Power distribution network switch configuration method, device and system

Abstract

The invention discloses a power distribution network switch configuration method, device and system, and designs a power distribution network switch optimal configuration strategy considering the common influence of economic-accident reconstruction so as to solve the power supply reliability guarantee problem of a high-permeability PV access power distribution network. By adopting the technical scheme of the invention, when the automatic switch and interconnection switch configuration is carried out on the power distribution network, the system resource investment can be optimized, the operation efficiency of the system in normal and fault states can be guaranteed, and the optimal coordination of resource allocation and fault recovery capability can be realized.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network planning technology, and specifically relates to a power distribution network switch configuration method, device, and system. Background Technology

[0002] The distribution network, located at the end of the power system and directly connected to the user side, directly impacts social production and residents' daily power supply. With the increasing penetration of distributed generation (DG), the distribution network's operating topology is becoming more flexible, significantly increasing the demands on power supply reliability for residential and industrial production. Climate change is leading to an increase in the frequency and intensity of extreme natural disasters, resulting in more large-scale power outages. Therefore, there is an urgent need to develop more adaptive methods for optimizing the configuration of distribution network switches to address the reliability issues of distribution networks with high PV penetration.

[0003] With the advancement of power market reform and the continuous improvement of competition mechanisms, power companies face an urgent need to improve power supply reliability and power quality to meet the differentiated electricity requirements of various users. Improving power supply reliability can typically be achieved by reducing equipment failure rates, accelerating power outage recovery speed, and enhancing the accuracy of fault location and isolation. The application of distribution automation technology enables real-time monitoring of the distribution system's operating status and allows for rapid fault isolation and power restoration to non-faulty areas through remote control switches, effectively shortening user outage time and enhancing power supply reliability. Therefore, the type, quantity, and location of switches in the distribution network have a significant impact on its operational reliability. However, in actual operation, remote automatic switches may fail due to manufacturing defects, hardware and software malfunctions, or receiving incorrect signals. The failure rate of such switches not only weakens their role in reducing user outage time but also affects the actual effectiveness of optimized switchgear configuration schemes. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a method, apparatus, and system for configuring distribution network switches, aiming to improve the operating efficiency of the distribution network and enhance its rapid reconfiguration capability in case of faults by rationally configuring automated switches and tie switches.

[0005] To achieve the above objectives, the present invention provides the following solution: A method for configuring switches in a power distribution network, comprising: Step S1: Construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. Step S2: Based on the two-level planning framework, treat each segment branch failure as an independent scenario and classify the loads affected under different accident scenarios. Step S3: Establish a mixed-integer linear programming model for the system that comprehensively considers operational efficiency and reconfiguration performance; Step S4: Optimize and solve the mixed-integer linear programming model of the system.

[0006] Preferably, in step S1, the two-layer planning framework simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated switches and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection layer and a lower-layer simulation and operation layer. The upper layer is responsible for deciding on the site selection and type of automated switches and tie switches, and transmitting the planning scheme to the lower layer. The lower layer then simulates the system's operating state based on this planning scheme and feeds the results back to the upper layer. The upper-layer model aims to optimize the overall system resource utilization and operating efficiency, iteratively optimizing based on the feedback information from the lower layer to ultimately arrive at the optimal switch configuration scheme.

[0007] As a preferred option, in step S2, a multi-scenario accident downtime decomposition method is adopted, which treats each segment branch failure as an independent scenario and classifies the loads affected under different accident scenarios.

[0008] Preferably, in step S4, the discrete binary particle swarm optimization algorithm is applied for optimization.

[0009] The present invention also provides a power distribution network switch configuration device, comprising: The first processing module is used to construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. The second processing module is used to treat each segment branch fault as an independent scenario according to the two-layer planning framework, and to classify the loads affected under different accident scenarios. The third processing module is used to establish a mixed-integer linear programming model for the system that comprehensively considers both operational efficiency and reconfiguration performance. The fourth processing module is used to optimize and solve the mixed-integer linear programming model of the system.

