Multi-voltage-class power distribution network flexible interconnection topology adaptive optimization method, system, device and medium

Abstract

The invention relates to the technical field of power distribution network intelligent optimization, and discloses a multi-voltage-class power distribution network flexible interconnection topology adaptive optimization method, system and device and a medium, and the method comprises the steps: building a unified topology model of a multi-voltage-class power distribution network based on a graph theory; determining an adjustable power transmission range according to the operation state and the rated parameters of the flexible interconnection device; carrying out topology pre-optimization on the interior of each voltage grade by taking the minimum network loss and the load balance as optimization objectives to obtain a pre-optimization topology scheme of the interior of each voltage grade; and cross-voltage grade coordination is realized by adjusting the power of the flexible interconnection device, and finally fine optimization of the whole network is carried out. The whole optimization process adopts an improved particle swarm algorithm for rapid solution, and the feasibility of the scheme is verified through real-time load flow calculation. And the optimized topology scheme is issued to a field switch device and a flexible interconnection device through a power distribution automation system to realize automatic adjustment of the operation mode of the power distribution network.

Description

Technical Field

[0001] This invention relates to the field of intelligent optimization technology for distribution networks, and in particular to an adaptive optimization method, system, device, and medium for flexible interconnection topology of multi-voltage level distribution networks. Background Technology

[0002] With the continuous growth of urban power distribution network load density and the large-scale integration of distributed energy resources, distribution network topology optimization and reconfiguration technologies are essential to improve power supply reliability and operational economy. Currently, topology optimization and reconfiguration typically focus on switching operations within a single voltage level, adjusting line connections to reduce network losses and balance loads, achieving positive results in certain scenarios. Meanwhile, soft-switching flexible interconnection technology provides a new equipment foundation for flexible power adjustment at specific locations.

[0003] However, existing technologies still have some limitations when facing the real-world requirements of multi-voltage level coordinated operation. Traditional topology optimization methods often treat networks of different voltage levels as independent systems for fragmented optimization, neglecting the power coupling and electrical constraints brought about by transformer connection points. This can lead to suboptimal optimization results at the global level, and may even cause voltage exceedances or equipment overloads. Furthermore, although flexible interconnection devices provide the ability to transmit power across voltage levels, there is still no systematic solution for how to deeply integrate them into the overall network topology optimization framework and achieve coordinated decision-making between device regulation and network structure changes. Most optimization methods rely on offline calculations and preset scenarios, making it difficult to cope with the real-time fluctuations in distributed generation output and load demand in distribution networks. They lack dynamic adaptive adjustment capabilities at the minute level or even faster, and cannot fully realize the real-time regulation potential of flexible interconnection devices. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method and system for adaptive optimization of flexible interconnection topology in multi-voltage-level distribution networks to solve the problems of lack of flexible interconnection between voltage levels, failure to consider coupling relationships in topology optimization, and lack of real-time optimization capabilities.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks, comprising: Acquire real-time operating data for multiple voltage levels in the distribution network, and identify the current network topology and operating status of each flexible interconnection device; Based on the identified structure and state, a unified topology model of the distribution network containing multiple voltage levels is constructed using graph theory; Determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; Based on the unified topology model, with the goals of reducing network loss and balancing load, topology pre-optimization is performed within each voltage level to obtain the pre-optimized topology scheme within each voltage level. Using the pre-optimized topology scheme as the initial solution, and taking the reduction of the overall network operation index as the objective function, the switching state and transmission power of the flexible interconnection device within each voltage level are optimized in a coordinated manner to obtain the optimized topology scheme for the entire network. Perform power flow calculations and security checks on the overall network topology optimization scheme; Once the verification is successful, control commands are generated and issued based on the optimized topology scheme for the entire network. Establish a historical optimization scheme library and intelligently recommend topology schemes based on the matching degree between the current operating scenario and historical scenarios.

[0007] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks described in this invention, the method involves: based on the identified structure and state, constructing a unified distribution network topology model containing multiple voltage levels using graph theory, including: Bus nodes, load nodes, and distributed power supply access points of different voltage levels are represented as a unified set of nodes. Lines connecting nodes within the same voltage level, transformers connecting nodes at different voltage levels, and flexible interconnection devices connecting different voltage levels or different feeders of the same voltage level are represented as a unified set of edges. Based on the set of nodes and the set of edges, an association matrix describing the connectivity of the entire network is formed, and topological constraints that maintain the radial operation of the distribution network are defined.

[0008] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks described in this invention, the adjustable power transmission range is determined based on the operating status and rated parameters of the flexible interconnection device, including: Calculate the current utilization rate of the flexible interconnection device based on its operating status and rated parameters; The utilization rate is defined as the ratio of the current apparent power of the flexible interconnect device to its rated capacity; A preset adjustment threshold is used to determine the adjustable power transmission range based on the ratio and the magnitude of the adjustment threshold.

[0009] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks described in this invention, the step of performing topology pre-optimization within each voltage level to obtain a pre-optimized topology scheme for each voltage level includes: Encode the state combinations of operable switches within the current voltage level into optimization variables; The fitness function is the weighted sum of the active power loss and load balance of the network at the current voltage level. A swarm intelligence optimization algorithm is used to search under the condition of satisfying radial constraints, and the combination of switching states that makes the fitness function optimal is obtained as the pre-optimized topology scheme for the current voltage level.

[0010] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of a multi-voltage-level distribution network described in this invention, the method of collaboratively optimizing the switching states and transmission power of the flexible interconnection devices within each voltage level to obtain an optimized topology scheme for the entire network includes: A two-level nested optimization structure is adopted, wherein: The outer layer optimization uses the operable switch states at all voltage levels as decision variables and employs a particle swarm optimization algorithm for optimization. For each candidate topology generated by the outer layer optimization, the inner layer optimization is initiated. Based on the overall network optimization objective function, the transmission power of each flexible interconnection device is used as a continuous decision variable, and the optimal power allocation under the topology is obtained by solving the sequential quadratic programming method. During the outer particle swarm iteration process, the globally optimal solution and its corresponding power setting value for the flexible interconnect device are recorded.

