CN119849951B

CN119849951B - Electric power space data auditing management method and system

Info

Publication number: CN119849951B
Application number: CN202510326843.9A
Authority: CN
Inventors: 孟小前; 杨璇; 王佳颖; 叶子; 宫雅文; 郑思嘉; 白皓东; 黎泽承; 吴建雄; 白雪; 李玉容; 李冽庚; 张健
Original assignee: State Grid Power Space Technology Co ltd; State Grid Corp of China SGCC
Current assignee: State Grid Power Space Technology Co ltd; State Grid Corp of China SGCC
Priority date: 2025-03-19
Filing date: 2025-03-19
Publication date: 2025-05-16
Anticipated expiration: 2045-03-19
Also published as: CN119849951A

Abstract

The invention discloses a method and a system for auditing and managing electric power space data, which relate to the technical field of electric power system data management and risk assessment, and mainly adopt the scheme that the actual number of electric power equipment is counted, the number of data sets is collected, and whether the integrity, the timeliness and the accuracy of data are qualified or not is judged by comparing the number of the electric power equipment with the time difference between the collection and the receiving time stamp of the data sets and the data deviation index of the data sets; the method solves the problems that the data accuracy evaluation is not accurate enough and misjudgment is easy to generate in the prior art, calculates the power space situation estimated index based on the data of the data set to judge whether to trigger the power space abnormal alarm information, generates corresponding evaluation reports and adjustment schemes, calculates various influence indexes based on various data and obtains the power space situation estimated index, and solves the problems that the operation state of the power system cannot be evaluated from various angles in the prior art, so that the operation risk exists.

Description

Electric power space data auditing management method and system

Technical Field

The invention relates to the technical field of power system data management, in particular to a power space data auditing management method and system.

Background

In the operation management of an electric power system, accurate acquisition and effective analysis of data related to electric power equipment are important. The integrity, timeliness and accuracy of the data directly influence the stable operation and reasonable planning of the power system, the data of the power system has complexity and diversity, the data comprises environmental monitoring, running state, user electricity consumption and other aspects, and how to comprehensively process the data to ensure the efficient operation of the power system is a key problem faced in the field.

In the prior art, an independent data acquisition and analysis method is generally adopted, for data acquisition of power equipment, data is acquired by installing sensors on the equipment, such as voltage and current sensors acquire operation data, and in terms of data processing, whether the operation of a power system is normal is simply analyzed according to the acquired data.

However, the data acquired in the prior art lacks integrity, various types of data are independently acquired, the relevance among the data of the power equipment is not fully considered, the running state of the power system is difficult to evaluate from the global angle, on the basis of data instruction judgment, the quality of the data cannot be judged and evaluated, the quality problem of the data judgment cannot be guaranteed, the data is single, and the running state of the power system cannot be evaluated from the global angle.

Disclosure of Invention

The technical problems to be solved are as follows:

Aiming at the defects of the prior art, the invention provides an electric power space data auditing management method and system, which solve the problems that the data acquisition lacks integrity and is difficult to judge the data integrity in the prior art by counting and comparing the actual number of electric power equipment with the number of acquired data sets, solve the problems that the data timeliness judging method is simple and the data timeliness cannot be accurately measured in the prior art by utilizing the acquisition time stamp and the receiving time stamp of the data sets to calculate the time difference value and compare the time difference value with the timeliness threshold value, solve the problems that the data timeliness cannot be accurately measured in the prior art, and solve the problems that the data accuracy is not accurate enough to evaluate and easy to produce misjudgment in the prior art by respectively calculating the environment and the electricity consumption deviation degree of a user and comparing the electricity deviation degree with the data deviation degree threshold value, and solve the problems that the prior art cannot evaluate the running state of an electric power system from multiple angles by calculating various influence indexes based on various data situation prediction indexes, so as to cause running risks.

