A method and system for constructing a power grid database based on power grid measurement data

Abstract

The application discloses a kind of based on power grid measurement data construction power grid database method and system, it is related to power grid field, existing power grid database construction method is solved the problem of construction effect, including step S1: respectively to each electric power node is carried out measurement data generation quantity analysis, according to analysis result, the first data quantity index deviation and the second data quantity index deviation corresponding to target area power grid are obtained, data quantity historical monitoring data is obtained, step S2: respectively to each electric power node is carried out measurement data access quantity analysis, according to analysis result, the first access quantity index deviation and the second access quantity index deviation corresponding to target area power grid are obtained, access quantity historical monitoring data is obtained, step S3: according to data quantity historical monitoring data and access quantity historical monitoring data, target area power grid is carried out power grid database storage mode matching, the application can improve the storage efficiency and access efficiency of power grid database.

Description

Technical Field

[0001] This invention belongs to the field of power grids and relates to data analysis technology. Specifically, it is a method and system for constructing a power grid database based on power grid measurement data. Background Technology

[0002] Existing methods for constructing power grid databases have the following specific drawbacks when storing data:

[0003] 1. Existing power grid database construction methods cannot perform time-based measurement data generation speed analysis and measurement data change analysis for each power node in the regional power grid, and cannot match the data generation analysis results with the database storage method, resulting in low database storage efficiency.

[0004] 2. Existing power grid database construction methods cannot perform time-based measurement data access frequency analysis and measurement data access change analysis for each power node in the regional power grid, and cannot match the database storage method with the data access volume analysis results, resulting in low database access efficiency.

[0005] To this end, we propose a method and system for constructing a power grid database based on power grid measurement data. Summary of the Invention

[0006] In view of the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for constructing a power grid database based on power grid measurement data. This invention aims to improve the storage efficiency and access efficiency of the power grid database.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a method for constructing a power grid database based on power grid measurement data, comprising the following specific steps:

[0008] Step S1: Acquire the power nodes of the power grid in the target area, perform measurement data generation analysis on each power node, and obtain the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, and obtain the historical monitoring data of the data quantity.

[0009] Step S2: Acquire the power nodes of the target area power grid, analyze the access volume of measurement data for each power node, and obtain the first access volume index deviation and the second access volume index deviation corresponding to the target area power grid based on the analysis results, and obtain the historical monitoring data of access volume.

[0010] Step S3: Match the power grid database storage method of the target area power grid based on the historical monitoring data of data volume and the historical monitoring data of access volume.

[0011] Furthermore, step S1 also includes the following specific steps:

[0012] Step S11: Obtain the regional power network that needs to be included in the power grid database, and arbitrarily select a target regional power grid from the multiple regional power networks obtained;

[0013] Step S12: Obtain the main power network entities involved in the target area power grid, and select a sample power grid entity from the multiple obtained power network entities;

[0014] Step S13: Analyze the generation of power measurement data of the sample power grid, and obtain the generation rate of time-period measurement data and the change of time-period measurement data based on the analysis results;

[0015] Step S14: Obtain the generation rate of time-period measurement data corresponding to each main body of the power network, obtain multiple generation rates of time-period measurement data, and calculate the average value of the multiple generation rates of time-period measurement data to obtain the generation rate of measurement data of the target power grid.

[0016] Step S15: Obtain the change in time-period measurement data corresponding to each main body of the power network, obtain multiple change in time-period measurement data, and calculate the average value of the multiple change in time-period measurement data to obtain the rate of change of the target power grid measurement data.

[0017] Step S16: Obtain the reference value of the measurement data generation speed and the reference value of the measurement data change rate respectively. Perform deviation analysis between the target power grid measurement data change rate and the target power grid measurement data generation speed and the reference value of the measurement data change rate and the reference value of the measurement data generation speed. Obtain historical monitoring data of the data volume based on the analysis results.

[0018] Furthermore, step S13 also includes the following specific steps:

[0019] Step S131: Acquire historical measurement data corresponding to the main body of the sample power grid, and acquire the historical time period covered by the historical measurement data. Divide the acquired historical time period into several historical monitoring time periods, and name the divided historical monitoring time periods from T1 historical time period to Tb historical time period in chronological order.

[0020] Step S132: Acquire the measurement data generated by the sample power grid entity in historical time period T1 to obtain the measurement data volume of time period T1. Acquire the measurement data generated by the sample power grid entity in historical time period T2 to obtain the measurement data volume of time period T2. And so on, acquire the measurement data generated by the sample power grid entity in historical time period Tb to obtain the measurement data volume of time period Tb.

[0021] Furthermore, step S13 also includes the following specific steps:

[0022] Step S133: Acquire the duration of historical monitoring periods to obtain the historical period length value, calculate the ratio of the measurement data volume from period T1 to period Tb to the historical period length value, and calculate the average of the obtained ratios to obtain the generation rate of periodic measurement data.

[0023] Step S134: Calculate the change in measurement data from time period T1 to time period Tb.

