Method and system for flexible dc interconnection site selection and capacity determination based on source load space-time complementation

Abstract

The present disclosure provides a flexible DC interconnection site selection and capacity determination method and system based on source-load space-time complementarity, relating to the technical field of power distribution network planning and operation, comprising: performing dynamic network division of the urban power distribution network based on source-load space-time complementarity, and dividing the power distribution network based on the weighted consensus clustering algorithm of the spectral graph theory; constructing an electrical node dominance degree model, calculating the influence ability of each node on the global voltage stability, sorting the nodes in the partition, screening the key nodes in each region, and pairing the high-ranking nodes of adjacent heterogeneous regions two by two to generate a candidate interconnection node set; performing VSC capacity and site selection optimization on the candidate interconnection node set, establishing an optimization model with the minimum annual total cost as the target, and solving the optimal position and capacity of the flexible DC interconnection. The present disclosure ensures that the planning scheme has excellent transient voltage support capability and technical and economic performance.

Description

Technical Field

[0001] This disclosure relates to the field of distribution network planning and operation technology, specifically to a flexible DC interconnection site selection and capacity determination method and system based on source-load spatiotemporal complementarity. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] The inevitable global transition to clean energy and carbon neutrality is driving a transformation in modern power distribution networks. This transformation is characterized by the rapid and high penetration of distributed generation and the large-scale use of power electronic devices. However, while distributed generation brings environmental benefits, its volatile nature leads to a severe spatiotemporal mismatch between photovoltaic output and load demand, resulting in serious problems such as bidirectional power flow, voltage exceeding limits, and renewable energy curtailment. Against the backdrop of high renewable energy penetration, the economic benefits of traditional grid upgrades and on-load tap-changing transformers are declining.

[0004] Against this backdrop, flexible DC interconnect technologies, represented by soft switching (SOP) and voltage source converter (VSC) based DC interconnect technologies, have become a transformative solution. Unlike mechanical switches, VSC devices can provide precise active power flow control, independent reactive power compensation, and rapid voltage regulation. However, determining their optimal installation location and capacity is crucial.

[0005] Currently, existing planning algorithms rely on expert experience or minimum cost criteria to achieve suboptimal layouts, but they still have the following limitations: (1) The planning method is too high in dimensionality: Existing algorithms rely on metaheuristics or mixed integer nonlinear programming (MINLP), which are prone to "curse of dimensionality" and convergence difficulties in large power distribution networks.

[0006] (2) Static limitations of partitioning methods: Existing partitioning is mainly based on electrical distance or topological modularization, which is a static and topology-oriented method that ignores the key spatiotemporal complementarity between source and load.

[0007] (3) Insufficient physical meaning of evaluation indicators: Commonly used indicators from complex network theory (such as degree centrality) or the degree centrality of classical electrical nodes are based only on topology and fail to effectively incorporate key physical and electrical properties such as line admittance and fault propagation. These problems together lead to traditional methods relying solely on experience or simple economic criteria when determining the optimal location and capacity of SOP / VSC, resulting in low system asset utilization or stability risks. Summary of the Invention

[0008] To address the aforementioned issues, this disclosure proposes a site selection and capacity determination method and system for flexible DC interconnection based on source-load spatiotemporal complementarity. The method involves sequentially performing dynamic network partitioning of the distribution network based on source-load spatiotemporal complementarity, using an electrical node dominance index that integrates network admittance and voltage drop physical characteristics to screen key nodes, and finally establishing a site selection and capacity determination optimization model that considers investment costs and operational risks. This enables the scientific and efficient planning of flexible DC interconnection in the distribution network.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: A flexible DC interconnection location and capacity determination method based on source-load spatiotemporal complementarity includes: The urban power distribution network is dynamically partitioned based on the spatiotemporal complementarity of source and load, and the power distribution network is partitioned based on the weighted consensus clustering algorithm of spectral graph theory. Using the electrical node dominance centrality index, the network admittance matrix and voltage drop impact factor are introduced to construct the electrical node dominance model, calculate the influence of each node on global voltage stability, rank the nodes in the partition, screen the key nodes in each region, and pair the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. VSC capacity and location optimization are performed on the candidate interconnection node set. An optimization model is established with the goal of minimizing the annualized total cost, and the optimal location and capacity of the flexible DC interconnection are solved.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A flexible DC interconnection addressing and capacity-determining system based on source-load spatiotemporal complementarity includes: The dynamic network partitioning module is used to perform dynamic network partitioning of urban power distribution networks based on the spatiotemporal complementarity of sources and loads, and to partition the power distribution network based on a weighted consensus clustering algorithm based on spectral graph theory. The node screening and importance assessment module is used to construct an electrical node dominance model by using the electrical node dominance centrality index, introducing the network admittance matrix and voltage drop impact factor, calculating the influence of each node on global voltage stability, ranking the nodes in the partition, screening the key nodes in each region, and pairing the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. The location and capacity optimization module is used to optimize the VSC capacity and location of the candidate interconnection node set, establish an optimization model with the goal of minimizing the annualized total cost, and solve for the optimal location and capacity of the flexible DC interconnection.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program that, when executed by a processor, implements the aforementioned flexible DC interconnect addressing and sizing method based on source-load spatiotemporal complementarity.