(II) technical scheme:

In order to achieve the purpose, the invention is realized by the following technical scheme that the electric power space data auditing management method comprises the following steps:

Counting the actual number of power devices covered by a power system Collecting data sets of the areas where each power device is located, and counting the actual number of the data setsThe data set comprises environment monitoring data, basic running state data, user electricity data and historical electric power data;

According to the actual number of the power equipment And the actual number of data setsComparing, judging whether the integrity of the data accords with the standard or not, and collecting the time stamp through the data setAnd receiving a time stampCalculating a time differenceBy time differenceAnd a time-efficiency thresholdComparing, judging whether the timeliness of the data meets the standard, calculating the deviation degree of the environmental data according to the environmental monitoring dataCalculating the fluctuation deviation degree of the electricity consumption according to the electricity consumption data of the userAccording to the deviation degree of the environmental dataAnd the degree of deviation of fluctuation of electricity consumptionCalculating a data deviation indexPresetting a data deviation thresholdIndex the data deviation degreeThreshold value of deviation from dataJudging whether the accuracy of the data meets the standard according to the comparison result, and determining whether to send out early warning according to the judgment result of the integrity, timeliness and accuracy;

re-acquiring the data when any one of the integrity, timeliness and accuracy of the data is not in accordance with the standard, calculating a predictive environmental impact index from the environmental monitoring data when the integrity, timeliness and accuracy of the data are in accordance with the standard Calculating a base operating state index from the base operating state dataCalculating a predicted power load impact index according to the user power consumption data and the historical power dataAccording to the environmental impact indexBasic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated index;

Setting a power space situation estimation index thresholdEstimating an index according to the state of the power spaceAnd power space situation predictive index thresholdAnd judging whether to trigger the power space abnormality alarm information or not, and generating a corresponding evaluation report and an adjustment scheme.

In the preferred scheme of the power space data auditing management method, the time difference value is calculatedThe specific method of (a) is as follows:

Receiving time stamps according to time Acquisition time stampCalculating a time differenceThe specific formula is as follows:

;

in the preferred scheme of the power space data auditing management method, the environmental data deviation degree is calculated Degree of deviation of fluctuation of electricity consumptionAnd data bias indexThe method of (1) is as follows:

Computing environmental data bias degree The specific method of (a) is as follows:

the environmental monitoring data includes a real-time temperature value of the current detection period Average value of temperatureReal-time humidity valueHumidity averageReal-time air pressure valueAverage value of air pressureReal-time carbon dioxide concentration valueAverage value of carbon dioxide concentration;

Calculating the deviation degree of the environmental data according to the environmental monitoring dataThe specific formula is as follows:

;

Wherein, Representing the first measurement during the current detection periodThe value of the temperature is set to be the same,Representing the first measurement during the current detection periodThe value of the humidity is set to be the value of the humidity,Representing the first measurement during the current detection periodThe value of the air pressure is set to be equal to the value of the air pressure,Representing the first measurement during the current detection periodThe concentration value of the carbon dioxide,A serial number representing the number of measurements in the current detection period, the serial number being the value,Representing the total number of measurements taken,Representing real-time temperature valuesThe weight coefficient of (2) is 0.1-0≤0.3,Representing real-time humidity valuesThe weight coefficient of (2) is 0.2-less≤0.4,Representing real-time air pressure valueThe weight coefficient of (2) is 0.3-0≤0.5,Representing real-time carbon dioxide concentrationThe weight coefficient of R is 0.1<Is less than or equal to 0.3, and;

Calculating the fluctuation deviation degree of the electricity consumptionThe specific method of (a) is as follows:

The user electricity data comprises real-time electricity consumption of the current detection period Real-time average power consumptionHistorical electricity consumption of historical detection periodAverage historical electricity consumption;

Calculating the fluctuation deviation degree of the electricity consumption according to the electricity consumption data of the userThe specific formula is as follows:

;

Wherein, Representing the first measurement during the current detection periodThe power consumption is carried out in real time,A serial number representing the number of measurements in the current detection period, the serial number being the value,Representing the total number of measurements in the current detection period,Representing the first measurement in a historical detection periodThe amount of electricity used in the history is,A serial number indicating the number of measurements in the history detection period, the serial number being given as,Representing the total number of measurement times in the history detection period;

Calculating a data deviation index The specific method of (a) is as follows:

According to the deviation degree of the environmental data And the degree of deviation of fluctuation of electricity consumptionCalculating a data deviation indexThe formula according to is as follows:

