Power-carbon collaborative power distribution network dynamic partition management method and system

Abstract

The invention discloses a dynamic partition management method and system for an electricity-carbon cooperative power distribution network, and relates to the technical field of power distribution network partition management, and the method comprises the following steps: obtaining a first constraint condition, and carrying out the initial division of the power distribution network, and obtaining an initial partition set; performing state evaluation on the initial partition set, and correcting the initial partitions by adopting an improved greedy algorithm according to an evaluation result; extending adjacent regions outwards layer by layer from the corrected subregions, and performing electricity-carbon relation analysis on each layer of subregion by adopting an analytic hierarchy process; according to an analysis result, judging whether to continue hierarchical expansion and update a correction range; the partition boundary is dynamically adjusted according to the correction range, partition management is performed according to the adjustment result, and the problems that when partition division is performed on an existing power distribution network, the division rule is fixed, and the real-time scheduling requirement cannot be met are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network zoning management, and more specifically, to a method and system for dynamic zoning management of an electric-carbon coordinated distribution network. Background Art

[0002] As a key part of the power system, the distribution network is responsible for energy distribution and dispatching. With the access of distributed energy, renewable energy and smart devices, the distribution network faces increasingly complex dispatching and load management problems. At the same time, the carbon emission problem has become a challenge that needs to be solved urgently in the global power industry. Traditional power dispatching methods often ignore carbon emission control, resulting in low energy efficiency and high emission levels. Therefore, how to achieve the coordinated optimization of power dispatching and carbon emissions in the distribution network has become an important issue in the current power system research. Dynamic zoning management of the power-carbon coordinated distribution network is one of the important technical paths to achieve the green transformation of the power system. With the increasing global demand for sustainable development, the traditional power system has gradually exposed the problem of lack of effective control and optimized dispatching of carbon emissions. In this context, the power-carbon coordinated distribution network came into being, aiming to achieve the coordinated optimization of high efficiency of power supply and low carbon emissions through real-time monitoring and intelligent dispatching of the distribution network.

[0003] For example, the invention patent with announcement number: CN113239540B announces a method and system for dynamic planning of urban distribution network lines, which divides the planning period into multiple time periods; obtains the regional street layout and load power data within the set time period, and models the regional street layout; processes the load of each block in the planning area; takes the minimum load moment as the optimization goal, considers the line non-crossing constraint, and establishes a distribution network line dynamic planning model for different time periods; processes the nonlinear part in the distribution network line dynamic planning model and converts it into a mixed integer linear programming model; solves the converted model to obtain the optimal distribution network line dynamic planning solution. The present invention considers the line non-crossing constraint, can improve the reliability of the distribution line, and can make the boundaries of each distribution line clear, which is convenient for zoning management; and solves the distribution network management personnel's demand for non-crossing distribution lines.

[0004] For example, the invention patent with announcement number CN114861459A announces a method for dynamic partitioning of distribution network based on improved VVS calculation model, which calculates voltage / reactive sensitivity matrix between nodes by adding voltage reactive output perturbation to reactive source; secondly, fuzzifies voltage / reactive sensitivity matrix to obtain membership matrix between nodes; and analyzes membership relationship between reactive source nodes according to membership matrix between nodes, and pre-partitions reactive source nodes; then, analyzes membership relationship between load nodes and reactive source nodes according to membership matrix between nodes, and determines partitioning result; finally, constructs partitioning membership index to evaluate partitioning result, and ensures reactive balance within partition. The present invention calculates VVS of each reactive source to other nodes by adding voltage reactive output perturbation to reactive source, which can reflect the temporal changes of power supply and load, and better ensures reasonable distribution of voltage reactive power within each partition.

