Distribution network line adaptive balance switching method and device based on real-time state evaluation

Abstract

The invention discloses a distribution network line adaptive balance switching method and device based on real-time state evaluation, and relates to the technical field of power system automation, and the method comprises the following steps: obtaining a distribution network line real-time state vector, and forming balance priority data of each branch; dynamically adjusting the switch data according to the balance priority data to form an optimized switching sequence set; when the optimization switching sequence set is executed, line load data are obtained, and balance priority data are dynamically updated; correcting the real-time state vector of the distribution network line according to the updated balance priority data; according to the invention, a closed-loop feedback control mechanism based on the real-time state vector and the balance priority data is constructed, so that the problems of insufficient comprehensive evaluation dimension and difficult switching strategy in the self-adaptive balance switching process of the traditional distribution network line are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system automation, more particularly, the present application relates to a kind of based on real-time state evaluation distribution network line adaptive balance switching method and device. BACKGROUND

[0002] Under the background of the rapid development of smart grid and distribution network automation technology, the safety, reliability and economy requirements of power system operation are increasing. As the key link of power system facing users, the complexity of distribution network line structure and the diversity of operation mode are growing, especially in the environment of high proportion of distributed energy access and diversified load characteristics, the operation state of distribution network line presents stronger dynamic and uncertainty. Traditional operation control method depends on fixed strategy and off-line calculation, and it is difficult to adapt to real-time changes of power grid working condition. When dealing with line load fluctuation, intermittent distributed power output and network topology adjustment, it often lacks enough flexibility and adaptability.

[0003] In recent years, with the progress of sensing technology, communication network and data analysis method, the real-time state monitoring and evaluation ability of distribution network has been significantly enhanced. By collecting multi-dimensional data such as electrical quantity, switch state and environmental parameter in line operation, the current operation condition of distribution network can be finely described. On this basis, how to use real-time state information to dynamically guide network reconfiguration, load transfer and other operations to realize the optimization and recovery of line operation balance has gradually become an important research direction in the field of distribution network operation control. Adaptive balance switching, as a technical means that can make autonomous decision and adjust switch state according to real-time working condition, helps to improve the operation efficiency of distribution network, relieve line overload, improve voltage quality, and enhance the resistance of system to various disturbances.

[0004] For example, the invention patent with publication number CN119171437A discloses an intelligent power supply planning method based on medium voltage distribution network, which comprises: constructing a digital twin model according to preprocessed data; generating an adaptive dynamic cloning model pool to monitor future load changes and device states of the power grid; performing load prediction and power supply strategy simulation according to real-time state data output by the cloning model pool and the digital twin model, selecting the optimal strategy to cope with various possible power grid operating conditions and emergencies; combining multi-modal load prediction results and priority ranking calculated according to comprehensive score; executing the optimal power supply strategy and performing real-time monitoring, dynamically adjusting strategy parameters when executing the strategy; implementing fault prediction and self-healing mechanism according to real-time monitoring and feedback data. An intelligent, dynamic and integrated solution is provided, laying a foundation for the development of future smart grid.

[0005] For example, the invention patent with publication number CN119994909A discloses a kind of intelligent power distribution load prediction and self-adaptive scheduling method, to improve the response capability and operating efficiency of power distribution system to load fluctuation;The method is to collect the historical load data of target power distribution area, real-time meteorological information and user power consumption behavior data, establish multidimensional input data set, construct short-term load prediction model based on the data set, realize the prediction of the future load level of multiple feeders and key nodes;According to the prediction result, identify potential voltage deviation, load imbalance and equipment overload risk, then combine power grid topology structure and operation constraint, generate dynamic scheduling control strategy using rolling time domain optimization method;The strategy includes transformer tap position adjustment, capacitor bank switching and other control measures;By issuing scheduling strategy to equipment control unit, active adjustment is completed before load change, voltage stability, load balancing and energy optimization are realized, to provide intelligent, adaptive operation guarantee for power distribution system.

[0006] In the above disclosed technical solution, at least the following technical problems exist:

[0007] Traditional adaptive balancing switching method of distribution network line depends on fixed rules or single calculation result, and its switching strategy is often based on static judgment of current state, lacks comprehensive evaluation ability for continuous change process of line operation state, so that the adaptive ability of line switching to complex operation scene is limited.

[0008] To solve the above problems, the present application provides a solution. SUMMARY

[0009] To overcome the above-mentioned defects of the prior art, embodiments of the present application provide a distribution network line adaptive balancing switching method and device based on real-time state evaluation, which solves the problem of real-time self-adaptation of distribution network line balancing regulation by dynamic priority feedback switching.

[0010] To achieve the above-mentioned purpose, the present application provides the following technical solutions: A distribution network line adaptive balancing switching method based on real-time state evaluation, comprising: obtaining distribution network line real-time state vector, forming each branch balancing priority data;According to balancing priority data, dynamically adjust switch data, form optimized switching sequence set;When executing optimized switching sequence set, obtain line load data, and dynamically update balancing priority data;According to updated balancing priority data, correct distribution network line real-time state vector.

[0011] In a preferred technical solution, the real-time state vector of the distribution network line is obtained, and branch balance priority data is formed as follows: real-time state data of each branch distribution network line is collected, and the real-time state data of each branch is uniformly time-aligned to form an original state data set; the original state data set is processed by semantic mapping to convert the state data into state features, and a state vector of each branch is constructed; structure perception reorganization is performed on the state vector of each branch, and the weight of the running imbalance state data in the reorganized state vector is rearranged to obtain a branch state vector; based on the running evolution trajectory analysis method, the persistence feature of the state vector of each branch is extracted, and the persistence feature is embedded into the weight rearranged branch state vector to form a state vector set; based on the state vector set, priority differentiation sorting is performed on each branch to form branch balance priority data; the branch balance priority data is self-checked and consistent, the conflict sorting result is dynamically corrected, and the branch balance priority data is output.