[0010] As a preferred approach, the two-layer planning framework considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated switches and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection layer and a lower-layer simulation and operation layer. The upper layer is responsible for deciding on the site selection and type of automated switches and tie switches, and then transmitting the planning scheme to the lower layer. The lower layer simulates the system's operating state based on this planning scheme and feeds the results back to the upper layer. The upper-layer model aims to optimize the overall system resource utilization and operating efficiency, iteratively optimizing based on the feedback information from the lower layer to ultimately arrive at the optimal switch configuration scheme.

[0011] As a preferred approach, the second processing module adopts a multi-scenario accident downtime decomposition method, treating each segment branch failure as an independent scenario and classifying the loads affected under different accident scenarios.

[0012] As a preferred option, the fourth processing module uses the discrete binary particle swarm optimization algorithm for optimization.

[0013] The present invention also provides a power distribution network switch configuration system, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes a power distribution network switch configuration method when executed by the processor.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention constructs a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in a distribution network. The upper layer is responsible for deciding the placement scheme of automated switches and tie switches, while the lower layer optimizes system operation and performs fault recovery and reconfiguration based on the upper layer's decisions, feeding back the optimal operating results to the upper layer. Based on this, a multi-scenario outage time decomposition method is adopted, treating each segmented branch fault as an independent scenario. The affected loads under different fault scenarios are classified, and the impact of automated switches and tie switches participating in fault reconfiguration on the power supply reliability and self-healing capability of the distribution network under different switch configuration scenarios is evaluated. Secondly, a mixed-integer linear programming model considering both operating efficiency and reconfiguration performance is established to analyze the improvement effect of switch configuration on the overall operating efficiency of the distribution network. Finally, a discrete binary particle swarm optimization algorithm is applied for optimization, and the effectiveness of the proposed configuration method is verified through the IEEE 33-node system. Using the technical solution of this invention, system resource investment can be optimized when configuring automated switches and tie switches in the distribution network, ensuring the operating efficiency of the system under normal and fault conditions, and achieving optimal synergy between resource allocation and fault recovery capabilities. Attached Figure Description

[0015] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. 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.

[0016] Figure 1 This is a flowchart of the distribution network switch configuration method according to an embodiment of the present invention.

[0017] Figure 2 The operating principle and overall recovery process of automated switches and interconnecting switches; Figure 3 The locations of automated switches and tie switches obtained by solving the BPSO+ mathematical programming method; Figure 4 Topological changes during economic restructuring; Figure 5 Taking a line fault between nodes 11 and 12 as an example, the load loss scale when no automatic switch and tie switch are configured; Figure 6 Taking a line fault between nodes 11 and 12 as an example, the load loss scale is calculated when only automated switches are configured. Figure 7 Taking a line fault between nodes 11 and 12 as an example, the scale of power loss is determined by the coordinated action of the automatic switch and the tie switch. Figure 8 Examples of weighting factors that affect optical cables are typically added to the construction of automated switches. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Example 1 like Figure 1 As shown, the present invention provides a method for configuring switches in a power distribution network, comprising: Step S1: Construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. Step S1.1 In the power distribution network, switches can be mainly divided into sectionalizing switches and tie switches. Sectionalizing switches include automated switches and manual switches, while the response time of tie switches is consistent with that of automated switches. The two-layer planning framework constructed in this invention considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection and a lower-layer simulation operation. The upper layer is responsible for deciding on the site selection and type of automated and tie switches and transmitting the planning scheme to the lower layer. The lower layer simulates the system operation state based on the planning scheme and feeds back the operation results to the upper layer. The upper-layer model aims to optimize the overall resource utilization and operating efficiency of the system, and iteratively optimizes based on the feedback information from the lower layer to finally obtain the optimal switch configuration scheme. The two-layer configuration mathematical model is shown below: In equation (1), the decision variable z inv and z ope These correspond to the investment and operational levels, respectively. C inv and C ope These represent the total resource input and operating energy consumption of the system during equipment deployment and operation, respectively; the model's constraints are... G (.)and H (.) Describes the inequality and equality constraints in the investment layer; g (.)and h (.) describes the corresponding constraints of the runtime layer.

