution substation topology optimization model based on the model decision variables, the model fitness function, and the constraints of the distribution substation.

[0029] In one embodiment, the variable determination submodule is further configured to remove duplicate branches in each matrix row of the sequential basic ring matrix before using the sequential basic ring matrix as a model decision variable, so that each branch in the sequential basic ring matrix corresponds to only one matrix row, and the segmented switches of the sequential basic ring matrix are located in the matrix row with the smallest power distance.

[0030] In one embodiment, the function determining submodule establishes the calculation formula for the model fitness function based on the voltage safety margin and current safety margin as follows:

[0031]

[0032]

[0033]

[0034] In the formula, These represent the number of nodes and branches in the distribution area, respectively. For nodes The actual operating voltage, , branch road The actual operating current, The maximum allowable current to ensure safety. As weight, , For voltage safety margin; For current safety margin, This is the model fitness function.

[0035] In one embodiment, the constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints.

[0036] In one embodiment, the optimization model solving module includes: a nation initialization submodule, a function calculation submodule, an imperial group initialization submodule, an imperial power calculation submodule, an imperial competition submodule, and an iteration judgment submodule. The nation initialization submodule is used to initialize nations by taking the number of disconnected switches in the distribution area topology optimization model as the nation solution dimension and the position of the disconnected switches as the nation position. The function calculation submodule is used to calculate the fitness function of each initialized nation based on the model fitness function of the distribution area topology optimization model. The imperial group initialization submodule is used to sort the fitness functions of each initialized nation and determine the order based on the sorting. As a result, each initial state is divided into imperialist states and colonial states, and each imperialist state is assigned a corresponding number of colonial states based on its power, forming initial imperial groups. The imperial power calculation submodule is used to perform assimilation and revolution operations on each empire within each initial imperial group, and to calculate the power of the imperial group after assimilation and revolution. The imperial competition submodule is used to conduct competition between imperial groups based on their power, and to divide the weakest empire. The iterative judgment submodule is used to determine whether the iteration termination condition has been met. If the judgment result is that the iteration termination condition has been met, the iterated imperial group is used as the optimal distribution area topology optimization model.

[0037] According to a third aspect of the present invention, a computer device is provided.

[0038] In some embodiments, the computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0039] According to a fourth aspect of the present invention, a computer-readable storage medium is provided.

[0040] In one embodiment, a computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the steps of the above method.

[0041] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0042] This invention constructs a distribution radio station topology optimization model by employing a sequential ring matrix-based encoding method, and uses an improved imperialist competition algorithm to find the optimal solution for the distribution radio station topology optimization model. This results in the optimal distribution radio station topology optimization model being used to optimize the distribution radio station, thereby effectively avoiding the occurrence of infeasible solutions, improving the topology optimization speed, maximizing the safety margin of the distribution radio station, and ensuring the safe and stable operation of the distribution radio station.

[0043] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0044] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0045] Figure 1 This is a flowchart illustrating a distribution area topology optimization method according to an exemplary embodiment;

[0046] Figure 2 This is a schematic diagram illustrating the structure of a distribution area topology optimization system according to an exemplary embodiment;

[0047] Figure 3 This is a schematic diagram of the structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0048] The following description and accompanying drawings fully illustrate specific embodiments described herein to enable those skilled in the art to practice them. Some embodiments may include or substitute parts and features of other embodiments. The scope of the embodiments herein encompasses the entire scope of the claims and all available equivalents thereof. Throughout this document, the terms “first,” “second,” etc., are used only to distinguish one element from another without requiring or implying any actual relationship or order between the elements. Indeed, a first element can also be referred to as a second element, and vice versa. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a structure, apparatus, or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the structure, apparatus, or device that includes said element. The various embodiments described herein are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments; similar or identical parts between embodiments can be referred to interchangeably.

