A flexible interconnected power distribution network optimal dispatching method, system and device considering static voltage safety and a storage medium

Abstract

The application discloses a kind of flexible interconnected distribution network optimization scheduling method, system, equipment and storage medium considering static voltage safety, it is related to distribution network optimization scheduling technical field, method includes: for containing multiple nodes radial distribution network, power flow calculation is carried out, according to the power inflow of node local network is equivalently handled, the static voltage stability index of entire distribution network is calculated;Combined with distribution network operation data, static voltage stability index is used as constraint condition, optimization scheduling model containing double objective function is established and is solved by particle swarm algorithm, obtains the daily power curve of voltage source converter, voltage source converter carries out power output control according to daily power curve, completes the optimization scheduling of distribution network;The application can effectively evaluate and improve the static voltage stability of high-capacity distributed power access distribution network, economic efficiency and new energy consumption are considered, reduce network loss, improve interconnected regional voltage stability.

Description

Technical Field

[0001] This invention relates to the field of distribution network optimization scheduling technology, and in particular to a method, system, device and storage medium for optimizing the scheduling of flexible interconnected distribution networks that takes into account static voltage safety. Background Technology

[0002] With the continuous development of power systems, the integration of high-capacity distributed generation into distribution networks has become an important trend in the power sector. However, this integration also brings numerous challenges to the dispatch and operation of distribution networks, among which ensuring the stability of static voltage is a critical issue. How to effectively assess and improve the static voltage stability of distribution networks in scenarios involving high-capacity distributed generation, while simultaneously considering the economic efficiency of dispatch and operation and the capacity for renewable energy absorption, is a significant technical challenge that needs to be overcome in the field of flexible interconnected distribution networks.

[0003] Existing flexible interconnected distribution network dispatching and operation technologies have significant shortcomings in the research on static voltage stability. In scenarios where high-capacity distributed generation sources are integrated into the distribution network, current technologies do not embed the Static Voltage Stability Index (SVSI) into the dispatching model. This makes it difficult to accurately assess and ensure the static voltage stability of the distribution network during actual dispatching, hindering the full utilization of the advantages of distributed generation sources and making it difficult to achieve economical dispatching operations and efficient absorption of renewable energy. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention provides a method, system, device and storage medium for optimized scheduling of flexible interconnected distribution networks that takes into account static voltage safety.

[0005] Therefore, the technical problems solved by this invention are: static voltage stability assessment calculation, economic efficiency of scheduling, new energy consumption, and voltage safety and stability in the scenario of high-capacity distributed power generation access to the distribution network.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides an optimized scheduling method for flexible interconnected distribution networks that takes into account static voltage safety, comprising: For a radial distribution network with multiple nodes, power flow calculation is performed. The local network is equivalently processed according to the power inflow of nodes, and the static voltage stability index of the entire distribution network is calculated. Based on the distribution network operation data, and taking the static voltage stability index as a constraint, an optimization scheduling model with a dual objective function is established. Based on the established optimal scheduling model, the particle swarm optimization algorithm is used to solve the problem and obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimal scheduling of the distribution network.

[0007] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: For a radial distribution network containing multiple nodes, power flow calculations are performed. Based on the power inflow to each node, the local network is equivalently processed, and the static voltage stability index of the entire distribution network is calculated, including: Power flow calculations are performed on the radial distribution network. The number of branches (m) into which power flows from node j is calculated, and the local network where node j is located is equivalently processed based on the current power flow results. For branches connected to node j, the power inflow and outflow situations are distinguished, and the sum of the power transmitted into node j and the sum of the power transmitted from node j to other nodes are calculated respectively. Then, the equivalent nodes, equivalent voltage vectors, and equivalent branch impedances are determined, and the local network is equivalent to a local network equivalent model.

[0008] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: The process of performing power flow calculations on a radial distribution network containing multiple nodes, performing equivalent processing on the local network based on the power inflow to the nodes, and calculating the static voltage stability index of the entire distribution network also includes: The static voltage stability index of node j is determined based on the value of m: when m = 0, the voltage relationship between node j and node N is analyzed, and the stability of the voltage is determined by judging the root discriminant of the equation, thus obtaining the static voltage stability index of node j; when m ≥ 1, the static voltage stability index of node j is obtained according to the corresponding rules.

