Technical metadata processing storage method and system of power grid system

Abstract

The invention relates to the technical field of power grid data management, in particular to a technical metadata processing storage method and system of a power grid system, and the method comprises the following steps: extracting node identifiers and associated line parameters in the power grid system, analyzing a connection relationship between nodes, identifying an initial weight value, calling the weight value to analyze topology hierarchy information, and storing the topology hierarchy information; and analyzing the capacity transfer characteristics of the power grid line, and generating a line capacity transfer characteristic table. According to the method, by extracting and analyzing the node identifiers and the line parameters in the power grid system, the load management efficiency of the power grid can be remarkably improved, the connection relation between the nodes and the network topology structure can be accurately identified, the capacity can be flexibly adjusted under the variable load requirement through the dynamic load capacity distribution table, and the load management efficiency is improved. The stability and reliability of the power grid are enhanced by combining the load capacity and the storage priority, and the operation continuity and safety of the power grid are improved by optimizing a risk management strategy and reducing system faults.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid data management, and in particular to a method and system for processing and reserving technical metadata of a power grid system. Background Art

[0002] The field of power grid data management technology covers a wide range of technologies and methods aimed at improving the operational efficiency and reliability of the power grid by integrating and analyzing the metadata of the power grid system. The technologies include data acquisition, storage, processing and analysis, aiming to optimize the performance and management of the power grid. Power grid data management technology applications include fault detection, load prediction, maintenance scheduling and asset management. This technical field relies on advanced data processing tools and algorithms, such as big data analysis, machine learning and artificial intelligence, as well as various software and hardware platforms to ensure real-time processing and analysis of data, making power grid operations more intelligent, automated and reliable.

[0003] Among them, the technical metadata processing and storage methods of power grid systems involve an important part of power grid data management technology, namely how to effectively process and store the technical metadata generated in the power grid system, including collecting metadata from various components of the power grid, such as power stations, substations and distribution networks, and how to convert data into useful information for optimizing the design and operation of the power grid. The processing and storage methods enable power grid operators to achieve better resource allocation, preventive maintenance and fault response, and improve the efficiency and reliability of the power grid. This topic is crucial to achieving efficient and automated management of the power grid, and is a research direction of particular concern in the current power industry.

[0004] Existing technologies have certain limitations in dealing with real-time changing load demands and optimizing grid resource allocation. Grid load management relies on traditional data processing methods, which are not flexible and timely enough in the face of high-speed and dynamically changing data streams, making it difficult to achieve rapid load adjustment. Existing technologies lack sufficient foresight in risk management and preventive maintenance strategies, resulting in insufficient response to emergencies, causing power outages and other problems, and thus affecting the stability and efficiency of the grid. Especially in extreme weather or high-load conditions, existing technologies fail to make full use of advanced data analysis tools to predict and manage potential grid risks, which limits the overall performance of grid operations. The lack of efficient load prediction and dynamic capacity adjustment capabilities also makes it difficult for the grid to achieve optimal energy conservation, emission reduction and cost-effectiveness, affecting the sustainable development and long-term operation efficiency of the grid. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for processing and reserving technical metadata of a power grid system.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a method for processing and reserving technical metadata of a power grid system, comprising the following steps:

[0007] S1: By extracting node identifiers and associated line parameters in the power grid system, analyzing the connection relationship between nodes and identifying initial weight values, calling weight values ​​to parse topological level information, analyzing the capacity transfer characteristics of power grid lines, and generating a line capacity transfer characteristic table;

[0008] S2: calling the capacity transfer parameters in the line capacity transfer characteristic table, combining the load capacity value and storage priority parameter of the power grid line, analyzing the storage allocation index, generating a capacity storage allocation sequence, and sorting the lines by capacity allocation weights, adjusting the capacity allocation ratio, and generating a power grid dynamic load capacity allocation table;

[0009] S3: calling the line adjustment value and the load line list in the dynamic load capacity allocation table of the power grid, analyzing the line stability parameters and screening the load lines, extracting the associated nodes and the remaining capacity of the load lines, generating a list of power grid risk reserve paths, extracting the priority data in the list of power grid risk reserve paths and sorting them, and generating a power grid path priority analysis result;

[0010] S4: Call the priority value and operation sequence of the reserve path in the power grid path priority analysis result, integrate the lines and reserve nodes in the path, extract the priority adjustment data of the reserve operation instruction, integrate the operation list corresponding to the reserve path, extract and record the line reserve and operation adjustment, and generate a power grid reserve parameter configuration plan.

[0011] As a further solution of the present invention, the step of obtaining the line capacity transfer characteristic table is specifically as follows:

[0012] S111: extracting node identifiers and associated line parameters in the power grid system, including voltage level, current capacity, and impedance characteristics, comparing values ​​between nodes in turn through the parameters, determining connection relationships between nodes, and obtaining connection information of initial nodes;

[0013] S112: Based on the connection information of the initial nodes, the current capacity and impedance characteristics between the nodes are called to calculate the initial weight values ​​between the nodes, using the formula:

[0014]

[0015] Get the weight value between nodes;

[0016] Among them, w ij represents the weight value between node i and node j, Q i and I j Represent the current values ​​of nodes i and j respectively, Z ijrepresents the impedance value between nodes i and j, V i and V j Represent the voltage values ​​of nodes i and j respectively, α and β are the voltage weight adjustment coefficients;

[0017] S113: Analyze the topological structure of the power grid lines by using the inter-node weight values, identify the connection characteristics and capacity transfer rules between the lines, and generate a line capacity transfer characteristic table.

