Main and Distribution Network Model Topology Stitching Method and System

Abstract

This invention discloses a method and system for splicing the topology of a main distribution network model. The method includes: acquiring real-time operating data of the distribution network and electrical basic data of the main grid, and then performing alignment processing; generating the optimal topology of the distribution network based on the processed real-time operating data and the constraints of the distribution network; locating the boundary nodes of the distribution network and the main grid based on the optimal topology, and extracting the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main grid; performing a security check on the distribution network and the main grid based on the electrical data and the real-time electricity price; if the check passes, splicing the distribution network and the main grid at the boundary nodes according to preset conditions to obtain the main distribution network model. This method can generate the distribution network topology by acquiring real-time operating data of the distribution network and dynamically splice the distribution network topology with the main grid model, thereby solving the problems of global optimization deficiency, topology response lag, and accumulation of security risks caused by fragmented scheduling of the main and distribution networks.

Description

Technical Field

[0001] This invention relates to the field of power distribution network technology, and in particular to a method and system for splicing the topology of a main power distribution network model. Background Technology

[0002] As the 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 access. The large-scale grid connection of distributed power sources such as wind and solar power, along with the widespread deployment of energy storage devices and flexible loads, has significantly altered the power flow distribution, operational structure, and control logic of the distribution network. Simultaneously, the interaction between the main grid and the distribution network is becoming increasingly close, leading to frequent issues such as tie-line power fluctuations and node voltage exceeding limits. Traditional hierarchical independent dispatching models are ill-suited to adapt to the stochastic changes on both the source and load sides. In existing technologies, main grid dispatching typically treats the distribution network as an equivalent boundary load, ignoring its internal distributed resource regulation capabilities; distribution network optimization focuses primarily on minimizing local losses or voltage stability, neglecting the global impact of main grid electricity price signals and security constraints. This fragmented dispatching strategy results in two major bottlenecks: first, the main grid cannot accurately perceive the flexible adjustment potential of distributed resources in the distribution network, missing opportunities for peak shaving and valley filling; second, distribution network reconfiguration relies on static topology and fixed load assumptions, frequently triggering tie-line power oscillations and even main grid safety protection actions under scenarios of fluctuating wind and solar power output and time-varying loads.

[0003] At the level of main grid-distribution network coordination, existing technologies have two key shortcomings. First, the model splicing is rigid: the main grid only receives the total load demand of the distribution network, without acquiring internal topology change information, leading to accumulated deviations between power flow calculations and actual operation; the distribution network passively accepts the main grid's electricity price, lacking the ability to dynamically perceive the power-voltage coupling relationship at boundary nodes. Second, a security closed loop is missing: when the main grid security check detects tie-line overload, there is a lack of topology rollback and power reallocation mechanisms, resorting only to simple load shedding, which reduces power supply reliability and wastes the potential for distributed resource regulation. Therefore, a solution integrating real-time data perception, dynamic topology generation, and seamless splicing of main grid-distribution models is urgently needed to support the safe and economical operation of the power grid under high-proportion renewable energy access. Summary of the Invention

[0004] This invention provides a method and system for splicing the topology of a main distribution network model. It generates the distribution network topology by acquiring real-time operation data of the distribution network and dynamically splices the distribution network topology with the main power grid model to solve the problems of global optimization deficiency, 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.

[0005] To achieve the above objectives, embodiments of the present invention provide a method for splicing the topology of a main distribution network model, comprising:

[0006] Acquire real-time operating data of the distribution network and electrical infrastructure data of the main power grid, and perform alignment processing on the real-time operating data and the electrical infrastructure data;

[0007] Based on the processed real-time operating data and the constraints of the distribution network, the optimal topology of the distribution network is generated using a hierarchical coded particle swarm algorithm.

[0008] Based on the optimal topology, the boundary nodes of the distribution network and the main power grid are located, and the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes of the main power grid are extracted.

[0009] Based on the electrical data and the real-time electricity price, the distribution network and the main power grid are verified through the boundary nodes;

[0010] If the verification passes, the distribution network and the main power grid are spliced ​​together at the boundary node according to preset conditions to obtain the main distribution network model.