[0012] In a preferred technical solution, the structure perception reorganization of the state vector of each branch is as follows: based on the original state data set, the physical connection relationship and the electrical association path between the branches are judged, and the topological association relationship between the branches is determined; according to the topological association relationship, the state features in the state vector of each branch are rearranged in structure to form adjacent arrangement; after completing the structural rearrangement, the running constraint association features in the state vector of each branch are combined to apply structural weight guidance to the arrangement order of the state features in the vector; based on the structure of the state vector after the structural weight guidance, multiple branches with a cooperative relationship in the topological structure and the running constraint level are identified, and the state features in the cooperative branches are embedded into the state vector of the corresponding branch; after the topological constraint rearrangement, the structural weight guidance and the multi-branch joint expression of each branch state vector are completed, the branch state vector after the structure perception reorganization is arranged, and the branch state vector after the structure perception reorganization is output.

[0013] In a preferred technical solution, the self-checking consistency processing of the branch balance priority data dynamically corrects the conflict ranking result and outputs the branch balance priority data, which is specifically as follows: the priority data size of each branch balance priority data is ranked, and the ordered branch sequence formed by sequentially arranging each branch is taken as the ordered path; based on the branch balance priority data, its corresponding order is retained as the initial state of the current ordered path; based on the perception reorganization of the state vector of each branch, the collaborative branch set existing in the collaborative relationship of the distribution network structure is obtained, and the relative position distribution of the collaborative branch in the current ordered path is marked; the relative position of the collaborative branch in the ordered path is determined, and the corresponding ordered segment is marked as a candidate conflict ranking area; based on the persistence feature in the state vector of each branch, the sorting change direction of the branch in the candidate conflict ranking area is analyzed, and whether the current ordered path is consistent with the branch operation evolution trend is judged; according to the candidate conflict ranking area of the inconsistent ordered path, combined with the consistency judgment result of the collaborative branch group based on the persistence feature of the state vector of each branch, the multi-feature consistent voting judgment is performed on the conflict ranking area to determine the unified adjustment direction of the ranking correction; according to the multi-feature consistent voting judgment result, the branch balance priority data in the candidate conflict ranking area is locally corrected; the branch balance priority data after local correction is compared and checked with the ordered path, and the branch balance priority data is output.

[0014] In a preferred technical solution, the switch data is dynamically adjusted according to the balance priority data to form an optimized switching sequence set, which is specifically as follows: based on the balance priority data of each branch, the switch data of each branch is obtained, and the switch data of each branch is one-to-one corresponding to the balance priority data of each branch; based on the corresponding relationship, the balance priority data of each branch is mapped to extract the feature value of the branch on the overall distribution network balance influence to form the balance influence strength corresponding to each branch; according to the balance influence strength, the corresponding switch data is planned in layers, and the relationship between different switch data is constrained in the layering process; the switch data combination with multiple execution paths is screened through the path screening mechanism; the screened and rearranged switch data is combined according to the balance influence strength to form a switching sequence; the matching state of each switching operation and the corresponding branch balance priority is checked, the sequence segment deviating from the associated logic is corrected, and an optimized switching sequence set is output.

[0015] In a preferred technical solution, the matching state of each switching operation with the corresponding branch balance priority is checked, and the sequence segment with deviation from the associated logic is corrected, and an optimized switching sequence set is output, specifically as follows: based on the switching sequence of the switch, the branch identifier of each switching operation in the sequence is extracted one by one, and the balance priority data of the branch is associated, and the mapping relationship between the switching operation and the branch balance priority data is established; according to the execution order of the switching sequence of the switch, the branch balance priority data corresponding to the switching operation is sequentially compared, the sequence position where the execution order of the switching operation is inconsistent with the branch balance priority ordering relationship is counted, and a switching sequence deviation marker set is formed; according to the switching sequence deviation marker set, the balance influence intensity associated with each switching operation in the sequence segment is extracted, and the balance influence evolution relationship in the corresponding sequence segment is constructed; the balance influence evolution relationship of adjacent switching operations in the sequence segment is analyzed for continuity, and the execution order of the switching operation in the balance discontinuous section is locally adjusted; after the local adjustment is completed, based on the updated switching sequence, the multi-branch combination with a common influence range in the sequence is counted, and the switching operation set of the multi-branch combination in the switching sequence is extracted; the balance influence intensity changes before and after the execution of the multi-branch combination in the switching sequence are traced back and compared, and inconsistent operations are obtained; the inconsistent operations are subjected to cooperative constraint correction processing, and an optimized switching sequence set is output.

[0016] In a preferred technical solution, when the optimized switching sequence set is executed, line load data is acquired, and the balance priority data is dynamically updated, specifically as follows: by executing the optimized switching sequence set, the switch in the distribution network line is sequentially subjected to switching operation, and the line load data is obtained; the line load data is time-aligned with the corresponding switching operation; based on the time-aligned line load data, the load change characteristics of each branch before and after the switching execution are extracted, and the load response characteristics are extracted through comprehensive analysis of the load change characteristics; the load response characteristics are associated with the balance priority data of the corresponding branch, the deviation degree between the load response and the priority is determined, and the branch range of the priority correction is obtained; for the branch in the branch range whose load response deviation degree exceeds a preset threshold, the balance priority data thereof is dynamically corrected according to the load response characteristics.

[0017] In a preferred technical solution, the load response feature is associated with the balance priority data of the corresponding branch, the deviation between the load response and the priority is determined, and the priority corrected branch range is obtained, which is specifically as follows: based on the load response feature, the response intensity data of each branch of the current switching operation is extracted; the response intensity sorting result is generated by sorting the response intensity data of each branch; the balance priority data corresponding to each branch is obtained, and the branch priority sorting relationship is established according to the balance priority data; the response intensity sorting result and the branch priority sorting relationship are compared and analyzed to determine whether there is an ordering deviation between the load response and the balance priority of the corresponding branch; the corresponding load response expected interval is established for different balance priority levels; the load response feature of each branch is matched with the load response expected interval of the corresponding balance priority level to determine whether there is an interval deviation between the load response and the balance priority of the branch; based on the ordering deviation determination result and the interval deviation determination result, the matching state between the load response and the balance priority of each branch is comprehensively judged; when the branch satisfies the ordering deviation and the interval deviation determination at the same time, the corresponding branch is determined as the balance priority corrected branch range; when the branch does not satisfy the determination at the same time, the original balance priority data of the branch is maintained unchanged.

