A method and system for power space data audit management

Abstract

The present invention discloses a method and system for auditing and managing electric power space data, and relates to the technical field of electric power system data management and risk assessment. The main scheme is: counting the actual number of electric power equipment, and collecting a data set of each equipment, counting the number of the data set, and judging whether the integrity, timeliness and accuracy of the data are qualified by comparing the two numbers, the time difference between the collection and reception timestamps of the data set, and the data deviation index of the data set; the problem that the prior art is not accurate enough in data accuracy assessment and is prone to misjudgment is solved, and the electric power space situation prediction index is calculated based on the data of the data set to judge whether the electric power space abnormal alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated, and a plurality of influence indexes are calculated based on various types of data, and the electric power space situation prediction index is obtained, which solves the problem that the prior art cannot evaluate the operating status of the electric power system from multiple angles, resulting in the existence of operating risks.

Description

Technical Field

[0001] The present invention relates to the technical field of power system data management, and in particular to a power space data audit management method and system. Background Art

[0002] In the operation and management of power systems, it is crucial to accurately obtain and effectively analyze data related to power equipment. The integrity, timeliness and accuracy of data directly affect the stable operation and reasonable planning of power systems. The data of power systems are complex and diverse, including environmental monitoring, operating status, user electricity consumption and other data. How to comprehensively process these data to ensure the efficient operation of power systems is a key issue facing this field.

[0003] Existing technologies usually use independent data collection and analysis methods. For power equipment data collection, data is obtained by installing sensors on the equipment, such as voltage and current sensors to obtain operating data. In terms of data processing, a simple analysis is performed based on the acquired data to determine whether the power system is operating normally.

[0004] However, the data collected by the existing technology lacks integrity. Various types of data are collected independently, and the correlation between power equipment data is not fully considered. It is difficult to evaluate the operating status of the power system from a global perspective. In terms of data instruction judgment, the existing technical methods lack judgment and evaluation of the data quality, and cannot guarantee the quality of data judgment. In addition, the data is relatively single, and it is impossible to evaluate the operating status of the power system from a global perspective. Summary of the invention

[0005] 1. Technical problems solved:

[0006] In view of the deficiencies in the prior art, the present invention provides a power space data audit management method and system, which solves the problem of lack of integrity in data collection and difficulty in judging data integrity in the prior art by counting and comparing the actual number of power equipment and the number of collected data sets; by using the collection timestamp and the reception timestamp of the data set to calculate the time difference and comparing it with the timeliness threshold, solves the problem of the prior art that the data timeliness judgment method is simple and cannot accurately measure the timeliness of the data; by separately calculating the deviation of the environment and the user's electricity consumption and comparing it with the data deviation threshold to judge the data accuracy, solves the problem of the prior art that the data accuracy assessment is not accurate enough and is prone to misjudgment; by calculating a variety of impact indexes based on various types of data and deriving the power space situation prediction index, solves the problem that the prior art cannot evaluate the operating status of the power system from multiple angles, resulting in operating risks.

[0007] (II) Technical solution:

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a power space data audit management method, comprising:

[0009] Count the actual number of power equipment covered by the power system , and collect data sets for each area where the power equipment is located, and calculate the actual number of statistical data sets ;The data set includes environmental monitoring data, basic operation status data, user power consumption data and historical power data;

[0010] According to the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation and power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and judge whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy;

[0011] When any of the completeness, timeliness and accuracy of the data does not meet the standards, the data will be re-acquired; when the completeness, timeliness and accuracy of the data all meet the standards, the predicted environmental impact index will be calculated based on the environmental monitoring data ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ;According to the Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index ;

[0012] Setting the threshold of power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

[0013] In the preferred embodiment of the above-mentioned power space data audit management method: calculating the time difference The specific method is:

[0014] Receive timestamp based on time And the acquisition timestamp , calculate the time difference The specific formula is as follows:

[0015] ;

[0016] In the preferred embodiment of the above-mentioned power space data audit management method: calculating the environmental data deviation , Power consumption fluctuation deviation and data deviation index The method is:

[0017] Calculate the deviation of environmental data The specific method is:

[0018] Environmental monitoring data includes real-time temperature values ​​during the current detection cycle , Temperature average , Real-time humidity value Humidity average , Real-time air pressure value Average air pressure , Real-time carbon dioxide concentration value and the average carbon dioxide concentration ;

[0019] Calculate the environmental data deviation based on environmental monitoring data The specific formula is as follows:

[0020] ;

[0021] in, Represents the number of measurements in the current detection cycle. Temperature value, Represents the number of measurements in the current detection cycle. Humidity value, Represents the number of measurements in the current detection cycle. The air pressure value, Represents the number of measurements in the current detection cycle. The carbon dioxide concentration value, Indicates the number of measurements in the current detection cycle. , represents the total number of measurements, Represents the real-time temperature value The weight coefficient is 0.1≤ ≤0.3, Represents the real-time humidity value The weight coefficient is 0.2≤ ≤0.4, Represents the real-time air pressure value The weight coefficient is 0.3≤ ≤0.5, Represents real-time carbon dioxide concentration The weight coefficient of R is 0.1< ≤0.3, and ;

[0022] Calculate the power consumption fluctuation deviation The specific method is:

[0023] User power consumption data includes real-time power consumption in the current detection cycle , Real-time average power consumption And the historical power consumption during the historical detection period , Historical average electricity consumption ;

[0024] Calculate the power consumption fluctuation deviation based on the user's power consumption data , the specific formula is as follows:

[0025] ;

[0026] in, Represents the number of measurements in the current detection cycle. Real-time power consumption, Indicates the number of measurements in the current detection cycle. , Represents the total number of measurements in the current detection cycle. Represents the first measurement in the historical detection cycle Historical electricity consumption, Indicates the number of measurements in the historical detection cycle, and its value is , Represents the total number of measurements during the historical detection period;

[0027] Calculate the data deviation index The specific method is:

[0028] According to the environmental data deviation and power consumption fluctuation deviation , calculate the data deviation index , the formula is as follows:

[0029] ;

[0030] in, Representative environmental data deviation The weight coefficient is 0.3≤ ≤0.5, Represents the power consumption fluctuation deviation The weight coefficient is 0.5≤ ≤0.7, and .