[0024] The specific formula for calculating the change in time-varying measurement data is as follows:

[0025] ;

[0026] Wherein, Bhd1 represents the change in time-varying measurement data, and Sjl i For the measurement data volume during the Ti period, Sjl i-1 b represents the amount of measurement data for the Ti-1 period, and b represents the quantity value corresponding to the historical monitoring period.

[0027] Furthermore, step S16 also includes the following specific steps.

[0028] The difference between the speed reference value generated by the measurement data and the speed generated by the target power grid measurement data is calculated to obtain the first data quantity index deviation;

[0029] The difference between the benchmark value of the rate of change of the measured data volume and the rate of change of the measured data volume of the target power grid is calculated to obtain the deviation of the second data volume index.

[0030] The deviations of the first and second data volume indicators are defined as historical data of data volume.

[0031] Furthermore, step S2 also includes the following specific steps:

[0032] Step S21: Obtain a target area power grid, acquire power network entities with access permissions to the target area power grid database, and select a sample power grid entity from the acquired power network entities;

[0033] Step S22: Analyze the historical measurement data access volume of the sample power grid main body, and obtain the time period measurement data access frequency and time period access change based on the analysis results;

[0034] Step S23: Obtain the time-period measurement data access frequency corresponding to each power network entity, obtain multiple time-period measurement data access frequencies, and calculate the average value of the multiple time-period measurement data access frequencies to obtain the target power grid measurement data access frequency.

[0035] Step S24: Obtain the time-period access change amount corresponding to each power network entity, obtain multiple time-period access change amounts, and calculate the average value of the multiple time-period access change amounts to obtain the target power grid measurement access change rate.

[0036] Step S25: Perform deviation analysis on the access frequency of the target power grid measurement data and the rate of change of the target power grid measurement access volume, and obtain historical monitoring data of the access volume based on the analysis results.

[0037] Furthermore, step S22 also includes the following specific steps:

[0038] Step S221: Obtain the historical measurement data access records corresponding to the main body of the sample power grid, and obtain the historical time periods covered by the historical measurement data access records. Divide the obtained historical time periods into several historical access time periods, and name the divided historical access time periods from F1 historical time period to Fc historical time period in chronological order.

[0039] Step S222: Obtain the access volume of the measurement data generated by the sample power grid entity in the historical period F1 to obtain the measurement access volume of the F1 period; obtain the access volume of the measurement data generated by the sample power grid entity in the historical period F2 to obtain the measurement access volume of the F2 period; and so on, obtain the access volume of the measurement data generated by the sample power grid entity in the historical period Fc to obtain the measurement access volume of the Fc period.

[0040] Step S223: Obtain the duration of the historical access period, calculate the ratio of the access volume measured in period F1 to the access volume measured in period Fc to the historical period length, and calculate the average of the multiple ratios to obtain the access frequency of the period measurement data.

[0041] Step S224: Calculate the time-period change in access volume from the access volume measured in time period F1 to the access volume measured in time period Fc;

[0042] The formula for calculating the change in access over a specific period is as follows:

[0043] ;

[0044] Where Fwl1 represents the time-varying access volume, and Fjl i To measure access volume during the Fi time period, Fjli-1 The number of visits is measured for the Fi-1 time period, and c is the number of visits corresponding to the historical time period.

[0045] Furthermore, step S25 also includes the following specific steps:

[0046] Obtain the baseline value of the measurement data access frequency and the baseline value of the measurement access rate change, respectively.

[0047] The difference between the reference value of the measurement data access frequency and the target power grid measurement data access frequency is calculated to obtain the first access quantity index deviation. The difference between the reference value of the measurement access quantity change rate and the target power grid measurement access quantity change rate is calculated to obtain the second access quantity index deviation.

[0048] The deviations of the first and second visitor metrics are defined as historical visitor monitoring data.

[0049] Furthermore, step S3 also includes the following steps:

[0050] Based on historical monitoring data, the deviations of the first and second data volume indicators are obtained respectively.

[0051] Obtain historical access volume monitoring data, and obtain the deviation of the first access volume indicator and the deviation of the second access volume indicator based on the historical access volume monitoring data;

[0052] If any one of the following indicators—the first data volume indicator deviation, the second data volume indicator deviation, the first access volume indicator deviation, and the second access volume indicator deviation—is negative, then the power grid database corresponding to the target area will be distributed for storage.

[0053] If the deviations of the first data volume index, the second data volume index, the first access volume index, and the second access volume index are all negative, then the power grid database corresponding to the target area will be centrally stored.

[0054] A system for constructing a power grid database based on power grid measurement data includes:

[0055] Historical Measurement Module: Acquires the power nodes of the power grid in the target area, performs measurement data generation analysis on each power node, and obtains the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, thus obtaining historical monitoring data of the data quantity.

[0056] Historical access module: acquires the power nodes of the power grid in the target area, analyzes the access volume of measurement data for each power node, and obtains the first access volume index deviation and the second access volume index deviation corresponding to the power grid in the target area based on the analysis results, thus obtaining historical access volume monitoring data.