[0018] In a preferred technical solution, the real-time state vector of the distribution network line is corrected according to the updated balance priority data, which is specifically as follows: according to the dynamically updated balance priority data of each branch, the balance priority data corresponding to the state vector of the previous round is compared to form the balance priority change feature; the balance priority change feature is associated and compared with the real-time state vector of the distribution network line branch by branch to identify the branch state part in the state vector that is inconsistent with the priority change; based on the inconsistent branch state part, the deviation feature related to the priority change is analyzed and extracted in combination with the balance priority change feature to form a set of state elements to be corrected; the phase state element in the real-time state vector is directionally corrected according to the dynamically updated balance priority data of the corresponding branch; the updated state vector of each branch is uniformly updated to establish a continuous corresponding relationship between the updated real-time state vector and the dynamically updated balance priority data, and the real-time state vector of the distribution network line that is consistent with the dynamically updated balance priority data is output.

[0019] In a preferred technical solution, a device for a distribution network line adaptive balance switching method based on real-time state evaluation comprises a state acquisition and balance priority generation module, an optimized switching sequence generation module, a load data acquisition and balance priority dynamic update module, and a state vector dynamic correction module, and there is a connection between the modules; the state acquisition and balance priority generation module is used to acquire the real-time state vector of the distribution network line and form the balance priority data of each branch; the optimized switching sequence generation module is used to dynamically adjust the switch data according to the balance priority data and form an optimized switching sequence set; the load data acquisition and balance priority dynamic update module is used to acquire the line load data when the optimized switching sequence set is executed and dynamically update the balance priority data; and the state vector dynamic correction module is used to correct the real-time state vector of the distribution network line according to the updated balance priority data.

[0020] The technical effect and advantages of the distribution network line adaptive balance switching method based on real-time state evaluation of the present application are as follows: 1. The present application can accurately depict the operation difference and imbalance degree of each branch by acquiring the real-time state vector of the distribution network line and forming the balance priority data of each branch, combining the unified time sequence alignment and feature mapping processing of the real-time state data such as the branch topology connection relationship and the branch load rate, and realizing the fine-grained identification of the branch load distribution state. At the same time, the priority data has the dynamic update ability by the structure correlation correction of the state vector, which effectively avoids the branch state misjudgment and ordering drift, and significantly improves the accuracy and adaptive flexibility of the distribution network line balance decision.

[0021] 2. The present application can keep the switching sequence and the line load change synchronous matching by dynamically adjusting the switch data according to the balance priority data, forming an optimized switching sequence set, and acquiring the line load data in real time during the execution of the optimized switching sequence set to dynamically update the balance priority data, and reducing the load mutation risk in the switching process. At the same time, the real-time state vector of the distribution network line is corrected based on the updated balance priority data, which can continuously correct the line operation evaluation deviation, avoid the instability and low response efficiency of the switching strategy, and significantly enhance the reliability of the adaptive balance switching of the distribution network line. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The flowchart of the distribution network line adaptive balance switching method based on real-time state evaluation of the present application.

[0023] Figure 2 The device structure diagram of the distribution network line adaptive balance switching method based on real-time state evaluation of the present application. DETAILED DESCRIPTION

[0024] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0025] Embodiment 1, Figure 1 A line adaptive balance switching method based on real-time state evaluation is given, comprising the following steps: S1, obtaining a real-time state vector of the distribution network line to form balance priority data of each branch; In this embodiment, the real-time state vector of the distribution network line is obtained to form balance priority data of each branch, which is specifically as follows: Through the data acquisition device, the real-time state data of each branch of the distribution network line is collected, and the real-time state data of each branch is uniformly time-aligned to form an original state data set containing line structure relationship, load performance and operation constraint correlation characteristics. The state data includes topological connection data (connection relationship of branch and main line, adjacent branch), branch load rate and line capacity utilization rate; The original state data set is subjected to semantic mapping processing to convert the state data into state features representing the running difference of the branch, and a state vector of each branch is constructed. The semantic mapping processing is to take the line structure relationship, load performance and operation constraint correlation characteristics already contained in the original state data set as the mapping basis, to uniformly classify the real-time state data of each branch, to align different data in the same state data, and to convert into state feature representation for describing the running difference of the branch, thereby supporting the construction of the subsequent state vector; The structure of the state vector of each branch is perceived and reorganized to make the state vector of each branch have the expression ability of reflecting mutual restriction and coordination characteristics; The weight rearrangement is performed on the running imbalance state data in the recombined state vector, to obtain a branch state vector after weight rearrangement, and to improve the priority degree of the branch state vector, wherein the weight rearrangement is specifically as follows: for each branch state vector after recombination, a balanced reference benchmark is constructed within a unified time window, and the deviation degree of each state feature in the state vector relative to the benchmark is calculated, when the deviation degree of a certain state feature represents that it has a significant contribution to the branch running imbalance, it is identified as the running imbalance state data, and on the premise of keeping the structure of the state vector unchanged, the weight of the corresponding state feature is rearranged according to the size of the deviation degree, so that the state feature with higher imbalance degree obtains higher weight, and the weight of the balanced or weakly affected feature is relatively reduced, and the balanced reference benchmark is adaptively generated based on the state vectors of all branches after structural perception recombination within the same time window, and it is generated by calculating the statistical expectation of each state feature within the range of all branches; Based on the running evolution trajectory analysis method, the persistence feature of each branch state vector is extracted, and the persistence feature is embedded into the branch state vector after weight rearrangement, to form a state vector set, wherein the persistence feature includes the maintenance degree of the branch load level within a continuous period and the fluctuation amplitude of the branch running state; Based on the state vector set, the priority degree of each branch is sorted, to form branch balance priority data with a clear sequence relationship; The branch balance priority data is subjected to self-checking and consistency processing, to automatically correct the conflict sorting result, and to output stable and usable branch balance priority data.