[0018] As a further solution of the present invention, the step of obtaining the capacity storage allocation sequence is specifically as follows:

[0019] S211: extracting the load capacity value corresponding to the line based on the capacity transfer parameter in the line capacity transfer characteristic table, dividing the distribution interval of the load capacity value into intervals, analyzing the correlation between the line operation state and the capacity transfer parameter, and obtaining the line load capacity distribution sequence;

[0020] S212: Based on the line load capacity distribution sequence, storage priority parameters are matched section by section, and the corresponding relationship between the priority parameters and the line load requirements is calculated and weighted item by item, and a comparison and analysis of the priority characteristics and the load distribution is performed to refine the priority requirement contribution and obtain a storage requirement characteristic distribution table;

[0021] S213: Based on the storage demand characteristic distribution table, storage capacity is allocated by segmenting and gradually allocating the proportion of priority demands, adjusting the proportion and supplementing the difference in combination with capacity transfer parameters, optimizing the dynamic allocation results according to line requirements, and obtaining a capacity storage allocation sequence.

[0022] As a further solution of the present invention, the steps of obtaining the dynamic load capacity allocation table of the power grid are specifically as follows:

[0023] S221: Based on the capacity storage allocation sequence, according to the original load data and the real-time monitoring data, extract the daily average capacity occupancy rate of each line in the power grid, the fluctuation range of the peak value and the valley value, perform data statistics, analyze the stability and efficiency indicators of the line, and obtain the dynamic load weight set of the line;

[0024] S222: Using the dynamic load weight set of the lines, sort each line according to the weight, power transmission efficiency and capacity requirement, using the formula:

[0025]

[0026] Calculate the capacity allocation weight adjustment factor for each line and generate a capacity allocation weight sorted list;

[0027] Among them, V loadrepresents capacity utilization, E represents power transmission efficiency, R d is the load fluctuation range, b and B are the adjustment factor and exponential factor respectively, and A represents the capacity allocation weight of the line;

[0028] S223: Based on the capacity allocation weight sorting list, adjust the capacity of the lines in the power grid according to the current weight allocation ratio, and generate a power grid dynamic load capacity allocation table in combination with the line power demand and load characteristics.

[0029] As a further solution of the present invention, the steps of obtaining the risk reserve path list are specifically as follows:

[0030] S311: extracting the real-time adjustment value and load parameter of the line from the dynamic load capacity allocation table of the power grid, screening unstable and overloaded lines by comparing the difference between the real-time load and the set upper and lower limits of the load, and generating a preliminary screened line set;

[0031] S312: Based on the initially screened line set, the nodes and remaining capacity of each line are analyzed, and the potential risk index of each line is calculated using the formula:

[0032]

[0033] Determine the priority of each route and generate a list of risk assessment results;

[0034] Among them, C current Indicates the current load capacity, C max represents the maximum allowed capacity, ΔC represents the capacity difference with nearby nodes, γ is the adjustment coefficient, and R risk Indicates the potential risk index of the line;

[0035] S313: calling the risk assessment result list, sorting each line according to the risk index, screening risk lines and checking the spare capacity of associated nodes, summarizing the screened data, and creating a grid risk reserve path list.

[0036] As a further solution of the present invention, the step of obtaining the path priority analysis result is specifically as follows:

[0037] S321: Based on the grid risk reserve path list, extract the priority field data, locate the priority fields in the list, separate them one by one, and determine and standardize the field data type, remove non-priority related fields and duplicate items, and generate a grid priority data set;

[0038] S322: Based on the power grid priority data set, classify and sort the priority data, analyze the priority rules and compare and group the path attributes in the data items, combine the path characteristic fields in the data, adjust the items with repeated and missing attributes in the classification, and generate the power grid path attribute priority sorting result;

[0039] S323: Based on the grid path attribute priority sorting results, path priority weights are summarized and sorted, classified path weight data is extracted, and the priority sequence is re-sorted in combination with the path characteristic fields. The weight proportion relationship in the sorting results is analyzed and the sequence deviation is corrected to generate a grid path priority analysis result.

[0040] As a further solution of the present invention, the steps of obtaining the power grid reserve parameter configuration solution are specifically as follows:

[0041] S411: extracting the priority value and operation sequence of the reserve path from the power grid path priority analysis result, parsing the parameters of the line in each path and the associated reserve node information, evaluating the reserve contribution level of the path by analyzing the line priority value in the path and the load distribution ratio of the reserve node, and establishing a path reserve contribution information set;

[0042] S412: Call the path reserve contribution information set, extract the operation instruction priority of the reserve node, combine the remaining capacity and load fluctuation data, and use the formula:

[0043]

[0044] Calculate the adjusted operation priority, integrate the priority data of the path reserve nodes, and obtain the reserve operation instruction priority adjustment data;

[0045] Among them, P adj Indicates the adjusted operation priority, P base is the basic priority, ΔR represents the coefficient of variation of the remaining capacity of the reserve node, ΔL is the load fluctuation difference value, and η is the adjustment factor;

[0046] S413: Reorder the adjustment priority instructions within the reserve path in combination with the reserve operation instruction priority adjustment data and the path reserve contribution information set, record the operation information of the reserve nodes and lines, integrate the operation steps according to the sorting results, and generate a power grid reserve parameter configuration plan.