[0057] Pattern matching module: Matches the power grid database storage method of the target area's power grid based on historical monitoring data of data volume and historical monitoring data of access volume.

[0058] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0059] 1. This invention performs time-period measurement data generation speed analysis and measurement data generation change analysis on each power node in the regional power grid, and matches the database storage method according to the analysis results of the data generation, which can ensure the targeting of the database storage method and improve the low database storage efficiency.

[0060] 2. This invention performs time-period measurement data access frequency analysis and measurement data access change analysis on each power node in the regional power grid, and matches the database storage method according to the data access volume analysis results, which can ensure the efficiency of user access to the database. Attached Figure Description

[0061] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0062] Figure 1 This is a diagram illustrating the implementation steps of the present invention;

[0063] Figure 2 This is an overall system block diagram of the present invention. Detailed Implementation

[0064] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0065] Example 1

[0066] Please see Figure 1 This invention provides a technical solution: a method for constructing a power grid database based on power grid measurement data, comprising the following steps:

[0067] Step S1: Acquire the power nodes of the power grid in the target area, perform measurement data generation analysis on each power node, and obtain the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, and obtain the historical monitoring data of the data quantity.

[0068] Step S1 further includes the following steps:

[0069] The regional power networks that need to be included in the power grid database are acquired, and a target regional power grid is randomly selected from the acquired regional power networks.

[0070] It should be noted here that:

[0071] In this application, the regional power network referred to herein is a small regional power network;

[0072] The main power network entities involved in the target area power grid are acquired, and a sample power grid entity is selected from the acquired multiple power network entities.

[0073] It should be noted here that:

[0074] In this application, the power network entity referred to herein is specifically a physical entity connected to the power network, including but not limited to factories, residential communities, and power plants.

[0075] The generation of electrical power measurement data is analyzed for the main body of the sample power grid. Based on the analysis results, the generation rate of time-period measurement data and the change of time-period measurement data are obtained.

[0076] Specifically as follows:

[0077] Historical measurement data corresponding to the main body of the sample power grid were acquired, and the historical time periods covered by the historical measurement data were obtained. The acquired historical time periods were then divided into several historical monitoring periods, and the divided historical monitoring periods were named from historical period T1 to historical period Tb in chronological order.

[0078] It should be noted here that:

[0079] In this application, the historical monitoring periods referred to herein are of equal duration.

[0080] In this application, T refers to the symbol corresponding to the historical monitoring period, b refers to the quantity value corresponding to the historical monitoring period, and b is an integer greater than 0;

[0081] The measurement data generated by the sample power grid in historical time period T1 is obtained to obtain the measurement data volume of time period T1. The measurement data generated by the sample power grid in historical time period T2 is obtained to obtain the measurement data volume of time period T2. And so on, the measurement data generated by the sample power grid in historical time period Tb is obtained to obtain the measurement data volume of time period Tb.

[0082] The duration of historical monitoring periods is acquired to obtain the historical period length value. The ratio of the measurement data volume from period T1 to period Tb to the historical period length value is calculated, and the average of the obtained ratios is calculated to obtain the generation rate of periodic measurement data.

[0083] The change in measurement data from time period T1 to time period Tb is calculated to obtain the time period measurement data change.

[0084] The specific formula for calculating the change in time-varying measurement data is as follows:

[0085] ;

[0086] Wherein, Bhd1 represents the change in time-varying measurement data, and Sjl i For the measurement data volume during the Ti period, Sjl i-1 b represents the amount of measurement data for the Ti-1 period, and b represents the quantity value corresponding to the historical monitoring period.

[0087] It should be noted here that:

[0088] In this application, the amount of measurement data in time period Ti can be any one of the measurement data in time periods T1 to Tb.

[0089] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the generation rate of time-period measurement data for each power network body, resulting in multiple generation rates of time-period measurement data. The average value of the multiple generation rates of time-period measurement data is then calculated to obtain the generation rate of measurement data of the target power grid.

[0090] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the time-period measurement data change for each power network body, resulting in multiple time-period measurement data change values. The average value of the multiple time-period measurement data change values ​​is then calculated to obtain the rate of change of the target power grid measurement data.

[0091] The measurement data are acquired to generate a velocity reference value and a measurement data change rate reference value, respectively.

[0092] It should be noted here that:

[0093] The speed baseline value is obtained from the measurement data, as detailed below:

[0094] Obtain several regional power networks corresponding to centralized data storage databases to obtain multiple historical power networks;

[0095] The generation rate of power grid measurement data for each regional power network is obtained separately, and the values ​​of the multiple power grid measurement data generation rates are compared. The power grid measurement data generation rate with the smallest value is marked as the benchmark value of measurement data generation rate.

[0096] The rate of change of power grid measurement data corresponding to each regional power network is obtained, and the values ​​of multiple power grid measurement data change rates are compared. The power grid measurement data change rate with the smallest value is marked as the benchmark value of the rate of change of measurement data.

