Topology splicing method and system for main distribution network model

Abstract

The invention discloses a main power distribution network model topology splicing method and system. The method comprises the steps of obtaining real-time operation data of a power distribution network and electrical basic data of a main power grid, and then performing alignment processing; generating an optimal topological structure of the power distribution network according to the processed real-time operation data and the constraint limitation of the power distribution network; positioning boundary nodes of the power distribution network and the main power grid according to the optimal topological structure, and extracting electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main power grid; safety verification is carried out on the power distribution network and the main power grid according to the electrical data and the real-time electricity price; and if the verification is passed, splicing the power distribution network and the main power grid at the boundary node according to a preset condition to obtain a main power distribution network model. The power distribution network topology can be generated by obtaining the real-time operation data of the power distribution network, and dynamic splicing of the power distribution network topology and the main power grid model is carried out, so that the problems of global optimization missing, topology response lag and safety risk accumulation caused by main and power distribution network split scheduling are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution networks, and in particular to a method and system for topological splicing of a main distribution network model. Background Art

[0002] As energy transition accelerates, the power system is evolving from a traditional centralized power supply model to an active distribution network with a high proportion of distributed energy resources. The large-scale grid integration of distributed power sources such as wind power and photovoltaics, as well as the widespread deployment of energy storage devices and flexible loads, have significantly changed the power flow distribution, operating structure, and regulation logic of the distribution network. Simultaneously, the interaction between the main grid and distribution networks is becoming increasingly close, leading to frequent problems such as power fluctuations on tie lines and voltage limits at nodes. The traditional hierarchical independent scheduling model struggles to adapt to the random fluctuations on both the source and load sides. Existing technologies typically treat the distribution network as a boundary load, ignoring the regulation capabilities of its internal distributed resources. Distribution network optimization often focuses on minimizing local losses or maintaining voltage stability, without considering the global impact of main grid electricity price signals and safety constraints. This fragmented scheduling strategy leads to two major bottlenecks: First, the main grid cannot accurately perceive the flexible regulation potential of the distribution network's distributed resources, missing opportunities for peak shaving and valley filling. Second, distribution network reconstruction relies on static topology and fixed load assumptions. This frequently causes tie line power fluctuations and even triggers main grid safety protection actions in scenarios with fluctuating wind and solar power output and time-varying loads.

[0003] At the level of coordination between the main and distribution networks, existing technologies have two key flaws. The first is the rigidity of model splicing: the main network only receives the total load demand of the distribution network and does not obtain information on internal topology changes, resulting in the accumulation of deviations between power flow calculations and actual operations; the distribution network passively accepts the main network electricity price and lacks the ability to dynamically perceive the power-voltage coupling relationship of boundary nodes. The second is the lack of a safe closed loop: when the main network safety check detects an overload on the tie line, there is a lack of topology rollback and power redistribution mechanisms, and only simple load shedding is used, which not only reduces power supply reliability but also wastes the potential for distributed resource regulation. Therefore, there is an urgent need for a solution that integrates real-time data perception, dynamic topology generation, and seamless splicing of main and distribution models to support the safe and economical operation of the power grid with a high proportion of new energy access. Summary of the Invention

[0004] The present invention provides a main distribution network model topology splicing method and system, which generates the distribution network topology by acquiring the real-time operation data of the distribution network, and dynamically splices the distribution network topology with the main grid model, so as to solve the problems of global optimization loss, topology response lag and safety risk accumulation caused by the fragmented scheduling of the main distribution network under the high proportion of new energy access.

[0005] To achieve the above objectives, an embodiment of the present invention provides a main distribution network model topology splicing method, comprising: Acquire real-time operation data of the distribution network and basic electrical data of the main power grid, and align the real-time operation data with the basic electrical data; Generate an optimal topology of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operating data and the constraints of the distribution network; Locating boundary nodes of the distribution network and the main grid according to the optimal topology, and extracting electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; Performing safety verification on the distribution network and the main power grid through the boundary node according to the electrical data and the real-time electricity price; If the verification passes, the distribution network and the main grid are spliced ​​at the boundary node according to preset conditions to obtain a main distribution network model.