[0012] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement the aforementioned flexible DC interconnect addressing and sizing method based on source-load spatiotemporal complementarity.

[0013] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the flexible DC interconnection addressing and sizing method based on source-load spatiotemporal complementarity.

[0014] Compared with the prior art, the beneficial effects of this disclosure are as follows: The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity disclosed herein, compared with the traditional static topology partitioning, constructs a weighted consensus clustering algorithm that includes temporal complementarity affinity and physical connection affinity, ensuring that the partitioned regions have the greatest potential for cross-regional power exchange.

[0015] This disclosure presents a flexible DC interconnection location and capacity determination method based on source-load spatiotemporal complementarity, proposing an electrical node dominance (IE) centrality index. Compared with the pure topology network centrality analysis method, it innovatively introduces the electrical coupling strength of the network admittance matrix and the voltage drop influence factor based on the impedance matrix, which can accurately identify the key nodes with the greatest influence on global voltage stability from the physical level.

[0016] The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity disclosed in this paper establishes a multi-objective site selection and capacity determination model that takes into account both investment cost and operational flexibility. By significantly reducing the search space to the candidate node set selected by the electrical node dominance, it effectively overcomes the "curse of dimensionality" problem in large-scale node optimization of traditional distribution networks, and ensures that the planning scheme has excellent transient voltage support capability and technical and economic performance. Attached Figure Description

[0017] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0018] Figure 1 This is a flowchart of a flexible DC interconnection addressing and capacity determination method based on source-load spatiotemporal complementarity according to an embodiment of this disclosure. Detailed Implementation

[0019] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0020] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. 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 disclosure pertains.

[0021] 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 exemplary embodiments according to this disclosure. 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.

[0022] Example 1 One embodiment of this disclosure provides a flexible DC interconnection addressing and capacity determination method based on source-load spatiotemporal complementarity, the method steps including: Step 1: Perform dynamic network partitioning of the urban power distribution network based on the spatiotemporal complementarity of source and load, and partition the power distribution network based on the weighted consensus clustering algorithm of spectral graph theory; Step 2: Using the electrical node dominance centrality index, introduce the network admittance matrix and voltage drop impact factor to construct the electrical node dominance model, calculate the influence of each node on global voltage stability, rank the nodes in the partition, screen the key nodes in each region, and pair the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. Step 3: Optimize the VSC capacity and location of the candidate interconnection node set, establish an optimization model with the goal of minimizing the annualized total cost, and solve for the optimal location and capacity of the flexible DC interconnection.

[0023] As one embodiment, the flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity disclosed herein sequentially performs dynamic network partitioning of the distribution network based on source-load spatiotemporal complementarity, utilizes the electrical node dominance index that integrates network admittance and voltage sag physical characteristics to screen key nodes, and finally establishes a site selection and capacity determination optimization model that takes into account investment costs and operational risks. The specific implementation process is as follows: Step 1: Perform dynamic network partitioning of the urban power distribution network based on the spatiotemporal complementarity of source and load, and partition the power distribution network based on the weighted consensus clustering algorithm of spectral graph theory; Specifically, for each node in the distribution network diagram model, the net load characteristics over time are calculated. Net load characteristics refer to the numerical characteristics of the node's net load over a 24-hour timescale, including: Define nodes i In time t The active power load demand is P i,t L The output of distributed power sources is P i,t L The net load is then calculated as follows:

[0024] Obtain the node i exist T The net load sequence within each time step is .