[0049] The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" used in this document to indicate orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings. They are used solely for the convenience of describing the document and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In the description herein, unless otherwise specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two elements; they can be direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0050] In this document, unless otherwise stated, the term "multiple" means two or more.

[0051] In this article, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0052] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0053] It should be understood that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order constraint on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the diagram may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0054] The modules in the apparatus or system of this application can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0055] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0056] Figure 1 An embodiment of the distribution radio area topology optimization method of the present invention is shown.

[0057] In this optional embodiment, the distribution area topology optimization method includes:

[0058] Step S101: Using the sequential ring matrix real number encoding method, the basic loop circuits in the distribution transformer area are encoded to obtain the distribution transformer area topology optimization model.

[0059] Step S103: Solve the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model;

[0060] Step S105: Optimize the operating parameters of each distribution station area using the optimal distribution station area topology optimization model.

[0061] In one embodiment, the operating parameters include at least one of the following: distribution area topology connection information parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

[0062] In one embodiment, when encoding the basic loop circuits in the distribution network using a sequential ring matrix real-number encoding method to obtain the distribution substation topology optimization model, the basic loop circuits in the distribution substation can be reordered according to the connection order of each row of branches in the distribution substation topology to obtain a sequential basic ring matrix. Duplicate branches in each row of the sequential basic ring matrix are removed, ensuring that each branch corresponds to only one row, and that the segmented switches in the sequential basic ring matrix are located in the row with the smallest power distance. The resulting sequential basic ring matrix is ​​used as the model decision variable. Voltage safety margin and current safety margin are determined based on the distribution substation safety margin assessment index. A model fitness function is established based on the voltage safety margin and current safety margin. A distribution substation topology optimization model is constructed based on the model decision variables, the model fitness function, and the constraints of the distribution substation.

[0063] Specifically, in a radial distribution network, a loop consisting of a tie switch and several sectionalizing switches is called a basic loop. The basic loop matrix is ​​defined as follows: ,in The number of basic rings. The maximum number of sectionalizing switches in all basic rings, where the number of sectionalizing switches is less than... Lines with zeros are padded with zeros. Non-zero elements. Indicates the first The first basic ring The branch number where the sectionalizing switch is located.

[0064] By reordering each row of the fundamental ring matrix according to the branch connection order in the topology, it becomes an ordered fundamental ring matrix. However, the order of the basic ring matrix There may be duplicate branches in each row. If the broken branches of different loops are the same branch, a loop will still be formed, which does not satisfy the radial constraint of the distribution area. The solution formed by the corresponding decision variables is an infeasible solution. To avoid the occurrence of infeasible solutions and improve the reconstruction speed, it is necessary to optimize the sequential basic loop matrix. Remove duplicate branches from each row so that each branch exists in at most one row.

[0065] Specific removal rules: For those appearing in the sequential fundamental ring matrix A segmented switch in multiple rows In the order of fundamental ring matrices The position in the middle is ,in Let its repetition count be represented by the last node of its branch. Calculate the situation when this sectionalizing switch is open and the corresponding tie switches for each row are closed. power torque Let the minimum power torque be... Then let

[0066]

[0067] That is, in the sequential fundamental ring matrix The switch is only in the middle Retain the row with the lowest power torque, and switch the switches on the remaining rows. The value is assigned to 0.

[0068] Power torque The specific calculation method is as follows:

[0069]

[0070]

[0071] in, This is the reverse path formed by the set of branches and nodes traversed from a node to the power inflow point of its loop. Let be the generalized load of node t. Reverse path The sum of the impedances of all branches, It is the conjugate of the node load.

[0072] After removing duplicate branches, add the tie switch to the sequential basic ring matrix. The corresponding positions in the corresponding rows become the final sequential ring matrix. .

[0073] When establishing the model fitness function, based on the voltage safety margin and current safety margin, the calculation formula for the model fitness function is as follows:

[0074]

[0075]

[0076]

[0077] In the formula, These represent the number of nodes and branches in the distribution area, respectively. For nodes The actual operating voltage, , branch road The actual operating current, The maximum allowable current to ensure safety. As weight, , For voltage safety margin; For current safety margin, This is the model fitness function.