[0009] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: The process of performing power flow calculations on a radial distribution network containing multiple nodes, performing equivalent processing on the local network based on the power inflow to the nodes, and calculating the static voltage stability index of the entire distribution network also includes: After obtaining the static voltage stability index of each node, the maximum value among all the static voltage stability indices of the nodes is taken as the static voltage stability index of the entire distribution network.

[0010] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: The aforementioned optimization scheduling model, which combines distribution network operation data and uses static voltage stability indicators as constraints, to establish a dual-objective function includes: An optimized scheduling model is established, which takes the minimum daily operating cost and the minimum daily total number of distributed power source trips as dual objective functions to optimize the active and reactive power output states of the voltage source converter in each time period.

[0011] The beneficial effects of this preferred technical solution are as follows: by using a dual objective function for optimized scheduling, the daily operating cost of the distribution network and the total daily tripping volume of distributed power sources are comprehensively considered. While reducing operating costs, the tripping of distributed power sources is reduced, the absorption capacity of distributed power sources is improved, and the economic operation of the distribution network and the efficient utilization of energy are realized.

[0012] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: The method of establishing an optimization scheduling model with dual objective functions, which combines distribution network operation data and uses static voltage stability indicators as constraints, also includes: To optimize the scheduling model, constraints are set, including: power flow equation constraints to ensure that power injection, node voltage, and line parameters meet electrical laws; node voltage upper and lower limit constraints to require that the voltage amplitude of all nodes in the distribution system be within a certain proportion of the standard voltage range; branch power maximum constraints to stipulate that the power value after adding the VSC and the original load power of the branch does not exceed the branch's allowable capacity; constraints on power fed back to the upper-level grid to prohibit the distribution network from feeding active power back to the upper-level grid; VSC capacity constraints to ensure that the active and reactive power on the AC side of the VSC meets the capacity limit; and static voltage stability constraints to require that the voltage stability index value of the planned distribution network be within the allowable upper limit range.

[0013] The beneficial effects of this preferred technical solution are as follows: by setting multiple constraints, the operation of the distribution network during the optimized scheduling process is ensured to conform to electrical laws and actual operating requirements, thus ensuring the stability of node voltage; the constraints include static voltage stability indicators, which further ensure the static voltage safety of the distribution network and improve the reliability and stability of the distribution network operation.

[0014] As a preferred scheme for the optimized scheduling method of flexible interconnected distribution networks that takes into account static voltage safety, wherein: The method of establishing an optimization scheduling model with dual objective functions, which combines distribution network operation data and uses static voltage stability indicators as constraints, also includes: The particle swarm optimization algorithm was used to solve the established optimal scheduling model, and the intraday power curve of VSC was finally calculated.

[0015] Secondly, the present invention provides a flexible interconnected distribution network optimized scheduling system that takes into account static voltage safety, comprising: The power flow and voltage index calculation module is used to perform power flow calculations for radial distribution networks containing multiple nodes, perform equivalent processing on local networks based on the power inflow of nodes, and calculate the static voltage stability index of the entire distribution network. The dual-objective optimization scheduling modeling module is used to combine distribution network operation data and take static voltage stability index as a constraint to establish an optimization scheduling model with dual objective functions. The particle swarm optimization and converter power regulation module is used to solve the established optimization scheduling model using the particle swarm optimization algorithm to obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimization scheduling of the distribution network.

[0016] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the flexible interconnected distribution network optimization scheduling method that takes into account static voltage safety.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of a method for optimizing the scheduling of a flexible interconnected distribution network that takes into account static voltage safety.

[0018] The beneficial effects of this invention are as follows: The distribution network SVSI calculation method based on local network equivalence and the optimized scheduling method for flexible interconnection equipment in distribution networks that considers static voltage stability proposed in this invention have significant advantages in actual high-capacity distributed generation access to distribution networks. This invention has a wide range of applications. By embedding SVSI into the scheduling model as an operational constraint, it can effectively improve the voltage stability of the two interconnected areas in the scenario of high-capacity DG access to distribution networks, which helps to build a safer and more stable power grid. An optimized scheduling model with dual objective functions is established with the goals of economy and DG absorption. This satisfies the requirements of operational economy while helping to improve the absorption capacity of the distribution network and reduce network losses. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1This is an overall flowchart of an optimized scheduling method for a flexible interconnected distribution network that takes into account static voltage safety, provided by the present invention.