[0047] A technical metadata processing and reserve system for a power grid system, the technical metadata processing and reserve system for a power grid system is used to execute the technical metadata processing and reserve method for a power grid system, the system comprising:

[0048] The node topology relationship analysis module extracts node identifiers and associated line parameters in the power grid system, quantifies the power flow between nodes, classifies the topological structure of the power grid, and constructs topological hierarchical analysis results;

[0049] The line capacity dynamic distribution module uses the structural information in the topology level analysis result to identify key transmission lines, adjust the load capacity of the lines to match the real-time demand, and adjust the priority of the lines according to the real-time load to obtain the line capacity dynamic distribution data;

[0050] The storage priority planning module analyzes the matching degree between the storage unit and the line according to the dynamic distribution data of the line capacity, prioritizes the storage unit according to the load fluctuation, adjusts the storage strategy and optimizes the energy allocation, and obtains the storage allocation priority sequence;

[0051] The grid resilience optimization module extracts risk assessment of key lines from the storage allocation priority sequence, identifies potential failure points, develops emergency response paths and responds to power outages, and builds a risk reserve path list;

[0052] The reserve path integration module configures the backup resources according to the risk reserve path list and refers to the real-time conditions of the lines and nodes to generate a power grid reserve parameter configuration plan.

[0053] Compared with the prior art, the advantages and positive effects of the present invention are:

[0054] In the present invention, by extracting and analyzing the node identification and associated line parameters in the power grid system, identifying and sorting the capacity allocation weights of the lines, the load management efficiency of the power grid can be significantly improved. This analysis method can accurately identify the connection relationship between nodes and parse the topological structure of the network, which helps to more accurately predict and manage the energy flow in the power grid. Through the dynamic load capacity allocation table, the power grid is supported to flexibly adjust its capacity under different circumstances, improve its responsiveness to changing load demands, and combine load capacity with storage priority to ensure the energy supply of important nodes at critical moments and enhance the stability and reliability of the power grid. By analyzing and screening the stability parameters of the lines and optimizing the risk management strategy of the power grid, the possibility of power grid system failures is further reduced, ensuring the continuity and safety of power grid operation. Through efficient data processing and intelligent load distribution, the optimization of power grid operation is achieved, which plays a key role in promoting the modernization and automation of power grid management. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0056] Figure 2 It is a flow chart of the line capacity transfer characteristic table in the present invention;

[0057] Figure 3 A flow chart of a capacity storage allocation sequence in the present invention;

[0058] Figure 4 It is a flow chart of the dynamic load capacity allocation table of the power grid in the present invention;

[0059] Figure 5 A flow chart of the risk reserve path list in the present invention;

[0060] Figure 6 It is a flow chart of the path priority analysis result in the present invention;

[0061] Figure 7 The figure is a flow chart of the power grid reserve parameter configuration scheme in the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0063] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0064] See also Figure 1 The present invention provides a technical solution: a method for processing and reserving technical metadata of a power grid system, comprising the following steps:

[0065] S1: By extracting node identifiers and associated line parameters in the power grid system, analyzing the connection relationship between nodes and identifying initial weight values, calling weight values ​​to parse topological level information, analyzing the capacity transfer characteristics of power grid lines, and generating a line capacity transfer characteristic table;

[0066] S2: call the capacity transfer parameters in the line capacity transfer characteristic table, combine the load capacity value of the power grid line with the storage priority parameter, analyze the storage allocation index, generate the capacity storage allocation sequence, sort the lines by capacity allocation weight, adjust the capacity allocation ratio, and generate the power grid dynamic load capacity allocation table;

[0067] S3: Call the line adjustment value and the load line list in the power grid dynamic load capacity allocation table, analyze the line stability parameters and filter the load lines, extract the associated nodes and remaining capacity of the load lines, generate a power grid risk reserve path list, extract the priority data in the power grid risk reserve path list and classify and sort it, and generate a power grid path priority analysis result;

[0068] S4: Call the priority value and operation sequence of the reserve path in the power grid path priority analysis result, integrate the lines and reserve nodes in the path, extract the priority adjustment data of the reserve operation instruction, integrate the operation list corresponding to the reserve path, extract and record the line reserve and operation adjustment, and generate a power grid reserve parameter configuration plan.

[0069] The power grid line capacity transfer characteristic table includes node identification, associated line parameters, and capacity transfer characteristics. The capacity storage allocation sequence includes storage allocation indicators, load capacity values, and storage priority parameters. The power grid dynamic load capacity allocation table includes capacity allocation weights, adjusted capacity allocation ratios, and circuit load adjustment values. The power grid risk reserve path list includes risk reserve paths, remaining capacity, and priority classification data. The power grid path priority analysis results include path priority values, operation sequences, and reserve path integration information. The power grid reserve parameter configuration plan includes a reserve path list, reserve operation adjustment data, and line reserve configuration parameters.

[0070] See also Figure 2 , the specific steps for obtaining the line capacity transfer characteristic table are:

[0071] S111: extracting node identifiers and associated line parameters in the power grid system, including voltage level, current capacity, and impedance characteristics, comparing values ​​between nodes in turn through the parameters, determining connection relationships between nodes, and obtaining connection information of initial nodes;

[0072] The unique identifier of each node in the power grid system and the basic parameters of the associated lines, including voltage level, current capacity and impedance characteristics, are extracted, and the basic parameters are organized into a node attribute table. By classifying and summarizing the voltage level, current capacity and impedance characteristics, the basic information of each node is ensured to be accurate. For each parameter in the node attribute table, it is called in sequence according to the logical order of the node unique identifier, and the parameters of each node are grouped and organized to form a node attribute set. Each group of parameters is checked for consistency to ensure that the node parameters are logically relevant and data valid. Based on the node attribute set, the association randomness between nodes is calculated. By comparing the voltage level difference, the current capacity ratio and the impedance matching degree, it is determined whether there is a physical connection relationship between the nodes. Further, combined with the basic parameters of the associated lines, the lines between the nodes are parsed row by row and column by column to ensure that each row and column represents a unique node, and its elements are the identifier of the connection between nodes or the associated line parameter information, and the connection information of the initial node is generated.