;

Wherein, Representing the degree of deviation of environmental dataThe weight coefficient of (2) is 0.3-0≤0.5,Representing the degree of deviation of fluctuation of electricity consumptionThe weight coefficient of (2) is 0.5-lessIs less than or equal to 0.7, and。

In the preferred scheme of the power space data auditing management method, the specific method for determining whether to send out early warning according to the judging results of integrity, timeliness and accuracy comprises the following steps:

The method for judging the data integrity comprises the following steps:

Actual number of power equipment And the actual number of data setsFor comparison, ifThen the integrity is judged to be in compliance with the standard,Judging that the integrity does not meet the standard, and performing data loss early warning;

the method for judging the timeliness of the data comprises the following specific steps of:

setting a timeliness threshold By time differenceAnd a time-efficiency thresholdComparing if the time differenceTime-efficiency threshold value less than or equal toWhen the time is equal to the time difference, the time is equal to the time differenceTime-effectiveness thresholdWhen the time is not in accordance with the standard, the data delay early warning is carried out;

the specific steps for judging the accuracy of the data are as follows:

Setting a data deviation threshold Data deviation index< Data deviation threshold valueWhen the representative accuracy meets the standard, the data deviation indexNot less than data deviation threshold valueAnd when the representative accuracy does not meet the standard, triggering abnormal early warning of the data accuracy.

In the preferred scheme of the power space data auditing management method, the predicted environmental impact index is calculatedThe specific steps of (a) are as follows:

The environmental monitoring data also includes real-time temperature maxima Real-time temperature minimumMaximum value of real-time humidityReal-time humidity minimumMaximum value of real-time air pressureReal-time air pressure minimumMaximum value of real-time carbon dioxide concentrationReal-time carbon dioxide concentration minimum;

Calculating a predicted environmental impact index from environmental monitoring dataThe specific formula is as follows:

;

Wherein, Representative temperature averageThe weight coefficient of (2) is 0.1-0≤0.3,Represents the average value of humidityThe weight coefficient of (2) is 0.2-less≤0.4,Representing the average value of the air pressureThe weight coefficient of (2) is 0.3-0≤0.5,Represents the average value of the concentration of carbon dioxideThe weight coefficient of (2) is 0.1<Is less than or equal to 0.3, and。

In the preferred scheme of the power space data auditing management method, the basic operation state index is calculatedThe specific steps of (a) are as follows:

the base operating state data includes real-time voltage values Real time maximum voltage valueReal-time minimum voltage valueReal-time current valueMaximum current value in real timeReal-time minimum current valueReal-time operating temperature valueReal-time maximum operating temperature valueReal-time minimum operating temperature value;

Setting rated voltage valueRated current valueRated operating temperature value;

According to basic operation state data and rated voltage valueRated current valueRated operating temperature valueCalculating a base operating state indexThe specific formula is as follows:

;

Wherein, Representing the power factor, the value is 0<≤1;Representative voltage valueThe weight coefficient of (2) is 0.2-less≤0.4,Representative current valueThe weight coefficient of (2) is 0.1<≤0.3,Representing power factor≤0.3,Representing the operating temperature valueThe weight coefficient of (2) is 0.3-0Is less than or equal to 0.5, and。

In the preferred scheme of the power space data auditing management method, the power load influence index is calculated and predictedThe specific steps of (a) are as follows:

The user electricity consumption data also comprises electricity consumption at peak time Peak power supply Gu ChalvLoad increase rate;

Real-time electricity consumption according to current detection periodElectricity consumption at peak timePeak power supply Gu ChalvLoad increase rateReal-time average power consumptionCalculating a predicted electrical load impact indexThe specific formula is as follows:

;

Wherein, Representing real-time electricity consumptionThe weight coefficient of (2) is 0.1<≤0.3,For load increase rateThe weight coefficient of the weight coefficient is within the range of 0.3 to less than or equal to≤0.6,Peak for electricity use Gu ChalvThe weight coefficient of (2) is 0.2-lessIs less than or equal to 0.5, and++=1。

In the preferred scheme of the power space data auditing management method, the predicted power space comprehensive index is calculatedThe specific steps of (a) are as follows:

According to the environmental impact index Basic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated indexThe specific formula is as follows:

;

Wherein, Is a constant term.