[0031] In the preferred embodiment of the above-mentioned power space data audit management method, the specific method for determining whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy is:

[0032] The method to determine data integrity is:

[0033] The actual number of electrical equipment The actual number of data sets For comparison, if , then the integrity is judged to meet the standard, , then the integrity is judged to be not up to standard and a data missing warning is issued;

[0034] The specific steps to determine the timeliness of data are:

[0035] Setting a timeliness threshold , the time difference and timeliness threshold Compare, if the time difference ≤Timeliness threshold When , it means that the timeliness meets the standard. >Timeliness threshold If the timeliness does not meet the standard, a data delay warning will be issued;

[0036] The specific steps to determine the accuracy of data are:

[0037] Set the data deviation threshold , when the data deviation index <Data deviation threshold When the data deviation index is ≥Data deviation threshold , it means that the accuracy does not meet the standard, triggering a data accuracy abnormality warning.

[0038] In the preferred embodiment of the above-mentioned power space data audit management method: calculating and predicting the environmental impact index The specific steps are:

[0039] Environmental monitoring data also includes real-time maximum temperature , Real-time minimum temperature , Real-time maximum humidity , Real-time minimum humidity , Real-time maximum air pressure , Real-time minimum air pressure , Real-time maximum carbon dioxide concentration And the real-time minimum carbon dioxide concentration ;

[0040] Calculate and predict the environmental impact index based on environmental monitoring data The specific formula is as follows:

[0041] ;

[0042] in, Represents the average temperature The weight coefficient is 0.1≤ ≤0.3, Represents the average humidity The weight coefficient is 0.2≤ ≤0.4, Represents the average air pressure The weight coefficient is 0.3≤ ≤0.5, Represents the average carbon dioxide concentration The weight coefficient is 0.1< ≤0.3, and .

[0043] In the preferred embodiment of the above-mentioned power space data audit management method: calculating the basic operation status index The specific steps are:

[0044] Basic operating status data includes real-time voltage value , Real-time maximum voltage value , Real-time minimum voltage value , Real-time current value , Real-time maximum current value , Real-time minimum current value , Real-time operating temperature value , Real-time maximum operating temperature value And real-time minimum operating temperature value ;

[0045] Set rated voltage , Rated current value And the rated operating temperature ;

[0046] According to the basic operating status data, rated voltage value , Rated current value And the rated operating temperature , calculate the basic operating status index , the specific formula is as follows:

[0047] ;

[0048] in, Represents the power factor, the value is 0< ≤1; Representative voltage value The weight coefficient is 0.2≤ ≤0.4, Representative current value The weight coefficient is 0.1< ≤0.3, Represents power factor ≤0.3, Represents the operating temperature value The weight coefficient is 0.3≤ ≤0.5, and .

[0049] In the preferred embodiment of the above-mentioned power space data audit management method: calculating the predicted power load impact index The specific steps are:

[0050] The user's electricity consumption data also includes the electricity consumption during peak hours. , peak-to-valley difference rate of electricity consumption And the load growth rate ;

[0051] Real-time power consumption based on the current detection cycle , power consumption during peak hours , peak-to-valley difference rate of electricity consumption , Load growth rate And real-time average power consumption , calculate and predict the power load impact index , the specific formula is as follows:

[0052] ;

[0053] in, Represents real-time power consumption The weight coefficient is 0.1< ≤0.3, is the load growth rate The weight coefficient is in the range of 0.3≤ ≤0.6, The peak-to-valley rate of electricity consumption The weight coefficient is 0.2≤ ≤0.5, and + + =1.

[0054] In the preferred embodiment of the above-mentioned power space data audit management method: calculating and predicting the power space comprehensive index The specific steps are:

[0055] According to the environmental impact index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index , the specific formula is as follows:

[0056] ;

[0057] in, is a constant term.

[0058] In the preferred embodiment of the above-mentioned power space data audit management method, the specific steps of determining whether to trigger the power space risk alarm information and generating the corresponding assessment report and adjustment plan are as follows:

[0059] Power space situation prediction index threshold Including the first threshold , Secondary threshold and the third threshold ,in, < ;

[0060] When the power space situation prediction index ≤ When the power space abnormality alarm information is not triggered;

[0061] when <Electricity Space Situation Forecast Index ≤ When the power abnormality risk alarm information is triggered, the primary adjustment instruction and risk assessment report are generated;

[0062] when <Electricity Space Situation Forecast Index When the secondary power space abnormal alarm information is triggered, the intermediate adjustment instructions and risk assessment report are generated;

[0063] when <Electricity Space Situation Forecast Index When the alarm is triggered, the third-level power space abnormality alarm information is generated, and advanced adjustment instructions and risk assessment reports are generated.

[0064] The present invention also discloses a power space data audit management system, comprising:

[0065] Data collection module, used to count the actual number of power equipment covered by the power system , and collect data sets for each area where the power equipment is located, and calculate the actual number of statistical data sets ;The data set includes environmental monitoring data, basic operation status data, user power consumption data and historical power data;

[0066] Data detection module, used to detect the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation and power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and judge whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy;

[0067] The data analysis module is used to re-acquire data when any of the data's integrity, timeliness and accuracy do not meet the standards; when the data's integrity, timeliness and accuracy all meet the standards, the environmental impact index is calculated and predicted based on the environmental monitoring data. ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ;According to the Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index ;

[0068] Data evaluation module, used to set the threshold of power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

[0069] (III) Beneficial effects:

[0070] The present invention provides a power space data audit management method and system, which has the following beneficial effects:

[0071] (1) By comprehensively counting the number of power equipment and the corresponding number of data sets, we can achieve systematic collection of the power system's environment, operation, electricity consumption and historical data. This will help build a complete data foundation and provide rich materials for subsequent accurate analysis and evaluation, avoiding one-sided judgment of the power system status due to missing or omitted data, so that power system operation management decisions can be based on comprehensive and detailed data, thereby improving the scientificity and accuracy of management.