[0097] The difference between the speed at which the measurement data is generated and the speed at which the target power grid measurement data is generated is calculated to obtain the first data quantity index deviation. The difference between the speed at which the measurement data quantity changes and the speed at which the target power grid measurement data quantity changes is calculated to obtain the second data quantity index deviation.

[0098] The deviations of the first and second data volume indicators are defined as historical data of data volume.

[0099] The above step S1 has the following advantages:

[0100] By constructing a time-segmented refined monitoring system, the generation of power grid measurement data is analyzed in multiple dimensions: First, the historical monitoring period is divided into multiple consecutive time periods, and the data generation rate and fluctuation of adjacent time periods are calculated for each time period to form a dynamic change curve; Second, by aggregating data from multiple power network entities, single-point sampling errors are eliminated to obtain regional data load characteristics; Finally, an industry benchmark comparison mechanism is introduced to quantify the deviation between the target power grid data generation efficiency and change rate and the optimal practice of centralized database. This not only enables real-time dynamic tracking of data load status, but also provides data support for the selection of power grid database storage methods by establishing dual-indicator early warning thresholds.

[0101] Step S2: Acquire the power nodes of the target area power grid, analyze the access volume of measurement data for each power node, and obtain the first access volume index deviation and the second access volume index deviation corresponding to the target area power grid based on the analysis results, and obtain the historical monitoring data of access volume.

[0102] Step S2 further includes the following steps:

[0103] Obtain a target area power grid, acquire power network entities with access permissions to the target area power grid database, and select a sample power grid entity from the acquired power network entities.

[0104] It should be noted here that:

[0105] The target area power grid database is a dedicated database storage facility built for the target area power grid;

[0106] Historical measurement data access volume analysis was conducted on the sample power grid, and the time-period measurement data access frequency and time-period access change were obtained based on the analysis results;

[0107] Specifically as follows:

[0108] Historical measurement data access records corresponding to the main body of the sample power grid were acquired, and the historical time periods covered by the historical measurement data access records were obtained. The acquired historical time periods were then divided into several historical access periods, and the divided historical access periods were named F1 historical period to Fc historical period in chronological order.

[0109] It should be noted here that:

[0110] In this application, the duration of the historical access periods referred to herein is equal.

[0111] In this application, F is the symbol corresponding to the historical access period, c is the quantity value corresponding to the historical access period, and c is an integer greater than 0.

[0112] Access volume is obtained by acquiring the measurement data generated by the sample power grid entity in the F1 historical period. The access volume of measurement data generated by the sample power grid entity in the F2 historical period is obtained. Similarly, the access volume of measurement data generated by the sample power grid entity in the Fc historical period is obtained.

[0113] The duration of historical access periods is obtained, the length of the historical period is calculated, the ratio of the access volume measured in period F1 to the access volume measured in period Fc to the length of the historical period is calculated, and the average of the obtained ratios is calculated to obtain the access frequency of the periodic measurement data.

[0114] The time-specific visitor change is obtained by calculating the visitor count from the F1 time period to the Fc time period.

[0115] The formula for calculating the change in access over a specific period is as follows:

[0116] ;

[0117] Where Fwl1 represents the time-varying access volume, and Fjl i To measure access volume during the Fi time period, Fjl i-1 The number of visits is measured for the Fi-1 time period, and c is the number of visits corresponding to the historical time periods.

[0118] It should be noted here that:

[0119] In this application, the measurement access volume during the Fi time period can be any one of the measurement access volumes during the F1 time period to the Fc time period.

[0120] The process of analyzing historical power measurement data of the sample power grid body is repeated. The time-period measurement data access frequency corresponding to each power network body is obtained, resulting in multiple time-period measurement data access frequencies. The average value of the multiple time-period measurement data access frequencies is calculated to obtain the target power grid measurement data access frequency.

[0121] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the time-period access change for each power network body, resulting in multiple time-period access change values. The average value of the multiple time-period access change values ​​is then calculated to obtain the rate of change of the target power grid measurement access.

[0122] The measurement data is acquired to generate a speed baseline value and a measurement access volume change rate baseline value, respectively.

[0123] It should be noted here that:

[0124] The speed baseline value is obtained from the measurement data, as detailed below:

[0125] Obtain several regional power networks corresponding to centralized data storage databases to obtain multiple historical power networks;

[0126] The power grid measurement data access frequency corresponding to each regional power network is obtained, and the values ​​of the multiple obtained power grid measurement data access frequencies are compared. The power grid measurement data access frequency with the smallest value is marked as the measurement data access frequency benchmark value.

[0127] The rate of change of power grid measurement access volume corresponding to each regional power network is obtained, and the values ​​of the obtained multiple rates of change of power grid measurement access volume are compared. The rate of change of power grid measurement access volume with the smallest value is marked as the benchmark value of the rate of change of measurement access volume.

[0128] The difference between the reference value of the measurement data access frequency and the target power grid measurement data access frequency is calculated to obtain the first access quantity index deviation. The difference between the reference value of the measurement access quantity change rate and the target power grid measurement access quantity change rate is calculated to obtain the second access quantity index deviation.