[0006] As an improvement to the above solution, the layered coding particle swarm algorithm is used to generate the optimal topology of the distribution network based on the processed real-time operation data and the constraints of the distribution network, including: Based on the processed real-time operating data and the constraints of the distribution network, the nodes of the distribution network are divided into power supply points, connection hub nodes and ordinary nodes; the power supply points and the connection hub nodes are merged through branch chains to generate a simplified network structure; Constructing a mapping relationship matrix between loops and branch chains according to the simplified network structure; According to the mapping relationship matrix, a layered coding particle swarm algorithm is used to select the interruption branch circuits of each circuit to ensure that the topology satisfies the radial shape and has no island operation, and output the switch operation plan; According to the time-varying characteristics of the load and the fluctuation of the output of the distributed power source, the reconstruction period is divided into multiple time periods through the switching operation scheme, and the topology of the distribution network is updated in each time period to obtain the optimal topology of the distribution network.

[0007] As an improvement to the above solution, locating the boundary nodes of the distribution network and the main grid according to the optimal topology structure, and extracting the electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid, includes: According to the optimal topology, a physical connection point between the distribution network and the main grid is used as a boundary node; The electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid are extracted.

[0008] As an improvement to the above solution, the performing of safety verification on the distribution network and the main power grid through the boundary node according to the electrical data and the real-time electricity price includes: The main grid sends the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's electricity purchase and sales plan; According to the economic constraint reference, the distribution network uploads the power purchase and sales plan, the topology change request and the electrical data of the boundary node to the main power grid through the boundary node; The main grid extracts the voltage and the upper limit of the transmission capacity of the tie line from the electrical data of the corresponding boundary node, and calculates the economic and safety boundaries of the power exchange in combination with the real-time electricity price of the boundary node; A safety check is performed on the distribution network and the main power grid according to the economic and safety boundaries.

[0009] As an improvement to the above solution, if the verification is passed, the distribution network and the main grid are spliced ​​at the boundary node according to preset conditions to obtain a main distribution network model, including: If the verification passes, the topology of the distribution network and the power flow model of the main grid are spliced ​​at the boundary node to ensure that the power balance and voltage of the tie line at the boundary node are consistent; The connected power grid model is verified by using power flow calculation to make the actual exchange power of the tie line equal to the permitted power exchange amount, thereby obtaining the main power grid and the main distribution network model of the distribution network.

[0010] As an improvement to the above solution, after obtaining the main distribution network model, the method includes: According to the main distribution network model, grid coordinated dispatch is performed with minimization of the whole network operation cost as the objective function.

[0011] As an improvement to the above solution, the grid coordinated dispatching is performed based on the main distribution network model with minimization of the whole network operation cost as the objective function, including: Obtaining the full network operation cost and constraint conditions of the main distribution network model, wherein the full network operation cost includes the main grid power generation cost, distribution network loss, voltage stability index, and tie line power deviation penalty item; Taking minimization of the entire network operation cost as the objective function and combining the constraints, a distributed optimization algorithm is used to solve the dispatching model of the main distribution network model to obtain a grid coordinated dispatching scheme for the main distribution network model; Grid coordinated dispatching is performed according to the grid coordinated dispatching scheme.

[0012] To achieve the above objectives, an embodiment of the present invention provides a main distribution network model topology splicing system, including: A power grid data acquisition module is used to acquire real-time operation data of the distribution network and basic electrical data of the main power grid, and align the real-time operation data and the basic electrical data; A topology structure generation module is used to generate an optimal topology structure of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operation data and the constraints of the distribution network; a node data extraction module, configured to locate boundary nodes between the distribution network and the main grid according to the optimal topology, and to extract electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; a node safety verification module, configured to perform safety verification on the distribution network and the main power grid through the boundary nodes according to the electrical data and the real-time electricity price; The power grid model generation module is used to, if the verification is passed, splice the distribution network and the main grid at the boundary node according to preset conditions to obtain a main distribution network model.

