Configuration adjustment strategy determination method and device of power transmission and distribution network, and electronic equipment

Abstract

The invention discloses a configuration adjustment strategy determination method and device for a power transmission and distribution network, and electronic equipment. The method comprises the steps that a power transmission and distribution network is divided based on power flow contribution information, a plurality of partitions are obtained, and the power flow contribution information comprises contribution of different topological structures in the power transmission and distribution network to electric energy transmission; marginal electricity price information generated by the power transmission and distribution network in the historical time period is obtained, the marginal electricity price information comprises the blocking cost, and the blocking cost is the cost caused by the fact that part of topological structures in the power transmission and distribution network exceed the transmission capacity limit; on the basis of the marginal electricity price information, power grid blocking frequencies corresponding to the multiple subareas are determined, and the power grid blocking frequencies are used for representing power grid blocking conditions of the corresponding subareas; and based on the power grid blocking frequencies corresponding to the plurality of partitions, determining configuration adjustment strategies corresponding to the plurality of partitions. The technical problem that the power transmission and distribution resource utilization rate is not ideal due to inaccurate power transmission and distribution network configuration in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of electric power, and in particular, to a method, device and electronic equipment for determining a configuration adjustment strategy for a transmission and distribution network. Background Art

[0002] With the acceleration of the construction of new power systems, the large-scale connection of new energy sources to the grid has brought new challenges to the balance of power supply and demand. As a bridge connecting the power generation and consumption sides, the changes in the spatiotemporal characteristics of power supply and demand will inevitably affect the operating characteristics of the transmission and distribution network, thereby increasing the pressure on power grid transmission and distribution and causing blockage of transmission and distribution channels. The transmission and distribution price incentive mechanism in the relevant technology is to assess the operating performance of power grid companies in the historical regulatory cycle, thereby encouraging power grid companies to reduce costs and increase efficiency in terms of safety, economy, and greenness. However, it rarely takes into account the degree of blockage of transmission and distribution channels. Under the incentive mechanism set by the relevant technology, it is impossible to distinguish the degree of occupancy of transmission and distribution resources in different regions, and thus it is impossible to guide the source and load sides to actively adjust electricity consumption in the transmission and distribution configuration link, thereby reducing the occurrence of blockage and the problem of unsatisfactory utilization of transmission and distribution resources in the power system.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method, device and electronic device for determining a configuration adjustment strategy for a power transmission and distribution network, so as to at least solve the technical problem in the related art that the configuration of the power transmission and distribution network is inaccurate, resulting in unsatisfactory utilization of power transmission and distribution resources.

[0005] According to one aspect of an embodiment of the present application, a method for determining a configuration adjustment strategy of a transmission and distribution network is provided, comprising: dividing the transmission and distribution network based on power flow contribution information to obtain a plurality of partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to electric energy transmission; obtaining marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes a congestion cost, which is the cost caused by some topological structures in the transmission and distribution network exceeding the transmission capacity limit; determining power grid congestion frequencies corresponding to the plurality of partitions respectively based on the marginal electricity price information, wherein the power grid congestion frequency is used to indicate the power grid congestion status of the corresponding partition; and determining the configuration adjustment strategies corresponding to the plurality of partitions respectively based on the power grid congestion frequencies corresponding to the plurality of partitions respectively.

[0006] Optionally, the topological structure includes multiple source-load node pairs formed by power nodes and load nodes in the transmission and distribution network, the flow contribution information includes the contributions of the multiple source-load node pairs to the power transmission, and the transmission and distribution network is divided based on the flow contribution information to obtain multiple partitions, including: determining the total flow contribution based on the contributions corresponding to the multiple source-load node pairs; determining the excitation factors corresponding to the multiple source-load node pairs according to the proportion of the contribution corresponding to each node pair in the multiple source-load node pairs to the total flow contribution; determining the contribution threshold based on the excitation factors corresponding to the multiple source-load node pairs; dividing the transmission and distribution network according to the contribution threshold and the excitation factors corresponding to the multiple source-load node pairs to obtain the multiple partitions.

[0007] Optionally, the method also includes: determining the power change between multiple source-load node pairs in the transmission and distribution network, and determining the power transfer factors corresponding to the multiple source-load node pairs, wherein the power transfer factors represent the degree of influence of the corresponding source-load node pairs on the power change; obtaining the per-unit transmission capacity of the branches between the multiple source-load node pairs; and determining the power flow contribution information based on the per-unit transmission capacity and the power transfer factors corresponding to the multiple source-load node pairs.

[0008] Optionally, the determining of the power flow contribution information based on the transmission capacity per-unit value and the power transfer factors respectively corresponding to the multiple source-load node pairs includes: determining the weight coefficients of the branches formed by each node pair in the multiple source-load node pairs based on the transmission capacity per-unit value and the power transfer factors respectively corresponding to the multiple source-load node pairs; in the case where there are multiple branches formed between each node pair, determining a feasible path between each node pair based on the multiple branches, wherein the feasible path is a transmission path among the multiple branches according to the power transmission direction; determining the minimum weight coefficient of the branches passed by the feasible path among the multiple branches; processing the contribution of each node pair to the power transmission based on the minimum weight coefficient of the feasible path; and determining the power flow contribution information based on the contribution of each node pair.

[0009] Optionally, the configuration adjustment strategies corresponding to the multiple partitions are determined based on the grid congestion frequencies corresponding to the multiple partitions, including: for each of the multiple partitions, determining a marginal electricity price fluctuation parameter of each partition in a predetermined time period, wherein the marginal electricity price fluctuation parameter is associated with a grid congestion condition in the transmission and distribution network; based on the grid congestion frequency and the marginal electricity price fluctuation parameter, determining a grid congestion incentive coefficient corresponding to each partition, wherein the grid congestion incentive coefficient is used to indicate the degree of correlation between the occurrence of a grid congestion condition and the occurrence of a marginal electricity price; according to the grid congestion incentive coefficient corresponding to each partition, determining the configuration adjustment strategies corresponding to the multiple partitions.

[0010] Optionally, the configuration adjustment strategies corresponding to the multiple partitions are determined according to the grid congestion excitation coefficient corresponding to each partition, including: when the grid congestion excitation coefficient indicates that the first partition among the multiple partitions is in a congested state, the configuration adjustment strategy of the first partition is determined to be: reducing the line occupancy rate of the first partition, and increasing the number of additional power facilities in the first partition; wherein, reducing the line occupancy rate of the first partition includes: determining the contribution amount corresponding to the first source-load node pair included in the first partition based on the flow contribution information; determining a contribution amount threshold; when the contribution amount corresponding to the first source-load node pair is greater than or equal to the contribution amount threshold, increasing the excitation signal for the first source-load node pair to obtain a first excitation signal; and using the first excitation signal to reduce the line occupancy rate of the first partition.

[0011] Optionally, the configuration adjustment strategies corresponding to the multiple partitions are determined according to the grid congestion excitation coefficient corresponding to each partition, including: when the grid congestion excitation coefficient indicates that the second partition among the multiple partitions is in a non-blocked state, determining the configuration adjustment strategy of the second partition as: increasing the line occupancy rate of the second partition, and reducing the amount of additional power facilities in the second partition; wherein, increasing the line occupancy rate of the second partition includes: determining the contribution amount corresponding to the second source-load node pair included in the second partition based on the flow contribution information; determining a contribution amount threshold; when the contribution amount corresponding to the second source-load node pair is less than the contribution amount threshold, reducing the excitation signal for the second source-load node pair to obtain a second excitation signal; and using the second excitation signal to increase the line occupancy rate of the second partition.