[0078] In one embodiment, the constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints. Specifically:

[0079] For the power balance constraint, the calculation formula is:

[0080]

[0081] In the formula, They are nodes The injected active and reactive power; , They are nodes , The voltage amplitude; , These are the real and imaginary parts of the system admittance matrix, respectively. For nodes , The voltage phase angle difference, where N is the number of nodes.

[0082] As for the voltage operation constraints, the calculation formula is:

[0083]

[0084] In the formula, This is the maximum allowable voltage. node The voltage amplitude; This is the minimum allowable voltage.

[0085] As for the current operation constraint, the calculation formula is:

[0086]

[0087] In the formula, branch road The actual operating current, The maximum allowable current to ensure safety.

[0088] The calculation formula for the output constraints of distributed photovoltaic power is as follows:

[0089]

[0090] In the formula, For nodes The actual output of the distributed photovoltaic system For nodes The maximum output of the connected distributed photovoltaic system.

[0091] Regarding the connectivity constraints of the distribution area topology, the network topology before and after the switching action must satisfy the radial constraint. Regarding the constraint on the number of switching actions, the number of switching actions should be less than the maximum number of actions set.

[0092] In one embodiment, solving the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model includes: initializing the countries by taking the number of disconnected switches in the distribution area topology optimization model as the national solution dimension and the positions of the disconnected switches in the distribution area topology optimization model as national positions; calculating the fitness function of each initialized country according to the model fitness function of the distribution area topology optimization model; sorting the fitness functions of each initialized country and dividing each initialized country into imperialist countries and colonial countries according to the sorting results, and assigning colonial countries to the imperialist countries in batches according to their power size to form initial imperial groups; performing assimilation and revolution operations on each empire within each initial imperial group and calculating the power size of the imperial group after assimilation and revolution operations; conducting competition between imperial groups according to the power size of each imperial group and dividing the weakest empire; determining whether the iteration termination condition has been met, and if the determination result is that the iteration termination condition has been met, taking the iterated imperial group as the optimal distribution area topology optimization model.

[0093] In practical applications, the steps can be as follows:

[0094] 1) The dimension of the national solution is equivalent to the number of switches that are turned off, from the sequential ring matrix. A switch is randomly selected in each row and turned off.

[0095]

[0096] in, For the first Select the switch to disconnect from the circuit. For the position of the country.

[0097] 2) Calculate and sort the fitness function (power) of each initial country, and divide the countries into imperialist countries or colonial countries in order of priority. At the same time, randomly assign a certain number of colonies (matching their power size) to each empire to form the initial imperial group.

[0098]

[0099]

[0100] in, and The first The power and relative power of each empire To allocate to the first The number of colonies of each empire The number of colonies.

[0101] 3) Colonies move towards assimilation into the empire; this facilitates better control of the colonies by the empire. In essence, it represents the process by which colonies with poor fitness functions move closer to the empire with better fitness functions, thus changing the colonies' own fitness functions.

[0102]

[0103] in, For the location of colonies and empires. The assimilation coefficient, For the numerical value in Between dimensional vector, Indicates rounding down.

[0104] 4) Imperial Reform: The Cauchy mutation method is used to perturb the imperial position in order to generate a better fitness function value. This is considered as a process of imperial reform itself, and the perturbation process is as follows.

[0105]

[0106] in, For the new position after the imperial reforms, Let represent a random variable that follows a standard Cauchy distribution. Indicates rounding down.

[0107] The fitness function of the reformed empire is calculated and compared with that before the reform. If the fitness function of the reformed empire is better than that before the reform, the reform is considered successful and the original position is replaced by the new position of the reformed empire. Otherwise, the reform is considered a failure and the original position of the empire is maintained.