[0011] As an improvement to the above scheme, the step of generating the optimal topology of the distribution network using a hierarchical coded particle swarm optimization algorithm based on the processed real-time operating data and the constraints of the distribution network includes:

[0012] 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 source points, connection hub nodes, and ordinary nodes; a simplified network structure is generated by merging the power source points and the connection hub nodes through branch chains.

[0013] Construct a mapping matrix between loops and branch chains based on the simplified network structure;

[0014] Based on the mapping matrix, a hierarchical coded particle swarm algorithm is used to select the interrupt branch of each loop to ensure that the topology satisfies the radial shape and that there is no island operation, and outputs the switch operation scheme.

[0015] Based on the time-varying characteristics of the load and the fluctuation of the output of distributed power sources, the reconfiguration cycle 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.

[0016] As an improvement to the above scheme, the step of locating the boundary nodes of the distribution network and the main power grid according to the optimal topology, and extracting the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main power grid, includes:

[0017] Based on the optimal topology, the physical connection points between the distribution network and the main power grid are taken as boundary nodes;

[0018] Extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main power grid.

[0019] As an improvement to the above scheme, the step of performing security verification on the distribution network and the main power grid through the boundary node based on the electrical data and the real-time electricity price includes:

[0020] The main power grid issues the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's power purchase and sale plan;

[0021] Based on the economic constraint reference, the distribution network uploads power purchase and sale plans, topology change requests, and electrical data of the boundary nodes to the main grid through the boundary nodes;

[0022] The main power grid extracts the voltage and tie-line transmission capacity limits from the electrical data of the corresponding boundary nodes, and calculates the economic and security boundaries of power exchange in combination with the real-time electricity price of the boundary nodes.

[0023] The distribution network and the main power grid are subjected to security verification based on the economic and security boundaries.

[0024] As an improvement to the above scheme, if the verification passes, the distribution network and the main network are spliced ​​together at the boundary node according to preset conditions to obtain the main distribution network model, including:

[0025] If the verification passes, the topology of the distribution network and the power flow model of the main network are spliced ​​together at the boundary node to ensure that the tie-line power balance and voltage consistency of the boundary node are achieved.

[0026] Power flow calculations are used to verify the spliced ​​power grid model to ensure that the actual exchange power of the tie lines is equal to the permitted power exchange amount, thus obtaining the main power grid and the main distribution network model of the distribution network.

[0027] As an improvement to the above scheme, after obtaining the main distribution network model, the method includes:

[0028] Based on the aforementioned main and distribution network model, grid coordinated scheduling is performed with the objective function of minimizing the overall network operating cost.

[0029] As an improvement to the above scheme, the step of performing grid coordinated scheduling based on the main distribution network model with the objective function of minimizing the overall network operating cost includes:

[0030] Obtain the total network operating cost and constraints of the main distribution network model, wherein the total network operating cost includes the main grid generation cost, distribution network loss, voltage stability index, and tie line power deviation penalty term;

[0031] With the goal of minimizing the overall network operating cost, and in conjunction with the aforementioned constraints, a distributed optimization algorithm is used to solve the scheduling model of the main distribution network model, thereby obtaining the grid coordinated scheduling scheme of the main distribution network model.

[0032] Power grid collaborative scheduling is carried out according to the aforementioned power grid collaborative scheduling scheme.

[0033] To achieve the above objectives, embodiments of the present invention provide a main distribution network model topology splicing system, comprising:

[0034] The power grid data acquisition module is used to acquire real-time operating data of the distribution network and electrical basic data of the main power grid, and to perform alignment processing on the real-time operating data and the electrical basic data.

[0035] The topology generation module is used to generate the optimal topology of the distribution network based on the processed real-time operating data and the constraints of the distribution network, using a hierarchical coded particle swarm algorithm.

[0036] The node data extraction module is used to locate the boundary nodes of the distribution network and the main power grid according to the optimal topology, and to extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main power grid.