[0011] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks described in this invention, the method includes: performing power flow calculation and security verification on the optimized topology scheme for the entire network, including: Power flow calculations were performed using the Newton-Raphson method, with the high-voltage side busbars of each substation as the balancing nodes and all other nodes as PQ nodes or PV nodes. The transformer branch is incorporated into the Jacobian matrix through the equivalent impedance model, while the flexible interconnection device is treated as a constant power source, and the injected power is the set value determined by optimization. The power flow equations are solved iteratively. When the voltage magnitude and phase angle correction of all nodes are less than the preset first threshold, the power flow is considered to have converged. After the power flow converges, check all constraints. If all constraints are satisfied, the safety check passes.

[0012] As a preferred embodiment of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks described in this invention, the method includes: establishing a historical optimization scheme library, and intelligently recommending topology schemes based on the matching degree between the current operating scenario and historical scenarios, including: Record the runtime scenario characteristic data and the corresponding optimized topology scheme during historical optimization; Clustering algorithms are used to divide historical operation scenarios into multiple typical scenario categories, and one or more preferred topology schemes are associated with each typical scenario; When optimization is required, the similarity between the current running scenario and each typical scenario is calculated; If the similarity exceeds a preset second threshold, the corresponding preferred topology scheme is directly called as the network-wide optimized topology scheme.

[0013] Secondly, the present invention provides a flexible interconnection topology adaptive optimization system for multi-voltage level distribution networks, comprising: The acquisition module is used to acquire real-time operating data of multiple voltage levels in the distribution network and identify the current network topology and the operating status of each flexible interconnection device. The topology model building module is used to construct a unified topology model of a distribution network containing multiple voltage levels based on the identified structure and state using graph theory. The determination module is used to determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; The pre-optimization module is used to perform topology pre-optimization within each voltage level based on the unified topology model, with the goal of reducing network loss and balancing load, to obtain the pre-optimized topology scheme within each voltage level. The collaborative optimization module is used to take the pre-optimized topology scheme as the initial solution and reduce the overall network operation index as the objective function to collaboratively optimize the switching state and transmission power of flexible interconnection devices within each voltage level to obtain the network-wide optimized topology scheme. The verification module is used to perform power flow calculations and security verifications on the network-wide optimized topology scheme. The execution module is used to generate and issue control commands based on the network-wide optimized topology scheme after the verification is passed. The matching and recommendation module is used to build a historical optimization solution library and intelligently recommend topology solutions based on the matching degree between the current running scenario and historical scenarios.

[0014] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of an adaptive optimization method for flexible interconnection topology of a multi-voltage level distribution network.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the adaptive optimization method for flexible interconnection topology of a multi-voltage-level distribution network.

[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention abstracts a multi-voltage-level distribution network into a unified graph theory model, which simultaneously represents network nodes, line connections, and cross-voltage-level devices such as transformers and flexible interconnection devices at different voltage levels. It accurately describes the power exchange and constraint relationships between voltage levels, providing an accurate mathematical basis for global optimization. Furthermore, it establishes controllable power transmission channels between networks at different voltage levels through flexible interconnection devices, enabling the shared utilization of surplus capacity at each voltage level. The flexible interconnection devices can adjust the magnitude and direction of transmitted power according to real-time operational needs, while maintaining electrical decoupling between voltage levels, preventing fault propagation between different voltage levels. Additionally, through a hierarchical progressive optimization strategy, the complex whole-network optimization problem is decomposed into multiple sub-problems, reducing computational complexity. Combined with real-time data acquisition and fast power flow calculation methods, topology optimization calculations can be completed and control commands issued within minutes, enabling adaptive adjustment of the distribution network topology as operating conditions change. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the overall process of an adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks according to an embodiment of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0020] Example 1, referring to Figure 1 As an embodiment of the present invention, an adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks is provided, comprising: S100: Acquires real-time operating data of multiple voltage levels in the distribution network and identifies the current network topology and the operating status of each flexible interconnection device; S200: Based on the identified structure and state, a unified topology model of the distribution network containing multiple voltage levels is constructed using graph theory; S300: Determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; S400: Based on the unified topology model, with the goal of reducing network loss and balancing load, the topology is pre-optimized for each voltage level to obtain the pre-optimized topology scheme for each voltage level. S500: Using the pre-optimized topology scheme as the initial solution, and taking the reduction of the overall network operation index as the objective function, the switching state and transmission power of the flexible interconnection device within each voltage level are optimized in a coordinated manner to obtain the optimized topology scheme for the entire network. S600: Performs power flow calculations and security verifications on the network-wide optimized topology scheme; S700: After the verification is passed, control commands are generated and issued according to the network-wide optimized topology scheme; S800: Establishes a historical optimization scheme library and intelligently recommends topology schemes based on the matching degree between the current operating scenario and historical scenarios.

[0021] Specifically, this invention establishes a unified topology model for multi-voltage level distribution networks based on graph theory using S100-S800, representing lines, nodes, transformers, and flexible interconnection devices at different voltage levels as edges and nodes in the graph. Based on this model, a multi-objective optimization problem is established with the optimization objectives of minimizing network losses and load balancing, incorporating radial constraints, node voltage constraints, and branch capacity constraints. A hierarchical progressive optimization strategy is adopted, first performing topology pre-optimization within each voltage level, then achieving cross-voltage level coordination by adjusting the power of flexible interconnection devices, and finally performing refined optimization across the entire network. The entire optimization process is solved quickly using an improved particle swarm optimization algorithm, and the feasibility of the scheme is verified through real-time power flow calculations. The optimized topology scheme is distributed to field switchgear and flexible interconnection devices through the distribution automation system, enabling automatic adjustment of the distribution network operation mode.