[0005] The above disclosed technical solutions have at least the following technical problems: The existing distribution network zoning method is based on electrical characteristics or static load distribution, lacks a dynamic response mechanism to carbon emissions, and the zoning rules are fixed when zoning is performed, which cannot adapt to real-time scheduling requirements. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for dynamic zoning management of an electricity-carbon coordinated distribution network, which dynamically adjusts the partition boundaries through a hierarchical correction and overlap detection mechanism to solve the problem that the existing distribution network has fixed zoning rules and cannot adapt to real-time scheduling needs when zoning.

[0007] To achieve the above object, the present invention provides the following technical solutions: A method for dynamic partition management of an electricity-carbon coordinated distribution network comprises the following steps: obtaining a first constraint condition, and initially dividing the distribution network to obtain an initial partition set; performing a state evaluation on the initial partition set, and correcting the initial partition using an improved greedy algorithm according to the evaluation result; expanding the corrected partition outward to adjacent areas layer by layer, and performing an electricity-carbon relationship analysis on each partition layer using a hierarchical analysis method; judging whether to continue the hierarchical expansion and updating the correction range according to the analysis result; dynamically adjusting the partition boundary according to the correction range, and performing partition management according to the adjustment result.

[0008] In a preferred embodiment, the obtaining of the first constraint condition is specifically as follows: obtaining the historical operation data of the distribution network and performing data analysis to obtain the load fluctuation range and carbon emission intensity of each node; constructing the distribution network topology, and combining the load fluctuation range and carbon emission intensity of each node to calculate the maximum allowable number of partitions supported by the system and the upper limit of dynamic partitions that meet the carbon emission constraints; determining the minimum number of partitions supported by the system according to the topological connectivity of the distribution network topology; constructing the first constraint condition according to the maximum allowable number of partitions, the upper limit of dynamic partitions that meet the carbon emission constraints, and the minimum number of partitions.

[0009] In a preferred embodiment, the initial division of the distribution network to obtain an initial partition set is specifically: calculating the node electricity-carbon coupling intensity matrix, and clustering the distribution network nodes in combination with the spectral clustering algorithm to obtain a first partition set; setting a minimum partition capacity threshold, merging partitions in the first partition set whose capacity is lower than the threshold, until the number of partitions meets the first constraint condition, to obtain an initial partition set.

[0010] In a preferred embodiment, the state of the initial partition set is evaluated, and the initial partition is corrected by using an improved greedy algorithm according to the evaluation result, specifically: a partition state evaluation index system is constructed and the weight of each index is calculated by using the entropy weight method, and the index value of each partition is weighted summed based on the index weight to obtain the state evaluation value of the partition; according to the state evaluation value, the partition is identified as abnormal, and the adjacent node set of the abnormal partition is extracted; the adjacent nodes are added to the abnormal partition by using the greedy algorithm, and the number of newly added nodes is counted; a dynamic second constraint condition is constructed according to the change in the ratio of the number of newly added nodes to the number of partition nodes; based on the dynamic second constraint condition, the initial partition is corrected to obtain a corrected partition.

[0011] In a preferred embodiment, the modified partition is expanded outward to adjacent areas layer by layer, and the hierarchical analysis method is used to perform an electricity-carbon relationship analysis on each partition layer, specifically: the modified partition is used as the parent layer and the coupling strength values ​​of all nodes in the parent layer partition are calculated, and the corresponding nodes are selected as core nodes based on the coupling strength values; the power grid topology diagram of the parent layer is obtained, and the Dijkstra algorithm is used to calculate the shortest path hops from each node to the core node; the maximum value of the shortest path hops from all nodes to the core node is used as the initial expansion radius; according to the initial expansion radius, the parent layer is expanded outward to adjacent areas layer by layer to obtain several sublayers; the electricity-carbon interaction matrix of each sublayer and the parent layer is constructed, and the eigenvalue of the electricity-carbon interaction matrix is ​​solved based on the hierarchical analysis method to obtain the layer-associated eigenvalue.