[0037] The node security verification module is used to perform security verification on the distribution network and the main power grid through the boundary nodes based on the electrical data and the real-time electricity price;

[0038] The power grid model generation module is used to splice the distribution network and the main power grid at the boundary node according to preset conditions if the verification passes, so as to obtain the main distribution network model.

[0039] As an improvement to the above solution, the topology generation module is used for:

[0040] 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 source points, connection hub nodes, and ordinary nodes; a simplified network structure is generated by merging the power source points and the connection hub nodes through branch chains.

[0041] Construct a mapping matrix between loops and branch chains based on the simplified network structure;

[0042] Based on the mapping matrix, a hierarchical coded particle swarm algorithm is used to select the interrupt branch of each loop to ensure that the topology satisfies the radial shape and that there is no island operation, and outputs the switch operation scheme.

[0043] Based on the time-varying characteristics of the load and the fluctuation of the output of distributed power sources, the reconfiguration cycle 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.

[0044] As an improvement to the above solution, the system further includes:

[0045] The power grid coordinated dispatch module is used to perform power grid coordinated dispatch based on the main and distribution network model with the objective function of minimizing the overall network operating cost.

[0046] Compared with existing technologies, the present invention discloses a method and system for splicing the topology of a main distribution network model. This method acquires real-time operating data of the distribution network and electrical infrastructure data of the main grid, and aligns the real-time operating data and electrical infrastructure data. Based on the processed real-time operating data and the constraints of the distribution network, a hierarchical coded particle swarm optimization algorithm is used to generate the optimal topology of the distribution network. The boundary nodes of the distribution network and the main grid are located based on the optimal topology, and the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main grid are extracted. Security verification is performed on the distribution network and the main grid through the boundary nodes based on 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 nodes according to preset conditions to obtain the main distribution network model. This method can generate the distribution network topology by acquiring real-time operating data of the distribution network and dynamically splice the distribution network topology with the main grid model, thereby solving the problems of global optimization deficiency, topology response lag, and accumulated security risks caused by fragmented scheduling of the main distribution network under high-proportion renewable energy access. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating a method for splicing the topology of a main distribution network model provided in an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of a main distribution network model topology splicing system provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] It should be noted that the terms "comprising" and "specific" in this invention, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0051] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for splicing the topology of a main distribution network model according to an embodiment of the present invention. The method includes:

[0052] S1, acquire real-time operating data of the distribution network and electrical basic data of the main power grid, and perform alignment processing on the real-time operating data and the electrical basic data;

[0053] S2, Based on the processed real-time operating data and the constraints of the distribution network, the optimal topology of the distribution network is generated using a hierarchical coded particle swarm algorithm;

[0054] S3, locate the boundary nodes of the distribution network and the main power grid according to the optimal topology, and extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes of the main power grid;

[0055] S4, based on the electrical data and the real-time electricity price, perform security verification on the distribution network and the main power grid through the boundary node;

[0056] S5. If the verification passes, the distribution network and the main network are spliced ​​together at the boundary node according to the preset conditions to obtain the main distribution network model.

[0057] For example, the main distribution network model topology splicing method described in this embodiment of the invention is implemented by a power grid management system server. The power grid management system server can interact with target users and with the power grid system. The power grid management system server acquires real-time operating data of the distribution network (e.g., distributed generation output data, energy storage device status, active load demand response information, node voltage, branch power flow, and network topology change signals) and electrical basic data of the main power grid (e.g., tie-line power, node price, and security constraint information). It preprocesses the real-time operating data and the electrical basic data, including noise filtering, data normalization, and time series alignment. For example, smart meters, PMUs (synchronous phasor measurement units), and DG controllers are deployed on the distribution network side to capture in real time the output of distributed generation (wind power output curves are dynamically fitted based on the Weibull distribution of wind speed, and photovoltaic output probability models are generated based on the Beta distribution of irradiance), the state of charge and charging / discharging power of energy storage devices, active load demand response quantities (e.g., load transfer matrix based on real-time electricity prices), node voltage phasors, branch power flow, and switch position change signals. On the main grid side, the bidirectional power of tie lines, marginal electricity prices at nodes, unit reserve capacity, and line transmission margins are obtained through the energy management system. Wavelet denoising technology is used to filter out measurement noise, and heterogeneous data (such as second-level PMU data and minute-level load data) are timestamped. Dimensional differences are eliminated through range normalization to generate a standardized dataset, ensuring the spatiotemporal consistency of subsequent algorithm inputs. Based on the processed real-time operating data and the constraints of the distribution network, a hierarchical coded particle swarm optimization algorithm is used to generate the optimal topology of the distribution network. The boundary nodes between the distribution network and the main grid are located based on the optimal topology, and the electrical data of the boundary nodes and the real-time electricity prices of the corresponding nodes in the main grid are extracted. The distribution network and the main grid are then subjected to security verification through the boundary nodes based on the electrical data and the real-time electricity prices. If the verification passes, the distribution network and the main grid are spliced ​​together at the boundary nodes according to preset conditions to obtain the main distribution network model. The embodiments of the present invention can generate a distribution network topology by acquiring real-time operation data of the distribution network, and dynamically splice the distribution network topology with the main power grid model, so as to solve the problems of global optimization deficiency, topology response lag and security risk accumulation caused by the fragmented scheduling of the main and distribution networks under the high proportion of new energy access.