[0022] Example 2, refer to Figure 1 As an embodiment of the present invention, based on the above embodiment, an adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks is provided. The method includes: S100: Acquires real-time operating data of multiple voltage levels in the distribution network and identifies the current network topology and the operating status of each flexible interconnection device; Specifically, real-time operational data can include: electrical quantities such as voltage amplitude and phase angle at each node, current in each branch, active power and reactive power, as well as the opening and closing status of each switchgear and the operating parameters of the flexible interconnection device. For example, the acquisition cycle can be 5 seconds to ensure the real-time nature of the data.

[0023] In one optional implementation, S100 can collect real-time operating data of multi-voltage level distribution networks through the distribution automation master station, and perform quality verification on the collected raw data to remove outliers; specifically, the data integrity index can be defined as the ratio of the actual number of received data packets to the number of data packets that should be received: (1) In the formula, The data integrity coefficient. This represents the actual number of data packets received. The number of data packets to be received. If the data for that period is incomplete, it is determined that the data needs to be re-collected or interpolated from adjacent measurement points.

[0024] For voltage data, a reasonableness check is performed. Node voltage deviation is defined as the difference between the measured voltage and the rated voltage of a node divided by the rated voltage. When the absolute value of the voltage deviation of a node exceeds 10%, the data is considered abnormal, and the data repair process is initiated. Data repair can use the average value substitution method of adjacent nodes, that is, using the average voltage of all normal nodes directly connected to the current node as the repair value.

[0025] In another optional implementation, the current network topology can be identified in S100 based on the status of the switching equipment. All lines corresponding to switches in the closed state are marked as connected, and lines corresponding to switches in the open state are marked as disconnected. A depth-first search algorithm is used to traverse the network, identifying connected branches within each voltage level and determining whether they meet the requirements for radial operation. If a loop network exists within a certain voltage level, the system automatically records the loop path and prioritizes its handling during subsequent topology optimization.

[0026] In addition, the operating status of each flexible interconnection device is identified in S100, which may include the active and reactive power currently transmitted by the device, DC side voltage, AC side current, and device operating mode, etc.; the above parameters can be used in S300 to determine the adjustable range of the flexible interconnection device.

[0027] S200: Based on the identified structure and state, a unified topology model of the distribution network containing multiple voltage levels is constructed using graph theory; In this embodiment of the application, step S200 involves constructing a unified topology model of the distribution network containing multiple voltage levels based on the identified structure and state using graph theory, including the following steps A1-A3: A1: Represent bus nodes, load nodes, and distributed power supply access points of different voltage levels as a unified set of nodes; A2: Lines connecting nodes within the same voltage level, transformers connecting nodes at different voltage levels, and flexible interconnection devices connecting different voltage levels or different feeders of the same voltage level are represented as a unified set of edges. A3: Based on the set of nodes and the set of edges, form an association matrix describing the connection relationship of the entire network, and define topological constraints to maintain the radial operation of the distribution network.

[0028] Specifically, in A1, the bus nodes, load nodes, and distributed power source access points in the distribution network are uniformly represented as the node set in the graph, and the lines, transformers, and flexible interconnection devices are uniformly represented as the edge set in the graph.

[0029] For example, for those containing One 110kV node, 35kV nodes and The distribution network with 10kV nodes has a total number of nodes: (2) In the formula, This represents the total number of nodes in the distribution network. The number of nodes at the 110kV voltage level. The number of nodes at the 35kV voltage level. This refers to the number of nodes at the 10kV voltage level.

[0030] To distinguish between different voltage levels, a voltage level label is attached to each node. The state vector contains the node voltage magnitude Voltage phase angle Injected active power and injected reactive power .

[0031] Specifically, in A2, the branch set includes three types of edges: distribution lines within the same voltage level, transformers connecting different voltage levels, and flexible interconnection devices connecting different voltage levels. Branch Connecting nodes and nodes Its state is determined by the switch state variable. The value is 1, which indicates that the branch is connected, and 0 indicates that the branch is disconnected.

[0032] Specifically, in A3, the network correlation matrix is ​​constructed. The matrix elements are defined as follows: if the branch The beginning is a node Then matrix elements The value is 1; if the branch The end is a node ,but The value is -1; if the branch Not with nodes If connected, then The value is 0. The correlation matrix can be used to conveniently express the topological connections of a network.

[0033] For transformer branches, in addition to recording the high-voltage and low-voltage side nodes they are connected to, the transformer's turns ratio, rated capacity, and impedance parameters must also be recorded. For flexible interconnection device branches, the nodes on both sides they are connected to (which may belong to different voltage levels), as well as the device's capacity limitations and current operating point, should be recorded.

[0034] Specifically, in A3, topological constraints for maintaining the radial operation of the distribution network are defined, namely: establishing radial constraint conditions; the radial operation of the distribution network requires that there are no loops in the network, that is, there is only one path connecting any two nodes. Mathematically, this can be expressed as: for In a network with a given number of nodes, the number of branches in the connected state should be equal to... And all nodes are connected. Network connectivity is determined by checking the rank of the incidence matrix, where the rank is 1. This indicates that the network is connected and has no loops.

[0035] S300: Determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; In this embodiment of the application, step S300, determining the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device, includes the following steps B1-B3: B1: Calculate the current utilization rate of the flexible interconnection device based on its operating status and rated parameters; Specifically, flexible interconnect devices achieve power exchange between different voltage levels through power electronic converters, but their operation is limited by capacity. For connection nodes... and nodes Flexible interconnected devices The active power transmitted is denoted as The transmitted reactive power is denoted as .