[0021] The overall investment cost of the system in step S1.2 can be expressed as: In the formula, c inv This indicates the overall configuration weighting coefficient of automatic switches and tie switches within the system. μ n , μ s c represents a 0-1 variable indicating whether the automatic switch and the interlocking switch are configured. branch This indicates the allocation weight of optical fiber communication per unit length in the resource structure. L ∑ This indicates the total length of the optical cable.

[0022] The overall operating cost of the system in step S1.3 can be expressed as: In the formula C ope C represents the overall system operating loss. ope1 C represents the system losses during economic restructuring. ope2 C represents the system loss during accident reconfiguration.ope1 This includes network loss and load shedding during the accident reconstruction process under various fault scenarios. C ope2 This includes network losses and load shedding during the economic restructuring process.

[0023] The overall operating cost of the system in step S1.4 can be expressed as: According to DL / T 390-2016 "Technical Guidelines for Planning and Design of Distribution Network Automation", fiber optic communication is commonly used for automated switches. Therefore, the construction of automated switches usually involves additional investment costs for fiber optic cables.

[0024] The generalized model for the total length of optical cable laying can be expressed as: In the formula x j,b+r , x j,b+r-i Indicates the first j The route from the starting point or a fork in the road to another fork or the end point r The 0-1 decision variables for the automatic switches on +1 branch, Δ l j,b+r-i Indicates the first j On the line from the first b + r - (i + 1) The section of the branch road was paved to the first b+ri The length of newly added optical cable on the branch line.

[0025] Step S2 employs a multi-scenario outage time decomposition method, treating each segmented branch fault as an independent scenario. The affected loads under different fault scenarios are categorized, and the impact on distribution network reliability after the involvement of automated switches and tie switches in fault reconfiguration is assessed. Step S2.1 Based on the recovery path and time characteristics of the load after a fault, the out-of-service loads can be divided into the following three categories: Category a loads are located within the fault section and require power restoration only after the fault is repaired. Their downtime is the sum of the fault location time and the fault repair time. Category b loads can be directly switched to power supply after fault isolation. Their downtime includes fault location, isolation, and circuit breaker closing waiting time. Category c loads require power restoration via tie lines after fault isolation. Their downtime composition is the same as that of Category b loads. That is: In the formula, t a , t b , t c These correspond to the downtime of load types a, b, and c, respectively. t a1 , t b1 ,t c1 This refers to the fault location time common to all types of loads. The specific composition of downtime for each type of load is as follows: Category A includes fault repair time. t a5 Class B includes fault isolation time. t b2 Waiting time for closing the circuit breaker t b4 Class C includes fault isolation time based on the link branch. t c2 and circuit breaker closing waiting time t c4 .

[0026] The mathematical model for accident reconstruction in step S2.2 is as follows: The objective function is as follows: In the formula, C ope1 The total loss from accident reconstruction. c load P represents the weighting factor for unit load loss. m,n load-loss represents the amount of load loss in the system. c line Weighting coefficient for unit network loss P ij,loss This indicates the amount of network loss.

[0027] The power flow constraints are as follows: In the formula: power is defined as flowing from the starting node to the ending node as positive, where the starting node is called the parent node and the ending node is called the child node. ∑ Pt ij ,∑ Pt jk and Pt j,DG They are respectively t Time period j The sum of active power injected into nodes, the sum of active power outflowed, and the sum of predicted active power output from all DG nodes; ∑ Qt ij ,∑ Qt jk and Qt j,DG They are respectively t Time period j The sum of reactive power injected into the node, the sum of reactive power outflowed, the sum of reactive power output of all DGs, and the reactive power provided by CB; and They are respectively j The set of all parent and child nodes of a node; ∑ r ij lt ij ,∑ x ij lt ij They are respectivelyt Time period ij The sum of active and reactive line losses; vt i represent t Time period i The squared term of the node voltage; lt ij express t Time period ij The square term of the transmission current of the line. It is worth noting that if the branch... ij When disconnected, branch power P ij , Q ij , l ij It will be restricted to 0, and at this time equation (11) will become vt i - vt i= Setting the voltage to 0, meaning forcing all unconnected branches to have equal voltage amplitudes, is clearly unreasonable. Therefore, a 0-1 variable representing the line's open / closed state is introduced. Z Furthermore, the big-M method is introduced to transform equation (11) into equation (12), which makes the DistFlow power flow constraint still highly applicable when dealing with the flexible topology transformation during the distribution network fault recovery process.