[0012] In a preferred embodiment, the method determines whether to continue the layered expansion and update the correction range based on the analysis results, specifically: obtaining the sublayer to be corrected based on the layer-associated characteristic value, and adding the sublayer to be corrected to the preset correction range set; detecting the overlapping areas between the partitions of the sublayer to be corrected in the correction range set and the partitions of the parent layer; merging the overlapping partitions with the partitions of the parent layer based on the detection results, and updating the correction range set.

[0013] In a preferred embodiment, the partition boundaries are dynamically adjusted according to the correction range, and the partition management is performed according to the adjustment results, specifically: the partition boundaries are dynamically adjusted according to the correction range, and the dynamic partitioning results are used to generate partition scheduling instructions, wherein the instructions include the carbon emission quota, load adjustment priority and spare capacity allocation strategy of the power generation units in each partition; the partition operation data is collected in real time during the scheduling process. If it is detected that the carbon emission or load exceeds the limit, the partition re-division process is triggered and the scheduling instructions are updated.

[0014] The technical effects and advantages of the method and system for dynamic partition management of an electric-carbon coordinated distribution network of the present invention are as follows: 1. The present invention constructs the first constraint condition by acquiring historical operation data, comprehensively considers the node load volatility and carbon emission intensity, and determines the minimum, maximum and carbon constraint numbers of partitions through topological structure analysis, effectively improving the feasibility and rationality of the partitions; the electric-carbon coupling intensity matrix and the improved spectral clustering algorithm are used to realize the initial partition division, which not only ensures the intrinsic correlation between the nodes in energy consumption and carbon emissions, but also avoids the formation of too small isolated areas through the minimum capacity threshold control, thereby improving the partition stability and resource allocation efficiency.

[0015] 2. In the partition correction stage, the present invention introduces the entropy weight method to construct a multi-index state evaluation system, comprehensively quantifies the partition state, effectively identifies abnormal areas, and performs targeted corrections through the improved greedy algorithm, ensuring that the partition structure achieves the optimal compromise between operational stability and carbon efficiency, and enhancing the dynamic adaptability of the system; further, the hierarchical analysis method is used to perform hierarchical electricity-carbon relationship analysis on the corrected partitions, and the expansion boundaries are accurately delineated by the Dijkstra algorithm, and the electricity-carbon interaction matrix is ​​constructed and the eigenvalues ​​are extracted, and the electricity-carbon synergy characteristics between each layer are systematically revealed, providing a quantitative basis for subsequent expansion and boundary adjustment, and realizing rational decision-making and dynamic tuning of the expansion process; in addition, the partition boundaries are dynamically adjusted through hierarchical correction and overlap detection mechanisms to avoid unreasonable overlap or breakage between partitions, thereby improving the consistency and scheduling accuracy of the partition results. In terms of scheduling applications, the method generates scheduling instructions containing key parameters such as carbon emission quotas, load priorities, and backup strategies from the partition results, and has real-time monitoring and adaptive re-division capabilities, realizing intelligent scheduling, low-carbonization, and high-toughness operation of the distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for dynamic partition management of an electricity-carbon coordinated distribution network according to the present invention.

[0017] Figure 2 This is a structural schematic diagram of a dynamic zoning management system for an electricity-carbon collaborative distribution network according to the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1, Figure 1 The present invention provides a method and system for dynamic partition management of an electric-carbon coordinated distribution network, comprising the following steps: S1, obtaining the first constraint condition and performing initial partitioning on the distribution network to obtain an initial partition set; In this example, the first constraint condition is obtained, specifically: Obtain historical operation data of the distribution network and perform data analysis to obtain the load fluctuation range and carbon emission intensity of each node; Construct the distribution network topology, and calculate the maximum number of partitions supported by the system and the upper limit of dynamic partitions that meet carbon emission constraints by combining the load fluctuation range and carbon emission intensity of each node; Determine the minimum number of partitions supported by the system according to the topological connectivity of the distribution network topology; The first constraint is constructed based on the maximum allowed number of partitions, the upper limit of dynamic partitions that meet the carbon emission constraint, and the minimum number of partitions.