[0021] Figure 2 This invention provides a local network model of a flexible interconnected distribution network optimization scheduling method that considers static voltage safety. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides an optimized scheduling method for a flexible interconnected distribution network that takes into account static voltage safety, including: S1: For a radial distribution network with multiple nodes, perform power flow calculations, perform equivalent processing on the local network based on the power inflow to the nodes, and calculate the static voltage stability index of the entire distribution network. S2: Combining distribution network operation data, and taking the static voltage stability index as a constraint, an optimization scheduling model with a dual objective function is established; S3: Based on the established optimal scheduling model, the particle swarm optimization algorithm is used to solve the problem and obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimal scheduling of the distribution network.

[0024] It should be noted that through steps S1-S3, a complete and scientific optimized scheduling system for flexible interconnected distribution networks that considers static voltage safety was constructed. From accurately calculating the static voltage stability index of the distribution network, to integrating it into the optimized scheduling model to balance economy and renewable energy absorption, and then to solving the intraday power curve of the voltage source converter and implementing control, the system achieves an organic unity of safety, economy, and efficiency in distribution network operation. This effectively improves the static voltage stability of the distribution network, reduces operating costs, and enhances the absorption capacity of distributed power sources, providing a practical and feasible optimized scheduling solution for the reliable and high-quality operation of flexible interconnected distribution networks.

[0025] Example 2, refer to Figures 1-2 As one embodiment of the present invention, based on the previous embodiment, a method for optimizing the scheduling of a flexible interconnected distribution network that considers static voltage safety is provided, comprising: In this embodiment, step S1 above involves performing power flow calculations on a radial distribution network containing multiple nodes, performing equivalent processing on the local network based on the power inflow to the nodes, and calculating the static voltage stability index of the entire distribution network, including: First, power flow calculations are performed using the Matpower toolkit.

[0026] In another possible implementation, the Newton-Raphson method can be used for power flow calculation. This involves establishing nonlinear power flow equations and iteratively correcting node voltages and power until convergence is achieved. Specifically, first, a node admittance matrix is ​​established based on the distribution network topology and component parameters. Then, initial node voltage values ​​are set, and the voltages are corrected by calculating power imbalances. This process is iterated until the power imbalance is less than a pre-set error threshold.

[0027] In another possible implementation, the forward-backward substitution method can also be used for power flow calculation. The forward-backward substitution method is suitable for radial distribution networks. It starts from the power source point and calculates the power and voltage in the order of the branches. First, the power of each branch is calculated forward, and then the voltage of each node is calculated backward. Through multiple iterations, the node voltage and power reach stable values.

[0028] Then, calculate m (the number of branches into which power flows to node j) and perform an equivalent transformation on the local network containing node j. For the local network model of the distribution network, based on the current power flow results, such as... Figure 2 As shown, the power of the branches connected to node j from nodes 1, 2, ..., m flows into node j, where m represents the total number of branches from which power flows into node j. The power of the other branches connected to node j flows out of node j, where n represents the total number of branches from which power flows out of node j. , , …, This represents the branch impedance of each branch. , , …, This indicates the transmission power of each branch. , ,…, This represents the node voltage of each node.

[0029] Calculate the transmission power from node i to node j through a branch: Let the sum of the transmission power from the branches associated with node j to node j be... ,but: make ,but: In the formula: It is the branch admittance, which is The reciprocal of.

[0030] The sum of the power transmitted from node j to other nodes through the branch is: ,but: make ,but: It is equivalent to a local network equivalence model, where M and N are equivalence nodes; , These are the equivalent voltage vectors of nodes M and N, respectively; The equivalent impedance of the branch is denoted by , and the equivalent admittance of the branch is denoted by . The reciprocal of; The equivalent impedance of the branch is denoted by , and the equivalent admittance of the branch is denoted by . The reciprocal of.

[0031] In another possible implementation, equivalent nodes, equivalent voltage vectors, and branch equivalent impedances can be determined based on the network topology and power distribution. Specifically, suitable nodes are selected as equivalent nodes based on the power injection and connection relationships of the nodes; then, the voltage values ​​of each node are obtained by performing power flow calculations on the local network, and the equivalent voltage vectors are determined according to the definition of equivalent nodes and relevant electrical principles; finally, the branch equivalent impedances are calculated using the network's impedance parameters and power transmission relationships.

[0032] In another possible implementation, measurement and statistical methods can be used to determine equivalent nodes, equivalent voltage vectors, and branch equivalent impedances. Specifically, in an actual distribution network, measurement equipment is installed to acquire data such as voltage, current, and power at nodes, and statistical analysis is performed. Combined with the network topology and component parameters, the locations of equivalent nodes are determined, and the equivalent voltage vectors and branch equivalent impedances are calculated.