[0073] S112: Based on the connection information of the initial nodes, the current capacity and impedance characteristics between the nodes are called to calculate the initial weight values ​​between the nodes using the formula:

[0074]

[0075] Get the weight value between nodes;

[0076] Among them, w ij represents the weight value between node i and node j, Q i and I j Represent the current values ​​of nodes i and j respectively, Z ij represents the impedance value between nodes i and j, V i and V j Represent the voltage values ​​of nodes i and j respectively, α and β are the voltage weight adjustment coefficients;

[0077] The formula is beneficial in that it takes into account the strength of the physical connection between nodes in the power grid by introducing a calculation form combining the current difference and the impedance ratio. At the same time, the weighted term of the square of the voltage strengthens the role of the voltage in the weight calculation, so that the calculation result can more truly reflect the connection characteristics and operating conditions between nodes.

[0078] According to the connection information of the initial node, extract each parameter from the node attribute set and set Q i =300A, I j =280A, Z ij =0.05Ω、V i =220kV, V j =220kV, adjustment coefficient α=0.1, β=0.2, substitute into the formula:

[0079]

[0080] The result shows that the weight value between nodes is 14920. This weight value quantifies the connection characteristics of node i and node j, which can be used for further analysis and classification of line capacity transfer characteristics.

[0081] S113: Analyze the topological structure of the power grid lines by using the weight values ​​between the nodes, identify the connection characteristics and capacity transfer rules between the lines, and generate a line capacity transfer characteristic table;

[0082] The weight values ​​between nodes are used to parse the weight value matrix and the initial node connection information. First, the weight value matrix is ​​traversed row by row and column by column to determine the weight values ​​of each pair of nodes in the matrix. By sorting the weight values ​​from high to low, the lines that are significantly higher than the node weight values ​​are screened and the lines are divided into high levels. Then, the remaining lines with lower weight values ​​are layered according to the weight value range distribution to ensure the dynamic and adaptability of the hierarchical division. Through this hierarchical analysis method, the multi-level line division results are obtained. Combined with the weight value change law in each level, the capacity distribution characteristics between lines are analyzed. For lines in the same level, according to the specific distribution range of the weight value, the unevenly distributed lines are marked as special lines, and the lines are further dynamically adjusted. Through multiple iterations, the line capacity transfer characteristic table is generated to ensure that the line distribution characteristics can fully reflect the topological structure and capacity distribution law of the power grid line connection.

[0083] See also Figure 3 , the steps for obtaining the capacity storage allocation sequence are as follows:

[0084] S211: extracting the load capacity value corresponding to the line based on the capacity transfer parameter in the line capacity transfer characteristic table, dividing the distribution interval of the load capacity value into intervals, analyzing the correlation between the line operation state and the capacity transfer parameter, and obtaining the line load capacity distribution sequence;

[0085] By screening and sorting the load capacity data of each time period during the operation of the line, a distribution characteristic set of load capacity values ​​is constructed, and the load capacity in each time period is subdivided into distribution intervals to clarify the range of high load and low load intervals. According to the interval, according to the transfer parameters in the capacity transfer characteristic table, the distribution of load capacity values ​​is classified item by item, and the significant change values ​​of capacity transfer in different intervals are marked. By analyzing the corresponding relationship between the line operation status and the capacity transfer parameters, the capacity transfer rules under different operation states are identified. Combined with the historical operation data of the line, the contribution ratio of capacity transfer under each operation state is refined, and the line load capacity distribution sequence is obtained. Abnormal points and trends are marked to support subsequent storage priority parameter matching.

[0086] S212: Based on the line load capacity distribution sequence, the storage priority parameters are matched section by section, the corresponding relationship between the priority parameters and the line load requirements is calculated and weighted item by item, and the priority characteristics are compared and analyzed with the load distribution to refine the priority requirement contribution and obtain a storage requirement characteristic distribution table;

[0087] By calculating the one-to-one correspondence between the load capacity distribution interval and the storage priority parameter, and using the different hierarchical values ​​of the priority parameter, the weight value of each interval in the storage demand is refined, and by comparing the item-by-item calculation results of the priority parameter and the line load demand, the contribution ratio of different priorities to the load demand is determined, and the contribution ratio is normalized according to the hierarchical weight of the priority to enhance the accuracy of the analysis. Combined with the comparison results, a comparison characteristic table of priority characteristics and load distribution is generated, and the significant impact intervals of different priorities in the load distribution are marked in the table. Through the refined calculation of the distribution trend, the calculation results of the priority demand contribution are optimized, thereby forming a storage demand characteristic distribution table.

[0088] S213: Based on the storage demand characteristic distribution table, storage capacity is allocated, by segmenting and gradually allocating the proportion of priority demand, adjusting the proportion and supplementing the difference in combination with capacity transfer parameters, and optimizing the dynamic allocation result according to the line demand to obtain the capacity storage allocation sequence;

[0089] The required capacity is calculated by segmenting the priority contribution data in the storage demand table, and the different priority demand ratios are allocated segment by segment. The specific storage occupancy value of each priority partition is refined. Combined with the capacity transfer parameters, the allocation ratio is dynamically adjusted by comparing the change rate of the transfer characteristics in different time periods. The dynamic allocation optimization of the supplementary capacity is performed according to the difference after the segment adjustment to make up for the deviation of the storage capacity. For the dynamic allocation results, the load demand characteristic table of the line is checked one by one to ensure that each storage capacity allocation value meets the priority demand characteristics of the corresponding line. The optimized capacity storage allocation results are organized into a capacity storage allocation sequence for subsequent dynamic management and optimization.