[0026] In this embodiment, structural perception recombination is performed on each branch state vector, specifically as follows: Based on the line structure relationship of the original state data set, the physical connection relationship and the electrical association path between the branches are judged, and the topological association relationship between the branches is determined, which exists directly; According to the topological association relationship, the state features in each branch state vector are subjected to structural rearrangement, so that the state features of the branches having a constraint relationship in the distribution network topology are arranged adjacent to or associated with each other in the state vector, wherein the structural rearrangement is to reorganize the state features originally arranged in the order of collection in each branch state vector according to the topological association relationship between the branches, so that the state features of adjacent branches constrained by the same topology are kept associated in adjacent positions; After completing the structural rearrangement, the arrangement order of the state features in the vector is guided by the structural weight in combination with the running constraint association features in each branch state vector, wherein the structural weight guidance is to assign corresponding structural weights to different state features, and to guide the arrangement position in the state vector according to the size of the structural weight, so that the state features with strong constraint effect on the branch running occupy prominent positions in the state vector, and the state features with weak constraint are placed at the back; Based on the structure of the guided state vector, identify multiple branches that exist in the topology and operating constraints, and embed the representative state characteristics in the corresponding branch state vector, wherein the coordination relationship refers to the correlation between multiple branches in the topology, and the characteristics of consistent state change direction and coupled constraints in the operation process; After the topology constraint rearrangement, structure weight guidance and multi-branch joint expression, the consistency of each branch state vector is arranged to ensure that the internal structure of the state vector and the constraint and coordination relationship between the branches are consistent, and the reorganized branch state vector is output.

[0027] Based on the line structure relationship of the original state data set, the physical connection relationship and the electrical correlation path between the branches are determined, and the topological correlation relationship between the branches is determined, specifically: The topology identifier of each branch is extracted from the original state data set, including the branch start and end node identifier, the feeder number to which it belongs, the switch connection state and the upstream and downstream level relationship; Based on the topology identifier, a node-branch association table of the distribution network line is constructed, and the actual connection structure of each branch in the distribution network is restored accordingly; In the connection structure, the branches are path traversed along the power supply direction and the transferable supply direction. When two or more branches share the same power supply path or the same upstream node, key branch node or are constrained by the same switch or transformer, it is determined that there is an electrical correlation path between them; If there is no open switch or isolation node in the electrical correlation path, the corresponding branch pair is marked as a topological correlation relationship with direct constraints.

[0028] In this embodiment, the branch balance priority data is self-checked and consistent, and the conflict sorting result is automatically corrected. The stable and usable branch balance priority data is output, as follows: The branch balance priority data is sorted by priority data size, and the ordered branch sequence formed by sequentially arranging each branch is used as the sorting path; Based on the branch balance priority data, the sorting order of the corresponding branch balance priority data is retained as the initial state of the current sorting path; Based on the perception and reorganization of the branch state vector, the coordination branch set with coordination relationship in the distribution network structure is obtained, and the relative position distribution of the coordination branch in the current sorting path is marked; The relative position of the coordination branch in the sorting path is determined. When the coordination branch presents discrete distribution and sequential fragmentation in the sorting path, the corresponding sorting fragment is marked as a candidate conflict sorting area; The sorting change direction of the branch in the candidate conflict sorting region is analyzed by contrasting the persistence characteristics in the branch state vectors, and it is judged whether the current sorting path is consistent with the evolution trend of the branch operation; According to the candidate conflict sorting region of the inconsistent sorting path, combined with the consistency determination result of the cooperative branch group based on the persistence characteristics of each branch state vector, a multi-feature consistent voting determination is performed on the conflict sorting region to determine the unified adjustment direction of the sorting correction, wherein the multi-feature consistent voting determination refers to giving the branch sorting adjustment direction of each determination feature based on the consistency determination result of the cooperative branch group, and the determination results are summarized and counted, and when the majority of the determination features point to the same sorting adjustment direction, the direction is determined as the unified sorting correction direction of the conflict sorting region. The consistency determination result of the cooperative branch group is that if the persistence characteristics of each branch in the same cooperative branch group are consistent in the time evolution direction and the change trend, it is determined that the cooperative branch group has consistency in the operation evolution level; According to the multi-feature consistent voting determination result, the branch balance priority data in the candidate conflict sorting region is locally corrected; After comparing and verifying the branch balance priority data after local correction with the sorting path, and confirming that the sorting adjustment does not introduce new conflict relations, the stable and usable branch balance priority data is output.

[0029] In this embodiment, according to the multi-feature consistent voting determination result, the branch balance priority data in the candidate conflict sorting region is locally corrected, as follows: Based on the balance priority data of each branch in the candidate conflict sorting region and the sorting correction direction obtained by the multi-feature consistent voting determination, the adjustable interval of each branch in the current sorting path is limited as the preliminary sorting correction range of the corresponding branch; In the candidate conflict sorting region, the position exchange of adjacent branches is gradually performed within the constraint of the preliminary sorting correction range, forming a plurality of neighborhood solutions, and recording the sorting deviation after each exchange; The neighborhood solution that meets the multi-feature consistent voting determination result and has the smallest sorting deviation is selected as the candidate local correction scheme; The candidate local correction scheme is input into the trained sorting prediction model to predict the optimal sorting correction amount and adjustment direction of each branch in the conflict region, wherein the trained sorting prediction model is trained by using supervised learning algorithm according to the branch state characteristics and load response characteristics as samples, and the target value of the executed sorting adjustment is labeled, and the model prediction accuracy and stability are ensured through cross-validation; The predicted results of the ranking prediction model are compared with the candidate schemes obtained by the iterative neighborhood search, and a correction scheme that can further reduce the ranking deviation and enhance the consistency of multiple features is screened out. The initial value of the ranking correction amount is solved based on the screened correction scheme, the ranking deviation amount and the branch state vector are used as constraint conditions, and the ranking correction amount of each branch in the candidate conflict area is optimized and solved; The optimized local correction result is applied to the branch balance priority data in the candidate conflict ranking area, the corresponding ranking path is updated, and the final corrected branch balance priority data in the candidate conflict ranking area is output.

