A site selection method and system for a direct current power distribution converter station configured with a mesh network

Abstract

The application belongs to the technical field of converter station planning, and particularly relates to a site selection method and system of a DC power distribution converter station configured with a follow-up network and a constructed network, comprising the following steps: obtaining a voltage stability margin of a DC power distribution node; determining a DC power distribution key node according to the determined voltage stability margin; taking the minimum total active loss and voltage deviation as the target, taking the voltage drop amplitude and the power distribution network short-circuit ratio as the converter station site selection evaluation index, and constructing a converter station site selection optimization model of the DC power distribution key node; solving the constructed converter station site selection optimization model to obtain the converter station site selection evaluation index weight; according to the converter station site selection evaluation index and the weight, considering the follow-up network and the constructed network configuration of the power grid, optimizing the power grid control mode of the follow-up network and the constructed network, obtaining the optimal site selection scheme of the converter station, and completing the site selection of the DC power distribution converter station.

Description

Technical Field

[0001] This invention belongs to the field of converter station planning technology, specifically relating to a site selection method and system for a DC distribution converter station with configured network structure. 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] With the increasing integration of distributed photovoltaic and wind power, the operation of renewable energy is gradually becoming more diversified. Traditional DC distribution interconnection operation and control modes may not be able to meet all the operational needs of urban power grids. When the grid is operating stably, a grid-following control strategy can be adopted to achieve DC distribution interconnection; that is, when one converter station operates under constant DC voltage control, another converter station operates under constant active power control, providing a stable active power supply for the urban power grid with DC distribution interconnection.

[0004] The increase in renewable energy has led to a decrease in grid inertia, making urban grid behavior more complex. Grid integration relies on a pre-existing grid-provided control reference phase angle; therefore, simply configuring grid-integrated DC distribution interconnections cannot meet the operational needs of weak grids. Based on this, grid-based control technology has emerged. The difference between grid integration and grid-based integration lies in the method of generating the reference phase angle. Therefore, DC distribution interconnections configured with grid-based integration operate well in weak grids, providing dynamic active power support and phase angle reference for these areas, thus creating conditions for normal grid operation. Under the premise of ensuring normal grid operation, the site selection of DC distribution converter stations configured with grid-based integration is a fundamental and crucial step in grid planning, directly affecting the network structure and operational performance of the DC distribution network. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a site selection method and system for DC distribution converter stations configured to be integrated with the grid. By constructing converter station site selection evaluation indicators and a site selection optimization model, the method optimizes the grid-connected operation mode and the grid-connected operation mode, determines the optimal site selection scheme for the DC distribution converter, and maximizes the reliability and flexibility of grid operation.

[0006] According to some embodiments, the first aspect of the present invention provides a site selection method for a DC distribution converter station configured with a grid, employing the following technical solution:

[0007] A method for site selection of a DC distribution converter station configured with a grid includes:

[0008] Obtain the voltage stability margin of DC distribution nodes;

[0009] Determine the key nodes of DC power distribution based on the determined voltage stability margin;

[0010] With the goal of minimizing total active power loss and voltage deviation, and using voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station location, an optimization model for converter station location at key nodes of DC power distribution is constructed.

[0011] Solve the constructed converter station site selection optimization model to obtain the weights of the converter station site selection evaluation indicators;

[0012] Based on the evaluation indicators and their weights for the selection of converter stations, and considering the grid connection and grid construction configuration, the grid control mode for grid connection and grid construction is optimized to obtain the optimal location scheme for the converter station, thus completing the location selection of the DC distribution converter station.

[0013] As a further technical limitation, permutation entropy, used to evaluate the randomness of time series, is adopted. The weight of the evaluation index is determined by calculating the magnitude of the permutation entropy. The weights obtained are evaluated by using grey relational analysis and suitable solution ranking method. The evaluation results are obtained by comparing the closeness of the decision scheme measurement sequence with the positive and negative ideal state measurement sequences. The optimal location scheme of the converter station is obtained by combining the closeness coefficient.