[0036] Define the apparent power constraint of flexible interconnect devices as follows: (3) In the formula, For flexible interconnect devices Transmitted active power, For flexible interconnect devices Transmitted reactive power For device The rated capacity; this constraint ensures that the device operates within a safe range.

[0037] Furthermore, the power transmission direction of flexible interconnect devices can be flexibly adjusted, i.e., active power... Can be a positive value (from node) To the node (transmission) or negative value (from node) To the node transmission).

[0038] It should be noted that the aforementioned bidirectional adjustment capability enables the flexible interconnection device to flexibly allocate power according to the load requirements of the networks on both sides.

[0039] B2: The utilization rate is defined as the ratio of the current apparent power of the flexible interconnect device to its rated capacity; Specifically, based on flexible interconnect devices The current utilization rate is calculated from the real-time operating data and is defined as the ratio of the current apparent power to the rated capacity.

[0040] B3: A preset adjustment threshold is used to determine the adjustable power transmission range based on the ratio and the magnitude of the adjustment threshold.

[0041] For example, when the utilization rate exceeds the adjustment threshold (90%), it indicates that the device is operating close to full load and has a small adjustment margin. In subsequent optimization, it is necessary to focus on the load transfer of the area connected to the device to avoid overloading the device.

[0042] Furthermore, the adjustable power range of all flexible interconnect devices is statistically analyzed. For the device... Its active power adjustable range is between the negative rated capacity and the positive rated capacity, while the reactive power adjustable range depends on the current active power and can be calculated by the apparent power constraint of formula (3). The adjustable power transmission range is used as the boundary of the decision variable in the optimization calculation of S500.

[0043] S400: Based on the unified topology model, with the goal of reducing network loss and balancing load, the topology is pre-optimized for each voltage level to obtain the pre-optimized topology scheme for each voltage level. In this embodiment of the application, the topology pre-optimization performed in step S400 to obtain the pre-optimized topology scheme within each voltage level includes the following steps C1-C3: C1: Encode the state combination of operable switches within the current voltage level into optimization variables; C2: The fitness function is the weighted sum of the active power loss and load balance of the network at the current voltage level. C3: Using a swarm intelligence optimization algorithm, a search is performed under the condition of satisfying radial constraints to obtain the switching state combination that optimizes the fitness function, which serves as the pre-optimized topology scheme for the current voltage level.

[0044] It should be noted that, in C1-C3, before performing network-wide coordinated optimization, topology pre-optimization is first performed within each voltage level to reduce the search space for subsequent global optimization.

[0045] For example, the single-voltage-level topology optimization process is illustrated using a 10kV distribution network as an example.

[0046] Identify all operable tie switches and sectionalizing switches in the 10kV network, ensuring that adjustments to their opening and closing states do not affect operation at other voltage levels. For [specific voltage levels]... A 10kV network with operable switches theoretically exists. There are several topological combinations, but they need to satisfy radial constraints, and the actual number of feasible solutions is much smaller than this value.

[0047] An improved particle swarm optimization algorithm is used to solve for the optimal topology. In C1, the state of each operable switch is encoded as a dimension of a particle, with a value of 0 or 1 representing the switch being open or closed, respectively. When initializing the particle swarm, the current running topology is used as one particle, and the remaining particles are randomly generated, but must satisfy radial constraints. The particle swarm size is set to 30 particles to achieve a balance between search efficiency and solution quality.

[0048] In C2, the fitness function is defined as a weighted sum of network active power loss and load balance: (4) In the formula, To optimize the objective function value, This is the network loss weighting coefficient. For the total active power loss of the network, This is the load balancing weighting coefficient. The standard deviation of the load rate for each branch is represented. Network active power loss is calculated through power flow and equals the sum of losses across all branches. Load balance is defined as the standard deviation of the load rate for all branches; a smaller standard deviation indicates a more balanced load distribution across branches. By adjusting the weighting coefficients, a preference can be set between loss reduction and load balance. In this embodiment... =0.5, =0.5.

[0049] In C3, during particle updates, each particle adjusts its velocity and position based on its historical best position and global best position. Since the particle dimension is discrete (0 or 1), a sigmoid function is used to map continuous velocities to on / off state flip probabilities. After each iteration, it is necessary to check whether the new topology satisfies the radial constraints; if not, it is regenerated.

[0050] The maximum number of iterations is set to 50. The search terminates and the current optimal topology is output when the maximum number of iterations is reached or the global optimal solution fails to improve after 10 consecutive iterations. The network loss and load distribution of this solution are recorded as the initial state for the fifth step of network-wide coordination.

[0051] The optimization process was repeated for the 35kV and 110kV networks to obtain pre-optimized topology schemes for each voltage level. Since different voltage levels are connected via transformers and flexible interconnection devices, the pre-optimized schemes for each voltage level may require further adjustments during network-wide coordination.

[0052] S500: Using the pre-optimized topology scheme as the initial solution, and taking the reduction of the overall network operation index as the objective function, the switching state and transmission power of the flexible interconnection device within each voltage level are optimized in a coordinated manner to obtain the optimized topology scheme for the entire network. Specifically, with the objective function of reducing the overall network performance indicators, it can be expressed as: (5) In the formula, To optimize the objective function for the entire network, For the first Network loss at each voltage level ( (These correspond to 110kV, 35kV, and 10kV respectively.) This is the voltage deviation penalty coefficient. For nodes The actual voltage, For nodes The rated voltage. The objective is to minimize the objective function while satisfying all constraints. In this embodiment... =100.

[0053] Constraints may include: radial constraints, node voltage upper and lower limits constraints, branch capacity constraints, transformer capacity constraints, and flexible interconnection device capacity constraints.

[0054] The node voltage constraint can be expressed as: (6) For example, in the formula, the allowable deviation of the node voltage is ±7% of the rated voltage.