In the preferred scheme of the power space data auditing management method, the specific steps of judging whether to trigger power space risk alarm information and generating a corresponding evaluation report and an adjustment scheme are as follows:

Power space situation predictive index threshold Includes a first level thresholdSecond order thresholdAnd a three-level threshold, wherein,<;

When the power space situation is estimated to be exponential≤When the power space abnormality alarm information is not triggered;

When (when) < Power space situation prediction index >≤Triggering first-level power abnormality risk alarm information to generate a primary regulation instruction and a risk assessment report;

When (when) < Power space situation prediction index >Triggering secondary power space abnormality alarm information to generate a medium-level adjustment instruction and a risk assessment report;

When (when) < Power space situation prediction index >And triggering three-level power space abnormality alarm information to generate an advanced regulation instruction and a risk assessment report.

The invention also discloses an electric power space data auditing management system, which comprises:

The data acquisition module is used for counting the actual number of the power equipment covered by the power system Collecting data sets of the areas where each power device is located, and counting the actual number of the data setsThe data set comprises environment monitoring data, basic running state data, user electricity data and historical electric power data;

The data detection module is used for detecting the actual quantity of the power equipment And the actual number of data setsComparing, judging whether the integrity of the data accords with the standard or not, and collecting the time stamp through the data setAnd receiving a time stampCalculating a time differenceBy time differenceAnd a time-efficiency thresholdComparing, judging whether the timeliness of the data meets the standard, calculating the deviation degree of the environmental data according to the environmental monitoring dataCalculating the fluctuation deviation degree of the electricity consumption according to the electricity consumption data of the userAccording to the deviation degree of the environmental dataAnd the degree of deviation of fluctuation of electricity consumptionCalculating a data deviation indexPresetting a data deviation thresholdIndex the data deviation degreeThreshold value of deviation from dataJudging whether the accuracy of the data meets the standard according to the comparison result, and determining whether to send out early warning according to the judgment result of the integrity, timeliness and accuracy;

The data analysis module is used for re-acquiring the data when any one of the integrity, the timeliness and the accuracy of the data is out of the standards, and calculating and predicting an environmental impact index according to the environmental monitoring data when the integrity, the timeliness and the accuracy of the data are out of the standards Calculating a base operating state index from the base operating state dataCalculating a predicted power load impact index according to the user power consumption data and the historical power dataAccording to the environmental impact indexBasic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated index;

The data evaluation module is used for setting a power space situation pre-estimation index threshold valueEstimating an index according to the state of the power spaceAnd power space situation predictive index thresholdAnd judging whether to trigger the power space abnormality alarm information or not, and generating a corresponding evaluation report and an adjustment scheme.

(III) beneficial effects:

The invention provides an electric power space data auditing management method and system, which have the following beneficial effects:

(1) By comprehensively counting the number of the power equipment and the number of the corresponding data sets, the systematic collection of the environment, operation, electricity consumption and historical data of the power system is realized, a complete data base is constructed, rich materials are provided for follow-up accurate analysis and evaluation, the situation that the state of the power system is judged due to data missing or omission is avoided, the operation management decision of the power system can be based on comprehensive and detailed data basis, and the scientificity and accuracy of management are improved.

(2) The time difference is calculated by utilizing the time stamp and compared with the threshold value, the timeliness of the data is accurately evaluated, the data hysteresis problem is timely found and early warned, the comparison judgment accuracy of various deviation degrees and the threshold value is calculated, the data quality is effectively screened, the error decision caused by error or outdated data is reduced, the stable operation and high-efficiency regulation and control of the power system are ensured, and the operation risk caused by the data problem is reduced.

(3) According to the environment, basic operation and power load data, influence indexes are calculated respectively, the action degree of each factor on the power system is quantized, the power space situation estimated indexes are obtained by integrating the indexes, and the overall operation situation and trend change of the power system can be accurately mastered, so that resource allocation and potential risk prediction are planned in advance, key quantized support is provided for optimizing operation, fault prevention and coping strategy formulation of the power system, and the reliability and economy of operation of the power system are improved.