[0033] When m = 0, power flows from node j to node N, then the relationship between the voltages of node j and node N is expressed as: In the formula: Let be the voltage phasor of node j. Let N be the voltage phasor of node N. Let be the resistance between nodes j and N. Let J be the reactance between nodes J and N. Let J be the active power flowing out of node j in branch N. Let be the reactive power flowing out of node j in branches j and N. phasor . conjugate.

[0034] Assumption With an angle of 0°, expanding the above equation yields: In the formula: The voltage amplitude at node N; Let be the voltage amplitude at node j. The above equation can be simplified to: like A solution exists, which can be obtained from the discriminant of the equation: Therefore, we can conclude that: exist Under the condition of ≥0, There always exists at least one positive value, and correspondingly, If there is a solution, then the voltage is stable; otherwise, it means that... Under the condition of <0, The current flow solution does not exist, and correspondingly, If there is no solution, then the voltage becomes unstable.

[0035] Will Simplifying to ≥0, we get: Therefore, the SVSI representation of node j when m=0 can be derived as follows: If m ≥ 1, the SVSI of node j is represented as: in, Let be the voltage amplitude at node i. The line resistance between nodes i and j; Let i be the line reactance between nodes i and j. Let be the active power flowing into node j from branches i and j. Let be the reactive power flowing into node j from branches i and j.

[0036] After obtaining the SVSI of node j, the SVSI of the entire distribution network is calculated and expressed as: in, This represents the static voltage stability index of the entire distribution network, representing each node in the distribution network, and its value ranges from... The total number of nodes in the distribution network, H, is... H represents the total number of nodes in the distribution network.

[0037] In another possible implementation, the Thevenin equivalent method can be used to perform equivalent processing on the local network; the local network is equivalent to a voltage source and an impedance in series. Specifically, the open-circuit voltage of the local network under a specific operating state is first calculated and used as the equivalent voltage source; then, the independent power sources in the network are set to zero, and the equivalent impedance seen from the port is calculated and used as the equivalent impedance, thus completing the equivalent processing of the local network.

[0038] In another possible implementation, Norton's equivalent method can be used to perform equivalent processing on the local network, which is equivalent to a current source and an impedance in parallel. Specifically, the short-circuit current of the local network port is first calculated as the equivalent current source, and then the equivalent impedance of the port is calculated, thereby realizing the equivalence of the local network.

[0039] In another possible implementation, the maximum value among all node static voltage stability indicators can be obtained during real-time monitoring. Specifically, by installing voltage monitoring equipment at each node of the distribution network, the static voltage stability indicator data of the nodes is acquired in real time and transmitted to the monitoring center. Data processing software is then used to compare the indicators of all nodes and find the maximum value in real time.

[0040] In another possible implementation, the maximum value among all node static voltage stability indices can be taken during periodic evaluations. Specifically, comprehensive power flow calculations and static voltage stability index calculations are performed on the distribution network at certain time intervals (e.g., daily, weekly). The calculated indices for each node are stored in a database, and during evaluation, data is retrieved from the database and compared to determine the maximum value.

[0041] In this embodiment, step S2 above, which combines distribution network operation data and uses the static voltage stability index as a constraint, establishes an optimization scheduling model with a dual objective function, including: The optimized scheduling model takes the minimum daily operating cost and the minimum daily total number of distributed generation (DG) units as its objective functions, and includes static voltage stability as a constraint condition to optimize the active and reactive power output status of the voltage source converter (VSC) in each time period.

[0042] Specifically, the objective function aims to minimize operating and maintenance costs and the total annual DG (Decentralized Generation) outage volume. In the formula: This indicates the real-time electricity price. , Let them represent the branches at time t in the AC and DC systems, respectively. Network loss. , These represent the sets of circuits for AC and DC systems, respectively. This represents the unit operating cost of VSC. It contributes to VSC. This represents the number of time points, i.e., 24 hours.

[0043] The constraints for optimizing the scheduling model include: Power flow equation constraints: In the formula: , These represent the active power and reactive power injected by DG into node i, respectively. , These represent the active power and reactive power injected by VSC into node i, respectively. , These represent the active and reactive load power of node i, respectively. , , These represent the conductance, susceptance, and voltage phase angle difference of the line between nodes i and j, respectively. , These represent the voltage amplitudes at nodes i and j, respectively.