[0014] As a further technical limitation, in the process of obtaining the voltage stability margin of the DC distribution node, the current state voltage and critical voltage of the DC distribution node are obtained, and the voltage stability margin is obtained based on the percentage of the difference between the current state voltage and the critical voltage to the current state voltage.

[0015] As a further technical limitation, the DC distribution nodes are sorted according to the magnitude of the obtained voltage stability margin to obtain the key DC distribution nodes.

[0016] As a further technical constraint, the objective function L of the converter station site selection optimization model for key DC power distribution nodes is L = L1 + L2; where L1 is the total active power loss function, and N is the total number of branches; P i and Q i These are the active power and reactive power of the i-th branch, respectively; U i R is the voltage at the terminal node of the i-th branch; i It is the resistance of the i-th branch; k i This represents the switch state of the i-th branch, where 0 indicates open and 1 indicates closed; L2 represents the voltage offset, and... t is the number of nodes; k is the total number of nodes; U ts and U tN These represent the actual voltage and the rated voltage of the i-th node, respectively.

[0017] As a further technical limitation, the distribution network short-circuit ratio is the minimum eigenvalue of the extended admittance matrix, which is related to the capacity and admittance matrix of the distribution network.

[0018] According to some embodiments, a second aspect of the present invention provides a site selection system for a DC distribution converter station configured with a grid, employing the following technical solution:

[0019] A site selection system for a DC distribution converter station configured with a network includes:

[0020] The acquisition module is configured to acquire the voltage stability margin of the DC distribution node;

[0021] The module is configured to determine critical nodes in DC power distribution based on the determined voltage stability margin.

[0022] The module is configured to minimize total active power loss and voltage deviation, and to use voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station site selection, to build an optimization model for converter station site selection at key nodes of DC power distribution.

[0023] The calculation module is configured to solve the constructed converter station site selection optimization model to obtain the weights of the converter station site selection evaluation indicators.

[0024] The selection module is configured to optimize the grid control mode of grid connection and grid construction based on the evaluation indicators and weights of the converter station location, taking into account the grid connection and grid construction configuration, to obtain the optimal location scheme of the converter station and complete the location selection of the DC distribution converter station.

[0025] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium, employing the following technical solution:

[0026] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the site selection method for a DC distribution converter station configured with a network as described in the first aspect of the present invention.

[0027] According to some embodiments, the fourth aspect of the present invention provides an electronic device, which adopts the following technical solution:

[0028] 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 site selection method for a DC distribution converter station configured with a grid as described in the first aspect of the present invention.

[0029] According to some embodiments, the fifth aspect of the present invention provides a computer program product, which adopts the following technical solution:

[0030] A computer program product includes software code, wherein the program in the software code performs the steps in the site selection method for a DC distribution converter station configured and connected to a network as described in the first aspect of the present invention.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0032] This invention constructs converter station site selection evaluation indicators and site selection optimization models, optimizes grid-connected operation mode and grid-connected operation mode, determines the optimal site selection scheme for DC distribution converters, and maximizes the reliability and flexibility of grid operation. Attached Figure Description

[0033] 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.

[0034] Figure 1 This is a schematic diagram of the hybrid proportional control structure for DC power distribution interconnection in an urban power grid according to Embodiment 1 of the present invention;

[0035] Figure 2 This is a schematic diagram of the simulation results of a converter station connected to the power grid at a selected location in Embodiment 1 of the present invention; wherein, Figure 2 (a) in the diagram represents a voltage simulation schematic; Figure 2 (b) in the diagram represents a simulation of active power; Figure 2 (c) in the diagram represents a simulation of reactive power. Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0037] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. 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 application pertains.

[0038] 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.

[0039] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0040] Example 1

[0041] Embodiment 1 of the present invention introduces a method for site selection of a DC distribution converter station with a configured network.