[0058] Specifically, step S2 includes:

[0059] S21, 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 source points, connection hub nodes, and ordinary nodes; a simplified network structure is generated by merging the power source points and the connection hub nodes through branch chains.

[0060] S22, Construct a mapping matrix between loops and branch chains based on the simplified network structure;

[0061] S23, according to the mapping relationship matrix, the hierarchical coding particle swarm algorithm is used to select the interrupt branch of each loop to ensure that the topology satisfies the radial shape and no island operation, and output the switch operation scheme.

[0062] S24. Based on the time-varying characteristics of the load and the fluctuation of the output of distributed power sources, the reconfiguration cycle 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.

[0063] For example, distribution network nodes are classified into power supply nodes (substation outlets), connection hub nodes (buses with a degree ≥ 3), and ordinary nodes (load points with a degree < 3). 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 (e.g., branch chain L1 contains series lines e1-e2-e3), and a simplified network is constructed. Based on the simplified network, a mapping relationship matrix of loops and branch chains is generated. The matrix rows represent independent loops (the number of which is equal to the number of tie switches), the columns identify branch chains, and the elements mark the loop to which the branch chain belongs, thus eliminating redundant common branch conflicts. The initial particle position is the branch number to be disconnected in each loop, and the loop is traversed in hierarchical order. If the current loop has no common branch chain with the upper loop, a disconnectable branch in this loop is randomly selected. If a common branch chain exists, the branch associated with the branch chain that has been disconnected by the upper loop is removed to avoid islanding or ring networks. The output is a switch combination scheme that meets the requirements of radial shape, no islanding, and branch capacity constraints. The time periods are initially divided according to the monotonicity (rising / falling trend) and change amplitude threshold (e.g., single-hour load fluctuation exceeds 5%) of the load curve. The wind power / solar power output characteristics are superimposed: the high wind power period at night, the high solar power period at noon, and the wind and solar mixed period are further subdivided. Based on the limit of the number of switch actions (e.g., total operation within the day ≤ 20 times), adjacent time periods with topology changes below the set threshold are merged to generate the final reconstructed timetable (e.g., 0:00, 8:00, 17:00).

[0064] Specifically, step S3 includes:

[0065] S31, Based on the optimal topology, the physical connection point between the distribution network and the main network is taken as the boundary node;

[0066] S32, extract the electrical data of the boundary node and the real-time electricity price of the corresponding node of the main power grid.

[0067] For example, based on the optimal topology, the physical connection point of the tie line is located as the boundary node, and the active power, reactive power and voltage phase angle injected on 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.

[0068] Specifically, step S4 includes:

[0069] S41, the main power grid issues the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's power purchase and sale plan;

[0070] S42, according to the economic constraint reference, the distribution network uploads the power purchase and sale plan, topology change request and electrical data of the boundary node to the main grid through the boundary node;

[0071] S43, the main power grid extracts the voltage and tie-line transmission capacity upper limit from the electrical data of the corresponding boundary node, and calculates the economic and security boundaries of power exchange in combination with the real-time electricity price of the boundary node;

[0072] S44, Perform a security check on the distribution network and the main power grid based on the economic and security boundaries.