[0020] The formula for the first constraint is as follows:

[0021] in, is the minimum number of partitions, is the actual number of partitions, is the maximum number of partitions, is the upper limit of dynamic partitioning based on carbon emission constraints.

[0022] It should be noted that by obtaining the historical operation data of the distribution network, the load fluctuation range and carbon emission intensity of each node are deeply analyzed, and the characteristics of the nodes in terms of energy regulation and carbon emission are comprehensively characterized. Subsequently, on the basis of constructing a complete distribution network topology, combined with the above node characteristics, the maximum allowable number of partitions that the system can carry is evaluated, and the upper limit of the dynamic partition under the condition of ensuring that carbon emissions meet the standards is further calculated, reflecting the regulatory effect of carbon constraints on partition capacity. At the same time, according to the connectivity of the topological structure, the minimum number of partitions required for the system to operate stably is identified to ensure the integrity and robustness of the physical structure and power supply capacity of the divided distribution network. Finally, the maximum allowable number of partitions, the upper limit of the partition under the carbon constraint, and the minimum number of partitions are integrated to construct the first constraint condition for dynamic partitioning, providing a basic framework for the dynamic adjustment and range control of subsequent partitioning strategies.

[0023] In this example, the distribution network is initially divided to obtain an initial partition set, which is: The node electricity-carbon coupling intensity matrix is ​​calculated, and the distribution network nodes are clustered using the spectral clustering algorithm to obtain the first partition set; A minimum partition capacity threshold is set, and partitions whose capacity is lower than the threshold in the first partition set are merged until the number of partitions meets the first constraint condition, thereby obtaining an initial partition set.

[0024] It should be noted that by calculating the node electricity-carbon coupling intensity matrix, the power load characteristics and carbon emission indicators are quantitatively integrated to construct a numerical model that reflects the synergistic relationship between nodes. The electricity-carbon coupling intensity not only covers electrical parameters (such as power flow, node voltage, etc.), but also considers indicators such as carbon emission factors, carbon intensity and unit load carbon consumption, ensuring the low-carbon orientation and energy efficiency consistency in the zoning process. Subsequently, the improved spectral clustering algorithm is used to process the coupling matrix to achieve intelligent clustering of nodes. The spectral clustering algorithm is based on graph theory and can accurately identify the intrinsic connections between nodes.

[0025] Furthermore, in order to avoid the generation of edge partitions with too small capacity and weak scheduling significance during the clustering process, this method sets a minimum partition capacity threshold and adjusts the capacity based on the first partition set. This merging mechanism ensures that each partition has basic load support capacity and operational independence, effectively preventing the increase in control complexity and imbalance in carbon emission allocation caused by "over-segmentation".

[0026] S2, evaluate the status of the initial partition set, and modify the initial partition using an improved greedy algorithm based on the evaluation results; In this example, the initial partition set is evaluated, and the initial partition is modified using an improved greedy algorithm based on the evaluation results. Specifically: Construct a partition status evaluation index system and use the entropy weight method to calculate the weight of each index. Based on the index weight, perform weighted summation on the index value of each partition to obtain the status evaluation value of the partition. According to the state evaluation value, the partition is identified as abnormal, and the adjacent node set of the abnormal partition is extracted; A greedy algorithm is used to add adjacent nodes to the abnormal partition and count the number of newly added nodes; A dynamic second constraint condition is constructed according to the change in the ratio of the number of newly added nodes to the number of partitioned nodes; Based on the dynamic second constraint condition, the initial partition is modified to obtain a modified partition.

[0027] It should be noted that a partition status evaluation index system is constructed, and the weight of each index is calculated by the entropy weight method to quantify the operating status of the partition. The entropy weight method can effectively eliminate the interference of subjective factors and make the status evaluation of each partition more accurate by objectively weighting the importance of each index. Then, based on the calculated index weight, the index value of each partition is weighted and summed to obtain the comprehensive status evaluation value of the partition. This evaluation value provides a basis for the subsequent abnormal partition identification. By analyzing the evaluation value of the partition, abnormal partitions with poor operating status can be identified.