[0025] To eliminate the dimensional influence of different node capacity sizes, the net load sequence is normalized by dividing by the maximum capacity of that node, resulting in a sequence of length [length missing]. T spatiotemporal feature vectors This vector x i This will be used directly as the input for subsequent calculation of the Pearson correlation coefficient.

[0026] To quantize nodes i and j To assess the similarity of the power curves between them, this disclosure uses the Pearson correlation coefficient (PCC), denoted as... r ij :

[0027] Where T is the total number of steps in the time series. and They are nodes i and j exist t Normalized net load value at any given time; and The corresponding nodes are respectively T The average net load over a given time step.

[0028] Furthermore, to balance the similarity of power fluctuation patterns with the integrity of the power grid structure, two independent affinity matrices are constructed: (1) Temporal complementary affinity matrix W ij comp The similarity of power curves between nodes is quantified using the Pearson correlation coefficient (PCC) and mapped to weights.

[0029] (2) Physical connection affinity matrix W ijphys Based on the network admittance matrix Y bus Admittance matrix Y bus It is a complex matrix constructed based on the impedance parameters and topological connections of the actual distribution network lines. Electrical weights are defined as follows to prevent the formation of geographical islands.

[0030]

[0031] in, The first element in the admittance matrix represents the... i Line number j The magnitude of the column element, This represents the maximum value of the mutual admittance among all directly connected branches in the entire distribution network, used to normalize the weights to the [0,1] interval.

[0032] Furthermore, we first address the temporal complementary affinity matrix separately. Physical affinity matrix Calculate the corresponding degree matrix D, and construct the normalized Laplacian matrix:

[0033] Secondly, the time complementary affinity matrix was analyzed separately. Physical affinity matrix Eigenvalue decomposition is performed on the two constructed Laplacian matrices to extract the eigenvalues. K The eigenvectors corresponding to the smallest eigenvalues ​​are used to construct the partition indicator matrix, H. (comp) and H (phys) Through parameters α Constructing a unified consensus matrix:

[0034] Finally, the consensus matrix is ​​calculated. S The Laplace matrix is ​​obtained and its eigenvectors are calculated. These eigenvectors are then clustered row-wise to finally output the distribution network. K Results for each partition.

[0035] Step 2: Using the electrical node dominance centrality index, introduce the network admittance matrix and voltage drop impact factor to construct the electrical node dominance model, calculate the influence of each node on global voltage stability, sort the nodes in the partition, screen the key nodes in each region, and pair the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. Traditional electrical node dominance centrality assumes all connections are homogeneous and ignores the physical state of the power grid. This disclosure addresses this by: (1) Introduce the electrical coupling matrix W to replace the binary adjacency matrix, and the weights are obtained from the admittance matrix:

[0036] The electrical coupling matrix reflects the relative ease of power transfer and disturbance propagation, in which... e Denotes the set of connecting edges, if ( m,n )∈ uh, This indicates the node m With nodes n There are line connections between them; the denominator represents the maximum mutual admittance in the distribution network; and the numerator represents the node. i With nodes j Inter-conductivity.

[0037] (2) Introduce the voltage sag domain (VSD) and construct the voltage sag matrix D. Based on the node impedance matrix Z bus Define the severity of voltage drop. Z ji For nodes i , j Mutual impedance between them Z ii For nodes i Self-impedance.

[0038]

[0039] Subsequently, they aggregate to form node influence factors. d :

[0040] in, oh j This represents the weighting of load importance.

[0041] The final dynamic equation for the electrical node dominance is defined as follows:

[0042] In this dynamic model, the second term represents the propagation of competitive advantage through electrical connections, with the initial voltage distribution. V Normalize by 0. Divide by V The 0 operation essentially increases the advantage sensitivity of nodes with naturally lower voltage distributions, reflecting their greater need for voltage support. (Third item) gd i A physical bias is introduced, in which parameters c The weight of the consequences of the control failure is determined in the final ranking. The equation evolves iteratively until a steady state is reached, at which point the time derivative approaches zero.