[0012] According to another aspect of an embodiment of the present application, a device for determining a configuration adjustment strategy of a transmission and distribution network is provided, comprising: a partitioning module, for dividing the transmission and distribution network based on power flow contribution information to obtain a plurality of partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to electric energy transmission; an acquisition module, for acquiring marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes a congestion cost, which is the cost caused by some topological structures in the transmission and distribution network exceeding the transmission capacity limit; a congestion determination module, for determining, based on the marginal electricity price information, grid congestion frequencies corresponding to the plurality of partitions, respectively, wherein the grid congestion frequencies are used to represent grid congestion conditions of the corresponding partitions; a configuration adjustment module, for determining, based on the grid congestion frequencies corresponding to the plurality of partitions, the configuration adjustment strategies corresponding to the plurality of partitions, respectively.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing any one of the methods for determining a configuration adjustment strategy for a transmission and distribution network.

[0014] According to another aspect of an embodiment of the present application, there is provided an electronic device, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the methods for determining a configuration adjustment strategy for a transmission and distribution network.

[0015] In an embodiment of the present application, the transmission and distribution network is divided based on the power flow contribution information to obtain multiple partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to the transmission of electric energy; the marginal electricity price information generated by the transmission and distribution network in the historical time period is obtained, wherein the marginal electricity price information includes the congestion cost, and the congestion cost is the cost caused by the fact that some topological structures in the transmission and distribution network exceed the transmission capacity limit; based on the marginal electricity price information, the grid congestion frequencies corresponding to the multiple partitions are determined, wherein the grid congestion frequencies are used to represent the grid congestion status of the corresponding partitions; based on the grid congestion frequencies corresponding to the multiple partitions, the configuration adjustment strategies corresponding to the multiple partitions are determined. The purpose of optimizing the utilization of transmission and distribution resources in a targeted manner according to the grid congestion situation and improving the operating efficiency of the power system is achieved, and the technical effect of improving the accuracy of the configuration of the transmission and distribution network resources is achieved, thereby solving the technical problem of inaccurate configuration of the transmission and distribution network in the related technology, resulting in unsatisfactory utilization of transmission and distribution resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 It is a flowchart of an optional method for determining a configuration adjustment strategy of a transmission and distribution network provided according to an embodiment of the present application;

[0018] Figure 2 is a schematic diagram of an optional method for determining a configuration adjustment strategy of a transmission and distribution network provided according to an embodiment of the present application;

[0019] Figure 3 It is a schematic diagram of an optional device for determining a configuration adjustment strategy for a transmission and distribution network provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0022] According to an embodiment of the present application, a method embodiment for determining a configuration adjustment strategy for a transmission and distribution network is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0023] Figure 1is a flow chart of a method for determining a configuration adjustment strategy for a transmission and distribution network according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0024] Step S102, dividing the transmission and distribution network into multiple partitions based on the power flow contribution information, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to power transmission;

[0025] It can be understood that in the embodiment of the present application, the transmission and distribution network is divided based on the power flow contribution information to obtain multiple partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to power transmission. This process is essentially to identify the key areas or node pairs that have a significant impact on the operation status of the power grid, especially the congestion status, by analyzing the direct impact of each node and line in the power grid on power transmission.

[0026] Optionally, the above-mentioned power flow contribution information includes but is not limited to the power transmission efficiency of node pairs, the transmission capacity utilization of branches, and the distribution of power transmission in the power grid, providing a detailed data basis for the zoning of the power grid and the formulation of incentive strategies.

[0027] In an optional embodiment, the method also includes: determining the power change between multiple source-load node pairs in the transmission and distribution network, determining the power transfer factors corresponding to the multiple source-load node pairs, wherein the power transfer factors represent the degree of influence of the corresponding source-load node pairs on the power change; obtaining the per-unit transmission capacity of the branches between the multiple source-load node pairs; and determining the power flow contribution information based on the per-unit transmission capacity and the power transfer factors corresponding to the multiple source-load node pairs.

[0028] It can be understood that the power change between multiple source-load node pairs in the transmission and distribution network is determined, and the flow of electric energy from the generation side to the load side in the power grid is quantified, so as to understand the direction and magnitude of electric energy transmission between different node pairs. The power transmission factor reflects the sensitivity and influence of the source-load node pair on the power change in the power grid. Through the power transmission factor, the influence of the source-load node pair on the stability of the power grid and the efficiency of resource utilization can be evaluated. The per-unit value of the branch transmission capacity is a standardized representation of the branch transmission capacity in the power grid, which eliminates the influence of the actual capacity size on the analysis results and makes it possible to compare branches of different sizes. The calculation of the per-unit value is usually based on the benchmark capacity of the power grid, such as converting the transmission capacity of all branches into a relative value relative to the benchmark capacity. Combining the per-unit value of the branch transmission capacity obtained above with the power transmission factor of the source-load node pair, the influence of the source-load node pair on the power grid flow, that is, the power flow contribution information, can be calculated. The actual amount of power transmission between node pairs and the influence of the transmission path on the overall operation of the power grid are combined, which is the basis for evaluating the congestion status of the power grid and formulating incentive strategies.

[0029] Through the above processing, the power transmission characteristics between source-load node pairs and their impact on grid stability and resource utilization efficiency can be accurately captured. The calculation of the power transfer factor and the per-unit value of branch transmission capacity provides a method to quantify the flow of power and resource occupancy in the grid, making it possible to identify which node pairs have a key impact on the operation status of the grid. Based on the analysis of power flow contribution information, the partitioning and incentive strategy formulation of the grid can be further guided to achieve accurate management of grid congestion and efficient allocation of resources.

[0030] Optionally, the power transfer factor is jointly determined by the physical connection characteristics between the source-load node pair (such as line impedance, reactance, etc.) and the operating state of the power grid (such as load distribution, power source type, etc.).

[0031] Optionally, the topological structure model of the transmission and distribution network can be constructed by analogy, and the concept and method of directed graph in graph theory can be used for the analysis of the topological structure of the power grid. The busbars in the transmission and distribution network are regarded as nodes in the directed graph, and the lines in the power grid are regarded as edges of the directed graph. The direction of the edge is determined by the basic flow, and the weight of the edge is equivalent to the power transmission contribution value of the branch. The nodes in the transmission and distribution network can include power nodes and load nodes.

[0032] Optionally, the node flow data at each moment of a typical peak load scenario in a simplified network model can be statistically analyzed and the relevant data can be screened; the sub-category data in the indicator basic data set can be normalized and preprocessed and validity tested as the node flow data set Q1 to obtain flow contribution information.

[0033] Optionally, according to the directed graph topology model of the transmission and distribution network, let the set of multiple power nodes be P, the set of multiple load nodes be L, and (n, m) be used to represent a source-load node pair formed by a certain power node and a load node, where n∈P, m∈L. Search for a feasible path between all elements in a single power node and a load node set, denoted as k, and then traverse all elements in the power node set P to obtain a feasible path between all power nodes and all load nodes. It should be noted that the branch formed in the source-load node pair (n, m) is denoted as ij, i and j represent any node, regardless of whether it is a power node or a load node. The branch ij between the source-load node pair (n, m) is not the same as the feasible path k. In the power grid topology, the physical line directly connected between the source-load node pair (n, m) is called a branch, which is a specific, physically existing path in the power grid. The characteristics of the branch include its transmission capacity, impedance, loss, etc., which directly determine the transmission efficiency and possibility of electric energy on the path. The feasible paths include not only directly connected branches, but also the set of all possible transmission paths of electric energy from n to m, including indirect paths through other nodes. In a complex power grid network, the transmission of electric energy from the power source node to the load node may pass through multiple intermediate nodes and branches.