[0108] 5) Competition within the imperial group: powerful colonies replace the original empires and become new empires through internal competition, that is, comparing the fitness functions of colonies that have moved into the empire and the empire itself.

[0109] 6) Competition between imperial groups; simulating the process in real society where a stronger empire occupies and controls the colonies of a weaker empire to expand its own power.

[0110] Calculate and rank the power of the imperial groups using the following formula.

[0111]

[0112] in, For the first The power of the imperial group For the first The first empire The power of a colony, The influencing factor of colonial power depends on the degree of influence of the colonies on the imperial group.

[0113] Competition between imperial groups involves powerful imperial groups occupying the weakest colonies of the weakest imperial groups. The standardized power of each imperial group and the probability of each empire occupying a colony are calculated using the following formula, and a roulette wheel method is used to determine the empire.

[0114]

[0115]

[0116] in, As a standardized force for the Imperial Group, The probability that each empire occupies the weakest colony of the weakest empire group; i is the i-th empire.

[0117] 7) The demise of an imperial group; an imperial group perishes when it loses all its colonies.

[0118] 8) Determine if the termination condition, i.e., the maximum number of iterations, has been met. If so, output the optimal solution; otherwise, return to step 3.

[0119] Figure 2 An embodiment of the distribution area topology optimization system of the present invention is shown.

[0120] In this optional embodiment, the distribution area topology optimization system includes:

[0121] The optimization model construction module 201 is used to encode the basic loop circuits in the distribution transformer area using a sequential ring matrix real number encoding method to obtain the distribution transformer area topology optimization model.

[0122] The optimization model solving module 203 is used to solve the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model.

[0123] The model optimization processing module 205 is used to optimize the operating parameters of the distribution radio station using the optimal distribution radio station topology optimization model.

[0124] Correspondingly, in one embodiment, the operating parameters include at least one of the following: distribution substation topology connection information parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

[0125] Correspondingly, in one embodiment, the optimization model construction module 201 includes: a variable determination submodule (not shown in the figure), a function determination submodule (not shown in the figure), and a model construction submodule (not shown in the figure). The variable determination submodule is used to reorder the basic loops in the distribution substation according to the connection order of each row of branches in the distribution substation topology, obtaining an ordered basic loop matrix, and using the ordered basic loop matrix as the model decision variable. The function determination submodule is used to determine the voltage safety margin and current safety margin based on the distribution substation safety operation margin assessment index, and establish a model fitness function based on the voltage safety margin and current safety margin. The model construction submodule is used to construct a distribution substation topology optimization model based on the model decision variables, the model fitness function, and the constraints of the distribution substation.

[0126] Correspondingly, in one embodiment, the variable determination submodule (not shown in the figure) is also used to remove duplicate branches in each matrix row of the sequential basic ring matrix before using the sequential basic ring matrix as a model decision variable, so that each branch in the sequential basic ring matrix corresponds to only one matrix row, and the segmented switch of the sequential basic ring matrix is ​​located in the matrix row with the smallest power distance.

[0127] Correspondingly, in one embodiment, the constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints.

[0128] Correspondingly, in one embodiment, the optimization model solving module 203 includes: a country initialization submodule (not shown in the figure), a function calculation submodule (not shown in the figure), an imperial group initialization submodule (not shown in the figure), an imperial power calculation submodule (not shown in the figure), an imperial competition submodule (not shown in the figure), and an iteration judgment submodule (not shown in the figure). The country initialization submodule is used to initialize countries by taking the number of disconnected switches in the distribution area topology optimization model as the country solution dimension and the position of the disconnected switches in the distribution area topology optimization model as the country position. The function calculation submodule is used to calculate the fitness function of each initialized country based on the model fitness function of the distribution area topology optimization model. The imperial group initialization submodule is used to... The fitness functions of each initial state are sorted, and based on the sorting results, each initial state is divided into imperialist states and colonial states. Imperialist states are then assigned colonial states corresponding to their respective power levels, forming initial imperial groups. The imperial power calculation submodule performs assimilation and revolution operations on each empire within each initial imperial group and calculates the power level of the imperial group after these operations. The imperial competition submodule initiates competition between imperial groups based on their power levels, dividing up the weakest empire. The iteration judgment submodule determines whether the iteration termination condition has been met. If the determination result indicates that the iteration termination condition has been met, the iterated imperial group is used as the optimal distribution area topology optimization model.