[0055] Branch current constraints are defined as branch currents not exceeding their rated current carrying capacity, and the apparent power of transformers and flexible interconnection devices not exceeding their rated capacity.

[0056] Radial constraints require that the distribution network topology maintain a loop-free tree structure, meaning that the number of closed branches is one less than the number of nodes.

[0057] Transformer capacity constraint means that the apparent power flowing through the transformer does not exceed its rated capacity.

[0058] The capacity constraint of a flexible interconnect device is defined as the apparent power transmitted by the device not exceeding its rated capacity.

[0059] In this embodiment of the application, the step S500, which involves collaboratively optimizing the switching states and transmission power of flexible interconnect devices within each voltage level to obtain a network-wide optimized topology scheme, includes the following steps D1-D3: A two-level nested optimization structure is adopted, wherein: D1: The outer layer optimization uses the operable switch states of all voltage levels as decision variables and employs the particle swarm optimization algorithm for optimization. D2: For each candidate topology generated by the outer layer optimization, the inner layer optimization is initiated. Based on the overall network optimization objective function, the transmission power of each flexible interconnection device is used as a continuous decision variable. The optimal power allocation under the topology is obtained by solving the sequential quadratic programming method. D3: Record the globally optimal solution and its corresponding power setting value for the flexible interconnect device during the outer particle swarm iteration process.

[0060] The decision variables include the states of all operable switches. Active power transmitted by all flexible interconnect devices The active power of the flexible interconnect device is treated as a continuous variable and optimized within its adjustable range. Reactive power is determined based on the active power and the device control strategy. For example, in this embodiment, the flexible interconnect device employs constant power factor control, with the power factor set to 0.95.

[0061] Specifically, in D1-D3, the outer layer optimizes and adjusts the switch states, i.e., determines the network topology; the inner layer optimizes and adjusts the power of flexible interconnect devices, i.e., finds the optimal power allocation under a given topology. The outer layer uses the particle swarm optimization algorithm, and the inner layer uses a sequential quadratic programming algorithm to solve the continuous optimization problem.

[0062] The particle encoding of the outer particle swarm optimization algorithm includes the states of all voltage-level operable switches. For each topology scheme represented by a particle, the inner optimization is initiated to adjust the power of the flexible interconnect device. The inner optimization uses the objective function of formula (5) as the optimization objective and the power of the flexible interconnect device as the decision variable, and is solved quickly by the sequential quadratic programming method.

[0063] After each inner-layer optimization, a power flow calculation is performed to verify whether the scheme satisfies all constraints. The power flow calculation uses the forward-backward substitution method, which is highly efficient and convergent for radial distribution networks. The power flow calculation obtains the voltages of all nodes and the currents of all branches, and checks for voltage overruns or overloads. If an overrun occurs, a penalty is imposed on the particle, reducing its fitness; if all constraints are satisfied, the objective function value of the scheme is calculated as its fitness.

[0064] During the outer-layer particle swarm optimization process, the globally optimal solution and its corresponding power setting value for the flexible interconnect device are recorded. The iteration termination condition is the same as that for single-voltage-level optimization: it stops when the maximum number of iterations is reached or when there is no improvement after multiple consecutive iterations.

[0065] It should be noted that, based on pre-optimization at each voltage level, the S500 achieves cross-voltage level coordination by adjusting the power of the flexible interconnect device, further reducing overall network losses and improving voltage quality.

[0066] S600: Performs power flow calculations and security verifications on the network-wide optimized topology scheme; In this embodiment of the application, step S600, which involves power flow calculation and security verification of the network-wide optimized topology scheme, includes the following steps E1-E4: E1: Power flow calculation is performed using the Newton-Raphson method, with the high-voltage side busbar of each substation as the balancing node and all other nodes as PQ nodes or PV nodes. Specifically, the Newton-Raphson method obtains accurate nodal voltages and branch power by solving the nonlinear power flow equations, achieving higher calculation accuracy than the forward-backward substitution method; for nodes Its power balance equation is: (7) (8) In the formula, and They are nodes The injection of active and reactive power, and They are nodes and nodes voltage amplitude, The phase angle difference between the two nodes. and These are the real and imaginary parts of the elements in the nodal admittance matrix, respectively.

[0067] In the power flow calculation, the high-voltage side bus of each substation is taken as the balancing node, and all other nodes are taken as PQ nodes or PV nodes; for example, the grid connection point of distributed power source is regarded as PV node, and the constant power load point is regarded as PQ node.

[0068] E2: The transformer branch is incorporated into the Jacobian matrix through the equivalent impedance model, while the flexible interconnection device is treated as a constant power source, and the injected power is the set value determined by optimization. It should be noted that the Jacobian matrix of the power flow equations needs to take into account the special characteristics of transformers and flexible interconnection devices. Therefore, it is incorporated into the Jacobian matrix through an equivalent impedance model, and the flexible interconnection devices are treated as constant power sources.

[0069] E3: Iteratively solve the power flow equations. When the voltage magnitude and phase angle correction of all nodes are less than the preset first threshold, the power flow is determined to be converged. For example, the first threshold can be set to 0.0001 per unit to ensure calculation accuracy. If the power flow fails to converge within 20 iterations, the scheme is deemed to have a power flow infeasibility problem, and the process returns to step five for re-optimization.

[0070] E4: After the power flow converges, check all constraints. If all constraints are satisfied, the safety check passes.

[0071] In an alternative implementation, the constraint in E4 can be: check whether all node voltages satisfy the constraint of formula (6), and if any voltage exceeds the lower limit (below the lower limit)... or exceeding the upper limit (higher than) For each node, record the node number and degree of over-limit. Check whether the current of all branches exceeds the rated current carrying capacity. If there are overloaded branches, record the overloaded branch number and overload rate. Check whether the apparent power of all transformers and flexible interconnection devices meets the capacity constraint of formula (3).