[0042] The site selection method for DC distribution converter stations with grid-connected and network-connected configurations proposed in this embodiment is applicable to distribution network operation schemes with both grid-connected and network-connected configurations, making full use of the converter station's ability to both track and connect to the grid. Voltage stability margin is used as the initial selection criterion to exclude nodes with low attention. In the site selection optimization process, Euclidean distance is used as a supplement to the grey relational analysis method. The optimal location of the converter station is determined by calculating the proximity coefficient of the two algorithms, thereby maximizing grid stability and enhancing operational flexibility.

[0043] In this embodiment of a DC power distribution interconnection converter station, an improved hybrid proportional control method is introduced. To simulate a circuit where the grid-connecting and grid-following operations run in parallel, the ratio of grid-connecting to grid-following is based on the parameters of a virtual equivalent circuit. This ratio is unaffected by the virtual parameters and can be used during control mode switching, ensuring a smooth and fluctuation-free transition. The hybrid proportional control architecture consists of independent grid-connecting and grid-following control systems, whose outputs are summed and directly input to the converter, forming a highly efficient hybrid control strategy.

[0044] The schematic diagram of the hybrid proportional control structure for DC distribution interconnection in the urban power grid in this embodiment is shown below. Figure 1 As shown; specifically, the required virtual electrical parameters are calculated using the voltage at the common coupling point, and the obtained virtual electrical parameters are sent to the grid-forming and grid-following control system to generate the reference voltage V' grid-following and V' grid-forming; where G GFM and G GFL These represent the initial ratio values ​​for the network construction and network following modes, respectively.

[0045] During normal urban power grid operation, the inverter operates in grid-following mode. When the urban power grid's operational demands change, the DC distribution converter station receives controller signals, alters its control strategy, and switches from grid-following mode to grid-connecting mode. This achieves a smooth transition between grid-following and grid-connecting control, resulting in a hybrid proportional switching strategy. In this strategy, the two control systems operate continuously in a closed loop, allowing for unified switching and reducing interference during transition periods.

[0046] As one or more implementation methods, in the process of obtaining the voltage stability margin of a DC distribution node, the current state voltage and critical voltage of the DC distribution node are obtained, and the voltage stability margin is obtained based on the percentage of the difference between the current state voltage and the critical voltage to the current state voltage.

[0047] Voltage stability margin is a quantitative indicator that shows the relationship between the current operating state and the voltage collapse threshold; it is an important parameter for evaluating voltage stability resilience. Locations with poor voltage stability at DC distribution nodes are selected as "potential site selection nodes," which meets the preliminary site selection requirements of this embodiment.

[0048] The voltage stability margin U in this embodiment m(i) is Among them, U m (i) is the voltage stability margin of node i; U0(i) is the voltage of node i in its current state; U cr (i) is the critical voltage value of node i.

[0049] As one or more implementation methods, the DC distribution nodes are sorted according to the magnitude of the obtained voltage stability margin to obtain the key DC distribution nodes.

[0050] In this embodiment, nodes are sorted from high to low according to voltage stability margin, and the top 60% of nodes are identified as key DC distribution nodes for preliminary site selection evaluation; the identified key DC distribution nodes are systematically numbered for further analysis.

[0051] As one or more implementation methods, with the goal of minimizing total active power loss and voltage deviation, and using voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station site selection, an optimization model for converter station site selection at key nodes of DC power distribution is constructed.

[0052] The converter station site selection evaluation indicators in this embodiment include voltage drop magnitude and distribution network short-circuit ratio.

[0053] (1) Voltage drop amplitude

[0054] In power distribution networks, due to power system faults or disturbances, the effective voltage can rapidly drop to between 90% and 10% of the rated voltage, and recover to at least 0.9 pu within 10 seconds after the fault is cleared. The magnitude of the voltage drop is the proportion of the voltage decrease relative to the rated voltage. The greater the voltage drop, the greater the disturbance to the power system, and the more challenging the stability and reliability of the power supply.