[0129] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores static and dynamic information data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0130] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0131] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0132] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the method embodiments described above.

[0133] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0134] This invention is not limited to the structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this invention is limited only by the appended claims.

Claims

1. A method for optimizing the topology of a distribution radio station area, characterized in that, include: A topology optimization model for the distribution transformer area is obtained by encoding the basic loop circuits in the distribution transformer area using a sequential ring matrix real number encoding method. Based on the improved imperialist competition algorithm, the topology optimization model of the distribution area is solved to obtain the optimal distribution area topology optimization model; The optimal distribution area topology optimization model is used to optimize the operating parameters of each distribution area. Using a sequential ring matrix real-number encoding method, the basic loop circuits in the distribution network are encoded to obtain the distribution substation topology optimization model, which includes: The basic loops in the distribution transformer area are reordered according to the connection order of each branch in the distribution transformer area topology to obtain the sequential basic loop matrix, and the sequential basic loop matrix is ​​used as the model decision variable. Based on the safety margin assessment index of the distribution substation area, the voltage safety margin and current safety margin are determined, and based on the voltage safety margin and current safety margin, the model fitness function is established. Based on the model decision variables, the model fitness function, and the constraints of the distribution area, a distribution area topology optimization model is constructed. Based on the voltage safety margin and current safety margin, the formula for calculating the model fitness function is as follows: In the formula, These represent the number of nodes and branches in the distribution area, respectively. For nodes The actual operating voltage, , branch road The actual operating current, The maximum allowable current to ensure safety. As weight, , For voltage safety margin; For current safety margin, This is the model fitness function.

2. The distribution area topology optimization method according to claim 1, characterized in that, The operating parameters include at least one of the following: Distribution network topology connection parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

3. The distribution area topology optimization method according to claim 1, characterized in that, The basic loop circuits in the distribution network are encoded using a sequential ring matrix real number encoding method. The resulting distribution substation topology optimization model also includes: Before using the sequential basic ring matrix as a model decision variable, the duplicate branches in each matrix row of the sequential basic ring matrix are removed, so that each branch in the sequential basic ring matrix corresponds to only one matrix row, and the segmented switches of the sequential basic ring matrix are located in the matrix row with the smallest power distance.

4. The distribution area topology optimization method according to claim 1, characterized in that, The constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints.

5. The distribution area topology optimization method according to claim 1, characterized in that, Based on the improved imperialist competition algorithm, the distribution area topology optimization model is solved to obtain the optimal distribution area topology optimization model, which includes: The number of disconnected switches in the distribution area topology optimization model is used as the national solution dimension, and the position of the disconnected switches in the distribution area topology optimization model is used as the national position to initialize the national; Based on the model fitness function of the distribution area topology optimization model, calculate the fitness function of each initial country; The fitness functions of each initial country are sorted, and based on the sorting results, each initial country is divided into imperialist countries and colonial countries. The imperialist countries are then assigned colonial countries in batches corresponding to their power levels to form an initial imperial group. Assimilate and revolutionize the empires within each initial imperial group, and calculate the power of the imperial group after assimilation and revolution. Based on the strength of each imperial group, competition was held between the imperial groups to divide up the weakest empire. Determine whether the iteration termination condition has been met. If the result indicates that the iteration termination condition has been met, use the iterated Empire Group as the optimal distribution area topology optimization model.