[0072] (2) Compare the number of devices and data sets to determine data integrity and ensure that no data is missed; use timestamps to calculate time differences and compare them with thresholds to accurately evaluate data timeliness, promptly detect data lag problems and issue warnings, calculate various types of deviations and compare them with thresholds to determine accuracy, effectively identify data quality, reduce erroneous decisions caused by erroneous or outdated data, ensure stable operation and efficient regulation of the power system, and reduce operational risks caused by data problems.

[0073] (3) The impact index is calculated based on the environment, basic operation and power load data to quantify the degree of influence of each factor on the power system. The power spatial situation prediction index is obtained by combining these indices, which can accurately grasp the overall operation situation and trend changes of the power system. This helps to plan resource allocation and predict potential risks in advance, provide key quantitative support for the optimization of power system operation, fault prevention and response strategy formulation, and improve the reliability and economy of power system operation.

[0074] (4) By setting the threshold of the power space situation prediction index, a key assessment of the overall status of the power system is conducted, and it is accurately determined whether the power space abnormal alarm information is triggered. The system abnormality is detected in time and a warning is issued. The generated assessment report records the system status and the root cause of the problem in detail, and the adjustment plan proposes targeted optimization measures. This provides a clear action guide for power operation and maintenance personnel, promotes the power system to quickly resume normal operation, continuously optimize performance, and ensure the continuity and stability of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 A schematic diagram of a flow chart of a power space data audit management method of the present invention;

[0076] Figure 2 A schematic diagram of a flow chart of data set accuracy judgment in a power space data audit management method of the present invention;

[0077] Figure 3 The present invention is a schematic diagram of the composition of an electric power space data audit management system. DETAILED DESCRIPTION

[0078] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0079] See also Figure 1-2 The present invention provides a method for power space data audit management, comprising:

[0080] Steps: 1: Count the actual number of power equipment covered by the power system, and collect data sets in the area where each power equipment is located, and count the actual number of data sets; the data sets include environmental monitoring data, basic operating status data, user power consumption data and historical power data.

[0081] Counting the actual number of power equipment helps to understand the scale and composition of the power system. Environmental monitoring data can assess the impact of the external environment on the equipment and take protective measures in advance. Basic operating status data can promptly detect equipment abnormalities. User electricity consumption data helps to analyze user habits and needs, optimize power distribution and electricity price strategies. Historical power data can summarize operating rules, predict electricity consumption trends, and provide a basis for system expansion and upgrades. Statistical data collects actual quantities, which helps to establish a sound data management system, avoid data loss or confusion, and improve the efficiency and accuracy of data management.

[0082] Step 2: According to the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation and power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and determine whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy.

[0083] Step 201: Determine whether the integrity of the data meets the standards:

[0084] Obtain the actual number of power equipment The actual number of data sets , the actual number of power equipment The actual number of data sets For comparison, if , then the integrity is judged to meet the standard, , then the integrity is judged not to meet the standard;

[0085] It should be noted that the actual number of power equipment is the actual number of power equipment in the area covered by the power system, the actual number of data sets is the actual number of data sets obtained;

[0086] Step 202: Determine whether the timeliness of the data meets the standard:

[0087] Calculate time difference The specific method is:

[0088] Get the receiving timestamp And the acquisition timestamp , according to the receiving timestamp And the acquisition timestamp Calculate time difference The specific formula is as follows:

[0089] .

[0090] It should be noted that the collection timestamp It is the time point when the data in the data set is collected by the collection device, and the receiving timestamp It is the time point at which the data in the data set is received after it is uploaded.

[0091] The specific steps to determine the timeliness of data are:

[0092] Setting a timeliness threshold ;

[0093] The time difference and timeliness threshold Compare, if the time difference ≤Timeliness threshold When , it means that the timeliness meets the standard. >Timeliness threshold , it means that the timeliness does not meet the standards.

[0094] It should be noted that the timeliness threshold The time difference is calculated by using a large number of historical data collection timestamps and historical reception timestamps of the same period. , take the average value and set it as the timeliness threshold .

[0095] It should be noted that by setting the receiving timestamp Subtract acquisition timestamp , the time difference obtained , which can reflect the time it takes for data to be collected and received. By comparing the time difference with the timeliness threshold, it can be determined whether the timeliness of the data meets the standard. is less than or equal to the timeliness threshold, the data timeliness meets the standard; if If it is greater than the timeliness threshold, the data timeliness does not meet the standard and needs to be reacquired. The core of this formula is to quantify the data transmission delay through a simple timestamp subtraction operation, and then evaluate the timeliness of the data.

[0096] Step 203: Determine whether the accuracy of the data meets the standard:

[0097] Calculate the deviation of environmental data , Power consumption fluctuation deviation and data deviation index The steps are:

[0098] Calculate the deviation of environmental data , the specific method is:

[0099] Environmental monitoring data includes real-time temperature values ​​during the current detection cycle , Temperature average , Real-time humidity value Humidity average , Real-time air pressure value Average air pressure , Real-time carbon dioxide concentration value and the average carbon dioxide concentration .

[0100] It should be noted that Represents the number of measurements in the current detection cycle. temperature value, usually collected by a temperature sensor; the average temperature The real-time humidity value is obtained by adding up each real-time temperature value in the current detection cycle and dividing it by the total number of measurements. , Represents the number of measurements in the current detection cycle. Humidity values ​​are measured by the humidity sensor. Each real-time humidity value in the current detection cycle is added up, and then divided by the number of measurements to get the average humidity value. ; Real-time air pressure value And the average air pressure Obtained by the air pressure sensor, Represents the number of measurements in the current detection cycle. The pressure value is calculated by adding up the real-time pressure values ​​in the current detection cycle and dividing by the number of measurements to get the average pressure value. ; Real-time carbon dioxide concentration value , detected by the carbon dioxide concentration sensor, Represents the number of measurements in the current detection cycle. The carbon dioxide concentration value is added up in the current detection cycle, and then divided by the number of measurements to get the average carbon dioxide concentration. .

