A method and system for multi-objective online rolling reconfiguration of power distribution networks

Abstract

This invention belongs to the field of distribution network dispatching technology, specifically relating to a multi-objective online rolling reconfiguration method and system for distribution networks. The method includes: introducing a rolling time-domain mechanism to construct an online dynamic reconfiguration framework for distribution networks that considers equipment dead-zone constraints; constructing a directed graph of the vertical voltage support topology based on branch reactive power voltage sensitivity and the online dynamic reconfiguration framework; resolving the voltage support strength to the branch level based on the constructed directed graph to obtain a local targeted dimensionality reduction mechanism based on voltage support topology early warning; calculating the equivalent support strength of nodes based on the local targeted dimensionality reduction mechanism; constructing a multi-objective online rolling reconfiguration model considering the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost, and reactive power compensation action cost; and performing coordinated optimization of distribution network voltage level and voltage support capability based on the constructed multi-objective online rolling reconfiguration model to complete the multi-objective online rolling reconfiguration of the distribution network.

Description

Technical Field

[0001] This invention belongs to the field of distribution network dispatching technology, specifically relating to a method and system for multi-objective online rolling reconfiguration of distribution networks. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] The penetration rate of distributed photovoltaic (PV) power in distribution networks is increasing. The high proportion of PV installations alters the traditional unidirectional power flow characteristics of distribution networks. Frequent changes in the source-load states of nodes exacerbate the uncertainty of distribution system operation, leading to frequent local voltage exceedances and insufficient support capacity. Traditional voltage mitigation methods largely rely on static reactive power compensation devices, which are costly and difficult to flexibly address time-varying disturbances across the entire network. Distribution network reconfiguration optimizes network topology by changing the on / off states of tie switches and sectionalizing switches, directly improving voltage distribution at the network structure level.

[0004] The randomness and uncertainty of photovoltaic power output place extremely high demands on the timeliness of grid regulation, and distribution network reconfiguration is gradually evolving towards online closed-loop control. Distribution network reconfiguration is essentially a high-dimensional mixed-integer nonlinear programming (MINLP) problem, with candidate topology combinations growing exponentially. How to reduce the dimensionality and improve the solution efficiency from a massive number of topologies, while ensuring that the reconfigured grid has a good voltage level and voltage support capability, is an urgent problem to be solved. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a multi-objective online rolling reconfiguration method and system for distribution networks. It employs an online local dimensionality reduction reconfiguration strategy based on voltage support topology analysis and early warning, introduces a rolling time-domain mechanism, and constructs an online dynamic reconfiguration framework that considers equipment dead-zone constraints. A directed graph of the vertical voltage support topology is built based on branch reactive power-voltage sensitivity, and a local targeted dimensionality reduction and optimal loop-solving method for weak areas is proposed. Taking into account node equivalent support strength KRPVS, voltage deviation, active power loss, and the cost of switching and reactive power compensation actions, a multi-objective online rolling reconfiguration model is established to achieve synergistic optimization of voltage level and voltage support capability. This effectively compresses the reconfiguration decision space, quickly locates and reassembles weak voltage support paths, and significantly improves the system's voltage safety level and disturbance resistance robustness under both normal and extreme time-varying conditions.

[0006] According to some embodiments, the first aspect of the present invention provides a multi-objective online rolling reconfiguration method for distribution networks, employing the following technical solution: A multi-objective online rolling reconfiguration method for distribution networks includes: A rolling time-domain mechanism is introduced to construct an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions; Based on the reactive voltage sensitivity of branches and the online dynamic reconfiguration framework of distribution networks, a directed graph of vertical voltage support topology is constructed. According to the constructed directed graph, the voltage support strength is analyzed to the branch level, and a local targeted dimensionality reduction mechanism based on voltage support topology early warning is obtained. Based on the local targeted dimensionality reduction mechanism, calculate the equivalent support strength of the nodes; Considering the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost, and reactive power compensation action cost, a multi-objective online rolling reconfiguration model is constructed. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner, and the multi-objective online rolling reconfiguration of the distribution network is completed.

[0007] As a further technical limitation, the equipment operation dead zone constraint includes the following: within the operation dead zone time window, the already operated tie switch or parallel capacitor bank shall not undergo state reversal again; the number of tie switches and parallel capacitor banks allowed to operate within a single decision window shall not exceed the set maximum value; and the total number of times a single tie switch or parallel capacitor bank is allowed to operate within the total simulation cycle shall not exceed the set maximum value.

[0008] As a further technical limitation, the local targeted dimensionality reduction mechanism includes: Automatic identification of weak voltage support nodes based on branch reactive voltage sensitivity threshold; Using the shortest path optimization mechanism, we search for alternative interconnection switches in the global interconnection switch set that can quickly connect weak nodes to the high-voltage support area; Close the alternative contact switch to form a temporary loop, and disconnect the branch with the lowest reactive voltage sensitivity value in the loop to complete the loop unblocking.

[0009] As a further technical limitation, in the process of constructing the directed graph of the vertical voltage support topology, a propagation direction indicator variable is introduced based on the reactive power-voltage sensitivity of the branch. The undirected distribution network is mapped into a directed graph according to the reactive power incremental response. Nodes represent the grid bus and directed edges represent the directional propagation path of reactive power support capability.