6. A distribution area topology optimization system, characterized in that, include: The optimization model construction module is used to encode the basic loop circuits in the distribution transformer area using a sequential ring matrix real number encoding method to obtain the distribution transformer area topology optimization model. The optimization model solving module is used to solve the distribution area topology optimization model according to the improved imperialist competition algorithm to obtain the optimal distribution area topology optimization model; The model optimization processing module is used to optimize the operating parameters of the distribution area using the optimal distribution area topology optimization model. The optimization model construction module includes: a variable determination submodule, a function determination submodule, and a model construction submodule, wherein, The variable determination submodule is used to reorder the basic loops in the distribution area according to the connection order of each row of branches in the distribution area topology to obtain the sequential basic loop matrix, and use the sequential basic loop matrix as the model decision variable. The function determination submodule is used to determine the voltage safety margin and current safety margin based on the distribution substation safety operation margin assessment index, and to establish the model fitness function based on the voltage safety margin and current safety margin. The model construction submodule is used to construct a distribution area topology optimization model based on the model decision variables, the model fitness function, and the constraints of the distribution area. The function determines the calculation formula for the model fitness function based on the voltage safety margin and current safety margin. In the formula, These represent the number of nodes and branches in the distribution area, respectively. For nodes The actual operating voltage, branch road The actual operating current, The maximum allowable current to ensure safety. As weight, , For voltage safety margin; For current safety margin, This is the model fitness function.

7. The distribution area topology optimization system according to claim 6, characterized in that, The operating parameters include at least one of the following: Distribution network topology connection parameters, distribution network line model parameters, distribution network resistance and reactance parameters, distribution network node load level parameters, distribution network distributed photovoltaic access node parameters, and distribution network distributed photovoltaic node output level parameters.

8. The distribution area topology optimization system according to claim 6, characterized in that, The variable determination submodule is also used to remove duplicate branches in each matrix row of the sequential basic ring matrix before using the sequential basic ring matrix as a model decision variable, so that each branch in the sequential basic ring matrix corresponds to only one matrix row, and the segmented switch of the sequential basic ring matrix is ​​located in the matrix row with the smallest power distance.

9. The distribution area topology optimization system according to claim 6, characterized in that, The constraints include: power balance constraints, voltage operation constraints, current operation constraints, distributed photovoltaic output constraints, distribution area topology connectivity constraints, and switching operation count constraints.

10. The distribution area topology optimization system according to claim 6, characterized in that, The optimization model solution module includes: a national initialization submodule, a function calculation submodule, an imperial group initialization submodule, an imperial power calculation submodule, an imperial competition submodule, and an iterative judgment submodule. The country initialization submodule is used to initialize the country by taking the number of disconnected switches in the distribution area topology optimization model as the country solution dimension and the position of the disconnected switches in the distribution area topology optimization model as the country position. The function calculation submodule is used to calculate the fitness function of each initial country based on the model fitness function of the distribution area topology optimization model. The Imperial Group initialization submodule is used to sort the fitness functions of each initialization country, and according to the sorting results, divide each initialization country into imperialist countries and colonial countries, and assign colonial countries to the imperialist countries in batches corresponding to their power levels to form the initial imperial group. The imperial power calculation submodule is used to perform assimilation and revolution operations on each empire within each initial imperial group, and to calculate the power size of the imperial group after the assimilation and revolution operations. The Empire Competition submodule is used to conduct competition between empires based on the strength of each empire group, and to divide up the weakest empire. The iteration judgment submodule is used to determine whether the iteration termination condition has been met. If the judgment result is that the iteration termination condition has been met, the iterated Empire Group is used as the optimal distribution radio station topology optimization model.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of any one of claims 1 to 5.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 1.

13. A computer-readable storage medium according to claim 12, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 2.

14. A computer-readable storage medium according to claim 12, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 3.

15. A computer-readable storage medium according to claim 12, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 4.

16. A computer-readable storage medium according to claim 12, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 5.

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