(4) By setting the power space situation estimation index threshold value, the key evaluation is carried out on the overall state of the power system, whether the power space abnormality alarm information is triggered or not is accurately judged, the abnormal state of the system is timely perceived and the alarm is given out, the generated evaluation report is used for recording the system state and the problem root in detail, and the adjustment scheme is used for pertinently providing the optimization measures, so that clear action guidance is provided for power operation and maintenance personnel, the power system is promoted to quickly recover normal operation, the performance is continuously optimized, and the continuity and the stability of power supply are ensured.

Drawings

FIG. 1 is a flow chart of a method for auditing and managing electrical space data according to the present invention;

FIG. 2 is a schematic flow chart of data set accuracy judgment in an electric power space data auditing management method according to the present invention;

Fig. 3 is a schematic diagram of a power space data auditing management system according to the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Referring to fig. 1-2, the present invention provides a method for auditing and managing electric power space data, which includes:

the method comprises the steps of 1, counting the actual number of the power equipment covered by a power system, collecting a data set of an area where each power equipment is located, and counting the actual number of the data set, wherein the data set comprises environment monitoring data, basic running state data, user power consumption data and historical power data.

The method comprises the steps of calculating the actual quantity of the power equipment, helping to know the scale and the constitution of the power system, enabling environment monitoring data to evaluate the influence of external environment on the equipment, taking protective measures in advance, enabling basic operation state data to discover equipment abnormality in time, enabling user electricity consumption data to help analyze user habits and demands, optimizing power distribution and electricity price strategies, enabling historical electricity data to summarize operation rules, predicting electricity consumption trend, providing basis for expanding and upgrading the system, calculating the actual quantity of data sets, helping to establish a perfect data management system, avoiding data loss or confusion, and improving efficiency and accuracy of data management.

Step2, according to the actual number of the power equipmentAnd the actual number of data setsComparing, judging whether the integrity of the data accords with the standard or not, and collecting the time stamp through the data setAnd receiving a time stampCalculating a time differenceBy time differenceAnd a time-efficiency thresholdComparing, judging whether the timeliness of the data meets the standard, calculating the deviation degree of the environmental data according to the environmental monitoring dataCalculating the fluctuation deviation degree of the electricity consumption according to the electricity consumption data of the userAccording to the deviation degree of the environmental dataAnd the degree of deviation of fluctuation of electricity consumptionCalculating a data deviation indexPresetting a data deviation thresholdIndex the data deviation degreeThreshold value of deviation from dataAnd determining whether to send out early warning according to the judging results of the integrity, the timeliness and the accuracy.

Step 201, judging whether the integrity of the data meets the standard:

Obtaining actual quantity of power equipment And the actual number of data setsActual number of power equipmentAnd the actual number of data setsFor comparison, ifThen the integrity is judged to be in compliance with the standard,Judging that the integrity does not accord with the standard;

The actual number of the power equipment Is the actual number of electrical devices in the power system coverage area, the actual number of data setsIs the actual number of acquired data sets;

step 202, judging whether the timeliness of the data meets the standard:

Calculating a time difference The specific method of (a) is as follows:

Acquiring a receive timestamp Acquisition time stampAccording to the received time stampAcquisition time stampCalculating a time differenceThe specific formula is as follows:

。

The acquisition time stamp is used for the acquisition of the data Is the time point when the data in the data set is collected by the collecting equipment, and receives the time stampIs the point in time when data is received after uploading the data in the data set.

setting a timeliness threshold ;

Difference of timeAnd a time-efficiency thresholdComparing if the time differenceTime-efficiency threshold value less than or equal toWhen the time is equal to the time difference, the time is equal to the time differenceTime-effectiveness thresholdIn the time-course of which the first and second contact surfaces, then it is representative that the timeliness is not in compliance with the standard.