[0010] As a further technical limitation, the objective function of the multi-objective online rolling reconfiguration model is the weighted sum of various operational indicators within the look-ahead time window. These operational indicators include at least the steady-state voltage soft constraint deviation sub-objective, the active power loss economy sub-objective, the node voltage support strength sub-objective, the line switching equipment operation cost sub-objective, the discrete reactive power equipment operation cost sub-objective, and the operating parameter over-limit penalty sub-objective. Among them, the steady-state voltage soft constraint deviation sub-objective adopts a soft constraint-based quadratic penalty mechanism, introducing a penalty term when the node voltage is lower than the safety lower limit, guiding the reconfiguration strategy to converge towards the direction of the shallowest voltage drop. The node voltage support strength sub-objective aims to maximize the minimum equivalent support strength of nodes in the weak region.

[0011] As a further technical constraint, when the node voltage approaches the lower limit of safety, the absolute voltage level is increased first to eliminate the risk of exceeding the limit; when the node voltage is in the safe range but the support strength is insufficient, the voltage operating margin is allowed to be slightly released on the premise of ensuring that no limit is exceeded, and the overall voltage support capacity is improved by topology reconfiguration; under ideal operating conditions, voltage distribution and voltage support strength are optimized at the same time; and the online rolling reconfiguration of multiple objectives of the distribution network is completed.

[0012] According to some embodiments, the second aspect of the present invention provides a multi-objective online rolling reconfiguration system for a distribution network, employing the following technical solution: A multi-objective online rolling reconfiguration system for a distribution network, comprising: The module is configured to introduce a rolling time-domain mechanism to build an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions. The analysis module is configured to construct a directed graph of the vertical voltage support topology based on the branch reactive voltage sensitivity and the online dynamic reconfiguration framework of the distribution network. Based on the constructed directed graph, the voltage support strength is analyzed to the branch level, resulting in a local targeted dimensionality reduction mechanism based on voltage support topology early warning. The calculation module is configured to calculate the equivalent support strength of the nodes according to the local targeted dimensionality reduction mechanism; The optimization module is configured to consider the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost and reactive power compensation action cost to construct a multi-objective online rolling reconfiguration model. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner to complete the multi-objective online rolling reconfiguration of the distribution network.

[0013] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium, employing the following technical solution: A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the multi-objective online rolling reconfiguration method for distribution networks as described in the first aspect of the present invention.

[0014] According to some embodiments, the fourth aspect of the present invention provides an electronic device, which adopts the following technical solution: An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps in the multi-objective online rolling reconfiguration method for distribution networks as described in the first aspect of the present invention.

[0015] According to some embodiments, the fifth aspect of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software code, wherein the program in the software code performs the steps in the multi-objective online rolling reconfiguration method for distribution networks as described in the first aspect of the present invention.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention aims to synergistically improve topology dimensionality reduction and voltage support capability. It comprehensively considers voltage level and voltage support capability to perform multi-objective online rolling reconstruction of the distribution network. From the perspective of reactive power sensitivity transmission path, it synergistically achieves physical targeted dimensionality reduction and improves the overall system safety and robustness. Guided by voltage early warning information and using the RPVS threshold as a criterion, based on sensitivity propagation theory, the downstream area of ​​weak branches in the vertical voltage support topology is directly identified as a weak support area. Only the tie switches around the weak area are closed to construct a temporary power supply loop. Using sensitivity propagation theory, the conventional branch with the smallest RPVS value in the loop is precisely disconnected to quickly restore the radial operation of the power grid. It directly locks the physical weak area and actively strips away the strong support network structure. By pruning a massive number of invalid topology branches, it achieves a leap from pure mathematical dimensionality reduction to dynamic electrical targeted dimensionality reduction, and the reconstruction decision time is compressed to the second level.

[0017] To respond to subsequent photovoltaic timing fluctuations and avoid the dimensionality curse of long-term forecasts, this embodiment introduces a forward-looking time window to acquire characteristic data in real time from current and predicted power flow sections, and decides on a comprehensive reconfiguration scheme. This embodiment addresses the spatiotemporal imbalance of source and load in the actual distribution system by designing an adaptive optimization mechanism based on a dynamic trade-off between operating margin and safety boundary. When node voltage approaches the safety lower limit, the absolute voltage level is prioritized to eliminate the risk of exceeding the limit. When the voltage level is within the safe range but the support strength is insufficient, a small release of the voltage operating margin is allowed, under the premise of ensuring safety without exceeding the limit, to achieve a significant leap in overall voltage support capacity through topology reconfiguration. Under ideal operating conditions, it seeks synergistic optimization of voltage distribution and support strength; taking into account both the current operating state and future predicted trends, it proactively enhances the robustness of the grid in responding to subsequent high-frequency power fluctuations. Attached Figure Description

[0018] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0019] Figure 1 This is a flowchart of the online rolling reconfiguration method for multi-objective distribution networks in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of a local dimensionality reduction optimization strategy for voltage support topology early warning in the location of voltage support weak regions in Embodiment 1 of the present invention. Figure 3 This is a schematic diagram of the local dimensionality reduction optimization strategy for voltage support topology early warning based on tie line closure and temporary ring network construction in Embodiment 1 of the present invention. Figure 4 This is a schematic diagram of the local dimensionality reduction optimization strategy for voltage support topology early warning based on the optimal loop-breaking strategy of branch RPVS in Embodiment 1 of the present invention. Figure 5 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 7 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 8 This is a comparison chart of the lowest voltage amplitude before and after reconstruction in Scenario 1 of Embodiment 1 of the present invention; Figure 9 This is a comparison chart of the lowest KRPVS before and after reconstruction in Scenario 1 of Embodiment 1 of the present invention; Figure 10 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 11 This is a schematic diagram of a simple function graph with units on the A5 horizontal and vertical axes in Embodiment 1 of the present invention; Figure 12 This is a comparison chart of the lowest voltage amplitude before and after reconstruction in Scenario 2 of Embodiment 1 of the present invention; Figure 13 This is a comparison chart of the lowest KRPVS before and after reconstruction in Scenario 2 of Embodiment 1 of the present invention; Figure 14 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 15 This is a schematic diagram of a simple function graph with units on the horizontal and vertical axes in Embodiment 1 of the present invention; Figure 16This is a comparison chart of the lowest voltage amplitude before and after reconstruction in Scenario 2 of Embodiment 1 of the present invention; Figure 17 This is a comparison chart of the lowest KRPVS before and after reconstruction in Scenario 3 of Embodiment 1 of the present invention; Figure 18 This is a structural block diagram of the multi-objective online rolling reconfiguration system for power distribution networks in Embodiment 2 of the present invention. Detailed Implementation

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] In this invention, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used only to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any component or element in this invention. They should not be construed as limiting the invention.