[0013] As an improvement to the above solution, the topology structure generating module is used to: Based on the processed real-time operating data and the constraints of the distribution network, the nodes of the distribution network are divided into power supply points, connection hub nodes and ordinary nodes; the power supply points and the connection hub nodes are merged through branch chains to generate a simplified network structure; Constructing a mapping relationship matrix between loops and branch chains according to the simplified network structure; According to the mapping relationship matrix, a layered coding particle swarm algorithm is used to select the interruption branch circuits of each circuit to ensure that the topology satisfies the radial shape and has no island operation, and output the switch operation plan; According to the time-varying characteristics of the load and the fluctuation of the output of the distributed power source, the reconstruction period is divided into multiple time periods through the switching operation scheme, and the topology of the distribution network is updated in each time period to obtain the optimal topology of the distribution network.

[0014] As an improvement to the above solution, the system further includes: The grid coordinated dispatching module is used to perform grid coordinated dispatching based on the main distribution network model with the minimization of the whole network operation cost as the objective function.

[0015] Compared with the prior art, the present invention discloses a main distribution network model topology splicing method and system. By acquiring the real-time operation data of the distribution network and the electrical basic data of the main grid, the real-time operation data and the electrical basic data are aligned; based on the processed real-time operation data and the constraints of the distribution network, a layered coding particle swarm algorithm is used to generate the optimal topology of the distribution network; based on the optimal topology, the boundary nodes of the distribution network and the main grid are located, and the electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid are extracted; based on the electrical data and the real-time electricity prices, the distribution network and the main grid are security verified through the boundary nodes; if the verification passes, the distribution network and the main grid are spliced ​​at the boundary nodes according to preset conditions to obtain the main distribution network model. The system can generate the distribution network topology by acquiring the real-time operation data of the distribution network, and dynamically splice the distribution network topology with the main grid model to solve the problems of global optimization loss, topology response lag, and security risk accumulation caused by the fragmented scheduling of the main distribution network under the high proportion of new energy access. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of a main distribution network model topology splicing method provided by an embodiment of the present invention; Figure 2 It is a structural diagram of a main distribution network model topology splicing system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "comprises" and "specifically" and any variations thereof in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, products or apparatuses.

[0019] See also Figure 1 , Figure 1 1 is a flow chart of a main distribution network model topology splicing method provided by an embodiment of the present invention, the main distribution network model topology splicing method comprising: S1, acquiring real-time operation data of the distribution network and basic electrical data of the main power grid, and aligning the real-time operation data and the basic electrical data; S2, generating an optimal topology of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operating data and the constraints of the distribution network; S3, locating boundary nodes of the distribution network and the main grid according to the optimal topology, and extracting electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; S4, performing a safety check on the distribution network and the main grid through the boundary node according to the electrical data and the real-time electricity price; S5. If the verification passes, the distribution network and the main grid are connected at the boundary nodes according to preset conditions to obtain a main distribution network model.

[0020] Exemplarily, the main distribution network model topology splicing method described in an embodiment of the present invention is implemented by a power grid management system server, which is capable of exchanging information with target users and the power grid system. The power grid management system server obtains real-time operating data of the distribution network (e.g., distributed power generation output data, energy storage device status, active load demand response information, node voltage, branch power flow, and network topology change signals) and basic electrical data of the main power grid (e.g., tie line power, node electricity price, and safety constraint information), and preprocesses the real-time operating data and basic electrical data, including noise filtering, data normalization, and time series alignment. For example, smart meters, PMUs (synchronized phasor measurement units), and DG controllers are deployed on the distribution network side to capture real-time distributed power generation output (wind power dynamically fits output curves based on wind speed Weibull distribution, photovoltaic power generates output probability models based on light intensity Beta distribution), energy storage device state of charge and charge and discharge power, active load demand response quantities (e.g., load transfer matrix based on real-time electricity price), node voltage phasors, branch power flow, and switch position signals. On the main grid side, the energy management system acquires bidirectional tie-line power, node marginal electricity prices, unit reserve capacity, and line transmission margin. Wavelet noise reduction technology is used to filter measurement noise, and timestamps are aligned for heterogeneous data (such as second-level PMU data and minute-level load data). Range normalization eliminates dimensional differences and generates a standardized data set, ensuring the spatiotemporal consistency of subsequent algorithm inputs. Based on the processed real-time operating data and the constraints of the distribution network, a layered coding particle swarm algorithm is used to generate the optimal topology of the distribution network. Based on this optimal topology, the boundary nodes between the distribution network and the main grid are located, and electrical data and real-time electricity prices of the corresponding nodes on the main grid are extracted from these boundary nodes. A safety check is performed on the distribution network and the main grid through the boundary nodes based on the electrical data and real-time electricity prices. If the check passes, the distribution network and the main grid are joined at the boundary nodes according to preset conditions to obtain the main distribution network model. The embodiments of the present invention can generate the distribution network topology by acquiring the real-time operation data of the distribution network, and dynamically splice the distribution network topology with the main grid model, so as to solve the problems of global optimization loss, topology response lag and safety risk accumulation caused by the fragmented scheduling of the main distribution network under the high proportion of new energy access.