[0028] During fault recovery, the branch capacity, current, and voltage at each node must meet the following constraints: Equation (13) is the capacity constraint of the distribution network branch, Equation (14) is the current constraint of the distribution network branch, and Equation (15) is the voltage constraint of the distribution network node. U min and U max These are the lower and upper limits of the node voltage.

[0029] Considering the uncertainty of fault location, a dynamic microgrid formation method is adopted. It is assumed that the distribution network will be divided into several islands due to a fault. Some islands contain distributed generation (DG) or tie switches, while others only contain DG or sectionalizing switches and can only form islands. For the former, the island can be connected to other nodes via tie lines and reconnected to the distribution network; or they can form an independent island. Since all islands are generated by the faulty line, we consider the two nodes at the beginning and end of the faulty line as "potential" root nodes, meaning they could be a "real" root node in the reconstructed island. This invention introduces a 0-1 variable. This is used to characterize whether a "potential" root node is a "real" root node.

[0030] The radial and connectivity constraints of the fault recovery model are as follows: Equation (16) represents the virtual power flow constraint of the virtual network, in which... Ft ij In virtual networks t time, ij The virtual power flowing through the branch, v / R Let M represent the set of nodes that are not "potential" root nodes; M is a very large positive number; Equation (19) represents the first condition in the necessary and sufficient conditions for a radial structure. γ represents the total number of nodes. j,t express t The root node is always "potential". j The state, γ j,t When =1, j The node is the "true" root node, otherwise it is not; in order to avoid the existence of islands that still operate independently for a long time after maintenance is completed, equation (20) is introduced, indicating that at the last moment of the final fault repair, there is only one sub-graph in the system, that is, all islands are connected back to the distribution network.

[0031] Step S3: Establish a mixed-integer linear programming model of the system considering economic restructuring, and analyze the effect of switch configuration on the economic operation of the distribution network; The economic operation reconstruction part of this invention uses the total daily network loss of the system as the optimization target, that is: In the formula: T Indicates the total number of time periods; Δt Indicates the time interval.

[0032] The constraints need to comprehensively consider power flow constraints, network security constraints, and network topology constraints that ensure the distribution network maintains its radial and connectivity characteristics after reconfiguration. These constraints are the same as those in accident reconfiguration.

[0033] Step S4: The discrete binary particle swarm optimization algorithm is applied to solve the problem, and the effectiveness of the proposed planning method is verified through the IEEE 33-node system.

[0034] The overall framework is based on equation (1) as the overall objective. The objectives of accident reconstruction and economic reconstruction correspond to equations (8) and (21) respectively. The constraints for accident reconstruction are equations (9) to (20), while the constraints for economic reconstruction and accident reconstruction are consistent. The system model is constructed in this way. The discrete binary particle swarm optimization algorithm is used for optimization.

[0035] The rules for updating particle velocity, position, and weights are as follows: In equations (22)-(23) and They represent the firstk Particles in the next iteration i Speed ​​and position w Indicates the inertia factor. c 1 represents the individual learning factor. c 2 represents the social learning factor. r 1. r 2 represents a random number between [0, 1]. p best , g best represents the best position found by a single particle and all particles, respectively. In equation (24): w max and w min The maximum and minimum weights; k max This represents the total number of iterations. k This represents the current iteration number.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The switch configuration method that considers the coordinated optimization of operating efficiency and fault recovery significantly improves the technical rationality of the switch configuration scheme. Based on this configuration scheme, the system power supply reliability and fault recovery capability are effectively improved. (2) The planning method proposed in this invention has clear engineering applicability, can effectively control the impact range of system faults, improve the power supply recovery speed, optimize the overall system operation efficiency, and significantly improve the comprehensive resource utilization efficiency.