[0024] In this invention, terms such as "fixed connection," "connected," and "linked" should be interpreted broadly, indicating a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can determine the specific meaning of these terms in this invention based on the specific circumstances, and they should not be construed as limitations on the invention.

[0025] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0026] Example 1 Embodiment 1 of this invention introduces a multi-objective online rolling reconfiguration method for power distribution networks.

[0027] like Figure 1 The method for multi-objective online rolling reconfiguration of a distribution network, as shown, includes: A rolling time-domain mechanism is introduced to construct an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions; Based on the reactive voltage sensitivity of branches and the online dynamic reconfiguration framework of distribution networks, a directed graph of vertical voltage support topology is constructed. According to the constructed directed graph, the voltage support strength is analyzed to the branch level, and a local targeted dimensionality reduction mechanism based on voltage support topology early warning is obtained. Based on the local targeted dimensionality reduction mechanism, calculate the equivalent support strength of the nodes; Considering the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost, and reactive power compensation action cost, a multi-objective online rolling reconfiguration model is constructed. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner, and the multi-objective online rolling reconfiguration of the distribution network is completed.

[0028] This embodiment presents an online local dimensionality reduction and reconfiguration strategy for distribution networks based on voltage support topology analysis and early warning. A rolling time-domain mechanism is introduced to construct an online dynamic reconfiguration framework that considers equipment dead-zone constraints, thereby improving the foresight and engineering feasibility of reconfiguration decisions. A directed graph of the longitudinal voltage support topology is constructed based on branch reactive power-voltage sensitivity, revealing the propagation law of series attenuation and parallel accumulation of voltage support strength along the propagation path. Based on this, a local targeted dimensionality reduction and optimal loop-solving method for weak areas is proposed. Taking into account node equivalent support strength KRPVS, voltage deviation, active power loss, and the cost of switching and reactive power compensation actions, a multi-objective online rolling reconfiguration model is established to achieve synergistic optimization of voltage level and voltage support capability. This embodiment introduces the Rolling Horizon (RH) mechanism from Model Predictive Control (MPC) to construct an online dynamic reconfiguration framework for the distribution network. The core idea of ​​online dynamic reconfiguration is to achieve temporal coupling of operating states across multiple time periods; its essence lies in overcoming the static limitations of a single section, enabling the current reconfiguration action to take into account the system's operational requirements in the future prediction time domain.

[0029] Define discrete time series as ;in, This represents the total time period within the simulation cycle, with a resolution of 15 minutes.

[0030] This embodiment is set For the forward-looking time window, online dynamic reconstruction needs to be based on forward-looking forecast data, at any given time. t Solve and provide the optimal switching decision that not only satisfies the constraints of the current time segment, but also continuously satisfies them. t to t + Hp -1 Control the system's operating standards within the time domain to effectively address the uncertainties in subsequent photovoltaic output.

[0031] In the online dynamic restructuring decision-making framework, the forward-looking time domain H p The value of directly determines the robustness and economy of the reconstruction strategy. To balance a forward-looking response to subsequent photovoltaic time-series fluctuations with avoiding a decrease in long-term prediction accuracy and the curse of model dimensionality, this embodiment sets... Define the dead time of the action. for .

[0032] The deadband constraint is as follows: ; ; in, This refers to the state change of tie switches in the distribution network; Let be the state change of CB.

[0033] The model for determining whether the switching of the interconnecting switch and the parallel capacitor bank (CB) has been activated is as follows: ; ; ; ; in, It is the set of all controllable switches in the power distribution network; For CB access node set; This is the index of the controllable switches in the system; This is the moment for making a decision regarding the current restructuring action; For switch At any moment The opening / closing state parameter, a value of 0 indicates that the switch... At any moment When in the off state, a value of 1 indicates a switch. At any moment It is in a closed state; For nodes The CB connected The number of groups involved at any given time; This refers to the time step parameter within the action dead zone.

[0034] If switch k At any moment t Make the action, then To ensure the constraint equation holds, the summation term must be strictly zero, meaning the switch must be active within the dead zone. k No further action will occur; similarly, if the capacitor i At any moment t Make the action, then To ensure that the constraint equation holds, the summation term must be strictly 0, meaning that CB is absolutely not allowed to reverse state again within the action dead zone.

[0035] To prevent power flow transient security issues caused by excessive topology reconfiguration, this paper limits the maximum values ​​of the tie switches and CBs allowed to undergo state reversal within a single decision window as follows: ; ; in, This represents the maximum number of handshake switches that are allowed to undergo state reversal within a single decision window; This represents the maximum number of CBs allowed to undergo state reversal within a single decision window.

[0036] At the same time, the maximum values ​​of the tie switches and CBs that are allowed to undergo state reversal within the total simulation cycle are strictly limited as follows: ; ; in, This is the maximum number of tie switches allowed to undergo state reversal within the total simulation runtime window; This is the maximum number of CBs allowed to undergo state reversal within the total simulation runtime window.