[0021] Specifically, step S2 includes: S21, based on the processed real-time operating data and the constraints of the distribution network, dividing the nodes of the distribution network into power supply points, connection hub nodes, and ordinary nodes; and generating a simplified network structure by merging the power supply points and the connection hub nodes through branch chains; S22, constructing a mapping relationship matrix between loops and branch chains according to the simplified network structure; S23, using a layered coding particle swarm algorithm according to the mapping relationship matrix to select interruption branches of each circuit to ensure that the topology satisfies the radial shape and has no island operation, and output a switch operation plan; S24, dividing the reconstruction period into multiple time periods through the switch operation scheme according to the time-varying characteristics of the load and the fluctuation of the output of the distributed power source, and updating the topology of the distribution network in each time period to obtain the optimal topology of the distribution network.

[0022] Exemplarily, the distribution network nodes are classified into power supply nodes (substation outlets), connection hub nodes (busbars with degree ≥ 3) and ordinary nodes (load points with degree < 3), and the first two types of nodes are merged to form a special node set; branch chains between special nodes are generated through depth-first search (for example, branch chain L1 contains series lines e1-e2-e3) to construct a simplified network; based on the simplified network, a loop-branch chain mapping relationship matrix is ​​generated, in which the rows of the matrix represent independent loops (the number is equal to the number of tie switches), the columns identify the branch chains, and the elements mark the loops to which the branch chains belong, thereby eliminating redundant common branch conflicts. Initialize the particle position to the number of the branch to be disconnected in each circuit and traverse the circuit hierarchy in order. If the current circuit has no common branch chain with the upper-level circuit, randomly select a branch within the current circuit that can be disconnected. If a common branch chain exists, remove the associated branches of the branch chain that has been disconnected by the upper layer to avoid islanding or ring networks. Output a switch combination scheme that satisfies the radial shape, has no islands, and meets the branch capacity constraints. Preliminary time periods are divided according to the monotonicity of the load curve (upward / downward trend) and the change amplitude threshold (such as a single-hour load fluctuation exceeding 5%). Superimpose wind power / photovoltaic output characteristics: further subdivide the high wind power period at night, the high photovoltaic period at noon, and the wind-solar mixed period. Based on the limit on the number of switch operations (such as total operations ≤ 20 times per day), merge adjacent time periods with topology changes below the set threshold to generate the final reconstructed timetable (such as 0:00, 8:00, and 17:00).

[0023] Specifically, step S3 includes: S31, according to the optimal topology, taking the physical connection point between the distribution network and the main grid as a boundary node; S32: extracting electrical data of the boundary node and real-time electricity prices of corresponding nodes of the main grid.

[0024] Exemplarily, according to the optimal topology structure, the physical connection point of the interconnection line is located as the boundary node, and the active power, reactive power and voltage phase angle injected into the distribution network side are extracted; the marginal electricity price of the main grid node is mapped to the distribution network boundary node to obtain the real-time electricity price of the corresponding node of the main grid.

[0025] Specifically, step S4 includes: S41, the main grid sends the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's electricity purchase and sales plan; S42, according to the economic constraint reference, the distribution network uploads the power purchase and sales plan, the topology change request and the electrical data of the boundary node to the main grid through the boundary node; S43, the main grid extracts the voltage and the upper limit of the tie line transmission capacity from the electrical data of the corresponding boundary node, and calculates the economic and safety boundaries of power exchange in combination with the real-time electricity price of the boundary node; S44: Perform safety verification on the distribution network and the main power grid according to the economic and safety boundaries.