[0044] Node voltage upper and lower limit constraints: For all nodes in the power distribution system, the voltage amplitude must not exceed the upper and lower voltage limits, which are 90% to 110% of the standard voltage. This means the following constraint must be met: In the formula: , Let be the minimum and maximum allowed values ​​for node i, respectively.

[0045] Branch power maximum constraint: VSC utilizes flexible interconnection technology to achieve energy sharing. The sum of its power value and the original load power of the branch is required not to exceed the branch's allowable capacity, expressed as: In the formula: , , These represent the power of VSC on both sides. , and These represent the load power in AC and DC distribution networks, respectively. , These represent the maximum allowable capacity of the AC and DC branches, respectively.

[0046] Constraints on power fed back to the upper-level grid: Since the goal is to improve the absorption capacity of distributed generation (DG), it is not allowed for the distribution network to feed active power back to the upper-level grid. The constraint is as follows: In the formula: This represents the output power of the distribution transformer at time t.

[0047] VSC capacity constraints: In the formula: , These represent the active power and reactive power of the VSC on the AC side at time t, respectively. This refers to the capacity of the VSC.

[0048] Static voltage stability constraints: In the formula: The voltage stability index value of the distribution network after planning, This represents the upper limit of the allowable voltage stability index of the distribution network at time t, which is specified by the system dispatcher according to the actual situation.

[0049] Finally, the particle swarm optimization algorithm was used to solve the optimal scheduling model and calculate the intraday power curve of VSC.

[0050] In this embodiment, step S3 above, based on the established optimized scheduling model, is solved using the particle swarm optimization algorithm to obtain the intraday power curve of the voltage source converter. The voltage source converter then performs power output control according to the intraday power curve to complete the optimized scheduling of the distribution network, including: After obtaining the intraday power curve of VSC using the particle swarm optimization algorithm, this curve is applied to the actual operation of the distribution network. VSC performs precise power output control according to this curve, continuously monitors the operating status of the distribution network, and dynamically fine-tunes the power curve according to the real-time situation to ensure that the distribution network is always in the optimal operating state, achieving the expected goals of voltage stability, economical operation, and efficient absorption of distributed power sources.

[0051] Example 3: The above is an illustrative scheme of a flexible interconnected distribution network optimization scheduling method considering static voltage safety according to this embodiment. It should be noted that the technical solution of a flexible interconnected distribution network optimization scheduling system considering static voltage safety belongs to the same concept as the above-described flexible interconnected distribution network optimization scheduling method considering static voltage safety. Details not described in detail in the technical solution of the flexible interconnected distribution network optimization scheduling system considering static voltage safety in this embodiment can be found in the description of the above-described flexible interconnected distribution network optimization scheduling method considering static voltage safety.

[0052] This embodiment also provides a flexible interconnected distribution network optimization scheduling system that takes into account static voltage safety, including: The power flow and voltage index calculation module is used to perform power flow calculations for radial distribution networks containing multiple nodes, perform equivalent processing on local networks based on the power inflow of nodes, and calculate the static voltage stability index of the entire distribution network. The dual-objective optimization scheduling modeling module is used to combine distribution network operation data and take static voltage stability index as a constraint to establish an optimization scheduling model with dual objective functions. The particle swarm optimization and converter power regulation module is used to solve the established optimization scheduling model using the particle swarm optimization algorithm to obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimization scheduling of the distribution network.

[0053] This embodiment also provides an electronic device applicable to a flexible interconnected distribution network optimization scheduling method that considers static voltage safety, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a flexible interconnected distribution network optimization scheduling method that considers static voltage safety, as proposed in the above embodiments.

[0054] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a flexible interconnected distribution network optimization scheduling method that takes into account static voltage safety, as proposed in the above embodiments.

[0055] The storage medium proposed in this embodiment belongs to the same inventive concept as the flexible interconnected distribution network optimization scheduling method considering static voltage safety proposed in the above embodiment. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0056] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the scheduling of a flexible interconnected distribution network that considers static voltage safety, characterized in that, include: For a radial distribution network with multiple nodes, power flow calculation is performed. The local network is equivalently processed according to the power inflow of nodes, and the static voltage stability index of the entire distribution network is calculated. Based on the distribution network operation data, and taking the static voltage stability index as a constraint, an optimization scheduling model with a dual objective function is established. Based on the established optimal scheduling model, the particle swarm optimization algorithm is used to solve the problem and obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimal scheduling of the distribution network.