[0034] In an optional embodiment, based on the per-unit value of the transmission capacity and the power transfer factors corresponding to the multiple source-load node pairs, the power flow contribution information is determined, including: based on the per-unit value of the transmission capacity and the power transfer factors corresponding to the multiple source-load node pairs, the weight coefficients of the branches formed by each node pair in the multiple source-load node pairs are determined; in the case where there are multiple branches formed between each node pair, based on the multiple branches, a feasible path between each node pair is determined, wherein the feasible path is a transmission path in the multiple branches according to the direction of power transmission; the minimum weight coefficient of the feasible path passing through the branches in the multiple branches is determined; based on the minimum weight coefficient of the feasible path, the contribution of each node pair to the power transmission is processed; based on the contribution of each node pair, the power flow contribution information is determined.

[0035] It can be understood that the weight coefficient of each node pair forming a branch is calculated based on the per-unit value of the transmission capacity of the branch and the power transfer factor of the source-load node pair. The weight coefficient reflects the importance and effective utilization of the branch in the process of power transmission and is the basis for subsequent analysis and evaluation. For each source-load node pair (n, m), if there are multiple branches between them, it is necessary to determine the feasible path from n to m. These feasible paths are set according to the direction of power transmission, and the selection of feasible paths takes into account the topological structure and actual operation of the power grid. After determining the feasible path between the source-load node pair, the minimum weight coefficient of all passing branches in the feasible path is calculated. The minimum weight coefficient is a key parameter for evaluating the overall transmission efficiency of the path, reflecting the limitation of the branch with the weakest transmission capacity in the feasible path on the transmission efficiency of the entire path. Based on the minimum weight coefficient of the feasible path, the actual contribution of the source-load node pair to power transmission is processed and calculated. The power transfer factor is taken into account, and the actual transmission efficiency of the branch is also combined, so as to more accurately reflect the role of the node pair in power transmission of the power grid. Based on the contribution of each node pair, the power flow contribution information of the entire power grid is determined.

[0036] By introducing the concepts of weight coefficient, feasible path and minimum weight coefficient, the accuracy and detail of the evaluation of power transmission characteristics of power grid are improved. It can identify the key paths and bottlenecks of power transmission in the power grid, and provide more sophisticated analysis of power grid operation status for power grid operators. By evaluating the contribution of source-load node pairs, node pairs that consume large power grid resources and are prone to blockage can be identified, and then differentiated transmission and distribution price configuration strategies can be implemented for the areas where these node pairs are located. For example, for node pairs with large contributions, the transmission and distribution prices can be increased to encourage adjustments on the generation side and the load side to reduce dependence on key lines; for node pairs with small contributions, lower transmission and distribution prices can be adopted to encourage more power transactions, while avoiding excessive construction of power facilities in areas with sufficient resources.

[0037] Optionally, the power transmission distribution factor matrix A can be used to quantify the change in power of each branch caused by the injection (or outflow) of unit power by each node, and the change in power between nodes. It can be expressed as:

[0038]

[0039] Among them, (n, m) is a source-load node pair; is the change in active power caused by the power change of node pair (n, m) on branch ij; vector A ij∈(n,m) The elements in are the power transfer factors of the node pair (n, m) on branch ij, When unit power is injected into node n, the direct contribution to the power flow on branch ij is, When a unit power is injected into node n, it directly contributes to the power flow on branch ij. When node n transfers power to node m, The larger the value of , the more significantly the power change on branch ij is affected by the power transmission of node pair (n, m). If this value is positive, it means that when node n transmits power to node m, it will increase the power flow on branch ij; if it is negative, it means that this transmission will reduce the power on branch ij. nm is the power variation between the node pair (n, m).

[0040] Define the weight coefficient γ of the edge in the directed graph ij∈(n,m) is (which can be expressed in vector form):

[0041]

[0042] Among them, the vector χ ij The elements in are the transmission capacity of the long-term operation of branch ij, and the benchmark capacity is 100MVA (megavolt-ampere). Based on the nodes, branches, flow directions and weight coefficients of the power grid, according to the definition of directed graphs in graph theory, a directed graph topology model of the power grid is established.

[0043] In an optional embodiment, the topological structure includes multiple source-load node pairs formed by power nodes and load nodes in the transmission and distribution network, the flow contribution information includes the contribution of the multiple source-load node pairs to the power transmission, and the transmission and distribution network is divided based on the flow contribution information to obtain multiple partitions, including: determining the total flow contribution based on the contribution amounts corresponding to the multiple source-load node pairs; determining the excitation factors corresponding to the multiple source-load node pairs according to the proportion of the contribution amounts corresponding to each node pair in the multiple source-load node pairs to the total flow contribution; determining the contribution threshold based on the excitation factors corresponding to the multiple source-load node pairs; dividing the transmission and distribution network according to the contribution threshold and the excitation factors corresponding to the multiple source-load node pairs to obtain multiple partitions.

[0044] It can be understood that the topological structure of the transmission and distribution network is analyzed with a focus on multiple source-load node pairs formed by power nodes and load nodes. These node pairs represent the transmission path of electric energy from the power generation end to the power consumption end. By calculating the contribution of these source-load node pairs to the power transmission, we can have a deeper understanding of the characteristics of the power flow in the power grid and the impact of different paths on the congestion of the power grid. First, the sum of the power flow contributions of all source-load node pairs is calculated. This step helps to establish a global perspective of power transmission in the power grid and understand the proportion of different node pairs in the entire power grid. For each source-load node pair, its incentive factor is the ratio of its power flow contribution to the total power flow contribution. The incentive factor reflects the importance of the node pair in power transmission and can be used for subsequent partitioning and incentive strategy formulation. Based on the distribution of the incentive factor, one or more contribution thresholds are set to distinguish the degree of influence of the node pair on the power grid. This step is the basis of partitioning. By setting the threshold, the node pairs with greater influence on the power grid can be classified into one area, while the node pairs with less influence can be classified into another area. Finally, the transmission and distribution network is partitioned according to the set contribution threshold and the incentive factor of the node pair. Through the above processing, the power grid will be divided into multiple parts. The node pairs in each partition have similar power flow contribution characteristics. Corresponding incentive strategies can be adopted for these parts to optimize the operation and configuration of the power grid.

[0045] Optionally, define the branch flow contribution Mi between a single source-load node pair j∈(n,m) for:

[0046]

[0047] Where k is the kth feasible path between the source-load node pair (n, m); N k is the total number of feasible paths between source-load node pairs (n, m); min,k is the minimum weight coefficient of the branch that the kth feasible path passes through. For a power grid with multiple power sources and multiple load nodes, the branch power flow contribution of the entire network (i.e., the total power flow contribution) M ij for:

[0048]

[0049] The power flow contribution m of node i (regardless of load node or power node) i for: Among them, α is the set of nodes directly connected to node i.

[0050] Optionally, based on the ratio of the power flow contribution between each source-load node pair (n, m) to the branch power flow contribution of the entire network (i.e., the total power flow contribution), the excitation factor θ for the source-load node pair (n, m) to form a line is used. ij∈(n,m) as follows:

[0051]

[0052] Among them, t represents the time point that needs to be accumulated.

[0053] According to the size of the node power flow contribution, the node is divided into Classification:

[0054]

[0055] Among them, The contribution threshold is used to divide multiple source-load node pairs in the transmission and distribution network and the corresponding feasible paths into different partitions. This transmission and distribution network incentive strategy based on topological simplified partitions and flow contribution information can not only accurately identify the key paths of power transmission in the power grid, but also implement differentiated incentive strategies based on the evaluation results of the grid congestion status. Through the calculation of incentive factors and contribution thresholds, it is possible to more accurately determine which areas need to be focused on and which areas can be appropriately relaxed, thereby achieving efficient configuration and optimal utilization of power grid resources.