[0101] Calculate the environmental data deviation based on environmental monitoring data , the specific formula is as follows:

[0102] ;

[0103] in, Represents the number of measurements in the current detection cycle. Temperature value, Represents the number of measurements in the current detection cycle. Humidity value, Represents the number of measurements in the current detection cycle. The air pressure value, Represents the number of measurements in the current detection cycle. The carbon dioxide concentration value, Indicates the number of measurements in the current detection cycle. , represents the total number of measurements, Represents the real-time temperature value The weight coefficient is 0.1≤ ≤0.3, Represents the real-time humidity value The weight coefficient is 0.2≤ ≤0.4, Represents the real-time air pressure value The weight coefficient is 0.3≤ ≤0.5, Represents real-time carbon dioxide concentration The weight coefficient of R is 0.1< ≤0.3, and .

[0104] It should be noted that the degree of environmental data deviation is quantified by comprehensively considering the sum of squares of the deviations of temperature, humidity, air pressure, and carbon dioxide concentration, and combining their respective weight coefficients. The sum of these four items is used to obtain the degree of environmental data deviation. .

[0105] The formula comprehensively considers the data deviation of four key environmental factors: temperature, humidity, air pressure and carbon dioxide concentration. The formula can comprehensively reflect the comprehensive deviation degree of environmental data through the sum of squares of deviations and combined with weight coefficients. The value can quantify the degree of deviation of environmental data, which is convenient for relevant personnel to intuitively understand the accuracy of environmental data and promptly discover data anomalies, providing a reliable data quality reference for environmental monitoring and related decision-making. The weight of each parameter can be adjusted according to the actual situation so that the formula can adapt to the differences in sensitivity of each parameter to different environmental monitoring scenarios, improve the accuracy and practicality of the assessment, help ensure the reliability and effectiveness of environmental data, and lay the foundation for subsequent analysis and application.

[0106] Calculate the power consumption fluctuation deviation The specific method is:

[0107] User power consumption data includes real-time power consumption in the current detection cycle , Real-time average power consumption , Historical power consumption during the historical detection period And the historical average electricity consumption .

[0108] It should be noted that real-time power consumption It is measured by the electric meter installed in the power system. Represents the number of measurements in the current detection cycle. Real-time power consumption, real-time average power consumption It is obtained by adding up all the real-time power consumption in the current detection cycle and dividing it by the number of measurements. It is obtained through the power consumption data recorded in the past detection cycle. Represents the first measurement in the historical detection cycle Historical electricity consumption, historical average electricity consumption It is obtained by adding the historical electricity consumption data in the historical detection period and dividing it by the number of measurements. The historical detection period can be the previous detection period of the current detection period.

[0109] Calculate the power consumption fluctuation deviation based on the user's power consumption data , the specific formula is as follows:

[0110] ;

[0111] in, Represents the number of measurements in the current detection cycle. Real-time power consumption, Indicates the number of measurements in the current detection cycle. , Represents the total number of measurements in the current detection cycle. Represents the first measurement in the historical detection cycle Historical electricity consumption, Indicates the number of measurements in the historical detection cycle, and its value is , Represents the total number of measurements during the historical detection period.

[0112] It should be noted that the calculation of each real-time power consumption Real-time average power consumption The deviations are squared and summed, divided by Divide the value by , and then take the square root to get the standard deviation of real-time power consumption fluctuation; calculate each historical power consumption Compared with the historical average electricity consumption The deviations are squared and summed, divided by The result is then divided by , then take the square root to get the standard deviation of historical electricity consumption fluctuations; subtract the standard deviation of historical electricity consumption fluctuations from the standard deviation of real-time electricity consumption fluctuations, and then multiply by , get the power consumption fluctuation deviation .

[0113] This formula combines the fluctuations of real-time electricity consumption and historical electricity consumption, which helps power companies understand changes in users' electricity consumption habits and the dynamics of grid load. The accurate electricity consumption fluctuation deviation can provide data support for grid planning and scheduling, and determine whether the fluctuation is abnormal.

[0114] Calculate the data deviation index The specific method is:

[0115] According to the environmental data deviation and power consumption fluctuation deviation , calculate the data deviation index , the formula is as follows:

[0116] ;

[0117] in, Representative environmental data deviation The weight coefficient is 0.3≤ ≤0.5, Represents the power consumption fluctuation deviation The weight coefficient is 0.5≤ ≤0.7, and .

[0118] It should be noted that this formula is used to synthesize the deviation of environmental data. and power consumption fluctuation deviation Get the data deviation index , is the weight coefficient of environmental data deviation, The data deviation index is obtained by multiplying the environmental data deviation by its weight coefficient, multiplying the power consumption fluctuation deviation by its weight coefficient, and then adding the two together. , this index can comprehensively reflect the deviation of power system data in terms of environment and electricity consumption.

[0119] This formula combines the environmental data deviation and the electricity consumption fluctuation deviation, and integrates them through the weight coefficient. The resulting data deviation index can reflect the deviation of the power system data as a whole, avoiding the limitations of single factor evaluation, and providing quantitative indicators for the comprehensive management of the power system. When the data deviation index exceeds a certain range, it indicates that the data may be abnormal, prompting managers to take corresponding measures to optimize the operation and maintenance of the power system.

[0120] The specific steps to determine the accuracy of data are:

[0121] Set the data deviation threshold ;

[0122] It should be noted that the data deviation threshold By performing statistical analysis on the data of the same data source under normal conditions and calculating the data deviation index under normal conditions, the normal fluctuation range of the data deviation index can be determined. The average value of the data deviation index in this range is taken as the data deviation threshold .

[0123] When the data deviation index <Data deviation threshold When the data deviation index is ≥Data deviation threshold , it means that the accuracy does not meet the standard, triggering a data accuracy abnormality warning.

[0124] Step 204: Determine whether to issue an early warning based on the completeness, timeliness and accuracy of the judgment:

[0125] When the integrity is judged not to meet the standards, a data missing warning will be issued; when the timeliness is judged not to meet the standards, a data delay warning will be issued; when the accuracy does not meet the standards, a data accuracy abnormality warning will be triggered.