[0037] After optimization using the method of the present invention, the following is obtained: Figure 5 The voltage conditions shown effectively solve the problem of voltage exceeding limits, keeping the voltage within a safe range.

[0038] in, Figure 1 A site selection planning model for automated switches is presented. This model employs a two-layer optimization structure, consisting of an upper-layer planning and site selection layer for automated and tie switches, and a lower-layer active distribution network operation simulation layer. The model's objective function encompasses overall system resource input and operational energy efficiency indicators. The upper layer uses the site selection of automated and tie switches as decision variables to provide planning schemes for the lower-layer operation simulation. The lower layer performs operational simulations based on these schemes and feeds the simulation results back to the upper layer. The upper layer iteratively optimizes based on the feedback information, ultimately determining the optimal switch configuration scheme and technical implementation results.

[0039] Figure 2In the process, Phase 1: After detecting a fault, the circuit breaker quickly disconnects all downstream loads; Phase 2: The control center transmits the action command to the automatic switch via the communication network, and remotely controls the automatic switch to isolate the fault; Phase 3: After the automatic switch isolates the fault, the tie switch takes action to realize the load transfer; Phase 4: The operator operates the manual switch to isolate the fault; Phase 5: The automatic switch receives the action command and closes, reducing the scope of the fault.

[0040] Figure 3 The system's operational performance under a specific configuration of automated switches and tie switches was demonstrated. In fault scenarios, this deployment method can effectively reduce the system's load failure rate and improve power supply reliability through load transfer. Under normal operating conditions, the coordinated operation of automated switches and tie switches optimizes the system topology, reducing network losses and improving system operating efficiency.

[0041] Figure 4 The topology changes under four typical new energy fluctuation scenarios are shown in the figure below. If the topology does not change under the four scenarios, the network loss is 0.7465 pu. After the topology change, the network loss is 0.607 pu, which is a decrease of 18.687%.

[0042] Figure 5-6 Taking the fault in the line between nodes 11 and 12 as an example, if the automatic switch does not participate in the reconfiguration, the circuit breaker will open during the fault, and the entire network will lose all load during the fault. If only the automatic switch participates, the load will be lost by 0.2923 pu, and the load loss will be 23.55%.

[0043] Figure 7 The topology changes under four typical new energy fluctuation scenarios are shown in the figure below. If the automatic switch and the tie switch jointly participate in the reconfiguration, the load losses are 0.0425 pu; 0.0123 pu; 0.0468 pu; 0.0234 pu, respectively, corresponding to load loss percentages of 10.88%; 10.193%; 11.4%; and 11.5%.

[0044] Figure 8 According to DL / T 390-2016 "Technical Guidelines for Planning and Design of Distribution Network Automation", fiber optic communication is commonly used in automated switches. Therefore, the construction of automated switches usually incurs additional investment costs for fiber optic cables. If in b+ An automatic switch is configured at two locations, regardless of b , b Whether +1 is configured, the total length of the optical cable will be increased accordingly. l b+1 + l b+2 + l b+3.

[0045] Example 2 The present invention also provides a power distribution network switch configuration device, comprising: The first processing module is used to construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. The second processing module is used to treat each segment branch fault as an independent scenario according to the two-layer planning framework, and to classify the loads affected under different accident scenarios. The third processing module is used to establish a mixed-integer linear programming model for the system that comprehensively considers both operational efficiency and reconfiguration performance. The fourth processing module is used to optimize and solve the mixed-integer linear programming model of the system.