[0030] S2, according to the balance priority data, dynamically adjusting the switch data, forming an optimized switching sequence set; In this embodiment, the balance priority data is used to dynamically adjust the switch data to form an optimized switching sequence set, which is as follows: Based on the balance priority data of each branch, the switch data of each branch is obtained, including the operation direction and the affected range; The switch data of each branch is one-to-one corresponding to the balance priority data of each branch, so that each switch data directly corresponds to the balance priority data of the corresponding branch; Based on the corresponding relationship, the balance priority data of each branch is mapped, the characteristic value of the influence of the branch on the overall balance of the distribution network is extracted, and the balance influence strength corresponding to each branch is formed. Wherein, the characteristic value of the influence of the branch on the overall balance of the distribution network is obtained by using the weighted superposition method based on the topological association relationship between the operation constraints in the branch state vector and the branch, and the numerical characteristics reflecting the influence of the branch on the overall balance are obtained after quantifying each factor; According to the balance influence strength, the corresponding switch data is hierarchically planned, and the relationship between different switch data is constrained in the hierarchical process; The switch data combination with multiple execution paths is screened through the path screening mechanism driven by the balance priority data, the switch data combination that enhances the balance effect of the branch is retained, and the switch data that is not conducive to the balance of the branch and the whole is eliminated, so that the final determined switching path keeps consistent in the balance adjustment direction; For the case where there are multiple feasible switch data combinations, the balance priority data driven path screening process is introduced to retain the switch data that can enhance the balance effect of the branch, while eliminating the switch data that is not conducive to the balance, so that the switching process direction is consistent; The screened and rearranged switch data is combined according to the balance influence strength to form a complete switching sequence; Check the matching state of each switching operation and the corresponding branch balance priority, correct the sequence fragments that deviate from the associated logic, and output the stable and executable optimized switching sequence set.

[0031] In the embodiment, the corresponding switch data is hierarchically planned according to the balance influence strength, and the relationship between different switch data is constrained in the hierarchical process, specifically as follows: Based on the branch switch data and the corresponding balance influence strength, the influence characteristics of different switch data on the branch balance state under independent execution are obtained, wherein the influence characteristics are obtained by subtracting the reference value before the operation from the load and voltage data of the branch collected when the switch operation is performed, and the influence characteristics include the branch load change amplitude and the node voltage deviation data; Based on the influence characteristics, the superposition effect analysis of the combination of multiple switch data is performed to determine the change trend of the balance influence strength of different switch data when combined, and the switch data combination with significant change in balance influence strength due to superposition is marked as a high-impact combination; According to the balance influence strength of the switch data and the superposition effect analysis result, the switch data and the switch data combination are hierarchically divided, so that the switch data and combination with higher balance influence strength or significant superposition effect are divided into high level, and the rest of the switch data is divided into low level; After completing the hierarchical division, for the switch data in the same level, the in-layer sorting is performed according to the balance priority data of the branch, so that the switch data corresponding to the branch with higher balance priority is preferentially arranged in the level, and the in-layer sorting relationship is formed; Based on the in-layer sorting relationship, the mutual influence between switch data in different levels and the same level is constrained, and the disordered combination of high-level switch data and low-level switch data is limited; After the hierarchical division and constraint processing are completed, the consistency check is performed on the switch switching sequence formed, and when the original hierarchical division does not match the actual balance influence strength, the level of the switch data and its constraint relationship are locally modified; The hierarchical division and in-layer sorting result of the locally modified switch data are integrated to form a stable and consistent hierarchical planning result.

[0032] In the embodiment, the matching state of each switching operation and the corresponding branch balance priority is checked, the sequence fragments deviating from the associated logic are modified, and a stable and executable optimized switching sequence set is output, specifically as follows: Based on the switch switching sequence, the branch identifier of each switching operation in the sequence is extracted one by one, and the balance priority data of the branch is associated to establish a one-to-one mapping relationship between the switching operation and the branch balance priority data; According to the execution order of the switch switching sequence, the branch balance priority data corresponding to the switching operation is sequentially compared, the sequence positions where the switching operation execution order and the branch balance priority sorting relationship are inconsistent are counted, and a switching sequence deviation marker set is formed; According to the switching sequence deviation marking set, the balance influence intensity associated with each switching operation in the sequence segment is extracted, and the balance influence evolution relationship in the corresponding sequence segment is constructed; The continuity of the balance influence evolution relationship of adjacent switching operations in the sequence segment is analyzed, and when the balance influence intensity does not show an enhancing trend in the sequence advancing process, the switching operation is identified as a balance discontinuous section, and the execution order of the switching operation in the section is locally adjusted on the premise of keeping the switching operation set unchanged; After the local adjustment is completed, based on the updated switching sequence, the multiple branch combinations with common influence range in the sequence are counted, and the switching operation set of the multiple branch combinations in the switching sequence is extracted; The balance influence intensity change of the multiple branch combinations before and after the execution of the switching sequence is backtracked and compared, and when the synergistic balance effect of the multiple branch combinations is weakened due to individual switching operations in the sequence, the switching operation that is weakened is marked as a synergistic inconsistent operation; The synergistic inconsistent operation is subjected to synergistic constraint correction processing, the relative position of the corrected switching sequence in the switching sequence and the combination relationship with other switching operations are adjusted, so that the stability of the multiple branch synergistic balance relationship in the whole execution process of the corrected switching sequence is maintained, and an optimized switching sequence set is output, wherein the stability of the multiple branch synergistic balance relationship refers to the consistency between the change trend of the branch load and the balance priority order direction during the execution of the switching sequence.