[0055] (2) Distribution network short-circuit ratio

[0056] Compared to transmission networks, distribution networks have lower voltage levels and more significant phase angle differences between different equipment nodes. Distribution networks typically include overhead lines and cables. When analyzing them, the effects of line resistance and capacitance must be considered, and the higher impedance ratio R / X must be taken into account. This makes the power transmission system in distribution networks more complex than in transmission networks because the resistance and capacitance characteristics of cables differ from those of overhead lines, potentially leading to differences in system dynamic response and stability. Therefore, when analyzing power systems in distribution networks, it is crucial to consider the characteristics of different types of lines to ensure the stability and reliability of system operation.

[0057] This embodiment refers to the short-circuit ratio analysis method based on multi-feed distribution systems. Compared with multi-feed transmission systems, multi-feed distribution systems need to consider network capacitance factors, which depend on the weighted dynamic characteristics of the equipment and the network grounding capacitance.

[0058] This embodiment must meet the following three conditions:

[0059] (1) The impedance ratio (R / L) in the equivalent AC network is consistent;

[0060] (2) There is no three-phase imbalance in the interconnected system;

[0061] (3) The system operates stably at its rated point.

[0062] The short-circuit ratio in a power distribution network is defined as the minimum eigenvalue of the extended admittance matrix; that is...

[0063]

[0064]

[0065]

[0066] Where, ξ GSCR J represents the generalized short-circuit ratio; eq To extend the admittance matrix; λ1 is J eq The smallest characteristic root; S B Represents the capacity matrix of new energy equipment; B red B is the admittance matrix obtained after eliminating passive nodes through Schur complement; B is the equivalent admittance of the network.

[0067] The converter station site selection optimization model for key DC distribution nodes constructed in this embodiment is a multi-objective optimization mathematical model. Its objective function is to minimize the system's active power loss and voltage deviation. Low active power network loss helps reduce active power loss and can significantly reduce energy waste in the distribution network, thereby improving the overall economic efficiency of the power system. Reducing voltage deviation helps maintain stable voltage levels, which ensures the normal operation of various devices and loads in the power system. Excessively high or low voltage may lead to equipment failure or reduced efficiency, affecting system reliability and power quality for consumers.

[0068] In this embodiment, the objective function L of the converter station location optimization model is L = L1 + L2; where L1 is the total active power loss function, and N is the total number of branches; P i and Q i These are the active power and reactive power of the i-th branch, respectively; U i R is the voltage at the terminal node of the i-th branch; i It is the resistance of the i-th branch; k i This represents the switch state of the i-th branch, where 0 indicates open and 1 indicates closed; L2 represents the voltage offset, and... t is the number of nodes; k is the total number of nodes; Uts and U tN These represent the actual voltage and the rated voltage of the i-th node, respectively.

[0069] As one or more implementation methods, the constructed converter station site selection optimization model is solved to obtain the weights of the converter station site selection evaluation index; based on the converter station site selection evaluation index and its weights, considering the grid connection and grid construction configuration, the grid control mode of grid connection and grid construction is optimized to obtain the optimal site selection scheme of the converter station and complete the site selection of the DC distribution converter station.

[0070] In this embodiment, permutation entropy, used to assess the randomness of time series, is employed in calculating the weights of the converter station site selection evaluation indicators. By calculating the magnitude of the permutation entropy, it is determined which indicators among the evaluation indicators have a more significant impact on the selected distribution network nodes. Therefore, permutation entropy not only helps determine the influence weight of each evaluation indicator but also further narrows down the range of selected nodes.

[0071] Let the probabilities of each scenario be p1, p2, ..., p... n The permutation entropy H of time series X p (m) can be defined as Where 'a' is the number of reconstructed elements, and 'm' determines how many consecutive segments the time series is divided into when calculating permutation entropy.

[0072] It should be noted that permutation entropy is a method for detecting the randomness of time series data. It has advantages such as simple and fast calculation, strong noise resistance, and suitability for online monitoring. In a large number of distribution network nodes, the magnitude of permutation entropy can be used to quickly assess the impact of an indicator on certain nodes in the system. A large permutation entropy value indicates that the indicator has a significant impact on certain specific nodes within a series of distribution network nodes, and vice versa.