[0126] By judging the integrity, timeliness and accuracy of data, data problems can be discovered in a timely manner, data loss caused by the mismatch between equipment data and the corresponding data set can be prevented, and the integrity of the data foundation can be ensured; the stable operation of the power system is ensured in the timeliness judgment, and the timeliness threshold is reasonably set to ensure that the key data of the power system is updated in time to avoid power grid failures caused by data delays; the accuracy of data reliability is improved. The judgment based on the data deviation threshold can filter out data with excessive deviation, reduce misjudgment and potential risks caused by inaccurate data, and improve the overall data reliability of the power system.

[0127] Step 3: When any of the completeness, timeliness and accuracy of the data does not meet the standards, re-acquire the data; when the completeness, timeliness and accuracy of the data meet the standards, calculate the predicted environmental impact index based on the environmental monitoring data ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ; Based on the Geographic Impact Index , Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index .

[0128] Step 301: When any of the completeness, timeliness and accuracy of the data does not meet the standards, reacquire the data.

[0129] Step 302: When the data completeness, timeliness and accuracy meet the standards, calculate the power space situation prediction index , the specific steps are:

[0130] Calculate and predict the environmental impact index , the specific steps are:

[0131] Environmental monitoring data also includes real-time maximum temperature , Real-time minimum temperature , Real-time maximum humidity , Real-time minimum humidity , Real-time maximum air pressure , Real-time minimum air pressure , Real-time maximum carbon dioxide concentration And the real-time minimum carbon dioxide concentration .

[0132] It should be noted that the real-time maximum temperature , Real-time minimum temperature It is the real-time temperature value detected during the current detection cycle. The maximum and minimum values ​​in real time humidity And real-time minimum humidity It is the real-time humidity value detected during the current detection cycle. The maximum and minimum values ​​in real time; the maximum value of air pressure , Real-time minimum air pressure It is the real-time air pressure detected during the current detection cycle. Maximum and minimum values ​​of real-time carbon dioxide concentration And the real-time minimum carbon dioxide concentration It is the real-time carbon dioxide concentration value detected during the current detection cycle. The maximum and minimum values ​​in .

[0133] Calculate and predict the environmental impact index based on environmental monitoring data , the specific formula is as follows:

[0134] ;

[0135] in, Represents the average temperature The weight coefficient is 0.1≤ ≤0.3, Represents the average humidity The weight coefficient is 0.2≤ ≤0.4, Represents the average air pressure The weight coefficient is 0.3≤ ≤0.5, Represents the average carbon dioxide concentration The weight coefficient is 0.1< ≤0.3, and .

[0136] It should be noted that the formula takes into account the impact of four key environmental factors, namely temperature, humidity, air pressure and carbon dioxide concentration, on the power system, and can comprehensively and systematically reflect the comprehensive impact of the environment on the power system. The value can quantify the potential impact of the environment on the power system, which is convenient for power system operation and maintenance personnel to intuitively understand the comprehensive effect of current environmental factors and make scientific and reasonable decisions. The weight coefficient can be adjusted according to actual conditions so that the formula can adapt to the differences in sensitivity of different power systems to various environmental factors, improve the accuracy and practicality of the evaluation, and help ensure the stable operation of the power system under different environmental conditions.

[0137] Calculate the basic operating status index The specific steps are:

[0138] Basic operating status data includes real-time voltage values ​​of power equipment , Real-time maximum voltage value , Real-time minimum voltage value , Real-time current value , Real-time maximum current value , Real-time minimum current value , Real-time operating temperature value , Real-time maximum operating temperature value And real-time minimum operating temperature value .

[0139] It should be noted that the real-time voltage value Usually obtained by voltage sensors installed in the power system; the data acquisition system continuously receives real-time voltage values ​​from the voltage sensors , by comparing the real-time maximum voltage value within a unit time period And real-time minimum voltage value ; Real-time current value Measured by current sensor; collects real-time current value of power equipment in operation , by comparing the real-time maximum current value within this unit time period and real-time minimum current value ; Real-time operating temperature value Measured by temperature sensors installed on power equipment; collects real-time operating temperature values ​​of power equipment within a unit time period , by comparing the real-time maximum operating temperature value within this week and real-time minimum operating temperature value .

[0140] Set rated voltage , Rated current value And the rated operating temperature .

[0141] It should be noted that the rated voltage , Rated current value And the rated operating temperature It is determined based on the power distribution standard of the power system.

[0142] According to the basic operating status data, rated voltage value , Rated current value And the rated operating temperature , calculate the basic operating status index , the specific formula is as follows:

[0143] ;

[0144] in, Represents the power factor, the value is 0< ≤1; Representative voltage value The weight coefficient is 0.2≤ ≤0.4, Representative current value The weight coefficient is 0.1< ≤0.3, Represents power factor The weight coefficient is 0.1≤ ≤0.3, Represents the operating temperature value The weight coefficient is 0.3≤ ≤0.5, and .

[0145] It should be noted that the power factor It refers to the ratio of active power to apparent power in an AC circuit, reflecting the degree to which the power of the power source is effectively utilized, and its value range is between 0 and 1. When the power factor is equal to 1, it means that the voltage and current are in phase, there is only active power in the circuit, and the power energy is fully utilized by the load; the lower the power factor, the greater the proportion of reactive power, and a larger part is used for periodic exchange between the power source and the energy storage element, but is not actually consumed by the load to do work, and the power utilization efficiency is not high, which can be directly obtained through the power factor meter.

[0146] It should be noted that Indicates the relative deviation of the real-time voltage relative to the rated voltage within the voltage fluctuation range, multiplied by the weight coefficient , represents the contribution of voltage factor to the basic operation status index; is the current relative deviation, multiplied by the weight coefficient , represents the contribution of the current factor to the basic operating status index; Directly reflects the impact of power factor on operating status, multiplied by the weight coefficient , represents the contribution of power factor to the basic operating status index; is the equivalent temperature relative deviation, multiplied by the weight coefficient , represents the contribution of the equivalent temperature factor to the basic operating status index. Finally, add these four items to get the basic operating status index ,This index quantifies the operating status of power equipment by comprehensively considering the relative deviations of multiple ,operating factors and combining their respective weight coefficients.