The time-dependent threshold valueCalculating the time difference value by using a plurality of historical acquisition time stamps and historical receiving time stamps in the same period in the historical dataTaking an average value and setting the average value as a timeliness threshold。

By using the received time stampSubtracting the acquisition time stampThe obtained time differenceThe time from the acquisition to the reception of the data can be reflected, the time difference value is compared with the timeliness threshold value, whether the timeliness of the data meets the standard can be judged, ifIf the time-effectiveness threshold is less than or equal to the time-effectiveness threshold, the time-effectiveness of the data meets the standard, ifIf the time-lapse threshold is larger than the time-lapse threshold, the time-lapse of the data does not meet the standard, and the data needs to be acquired again, and the core of the formula is to quantify the transmission delay of the data through a simple time-stamp subtraction operation, so as to evaluate the time-lapse of the data.

Step 203, judging whether the accuracy of the data meets the standard:

Computing environmental data bias degree Degree of deviation of fluctuation of electricity consumptionAnd data bias indexThe method comprises the following steps:

Computing environmental data bias degree The specific method comprises the following steps:

the environmental monitoring data includes a real-time temperature value of the current detection period Average value of temperatureReal-time humidity valueHumidity averageReal-time air pressure valueAverage value of air pressureReal-time carbon dioxide concentration valueAverage value of carbon dioxide concentration。

It should be noted that the number of the substrates,Representing the first measurement during the current detection periodThe temperature value is usually acquired by a temperature sensor, and the average value of the temperatureThe real-time humidity value is obtained by adding each real-time temperature value in the current detection period and dividing the sum of measurement times,Representing the first measurement during the current detection periodThe humidity value is measured by a humidity sensor, each real-time humidity value in the current detection period is added, and then divided by the measurement times to obtain a humidity average valueReal-time air pressure valueAverage value of air pressureAcquired by the air pressure sensor,Representing the first measurement during the current detection periodThe air pressure values are added up and divided by the measurement times to obtain an air pressure average valueReal-time carbon dioxide concentration valueDetected by a carbon dioxide concentration sensor,Representing the first measurement during the current detection periodAdding the carbon dioxide concentration values in each real time in the current detection period, dividing by the measurement times to obtain the average value of the carbon dioxide concentration。

;

Wherein, Representing the first measurement during the current detection periodThe value of the temperature is set to be the same,Representing the first measurement during the current detection periodThe value of the humidity is set to be the value of the humidity,Representing the first measurement during the current detection periodThe value of the air pressure is set to be equal to the value of the air pressure,Representing the first measurement during the current detection periodThe concentration value of the carbon dioxide,A serial number representing the number of measurements in the current detection period, the serial number being the value,Representing the total number of measurements taken,Representing real-time temperature valuesThe weight coefficient of (2) is 0.1-0≤0.3,Representing real-time humidity valuesThe weight coefficient of (2) is 0.2-less≤0.4,Representing real-time air pressure valueThe weight coefficient of (2) is 0.3-0≤0.5,Representing real-time carbon dioxide concentrationThe weight coefficient of R is 0.1<Is less than or equal to 0.3, and。

The deviation degree of the environmental data is quantified by comprehensively considering the deviation square sum of the temperature, the humidity, the air pressure and the carbon dioxide concentration and combining the weight coefficients, and the deviation degree of the environmental data is obtained by adding the four items。

The formula comprehensively considers the data deviation conditions of four key environmental factors of temperature, humidity, air pressure and carbon dioxide concentration, can comprehensively reflect the comprehensive deviation degree of environmental data through the square sum of the deviation and the combination of weight coefficients,The deviation degree of the environmental data can be quantized, related personnel can intuitively know the accuracy condition of the environmental data, timely find out data abnormality, provide reliable data quality reference for environmental monitoring and related decisions, and the weight of each parameter can be adjusted according to actual conditions, so that a formula can adapt to the sensitivity difference of different environmental monitoring scenes to each parameter, the evaluation accuracy and practicability are improved, the reliability and effectiveness of the environmental data are guaranteed, and a foundation is laid for subsequent analysis and application.

The user electricity data comprises real-time electricity consumption of the current detection period Real-time average power consumptionHistorical electricity consumption of historical detection periodHistorical average power consumption。

It should be noted that, the real-time electricity consumptionMeasured by means of an electricity meter installed in the power system,Representing the first measurement during the current detection periodReal-time electricity consumption and real-time average electricity consumptionIs obtained by adding all the real-time power consumption in the current detection period and dividing by the measurement times, and the historical power consumptionObtained from the power consumption data recorded during the past detection period,Representing the first measurement in a historical detection periodHistorical electricity consumption and historical average electricity consumptionThe historical power consumption data in the historical detection period is added and divided by the measurement times, and the historical detection period can be the last detection period of the current detection period.