[0043] The dynamic equations described above are continuous-time differential equations. In practical computer solutions, the Euler method is used for discretization and numerical iteration. The dominance of all nodes at the initial time step is set. And set a very small convergence criterion. Updated in each iteration The value of when the maximum difference between two consecutive iterations. When the differential equation has evolved to a steady state, we can finally obtain... ψ* The final steady-state value obtained ψ* The ability of each node to influence the global voltage distribution was quantified. The equations iteratively evolved to a steady state, and the obtained static centrality score was used. Filter the top-ranked key nodes in each region, pair high-ranking nodes in adjacent heterogeneous regions, and extract K partition results. Within each partition... ψ* The high-scoring nodes of each partition are selected in descending order. Then, two high-scoring nodes from any different partition are paired up to form a set of candidate nodes for flexible DC interconnection across regions, thus forming a candidate set. This significantly reduces the search space.

[0044] Step 3: Optimize the VSC capacity and location of the candidate interconnection node set, establish an optimization model with the goal of minimizing the annualized total cost, and solve for the optimal location and capacity of the flexible DC interconnection.

[0045] Specifically, for each pair of interconnection schemes in the candidate interconnection node set, an optimization model is established to determine the optimal installation capacity and evaluate the overall cost.

[0046] First, define the capacity quantification mechanism: calculate the reactive power capacity requirement of the VSC based on the local short-circuit current. Then, calculate the steady-state power flow to find the scenario with the maximum DC power transfer and obtain the active power. Specifically, the moment with the maximum absolute value of active power flow transmitted across the DC interconnection line throughout the year is extracted; the power transmitted at that moment is the maximum DC active power required for configuration. .

[0047] And based on the Thevenin equivalent impedance under the worst fault scenario and residual voltage The required reactive power capacity is calculated as shown in the following formula:

[0048] The rated capacity of the VSC is determined by the square root of the sum of the squares of the active power and reactive power, as shown in the following formula:

[0049] Construct an annualized total cost (ATC) objective function F to minimize the annualized total cost, which includes investment cost, operating risk index, and weighted transient voltage loss, in order to minimize cost and expected elasticity penalty:

[0050] in: This is the annualized investment cost after discounting using the capital recovery factor; It is an operational risk index that includes network loss penalties, smoothing tiered voltage over-limit penalties, and renewable energy curtailment costs; To weight transient voltage loss, the economic cost of the physical damage of the global voltage sag caused by a short-circuit fault is quantified. The cost of all candidate solutions is calculated. F The minimum ATC configuration value is selected as the final addressing and capacity determination result.

[0051] Example 2 One embodiment of this disclosure provides a flexible DC interconnection addressing and capacity determination system based on source-load spatiotemporal complementarity, comprising: The dynamic network partitioning module is used to perform dynamic network partitioning of urban power distribution networks based on the spatiotemporal complementarity of sources and loads, and to partition the power distribution network based on a weighted consensus clustering algorithm based on spectral graph theory. The node screening and importance assessment module is used to construct an electrical node dominance model by using the electrical node dominance centrality index, introducing the network admittance matrix and voltage drop impact factor, calculating the influence of each node on global voltage stability, ranking the nodes in the partition, screening the key nodes in each region, and pairing the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. The location and capacity optimization module is used to optimize the VSC capacity and location of the candidate interconnection node set, establish an optimization model with the goal of minimizing the annualized total cost, and solve for the optimal location and capacity of the flexible DC interconnection.

[0052] Example 3 One embodiment of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned flexible DC interconnect addressing and sizing method based on source-load spatiotemporal complementarity.

[0053] Example 4 One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, they implement the aforementioned flexible DC interconnect addressing and sizing method based on source-load spatiotemporal complementarity.

[0054] Example 5 One embodiment of this disclosure provides an electronic device, including a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the flexible DC interconnection addressing and sizing method based on source-load spatiotemporal complementarity.

[0055] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. 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, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure one One or more processes and / or boxes Figure one A device that provides the functions specified in one or more boxes.

[0056] 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 one One or more processes and / or boxes Figure one The steps of the function specified in one or more boxes.