[0073] 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 issues the node electricity price, tie line transmission limit, and security verification results; if the main network security verification fails (e.g., tie line overload), the distribution network triggers topology rollback: switches to the previous feasible topology and re-applies for power.

[0074] Specifically, step S5 includes:

[0075] S51, If ​​the verification passes, the topology of the distribution network and the power flow model of the main network are spliced ​​together at the boundary node to make the tie line power balance and voltage consistency of the boundary node consistent.

[0076] S52, power flow calculation is used to verify the spliced ​​power grid model so that the actual exchange power of the tie line is equal to the permitted power exchange amount, thus obtaining the main power grid and the main distribution network model of the distribution network.

[0077] For example, the preset conditions include power balance and voltage consistency of tie lines at the boundary nodes, and that the actual switching power of the tie lines is equal to the permitted power switching amount. The distribution network dynamic topology and the main network power flow model are spliced ​​at the boundary nodes, and the boundary power balance equation is solved iteratively using the Newton-Raphson method to ensure that the actual transmission amount of the tie lines is equal to the permitted switching amount; the voltage deviation of the boundary nodes is checked to be ≤±5%, otherwise the output of the reactive power compensation equipment in the distribution network is adjusted.

[0078] Furthermore, after obtaining the main distribution network model, the method includes:

[0079] S6. Based on the main distribution network model, perform grid coordinated scheduling with the objective function of minimizing the overall network operating cost.

[0080] Specifically, step S6 includes:

[0081] S61, obtain the total network operating cost and constraints of the main distribution network model, wherein the total network operating cost includes the main grid generation cost, distribution network loss, voltage stability index and tie line power deviation penalty term;

[0082] S62, with the goal of minimizing the overall network operating cost, and in conjunction with the constraints, a distributed optimization algorithm is used to solve the scheduling model of the main distribution network model, thereby obtaining the grid collaborative scheduling scheme of the main distribution network model;

[0083] S63, Perform grid collaborative scheduling according to the grid collaborative scheduling scheme.

[0084] For example, the system jointly optimizes the main grid generation cost, distribution network losses, voltage stability indicators, and tie-line power deviation penalties, calculating the overall network operating cost through weighted average. It integrates main grid unit output limits, ramp rates, line transmission capacity constraints, distribution network power balance, energy storage charging and discharging limits, switching operation limits, and global power flow convergence and boundary voltage safety requirements as constraints. A distributed optimization algorithm is used to solve the scheduling model, outputting the main grid unit scheduling plan, distribution network switch status, distributed power output strategy, and load demand response instructions. For instance, multi-objective integration defines the comprehensive cost objective as: main grid generation cost (accumulated according to unit bidding functions) + distribution network losses (sum of the squared resistance of each branch current) + tie-line power deviation penalty (absolute value of the difference between planned and actual values ​​× penalty coefficient) + voltage stability weight (maximum static voltage stability indicator). A dynamic adjustment mechanism for the weight coefficients is set: priority is given to voltage stability during peak hours (weight 0.6), while economic efficiency is emphasized during off-peak hours (weight 0.8). Constraint-based joint management: Main grid side: Unit output limits (e.g., 10MW≤P≤300MW), ramp rate (e.g., ±30MW / h), line thermal stability capacity; Distribution grid side: Energy storage charging and discharging power (e.g., -6MW≤P≤6MW), state of charge (10%-100%), number of switching operations (single switch ≤ 5 times / day); Global: Boundary voltage deviation ≤ 5%, tie line power bidirectional balance. Distributed parallel solution: Using the Benders decomposition algorithm: The main problem optimizes the main grid unit combination, and the sub-problems solve the distribution network topology and DG output; outputs the main grid unit start-up and shutdown plan, distribution network switch status, energy storage charging and discharging curves, and load demand response instructions, and sends them to each execution terminal.