[0033] S3, when executing the optimized switching sequence set, acquiring line load data and dynamically updating balance priority data; In this embodiment, when the optimized switching sequence set is executed, the line load data is acquired, and the balance priority data is dynamically updated, as follows: By executing the optimized switching sequence set, the switching operations are sequentially performed on the switches in the distribution network line, and the line load states of each branch are collected in real time during the switching process to obtain line load data reflecting the switching influence, wherein the line load data includes active power, reactive power, current and voltage data of each branch; The line load data and the corresponding switching operation are time-aligned to make the branch load change consistent with the corresponding switching operation in the time dimension; Based on the time-aligned line load data, the load change characteristics of each branch before and after the switching execution are extracted, and through comprehensive analysis of the load change characteristics, the load response characteristics reflecting the switching effect are extracted, wherein the load change characteristics include the change amplitude and direction of active power, reactive power, current and voltage of each branch before and after the switching, and the load response characteristics include the instantaneous response of the switching operation to each branch load and the propagation path data of the multiple branch synergistic influence; The load response characteristics are associated with the balance priority data of the corresponding branch, the deviation between the load response and the priority is determined, and the range of the branch needing priority correction is determined; For the branch whose load response deviation exceeds the preset threshold in the branch range, the balance priority data is dynamically corrected according to the load response characteristics.

[0034] In the embodiment, based on the time-aligned line load data, the load change characteristics of each branch before and after the switching execution are extracted, and through comprehensive analysis of the load change characteristics, the load response characteristics reflecting the switching effect are extracted, as follows: Based on the line load data, the corresponding load data of each branch before and after the switching execution is determined according to the execution order of each switch switching operation in the switching sequence, and a one-to-one correspondence between the load state before switching and the load state after switching is formed; The load state before switching and the load state after switching are compared and analyzed, and the load evolution response characteristics directly reflecting the effect of single switching are extracted, including the change direction, change amplitude and change continuation trend of the load of each branch before and after the switching execution; Based on the load evolution response characteristics, the time continuity of the load change process of each branch is analyzed, whether the load change presents a smooth transition is judged, and an initial load response characteristic set describing the immediate influence characteristics of the switching effect is formed; According to the initial load response characteristic set, the load change process is expanded in multiple time scales, and the initial load response characteristics are extracted, including the short-time load response characteristics after switching execution and the continuation load response characteristics in the continuous operation stage, wherein the short-time load response characteristics include the instantaneous change amplitude and change direction of the active power, the reactive power, the current and the voltage of each branch after switching, and the continuation load response characteristics include the average change trend and the fluctuation range of the load of each branch in the continuous operation stage; The consistency of the initial load response characteristics extracted in different time scales is analyzed, whether the change direction and the change trend of the load response remain consistent in the time advancing process is counted, and the load response stability characteristics for characterizing the stability of the switching effect are formed; Based on the load response stability characteristics, the multi-branch combination of the associated load change under the action of the same switching operation is counted, the load change characteristics of the multi-branch combination are analyzed, the propagation path characteristics and the influence diffusion characteristics of the load response between the branches are extracted, wherein the propagation path characteristics include the order, path length and node connection relationship of the load response change of each branch in the topology structure, and the influence diffusion characteristics include the amplitude change, diffusion speed and affected branch quantity of the load response propagation between the branches; The propagation path feature is fused with the load evolution response feature corresponding to each branch (a weighted feature fusion method is adopted) to form a load response feature.

[0035] In this embodiment, the load response feature is associated with the balance priority data of the corresponding branch, the deviation degree between the load response and the priority is determined, and the branch range that needs to be corrected in priority is determined, as follows: Based on the load response feature, response intensity data representing the degree of load change is extracted for each branch of the current switching operation, and the response intensity data includes the load change amplitude, change rate and change direction of each branch; The response intensity data of each branch is sorted to generate a response intensity sorting result reflecting the strong and weak relationship of the load response of each branch in the current switching operation; The balance priority data corresponding to each branch is obtained, and a branch priority sorting relationship is established according to the balance priority data; The response intensity sorting result is compared and analyzed with the branch priority sorting relationship, and when the sorting relationship between them is inconsistent and the sorting deviation exceeds a preset deviation threshold, it is determined that the corresponding branch has a sorting deviation between the load response and the balance priority; For different balance priority levels, corresponding load response expected intervals are established, wherein the load response expected interval is used to limit the reasonable change range of the load response feature of the branch under the balance priority level, and the upper and lower limits are determined by the confidence interval method; The load response feature of each branch is matched with the load response expected interval corresponding to the balance priority level, and when the load response feature exceeds the corresponding load response expected interval, it is determined that the branch has an interval deviation between the load response and the balance priority; Based on the sorting deviation determination result and the interval deviation determination result, the matching state between the load response and the balance priority of each branch is comprehensively judged; When the branch meets the sorting deviation and interval deviation determination at the same time, the corresponding branch is determined as the branch range that needs to be corrected in balance priority, and when the branch does not meet the determination at the same time, the original balance priority data of the branch is maintained unchanged.

[0036] In this embodiment, for the branch whose load response deviation exceeds a preset threshold, the balance priority data of the branch is dynamically corrected according to the load response feature, as follows: Based on the load response feature, the load response deviation of each branch is obtained, and the load response deviation is divided into several deviation levels, wherein the load response deviation is used to quantify the deviation degree between the load response of the branch and the expected balance priority; The change direction of the load response characteristics of each branch is counted, and the load response direction is compared with the expected direction of the adjustment of the current balance priority of the branch to determine whether the load response direction is consistent with the priority adjustment direction; The contribution weight of each branch in the overall load balance is calculated to determine the priority execution order and adjustment range of the priority correction of each branch, wherein the contribution weight is obtained according to the principal component analysis method of quantifying the load change of the branch; According to the deviation level, the response direction comparison result and the contribution weight of the branch, the priority correction amount and the correction direction of each branch are determined, wherein the higher the deviation level, the greater the priority correction range, when the response direction is inconsistent with the expectation, the correction direction is adjusted to meet the load balance optimization goal, and the higher the contribution weight of the branch, the priority execution priority correction is performed; According to the priority correction amount and the correction direction, the dynamic adjustment operation of the balance priority data of the branch to be corrected is performed, and the adjustment result is recorded, wherein the dynamic adjustment operation refers to real-time increase or decrease of the original balance priority value according to the priority correction amount and the correction direction of the branch; After completing the balance priority correction operation of all branches, the branch priority order is updated.