[0147] The formula comprehensively considers key operating parameters such as voltage, current, power factor and equivalent temperature. By comparing with the rated value and combining the weight coefficient, it can fully reflect the operating status of the power equipment. The value can quantify the health of the equipment, making it easier for operation and maintenance personnel to intuitively understand the current status of the equipment and promptly discover potential problems. The weight of each parameter can be adjusted according to actual conditions so that the formula can adapt to the differences in sensitivity of different equipment to each parameter, thereby improving the accuracy of the assessment, helping to ensure the stable operation of the power system and reduce the occurrence of failures.

[0148] Calculate the predicted power load impact index The specific steps are:

[0149] The user's electricity consumption data also includes the electricity consumption during peak hours. And power consumption during low electricity .

[0150] It should be noted that the smart meter will record the power consumption of each period at the end of the period. In this way, the power consumption during peak hours can be directly obtained. And power consumption during low electricity .

[0151] Based on real-time average power consumption , power consumption during peak hours And the power consumption during the off-peak period , calculate the peak-to-valley difference rate of electricity consumption The specific formula is as follows:

[0152] .

[0153] Historical electricity data also includes the electricity consumption of the previous cycle .

[0154] Based on real-time power consumption And the power consumption in the previous cycle , calculate the load growth rate The specific formula is as follows:

[0155] ;

[0156] in, Represents the period, and the value is a positive number.

[0157] Real-time power consumption based on the current detection cycle , power consumption during peak hours , peak-to-valley difference rate of electricity consumption , Load growth rate And the average power consumption , calculate and predict the power load impact index The specific formula is as follows:

[0158] ;

[0159] in, Represents real-time power consumption The weight coefficient is 0.1< ≤0.3, is the load growth rate The weight coefficient ranges from 0.3 ≤ ≤0.6, The peak-to-valley rate of electricity consumption The weight coefficient is 0.2≤ ≤0.5, and + + =1.

[0160] It should be noted that It means averaging the relative deviations of multiple real-time power consumptions relative to the average power consumption within the peak power consumption range, multiplied by the weight coefficient , get the contribution of real-time power consumption factors to the predicted power load impact index, Obtain the contribution of the load growth rate factor to the predicted power load impact index, The contribution of the peak-to-valley difference factor to the predicted power load impact index is obtained, and finally the predicted power load impact index is obtained by adding these three items. ,This index quantifies the impact of the power load by comprehensively considering the relative deviations of multiple ,power load-related factors and combining their respective weight coefficients.

[0161] The formula comprehensively considers factors such as real-time power consumption, peak-to-valley difference rate and load growth rate. Through relative deviation and combined with weight coefficient, it can fully reflect the comprehensive impact of power load. The value can quantify the impact of power load on the system, which is convenient for power system operation and maintenance personnel to intuitively understand the current load status, discover potential problems in time, and provide a reference basis for power dispatching and equipment maintenance. The weight of each parameter can be adjusted according to the actual situation so that the formula can adapt to the differences in sensitivity of different power systems to various parameters, improve the accuracy of the evaluation, and ensure the stable operation of the power system.

[0162] Calculate and predict the comprehensive index of power space The specific steps are:

[0163] According to the environmental impact index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index The specific formula is as follows:

[0164] ;

[0165] in, is a constant term.

[0166] It should be noted that this formula is used to calculate the predicted power space comprehensive index , taking into account the environmental impact index , Basic Operation Status Index and power load impact index The impact of three factors on the power system state.

[0167] It should be noted that It is the average of the sum of the squares of the three exponents. is to add the three exponents and divide by Take the sine of the result and divide by This is to limit the results to a certain range. The value can be The sine function here is used to introduce nonlinear factors to more comprehensively reflect the results of the combined effects of the three exponents.

[0168] Finally, add the above two parts and take the square root to get the predicted power space comprehensive index ,This index quantifies the comprehensive state of the power system by comprehensively considering the sum of squares, average values ​​and nonlinear sine function relationships of ,multiple factors.

[0169] The formula incorporates the Environmental Impact Index , Basic Operation Status Index and power load impact index , which fully reflects the comprehensive impact of the environment, its own operating status and load conditions on the power system, avoids the one-sidedness of single factor evaluation, and can capture the interactive relationship between various factors by introducing sine function for nonlinear processing, so that the comprehensive index can more accurately reflect the actual state of the power system and provide a more reliable basis for the evaluation of the system operating status. The value can be used as an intuitive comprehensive indicator to facilitate power system operation and maintenance personnel to quickly understand the overall operation of the system, discover potential problems in a timely manner, make reasonable operation and maintenance and scheduling decisions, and ensure the stable operation of the power system.

[0170] Step 4: Set the threshold of the power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

[0171] Step 401: Setting the power space situation prediction index threshold , power space situation prediction index threshold Including the first threshold , Secondary threshold and the third threshold ,in, < ;

[0172] It should be noted that through statistical analysis of the long-term historical operation data of the power system, when the system is operating normally and stably, the power space situation prediction index is Falls within a relatively stable range, and the upper limit of this range is set as the first-level threshold , collect statistics on historical small load fluctuations, slight performance degradation of equipment caused by local environmental changes, etc. When these events occur, There will be a certain degree of increase, and statistics and analysis will be conducted to determine the secondary threshold , and statistics on large-scale power outages and serious equipment damage that occurred in history. Before these major failures occurred, There is usually a significant upward trend, which can be seen by Analysis of numerical values ​​to determine the three-level threshold .

[0173] Step 402: Determine whether the power space risk alarm information is triggered, and generate a corresponding assessment report and adjustment plan. The specific steps are:

[0174] When the power space situation prediction index ≤ When the power space abnormality alarm information is not triggered;

[0175] when <Electricity Space Situation Forecast Index ≤ When the power abnormality risk alarm information is triggered, the primary adjustment instruction and risk assessment report are generated.

[0176] When a level one alarm is triggered, it means that a certain degree of abnormality has occurred in the power system, but the degree of abnormality is relatively mild and the system can still self-regulate within a certain range.