[0056] Step S104, obtaining marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes congestion cost, which is the cost caused by a part of the topology structure in the transmission and distribution network exceeding the transmission capacity limit;

[0057] It can be understood that the marginal electricity price information generated by the transmission and distribution network in the historical time period is obtained, where the marginal electricity price information includes congestion costs. The marginal electricity price will rise when the transmission capacity of the power grid is limited, forming a congestion cost. The additional cost caused by insufficient transmission capacity in some parts of the power grid is quantified.

[0058] Optionally, a data set Q2 (i.e., the above-mentioned marginal electricity price information) of the nodes of the transmission and distribution network at all times throughout the year is constructed, and the node marginal electricity price clearing data of the transmission and distribution network at multiple time points (8760 time points) throughout the year are counted, and the relevant data are screened; the sub-category data in the indicator basic data set are normalized and preprocessed and validity tested as data set Q2.

[0059] Step S106, based on the marginal electricity price information, determining the grid congestion frequencies corresponding to the plurality of partitions, wherein the grid congestion frequencies are used to indicate the grid congestion status of the corresponding partitions;

[0060] It can be understood that based on the marginal electricity price information, the grid congestion frequencies corresponding to multiple partitions are determined. The grid congestion frequency is the frequency of grid congestion in different partitions within a certain time period, which helps to more objectively evaluate the congestion status of each area of ​​the grid and provide data support for subsequent configuration adjustments.

[0061] Optionally, node electricity prices in the transmission and distribution network tend to be uniform clearing prices in the absence of congestion, while differential clearing prices will be formed in the presence of congestion. The degree of congestion is positively correlated with the price difference between nodes and the number of differential nodes. Therefore, the number and degree of difference of node marginal electricity prices can be used as an indicator to objectively measure and evaluate the degree of transmission congestion. In order to eliminate the impact of price mean fluctuations in different time periods, it is assumed that the node marginal electricity price follows a normal distribution, and the standard deviation is used to measure the degree of price dispersion. In theory, the degree of transmission congestion is positively correlated with the number and standard deviation of node electricity prices, that is, the larger the standard deviation of node electricity prices and the larger the number, the more severe the degree of transmission congestion and the higher the frequency.

[0062] Step S108: determining configuration adjustment strategies corresponding to the plurality of partitions respectively based on the grid blocking frequencies corresponding to the plurality of partitions respectively.

[0063] It can be understood that the configuration adjustment strategies corresponding to the multiple partitions are determined based on the grid congestion frequencies corresponding to the multiple partitions. This means that different incentive measures are taken according to the severity of grid congestion in each region, such as increasing or decreasing transmission and distribution prices, to guide the participants on the power generation and load sides to adjust their behaviors, so as to reduce the occurrence of congestion and improve resource utilization.

[0064] In an optional embodiment, based on the grid congestion frequencies corresponding to the multiple partitions, respectively, configuration adjustment strategies corresponding to the multiple partitions are determined, including: for each of the multiple partitions, determining the marginal electricity price fluctuation parameter of each partition in a predetermined time period, wherein the marginal electricity price fluctuation parameter is associated with the grid congestion condition occurring in the transmission and distribution network; based on the grid congestion frequency and the marginal electricity price fluctuation parameter, determining the grid congestion incentive coefficient corresponding to each partition, wherein the grid congestion incentive coefficient is used to indicate the degree of correlation between the occurrence of the grid congestion state and the occurrence of the marginal electricity price; according to the grid congestion incentive coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the multiple partitions are determined.

[0065] It can be understood that for each partition in the power grid, the fluctuation of the marginal electricity price of its nodes is collected and analyzed within a predetermined time period. The marginal electricity price fluctuation parameter can be a standard deviation, variance, mean or other statistic describing the volatility of electricity prices, which reflects the stability of the power grid operation in the region and the degree of fluctuation of electricity prices when the supply and demand of electricity are unbalanced. Large fluctuations in marginal electricity prices are often closely related to the congestion of the power grid, which means that there may be a mismatch between power supply and load in the partition, or the transmission capacity of the power grid is insufficient. Based on the grid congestion frequency and the marginal electricity price fluctuation parameter, the grid congestion incentive coefficient of each partition is calculated. The grid congestion incentive coefficient comprehensively considers the frequency of grid congestion and the degree of fluctuation of marginal electricity prices when congestion occurs, aiming to quantify the degree of impact of grid congestion on electricity prices. The grid congestion incentive coefficient is also high in areas with high grid congestion frequency and large marginal electricity price fluctuations, which indicates that the operation of the power grid in the area is unstable and easily affected by the imbalance of supply and demand. According to the grid congestion incentive coefficient of each partition, the specific configuration adjustment strategy is determined. For sub-areas with high incentive coefficients, it is possible to consider increasing the transmission and distribution price to encourage the generation and load sides to reduce the use of electricity or increase the production of local electricity, thereby reducing the burden of grid transmission and reducing congestion. For sub-areas with low incentive coefficients, there may be a problem of grid resource redundancy. At this time, it is possible to reduce the transmission and distribution price to encourage more power trading activities while avoiding excessive construction of power facilities.

[0066] Through the above processing, refined control of the grid operation status is achieved, and the transmission and distribution prices can be dynamically adjusted according to the grid congestion frequency and marginal electricity price fluctuation characteristics of different partitions to minimize the occurrence of grid congestion.

[0067] Optionally, first assume that there are multiple nodes in the transmission and distribution network of a certain region, with i as the node identifier, and each node has w node marginal electricity prices at time points every day. The calculation formula for the standard deviation of the node marginal electricity price at time point w in the region is as follows:

[0068]

[0069] Among them, σ w is the standard deviation of the node marginal electricity price in the area at time w; is the marginal electricity price of node i at time w; G i,w is the load of node i at time point w; μ w It is the average value of the marginal electricity price of each node at time w weighted by the transmission volume.

[0070] The calculation formulas for the standard deviation of the node marginal electricity price in the region on a certain day and throughout the year are as follows:

[0071]

[0072]

[0073] In the formula, σ d is the standard deviation of the node marginal electricity price in the area on a certain day; σ y is the standard deviation of the node marginal electricity price in the region throughout the year; G w is the power transmission of all nodes in the area at time w; G d is the power transmission at all time points in the area on a certain day, d represents the day, D d is the daily weight, D w is the weight at a single time point.

[0074] The frequency of node marginal electricity price generation can be used to judge the frequency of transmission congestion in the region. Therefore, the frequency of node marginal electricity price generation in the region throughout the year is f y It measures the frequency of transmission congestion in the area. The calculation formula is as follows:

[0075]

[0076] In the formula, Indicates the node marginal price frequency of node i at time w. If the node marginal price does not exist at this time, that is, it is 0, then it is recorded as 0; if the node marginal price exists at this time, that is, it is not 0, then it is recorded as 1. y ,t d Represents the number of days in a year and the time of day respectively.

[0077] Design the grid congestion incentive coefficient accordingly To assess the grid congestion in the region, it is understandable It is a quantitative value of the congestion situation in the partition, which comprehensively considers the frequency of occurrence of node marginal electricity prices and the impact of the deviation on the number and degree of grid congestion, σ ij∈(n,m) As the standard deviation of the marginal electricity price of all nodes in the partition, the calculation formula is as follows:

[0078]

[0079] The calculated mean and standard deviation are tested using the KS test, and according to the 3σ principle of normal distribution, five transmission congestion state intervals are obtained, such as too severe congestion, relatively severe congestion, occasional congestion, almost no congestion, and too low line utilization. Among them, occasional congestion does not require adjustment. The above μ is μ w .

[0080] The above five intervals are shown in Table 1.