[0129] The deviations of the first and second visitor metrics are defined as historical visitor monitoring data.

[0130] The following advantages exist in step S2 above:

[0131] Step S2 achieves multi-dimensional quantitative assessment of the power grid database access load by constructing a time-segmented refined access volume monitoring framework: First, the historical access cycle is divided into multiple consecutive time periods, and the access frequency and fluctuation of adjacent time periods are calculated for each time period to form a dynamic access behavior profile; Second, by aggregating access data from multiple power network entities, single-point sampling bias is eliminated to obtain regional-level access load characteristics; Finally, an industry benchmark comparison mechanism is introduced to quantify the deviation between the target power grid access efficiency and change rate and the optimal practice of the centralized database. This not only achieves real-time dynamic tracking of the access load status, but also provides quantifiable improvement directions and abnormal access risk warning capabilities for power grid database access performance optimization by establishing dual-indicator early warning thresholds (access frequency deviation and change rate deviation).

[0132] Step S3: Match the power grid database storage method of the target area power grid based on historical monitoring data of data volume and historical monitoring data of access volume;

[0133] Step S3 further includes the following steps:

[0134] Based on historical monitoring data, the deviations of the first and second data volume indicators are obtained respectively.

[0135] Obtain historical access volume monitoring data, and obtain the deviation of the first access volume indicator and the deviation of the second access volume indicator based on the historical access volume monitoring data;

[0136] If any one of the following indicators—the first data volume indicator deviation, the second data volume indicator deviation, the first access volume indicator deviation, and the second access volume indicator deviation—is negative, then the power grid database corresponding to the target area will be distributed for storage.

[0137] If the deviations of the first data volume index, the second data volume index, the first access volume index, and the second access volume index are all negative, then the power grid database corresponding to the target area will be centrally stored.

[0138] In this application, if a corresponding calculation formula appears, the above calculation formula is a dimensionless calculation. The weighting coefficient, proportional coefficient and other coefficients in the formula are set to quantify each parameter to obtain a result value. The size of the weighting coefficient and proportional coefficient is only required to not affect the proportional relationship between the parameter and the result value.

[0139] Example 2

[0140] Please see Figure 2 Based on another concept of the same invention, a system for constructing a power grid database based on power grid measurement data is proposed. The system includes a historical measurement module, a historical access module, a pattern matching module, and a server. The historical measurement module, the historical access module, and the pattern matching module are respectively connected to the server, and the server controls the historical measurement module, the historical access module, and the pattern matching module respectively.

[0141] The historical measurement module acquires the power nodes of the power grid in the target area, performs measurement data generation analysis on each power node, and obtains the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, thus obtaining historical monitoring data of the data quantity.

[0142] Specifically as follows:

[0143] The regional power networks that need to be included in the power grid database are acquired, and a target regional power grid is randomly selected from the acquired regional power networks.

[0144] It should be noted here that:

[0145] In this application, the regional power network referred to herein is a small regional power network;

[0146] The main power network entities involved in the target area power grid are acquired, and a sample power grid entity is selected from the acquired multiple power network entities.

[0147] It should be noted here that:

[0148] In this application, the power network entity referred to herein is specifically a physical entity connected to the power network, including but not limited to factories, residential communities, and power plants.

[0149] The generation of electrical power measurement data is analyzed for the main body of the sample power grid. Based on the analysis results, the generation rate of time-period measurement data and the change of time-period measurement data are obtained.

[0150] Specifically as follows:

[0151] Historical measurement data corresponding to the main body of the sample power grid were acquired, and the historical time periods covered by the historical measurement data were obtained. The acquired historical time periods were then divided into several historical monitoring periods, and the divided historical monitoring periods were named from historical period T1 to historical period Tb in chronological order.

[0152] It should be noted here that:

[0153] In this application, the historical monitoring periods referred to herein are of equal duration.

[0154] In this application, T refers to the symbol corresponding to the historical monitoring period, b refers to the quantity value corresponding to the historical monitoring period, and b is an integer greater than 0;

[0155] The measurement data generated by the sample power grid in historical time period T1 is obtained to obtain the measurement data volume of time period T1. The measurement data generated by the sample power grid in historical time period T2 is obtained to obtain the measurement data volume of time period T2. And so on, the measurement data generated by the sample power grid in historical time period Tb is obtained to obtain the measurement data volume of time period Tb.

[0156] The duration of historical monitoring periods is acquired to obtain the historical period length value. The ratio of the measurement data volume from period T1 to period Tb to the historical period length value is calculated, and the average of the obtained ratios is calculated to obtain the generation rate of periodic measurement data.

[0157] The change in measurement data from time period T1 to time period Tb is calculated to obtain the time period measurement data change.