[0072] In another alternative implementation, based on the above implementation, if all constraints in E4 are satisfied, the topology scheme is confirmed to be feasible, and the seventh step is prepared for execution; if any constraint is violated, the cause of the violation is analyzed and the optimization parameters are adjusted. For example, if the voltage is generally low in a certain area, the voltage deviation penalty coefficient in formula (5) can be increased. If a branch is continuously overloaded, consider adjusting the topology to shift the load on that branch. After adjustment, return to S500 for re-optimization.

[0073] S700: After the verification is passed, control commands are generated and issued according to the network-wide optimized topology scheme; In one optional implementation, after the control command is issued to the field equipment in S700 for execution, the current actual operating topology can be compared with the optimized target topology to identify the switching equipment that needs to change its state. Switches requiring opening are included in the opening operation sequence, and switches requiring closing are included in the closing operation sequence. An operation timing sequence is established to ensure that the radial constraint is satisfied at any time during the topology adjustment process, avoiding instantaneous loops or power outages. The operation principle is to open before closing, that is: first, perform the opening operation to open certain branches, and then perform the closing operation to connect other branches. Sufficient time intervals are maintained between opening and closing to ensure that the mechanical action of the switches is completed and the system remains stable.

[0074] In another optional implementation, based on the above implementation of S700, for the flexible interconnection device, its active and reactive power setpoints are calculated according to the optimization results and sent to the device controller via the communication interface. After receiving the instruction, the flexible interconnection device achieves a smooth transition in power transmission by adjusting the parameters of its internal power controller. The transition time is generally set to 30 seconds to avoid power surges impacting the power grid.

[0075] Control commands are issued through the power distribution automation system, which employs a dual confirmation mechanism to ensure safe command execution. First, a preset command is sent to the target device. Upon receiving this command, the device returns a confirmation message but does not execute it immediately. Only after receiving the confirmation does the system send an execution command, and the device actually changes its state upon receiving the execution command. After the device completes its action, it sends status information back to the system. Once the system confirms that the feedback information matches expectations, the operation process for that device ends.

[0076] After adjustments are made, the system collects operational data again to verify that the actual topology matches the target topology, and that the actual network loss and voltage distribution are basically consistent with the calculated values. If the actual results deviate significantly from the expectations, the scheme review process is initiated to analyze the causes of the deviations and make necessary secondary adjustments.

[0077] In this embodiment of the application, step S800 establishes a historical optimization scheme library and intelligently recommends topology schemes based on the matching degree between the current running scenario and historical scenarios, including the following steps F1-F4: F1: Records the runtime scenario feature data and the corresponding optimized topology scheme during historical optimizations; For example, the input conditions for each topology optimization, such as load distribution, distributed power output, and equipment status, are recorded; as well as the output results, such as optimal topology, network loss, and voltage level, to establish a topology scheme library. This library can be stored in a relational database for easy retrieval and analysis.

[0078] F2: Using a clustering algorithm, historical running scenarios are divided into multiple typical scenario categories, and one or more preferred topology schemes are associated with each typical scenario; In one alternative implementation, cluster analysis is performed on historical schemes in the scheme library to identify typical operating scenarios. The K-means clustering algorithm can be used, with the load distribution vector as the clustering feature, and each typical scenario corresponds to a set of preferred topology schemes.

[0079] F3: When optimization is required, calculate the similarity between the current running scenario and each typical scenario; Specifically, scene similarity is defined as: (9) In the formula, This represents the Euclidean distance between the current scene and the typical scene. For the current scene node The load power, For nodes in typical scenarios The load power. Historical data is divided into several typical scenarios, such as weekday peak, weekday off-peak, weekend peak, and weekend off-peak.

[0080] F4: If the similarity exceeds the preset second threshold, the corresponding preferred topology scheme is directly called as the network-wide optimized topology scheme.

[0081] For example, when the system detects that the current operating condition is similar to a typical scenario, that is: (second threshold) (5% of the total load can be taken) to directly call the optimal solution for this scenario without having to perform a complete optimization calculation again, which can significantly shorten the response time.

[0082] In another optional implementation, based on the above implementation, for new operating conditions that have not yet occurred, the system executes a complete optimization calculation process and adds the calculation results to the solution library, continuously enriching the content of the solution library. As the system's running time increases, the scenarios covered by the solution library become more comprehensive, and the system's intelligent recommendation capability gradually improves, gradually realizing the transformation from optimization calculation-based to case-based reasoning.

[0083] Regularly maintain the solution library and remove outdated solutions. When the network topology undergoes permanent changes such as adding lines or removing equipment, clear the historical solutions for the relevant areas and re-accumulate operational data under the new topology. Simultaneously, analyze the actual application frequency and effectiveness of each solution, retaining high-frequency, efficient, and high-quality solutions while removing low-frequency, inefficient, and redundant solutions to keep the solution library streamlined and efficient.

[0084] In summary, this invention establishes a controllable power transmission channel between different voltage levels through flexible interconnection devices, breaking through the electrical isolation between voltage levels in traditional distribution networks. This allows for the sharing and utilization of surplus capacity at each voltage level, enabling flexible power exchange between multiple voltage levels. The optimized average and maximum voltage deviations are significantly reduced, and all node voltages are within acceptable limits. Good voltage quality extends the lifespan of user equipment and reduces complaints caused by voltage quality issues. Simultaneously, topology optimization and flexible interconnection device adjustments improve the distribution network's ability to handle faults, enabling rapid power transfer in the event of a main equipment failure, thus enhancing power supply reliability. The combination of a hierarchical progressive optimization strategy and intelligent solution recommendation technology shortens optimization calculation time to meet real-time control requirements. Finally, the establishment of a solution library further reduces the system's response time to typical scenarios to the order of seconds, enabling the overall distribution network topology to adaptively adjust according to operating conditions.