[0073] This embodiment uses grey relational analysis and suitable solution ranking method for evaluation. The evaluation result is obtained by comparing the similarity between the measurement sequence of the decision scheme and the measurement sequence of the positive and negative ideal states.

[0074] This embodiment employs grey relational analysis, combined with similar calculations of Euclidean distance, to more comprehensively evaluate the similarity between each sample and the ideal positive and negative solutions; specifically:

[0075] Let X + and X - These represent the best and worst solutions for index m at position n, respectively, and are called the positive ideal solutions X. + and negative ideal solution X - ,Right now

[0076] Grey relational coefficient Where ε is the resolution coefficient, which is usually taken as 0.5;

[0077] Let g + / - The grey relational coefficient matrix representing each solution relative to its positive and negative ideal solutions, i.e. Calculate and normalize the distance at each location, i.e.

[0078] When constructing the proximity coefficient, the difference between positive and negative ideal solutions (calculated using Euclidean distance) and their similarity (based on grey relational analysis) were considered, i.e., the proximity coefficient is... Where α + β = 1. In this embodiment, the decision-maker's preference for grey relational analysis and the appropriate solution ranking method is not considered, so α = β = 0.5 is taken.

[0079] Overall proximity coefficient of analysis The closer the proximity coefficient is to 1, the more consistent the solution is with the ideal solution, indicating that the location is optimal.

[0080] It should be noted that this embodiment is based on the calculation of the proximity between the decision scheme index sequence and the ideal positive and negative states. Grey relational analysis focuses on the similarity of shapes between the evaluated and reference schemes, thus reflecting the internal dynamics of each scheme in more detail. Grey relational analysis based on Euclidean distance is used to calculate the relationship between each sample and the ideal positive and negative solutions. The positive and negative ideal solutions are regarded as a set of manually constructed best and worst solutions. The proximity coefficient is calculated by calculating the distance between the two methods and the optimal value and compared at each node. The closer the proximity coefficient is to 1, the more consistent the selected node of the solution is with the positive ideal solution, indicating that the location is optimal.

[0081] Case Analysis

[0082] This embodiment uses an urban power area as a case study to verify the effectiveness and practicality of selecting converter stations for grid configuration. The model used in this embodiment is an equivalent urban distribution network composed of multiple feeders. The external power grid of the urban system is simplified to an external power source, connected to a 110 kV bus using a dynamic equivalent method. The system is built in the PSCAD environment with a frequency of 50 Hz and a simulation time of 8 seconds. All loads use three-phase grounded load components. A three-phase fault simulation component is used to simulate various types of faults occurring in the system. The numbering and location scheme of the selected key nodes are shown in Table 1. For the initial location, nodes are classified according to their voltage stability margin from high to low. These key nodes are numbered; detailed information on the numbering and location scheme of the key nodes is shown in Table 1.

[0083] For each root network configuration, a mathematical model of the location criteria for the pre-selected nodes is calculated to obtain the permutation entropy value of the selected nodes; the weighted scores and rankings of various criteria calculated based on the permutation entropy are shown in Table 2, and the average distance is obtained using grey relational analysis and Euclidean distance, and the results are shown in Table 3.

[0084] This embodiment verifies the support performance of the converter station at the selected location for the power grid in grid-connected mode. To verify the support capability of the converter station switching from islanded operation to grid-connected mode when connected to the grid at the selected location, the test was conducted when the zone was disconnected from the main grid and operated in islanded mode. The test process included the zone disconnecting from the external power grid and entering islanded mode at the fourth second, while the converter station simultaneously switched to grid-connected mode. The simulation time was set to 8 seconds. A node was then randomly selected to evaluate its comparative advantage. The simulation results for the converter station connected to the grid at the selected location are as follows: Figure 2 As shown.