[0085] This invention discloses a method for stitching together a main distribution network model topology. The method involves acquiring real-time operational data of the distribution network and electrical infrastructure data of the main grid, aligning the real-time operational data and the electrical infrastructure data, generating the optimal topology of the distribution network using a hierarchical coded particle swarm optimization algorithm based on the processed real-time operational data and the constraints of the distribution network, locating the boundary nodes of the distribution network and the main grid based on the optimal topology, and extracting the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main grid, and performing a security verification of the distribution network and the main grid through the boundary nodes based on the electrical data and the real-time electricity price, and if the verification passes, stitching the distribution network and the main grid together at the boundary nodes according to preset conditions to obtain the main distribution network model. This method can generate a distribution network topology by acquiring real-time operational data of the distribution network and dynamically stitching the distribution network topology with the main grid model, thereby solving the problems of global optimization deficiency, topology response lag, and accumulated security risks caused by fragmented scheduling of the main distribution network under high-proportion renewable energy access.

[0086] See Figure 2 , Figure 2 This is a schematic diagram of a main distribution network model topology splicing system 10 provided in an embodiment of the present invention. The main distribution network model topology splicing system 10 includes:

[0087] The power grid data acquisition module 11 is used to acquire real-time operating data of the distribution network and electrical basic data of the main power grid, and to perform alignment processing on the real-time operating data and the electrical basic data.

[0088] The topology generation module 12 is used to generate the optimal topology of the distribution network based on the processed real-time operating data and the constraints of the distribution network using a hierarchical coded particle swarm algorithm.

[0089] The node data extraction module 13 is used to locate the boundary nodes of the distribution network and the main power grid according to the optimal topology, and to extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes of the main power grid.

[0090] The node security verification module 14 is used to perform security verification on the distribution network and the main power grid through the boundary node based on the electrical data and the real-time electricity price.

[0091] The power grid model generation module 15 is used to splice the distribution network and the main power grid at the boundary node according to preset conditions if the verification passes, so as to obtain the main distribution network model.

[0092] Furthermore, the system also includes:

[0093] The power grid coordinated dispatch module is used to perform power grid coordinated dispatch based on the main and distribution network model with the objective function of minimizing the overall network operating cost.

[0094] The main distribution network model topology splicing system 10 provided in this embodiment of the invention can realize all the processes of the main distribution network model topology splicing method of the above embodiments. The functions and technical effects of each module in the system are the same as those of the main distribution network model topology splicing method of the above embodiments, and will not be repeated here.

[0095] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for splicing the topology of a main distribution network model, characterized in that, include: Acquire real-time operating data of the distribution network and electrical infrastructure data of the main power grid, and perform alignment processing on the real-time operating data and the electrical infrastructure data; Based on the processed real-time operating data and the constraints of the distribution network, the optimal topology of the distribution network is generated using a hierarchical coded particle swarm algorithm. Based on the optimal topology, the boundary nodes of the distribution network and the main power grid are located, and the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes of the main power grid are extracted. Based on the electrical data and the real-time electricity price, the distribution network and the main power grid are verified through the boundary nodes; If the verification passes, the distribution network and the main power grid are spliced ​​together at the boundary node according to preset conditions to obtain the main distribution network model.

2. The main distribution network model topology splicing method as described in claim 1, characterized in that, The step of generating the optimal topology of the distribution network using a hierarchical coded particle swarm optimization algorithm based on the processed real-time operating 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 source points, connection hub nodes, and ordinary nodes; a simplified network structure is generated by merging the power source points and the connection hub nodes through branch chains. Construct a mapping matrix between loops and branch chains based on the simplified network structure; Based on the mapping matrix, a hierarchical coded particle swarm algorithm is used to select the interrupt branch of each loop to ensure that the topology satisfies the radial shape and that there is no island operation, and outputs the switch operation scheme. Based on the time-varying characteristics of the load and the fluctuation of the output of distributed power sources, the reconfiguration cycle 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 as described in claim 1, characterized in that, The step of locating the boundary nodes of the distribution network and the main power grid according to the optimal topology, and extracting the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main power grid, includes: Based on the optimal topology, the physical connection points between the distribution network and the main power grid are taken as boundary nodes; Extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes in the main power grid.