[0057] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity, characterized in that, include: The urban power distribution network is dynamically partitioned based on the spatiotemporal complementarity of source and load, and the power distribution network is partitioned based on the weighted consensus clustering algorithm of spectral graph theory. Using the electrical node dominance centrality index, the network admittance matrix and voltage drop impact factor are introduced to construct the electrical node dominance model, calculate the influence of each node on global voltage stability, rank the nodes in the partition, screen the key nodes in each region, and pair the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. VSC capacity and location optimization are performed on the candidate interconnection node set. An optimization model is established with the goal of minimizing the annualized total cost, and the optimal location and capacity of the flexible DC interconnection are solved.

2. The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity as described in claim 1, characterized in that, The process of dynamically partitioning the urban power distribution network based on the spatiotemporal complementarity of sources and loads, and partitioning the power distribution network using a weighted consensus clustering algorithm based on spectral graph theory, includes: For each node in the distribution network diagram model, calculate the net load characteristics over time series. The similarity of power curves between nodes is quantified using the Pearson correlation coefficient; The similarity of power fluctuation patterns and the integrity of the power grid structure are balanced by constructing a time-complementary affinity matrix and a physical connection affinity matrix. A weighted consensus clustering method based on spectral theory is used to construct normalized Laplace matrices and perform eigenvalue decomposition to obtain partition indicator matrices. A unified consensus matrix is ​​constructed through parameters and then spectral clustering is performed to output the final distribution network partitioning results.

3. The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity as described in claim 1, characterized in that, The method of constructing an electrical node dominance model using the electrical node dominance centrality index, introducing the network admittance matrix and voltage sag influence factor, includes: An electrical coupling matrix is ​​introduced to replace the binary adjacency matrix, and a voltage sag domain is introduced to construct the voltage sag matrix; The severity of voltage sag is defined based on the node impedance matrix, and then aggregated to form the node influence factor, thus constructing the final dynamic equation of electrical node dominance.

4. The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity as described in claim 3, characterized in that, The dynamic equation for the dominance of electrical nodes introduces physical biases through parameters. γ The equation controls the weight of fault consequences in the final ranking. It evolves iteratively until a steady state is reached, at which point the time derivative approaches zero. The final steady-state value quantifies the ability of each node to influence the global voltage distribution. The equation iterates to a steady state, and the obtained static centrality score is used to select the top-ranked key nodes in each region. The high-ranked nodes in adjacent heterogeneous regions are paired up to form a candidate interconnection node set.

5. The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity as described in claim 1, characterized in that, The VSC capacity and location optimization is performed on the candidate interconnection node set. The capacity determination mechanism includes calculating the reactive power capacity requirement of VSC based on the local short-circuit current, calculating the steady-state power flow to find the maximum DC power transfer scenario to obtain active power, and calculating the required reactive power capacity based on the Thevenin equivalent impedance and residual voltage under the worst fault scenario. The rated capacity of VSC is determined by the square root of the sum of the squares of reactive power capacity and active power.

6. The flexible DC interconnection site selection and capacity determination method based on source-load spatiotemporal complementarity as described in claim 1, characterized in that, The minimized annualized total cost includes investment cost, operating risk index, and weighted transient voltage loss. The operating risk index includes network loss penalty, smoothed step voltage over-limit penalty, and renewable energy curtailment cost.

7. A flexible DC interconnection addressing and capacity determination system based on source-load spatiotemporal complementarity, characterized in that, include: The dynamic network partitioning module is used to perform dynamic network partitioning of urban power distribution networks based on the spatiotemporal complementarity of sources and loads, and to partition the power distribution network based on a weighted consensus clustering algorithm based on spectral graph theory. The node screening and importance assessment module is used to construct an electrical node dominance model by using the electrical node dominance centrality index, introducing the network admittance matrix and voltage drop impact factor, calculating the influence of each node on global voltage stability, ranking the nodes in the partition, screening the key nodes in each region, and pairing the high-ranking nodes in adjacent heterogeneous regions to generate candidate interconnection node sets. The location and capacity optimization module is used to optimize the VSC capacity and location of the candidate interconnection node set, establish an optimization model with the goal of minimizing the annualized total cost, and solve for the optimal location and capacity of the flexible DC interconnection.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the flexible DC interconnection addressing and sizing method based on source-load spatiotemporal complementarity as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement the flexible DC interconnect addressing and sizing method based on source-load spatiotemporal complementarity as described in any one of claims 1-6.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to perform the addressing and sizing method for flexible DC interconnection based on source-load spatiotemporal complementarity as described in any one of claims 1-6.

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