[0028] For abnormal partitions, we further analyze them by extracting the set of adjacent nodes. On this basis, we use an improved greedy algorithm to add adjacent nodes to the abnormal partitions. The greedy algorithm makes the partition correction process more efficient by gradually selecting the adjacent nodes that have the greatest effect on improving the partition status. After adding the adjacent nodes, the system counts the number of newly added nodes and constructs a dynamic second constraint based on the change in the ratio of the number of newly added nodes to the number of nodes in the original partition to ensure that the partition adjustment is carried out within certain limits. The dynamic constraint can be flexibly adjusted according to the actual node changes, so that the partition correction process not only meets the performance requirements, but also avoids over-correction or unbalanced partitioning.

[0029] Finally, by applying the dynamic second constraint, the initial partition is modified to obtain the modified partition set. This process makes the partition more consistent with the actual operation of the power grid and improves the overall dispatching efficiency and carbon emission control capabilities of the system.

[0030] The advantages of this method are: first, the state assessment system based on the entropy weight method can accurately reflect the operating status of each partition and avoid human bias; second, the introduction of the greedy algorithm makes the partition adjustment process efficient and adaptive; finally, the dynamic constraint conditions ensure the flexibility and rationality of the partition adjustment, thereby realizing the precise management and optimized scheduling of the electricity-carbon coordinated distribution network, and effectively improving the intelligence and green operation level of the distribution network.

[0031] S3, expand the corrected partitions outward to the adjacent areas layer by layer, and use the hierarchical analysis method to analyze the electricity-carbon relationship of each partition; In this example, the modified partitions are extended outward to adjacent areas layer by layer, and the hierarchical analysis method is used to analyze the electricity-carbon relationship of each partition, specifically: The modified partition is used as the parent layer and the coupling strength values ​​of all nodes in the parent layer partition are calculated. The corresponding nodes are selected as core nodes based on the coupling strength values. Obtain the power grid topology of the parent layer and use the Dijkstra algorithm to calculate the shortest path hop count from each node to the core node; The maximum number of shortest path hops from all nodes to the core node is used as the initial expansion radius; According to the initial expansion radius, the parent layer is expanded outward to the adjacent area layer by layer to obtain several sub-layers; The electric-carbon interaction matrix between each sublayer and the parent layer is constructed, and the eigenvalue of the electric-carbon interaction matrix is ​​solved based on the hierarchical analysis method to obtain the layer-related eigenvalue.

[0032] Among them, the coupling strength values ​​of all nodes in the parent layer partition are calculated. The specific calculation formula is as follows:

[0033] in, is the coupling strength value between node i and node, is the interaction power, is the preset power threshold, is the carbon emission deviation rate, is the preset carbon emission threshold.

[0034] It should be noted that in the modified partition, the coupling strength values ​​of all nodes in the parent partition are first calculated. The coupling strength indicates the degree of correlation between electricity and carbon emissions. Nodes with larger coupling strength values ​​are usually important nodes that affect system operation. By selecting one or more nodes with the largest coupling strength as core nodes, the key areas of the system can be determined, and then targeted expansion and analysis can be carried out; Furthermore, the power grid topology of the parent layer is obtained, and the Dijkstra algorithm is used to calculate the number of hops of the shortest path from each node to the core node. The Dijkstra algorithm is a classic graph theory algorithm that can effectively calculate the shortest path between nodes in the graph. In this process, it helps identify the distance between the node and the core node, thereby determining the radius of the expansion area; The maximum value of the shortest path hop count from all nodes to the core node is used as the initial expansion radius. This radius determines the scope of expansion from the parent layer, ensuring that the expansion area can cover nodes with a strong coupling relationship with the core node, while avoiding unnecessary complexity of the system caused by excessive expansion. Based on the initial expansion radius, the adjacent areas of the parent layer are expanded outward layer by layer to obtain several sublayers. Each sublayer has a certain electricity-carbon interaction relationship with the parent layer, and the expansion area can provide necessary data support for subsequent power dispatch and carbon emission management. In addition, an electricity-carbon interaction matrix is ​​constructed between each sublayer and the parent layer. This matrix reflects the interaction between electricity and carbon emissions, and serves as an important basis for analyzing the relationship between partitions. By solving the eigenvalue of the electricity-carbon interaction matrix based on the hierarchical analysis method (AHP), the hierarchical correlation eigenvalue can be obtained, which reflects the strength of the relationship between each layer of partitions and provides a reference for subsequent decision-making.