[0177] The primary adjustment instruction is to make preliminary adjustments to the current slightly abnormal state of the system. For example, load adjustment of local equipment, fine-tuning of environmental control parameters, etc., in order to restore the system to normal operation. The risk assessment report mainly focuses on the analysis of the current abnormal situation. The report content includes the investigation of possible factors causing the abnormality, such as whether it is caused by a slight increase in load in a certain area, a small change in environmental parameters, etc. At the same time, the further impact that these factors may have on the system will be evaluated, and preliminary response strategies will be proposed.

[0178] when <Electricity Space Situation Forecast Index When the secondary power space abnormality alarm information is triggered, the intermediate adjustment instructions and risk assessment report are generated.

[0179] When the second-level alarm is triggered, it indicates that the abnormal situation of the power system is serious and has exceeded the range that the system can easily adjust by itself, and requires more in-depth intervention. Intermediate adjustment instructions involve comprehensive adjustments to multiple parts of the system. For example, it is necessary to redistribute the load of some transmission lines, make significant adjustments to the operating parameters of related equipment, start backup equipment to share the load, etc., to ensure that the system can return to stability. The report includes an analysis of the root causes of the current serious abnormal situation, such as whether it is caused by the combined effect of multiple factors, such as equipment aging and environmental deterioration. At the same time, a comprehensive assessment of the risks that the system may face in the current abnormal state will be conducted, including an assessment of the risk of equipment damage and power outages, and a corresponding comprehensive response strategy will be proposed.

[0180] when <Electricity Space Situation Forecast Index When the alarm is triggered, the third-level power space abnormality alarm information is generated, and advanced adjustment instructions and risk assessment reports are generated.

[0181] When the third-level alarm is triggered, it means that the power system is in a very dangerous state and a major failure is very likely to occur, such as large-scale power outages and serious damage to equipment.

[0182] Advanced regulation instructions involve emergency regulation of the entire power system, such as temporary changes to the topology of the power grid, emergency shutdown or switching of equipment, and calling external emergency power supplies to minimize the losses caused by failures. The assessment report includes a detailed analysis of the current extremely dangerous state, such as the investigation of all factors that lead to the collapse of the system, including equipment failure, extreme environmental conditions, and severe load imbalance. At the same time, it will accurately assess the possible consequences of the impending major failure, such as the scope of the power outage, the duration of the power outage, the impact on users and society, and propose response strategies, including the activation of emergency plans and the formulation of emergency repair plans.

[0183] See also Figure 3 The present invention provides a power space data audit management system, comprising:

[0184] Data collection module, used to count the actual number of power equipment covered by the power system , and collect data sets for each area where the power equipment is located, and calculate the actual number of statistical data sets ;The data set includes environmental monitoring data, basic operating status data, user electricity consumption data and historical electricity data.

[0185] Data detection module, used to detect the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation and power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and determine whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy.

[0186] The data analysis module is used to re-acquire data when any of the data's integrity, timeliness and accuracy do not meet the standards; when the data's integrity, timeliness and accuracy all meet the standards, the environmental impact index is calculated and predicted based on the environmental monitoring data. ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ;According to the Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index .

[0187] Data evaluation module, used to set the threshold of power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

[0188] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0189] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0190] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for auditing and managing power space data, characterized in that: include: Count the actual number of power equipment covered by the power system , and collect data sets for each area where the power equipment is located, and calculate the actual number of statistical data sets ;The data set includes environmental monitoring data, basic operation status data, user power consumption data and historical power data; According to the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation and power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and judge whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy; When any of the completeness, timeliness and accuracy of the data does not meet the standards, the data will be re-acquired; when the completeness, timeliness and accuracy of the data all meet the standards, the predicted environmental impact index will be calculated based on the environmental monitoring data ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ; Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index ; Setting the threshold of power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

2. The power space data audit management method according to claim 1 is characterized in that: Calculate time difference The specific method is: Receive timestamp based on time And the acquisition timestamp , calculate the time difference The specific formula is as follows: 。 3. The power space data audit management method according to claim 2 is characterized in that: Calculate the deviation of environmental data , Power consumption fluctuation deviation and data deviation index The method is: Calculate the deviation of environmental data The specific method is: Environmental monitoring data includes real-time temperature values ​​during the current detection cycle , Temperature average , Real-time humidity value Humidity average , Real-time air pressure value Average air pressure , Real-time carbon dioxide concentration value and the average carbon dioxide concentration ; Calculate the environmental data deviation based on environmental monitoring data , the specific formula is as follows: ； in, Represents the number of measurements in the current detection cycle. Temperature value, Represents the number of measurements in the current detection cycle. Humidity value, Represents the number of measurements in the current detection cycle. The air pressure value, Represents the number of measurements in the current detection cycle. The carbon dioxide concentration value, Indicates the number of measurements in the current detection cycle. , represents the total number of measurements, Represents the real-time temperature value The weight coefficient is 0.1≤ ≤0.3, Represents the real-time humidity value The weight coefficient is 0.2≤ ≤0.4, Represents the real-time air pressure value The weight coefficient is 0.3≤ ≤0.5, Represents real-time carbon dioxide concentration The weight coefficient of R is 0.1< ≤0.3, and ; Calculate the power consumption fluctuation deviation The specific method is: User power consumption data includes real-time power consumption in the current detection cycle , Real-time average power consumption And the historical power consumption during the historical detection period , Historical average electricity consumption ; Calculate the power consumption fluctuation deviation based on the user's power consumption data The specific formula is as follows: ； in, Represents the number of measurements in the current detection cycle. Real-time power consumption, Indicates the number of measurements in the current detection cycle. , Represents the total number of measurements in the current detection cycle. Represents the first measurement in the historical detection cycle Historical electricity consumption, Indicates the number of measurements in the historical detection cycle, and its value is , Represents the total number of measurements during the historical detection period; Calculate the data deviation index The specific method is: According to the environmental data deviation and power consumption fluctuation deviation , calculate the data deviation index , the formula is as follows: ； in, Representative environmental data deviation The weight coefficient is 0.3≤ ≤0.5, Represents the power consumption fluctuation deviation The weight coefficient is 0.5≤ ≤0.7, and .