[0085] like Figure 2 As shown, node 16 was selected as the optimal node, while node 9 was a randomly selected control group. The network mode started at 4 seconds, indicated by the shaded area. After transitioning to islanded mode, the voltage of both nodes dropped immediately. Compared to node 16, node 9 experienced a larger voltage drop of 0.15 pu, requiring 3 seconds to stabilize, while node 16 only saw a voltage drop of 0.05 pu within 0.3 seconds of entering islanded mode. During the islanded transition, node 16 generated more active and reactive power, demonstrating its ability to provide additional power to support local loads. Within 0.1 seconds of entering islanded mode, node 16's power increased sharply, indicating its role in stabilizing voltage and enhancing resilience by providing the necessary power.

[0086] This embodiment compares the simulation results between two nodes to evaluate the ability of the converter station at the selected location to transition to grid-connected mode during islanded operation; it emphasizes the robustness of local grid support and voltage stability control under such conditions.

[0087] This embodiment constructs converter station site selection evaluation indicators and site selection optimization models, optimizes grid-connected operation mode and grid-connected operation mode, determines the optimal site selection scheme for DC distribution converters, and maximizes the reliability and flexibility of grid operation.

[0088] Example 2

[0089] Embodiment 2 of the present invention introduces a site selection system for a DC power distribution converter station with a configured network.

[0090] A site selection system for a DC distribution converter station configured with a network includes:

[0091] The acquisition module is configured to acquire the voltage stability margin of the DC distribution node;

[0092] The module is configured to determine critical nodes in DC power distribution based on the determined voltage stability margin.

[0093] The module is configured to minimize total active power loss and voltage deviation, and to use voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station site selection, to build an optimization model for converter station site selection at key nodes of DC power distribution.

[0094] The calculation module is configured to solve the constructed converter station site selection optimization model to obtain the weights of the converter station site selection evaluation indicators.

[0095] The selection module is configured to optimize the grid control mode of grid connection and grid construction based on the evaluation indicators and weights of the converter station location, taking into account the grid connection and grid construction configuration, to obtain the optimal location scheme of the converter station and complete the location selection of the DC distribution converter station.

[0096] The detailed steps are the same as the site selection method for the DC distribution converter station configuration and network provided in Example 1, and will not be repeated here.

[0097] Example 3

[0098] Embodiment 3 of the present invention provides a computer-readable storage medium.

[0099] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the site selection method for a DC distribution converter station configured with a network as described in Embodiment 1 of the present invention.

[0100] The detailed steps are the same as the site selection method for the DC distribution converter station configuration and network provided in Example 1, and will not be repeated here.

[0101] Example 4

[0102] Embodiment 4 of the present invention provides an electronic device.

[0103] 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 site selection method for a DC distribution converter station with a configured network as described in Embodiment 1 of the present invention.

[0104] The detailed steps are the same as the site selection method for the DC distribution converter station configuration and network provided in Example 1, and will not be repeated here.

[0105] Example 5

[0106] Embodiment 5 of the present invention provides a computer program product.

[0107] A computer program product includes software code, wherein the program in the software code performs the steps in the site selection method for a DC distribution converter station configured with a grid as described in Embodiment 1 of the present invention.

[0108] The detailed steps are the same as the site selection method for the DC distribution converter station configuration and network provided in Example 1, and will not be repeated here.