[0085] Example 3, referring to Tables 1-3, provides a simulation application scheme for an adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks, to verify the feasibility and effectiveness of the present invention.

[0086] This simulation example is based on an actual urban power distribution network. The network includes one 110kV substation, three 35kV substations, and eight 10kV switching stations. The 110kV main transformer capacity is 2×50MVA, and the 35kV substation main transformer capacities are 2×20MVA, 2×20MVA, and 1×31.5MVA, respectively. There are 32 10kV feeders with a total length of approximately 185 kilometers. Twelve distributed photovoltaic power stations with a total installed capacity of 18MW are connected to the network, distributed across different 10kV feeders. One flexible interconnection device with a capacity of 10MVA is installed between the 110kV and 35kV busbars; one flexible interconnection device with a capacity of 8MVA is installed between the two 35kV substations; and three flexible interconnection devices with a capacity of 5MVA are installed between different 10kV feeders.

[0087] The simulation scenario was set to simulate a typical summer workday operation, with the load exhibiting a clear bi-peak characteristic. The load peaks at 10:00 AM and 3:00 PM, reaching a total load of 72MW and 75MW respectively; the load trough is at 3:00 AM, with a total load of approximately 28MW. The photovoltaic power station's output is related to solar radiation intensity, peaking at approximately 15MW at noon, with no output at night. The simulation used a 15-minute time step, totaling 96 time segments.

[0088] Table 1 shows a comparison of the optimization results: The method of this invention is compared with the traditional single voltage level optimization method to verify the effect of cross-voltage level coordinated optimization.

[0089] Table 1: Comparison of Optimization Effects of Different Methods

[0090] As shown in Table 1, the daily average network loss of the method of this invention is reduced by 28.3% compared with the baseline without optimization, and further reduced by 13.1 percentage points compared with the single voltage level optimization method, demonstrating significant optimization effect. Meanwhile, the calculation time of this method is only 156 seconds, far lower than the 412 seconds of the traditional two-layer optimization method, meeting the requirements of real-time optimization. The number of topology adjustments is controlled within a reasonable range to avoid frequent operations affecting equipment lifespan.

[0091] The utilization effect of flexible interconnection devices is shown in Table 2: We statistically analyzed the power transmission of each flexible interconnect device before and after optimization, and examined its role in cross-voltage level coordination.

[0092] Table 2: Power Adjustment of Flexible Interconnect Devices

[0093] Table 2 shows that the power transmission capacity of all flexible interconnect devices increased significantly after optimization, with an average regulation capacity of 3.0MW and a daily utilization rate of about 70%, which fully utilized the power regulation capability of the flexible interconnect devices and achieved optimized load distribution among different voltage levels.

[0094] The voltage quality improvement effect is shown in Table 3: By comparing the voltage distribution at each voltage level before and after optimization, the effectiveness of the method in improving voltage quality is evaluated.

[0095] Table 3: Statistics of Voltage Deviation Before and After Optimization

[0096] After optimization, the voltage deviation of all voltage levels was significantly reduced. The average voltage deviation of the entire network decreased from 2.9% to 1.5%, and the maximum voltage deviation decreased from 6.8% to 3.1%. The voltage of all nodes was within the specified allowable range, and no over-limit situations occurred, resulting in a significant improvement in voltage quality.

[0097] Example 4 illustrates a schematic scheme for an adaptive optimization method of flexible interconnection topology in a multi-voltage-level distribution network. It should be noted that the technical solution of this adaptive optimization system for flexible interconnection topology in a multi-voltage-level distribution network is based on the same concept as the aforementioned adaptive optimization method for flexible interconnection topology in a multi-voltage-level distribution network. Details not described in detail in this example can be found in the description of the aforementioned adaptive optimization method for flexible interconnection topology in a multi-voltage-level distribution network.

[0098] This embodiment also provides a multi-voltage level distribution network flexible interconnection topology adaptive optimization system, including: The acquisition module is used to acquire real-time operating data of multiple voltage levels in the distribution network and identify the current network topology and the operating status of each flexible interconnection device. The topology model building module is used to construct a unified topology model of a distribution network containing multiple voltage levels based on the identified structure and state using graph theory. The determination module is used to determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; The pre-optimization module is used to perform topology pre-optimization within each voltage level based on the unified topology model, with the goal of reducing network loss and balancing load, to obtain the pre-optimized topology scheme within each voltage level. The collaborative optimization module is used to take the pre-optimized topology scheme as the initial solution and reduce the overall network operation index as the objective function to collaboratively optimize the switching state and transmission power of flexible interconnection devices within each voltage level to obtain the network-wide optimized topology scheme. The verification module is used to perform power flow calculations and security verifications on the network-wide optimized topology scheme. The execution module is used to generate and issue control commands based on the network-wide optimized topology scheme after the verification is passed. The matching and recommendation module is used to build a historical optimization solution library and intelligently recommend topology solutions based on the matching degree between the current running scenario and historical scenarios.

[0099] This embodiment also provides a computer device applicable to a multi-voltage level distribution network flexible interconnection topology adaptive optimization scenario, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the multi-voltage level distribution network flexible interconnection topology adaptive optimization method proposed in the above embodiment.

[0100] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements an adaptive optimization method for flexible interconnection topology of a multi-voltage level distribution network as proposed in the above embodiments.