[0037] S4, according to the updated balance priority data, the real-time state vector of the distribution network line is corrected; In this embodiment, according to the updated balance priority data, the real-time state vector of the distribution network line is corrected, and the specific process is as follows: According to the dynamically updated balance priority data of each branch, the balance priority change characteristics are compared with the balance priority data corresponding to the state vector of the last round to form the balance priority change characteristics; The balance priority change characteristics are compared with the real-time state vector of the distribution network line branch by branch, and based on the state elements in the state vector, the state of the branch is determined whether the state of the branch is consistent with the change direction or the change degree of the balance priority change characteristics, so as to identify the inconsistent state part of the branch in the state vector; Based on the inconsistent state part of the branch, the deviation characteristics related to the priority change are analyzed and extracted according to the balance priority change characteristics to form a set of state elements to be corrected; According to the dynamically updated balance priority data of the corresponding branch, the phase state element in the real-time state vector is corrected; The state vector of each branch after correction is updated, the continuous corresponding relationship between the updated real-time state vector and the dynamically updated balance priority data is established, and the real-time state vector of the distribution network line consistent with the dynamically updated balance priority data is output.

[0038] In this embodiment, based on the inconsistent branch state part, combined with the balance priority change feature, the deviation feature related to the priority change is analyzed and extracted to form a set of state elements to be corrected, as follows: The real-time state vector of each branch and the balance priority change feature are used to construct a state-priority difference matrix, wherein the matrix row represents the branch, the matrix column represents each state element, and the deviation value of the matrix element is calculated to quantify the inconsistency between the branch state and the balance priority change; According to the state-priority difference matrix, it is judged whether the deviation value exceeds the preset threshold, and the state element whose deviation value exceeds the threshold is marked as a candidate state to be corrected; The contribution of each deviation to the overall distribution of the distribution network state balance is calculated, and the candidate state elements to be corrected are weighted and sorted according to the contribution, to form a set of state elements to be corrected, wherein the contribution is quantified by the weighted influence scoring method, and the influence of the deviation value of each state element on the overall branch load distribution and voltage stability, so as to obtain the contribution of each deviation to the overall distribution of the distribution network state balance.

[0039] In this embodiment, the phase state elements in the real-time state vector are corrected according to the dynamically updated balance priority data of the corresponding branch, as follows: Based on the set of state elements to be corrected of each branch and the corresponding dynamically updated balance priority data, the difference between the current priority and the last round priority of each branch is obtained; The difference value is mapped to the corresponding phase state element correction amount, and the phase state element to be corrected in the real-time state vector is preliminarily adjusted according to the priority difference, so that the correction amplitude and the priority change amount are kept in a corresponding relationship, wherein the preliminary directional adjustment is a linear increase or decrease processing of the value of each phase state element to be corrected; Combined with the contribution of each branch to the overall load balance of the distribution network, the branch contribution weight and the correction amount are weighted to determine the correction priority order and the final adjustment amplitude of the state elements to be corrected of each branch, so as to ensure that the key branch is corrected first, and the low-contribution branch is delayed or fine-tuned; After the preliminary directional correction is completed, the set of state elements to be corrected is reacquired, and the priority difference and the contribution weight of each branch are kept for the next round of directional correction operation; The next round of directional correction operation is performed according to the new set of state elements to be corrected, and the correction amplitude is kept consistent with the priority difference and the contribution weight, to form a multi-round feedback iterative correction; The multi-round feedback iteration is repeatedly performed until the correction amount of the state to be corrected of each branch meets the preset tolerance range, so as to realize the high consistency between the real-time state vector and the dynamically updated balance priority data; After completing multiple rounds of iterations, a continuous correspondence relationship with the dynamically updated balance priority data is established, and an updated real-time state vector is output.

[0040] Embodiment 2, Figure 2 A system of a distribution network line adaptive balance switching method based on real-time state evaluation is given, which comprises a state acquisition and balance priority generation module, an optimized switching sequence generation module, a load data acquisition and balance priority dynamic updating module, and a state vector dynamic correction module, and there is a connection between the modules. The state acquisition and balance priority generation module is used to acquire the real-time state vector of the distribution network line, and form the balance priority data of each branch. The optimized switching sequence generation module is used to dynamically adjust the switch data according to the balance priority data, and form the optimized switching sequence set. The load data acquisition and balance priority dynamic updating module is used to acquire the line load data when the optimized switching sequence set is executed, and dynamically update the balance priority data. The state vector dynamic correction module is used to correct the real-time state vector of the distribution network line according to the updated balance priority data.

[0041] The above embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. When realized by software, the above embodiments can be realized in the form of a computer program product in whole or in part.

[0042] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0043] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0044] The above is only a specific technical solution of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0045] Finally: the above only for the preferred embodiments of the present application, and not for limiting the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application, should be included in the scope of protection of the present application.

Claims

1. A real-time state evaluation-based distribution network line adaptive balanced switching method, characterized in that, The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device.

2. The method of claim 1, wherein, The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device.

3. The method of claim 2, wherein, The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device.

4. The method of claim 2, wherein the method further comprises: The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to a power distribution network line state vector real-time acquisition method and a power distribution network line state vector real-time acquisition device. The application relates to Based on the persistence characteristics in each branch state vector, the sorting change direction of the branch in the candidate conflict sorting region is analyzed, and it is judged whether the current sorting path is consistent with the branch operation evolution trend; According to the candidate conflict sorting region of the inconsistent sorting path, combined with the consistency judgment result of the coordinated branch group based on the persistence characteristics of each branch state vector, multi-feature consistent voting judgment is performed on the conflict sorting region to determine the unified adjustment direction of the sorting correction; According to the multi-feature consistent voting judgment result, the branch balance priority data in the candidate conflict sorting region is locally corrected; The branch balance priority data after local correction is compared and verified with the sorting path, and each branch balance priority data is output.