[0046] As one embodiment of the present invention, the two-layer planning framework simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated switches and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection layer and a lower-layer simulation and operation layer. The upper layer is responsible for deciding on the site selection and type selection of automated switches and tie switches, and transmitting the planning scheme to the lower layer. The lower layer simulates the system's operating state based on the planning scheme and feeds the results back to the upper layer. The upper-layer model aims to optimize the overall system resource utilization and operating efficiency, iteratively optimizing based on the feedback information from the lower layer, ultimately arriving at the optimal switch configuration scheme.

[0047] As one embodiment of the present invention, the second processing module adopts a multi-scenario accident downtime decomposition method, which treats each segment branch fault as an independent scenario and classifies the loads affected under different accident scenarios.

[0048] As one embodiment of the present invention, the fourth processing module applies the discrete binary particle swarm optimization algorithm for optimization.

[0049] Example 3 The present invention also provides a power distribution network switch configuration system, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes a power distribution network switch configuration method when executed by the processor.

[0050] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for configuring switches in a power distribution network, characterized in that, include: Step S1: Construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. Step S2: Based on the two-level planning framework, treat each segment branch failure as an independent scenario and classify the loads affected under different accident scenarios. Step S3: Establish a mixed-integer linear programming model for the system that comprehensively considers operational efficiency and reconfiguration performance; Step S4: Optimize and solve the mixed-integer linear programming model of the system.

2. The distribution network switch configuration method as described in claim 1, characterized in that, In step S1, the two-layer planning framework simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated switches and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection and a lower-layer simulation operation. The upper layer is responsible for deciding on the site selection and type selection of automated switches and tie switches, and transmitting the planning scheme to the lower layer. The lower layer simulates the system operation state based on the planning scheme and feeds back the operation results to the upper layer. The upper-layer model aims to optimize the overall resource utilization and operating efficiency of the system, and iteratively optimizes based on the feedback information from the lower layer to finally obtain the optimal scheme for switch configuration.

3. The distribution network switch configuration method as described in claim 2, characterized in that, In step S2, a multi-scenario accident outage time decomposition method is adopted, treating each segment branch fault as an independent scenario, and classifying the loads affected under different accident scenarios.

4. The distribution network switch configuration method as described in claim 3, characterized in that, In step S4, the discrete binary particle swarm optimization algorithm is applied for optimization.

5. A power distribution network switch configuration device, characterized in that, include: The first processing module is used to construct a two-layer planning framework that simultaneously considers the equipment configuration scale, operating energy consumption, and communication resource requirements of automated switches and tie switches in the distribution network. The second processing module is used to treat each segment branch fault as an independent scenario according to the two-layer planning framework, and to classify the loads affected under different accident scenarios. The third processing module is used to establish a mixed-integer linear programming model for the system that comprehensively considers both operational efficiency and reconfiguration performance. The fourth processing module is used to optimize and solve the mixed-integer linear programming model of the system.

6. The power distribution network switch configuration device as described in claim 5, characterized in that, The two-layer planning framework considers the equipment configuration scale, operating energy consumption, and communication resource requirements of both automated switches and tie switches. It adopts a hierarchical optimization structure, divided into an upper-layer planning and site selection and a lower-layer simulation operation. The upper layer is responsible for deciding on the site selection and type selection of automated switches and tie switches, and transmitting the planning scheme to the lower layer. The lower layer simulates the system operation state based on the planning scheme and feeds back the operation results to the upper layer. The upper-layer model aims to optimize the overall system resource utilization and operating efficiency, and iteratively optimizes based on the feedback information from the lower layer to finally obtain the optimal scheme for switch configuration.

7. The power distribution network switch configuration device as described in claim 6, characterized in that, The second processing module adopts a multi-scenario accident downtime decomposition method, treating each segment branch failure as an independent scenario and classifying the loads affected under different accident scenarios.

8. The power distribution network switch configuration device as described in claim 7, characterized in that, The fourth processing module uses the discrete binary particle swarm optimization algorithm for optimization.

9. A power distribution network switch configuration system, characterized in that, include: A memory and a processor, wherein the memory stores a computer program executed by the processor, the computer program performing the power distribution network switch configuration method as described in any one of claims 1-4 when executed by the processor.

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