[0035] S4, based on the analysis results, determine whether to perform layered expansion correction and update the correction range; In this example, based on the analysis results, it is determined whether to continue the layered expansion and update the correction range, specifically: Obtaining the sublayer to be corrected according to the layer-related characteristic value, and adding the sublayer to be corrected to the preset correction range set; Perform overlapping area detection on the partition of the sub-layer to be corrected in the correction range set and the partition of the parent layer; Based on the detection results, the overlapping partitions are merged with the parent layer partitions, and the correction range set is updated.

[0036] It should be noted that by analyzing the layer-associated eigenvalues ​​of each sub-layer, it is determined whether each sub-layer needs further correction. The layer-associated eigenvalues ​​are calculated by the analytic hierarchy process (AHP), which reflects the strength of the electric-carbon interaction relationship between each layer partition and the parent layer. If the associated eigenvalue of a sub-layer is low, it means that the electric-carbon synergy between the sub-layer and the parent layer is weak, and further correction and expansion may not be required. On the contrary, if the eigenvalue is high, it means that there is a strong electric-carbon coupling relationship between the sub-layer and the parent layer, and further correction is required to ensure the coordinated operation of the system. Therefore, based on these analysis results, it is possible to determine which sub-layers need to be corrected, and add the partitions to be corrected to the preset correction range set.

[0037] Next, the system will perform overlapping area detection on the partitions to be corrected in the preset correction range set and the original partitions. The purpose of this step is to check the overlapping parts between the partitions to be corrected and the original partitions to avoid unnecessary repeated corrections and redundant expansions. Through overlapping area detection, it can be ensured that each correction operation is based on actual needs, thereby avoiding affecting the stability and optimization effect of the system.

[0038] Once the overlapping area detection is completed, the system will merge the overlapping partitions with the parent layer partitions according to the detection results, and update the correction range set accordingly. By merging overlapping partitions, the division of the electricity-carbon collaborative management area can be further optimized, making the relationship between electricity and carbon emissions in each partition closer and improving the system's collaborative efficiency. At the same time, the updated correction range set provides a clear direction for the next step of hierarchical expansion, ensuring that the system can continue to optimize in dynamic changes.

[0039] S5, dynamically adjust the partition boundary according to the correction range, and perform partition management according to the adjustment result.

[0040] In this example, the partition boundary is dynamically adjusted according to the correction range, and the partition management is performed according to the adjustment result, specifically: Dynamically adjust the partition boundary according to the correction range, and generate partition scheduling instructions based on the dynamic partition results, the instructions include the carbon emission quota, load adjustment priority and spare capacity allocation strategy of the power generation units in each partition; During the scheduling process, partition operation data is collected in real time. If carbon emissions or loads are detected to be out of limit, the partition re-division process is triggered and the scheduling instructions are updated.