[0158] The specific formula for calculating the change in time-varying measurement data is as follows:

[0159] ;

[0160] Wherein, Bhd1 represents the change in time-varying measurement data, and Sjl i For the measurement data volume during the Ti period, Sjl i-1 b represents the amount of measurement data for the Ti-1 period, and b represents the quantity value corresponding to the historical monitoring period.

[0161] It should be noted here that:

[0162] In this application, the amount of measurement data in time period Ti can be any one of the measurement data in time periods T1 to Tb.

[0163] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the generation rate of time-period measurement data for each power network body, resulting in multiple generation rates of time-period measurement data. The average value of the multiple generation rates of time-period measurement data is then calculated to obtain the generation rate of measurement data of the target power grid.

[0164] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the time-period measurement data change for each power network body, resulting in multiple time-period measurement data change values. The average value of the multiple time-period measurement data change values ​​is then calculated to obtain the rate of change of the target power grid measurement data.

[0165] The measurement data are acquired to generate a velocity reference value and a measurement data change rate reference value, respectively.

[0166] It should be noted here that:

[0167] The speed baseline value is obtained from the measurement data, as detailed below:

[0168] Obtain several regional power networks corresponding to centralized data storage databases to obtain multiple historical power networks;

[0169] The generation rate of power grid measurement data for each regional power network is obtained separately, and the values ​​of the multiple power grid measurement data generation rates are compared. The power grid measurement data generation rate with the smallest value is marked as the benchmark value of measurement data generation rate.

[0170] The rate of change of power grid measurement data corresponding to each regional power network is obtained, and the values ​​of multiple power grid measurement data change rates are compared. The power grid measurement data change rate with the smallest value is marked as the benchmark value of the rate of change of measurement data.

[0171] The difference between the speed at which the measurement data is generated and the speed at which the target power grid measurement data is generated is calculated to obtain the first data quantity index deviation. The difference between the speed at which the measurement data quantity changes and the speed at which the target power grid measurement data quantity changes is calculated to obtain the second data quantity index deviation.

[0172] The deviations of the first and second data volume indicators are defined as historical data of data volume.

[0173] The historical access module acquires the power nodes of the target area power grid, analyzes the access volume of measurement data for each power node, and obtains the first access volume index deviation and the second access volume index deviation corresponding to the target area power grid based on the analysis results, thus obtaining historical access volume monitoring data.

[0174] Specifically as follows:

[0175] Obtain a target area power grid, acquire power network entities with access permissions to the target area power grid database, and select a sample power grid entity from the acquired power network entities.

[0176] It should be noted here that:

[0177] The target area power grid database is a dedicated database storage facility built for the target area power grid;

[0178] Historical measurement data access volume analysis was conducted on the sample power grid, and the time-period measurement data access frequency and time-period access change were obtained based on the analysis results;

[0179] Specifically as follows:

[0180] Historical measurement data access records corresponding to the main body of the sample power grid were acquired, and the historical time periods covered by the historical measurement data access records were obtained. The acquired historical time periods were then divided into several historical access periods, and the divided historical access periods were named F1 historical period to Fc historical period in chronological order.

[0181] It should be noted here that:

[0182] In this application, the duration of the historical access periods referred to herein is equal.

[0183] In this application, F is the symbol corresponding to the historical access period, c is the quantity value corresponding to the historical access period, and c is an integer greater than 0.

[0184] Access volume is obtained by acquiring the measurement data generated by the sample power grid entity in the F1 historical period. The access volume of measurement data generated by the sample power grid entity in the F2 historical period is obtained. Similarly, the access volume of measurement data generated by the sample power grid entity in the Fc historical period is obtained.

[0185] The duration of historical access periods is obtained, the length of the historical period is calculated, the ratio of the access volume measured in period F1 to the access volume measured in period Fc to the length of the historical period is calculated, and the average of the obtained ratios is calculated to obtain the access frequency of the periodic measurement data.

[0186] The time-specific visitor change is obtained by calculating the visitor count from the F1 time period to the Fc time period.

[0187] The formula for calculating the change in access over a specific period is as follows:

[0188] ;

[0189] Where Fwl1 represents the time-varying access volume, and Fjl i To measure access volume during the Fi time period, Fjl i-1 The number of visits is measured for the Fi-1 time period, and c is the number of visits corresponding to the historical time periods.

[0190] It should be noted here that:

[0191] In this application, the measurement access volume during the Fi time period can be any one of the measurement access volumes during the F1 time period to the Fc time period.

[0192] The process of analyzing historical power measurement data of the sample power grid body is repeated. The time-period measurement data access frequency corresponding to each power network body is obtained, resulting in multiple time-period measurement data access frequencies. The average value of the multiple time-period measurement data access frequencies is calculated to obtain the target power grid measurement data access frequency.

[0193] The process of analyzing historical power measurement data of the sample power grid body is repeated to obtain the time-period access change for each power network body, resulting in multiple time-period access change values. The average value of the multiple time-period access change values ​​is then calculated to obtain the rate of change of the target power grid measurement access.

[0194] The measurement data is acquired to generate a speed baseline value and a measurement access volume change rate baseline value, respectively.