[0037] In the solution of distribution network reconfiguration, the number of candidate topology combinations increases exponentially with the expansion of network node size. This embodiment proposes a local targeted dimensionality reduction mechanism based on voltage support topology early warning. This mechanism directly locks the weak voltage support area and realizes a dynamic electrical local dimensionality reduction optimization strategy.

[0038] Based on the reduced-order derivation of the Jacobian matrix of nonlinear AC power flow under the active power balance condition, the reactive voltage support strength (RPVS) index of a single branch can be expressed as: ; in: ; ; ; ; in, For a momentt branch road ( i , j The voltage support strength of a branch is its physical meaning. i , j The sensitivity of the reactive power transmitted on the receiving end node to the voltage. and For a moment t branch road ( i , j The voltage amplitude at both ends of the node; For a moment t branch road ( i , j The phase angle difference between the two endpoints; For branch roads ( i , j The absolute value of the conductivity; For branch roads ( i , j The absolute value of susceptance.

[0039] Because active power distribution networks exhibit bidirectional reactive power flow under time-varying conditions, it is necessary to further separate the actual reactive power sources and supported nodes within the system. To this end, a propagation direction indicator variable for RPVS is introduced. ,Right now .

[0040] Based on the actual reactive power incremental response The analytical model that strictly maps an undirected distribution network to a directed graph with a vertical voltage-supported topology is as follows: ; in, For a moment t branch road ( i , j The voltage-supported propagation direction indicator variable, The equivalent reactive power support strength of the entire network is represented by the nodes. Propagate in a single direction to the node ; For a moment The set of branches in a closed conducting state within the system; The set of voltage support sources defined for the system, namely the photovoltaic nodes in PV operation state; This represents the slight increase in reactive power generated by the branch before and after the disturbance.

[0041] Based on the directed graph, the transmission path of reactive power regulation from the supporting source node to the supported node is nothing more than series and parallel. In this embodiment, the voltage support strength is analyzed to the branch level, and the transmission law of the series and parallel connection of branch RPVS is analyzed to affect the voltage support strength of the node. Thus, the branches with greater influence on the voltage support capacity transmission line can be quickly and directly obtained, and the weak areas of voltage support can be located. Then, the tie line is closed and a temporary loop network is formed. Finally, the loop-breaking strategy is determined through the branch RPVS.

[0042] This embodiment utilizes the derived equivalent formula for RPVS series and parallel connections to calculate the equivalent connection from the supporting source node to the supported source node. K RPVS : ; ; in, and For nodes and nodes The equivalent voltage support strength of the propagation path from the support source to the supported source under a voltage-supported topology; For branch roads ( i , j Voltage support strength; upstream node of Along the side road ( i , j Propagation to nodes The single-path equivalent voltage support strength afterward; To point to a node in the voltage support topology diagram j The set of all parent nodes.

[0043] The propagation law of voltage support strength: The comprehensive voltage support strength of the upstream node, after passing through the physical branch ( i , j When transmitted downstream, it exhibits a series attenuation pattern, while the target node... If there are multiple upstream feed paths, the total support strength they acquire is accumulated in parallel.

[0044] like Figure 2As shown, based on the set RPVS threshold, in a radial distribution network, the voltage support capability attenuation of node 5 originates from the weakest RPVS branch on the transmission path between node 5 and the supporting source node 1, i.e., branch L4 severely restricts node 5's ability to obtain voltage support. Furthermore, the electrical distance between the supporting source and the supported source is also a significant factor in the propagation attenuation of voltage support capability, and node 5 happens to be located at the very end of the voltage support topology. Therefore, this embodiment targets node 5 and utilizes the shortest path optimization mechanism to search for alternative tie switches in the global tie switch set that can quickly connect node 5 to the surrounding high-voltage support area. Only L5 meets the requirements. The physical essence of this step is to quickly construct a low-impedance reactive power support path for the weak node among numerous candidate tie switches, i.e., directly connecting node 5 to the photovoltaic system of node 6 via L5, which can greatly improve the voltage support capability of node 5.

[0045] like Figure 3 As shown, after determining L5 as the alternative tie switch, its state is set to closed in the network topology matrix. At this time, the local distribution network structure changes from a standard radial tree structure to a temporary loop containing the weak node 5. (L4-L5-L6-L7). To meet the topology constraints and relay protection setting requirements of the radial operation of the distribution network, the system must disconnect L4 in this loop to achieve loop disconnection. This process aligns with the seamless switching engineering practice of the distribution network relay protection system, which prioritizes closing before opening, and can effectively avoid load outages during topology reconfiguration.

[0046] Traditional loop-breaking strategies often rely on repeated power flow calculations, which incur significant computational overhead. For example... Figure 4 As shown, this embodiment addresses the generated temporary loop. The RPVS of each branch within the loop is extracted sequentially, and the branch with the greatest impact on voltage support propagation is disconnected. In selecting the disconnection path, while considering branches with low RPVS, it is also necessary to avoid excessively long voltage support propagation paths within the system after reconstruction, in order to maximize the preservation of the overall voltage support capability of the system after loop de-circuiting. In this embodiment, disconnecting L4 is the optimal decision.

[0047] To overcome the limitations of a single economic objective, this embodiment introduces node equivalence, taking into account operational indicators such as voltage deviation, active power loss, switching action penalty cost, and voltage over-limit penalty cost. K RPVS As an evaluation indicator of topology support capability, a multi-objective dynamic reconfiguration strategy model for distribution networks was constructed. This model aims to balance the costs and benefits of reconfiguration actions, guiding the algorithm to prioritize the reconfiguration of voltage support paths in weak areas.