;

Wherein, Representing the first measurement during the current detection periodThe power consumption is carried out in real time,A serial number representing the number of measurements in the current detection period, the serial number being the value,Representing the total number of measurements in the current detection period,Representing the first measurement in a historical detection periodThe amount of electricity used in the history is,A serial number indicating the number of measurements in the history detection period, the serial number being given as,Representing the total number of measurements in the historical detection period.

It should be noted that, each real-time electricity consumption is calculatedAverage power consumption in real timeSum of squares of these deviations divided byDivided by the value of (2)Then square root is opened to obtain fluctuation standard deviation of real-time power consumption, and each historical power consumption is calculatedAverage power consumption with historySum of squares of these deviations divided byIs divided byThen square root is opened to obtain fluctuation standard deviation of the historical power consumption, and the fluctuation standard deviation of the historical power consumption is subtracted from the fluctuation standard deviation of the real-time power consumption and multiplied byObtaining the fluctuation deviation degree of the electricity consumption。

The power consumption fluctuation deviation degree of accurate power consumption planning and scheduling of the power grid can provide data support for planning and scheduling of the power grid, and whether fluctuation is abnormal or not is judged.

Calculating a data deviation indexThe specific method of (a) is as follows:

;

It should be noted that the formula is used for synthesizing the deviation degree of the environmental dataAnd the degree of deviation of fluctuation of electricity consumptionObtaining the data deviation index,Is a weight coefficient of the degree of deviation of the environmental data,The power consumption fluctuation deviation degree is multiplied by the weight coefficient, and then added to obtain the data deviation degree indexThe index can comprehensively reflect the deviation condition of the power system data in the aspects of environment and electricity utilization.

The formula combines the environmental data deviation degree and the electricity consumption fluctuation deviation degree, and synthesizes the environmental data deviation degree and the electricity consumption fluctuation deviation degree through the weight coefficient, the obtained data deviation degree index can reflect the deviation condition of the power system data on the whole, the limitation of single factor evaluation is avoided, a quantization index is provided for the comprehensive management of the power system, when the data deviation degree index exceeds a certain range, the data is indicated to be possibly abnormal, the manager is prompted to take corresponding measures, and the operation and the maintenance of the power system are optimized.

The specific steps for judging the accuracy of the data are as follows:

Setting a data deviation threshold ;

The data deviation threshold valueThe data bias index in the normal state is calculated by carrying out statistical analysis on the data in the normal state of the same data source, and the normal fluctuation range of the data bias index can be determined. The data deviation index of this interval is averaged as the data deviation threshold。

Data deviation index< Data deviation threshold valueWhen the representative accuracy meets the standard, the data deviation indexNot less than data deviation threshold valueAnd when the representative accuracy does not meet the standard, triggering abnormal early warning of the data accuracy.

Step 204, determining whether to send out an early warning according to the judging results of the integrity, the timeliness and the accuracy:

And when the integrity is judged to be inconsistent with the standard, carrying out data missing early warning, when the timeliness is inconsistent with the standard, carrying out data delay early warning, and when the accuracy is inconsistent with the standard, triggering data accuracy abnormality early warning.

The method has the advantages that the data problems can be found in time through judging the data integrity, timeliness and accuracy, the data loss caused by the fact that the number of the equipment data is inconsistent with that of the corresponding data sets can be prevented, the integrity of a data base is guaranteed, the stable operation of the power system in the timeliness judgment is guaranteed, the timeliness threshold value is reasonably set, the key data of the power system are guaranteed to be updated in time, the power grid faults caused by data delay are avoided, the accuracy of the data reliability is improved according to the data deviation threshold value, the data with overlarge deviation can be filtered, the misjudgment and the potential risk caused by inaccurate data are reduced, and the overall data reliability of the power system is improved.