5. The method of claim 1, wherein, The switch data is dynamically adjusted according to the balance priority data to form an optimized switching sequence set, specifically as follows: Based on the balance priority data of each branch, the switch data of each branch is obtained, and the switch data of each branch is corresponded to the balance priority data of each branch; Based on the corresponding relationship, the balance priority data of each branch is mapped, the characteristic value of the branch affecting the overall balance of the distribution network is extracted, and the balance influence strength corresponding to each branch is formed; According to the balance influence strength, the corresponding switch data is hierarchically planned, and the relationship between different switch data is constrained in the hierarchical process; Through the path screening mechanism, the switch data combination with multiple execution paths is screened; The screened and rearranged switch data is combined according to the balance influence strength to form a switching sequence; The matching state of each switching operation and the corresponding branch balance priority is checked, and the sequence segment deviating from the associated logic is corrected to output the optimized switching sequence set.

6. The method of claim 5, wherein the method further comprises: The matching state of each switching operation and the corresponding branch balance priority is checked, and the sequence segment deviating from the associated logic is corrected to output the optimized switching sequence set. Based on the switch switching sequence, the branch identifier of each switching operation in the sequence is extracted one by one, and the balance priority data of the branch is associated to establish a mapping relationship between the switching operation and the branch balance priority data; According to the execution order of the switch switching sequence, the branch balance priority data corresponding to the switching operation is sequentially compared, the sequence position where the switching operation execution order is inconsistent with the branch balance priority order is counted, and a switching order deviation marker set is formed; According to the switching order deviation marker set, the balance influence strength associated with each switching operation in the sequence segment is extracted to construct the balance influence evolution relationship in the corresponding sequence segment; The balance influence evolution relationship of adjacent switching operations in the sequence segment is analyzed for continuity, and the execution order of the switching operation in the balance discontinuous section is locally adjusted; After completing the local adjustment, based on the updated switching sequence, the multi-branch combination with common influence range in the sequence is counted, and the switching operation set of the multi-branch combination in the switching sequence is extracted; The balance influence strength change of the multi-branch combination before and after the switching sequence execution is backtracked and compared to obtain the inconsistent operation; The inconsistent operation is subjected to cooperative constraint correction processing, and the optimized switching sequence set is output.

7. The method of claim 1, wherein the method further comprises: When executing the optimized handover sequence set, line load data is obtained and balancing priority data is dynamically updated, as follows: By executing an optimized switching sequence set, switching operations are performed on the switches in the distribution network line in sequence, and line load data is obtained; The line load data is time-aligned with the corresponding switching operations. Based on the time-aligned line load data, the load change characteristics of each branch before and after the handover are extracted, and the load response characteristics are extracted through comprehensive analysis of the load change characteristics. By correlating load response characteristics with the balance priority data of the corresponding branches, the deviation between load response and priority is determined, and the range of branches for priority correction is obtained. For branches whose load response deviation exceeds a preset threshold, dynamic correction is performed on their balance priority data based on load response characteristics.

8. The method of claim 7, wherein the method further comprises: The process of associating load response characteristics with the balance priority data of corresponding branches to determine the deviation between load response and priority, and obtaining the branch range for priority correction, is as follows: Based on load response characteristics, response intensity data is extracted for each branch of the current switching operation; The response intensity data of each branch is sorted to generate a response intensity ranking result. Obtain the balance priority data for each branch and establish a branch priority ranking relationship based on the balance priority data. The response intensity ranking results are compared and analyzed with the branch priority ranking relationship to determine whether there is a ranking deviation between load response and balance priority for the corresponding branch. Establish corresponding load response expectation ranges for different load balancing priority levels; The load response characteristics of each branch are matched with the expected range of the load response for the corresponding balance priority level to determine whether there is a range deviation between the load response and the balance priority of the branch. Based on the sorting deviation judgment results and the interval deviation judgment results, a comprehensive judgment is made on the matching status between the load response and balance priority of each branch. When a branch simultaneously meets the criteria for sorting deviation and interval deviation, the corresponding branch is determined as the branch range for balance priority correction. If a branch does not simultaneously meet the criteria, its original balance priority data remains unchanged.

9. The method of claim 1, wherein, The real-time status vector of the distribution network lines is corrected based on the updated balance priority data, as follows: Based on the dynamically updated balance priority data of each branch, compare its balance priority data with the balance priority data corresponding to the previous round state vector to form balance priority change characteristics. By comparing the balance priority change characteristics with the real-time status vector of the distribution network line branch by branch, the status of the branch in the status vector that is inconsistent with the priority change is identified. Based on the inconsistent branch state, combined with the balance priority change characteristics, the deviation characteristics related to the priority change are analyzed and extracted to form a set of state elements to be corrected. Based on the dynamically updated balance priority data of the corresponding branch, the phase elements in the real-time state vector are corrected in a targeted manner. The state vectors of the branches are updated uniformly, a continuous corresponding relationship between the updated real-time state vectors and the dynamically updated balance priority data is established, and the real-time state vectors of the distribution network lines consistent with the dynamically updated balance priority data are output.

10. A device using the adaptive balancing switching method of distribution network lines based on real-time state evaluation according to any one of claims 1-9, characterized in that, The system comprises a state acquisition and balance priority generation module, an optimized switching sequence generation module, a load data acquisition and balance priority dynamic updating module, and a state vector dynamic correction module, and the modules are connected; The state acquisition and balance priority generation module is used to acquire real-time state vectors of the distribution network lines and form balance priority data of each branch. The optimized switching sequence generation module is used to dynamically adjust switch data according to the balance priority data and form an optimized switching sequence set. The load data acquisition and balance priority dynamic updating module is used to acquire line load data and dynamically update the balance priority data when the optimized switching sequence set is executed. The state vector dynamic correction module is used to correct the real-time state vectors of the distribution network lines according to the updated balance priority data.

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