[0101] The storage medium proposed in this embodiment belongs to the same inventive concept as the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0102] Based on the above description of the implementation methods, those skilled in the art will clearly understand that the present invention can be implemented using software and necessary general-purpose hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for adaptive optimization of flexible interconnection topology in multi-voltage level distribution networks, characterized in that, include: Acquire real-time operating data for multiple voltage levels in the distribution network, and identify the current network topology and operating status of each flexible interconnection device; Based on the identified structure and state, a unified topology model of the distribution network containing multiple voltage levels is constructed using graph theory; Determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; Based on the unified topology model, with the goals of reducing network loss and balancing load, topology pre-optimization is performed within each voltage level to obtain the pre-optimized topology scheme within each voltage level. Using the pre-optimized topology scheme as the initial solution, and taking the reduction of the overall network operation index as the objective function, the switching state and transmission power of the flexible interconnection device within each voltage level are optimized in a coordinated manner to obtain the optimized topology scheme for the entire network. Perform power flow calculations and security checks on the overall network topology optimization scheme; Once the verification is successful, control commands are generated and issued based on the optimized topology scheme for the entire network. Establish a historical optimization scheme library and intelligently recommend topology schemes based on the matching degree between the current operating scenario and historical scenarios.

2. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 1, characterized in that, Based on the identified structure and state, a unified topology model of the distribution network containing multiple voltage levels is constructed using graph theory, including: Bus nodes, load nodes, and distributed power supply access points of different voltage levels are represented as a unified set of nodes. Lines connecting nodes within the same voltage level, transformers connecting nodes at different voltage levels, and flexible interconnection devices connecting different voltage levels or different feeders of the same voltage level are represented as a unified set of edges. Based on the set of nodes and the set of edges, an association matrix describing the connectivity of the entire network is formed, and topological constraints that maintain the radial operation of the distribution network are defined.

3. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 2, characterized in that, Based on the operating status and rated parameters of the flexible interconnect device, determine the adjustable power transmission range, including: Calculate the current utilization rate of the flexible interconnection device based on its operating status and rated parameters; The utilization rate is defined as the ratio of the current apparent power of the flexible interconnect device to its rated capacity; A preset adjustment threshold is used to determine the adjustable power transmission range based on the ratio and the magnitude of the adjustment threshold.

4. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 3, characterized in that, The step of performing topology pre-optimization within each voltage level to obtain a pre-optimized topology scheme for each voltage level includes: Encode the state combinations of operable switches within the current voltage level into optimization variables; The fitness function is the weighted sum of the active power loss and load balance of the network at the current voltage level. A swarm intelligence optimization algorithm is used to search under the condition of satisfying radial constraints, and the combination of switching states that makes the fitness function optimal is obtained as the pre-optimized topology scheme for the current voltage level.

5. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 4, characterized in that, The collaborative optimization of the switching states and transmission power of flexible interconnect devices within each voltage level yields a network-wide optimized topology scheme, including: A two-level nested optimization structure is adopted, wherein: The outer layer optimization uses the operable switch states at all voltage levels as decision variables and employs a particle swarm optimization algorithm for optimization. For each candidate topology generated by the outer layer optimization, the inner layer optimization is initiated. Based on the overall network optimization objective function, the transmission power of each flexible interconnection device is used as a continuous decision variable, and the optimal power allocation under the topology is obtained by solving the sequential quadratic programming method. During the outer particle swarm iteration process, the globally optimal solution and its corresponding power setting value for the flexible interconnect device are recorded.

6. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 5, characterized in that, Perform power flow calculations and security checks on the overall network optimization topology scheme, including: Power flow calculations were performed using the Newton-Raphson method, with the high-voltage side busbars of each substation as the balancing nodes and all other nodes as PQ nodes or PV nodes. The transformer branch is incorporated into the Jacobian matrix through the equivalent impedance model, while the flexible interconnection device is treated as a constant power source, and the injected power is the optimized set value. The power flow equations are solved iteratively. When the voltage magnitude and phase angle correction of all nodes are less than the preset first threshold, the power flow is considered to have converged. After the power flow converges, check all constraints. If all constraints are satisfied, the safety check passes.

7. The adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in claim 6, characterized in that, Establish a historical optimization solution library, and intelligently recommend topology solutions based on the matching degree between the current operating scenario and historical scenarios, including: Record the runtime scenario characteristic data and the corresponding optimized topology scheme during historical optimizations; Clustering algorithms are used to divide historical operation scenarios into multiple typical scenario categories, and one or more preferred topology schemes are associated with each typical scenario; When optimization is required, the similarity between the current running scenario and each typical scenario is calculated; If the similarity exceeds a preset second threshold, the corresponding preferred topology scheme is directly called as the network-wide optimized topology scheme.

8. A flexible interconnection topology adaptive optimization system for multi-voltage level distribution networks, using the method described in any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire real-time operating data of multiple voltage levels in the distribution network and identify the current network topology and the operating status of each flexible interconnection device. The topology model building module is used to construct a unified topology model of a distribution network containing multiple voltage levels based on the identified structure and state using graph theory. The determination module is used to determine the adjustable power transmission range based on the operating status and rated parameters of the flexible interconnect device; The pre-optimization module is used to perform topology pre-optimization within each voltage level based on the unified topology model, with the goal of reducing network loss and balancing load, to obtain the pre-optimized topology scheme within each voltage level. The collaborative optimization module is used to take the pre-optimized topology scheme as the initial solution and reduce the overall network operation index as the objective function to collaboratively optimize the switching state and transmission power of flexible interconnection devices within each voltage level to obtain the network-wide optimized topology scheme. The verification module is used to perform power flow calculations and security verifications on the network-wide optimized topology scheme. The execution module is used to generate and issue control commands based on the network-wide optimized topology scheme after the verification is passed. The matching and recommendation module is used to build a historical optimization solution library and intelligently recommend topology solutions based on the matching degree between the current running scenario and historical scenarios.

9. A computer device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the adaptive optimization method for flexible interconnection topology of multi-voltage level distribution networks as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions, which, when executed by a processor, implement the steps of the adaptive optimization method for flexible interconnection topology of a multi-voltage level distribution network as described in any one of claims 1 to 7.

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