4. The main distribution network model topology splicing method as described in claim 1, characterized in that, The step of performing security verification on the distribution network and the main power grid through the boundary node based on the electrical data and the real-time electricity price includes: The main power grid issues the real-time electricity price to the distribution network through the boundary node as an economic constraint reference for the distribution network's power purchase and sale plan; Based on the economic constraint reference, the distribution network uploads power purchase and sale plans, topology change requests, and electrical data of the boundary nodes to the main grid through the boundary nodes; The main power grid extracts the voltage and tie-line transmission capacity limits from the electrical data of the corresponding boundary nodes, and calculates the economic and security boundaries of power exchange in combination with the real-time electricity price of the boundary nodes. The distribution network and the main power grid are subjected to security verification based on the economic and security boundaries.

5. The main distribution network model topology splicing method as described in claim 1, characterized in that, If the verification passes, the distribution network and the main network are spliced ​​together at the boundary node according to preset conditions to obtain the main distribution network model, including: If the verification passes, the topology of the distribution network and the power flow model of the main network are spliced ​​together at the boundary node to ensure that the tie-line power balance and voltage consistency of the boundary node are achieved. Power flow calculations are used to verify the spliced ​​power grid model to ensure that the actual exchange power of the tie lines is equal to the permitted power exchange amount, thus obtaining the main power grid and the main distribution network model of the distribution network.

6. The main distribution network model topology splicing method as described in claim 1, characterized in that, After obtaining the main distribution network model, the method includes: Based on the aforementioned main and distribution network model, grid coordinated scheduling is performed with the objective function of minimizing the overall network operating cost.

7. The main distribution network model topology splicing method as described in claim 6, characterized in that, The step of performing grid coordinated scheduling based on the main distribution network model with the objective function of minimizing the overall network operating cost includes: Obtain the total network operating cost and constraints of the main distribution network model, wherein the total network operating cost includes the main grid generation cost, distribution network loss, voltage stability index, and tie line power deviation penalty term; With the goal of minimizing the overall network operating cost, and in conjunction with the aforementioned constraints, a distributed optimization algorithm is used to solve the scheduling model of the main distribution network model, thereby obtaining the grid coordinated scheduling scheme of the main distribution network model. Power grid collaborative scheduling is carried out according to the aforementioned power grid collaborative scheduling scheme.

8. A main distribution network model topology splicing system, characterized in that, include: The power grid data acquisition module is used to acquire real-time operating data of the distribution network and electrical basic data of the main power grid, and to perform alignment processing on the real-time operating data and the electrical basic data. The topology generation module is used to generate the optimal topology of the distribution network based on the processed real-time operating data and the constraints of the distribution network, using a hierarchical coded particle swarm algorithm. The node data extraction module is used to locate the boundary nodes of the distribution network and the main power grid according to the optimal topology, and to extract the electrical data of the boundary nodes and the real-time electricity price of the corresponding nodes of the main power grid. The node security verification module is used to perform security verification on the distribution network and the main power grid through the boundary nodes based on the electrical data and the real-time electricity price; The power grid model generation module is used to splice the distribution network and the main power grid at the boundary node according to preset conditions if the verification passes, so as to obtain the main distribution network model.

9. The main distribution network model topology splicing system as described in claim 8, characterized in that, The topology generation module is used for: 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 source points, connection hub nodes, and ordinary nodes; a simplified network structure is generated by merging the power source points and the connection hub nodes through branch chains. Construct a mapping matrix between loops and branch chains based on the simplified network structure; Based on the mapping matrix, a hierarchical coded particle swarm algorithm is used to select the interrupt branch of each loop to ensure that the topology satisfies the radial shape and that there is no island operation, and outputs the switch operation scheme. Based on the time-varying characteristics of the load and the fluctuation of the output of distributed power sources, the reconfiguration cycle 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 as described in claim 8, characterized in that, The system also includes: The power grid coordinated dispatch module is used to perform power grid coordinated dispatch based on the main and distribution network model with the objective function of minimizing the overall network operating cost.

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