[0109] 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 site selection of a DC distribution converter station configured with a grid, characterized in that, include: Obtain the voltage stability margin of DC distribution nodes; Determine the key nodes of DC power distribution based on the determined voltage stability margin; With the goal of minimizing total active power loss and voltage deviation, and using voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station location, an optimization model for converter station location at key nodes of DC power distribution is constructed. Solve the constructed converter station site selection optimization model to obtain the weights of the converter station site selection evaluation indicators; Based on the evaluation indicators and their weights for the location of the converter station, and considering the grid connection and grid construction configuration, the grid control mode for grid connection and grid construction is optimized to obtain the optimal location scheme for the converter station and complete the location selection of the DC distribution converter station. The objective function of the converter station site selection optimization model for key DC distribution nodes is as follows: for ;in, Let be the total active power loss function, and N is the total number of branches; and These are the active power and reactive power of the i-th branch, respectively; It is the voltage at the terminal node of the i-th branch; It is the resistance of the i-th branch; For voltage offset, and t is the number of nodes; k is the total number of nodes; and These represent the actual voltage and the rated voltage of the i-th node, respectively. The permutation entropy used to evaluate the randomness of time series is adopted. The weight of the evaluation index is determined by calculating the magnitude of the permutation entropy. The weights obtained are evaluated by grey relational analysis and suitable solution ranking method. The evaluation results are obtained by comparing the closeness of the measurement sequence of the decision scheme with the measurement sequence of the positive and negative ideal states. The optimal location scheme of the converter station is obtained by combining the closeness coefficient. Let the probability of each scenario be... , … The permutation entropy of time series X Can be defined as , Where a is the number of reconstructed elements, and m determines how many consecutive segments the time series is divided into when calculating the permutation entropy; Proximity coefficient is Where α+β=1.

2. The site selection method for a DC distribution converter station with a configured grid as described in claim 1, characterized in that, In the process of obtaining the voltage stability margin of a DC distribution node, the current state voltage and critical voltage of the DC distribution node are obtained. The voltage stability margin is obtained based on the percentage of the difference between the current state voltage and the critical voltage to the current state voltage.

3. The site selection method for a DC distribution converter station with a configured grid as described in claim 1, characterized in that, The DC distribution nodes are sorted according to the obtained voltage stability margin to obtain the key DC distribution nodes.

4. The site selection method for a DC distribution converter station with a configured grid as described in claim 1, characterized in that, The distribution network short-circuit ratio is the minimum eigenvalue of the extended admittance matrix, which is related to the capacity and admittance matrix of the distribution network.

5. A site selection system for a DC distribution converter station configured with a grid, characterized in that, include: The acquisition module is configured to acquire the voltage stability margin of the DC distribution node; The module is configured to determine critical nodes in DC power distribution based on the determined voltage stability margin. The module is configured to minimize total active power loss and voltage deviation, and to use voltage drop amplitude and distribution network short-circuit ratio as evaluation indicators for converter station site selection, to build an optimization model for converter station site selection at key nodes of DC power distribution. The calculation module is configured to solve the constructed converter station site selection optimization model to obtain the weights of the converter station site selection evaluation indicators. The selection module is configured to optimize the grid control mode of grid connection and grid construction based on the evaluation indicators and weights of the converter station location, taking into account the grid connection and grid construction configuration, to obtain the optimal location scheme of the converter station and complete the location selection of the DC distribution converter station. The objective function of the converter station site selection optimization model for key DC distribution nodes is as follows: for ;in, Let be the total active power loss function, and N is the total number of branches; and These are the active power and reactive power of the i-th branch, respectively; It is the voltage at the terminal node of the i-th branch; It is the resistance of the i-th branch; For voltage offset, and t is the number of nodes; k is the total number of nodes; and These represent the actual voltage and the rated voltage of the i-th node, respectively. The permutation entropy used to evaluate the randomness of time series is adopted. The weight of the evaluation index is determined by calculating the magnitude of the permutation entropy. The weights obtained are evaluated by grey relational analysis and suitable solution ranking method. The evaluation results are obtained by comparing the closeness of the measurement sequence of the decision scheme with the measurement sequence of the positive and negative ideal states. The optimal location scheme of the converter station is obtained by combining the closeness coefficient. Let the probability of each scenario be... , … The permutation entropy of time series X Can be defined as , Where a is the number of reconstructed elements, and m determines how many consecutive segments the time series is divided into when calculating the permutation entropy; Proximity coefficient is Where α+β=1.

6. 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 location method for configuring and routing DC distribution converter stations as described in any one of claims 1-4.

7. 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 location method for the DC distribution converter station with configuration and network as described in any one of claims 1-4.

8. A computer program product, comprising software code, characterized in that, The program in the software code executes the steps of the site selection method for the DC distribution converter station configured according to any one of claims 1-4.

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