[0026] For example, the distribution network uploads the power purchase plan (positive value), power sales plan (negative value) and topology change timestamp to the main network; the main network sends the node electricity price, interconnection line transmission limit and safety verification results; if the main network safety verification fails (such as interconnection line overload), the distribution network triggers a topology rollback: switch to the last feasible topology and re-declare the power.

[0027] Specifically, step S5 includes: S51, if the verification passes, splicing the topology of the distribution network and the power flow model of the main grid at the boundary node to ensure that the power balance and voltage of the tie line at the boundary node are consistent; S52, verifying the spliced ​​power grid model by using power flow calculation to make the actual exchange power of the tie line equal to the permitted power exchange amount, and obtaining the main distribution network model of the main power grid and the distribution network.

[0028] Exemplary pre-conditions include the tie-line power balance and voltage consistency at boundary nodes, and the actual tie-line exchange power being equal to the permitted power exchange capacity. The distribution network dynamic topology and the main grid power flow model are combined at the boundary nodes, and the boundary power balance equation is iteratively solved using the Newton-Raphson method to ensure that the tie-line actual transmission capacity equals the permitted exchange capacity. The boundary node voltage deviation is verified to be ≤±5%, otherwise the output of the distribution network reactive power compensation equipment is adjusted.

[0029] Furthermore, after obtaining the main distribution network model, the method includes: S6, performing coordinated grid dispatching based on the main distribution network model with minimization of the entire network operation cost as the objective function.

[0030] Specifically, step S6 includes: S61, obtaining the full network operation cost and constraint conditions of the main distribution network model, wherein the full network operation cost includes the main grid power generation cost, distribution network loss, voltage stability index, and tie line power deviation penalty item; S62, taking minimization of the entire network operation cost as the objective function and combining the constraints, using a distributed optimization algorithm to solve the dispatching model of the main distribution network model to obtain a grid coordinated dispatching solution for the main distribution network model; S63: Performing grid coordinated dispatching according to the grid coordinated dispatching plan.

[0031] For example, the system jointly optimizes main grid generation costs, distribution network losses, voltage stability indicators, and tie-line power deviation penalties, calculating the overall network operating cost through weighted calculations. Constraints are integrated, including main grid unit output limits, ramp rates, and line transmission capacity constraints; distribution network power balance, energy storage charge and discharge limits, switch operation limits, and global power flow convergence and boundary voltage safety requirements. A distributed optimization algorithm is used to solve the dispatch model, outputting the main grid unit dispatch plan, distribution network switch status, distributed generation output strategy, and load demand response instructions. For example, multi-objective integration involves defining a comprehensive cost objective: main grid generation costs (accumulated as a function of unit bids) + distribution network losses (sum of squared resistance of each branch current) + tie-line power deviation penalty (absolute value of the difference between the planned and actual values ​​× penalty coefficient) + voltage stability weight (maximum static voltage stability index). A dynamic adjustment mechanism for the weight coefficients is then established, prioritizing voltage stability during peak hours (weight 0.6) and economic efficiency during off-peak hours (weight 0.8). Constraint management: On the main grid side, constraints include: unit output limits (e.g., 10MW ≤ P ≤ 300MW), ramp rates (e.g., ±30MW / h), and line thermal stability capacity; on the distribution network side, constraints include: energy storage charge and discharge power (e.g., -6MW ≤ P ≤ 6MW), state of charge (10%-100%), and number of switch operations (single switch ≤ 5 times / day); globally, constraints include: boundary voltage deviation ≤ 5%, and bidirectional tie line power balance. Distributed parallel solution: Utilizing the Benders decomposition algorithm, the main problem optimizes the main grid unit combination, while the subproblem solves the distribution network topology and DG output. Output includes: main grid unit start and shutdown plans, distribution network switch status, energy storage charge and discharge curves, and load demand response instructions, which are then distributed to each execution terminal.