[0081] Table 1 Standard deviation of node electricity prices to judge grid congestion and incentive demand standards

[0082] Standard deviation range Grid congestion status Transmission and distribution price incentives demand (μ+σ,+∞) Too much blockage Drastically reduce blocking (μ+0.5σ,μ+σ) The blockage is more serious Reduce obstruction appropriately (μ-0.5σ,μ+0.5σ) Occasional blocking none (μ-σ,μ-0.5σ) Almost no blocking Appropriately improve line utilization (0,μ-σ) Line utilization is too low Vigorously improve line utilization

[0083] In an optional embodiment, according to the grid congestion excitation coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the multiple partitions are determined, including: when the grid congestion excitation coefficient indicates that the first partition among the multiple partitions is in a congested state, the configuration adjustment strategy of the first partition is determined as: reducing the line occupancy rate of the first partition, and increasing the amount of additional power facilities in the first partition; wherein, reducing the line occupancy rate of the first partition includes: determining the contribution amount corresponding to the first source-load node pair included in the first partition based on the flow contribution information; determining the contribution amount threshold; when the contribution amount corresponding to the first source-load node pair is greater than or equal to the contribution amount threshold, increasing the excitation signal for the first source-load node pair to obtain a first excitation signal; using the first excitation signal to reduce the line occupancy rate of the first partition.

[0084] It can be understood that the configuration adjustment strategies of different partitions are guided by the grid congestion incentive coefficient. When the grid congestion incentive coefficient indicates that the first partition is in a congested state, the following two strategies can be adopted: reducing the line occupancy rate and increasing the amount of additional power facilities. The purpose of reducing the line occupancy rate is to reduce the dependence of the power supply and load nodes in the first partition on the grid line, thereby alleviating the grid congestion in the area. Based on the power flow contribution information, the contribution amount is determined, and the source-load node pair that contributes more to the grid occupancy in the first partition is identified, that is, the first source-load node pair. The contribution amount of the first source-load node pair can be obtained by calculating the weight coefficient of the branch formed by them, and the power transmission situation on different branches. The contribution amount threshold can be set in the manner provided in the above embodiment to distinguish which source-load node pairs have a more significant impact on the grid congestion. For the first source-load node pair whose contribution amount is greater than or equal to the threshold, the incentive signal will be increased. This incentive signal can be a price signal, such as increasing the transmission and distribution price, thereby prompting the power generation side to reduce production, the load side to save energy, or adjusting the power trading time to reduce the use of electricity during peak hours to reduce the occupancy of the line. The increased excitation signal is used to prompt the first source-load node pair to adjust its power transmission or consumption mode to reduce the occupancy of the first partition power grid line. This can be achieved through a user response mechanism and intelligent scheduling.

[0085] Increasing the number of power facilities is a physical improvement to enhance the power transmission capacity of the first district, thereby alleviating congestion. By increasing substations, transmission lines or optimizing the grid structure, the power transmission capacity of the first district can be increased to ensure that the grid can stably meet power demand even during high-load periods.

[0086] Through the configuration adjustment strategy in the above embodiment, accurate intervention in the congestion state of the power grid can be achieved, which not only reduces excessive occupation of lines and alleviates power grid congestion, but also improves the power transmission capacity of the power grid by increasing power facilities, thereby ensuring the stable operation of the power grid.

[0087] In an optional embodiment, according to the grid congestion excitation coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the multiple partitions are determined, including: when the grid congestion excitation coefficient indicates that the second partition among the multiple partitions is in a non-blocked state, the configuration adjustment strategy of the second partition is determined as: increasing the line occupancy rate of the second partition and reducing the amount of additional power facilities in the second partition; wherein, increasing the line occupancy rate of the second partition includes: determining the contribution amount corresponding to the second source-load node pair included in the second partition based on the flow contribution information; determining the contribution amount threshold; when the contribution amount corresponding to the second source-load node pair is less than the contribution amount threshold, reducing the excitation signal for the second source-load node pair to obtain a second excitation signal; and using the second excitation signal to increase the line occupancy rate of the second partition.

[0088] It can be understood that when the grid blocking incentive coefficient indicates that the second partition is in a non-blocked state, the purpose of increasing the line occupancy rate is to utilize the current sufficient grid transmission capacity of the second partition to encourage more electricity trading and transmission, thereby improving the efficiency of grid use. The contribution amount is determined based on the flow contribution information, the second source-load node pair (i.e., the pairing of the power supply node and the load node) is identified, and the specific amount of contribution of these node pairs to the grid transmission is calculated. The contribution amount threshold is determined as above, and for the second source-load node pair whose contribution amount is lower than the threshold, the incentive signal for the second source-load node pair is reduced, such as reducing the transmission and distribution price, or providing other forms of economic incentives to encourage these node pairs to increase electricity transmission or consumption. Through the adjusted incentive signal, the embodiment aims to encourage the second source-load node pair to make more full use of grid resources, thereby increasing the line occupancy rate in the second partition and improving the efficiency of grid use.

[0089] Reducing the number of additional power facilities is intended to avoid unnecessary grid expansion or upgrades in non-congested areas to save costs and resources. By reducing the number of additional power facilities in the second zone, excessive power investment can be avoided and resources can be more efficiently allocated to areas that really need to strengthen grid transmission capacity.

[0090] Optionally, the transmission and distribution price incentives for areas with different congestion levels can be as follows: based on the degree of grid usage by the main load nodes of typical lines and the grid congestion, while incentivizing the construction of different types of power facilities through electricity prices, the grid development plans and actual conditions in different regions should also be considered. Therefore, the expert adjustment coefficient ε is introduced to adjust the actual regional uncertainty, and the transmission and distribution incentive coefficient r considering the congestion signal is obtained.ij∈(n,m) As shown below:

[0091]

[0092] Under different blocking conditions, the occupancy of the power grid by different load nodes should be further differentiated, as shown in Table 2 below.

[0093] Table 2 Applicability of incentive mechanisms under different grid occupancy levels

[0094]

[0095] When the power grid is in a blocked state, the blocking judgment coefficient (σ-μ)>0, then r ij∈(n,m) >0, indicating that the transmission and distribution price will be increased, thereby guiding both the generation and consumption sides to reduce the occupancy of line ij and encouraging the power grid to increase investment in the area to alleviate congestion.

[0096] This indicates that the power flow of this line exceeds the average level of the network, and the incentive level should be increased. This indicates that the power flow occupancy of the line is lower than the network average and the incentive level should be reduced.

[0097] When the power grid is in surplus state, the blocking judgment coefficient (σ-μ) < 0, then r ij∈(n,m) <0, indicating that the transmission and distribution price is reduced, thereby guiding both the power generation and consumption sides to increase the use of line ij and restraining the grid's investment in this area to reduce redundancy.

[0098] at this time, This indicates that the power flow occupancy of the line is higher than the average level of the network, and the incentive level should be reduced. This indicates that the power flow occupancy of the line is lower than the network average and the incentive level should be increased.

[0099] Optionally, the first excitation signal and the second excitation signal may be configuration modes of the transmission and distribution price, for example, the transmission and distribution price P is finally formed. T&D As shown below:

[0100] P T&D =(C+R+T) / Q

[0101] R=A×η×r ij∈(n,m)

[0102] In the formula, C, R, T, and Q represent the permitted cost, permitted income, price-inclusive tax, and transmission and distribution volume, respectively. The permitted income R is calculated by multiplying the effective asset A by the permitted rate of return η, and is calculated by the transmission and distribution incentive coefficient r ij∈(n,m)Corrective adjustments are made to configure incentive technologies into transmission and distribution prices as a step towards implementing a configuration adjustment strategy.