[0041] It should be noted that in the distribution network dispatching system, dynamically adjusting the partition boundaries and generating corresponding dispatching instructions are the key to achieving flexible and efficient energy management. By adjusting the partition boundaries according to the correction range, the operation partitions of the power grid can be continuously optimized according to the actual operating conditions to ensure that the distribution network can continue to provide stable and efficient power supply under various changing load demands and carbon emission targets. Specifically, the system first dynamically adjusts the partition boundaries of the distribution network according to the correction range to obtain a new partition structure. Based on this new structure, the system generates corresponding partition dispatching instructions. Each dispatching instruction contains key information such as the carbon emission quota of the power generation unit in each partition, the load adjustment priority, and the spare capacity allocation strategy. These instructions guide the power dispatching process of each partition to ensure the coordination and balance of load and carbon emission control.

[0042] During the dispatching process, the system will monitor the operating status of each partition in real time, especially the carbon emissions and load data. If the carbon emissions or load of a partition exceeds the preset limits during operation, the system will immediately trigger the partition re-division process and update the dispatching instructions. During the re-division process, the system will readjust the partitions to ensure that each partition can reasonably distribute the power load while meeting the carbon emission limits. Through this dynamic adjustment and real-time response mechanism, the system can continuously optimize the operation of the power grid, avoid excessive carbon emissions or uneven load problems, and ensure the stability and sustainability of the system.

[0043] Embodiment 2, Figure 2The present invention provides a dynamic partition management system for an electric-carbon coordinated distribution network, including a data acquisition module, a partition correction module, a partition expansion module, a correction and update module, and a partition adjustment module: A data acquisition module is used to obtain the first constraint condition and perform initial partitioning on the distribution network to obtain an initial partition set; The partition correction module is used to evaluate the status of the initial partition set and correct the initial partition using an improved greedy algorithm based on the evaluation results; The partition expansion module is used to expand the corrected partitions outward to adjacent areas layer by layer, and use the hierarchical analysis method to analyze the electricity-carbon relationship of each partition layer; A correction and update module is used to determine whether to continue the layered expansion and update the correction scope according to the analysis results; The partition adjustment module is used to dynamically adjust the partition boundary according to the correction range and perform partition management according to the adjustment result.

[0044] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0045] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0046] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0047] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0048] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0049] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for dynamic partition management of an electricity-carbon coordinated distribution network, characterized in that: The following steps are involved: Obtaining the first constraint condition and performing initial partitioning on the distribution network to obtain an initial partition set; Perform status evaluation on the initial partition set, and use an improved greedy algorithm to modify the initial partition according to the evaluation results; The revised partitions are extended outward to adjacent areas layer by layer, and the electricity-carbon relationship of each partition is analyzed using the hierarchical analysis method. Based on the analysis results, determine whether to continue the layered expansion and update the correction scope; The partition boundaries are dynamically adjusted according to the correction range, and the partition management is performed based on the adjustment results.

2. The method for dynamic partition management of the electric-carbon coordinated distribution network according to claim 1 is characterized in that: The obtaining of the first constraint condition is specifically: Obtain historical operation data of the distribution network and perform data analysis to obtain the load fluctuation range and carbon emission intensity of each node; Construct the distribution network topology, and calculate the maximum number of partitions supported by the system and the upper limit of dynamic partitions that meet carbon emission constraints by combining the load fluctuation range and carbon emission intensity of each node; Determine the minimum number of partitions supported by the system according to the topological connectivity of the distribution network topology; The first constraint is constructed based on the maximum allowed number of partitions, the upper limit of dynamic partitions that meet the carbon emission constraint, and the minimum number of partitions.

3. The method for dynamic partition management of the electric-carbon coordinated distribution network according to claim 2 is characterized in that: The distribution network is initially divided to obtain an initial partition set, which is specifically: The node electricity-carbon coupling intensity matrix is ​​calculated, and the distribution network nodes are clustered using the spectral clustering algorithm to obtain the first partition set; A minimum partition capacity threshold is set, and partitions whose capacity is lower than the threshold in the first partition set are merged until the number of partitions meets the first constraint condition, thereby obtaining an initial partition set.