[0090] See also Figure 4 , the specific steps for obtaining the dynamic load capacity allocation table of the power grid are:

[0091] S221: Based on the capacity storage allocation sequence, according to the original load data and real-time monitoring data, the daily average capacity occupancy rate of each line in the power grid, the fluctuation range of the peak value and the valley value are extracted, and data statistics are performed to analyze the stability and efficiency indicators of the line, and the dynamic load weight set of the line is obtained;

[0092] First, it is necessary to call the original load records and real-time monitoring equipment to collect the daily maximum load value, minimum load value and the corresponding time of each line, and calculate the daily average capacity occupancy rate based on the data of multiple lines. Then, analyze the load fluctuation amplitude, and obtain the fluctuation range by counting the difference between the maximum and minimum values ​​of the daily fluctuation of each line. At the same time, record the load change trend in each time period, and then classify the above characteristic data into a load characteristic set. Finally, based on the comprehensive extraction results of all line data, establish a dynamic load weight set for the line.

[0093] S222: Using the dynamic load weight set of the lines, each line is sorted according to the weight, power transmission efficiency and capacity requirement, using the formula:

[0094]

[0095] Calculate the capacity allocation weight adjustment factor for each line and generate a capacity allocation weight sorted list;

[0096] Among them, V load represents capacity utilization, E represents power transmission efficiency, R d is the load fluctuation range, b and B are the adjustment factor and exponential factor respectively, and A represents the capacity allocation weight of the line;

[0097] The benefit of the formula is that it improves the flexibility of allocation calculation by introducing dynamic adjustment factor b and exponential factor B, and at the same time, according to the capacity utilization rate V load , power transmission efficiency E and load fluctuation range R d The weight effect improves the accuracy of the calculation results for actual capacity allocation;

[0098] Capacity utilization V load Directly extract from the load characteristic set in paragraph 1, let V load =0.75 (actual collection), the power transmission efficiency E is calculated by the ratio of line load power to transmission power, assuming E = 0.85, the load fluctuation range R d is the normalized value of the daily load fluctuation range of the line, and R d =0.20, weight factor b = 0.5, exponential factor B = 2, substitute into the formula:

[0099]

[0100] The result shows that the capacity allocation weight of the line is 0.527, which indicates the priority and proportion of the line in the total capacity allocation.

[0101] S223: Based on the capacity allocation weight sorting list, adjust the capacity of the lines in the power grid according to the current weight allocation ratio, and generate a power grid dynamic load capacity allocation table in combination with the line power demand and load characteristics;

[0102] First, sort the lines from high to low according to the weight, and adjust the capacity allocation ratio according to the sorting result. First, normalize the weight value of each line in the sorting, and use the normalized weight as the basic value of the capacity allocation ratio. Combined with the real-time power demand and power limit conditions of the line, calculate the final ratio. Multiply the ratio value of each line by the total capacity of the power grid to determine the specific capacity value allocated to each line, and finally form a dynamic load capacity allocation table for the power grid.

[0103] See also Figure 5 , the specific steps for obtaining the risk reserve path list are:

[0104] S311: extracting the real-time adjustment value and load parameters of the line from the power grid dynamic load capacity allocation table, screening unstable and overloaded lines by comparing the difference between the real-time load and the set upper and lower limits of the load, and generating a preliminary screened line set;

[0105] By analyzing the changing rules between the adjustment value and the load parameters, each line is preliminarily screened in combination with the historical data of the line operation. First, the actual load value of each line is compared with the set upper and lower limits of the load to determine which lines have load values ​​exceeding the threshold range and are marked as abnormal load lines. Secondly, the load change rate of each line is calculated, and the load change rate of each line is compared with the set change rate threshold. Lines with a change rate higher than the threshold are screened as candidate lines. Combined with the load fluctuation characteristics of the line, the amplitude change and fluctuation frequency of the load fluctuation within the fluctuation period are statistically analyzed to eliminate lines with low fluctuation amplitude and stable fluctuation frequency, and the remaining qualified lines are further marked as high fluctuation lines. Finally, the lines that meet the abnormal load and high fluctuation conditions are integrated into a preliminarily screened line set, and the load parameters, fluctuation characteristics and historical adjustment values ​​of each line are recorded in the set.

[0106] S312: Based on the initially screened line set, analyze the nodes and remaining capacity of each line, and calculate the potential risk index of each line using the formula:

[0107]

[0108] Determine the priority of each route and generate a list of risk assessment results;

[0109] Among them, C current Indicates the current load capacity, C max represents the maximum allowed capacity, ΔC represents the capacity difference with nearby nodes, γ is the adjustment coefficient, and R risk Indicates the potential risk index of the line;

[0110] The benefit of the formula is that by adding the adjustment factor γ and the load capacity difference ΔC, the line risk level is dynamically evaluated, and the current load capacity C is combined with current and maximum load capacity C max , which more comprehensively reflects the overall level of current risks of the line;

[0111] Set the current load capacity of a line to C current =50, the maximum allowable load capacity is C max =100, the capacity difference with the adjacent node is ΔC=20, and the adjustment coefficient is γ=0.05. According to the formula:

[0112]

[0113] First calculate the numerator-denominator ratio:

[0114] Then calculate the exponential term: -0.05·20=-1, e -1 ≈0.3679;

[0115] Finally calculate the risk index: R risk =0.5·0.3679≈0.18395;

[0116] The result shows that the risk index of the line is 0.18395, which means that the line is in a medium-low risk state. This risk value is used for sorting and further screening to generate a list of risk assessment results.