[0103] Through the above step S102, the transmission and distribution network is divided based on the power flow contribution information to obtain multiple partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to the transmission of electric energy; step S104, the marginal power price information generated by the transmission and distribution network in the historical time period is obtained, wherein the marginal power price information includes the blocking cost, which is the cost caused by the part of the topological structure in the transmission and distribution network exceeding the transmission capacity limit; step S106, based on the marginal power price information, the power grid blocking frequency corresponding to the multiple partitions is determined, wherein the power grid blocking frequency is used to indicate the power grid blocking status of the corresponding partition; step S108, based on the power grid blocking frequency corresponding to the multiple partitions, the configuration adjustment strategy corresponding to the multiple partitions is determined. It can achieve the purpose of optimizing the utilization of transmission and distribution resources in a targeted manner according to the power grid blocking situation and improving the operation efficiency of the power system, and achieve the technical effect of improving the accuracy of the configuration of the transmission and distribution network resources, thereby solving the technical problem of inaccurate configuration of the transmission and distribution network in the related technology, resulting in unsatisfactory utilization of transmission and distribution resources.

[0104] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation mode: Figure 2 is a schematic diagram of an optional method for determining a configuration adjustment strategy of a transmission and distribution network provided in an embodiment of the present application, such as Figure 2 The steps shown are described below.

[0105] Step S1, constructing a topological structure model of the power grid. The topological structure model of the transmission and distribution network can be constructed by analogy, and the concept and method of directed graph in graph theory can be used for the analysis of the topological structure of the power grid. The busbars in the transmission and distribution network are regarded as nodes in a directed graph, and the lines in the power grid are regarded as edges of the directed graph. The direction of the edge is determined by the basic flow, and the weight of the edge is equivalent to the power transmission contribution value of the branch. The nodes in the transmission and distribution network can include power nodes and load nodes.

[0106] The power transmission distribution factor matrix A can be used to quantify the change in power of each branch caused by the injection (or outflow) of unit power by each node, and the change in power between nodes. It can be expressed as:

[0107]

[0108] Among them, (n, m) is a source-load node pair; is the change in active power caused by the power change of node pair (n, m) on branch ij; vector A ij∈(n,m) The elements in are the power transfer factors of the node pair (n, m) on branch ij, When unit power is injected into node n, the direct contribution to the power flow on branch ij is, When a unit power is injected into node n, it directly contributes to the power flow on branch ij. When node n transfers power to node m, The larger the value of , the more significantly the power change on branch ij is affected by the power transmission of node pair (n, m). If this value is positive, it means that when node n transmits power to node m, it will increase the power flow on branch ij; if it is negative, it means that this transmission will reduce the power on branch ij. nm is the power variation between the node pair (n, m).

[0109] Define the weight coefficient γ of the edge in the directed graph ij∈(n,m) is (which can be expressed in vector form):

[0110]

[0111] Among them, the vector χ ij The elements in are the transmission capacity of the long-term operation of branch ij, and the benchmark capacity is 100MVA (megavolt-ampere). Based on the nodes, branches, flow directions and weight coefficients of the power grid, according to the definition of directed graphs in graph theory, a directed graph topology model of the power grid is established.

[0112] Step S2, constructing a node flow data set Q1 in a simplified network model, can count the node flow data at each moment of a typical peak load scenario in the simplified network model, and screen the relevant data; perform normalization and standardization preprocessing and validity verification on each subcategory data in the indicator basic data set as the node flow data set Q1, which is used to obtain flow contribution information.

[0113] Step S3, calculate the contribution of the node flow in the simplified network model. According to the directed graph topology model of the power transmission and distribution network in step S1, let the set of multiple power nodes be P, the set of multiple load nodes be L, and (n, m) be used to represent the source-load node pair formed by a certain power node and a load node, where n∈P, m∈L. Search for the feasible path between all elements in the single power node and the load node set, denoted as k, and then traverse all elements in the power node set P to obtain the feasible path between all power nodes and all load nodes. It should be noted that the branch formed in the source-load node pair (n, m) is denoted as ij, i and j represent any node, regardless of whether it is a power node or a load node. The branch ij between the source-load node pair (n, m) is not the same as the feasible path k. In the power grid topology, the physical line directly connected between the source-load node pair (n, m) is called a branch, which is a specific, physically existing path in the power grid. The characteristics of a branch include its transmission capacity, impedance, loss, etc. These characteristics directly determine the efficiency and possibility of power transmission on the path. A feasible path includes not only directly connected branches, but also a collection of all possible transmission paths for power from n to m, including indirect paths through other nodes. In a complex power grid network, power transmission from a power source node to a load node may pass through multiple intermediate nodes and branches.

[0114] Define the branch flow contribution M between a single source-load node pair ij∈(n,m) for:

[0115]

[0116] Where k is the kth feasible path between the source-load node pair (n, m); N k is the total number of feasible paths between source-load node pairs (n, m); min,k is the minimum weight coefficient of the branch that the kth feasible path passes through. For a power grid with multiple power sources and multiple load nodes, the branch power flow contribution of the entire network (i.e., the total power flow contribution) M ij for:

[0117]

[0118] The power flow contribution m of node i (regardless of load node or power node) i for: Among them, α is the set of nodes directly connected to node i.

[0119] Step S4, based on the node power flow contribution, simplify and classify the source and load nodes of the transmission and distribution network topology.

[0120] Based on step S3, the ratio of the power flow contribution between each source-load node pair (n, m) to the branch power flow contribution of the entire network (i.e., the total power flow contribution) is calculated as the excitation factor θ of the line formed by the source-load node pair (n, m). ij∈(n,m) as follows:

[0121]

[0122] Among them, t represents the time point that needs to be accumulated.

[0123] According to the size of the node power flow contribution, the node is divided into Classification:

[0124]

[0125] Among them, The contribution threshold is used to divide multiple source-load node pairs in the transmission and distribution network and the corresponding feasible paths into different partitions. This transmission and distribution network incentive strategy based on topological simplified partitions and flow contribution information can not only accurately identify the key paths of power transmission in the power grid, but also implement differentiated incentive strategies based on the evaluation results of the grid congestion status. Through the calculation of incentive factors and contribution thresholds, it is possible to more accurately determine which areas need to be focused on and which areas can be appropriately relaxed, thereby achieving efficient configuration and optimal utilization of power grid resources.

[0126] Step S5, construct the marginal electricity price data set Q2 (i.e. the above-mentioned marginal electricity price information) of the nodes of the transmission and distribution network at all times throughout the year, count the node marginal electricity price clearing data of the transmission and distribution network at multiple time points (8760 time points) throughout the year, and screen the relevant data; perform normalization and standardization preprocessing and validity inspection on each sub-category data in the indicator basic data set as data set Q2.

[0127] Step S6, measure and evaluate the congestion status of the transmission and distribution network area. The node electricity prices in the transmission and distribution network tend to be unified clearing prices when there is no congestion, but will form differential clearing prices when there is congestion. The degree of congestion is positively correlated with the price difference between nodes and the number of differential nodes. Therefore, the number and degree of difference of node marginal electricity prices can be used as indicators for objective measurement and evaluation of the degree of transmission congestion. In order to eliminate the impact of price mean fluctuations in different time periods, it is assumed that the node marginal electricity price follows a normal distribution, and the standard deviation is used to measure the degree of price dispersion. In theory, the degree of transmission congestion is positively correlated with the number and standard deviation of node electricity prices, that is, the larger the standard deviation of node electricity prices and the larger the number, the more severe the degree of transmission congestion and the higher the frequency.