4. The method for dynamic partition management of the electric-carbon coordinated distribution network according to claim 3 is characterized in that: The initial partition set is evaluated, and the initial partition is modified using an improved greedy algorithm according to the evaluation result, specifically: Construct a partition status evaluation index system and use the entropy weight method to calculate the weight of each index. Based on the index weight, perform weighted summation on the index value of each partition to obtain the status evaluation value of the partition. According to the state evaluation value, the partition is identified as abnormal, and the adjacent node set of the abnormal partition is extracted; A greedy algorithm is used to add adjacent nodes to the abnormal partition and count the number of newly added nodes; A dynamic second constraint condition is constructed according to the change in the ratio of the number of newly added nodes to the number of partitioned nodes; Based on the dynamic second constraint condition, the initial partition is modified to obtain a modified partition.

5. The method for dynamic partition management of the electricity-carbon coordinated distribution network according to claim 4 is characterized in that: The modified partition is expanded outward to adjacent areas layer by layer, and the hierarchical analysis method is used to analyze the electricity-carbon relationship of each partition, specifically: The modified partition is used as the parent layer and the coupling strength values ​​of all nodes in the parent layer partition are calculated. The corresponding nodes are selected as core nodes based on the coupling strength values. Obtain the power grid topology of the parent layer and use the Dijkstra algorithm to calculate the shortest path hop count from each node to the core node; The maximum number of shortest path hops from all nodes to the core node is used as the initial expansion radius; According to the initial expansion radius, the parent layer is expanded outward to the adjacent area layer by layer to obtain several sub-layers; The electric-carbon interaction matrix between each sublayer and the parent layer is constructed, and the eigenvalue of the electric-carbon interaction matrix is ​​solved based on the hierarchical analysis method to obtain the layer-related eigenvalue.

6. The method for dynamic partition management of the electricity-carbon coordinated distribution network according to claim 5 is characterized in that: According to the analysis results, it is determined whether to continue the layered expansion and update the correction range, specifically: Obtaining the sublayer to be corrected according to the layer-related characteristic value, and adding the sublayer to be corrected to the preset correction range set; Perform overlapping area detection on the partition of the sub-layer to be corrected in the correction range set and the partition of the parent layer; Based on the detection results, the overlapping partitions are merged with the parent layer partitions, and the correction range set is updated.

7. The method for dynamic partition management of the electricity-carbon coordinated distribution network according to claim 6 is characterized in that: The partition boundary is dynamically adjusted according to the correction range, and the partition management is performed according to the adjustment result, specifically: According to the real-time collection of partition operation data, the partition boundaries are dynamically adjusted based on the correction range, and the dynamic partition results are used to generate partition scheduling instructions, which include the carbon emission quotas of the power generation units in each partition, load adjustment priorities and spare capacity allocation strategies.

8. The method for dynamic partition management of the electricity-carbon coordinated distribution network according to claim 5 is characterized in that: The coupling strength values ​​of all nodes in the parent layer partition are calculated by the following specific calculation formula: in, is the coupling strength value between node i and node j, is the interaction power, is the preset power threshold, is the carbon emission deviation rate, is the preset carbon emission threshold.

9. A dynamic partition management system for an electricity-carbon coordinated distribution network, characterized in that: A method for dynamic partition management of an electric-carbon coordinated distribution network as described in any one of claims 1 to 8, characterized in that it includes a data acquisition module, a partition correction module, a partition expansion module, a correction and update module, and a partition adjustment module: A data acquisition module, used to acquire the first constraint condition and perform initial partitioning on the distribution network to obtain an initial partition set; The partition correction module is used to evaluate the status of the initial partition set and correct the initial partition using an improved greedy algorithm based on the evaluation results; The partition expansion module is used to expand the corrected partitions outward to adjacent areas layer by layer, and use the hierarchical analysis method to analyze the electricity-carbon relationship of each partition layer; A correction and update module is used to determine whether to continue the layered expansion and update the correction scope according to the analysis results; The partition adjustment module is used to dynamically adjust the partition boundaries according to the correction range and perform partition management based on the adjustment results.

Images