[0195] It should be noted here that:

[0196] The speed baseline value is obtained from the measurement data, as detailed below:

[0197] Obtain several regional power networks corresponding to centralized data storage databases to obtain multiple historical power networks;

[0198] The power grid measurement data access frequency corresponding to each regional power network is obtained, and the values ​​of the multiple obtained power grid measurement data access frequencies are compared. The power grid measurement data access frequency with the smallest value is marked as the measurement data access frequency benchmark value.

[0199] The rate of change of power grid measurement access volume corresponding to each regional power network is obtained, and the values ​​of the obtained multiple rates of change of power grid measurement access volume are compared. The rate of change of power grid measurement access volume with the smallest value is marked as the benchmark value of the rate of change of measurement access volume.

[0200] The difference between the reference value of the measurement data access frequency and the target power grid measurement data access frequency is calculated to obtain the first access quantity index deviation. The difference between the reference value of the measurement access quantity change rate and the target power grid measurement access quantity change rate is calculated to obtain the second access quantity index deviation.

[0201] The deviations of the first and second visitor metrics are defined as historical visitor monitoring data.

[0202] The pattern matching module matches the power grid database storage method of the target area's power grid based on historical monitoring data of data volume and historical monitoring data of access volume;

[0203] Specifically as follows:

[0204] Based on historical monitoring data, the deviations of the first and second data volume indicators are obtained respectively.

[0205] Obtain historical access volume monitoring data, and obtain the deviation of the first access volume indicator and the deviation of the second access volume indicator based on the historical access volume monitoring data;

[0206] If any one of the following indicators—the first data volume indicator deviation, the second data volume indicator deviation, the first access volume indicator deviation, and the second access volume indicator deviation—is negative, then the power grid database corresponding to the target area will be distributed for storage.

[0207] If the deviations of the first data volume index, the second data volume index, the first access volume index, and the second access volume index are all negative, then the power grid database corresponding to the target area will be centrally stored.

[0208] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for constructing a power grid database based on power grid measurement data, characterized in that, include: Step S1: Acquire the power nodes of the power grid in the target area, perform measurement data generation analysis on each power node, and obtain the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, and obtain the historical monitoring data of the data quantity. Step S2: Acquire the power nodes of the target area power grid, analyze the access volume of measurement data for each power node, and obtain the first access volume index deviation and the second access volume index deviation corresponding to the target area power grid based on the analysis results, and obtain the historical monitoring data of access volume. Step S3: Match the power grid database storage method of the target area power grid based on the historical monitoring data of data volume and the historical monitoring data of access volume.

2. The method for constructing a power grid database based on power grid measurement data according to claim 1, characterized in that, Step S1 further includes the following specific steps: Step S11: Obtain the regional power network that needs to be included in the power grid database, and arbitrarily select a target regional power grid from the multiple regional power networks obtained; Step S12: Obtain the main power network entities involved in the target area power grid, and select a sample power grid entity from the multiple obtained power network entities; Step S13: Analyze the generation of power measurement data of the sample power grid, and obtain the generation rate of time-period measurement data and the change of time-period measurement data based on the analysis results; Step S14: Obtain the generation rate of time-period measurement data corresponding to each power network entity, obtain multiple time-period measurement data generation rates, and calculate the average value of the multiple time-period measurement data generation rates to obtain the target power grid measurement data generation rate. Step S15: Obtain the change in time-period measurement data corresponding to each main body of the power network, obtain multiple changes in time-period measurement data, and calculate the average value of the multiple changes in time-period measurement data to obtain the rate of change of the target power grid measurement data. Step S16: Obtain the reference value of the measurement data generation speed and the reference value of the measurement data change rate. Perform deviation analysis between the target power grid measurement data change rate and the target power grid measurement data generation speed and the reference value of the measurement data change rate and the reference value of the measurement data generation speed. Obtain historical monitoring data of the data volume based on the analysis results.

3. The method for constructing a power grid database based on power grid measurement data according to claim 2, characterized in that, Step S13 further includes the following specific steps: Step S131: Acquire historical measurement data corresponding to the main body of the sample power grid, and acquire the historical time periods covered by the historical measurement data, and divide the acquired historical time periods into historical time periods T1 to Tb. Step S132: Acquire the measurement data generated by the sample power grid entity in the historical time period T1 to obtain the measurement data volume of the T1 time period. Similarly, acquire the measurement data generated by the sample power grid entity in the historical time period Tb to obtain the measurement data volume of the Tb time period.

4. The method for constructing a power grid database based on power grid measurement data according to claim 2, characterized in that, Step S13 further includes the following specific steps: Step S133: Acquire the duration of historical monitoring periods to obtain the historical period length value, calculate the ratio of the measurement data volume from period T1 to period Tb to the historical period length value, and calculate the average of the obtained ratios to obtain the generation rate of periodic measurement data. Step S134: Calculate the change in measurement data from time period T1 to time period Tb. The specific formula for calculating the change in time-varying measurement data is as follows: ； Where Bhd1 represents the change in time-varying measurement data, and Sjl i For the measurement data volume during the Ti period, Sjl i-1 b represents the amount of measurement data for the Ti-1 period, and b represents the quantity value corresponding to the historical monitoring period.