[0128] First, assume that there are multiple nodes in a certain area's transmission and distribution network, with i as the node identifier. Each node has w node marginal electricity prices at time points every day. The calculation formula for the standard deviation of the node marginal electricity price at time point w in the region is as follows:

[0129]

[0130] Among them, σ w is the standard deviation of the node marginal electricity price in the area at time w; is the marginal electricity price of node i at time w; G i,w is the load of node i at time point w; μ w It is the average value of the marginal electricity price of each node at time w weighted by the transmission volume.

[0131] The calculation formulas for the standard deviation of the node marginal electricity price in the region on a certain day and throughout the year are as follows:

[0132]

[0133]

[0134] In the formula, σ d is the standard deviation of the node marginal electricity price in the area on a certain day; σ y is the standard deviation of the node marginal electricity price in the region throughout the year; G w is the power transmission of all nodes in the area at time w; G d is the power transmission at all time points in the area on a certain day, d represents the day, D d is the daily weight, D w is the weight at a single time point.

[0135] The frequency of node marginal electricity price generation can be used to judge the frequency of transmission congestion in the region. Therefore, the frequency of node marginal electricity price generation in the region throughout the year is f y It measures the frequency of transmission congestion in the area. The calculation formula is as follows:

[0136]

[0137] In the formula, Indicates the node marginal price frequency of node i at time w. If the node marginal price does not exist at this time, that is, it is 0, then it is recorded as 0; if the node marginal price exists at this time, that is, it is not 0, then it is recorded as 1. y ,t d Represents the number of days in a year and the time of day respectively.

[0138] Design the grid congestion incentive coefficient accordingly To assess the grid congestion in the region, it is understandable It is a quantitative value of the congestion situation in the partition, which comprehensively considers the frequency of occurrence of node marginal electricity prices and the impact of the deviation on the number and degree of grid congestion, σ ij∈(n,m) As the standard deviation of the marginal electricity price of all nodes in the partition, the calculation formula is as follows:

[0139]

[0140] The calculated mean and standard deviation are tested using the KS test, and according to the 3σ principle of normal distribution, five transmission congestion state intervals are obtained, such as too severe congestion, relatively severe congestion, occasional congestion, almost no congestion, and too low line utilization. Among them, occasional congestion does not require adjustment. The above μ is μ w .

[0141] Step S7, based on the calculation results in the above steps S1-S6, provide transmission and distribution price incentives to areas with different congestion levels.

[0142] The transmission and distribution price incentives for areas with different congestion levels can be as follows: based on the degree of grid usage and grid congestion of the main load nodes of typical lines, while incentivizing the construction of different types of power facilities through electricity prices, the grid development plans and actual conditions in different regions should also be considered. Therefore, the expert adjustment coefficient ε is introduced to adjust the actual regional uncertainty, and the transmission and distribution incentive coefficient r considering the congestion signal is obtained. ij∈(n,m) As shown below:

[0143]

[0144] Under different blocking conditions, the occupancy of the power grid by different load nodes should be further differentiated, as shown in Table 1.

[0145] When the power grid is in a blocked state, the blocking judgment coefficient (σ-μ)>0, then r ij∈(n,m) >0, indicating that the transmission and distribution price will be increased, thereby guiding both the generation and consumption sides to reduce the occupancy of line ij and encouraging the power grid to increase investment in the area to alleviate congestion.

[0146] This indicates that the power flow of this line exceeds the average level of the network, and the incentive level should be increased. This indicates that the power flow occupancy of the line is lower than the network average and the incentive level should be reduced.

[0147] When the power grid is in surplus state, the blocking judgment coefficient (σ-μ) < 0, then r ij∈(n,m) <0, indicating that the transmission and distribution price is reduced, thereby guiding both the power generation and consumption sides to increase the use of line ij and restraining the grid's investment in this area to reduce redundancy.

[0148] at this time, This indicates that the power flow occupancy of the line is higher than the average level of the network, and the incentive level should be reduced. This indicates that the power flow occupancy of the line is lower than the network average and the incentive level should be increased.

[0149] The first excitation signal and the second excitation signal may be configuration modes of the transmission and distribution price, for example, the transmission and distribution price P is finally formed. T&D As shown below:

[0150] P T&D =(C+R+T) / Q

[0151] R=A×η×r ij∈(n,m)

[0152] In the formula, C, R, T, and Q represent the permitted cost, permitted income, price-inclusive tax, and transmission and distribution volume, respectively. The permitted income R is calculated by multiplying the effective asset A by the permitted rate of return η, and is calculated by the transmission and distribution incentive coefficient r ij∈(n,m) Corrective adjustments are made to configure incentive technologies into transmission and distribution prices as a step towards implementing a configuration adjustment strategy.

[0153] The above optional implementation method achieves at least the following effects: the purpose of improving the accuracy of the resource configuration of the transmission and distribution network is achieved, the technical effect of optimizing the utilization of transmission and distribution resources and improving the operating efficiency of the power system is achieved, and the technical problem of inaccurate configuration of the transmission and distribution network in related technologies, resulting in unsatisfactory utilization of transmission and distribution resources, is solved. By accurately identifying the blocking points and key transmission paths of the power grid and combining historical marginal electricity price data, it is possible to more effectively allocate power grid resources, reduce unnecessary investment and operating costs, and at the same time ensure the safe and stable operation of the power grid, and improve the economy and sustainability of the power market.

[0154] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0155] In this embodiment, a device for determining a configuration adjustment strategy for a transmission and distribution network is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the terms "module" and "device" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0156] According to an embodiment of the present application, there is also provided an embodiment of a device for implementing a method for determining a configuration adjustment strategy of a transmission and distribution network. Figure 3 is a schematic diagram of a device for determining a configuration adjustment strategy for a transmission and distribution network according to an embodiment of the present application, such as Figure 3 As shown, the above-mentioned device for determining the configuration adjustment strategy of the transmission and distribution network includes: a partition module 302, an acquisition module 304, a blocking determination module 306, and a configuration adjustment module 308. The device is described below.

[0157] A partitioning module 302 is used to divide the transmission and distribution network into multiple partitions based on the power flow contribution information, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to power transmission;

[0158] An acquisition module 304, connected to the partition module 302, is used to obtain marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes a congestion cost, which is a cost caused by a part of the topology structure in the transmission and distribution network exceeding the transmission capacity limit;

[0159] A congestion determination module 306, connected to the acquisition module 304, is used to determine the grid congestion frequencies corresponding to the plurality of partitions respectively based on the marginal electricity price information, wherein the grid congestion frequencies are used to indicate the grid congestion status of the corresponding partitions;

[0160] The configuration adjustment module 308 is connected to the congestion determination module 306 and is used to determine the configuration adjustment strategies corresponding to the multiple partitions respectively based on the power grid congestion frequencies corresponding to the multiple partitions respectively.

[0161] In a device for determining a configuration adjustment strategy of a transmission and distribution network provided in an embodiment of the present application, a partitioning module 302 is set to divide the transmission and distribution network based on power flow contribution information to obtain multiple partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to electric energy transmission; an acquisition module 304 is connected to the partitioning module 302, and is used to obtain marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes a congestion cost, which is the cost caused by some topological structures in the transmission and distribution network exceeding the transmission capacity limit; a congestion determination module 306 is connected to the acquisition module 304, and is used to determine the power grid congestion frequencies corresponding to the multiple partitions based on the marginal electricity price information, wherein the power grid congestion frequency is used to indicate the power grid congestion status of the corresponding partition; a configuration adjustment module 308 is connected to the congestion determination module 306, and is used to determine the configuration adjustment strategies corresponding to the multiple partitions based on the power grid congestion frequencies corresponding to the multiple partitions. The purpose of optimizing the utilization of transmission and distribution resources according to the grid congestion situation and improving the operating efficiency of the power system was achieved, and the technical effect of improving the accuracy of the allocation of transmission and distribution network resources was realized, thereby solving the technical problem of inaccurate transmission and distribution network configuration in related technologies, resulting in unsatisfactory utilization of transmission and distribution resources.