[0048] Overall objective function F Defined as a forward-looking time window The weighted sum of all internal operating indicators: ; in, , , , , and These are the weight coefficients for each sub-function; the specific mathematical model of the sub-objective function is as follows: (1) Steady-state voltage soft constraint deviation sub-target

[0049] Traditional voltage limit handling methods often employ hard constraints, but these can easily lead to an empty solution space under extreme time-varying conditions. To overcome this limitation, this model constructs a secondary penalty mechanism based on soft constraints: ;in, It is the set of all nodes in the distribution network; Represents a node i At any moment t The steady-state voltage per unit value; This is a hard boundary for the lower limit of the system voltage. This represents the lowest steady-state voltage per unit value measured across the entire network under the current candidate topology.

[0050] This penalty mechanism enables the dynamic reconstruction strategy to converge in the direction of minimizing the total penalty value, thereby determining the optimal solution with the shallowest fall.

[0051] (2) Economic sub-objective function of active power network loss , ;in, It is the set of all branches in the distribution network; In order to exchange trend data, at any time Injecting branches from the first node The active power; In order to exchange trend data, at any time Branches flowing out from the end node The active power.

[0052] (3) Sub-target of nodal voltage support strength

[0053] Introducing the equivalent support strength of nodes This is used to quantify the dynamic disturbance rejection capability of a local distribution network. The sub-objective aims to maximize the disturbance rejection capability of the weakest node within a voltage-supported weak area. ;in, This is the set of weak nodes identified by a voltage-supported topology visualization analysis and early warning mechanism. For nodes At any moment The equivalent voltage support strength.

[0054] (4) Sub-target of operating cost of line switchgear ,Right now ; (5) Sub-objective of discrete reactive power equipment operation cost ,Right now ; (6) Penalty sub-target for exceeding runtime parameter limits ,Right now ;in, For a moment Flowing through the branch road The current amplitude; The maximum allowable thermal stability current carrying capacity of the branch circuit; ,in, In order to exchange trend data, at any time Injecting branches from the first node reactive power; branch road The first node at time The voltage amplitude; This is the system's baseline capacity.

[0055] Taking into account the AC power flow balance constraints of reactive power coordination, i.e. ; ; in, and For nodes The location is supported by a voltage source At any moment Injected active and reactive power; For nodes At any moment Actual reactive load; This is the reactive power compensation step size for a single CB group.

[0056] In high-proportion photovoltaic (PV) distribution networks, the reactive power support capacity of PV inverters is not unlimited, but strictly limited by their own hardware capacity. To accurately reflect the true voltage regulation capability of PV, this embodiment constructs a reactive power output constraint for PV inverters, namely... ;in, For photovoltaic inverters The rated apparent capacity.

[0057] Considering that CB cannot be continuously and smoothly adjusted in actual engineering, this embodiment imposes strict constraints on the discrete input steps and capacity boundaries of the reactive power compensation equipment to ensure the feasibility of the decision-making scheme. ;in, The maximum number of CB groups allowed to be physically installed on this node; It is a set of integers.

[0058] To simplify relay protection settings and avoid network circulating currents, the distribution network must restore and maintain its tree-like radial structure after a reconfiguration switching operation. This is to ensure that the distribution network topology generated at any given time meets this fundamental requirement. .

[0059] Case Analysis To verify the design and implementation details proposed in this embodiment K RPVS To assess the effectiveness and rationality of the multi-objective dynamic reconstruction strategy, this embodiment establishes a system as follows: Figure 5 The improved IEEE 33-node distribution network simulation system shown was tested. The simulation time was from 7:00 to 18:00, with a time resolution of 15 minutes. The system was connected to 3 photovoltaic and 1 static var generator (STATCOM), and CBs were configured at 3 different nodes, with two sets configured at each node. The connection locations and capacities are shown in Table 1.

[0060] Table 1. Access Nodes and Capacity Configuration for Voltage Support Equipment

[0061] This embodiment constructs an uncertain spatiotemporal heterogeneous load evolution model that takes into account prediction errors. Gaussian white noise with a standard deviation of 0.05 is superimposed on the baseline heavy load expectation value to simulate the random oscillation disturbance of about 5% of the actual load.

[0062] The parameter values ​​are shown in Table 2, i.e. Table 2 Parameter Values

[0063] The photovoltaic power factor and load fluctuation coefficient are shown in Tables 3 and 4, respectively. Table 3 Photovoltaic Power Factor

[0064] Table 4 Load Fluctuation Coefficient

[0065] Furthermore, in real power distribution networks, there is a significant imbalance in electrical load both in time and space. Therefore, based on the basic IEEE 33-node power distribution network load parameters and a unified load fluctuation curve across the entire network, the following scenario is constructed: Scenario 1: From 7:00 to 11:00, the load of nodes 17 and 18 is amplified by 6 times to create the morning peak electricity consumption. Scenario 2: From 12:00 to 14:00, the load of nodes 21 and 22 is amplified by 8 times to create the midday peak electricity consumption. Scenario 3: From 15:00 to 18:00, the loads of nodes 24, 25, 32 and 33 are amplified by 5 times to create the evening peak electricity consumption.

[0066] The actions of CB during the total simulation cycle are shown in Table 5. Table 5. CB Action Details During the Simulation Period

[0067] To verify the effectiveness of the proposed voltage support topology analysis and early warning strategy for distribution networks in improving node voltage levels and voltage support levels, we take Scenario 1 at 7:00 AM as an example. At this time, the system is in the early morning peak electricity consumption phase. Nodes 17 and 18, located at the end of the feeder, experience a sudden increase in load of 6 times. Simultaneously, the sun is rising, photovoltaic output is extremely low, and the power factor is only 0.05. The voltage support topology before and after reconstruction is as follows: Figure 6 and Figure 7 As shown, the system's minimum voltage and minimum [voltage] during the online rolling look-ahead time before and after the reconfiguration are [data missing]. K RPVS Each as Figure 8 and Figure 9 As shown.