[0117] S313: calling the risk assessment result list, sorting each line according to the risk index, screening the risk lines and checking the spare capacity of the associated nodes, summarizing the screened data, and creating a grid risk reserve path list;

[0118] For each high-risk line, the remaining capacity and allocable load capacity of the nodes associated with it are calculated. By analyzing the capacity data and combining it with the real-time transmission power of the line, the potential backup paths of the high-risk lines are determined. First, the remaining capacity of each line is normalized, and the remaining capacity of each node is mapped to a unified interval to facilitate matching with the transmission power ratio of the associated lines. Secondly, the power ratio of high-risk lines and nodes is calculated. By comparing the degree of matching between the transmission power of each path and its remaining capacity ratio, the paths that meet the transmission capacity conditions are screened. Then, for each high-risk line, the transmission priority of its backup path is analyzed, and the priority ranking is calculated according to the remaining capacity of the nodes on the path and the transmission power of the associated lines. Finally, the node, path and remaining capacity data of all high-risk lines are integrated to generate a list of power grid risk reserve paths.

[0119] See also Figure 6 ,The specific steps for obtaining the path priority analysis results are:

[0120] S321: Based on the grid risk reserve path list, extract the priority field data, locate the priority fields in the list, separate them one by one, and judge and standardize the field data type, remove non-priority related fields and duplicate items, and generate a grid priority data set;

[0121] By analyzing the names, contents and associations of the list fields one by one, the field data related to the priority are accurately extracted, and the extracted data is judged and standardized according to the type of field content. For numeric fields, they are normalized to a unified interval to ensure the consistency of subsequent analysis. For text fields, matching is performed based on a predetermined standard dictionary and the field content is normalized. By separating the extracted data one by one, the fields that are not directly related to the priority, as well as the redundant and repeated data items in the list are eliminated, and the abnormal values ​​or missing values ​​are marked and processed to ensure data integrity and reliability. After the sorted priority field data is uniformly formatted, a power grid priority data set is formed. This data set contains complete and standardized priority fields and their corresponding data, laying the foundation for subsequent classification, sorting and analysis.

[0122] S322: Based on the power grid priority data set, classify and sort the priority data, analyze the priority rules and compare and group the path attributes in the data items, combine the path characteristic fields in the data, adjust the entries with repeated and missing attributes in the classification, and generate the power grid path attribute priority sorting results;

[0123] For each priority entry in the data set, combined with its associated path attribute field, the impact of priority rules on path characteristic fields is analyzed one by one, and data entries are compared and grouped based on the rules. For duplicate attribute entries that appear in the grouping process, they are eliminated one by one through the logical association between fields. For entries with missing attributes, they are completed with reference to the priority rules of similar paths. In the sorted classification results, the hierarchical relationship of priorities in each group of data is refined according to the key values ​​of the path characteristic fields to ensure that the priority of each path is consistent with the actual attributes. After sorting and adjustment, the power grid path attribute priority sorting results are generated, which include the path characteristic description of each priority classification group and the item distribution of the classification data, and clarify the role and influence of each priority in path classification.

[0124] S323: Based on the priority sorting result of the power grid path attribute, summarize and sort the path priority weights, extract the classified path weight data, and re-sort the priority sequence in combination with the path characteristic field, analyze the weight proportion relationship in the sorting result and correct the sequence deviation, and generate the power grid path priority analysis result;

[0125] By extracting the priority weight field from each group of path data in the classification results, summarizing the weight values ​​of each item one by one, and performing preliminary sorting, combined with the path characteristic field, re-examining the weight ratio relationship of each item in the sorting result, correcting the sequence deviation that occurs, and adjusting the weight value with a large ratio deviation to ensure the rationality and accuracy of the final sorting result. In the re-sorting process, the path characteristic field is used as a reference factor, and the data items with similar characteristics in the weight ranking are regrouped and marked to enhance the logic and consistency of the analysis results, generate the power grid path priority analysis results, clarify the weight ranking of each path under different priorities, and provide a basis for subsequent power grid management decisions.

[0126] See also Figure 7 , the specific steps for obtaining the grid reserve parameter configuration scheme are:

[0127] S411: extracting the priority value and operation sequence of the reserve path from the power grid path priority analysis result, parsing the parameters of the line in each path and the associated reserve node information, evaluating the reserve contribution level of the path by analyzing the line priority value in the path and the load distribution ratio of the reserve node, and establishing a path reserve contribution information set;

[0128] First, the priority value of each line in the path and the corresponding reserve node are parsed to obtain the reserve weight of the line in the path, and the load contribution and priority information of each line in the path are counted. Then, the load distribution ratio of the reserve node is combined with the path line weight to calculate the reserve contribution level of each line in each path, and the capacity of each reserve node is layered to identify the load level of different nodes. Subsequently, the total reserve contribution of each path is analyzed according to the priority value and capacity allocation ratio of the reserve node. By comprehensively evaluating the priority value and contribution level of the reserve nodes in each path, the path reserve is evaluated as a whole. Finally, the reserve capacity of each node, the reserve weight of the path and the operation instruction information are sorted out to generate a set of path reserve contribution information.

[0129] S412: Call the path reserve contribution information set, extract the operation instruction priority of the reserve node, combine the remaining capacity and load fluctuation data, and use the formula:

[0130]

[0131] Calculate the adjusted operation priority, integrate the priority data of the path reserve nodes, and obtain the reserve operation instruction priority adjustment data;

[0132] Among them, P adj Indicates the adjusted operation priority, P baseis the basic priority, ΔR represents the coefficient of variation of the remaining capacity of the reserve node, ΔL is the load fluctuation difference value, and η is the adjustment factor;

[0133] The benefit of the formula is that by dynamically introducing the remaining capacity change ΔR, the load fluctuation difference ΔL and the adjustment factor η, the calculation of the reserve operation instruction priority is improved, so that the priority can comprehensively reflect the actual usage status of the node reserve and the load fluctuation characteristics of the path, further enhancing the rationality of instruction execution;

[0134] Suppose the basic priority of a reserve node is P base =10, the remaining capacity change is ΔR=16, the load fluctuation difference is ΔL=5, and the adjustment factor is η=8. Substitute the values ​​into the formula to calculate P adj :

[0135]

[0136] The result shows that the adjusted priority is 81.25. The priority value will serve as an important basis for sorting reserve operations and guide the generation of operation priority adjustment data for reserve nodes and the configuration optimization of the final path.