[0162] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0163] It should be noted that the partition module 302, the acquisition module 304, the blocking determination module 306, and the configuration adjustment module 308 correspond to steps S102 to S108 in the embodiment, and the examples and application scenarios implemented by the modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the modules as part of the device can be run in a computer terminal.

[0164] It should be noted that the optional or preferred implementation of this embodiment can refer to the relevant description in the embodiment, which will not be repeated here.

[0165] The configuration adjustment strategy determination device of the above-mentioned transmission and distribution network may also include a processor and a memory. The partitioning module 302, the acquisition module 304, the blocking determination module 306, the configuration adjustment module 308, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0166] The processor includes a kernel, which retrieves the corresponding program unit from the memory. There can be one or more kernels. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0167] An embodiment of the present application provides a non-volatile storage medium having a program stored thereon, which, when executed by a processor, implements a method for determining a configuration adjustment strategy for a transmission and distribution network.

[0168] The embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the steps of the method for determining the configuration adjustment strategy of the transmission and distribution network when executing the program. The device in this article can be a server, a PC, etc.

[0169] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following steps of a method for determining a configuration adjustment strategy for a transmission and distribution network.

[0170] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0171] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0172] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0173] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0174] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0175] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0176] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0177] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0178] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0179] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining a configuration adjustment strategy for a transmission and distribution network, characterized in that: include: Based on the power flow contribution information, the transmission and distribution network is divided into a plurality of partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to power transmission; Obtain marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes congestion cost, which is the cost caused by a part of the topology structure in the transmission and distribution network exceeding the transmission capacity limit; Based on the marginal electricity price information, determining the grid congestion frequencies corresponding to the plurality of partitions respectively, wherein the grid congestion frequencies are used to indicate grid congestion conditions of the corresponding partitions; Based on the grid blocking frequencies respectively corresponding to the multiple partitions, configuration adjustment strategies respectively corresponding to the multiple partitions are determined.

2. The method according to claim 1, characterized in that The topological structure includes a plurality of source-load node pairs formed by power source nodes and load nodes in the transmission and distribution network, the power flow contribution information includes the contribution amounts of the plurality of source-load node pairs to the power transmission respectively, and the transmission and distribution network is divided based on the power flow contribution information to obtain a plurality of partitions, including: Determine the total tidal flow contribution based on the contributions of the plurality of source-load node pairs respectively corresponding to the respective contributions; Determine the excitation factors corresponding to the multiple source-load node pairs respectively according to the proportion of the contribution amount corresponding to each node pair in the multiple source-load node pairs to the total power flow contribution amount; Determining contribution thresholds based on the incentive factors corresponding to the plurality of source-load node pairs respectively; The transmission and distribution network is divided according to the contribution threshold and the incentive factors corresponding to the multiple source-load node pairs to obtain the multiple partitions.

3. The method according to claim 1, characterized in that The method further comprises: Determine the power change between multiple source-load node pairs in the transmission and distribution network, and determine the power transfer factors corresponding to the multiple source-load node pairs, wherein the power transfer factors represent the influence of the corresponding source-load node pairs on the power change; Obtaining per-unit values ​​of transmission capacities of branches between the plurality of source-load node pairs; The power flow contribution information is determined based on the transmission capacity per unit value and the power transmission factors respectively corresponding to the plurality of source-load node pairs.

4. The method according to claim 3, characterized in that: The determining the power flow contribution information based on the transmission capacity per unit value and the power transmission factors respectively corresponding to the plurality of source-load node pairs includes: Determine a weight coefficient of a branch formed by each node pair in the plurality of source-load node pairs based on the transmission capacity per unit value and the power transmission factors corresponding to the plurality of source-load node pairs respectively; In the case where there are multiple branches formed between each node pair, determining a feasible path between each node pair based on the multiple branches, wherein the feasible path is a transmission path in the multiple branches according to the power transmission direction; Determine a minimum weight coefficient of a branch that the feasible path passes through among the multiple branches; Processing based on the minimum weight coefficient of the feasible path, the contribution of each node pair to the power transmission; The power flow contribution information is determined based on the contribution of each node pair.

5. The method according to any one of claims 1 to 4, characterized in that: The determining, based on the grid blocking frequencies respectively corresponding to the plurality of partitions, the configuration adjustment strategies respectively corresponding to the plurality of partitions comprises: For each of the plurality of subareas, determining a marginal electricity price fluctuation parameter of the each subarea in a predetermined time period, wherein the marginal electricity price fluctuation parameter is associated with a grid congestion condition occurring in the transmission and distribution network; Based on the grid congestion frequency and the marginal electricity price fluctuation parameter, determining a grid congestion incentive coefficient corresponding to each partition, wherein the grid congestion incentive coefficient is used to indicate the degree of correlation between the occurrence of a grid congestion state and the occurrence of a marginal electricity price; According to the grid congestion excitation coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the multiple partitions are determined.

6. The method according to claim 5, characterized in that The determining, according to the grid blocking excitation coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the plurality of partitions respectively includes: When the grid blocking excitation coefficient indicates that a first partition among the multiple partitions is in a blocking state, determining the configuration adjustment strategy of the first partition is: reducing the line occupancy rate of the first partition and increasing the amount of additional power facilities in the first partition; Among them, the reducing of the line occupancy rate of the first partition includes: determining the contribution amount corresponding to the first source-load node pair included in the first partition based on the flow contribution information; determining a contribution amount threshold; when the contribution amount corresponding to the first source-load node pair is greater than or equal to the contribution amount threshold, increasing the excitation signal for the first source-load node pair to obtain a first excitation signal; using the first excitation signal to reduce the line occupancy rate of the first partition.

7. The method according to claim 5, characterized in that The determining, according to the grid blocking excitation coefficient corresponding to each partition, the configuration adjustment strategies corresponding to the plurality of partitions respectively includes: When the grid blocking excitation coefficient indicates that a second partition among the multiple partitions is in a non-blocked state, determining the configuration adjustment strategy of the second partition is: increasing the line occupancy rate of the second partition and reducing the amount of additional power facilities in the second partition; Among them, the increasing of the line occupancy rate of the second partition includes: determining the contribution amount corresponding to the second source-load node pair included in the second partition based on the flow contribution information; determining a contribution amount threshold; when the contribution amount corresponding to the second source-load node pair is less than the contribution amount threshold, reducing the excitation signal for the second source-load node pair to obtain a second excitation signal; using the second excitation signal to increase the line occupancy rate of the second partition.

8. A device for determining a configuration adjustment strategy for a transmission and distribution network, characterized in that: include: A partitioning module, used for partitioning the transmission and distribution network based on power flow contribution information to obtain a plurality of partitions, wherein the power flow contribution information includes the contribution of different topological structures in the transmission and distribution network to power transmission; An acquisition module, configured to acquire marginal electricity price information generated by the transmission and distribution network in a historical time period, wherein the marginal electricity price information includes a congestion cost, which is a cost caused by a part of the topology structure in the transmission and distribution network exceeding a transmission capacity limit; A congestion determination module, configured to determine the grid congestion frequencies corresponding to the plurality of partitions respectively based on the marginal electricity price information, wherein the grid congestion frequencies are used to indicate grid congestion conditions of the corresponding partitions; The configuration adjustment module is used to determine the configuration adjustment strategies corresponding to the multiple partitions respectively based on the grid blocking frequencies corresponding to the multiple partitions respectively.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by the method for determining a configuration adjustment strategy for a transmission and distribution network as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining a configuration adjustment strategy for a transmission and distribution network as described in any one of claims 1 to 7.

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