[0068] Depend on Figure 8 and Figure 6 It can be seen that, under the original topology, the steady-state voltage of node 18 has dropped to approximately 0.93 pu during the look-ahead window period of 7:00-9:00, exceeding the set safety boundary of 0.95 pu. Combined with... Figure 12 It can be seen that the lowest in this area K RPVSThe voltage level is only around 1.55; this low voltage level combined with low support strength creates a vulnerability in the current voltage support topology of the system. Faced with this extremely vulnerable area, the local dimensionality reduction optimization strategy proposed in this embodiment accurately identifies the weak propagation chain where node 18 is located and quickly generates a targeted improvement strategy: closing the tie switch L36 and opening the sectionalizing switch L14. From the perspective of the voltage support reactive power-sensitivity propagation mechanism, this action directly transfers the heavy load node 18 across regions to node 33, which has a shorter electrical distance and relatively better support margin, thereby reshaping the original weak voltage support propagation path.

[0069] Depend on Figure 7 , Figure 8 and Figure 9 It can be seen that after the reconfiguration strategy is executed, the lowest voltage of the entire network is instantly raised to a safe high level of about 0.978 pu; at the same time, the lowest KRPVS also jumps from 1.55 to above 2.45; in addition, as shown in Table 5, reactive power coordination instructions are added at 7:45 and 8:00 respectively: maintain the current topology and put a set of CBs into operation at node 22 and node 18 respectively.

[0070] The strategy of online dynamic reconfiguration and reactive power resource coordination adopted in this embodiment demonstrates that when facing security boundary threats, it is possible to prioritize the coordinated improvement of system voltage level and voltage support strength.

[0071] To verify the effectiveness of the reconfiguration strategy proposed in this embodiment in synergistically improving voltage level risk mitigation and support strength, a scenario was conducted at 13:00 in time (Scenario 2), during which the system experienced a midday power consumption peak. The voltage support topology before and after reconfiguration is shown below. Figure 10 and Figure 11 As shown, the system minimum voltage and minimum KRPVS before and after the online rolling look-ahead time are respectively as follows: Figure 12 and Figure 13 As shown.

[0072] Depend on Figure 12It is evident that if the original topology before reconfiguration is maintained, the system can still operate at time 13:00; however, as time progresses to time 15:00, due to extremely heavy load and the photovoltaic reactive power capacity nearing its limit, the original topology can no longer maintain power flow convergence, leading to a complete local voltage collapse, i.e., data loss occurs at 15:00. If a traditional single-section static reconfiguration is adopted, the system is highly likely to make incorrect decisions at time 13:00 because the current voltage has not exceeded the limit, making it unable to cope with the impending voltage collapse crisis. The rolling time-domain look-ahead mechanism of the strategy proposed in this paper, based on predicted data, warns of an impending system collapse. At time 13:00, the system outputs a reconfiguration action: closing tie line L23 and simultaneously disconnecting branch L37. From the perspective of sensitivity propagation mechanism, disconnecting the low RPVS L37 effectively avoids the series propagation attenuation effect on voltage support; while closing L23, under the premise of ensuring safety and preventing current limit exceedances, actively directs the reactive power regulation capability of the strong support source to the heavily loaded areas of nodes 21 and 22. Figure 10 and Figure 11 This action successfully reshaped the reactive power transmission path.

[0073] Depend on Figure 12 As can be seen, this strategy successfully reversed the system crash situation, forcibly boosting the node voltage, which was originally diverging and about to collapse at 15:00, to around 0.93 pu, achieving a significant voltage recovery and boost. Simultaneously, combined with... Figure 13 The lowest reconstructed K RPVS The voltage level remained stable at a relatively high level of 3.71. This indicates that during this phase, the strategy allowed for a slight release of the current healthy voltage operating margin in exchange for a significant increase in overall voltage support capacity. It balanced the current operating status with future projected trends, proactively enhancing the grid's robustness in responding to subsequent fluctuations.

[0074] It is worth noting that although the reconstructed voltage level is still slightly below the safety threshold of 0.95 pu, under the physical constraints of the limited discrete reactive power compensation capacity and topology adjustment space of the current distribution network, this is the optimal control decision that this strategy can achieve. The results of this example objectively demonstrate that under the impact of extreme spatiotemporal unbalanced loads, online topology reconstructing and discrete CB reactive power support alone have reached the physical limit of voltage increase in this region. To further eliminate the residual risk of exceeding the limit, it is necessary to promptly coordinate with the superior dispatch center or on-site maintenance personnel and take higher-level comprehensive intervention measures such as cross-regional active power allocation, emergency discharge of energy storage, or demand-side management.

[0075] To verify the effectiveness of the reconfiguration strategy proposed in this embodiment in terms of voltage margin transfer and voltage support capability improvement in the face of extreme collapse warning, taking 17:00 in scenario 3 as an example, the system ushered in the evening peak electricity consumption. At this time, the loads of nodes 24, 25, 32 and 33 faced heavy loads, and the photovoltaic output rapidly decreased, and the global reactive power reserve of the system faced a great test.

[0076] The voltage support topology before and after reconstruction is as follows: Figure 14 and Figure 15 As shown, the system's minimum voltage and minimum [voltage] during the online rolling look-ahead time before and after the reconfiguration are [data missing]. K RPVS Each as Figure 16 and Figure 17 As shown.