2. The optimized scheduling method for a flexible interconnected distribution network considering static voltage safety as described in claim 1, characterized in that, For a radial distribution network containing multiple nodes, power flow calculations are performed. Based on the power inflow to each node, the local network is equivalently processed, and the static voltage stability index of the entire distribution network is calculated, including: Power flow calculations are performed on the radial distribution network. The number of branches (m) into which power flows from node j is calculated, and the local network where node j is located is equivalently processed based on the current power flow results. For branches connected to node j, the power inflow and outflow situations are distinguished, and the sum of the power transmitted into node j and the sum of the power transmitted from node j to other nodes are calculated respectively. Then, the equivalent nodes, equivalent voltage vectors, and equivalent branch impedances are determined, and the local network is equivalent to a local network equivalent model.

3. The method for optimizing the scheduling of a flexible interconnected distribution network considering static voltage safety as described in claim 2, characterized in that, The process of performing power flow calculations on a radial distribution network containing multiple nodes, performing equivalent processing on the local network based on the power inflow to the nodes, and calculating the static voltage stability index of the entire distribution network also includes: The static voltage stability index of node j is determined based on the value of m: when m = 0, the voltage relationship between node j and node N is analyzed, and the stability of the voltage is determined by judging the root discriminant of the equation, thus obtaining the static voltage stability index of node j; when m ≥ 1, the static voltage stability index of node j is obtained according to the corresponding rules.

4. The method for optimizing the scheduling of a flexible interconnected distribution network considering static voltage safety as described in claim 3, characterized in that, The process of performing power flow calculations on a radial distribution network containing multiple nodes, performing equivalent processing on the local network based on the power inflow to the nodes, and calculating the static voltage stability index of the entire distribution network also includes: After obtaining the static voltage stability index of each node, the maximum value among all the static voltage stability indices of the nodes is taken as the static voltage stability index of the entire distribution network.

5. The method for optimizing the scheduling of a flexible interconnected distribution network considering static voltage safety as described in claim 4, characterized in that, The aforementioned optimization scheduling model, which combines distribution network operation data and uses static voltage stability indicators as constraints, to establish a dual-objective function includes: An optimized scheduling model is established, which takes the minimum daily operating cost and the minimum daily total number of distributed power source trips as dual objective functions to optimize the active and reactive power output states of the voltage source converter in each time period.

6. The optimized scheduling method for a flexible interconnected distribution network considering static voltage safety as described in claim 5, characterized in that, The method of establishing an optimization scheduling model with dual objective functions, which combines distribution network operation data and uses static voltage stability indicators as constraints, also includes: To optimize the scheduling model, constraints are set, including: power flow equation constraints to ensure that power injection, node voltage, and line parameters meet electrical laws; node voltage upper and lower limit constraints to require that the voltage amplitude of all nodes in the distribution system be within a certain proportion of the standard voltage range; branch power maximum constraints to stipulate that the power value after adding the VSC and the original load power of the branch does not exceed the branch's allowable capacity; constraints on power fed back to the upper-level grid to prohibit the distribution network from feeding active power back to the upper-level grid; VSC capacity constraints to ensure that the active and reactive power on the AC side of the VSC meets the capacity limit; and static voltage stability constraints to require that the voltage stability index value of the planned distribution network be within the allowable upper limit range.

7. The method for optimizing the scheduling of a flexible interconnected distribution network considering static voltage safety as described in claim 6, characterized in that, The method of establishing an optimization scheduling model with dual objective functions, which combines distribution network operation data and uses static voltage stability indicators as constraints, also includes: The particle swarm optimization algorithm was used to solve the established optimal scheduling model, and the intraday power curve of VSC was finally calculated.

8. A flexible interconnected distribution network optimization scheduling system considering static voltage safety, using the method described in any one of claims 1 to 7, characterized in that, include: The power flow and voltage index calculation module is used to perform power flow calculations for radial distribution networks containing multiple nodes, perform equivalent processing on local networks based on the power inflow of nodes, and calculate the static voltage stability index of the entire distribution network. The dual-objective optimization scheduling modeling module is used to combine distribution network operation data and take static voltage stability index as a constraint to establish an optimization scheduling model with dual objective functions. The particle swarm optimization and converter power regulation module is used to solve the established optimization scheduling model using the particle swarm optimization algorithm to obtain the intraday power curve of the voltage source converter. The voltage source converter performs power output control according to the intraday power curve to complete the optimization scheduling of the distribution network.

9. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.

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