[0032] The embodiment of the present invention discloses a main distribution network model topology splicing method, which obtains real-time operation data of the distribution network and electrical basic data of the main grid, aligns the real-time operation data and the electrical basic data; uses a layered coding particle swarm algorithm to generate the optimal topology of the distribution network based on the processed real-time operation data and the constraints of the distribution network; locates the boundary nodes of the distribution network and the main grid according to the optimal topology, and extracts the electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid; performs a safety check on the distribution network and the main grid through the boundary nodes based on the electrical data and the real-time electricity prices; if the check passes, splices the distribution network and the main grid at the boundary nodes according to preset conditions to obtain a main distribution network model. The method can generate a distribution network topology by obtaining real-time operation data of the distribution network, and dynamically splices the distribution network topology with the main grid model to solve the problems of global optimization loss, topology response lag, and safety risk accumulation caused by the fragmented scheduling of the main distribution network under the high proportion of new energy access.

[0033] See also Figure 2 , Figure 2 1 is a structural diagram of a main distribution network model topology splicing system 10 provided by an embodiment of the present invention. The main distribution network model topology splicing system 10 includes: The power grid data acquisition module 11 is used to acquire the real-time operation data of the distribution network and the basic electrical data of the main power grid, and align the real-time operation data and the basic electrical data; A topology structure generating module 12 is configured to generate an optimal topology structure of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operation data and the constraints of the distribution network; a node data extraction module 13, configured to locate boundary nodes between the distribution network and the main grid according to the optimal topology, and to extract electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; a node safety verification module 14, configured to perform safety verification on the distribution network and the main power grid through the boundary nodes according to the electrical data and the real-time electricity price; The power grid model generation module 15 is configured to, if the verification is passed, splice the distribution network and the main power grid at the boundary node according to preset conditions to obtain a main distribution network model.

[0034] Furthermore, the system further comprises: The grid coordinated dispatching module is used to perform grid coordinated dispatching based on the main distribution network model with the minimization of the whole network operation cost as the objective function.

[0035] A main distribution network model topology splicing system 10 provided in an embodiment of the present invention can implement all the processes of the main distribution network model topology splicing method of the above embodiment. The functions of each module in the system and the technical effects achieved are respectively the same as the functions and technical effects achieved by the main distribution network model topology splicing method of the above embodiment, and will not be repeated here.

[0036] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A main distribution network model topology splicing method, characterized in that: include: Acquire real-time operation data of the distribution network and basic electrical data of the main power grid, and align the real-time operation data with the basic electrical data; According to the processed real-time operation data and the constraints of the distribution network, a layered coding particle swarm algorithm is used to generate the optimal topology of the distribution network; Locating boundary nodes of the distribution network and the main grid according to the optimal topology, and extracting electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; Performing safety verification on the distribution network and the main power grid through the boundary node according to the electrical data and the real-time electricity price; If the verification passes, the distribution network and the main grid are spliced ​​at the boundary node according to preset conditions to obtain a main distribution network model.

2. The main distribution network model topology splicing method according to claim 1, characterized in that: The method of generating an optimal topology of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operation data and the constraints of the distribution network includes: Based on the processed real-time operating data and the constraints of the distribution network, the nodes of the distribution network are divided into power supply points, connection hub nodes and ordinary nodes; the power supply points and the connection hub nodes are merged through branch chains to generate a simplified network structure; Constructing a mapping relationship matrix between loops and branch chains according to the simplified network structure; According to the mapping relationship matrix, a layered coding particle swarm algorithm is used to select the interruption branch circuits of each circuit to ensure that the topology satisfies the radial shape and has no island operation, and output the switch operation plan; According to the time-varying characteristics of the load and the fluctuation of the output of the distributed power source, the reconstruction period is divided into multiple time periods through the switching operation scheme, and the topology of the distribution network is updated in each time period to obtain the optimal topology of the distribution network.

3. The main distribution network model topology splicing method according to claim 1, characterized in that: The locating of the boundary nodes of the distribution network and the main grid according to the optimal topology structure, and extracting the electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid, includes: According to the optimal topology, a physical connection point between the distribution network and the main grid is used as a boundary node; The electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes of the main grid are extracted.