[0077] Depend on Figure 14 and Figure 16 It is evident that if the original topology remains unchanged, at the future time of 19:00, the system's minimum voltage will experience a precipitous drop, falling to approximately 0.75 pu, triggering severe system instability. Facing this potential crisis, the strategy implemented an extremely decisive spatiotemporal reconfiguration strategy. At 17:00, the system output a reconfiguration action command: closing branch L14 and simultaneously disconnecting branch L31; and immediately following at 17:15, an additional reactive power coordination command was added: activating a set of CBs at node 33. From the voltage support topology analysis, the disconnection of branch L31 stripped away the low reactive voltage sensitivity propagation path of RPVS, while the closure of L14 reconfigured the strong voltage support propagation path of the system's main feeder.

[0078] Depend on Figure 15 and Figure 16 It is evident that the system made an unconventional cross-period reconstruction decision at 17:00: it proactively abandoned the safe operating state of 0.96 pu in the current period and accepted the over-limit voltage of approximately 0.89 pu after reconstruction.

[0079] Given that the system's safe operating voltage limit is 0.95 pu, this reverse degradation action has clearly exceeded the safety boundary. However, this is precisely the advantage of the soft constraint penalty mechanism and intertemporal multi-objective reconfiguration proposed in this paper. The strategy, based on a look-ahead mechanism using predicted data, assesses that if the current steady-state safety is maintained, the weakness of the voltage-supported topology will inevitably lead to an extremely low voltage level of 0.75 pu at time 19:00. Combined with... Figure 17It is evident that although node 10 maintains a relatively high voltage level during the system simulation period, its voltage support capability is weak. This means that, under the current structure, the system has exhausted its capacity to maintain a high voltage level at node 10, making it highly susceptible to severe voltage exceedances when facing load fluctuations. Therefore, the system adopts a strategy of sacrificing the current voltage level to enhance voltage support capability, reconstructing a topology with stronger voltage support, and minimizing the minimum voltage level. K RPVS The voltage was raised from approximately 1.8 to a relatively high level of 3.1. Simultaneously, the lowest node voltage at time 19:00 was increased from 0.75 pu to 0.82 pu. This demonstrates that the dynamic reconfiguration of the section at time 17:00 was a highly forward-thinking online reconfiguration strategy. Currently, by reducing voltage and increasing... K RPVS The construction of a strong voltage support topology can prevent future voltage overshoots; this fully demonstrates that the multi-objective reconfiguration strategy of this embodiment, which takes into account both enhanced voltage support capability and improved voltage level, has the overall planning capability to cope with the extreme time-varying blind spots of a high proportion of photovoltaic distribution networks.

[0080] This embodiment proposes a multi-objective online dynamic dimensionality reduction and reconstruction strategy that considers the KRPVS (Kinshaft Power Reduction and Dimensionality Variation) of node equivalent support strength. This strategy effectively overcomes the challenges of dimensionality curse in traditional global reconstruction and the difficulty of single-section reconstruction in handling online operation. In the spatial optimization dimension, a local targeted dimensionality reduction mechanism based on voltage support early warning is proposed. This mechanism directly relies on the propagation chain of weak voltage supports identified by dynamic early warning to construct local temporary loops and accurately unblock them. While significantly compressing the decision solution space and meeting the timeliness requirements of second-level online intervention, it completely cuts off the propagation path of weak voltage supports at the physical level. In the multi-dimensional collaborative control dimension, a system integrating voltage support topology reconstruction and discrete C is constructed. The joint online enhancement strategy of Action B establishes a multi-objective dynamic reconfiguration strategy that includes KRPVS enhancement, network loss economy, and voltage soft constraint penalty. This ensures that when the voltage approaches the safety lower limit, the system can prioritize the simultaneous leap in absolute safety and local disturbance resistance. In the time decision dimension, an online rolling time-domain look-ahead mechanism that takes into account the action dead zone is introduced. This mechanism can not only proactively release the system's operational safety margin under normal operating conditions to obtain a global improvement in voltage support strength, but also keenly predict future collapse risks when encountering extreme scenarios such as photovoltaic grid decommissioning and extreme heavy loads. This significantly enhances the extreme robustness of the distribution network in the face of future unknown high-frequency fluctuations.

[0081] Example 2 Embodiment 2 of the present invention introduces a multi-objective online rolling reconfiguration system for power distribution networks.

[0082] like Figure 18The multi-objective online rolling reconfiguration system for a distribution network shown includes: The module is configured to introduce a rolling time-domain mechanism to build an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions. The analysis module is configured to construct a directed graph of the vertical voltage support topology based on the branch reactive voltage sensitivity and the online dynamic reconfiguration framework of the distribution network. Based on the constructed directed graph, the voltage support strength is analyzed to the branch level, resulting in a local targeted dimensionality reduction mechanism based on voltage support topology early warning. The calculation module is configured to calculate the equivalent support strength of the nodes according to the local targeted dimensionality reduction mechanism; The optimization module is configured to consider the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost and reactive power compensation action cost to construct a multi-objective online rolling reconfiguration model. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner to complete the multi-objective online rolling reconfiguration of the distribution network.

[0083] The detailed steps are the same as those of the online rolling reconfiguration method for distribution networks provided in Example 1, and will not be repeated here.

[0084] Example 3 Embodiment 3 of the present invention provides a computer-readable storage medium.

[0085] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the multi-objective online rolling reconfiguration method for distribution networks as described in Embodiment 1 of the present invention.

[0086] The detailed steps are the same as those of the online rolling reconfiguration method for distribution networks provided in Example 1, and will not be repeated here.