[0137] S413: combining the reserve operation instruction priority adjustment data and the path reserve contribution information set, reordering the adjustment priority instructions in the reserve path, recording the operation information of the reserve nodes and lines, integrating the operation steps according to the ordering results, and generating a power grid reserve parameter configuration plan;

[0138] Firstly, the adjusted priorities are extracted for all lines and reserve nodes involved in the reserve path, and the reserve node and line data in each path are sorted. The operation instructions in the reserve path are sorted in sequence by adjusting the priority value. Then, all reserve nodes and paths are grouped according to the adjusted priorities, and the reserve paths with the highest priority and the corresponding operation instructions are identified. The reserve node capacity data and operation data in each path are merged to establish a comprehensive information table of reserve paths containing priority sorting. Subsequently, the operation instructions and node information of all reserve paths are integrated, and the operation information is gradually filled into the configuration plan according to the priority and reserve capacity of the path. Finally, a power grid reserve parameter configuration plan containing complete priority sorting and operation instructions is generated.

[0139] The technical metadata processing and reserve system of the power grid system is used to execute the technical metadata processing and reserve method of the power grid system, and the system includes:

[0140] The node topology relationship analysis module extracts node identifiers and associated line parameters in the power grid system, quantifies the power flow between nodes, classifies the topological structure of the power grid, and constructs topological hierarchical analysis results;

[0141] The line capacity dynamic distribution module uses the structural information in the topology level analysis results to identify key transmission lines, adjust the line load capacity to match the real-time demand, and adjust the line priority according to the real-time load to obtain the line capacity dynamic distribution data;

[0142] The storage priority planning module analyzes the matching degree between storage units and lines based on the dynamic distribution data of line capacity, prioritizes storage units according to load fluctuations, adjusts storage strategies and optimizes energy allocation to obtain a storage allocation priority sequence;

[0143] The grid resilience optimization module extracts risk assessment of key lines from the storage allocation priority sequence, identifies potential failure points, develops emergency response paths and responds to power outages, and builds a risk reserve path list;

[0144] The reserve path integration module configures the backup resources according to the risk reserve path list and refers to the real-time status of the lines and nodes to generate a grid reserve parameter configuration plan.

[0145] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for processing and reserving technical metadata of a power grid system, characterized in that: The following steps are involved: By extracting node identifiers and associated line parameters in the power grid system, analyzing the connection relationship between nodes and identifying the initial weight value, calling the weight value to parse the topological level information, analyzing the capacity transfer characteristics of the power grid line, and generating a line capacity transfer characteristic table; Calling the capacity transfer parameters in the line capacity transfer characteristic table, combining the load capacity value and storage priority parameter of the power grid line, analyzing the storage allocation index, generating a capacity storage allocation sequence, and sorting the lines by capacity allocation weights, adjusting the capacity allocation ratio, and generating a power grid dynamic load capacity allocation table; Calling the line adjustment value and the load line list in the dynamic load capacity allocation table of the power grid, analyzing the line stability parameters and screening the load lines, extracting the associated nodes and the remaining capacity of the load lines, generating a list of power grid risk reserve paths, extracting the priority data in the list of power grid risk reserve paths and sorting them, and generating a power grid path priority analysis result; The priority value and operation sequence of the reserve path in the power grid path priority analysis result are called, the lines and reserve nodes in the path are integrated, the priority adjustment data of the reserve operation instruction is extracted, the operation list corresponding to the reserve path is integrated, the line reserve and operation adjustment are extracted and recorded, and a power grid reserve parameter configuration plan is generated.

2. The method for processing and reserving technical metadata of a power grid system according to claim 1, characterized in that: The steps of obtaining the line capacity transfer characteristic table are specifically as follows: By extracting node identification and associated line parameters in the power grid system, including voltage level, current capacity and impedance characteristics, the connection relationship between nodes is determined through comparing the values ​​between the parameters, and the connection information of the initial node is obtained; Based on the connection information of the initial nodes, the current capacity and impedance characteristics between the nodes are called to calculate the initial weight values ​​between the nodes using the formula: Get the weight value between nodes; Among them, w ij represents the weight value between node i and node j, Q i and I j Represent the current values ​​of nodes i and j respectively, Z ij represents the impedance value between nodes i and j, V i and V j Represent the voltage values ​​of nodes i and j respectively, α and β are the voltage weight adjustment coefficients; The inter-node weight values ​​are used to analyze the topological structure of the power grid lines, identify the connection characteristics and capacity transfer rules between the lines, and generate a line capacity transfer characteristic table.

3. The method for processing and reserving technical metadata of a power grid system according to claim 2, characterized in that: The steps of obtaining the capacity storage allocation sequence are specifically as follows: Based on the capacity transfer parameters in the line capacity transfer characteristic table, the load capacity value corresponding to the line is extracted, and the distribution interval of the load capacity value is divided into intervals, and the relationship between the line operation state and the capacity transfer parameters is analyzed to obtain the line load capacity distribution sequence; Based on the line load capacity distribution sequence, storage priority parameters are matched section by section, and the corresponding relationship between the priority parameters and the line load requirements is calculated and weighted one by one, and a comparison and analysis of the priority characteristics and the load distribution is performed to refine the priority requirement contribution and obtain a storage requirement characteristic distribution table; Based on the storage demand characteristic distribution table, storage capacity allocation is performed, by segmenting and gradually allocating the proportion of priority demands, adjusting the proportion and supplementing the difference in combination with capacity transfer parameters, optimizing the dynamic allocation results according to line demands, and obtaining a capacity storage allocation sequence.