4. The power space data audit management method according to claim 3 is characterized in that: The specific method for deciding whether to issue an early warning based on the results of the completeness, timeliness and accuracy is as follows: The method to determine data integrity is: The actual number of electrical equipment The actual number of data sets For comparison, if , then the integrity is judged to meet the standard, , then the integrity is judged to be not up to standard and a data missing warning is issued; The specific steps to determine the timeliness of data are: Setting a timeliness threshold , the time difference and timeliness threshold Compare, if the time difference ≤Timeliness threshold When , it means that the timeliness meets the standard. >Timeliness threshold If the timeliness does not meet the standard, a data delay warning will be issued; The specific steps to determine the accuracy of data are: Set the data deviation threshold , when the data deviation index <Data deviation threshold When the data deviation index is ≥Data deviation threshold , it means that the accuracy does not meet the standard, triggering a data accuracy abnormality warning.

5. The power space data audit management method according to claim 4 is characterized in that: Calculate and predict the environmental impact index The specific steps are: Environmental monitoring data also includes real-time maximum temperature , Real-time minimum temperature , Real-time maximum humidity , Real-time minimum humidity , Real-time maximum air pressure , Real-time minimum air pressure , Real-time maximum carbon dioxide concentration And the real-time minimum carbon dioxide concentration ; Calculate and predict the environmental impact index based on environmental monitoring data The specific formula is as follows: ； in, Represents the average temperature The weight coefficient is 0.1≤ ≤0.3, Represents the average humidity The weight coefficient is 0.2≤ ≤0.4, Represents the average air pressure The weight coefficient is 0.3≤ ≤0.5, Represents the average carbon dioxide concentration The weight coefficient is 0.1< ≤0.3, and .

6. The power space data audit management method according to claim 5 is characterized by: Calculate the basic operating status index The specific steps are: Basic operating status data includes real-time voltage value , Real-time maximum voltage value , Real-time minimum voltage value , Real-time current value , Real-time maximum current value , Real-time minimum current value , Real-time operating temperature value , Real-time maximum operating temperature value And real-time minimum operating temperature value ; Set rated voltage , Rated current value And the rated operating temperature ; According to the basic operating status data, rated voltage value , Rated current value And the rated operating temperature , calculate the basic operating status index The specific formula is as follows: ； in, Represents the power factor, which is ; Representative voltage value The weight coefficient is 0.2≤ ≤0.4, Representative current value The weight coefficient is 0.1< ≤0.3, Represents power factor The weight coefficient is 0.1≤ ≤0.3, Represents the operating temperature value The weight coefficient is 0.3≤ ≤0.5, and .

7. The power space data audit management method according to claim 6 is characterized by: Calculate the predicted power load impact index The specific steps are: The user's electricity consumption data also includes the electricity consumption during peak hours. , peak-to-valley difference rate of electricity consumption And the load growth rate ; Real-time power consumption based on the current detection cycle , power consumption during peak hours , peak-to-valley difference rate of electricity consumption , Load growth rate And real-time average power consumption , calculate and predict the power load impact index The specific formula is as follows: ； in, Represents real-time power consumption The weight coefficient is 0.1< ≤0.3, is the load growth rate The weight coefficient ranges from 0.3 ≤ ≤0.6, The peak-to-valley rate of electricity consumption The weight coefficient is 0.2≤ ≤0.5, and + + =1.

8. The power space data audit management method according to claim 7 is characterized by: Calculate and predict the comprehensive index of power space The specific steps are: According to the environmental impact index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index The specific formula is as follows: ； in, is a constant term.

9. The power space data audit management method according to claim 8, characterized in that: The specific steps to determine whether to trigger the power space risk alarm information and generate the corresponding assessment report and adjustment plan are as follows: Power space situation prediction index threshold Including the first threshold , Secondary threshold and the third threshold ,in, < ; When the power space situation prediction index ≤ When the power space abnormality alarm information is not triggered; when <Electricity Space Situation Forecast Index ≤ When the power abnormality risk alarm information is triggered, the primary adjustment instruction and risk assessment report are generated; when <Electricity Space Situation Forecast Index When the secondary power space abnormal alarm information is triggered, the intermediate adjustment instructions and risk assessment report are generated; when <Electricity Space Situation Forecast Index When the alarm is triggered, the third-level power space abnormality alarm information is generated, and advanced adjustment instructions and risk assessment reports are generated.

10. An electric power space data audit management system, characterized by: include: Data collection module, used to count the actual number of power equipment covered by the power system , and collect data sets for each area where the power equipment is located, and calculate the actual number of statistical data sets ;The data set includes environmental monitoring data, basic operation status data, user power consumption data and historical power data; Data detection module, used to detect the actual number of power equipment The actual number of data sets Compare and determine whether the integrity of the data meets the standards; collect the timestamp of the data set and receiving timestamp , calculate the time difference , the time difference and timeliness threshold Compare and judge whether the timeliness of data meets the standards; calculate the environmental data deviation based on environmental monitoring data , calculate the power consumption fluctuation deviation based on the user's power consumption data , according to the environmental data deviation And power consumption fluctuation deviation Calculate the data deviation index , preset data deviation threshold , the data deviation index Deviation threshold from data Make a comparison and judge whether the accuracy of the data meets the standards based on the comparison results; decide whether to issue an early warning based on the judgment results of completeness, timeliness and accuracy; The data analysis module is used to re-acquire data when any of the data's integrity, timeliness and accuracy do not meet the standards; when the data's integrity, timeliness and accuracy all meet the standards, the environmental impact index is calculated and predicted based on the environmental monitoring data. ; Calculate the basic operation status index based on the basic operation status data ; Calculate and predict the power load impact index based on user power consumption data and historical power data ;According to the Environmental Impact Index , Basic Operation Status Index and power load impact index , calculate the power space situation prediction index ; Data evaluation module, used to set the threshold of power space situation prediction index , according to the power space situation forecast index Threshold of power space situation prediction index Based on the comparison results, it is determined whether the power space abnormality alarm information is triggered, and a corresponding evaluation report and adjustment plan are generated.

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