[0087] Example 4 Embodiment 4 of the present invention provides an electronic device.

[0088] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps in the multi-objective online rolling reconfiguration method for distribution networks as described in Embodiment 1 of the present invention.

[0089] The detailed steps are the same as those of the online rolling reconfiguration method for distribution networks provided in Example 1, and will not be repeated here.

[0090] Example 5 Embodiment 5 of the present invention provides a computer program product.

[0091] A computer program product includes software code, wherein the program in the software code performs the steps of the multi-objective online rolling reconfiguration method for distribution networks as described in Embodiment 1 of the present invention.

[0092] The detailed steps are the same as those of the online rolling reconfiguration method for distribution networks provided in Example 1, and will not be repeated here.

[0093] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0094] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0097] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0098] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0099] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A method for multi-objective online rolling reconfiguration of a distribution network, characterized in that, include: A rolling time-domain mechanism is introduced to construct an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions; Based on the reactive voltage sensitivity of branches and the online dynamic reconfiguration framework of distribution networks, a directed graph of vertical voltage support topology is constructed. According to the constructed directed graph, the voltage support strength is analyzed to the branch level, and a local targeted dimensionality reduction mechanism based on voltage support topology early warning is obtained. Based on the local targeted dimensionality reduction mechanism, calculate the equivalent support strength of the nodes; Considering the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost, and reactive power compensation action cost, a multi-objective online rolling reconfiguration model is constructed. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner, and the multi-objective online rolling reconfiguration of the distribution network is completed.

2. The method for multi-objective online rolling reconfiguration of a distribution network as described in claim 1, characterized in that, The equipment action dead zone constraints include: within the action dead zone time window, the already activated tie switch or parallel capacitor bank must not undergo state reversal again; the number of tie switches and parallel capacitor banks allowed to activate within a single decision window shall not exceed the set maximum value; and the total number of times a single tie switch or parallel capacitor bank is allowed to activate within the total simulation cycle shall not exceed the set maximum value.

3. The method for multi-objective online rolling reconfiguration of a distribution network as described in claim 1, characterized in that, The local targeted dimensionality reduction mechanism includes: Automatic identification of weak voltage support nodes based on branch reactive voltage sensitivity threshold; Using the shortest path optimization mechanism, we search for alternative interconnection switches in the global interconnection switch set that can quickly connect weak nodes to the high-voltage support area; Close the alternative contact switch to form a temporary loop, and disconnect the branch with the lowest reactive voltage sensitivity value in the loop to complete the loop unblocking.

4. The method for multi-objective online rolling reconfiguration of a distribution network as described in claim 1, characterized in that, In the process of constructing the directed graph of the vertical voltage support topology, a propagation direction indicator variable is introduced based on the reactive power-voltage sensitivity of the branch. The undirected distribution network is mapped into a directed graph based on the reactive power incremental response. Nodes represent the grid bus and directed edges represent the directional propagation path of reactive power support capability.

5. The method for multi-objective online rolling reconfiguration of a distribution network as described in claim 1, characterized in that, The objective function of the multi-objective online rolling reconfiguration model is the weighted sum of various operational indicators within the look-ahead time window. These operational indicators include at least the following sub-objectives: steady-state voltage soft constraint deviation, active power loss economy, node voltage support strength, line switching equipment operation cost, discrete reactive power equipment operation cost, and operational parameter over-limit penalty. The steady-state voltage soft constraint deviation sub-objective employs a soft constraint-based quadratic penalty mechanism, introducing a penalty term when the node voltage falls below the safety lower limit, guiding the reconfiguration strategy to converge towards the direction with the shallowest voltage drop. The node voltage support strength sub-objective aims to maximize the minimum equivalent support strength of nodes within the weak region.

6. The method for multi-objective online rolling reconfiguration of a distribution network as described in claim 1, characterized in that, When the node voltage approaches the safe lower limit, the absolute voltage level is increased first to eliminate the risk of exceeding the limit; when the node voltage is in the safe range but the support strength is insufficient, the voltage operating margin is allowed to be slightly released on the premise of ensuring that no limit exceeds the limit, and the overall voltage support capability is improved by reconfiguring the topology. Under ideal operating conditions, voltage distribution and voltage support strength are optimized simultaneously; multi-objective online rolling reconfiguration of the distribution network is completed.

7. A multi-objective online rolling reconfiguration system for a distribution network, characterized in that, include: The module is configured to introduce a rolling time-domain mechanism to build an online dynamic reconfiguration framework for the distribution network that takes into account the dead-zone constraints of equipment actions. The analysis module is configured to construct a directed graph of the vertical voltage support topology based on the branch reactive voltage sensitivity and the online dynamic reconfiguration framework of the distribution network. Based on the constructed directed graph, the voltage support strength is analyzed to the branch level, resulting in a local targeted dimensionality reduction mechanism based on voltage support topology early warning. The calculation module is configured to calculate the equivalent support strength of the nodes according to the local targeted dimensionality reduction mechanism; The optimization module is configured to consider the equivalent support strength of nodes, voltage deviation, active power loss, switching action cost and reactive power compensation action cost to construct a multi-objective online rolling reconfiguration model. Based on the constructed multi-objective online rolling reconfiguration model, the voltage level and voltage support capacity of the distribution network are optimized in a coordinated manner to complete the multi-objective online rolling reconfiguration of the distribution network.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the online rolling reconfiguration method for distribution networks as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the distribution network multi-objective online rolling reconfiguration method as described in any one of claims 1-6.

10. A computer program product, comprising software code, characterized in that, The program in the software code performs the steps of the distribution network multi-objective online rolling reconfiguration method as described in any one of claims 1-6.

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