4. The method for processing and reserving technical metadata of a power grid system according to claim 3, characterized in that: The steps for obtaining the dynamic load capacity allocation table of the power grid are specifically as follows: Based on the capacity storage allocation sequence, according to the original load data and real-time monitoring data, the daily average capacity occupancy rate of each line in the power grid, the fluctuation range of the peak value and the valley value are extracted, and data statistics are performed to analyze the stability and efficiency indicators of the line, and the dynamic load weight set of the line is obtained; Using the dynamic load weight set of the lines, each line is ranked according to weight, power transfer efficiency and capacity requirement, using the formula: Calculate the capacity allocation weight adjustment factor for each line and generate a capacity allocation weight sorted list; Among them, V load represents capacity utilization, E represents power transmission efficiency, R d is the load fluctuation range, b and B are the adjustment factor and exponential factor respectively, and A represents the capacity allocation weight of the line; Based on the capacity allocation weight sorting list, the capacity of the lines in the power grid is adjusted according to the current weight allocation ratio, and a power grid dynamic load capacity allocation table is generated in combination with the line power demand and load characteristics.

5. The method for processing and reserving technical metadata of a power grid system according to claim 4, characterized in that: The steps for obtaining the risk reserve path list are specifically as follows: Extracting the real-time adjustment value and load parameter of the line from the dynamic load capacity allocation table of the power grid, screening unstable and overloaded lines by comparing the difference between the real-time load and the set upper and lower limits of the load, and generating a preliminary screened line set; Based on the initially screened line set, the nodes and remaining capacity of each line are analyzed, and the potential risk index of each line is calculated using the formula: Determine the priority of each route and generate a list of risk assessment results; Among them, C current Indicates the current load capacity, C max represents the maximum allowed capacity, ΔC represents the capacity difference with nearby nodes, γ is the adjustment coefficient, and R risk Indicates the potential risk index of the line; The risk assessment result list is called, each line is sorted according to the risk index, risk lines are screened and the spare capacity of associated nodes is checked, the screened data is summarized, and a grid risk reserve path list is created.

6. The method for processing and reserving technical metadata of a power grid system according to claim 5, characterized in that: The steps for obtaining the path priority analysis result are specifically as follows: Based on the grid risk reserve path list, extract the priority field data, locate the priority fields in the list, separate them one by one, and judge and standardize the field data type, remove non-priority related fields and duplicate items, and generate a grid priority data set; Based on the power grid priority data set, the priority data is classified and sorted, the path attributes in the data items are analyzed and compared and grouped according to the priority rules, and the items with repeated and missing attributes in the classification are adjusted in combination with the path characteristic fields in the data, so as to generate the power grid path attribute priority sorting result; Based on the grid path attribute priority sorting results, the path priority weights are summarized and sorted, the classified path weight data are extracted, and the priority sequence is re-sorted in combination with the path characteristic fields. The weight proportion relationship in the sorting results is analyzed and the sequence deviation is corrected to generate the grid path priority analysis results.

7. The method for processing and reserving technical metadata of a power grid system according to claim 6, characterized in that: The steps for obtaining the power grid reserve parameter configuration scheme are specifically as follows: Extracting the priority value and operation sequence of the reserve path from the power grid path priority analysis result, parsing the parameters of the line in each path and the associated reserve node information, evaluating the reserve contribution level of the path by analyzing the line priority value and the load distribution ratio of the reserve node in the path, and establishing a path reserve contribution information set; The path reserve contribution information set is called to extract the operation instruction priority of the reserve node, and the remaining capacity and load fluctuation data are combined to adopt the formula: Calculate the adjusted operation priority, integrate the priority data of the path reserve nodes, and obtain the reserve operation instruction priority adjustment data; Among them, P adj Indicates the adjusted operation priority, P base is the basic priority, ΔR represents the coefficient of variation of the remaining capacity of the reserve node, ΔL is the load fluctuation difference value, and η is the adjustment factor; Combined with the reserve operation instruction priority adjustment data and the path reserve contribution information set, the adjustment priority instructions in the reserve path are reordered, the operation information of the reserve nodes and lines is recorded, the operation steps are integrated according to the sorting results, and a power grid reserve parameter configuration plan is generated.

8. A technical metadata processing and storage system for a power grid system, characterized in that: The method for processing and reserving technical metadata of a power grid system according to any one of claims 1 to 7, wherein the system comprises: The node topology relationship analysis module extracts node identifiers and associated line parameters in the power grid system, quantifies the power flow between nodes, classifies the topological structure of the power grid, and constructs topological hierarchical analysis results; The line capacity dynamic distribution module uses the structural information in the topology level analysis result to identify key transmission lines, adjust the load capacity of the lines to match the real-time demand, and adjust the priority of the lines according to the real-time load to obtain the line capacity dynamic distribution data; The storage priority planning module analyzes the matching degree between the storage unit and the line according to the dynamic distribution data of the line capacity, prioritizes the storage unit according to the load fluctuation, adjusts the storage strategy and optimizes the energy allocation, and obtains the storage allocation priority sequence; The grid resilience optimization module extracts risk assessment of key lines from the storage allocation priority sequence, identifies potential failure points, develops emergency response paths and responds to power outages, and builds a risk reserve path list; The reserve path integration module configures the backup resources according to the risk reserve path list and refers to the real-time conditions of the lines and nodes to generate a power grid reserve parameter configuration plan.

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