5. The method for constructing a power grid database based on power grid measurement data according to claim 2, characterized in that, Step S16 further includes the following specific steps. The difference between the speed reference value generated by the measurement data and the speed generated by the target power grid measurement data is calculated to obtain the first data quantity index deviation; The difference between the benchmark value of the rate of change of the measured data volume and the rate of change of the measured data volume of the target power grid is calculated to obtain the deviation of the second data volume index. The deviations of the first and second data volume indicators are defined as historical data of data volume.

6. The method for constructing a power grid database based on power grid measurement data according to claim 1, characterized in that, Step S2 further includes the following specific steps: Step S21: Obtain a target area power grid, acquire power network entities with access permissions to the target area power grid database, and select a sample power grid entity from the acquired power network entities; Step S22: Analyze the historical measurement data access volume of the sample power grid main body, and obtain the time-period measurement data access frequency and time-period access change based on the analysis results; Step S23: Obtain the time-period measurement data access frequency corresponding to each power network entity, obtain multiple time-period measurement data access frequencies, and calculate the average value of the multiple time-period measurement data access frequencies to obtain the target power grid measurement data access frequency. Step S24: Obtain the time-period access change amount corresponding to each power network entity, obtain multiple time-period access change amounts, and calculate the average value of the multiple time-period access change amounts to obtain the target power grid measurement access change rate. Step S25: Perform deviation analysis on the access frequency of the target power grid measurement data and the rate of change of the target power grid measurement access volume, and obtain historical monitoring data of the access volume based on the analysis results.

7. The method for constructing a power grid database based on power grid measurement data according to claim 6, characterized in that, Step S22 further includes the following specific steps: Step S221: Obtain the historical measurement data access records corresponding to the main body of the sample power grid, and obtain the historical time periods covered by the historical measurement data access records, and split the obtained historical time periods into historical time periods F1 to Fc. Step S222: Obtain the access volume of the measurement data generated by the sample power grid entity in the historical period F1 to obtain the measurement access volume of the F1 period. Similarly, obtain the access volume of the measurement data generated by the sample power grid entity in the historical period Fc to obtain the measurement access volume of the Fc period. Step S223: Obtain the duration of the historical access period, calculate the ratio of the access volume measured in period F1 to the access volume measured in period Fc to the historical period length, and calculate the average of the multiple ratios to obtain the access frequency of the period measurement data. Step S224: Calculate the time-period change in access volume from the access volume measured in time period F1 to the access volume measured in time period Fc; The formula for calculating the change in access over a specific period is as follows: ； Where Fwl1 represents the time-varying access variation, and Fjl i To measure access volume during the Fi period, Fjl i-1 The number of visits is measured for the Fi-1 time period, and c is the number of visits corresponding to the historical time period.

8. The method for constructing a power grid database based on power grid measurement data according to claim 6, characterized in that, Step S25 further includes the following specific steps: Obtain the baseline value of the measurement data access frequency and the baseline value of the measurement access rate change, respectively. The difference between the reference value of the measurement data access frequency and the target power grid measurement data access frequency is calculated to obtain the first access quantity index deviation. The difference between the reference value of the measurement access quantity change rate and the target power grid measurement access quantity change rate is calculated to obtain the second access quantity index deviation. The deviations of the first and second visitor metrics are defined as historical visitor monitoring data.

9. The method for constructing a power grid database based on power grid measurement data according to claim 1, characterized in that, Step S3 further includes the following steps: Based on historical monitoring data, the deviations of the first and second data volume indicators are obtained respectively. Obtain historical access volume monitoring data, and obtain the deviation of the first access volume indicator and the deviation of the second access volume indicator based on the historical access volume monitoring data; If any one of the deviations of the first data volume indicator, the second data volume indicator, the first access volume indicator, and the second access volume indicator is negative, then the power grid database corresponding to the target area will be distributed for storage. If the deviations of the first data volume index, the second data volume index, the first access volume index, and the second access volume index are all negative, then the power grid database corresponding to the target area will be centrally stored.

10. A system for constructing a power grid database based on power grid measurement data, applicable to the method for constructing a power grid database based on power grid measurement data as described in any one of claims 1-9, characterized in that, include: Historical measurement module: Analyzes the measurement data generated for each power node, and obtains the first data quantity index deviation and the second data quantity index deviation corresponding to the power grid in the target area based on the analysis results, thus obtaining historical monitoring data of the data quantity. Historical access module: Analyzes the access volume of measurement data for each power node, and obtains the first access volume index deviation and the second access volume index deviation corresponding to the power grid in the target area based on the analysis results, thus obtaining historical monitoring data of access volume; Pattern matching module: Matches the power grid database storage method of the target area's power grid based on historical monitoring data of data volume and historical monitoring data of access volume.

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