4. The main distribution network model topology splicing method according to claim 1, characterized in that: The performing safety verification on the distribution network and the main power grid through the boundary node according to the electrical data and the real-time electricity price includes: The main grid sends the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's electricity purchase and sales plan; According to the economic constraint reference, the distribution network uploads the power purchase and sales plan, the topology change request and the electrical data of the boundary node to the main power grid through the boundary node; The main grid extracts the voltage and the upper limit of the transmission capacity of the tie line from the electrical data of the corresponding boundary node, and calculates the economic and safety boundaries of the power exchange in combination with the real-time electricity price of the boundary node; A safety check is performed on the distribution network and the main power grid according to the economic and safety boundaries.

5. The main distribution network model topology splicing method according to claim 1, characterized in that: If the verification passes, the distribution network and the main grid are spliced ​​at the boundary nodes according to preset conditions to obtain a main distribution network model, including: If the verification passes, the topology of the distribution network and the power flow model of the main grid are spliced ​​at the boundary node to ensure that the power balance and voltage of the tie line at the boundary node are consistent; The connected power grid model is verified by using power flow calculation to make the actual exchange power of the tie line equal to the permitted power exchange amount, thereby obtaining the main power grid and the main distribution network model of the distribution network.

6. The main distribution network model topology splicing method according to claim 1, characterized in that: After obtaining the main distribution network model, the method includes: According to the main distribution network model, grid coordinated dispatch is performed with minimization of the whole network operation cost as the objective function.

7. The main distribution network model topology splicing method according to claim 6, characterized in that: The grid coordinated dispatching is performed based on the main distribution network model with minimization of the entire network operation cost as the objective function, including: Obtaining the full network operation cost and constraint conditions of the main distribution network model, wherein the full network operation cost includes the main grid power generation cost, distribution network loss, voltage stability index, and tie line power deviation penalty item; Taking minimization of the entire network operation cost as the objective function and combining the constraints, a distributed optimization algorithm is used to solve the dispatching model of the main distribution network model to obtain a grid coordinated dispatching scheme for the main distribution network model; Grid coordinated dispatching is performed according to the grid coordinated dispatching scheme.

8. A main distribution network model topology splicing system, characterized in that: include: A power grid data acquisition module is used to acquire real-time operation data of the distribution network and basic electrical data of the main power grid, and align the real-time operation data and the basic electrical data; A topology structure generation module is used to generate an optimal topology structure of the distribution network using a layered coding particle swarm algorithm based on the processed real-time operation data and the constraints of the distribution network; a node data extraction module, configured to locate boundary nodes between the distribution network and the main grid according to the optimal topology, and to extract electrical data of the boundary nodes and real-time electricity prices of corresponding nodes of the main grid; a node safety verification module, configured to perform safety verification on the distribution network and the main power grid through the boundary nodes according to the electrical data and the real-time electricity price; The power grid model generation module is used to, if the verification is passed, splice the distribution network and the main grid at the boundary node according to preset conditions to obtain a main distribution network model.

9. The main distribution network model topology splicing system according to claim 8, characterized in that: The topology structure generating module is used to: Based on the processed real-time operating data and the constraints of the distribution network, the nodes of the distribution network are divided into power supply points, connection hub nodes and ordinary nodes; the power supply points and the connection hub nodes are merged through branch chains to generate a simplified network structure; Constructing a mapping relationship matrix between loops and branch chains according to the simplified network structure; According to the mapping relationship matrix, a layered coding particle swarm algorithm is used to select the interruption branch circuits of each circuit to ensure that the topology satisfies the radial shape and has no island operation, and output the switch operation plan; According to the time-varying characteristics of the load and the fluctuation of the output of the distributed power source, the reconstruction period is divided into multiple time periods through the switching operation scheme, and the topology of the distribution network is updated in each time period to obtain the optimal topology of the distribution network.

10. The main distribution network model topology splicing system according to claim 8, characterized in that: The system further comprises: The grid coordinated dispatching module is used to perform grid coordinated dispatching based on the main distribution network model with the minimization of the whole network operation cost as the objective function.

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