Step 3, re-acquiring the data when any one of the integrity, the timeliness and the accuracy of the data does not meet the standard, and calculating a predicted environmental impact index according to the environmental monitoring data when the integrity, the timeliness and the accuracy of the data meet the standardCalculating a base operating state index from the base operating state dataCalculating a predicted power load impact index according to the user power consumption data and the historical power dataAccording to the geographical influence indexIndex of environmental impactBasic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated index。

Step 301, re-acquiring data when any one of the integrity, timeliness and accuracy of the data is not in compliance with the standard.

302, Calculating the power space situation predictive index when the integrity, timeliness and accuracy of the data meet the standardsThe method comprises the following specific steps of:

Calculating a predicted environmental impact index The method comprises the following specific steps of:

The environmental monitoring data also includes real-time temperature maxima Real-time temperature minimumMaximum value of real-time humidityReal-time humidity minimumMaximum value of real-time air pressureReal-time air pressure minimumMaximum value of real-time carbon dioxide concentrationReal-time carbon dioxide concentration minimum。

The real-time temperature maximum valueReal-time temperature minimumIs the real-time temperature value detected in the current detection periodMaximum and minimum of (a) real-time humidity maximumReal-time humidity minimumIs the real-time humidity value detected in the current detection periodMaximum and minimum of (a), real-time air pressure maximumReal-time air pressure minimumIs the real-time air pressure detected in the current detection periodMaximum and minimum of (a) and real-time carbon dioxide concentration maximumReal-time carbon dioxide concentration minimumIs the real-time carbon dioxide concentration value detected in the current detection periodAnd the maximum and minimum of (a) are defined.

;

The formula considers the influence of four key environmental factors of temperature, humidity, air pressure and carbon dioxide concentration on the power system, can comprehensively and systematically reflect the comprehensive influence of the environment on the power system, and is obtained through calculationThe value can quantify the potential influence degree of the environment on the power system, so that operation and maintenance personnel of the power system can intuitively know the comprehensive effect of the current environmental factors, further make scientific and reasonable decisions, and the weight coefficient can be adjusted according to actual conditions, so that the formula can adapt to the sensitivity difference of different power systems to each environmental factor, the evaluation accuracy and practicability are improved, and the stable operation of the power system under different environmental conditions is guaranteed.

Calculating a base operating state indexThe specific steps of (a) are as follows:

The base operating state data includes real-time voltage values of the electrical device Real time maximum voltage valueReal-time minimum voltage valueReal-time current valueMaximum current value in real timeReal-time minimum current valueReal-time operating temperature valueReal-time maximum operating temperature valueReal-time minimum operating temperature value。

The real-time voltage value is usedIs usually obtained by a voltage sensor arranged in the power system, and the data acquisition system continuously receives the real-time voltage value transmitted by the voltage sensorBy comparison to obtain the real-time maximum voltage value in unit time periodAnd real-time minimum voltage valueReal-time current valueThe real-time current value of the power equipment in operation is acquired by measuring the current by a current sensorBy comparison to obtain the real-time maximum current value in the unit time periodAnd a real-time minimum current valueReal-time operating temperature valueThe method is obtained by measuring a temperature sensor arranged on the power equipment, and the real-time operation temperature value of the power equipment in a unit time period is acquiredBy comparison, a real-time maximum operating temperature value within the week is obtainedAnd a real-time minimum operating temperature value。

Setting rated voltage valueRated current valueRated operating temperature value。

Rated voltage valueRated current valueRated operating temperature valueIs determined based on the power distribution criteria of the power system.

;

Wherein, Representing the power factor, the value is 0<≤1;Representative voltage valueThe weight coefficient of (2) is 0.2-less≤0.4,Representative current valueThe weight coefficient of (2) is 0.1<≤0.3,Representing power factorThe weight coefficient of (2) is 0.1-0≤0.3,Representing the operating temperature valueThe weight coefficient of (2) is 0.3-0Is less than or equal to 0.5, and。

The power factor is thatThe ratio of active power to apparent power in the alternating current circuit reflects the effective utilization degree of the power supply power, and the value range of the ratio is between 0 and 1. When the power factor is equal to 1, the voltage and the current are the same in phase, only active power is used in the circuit, and the power supply energy is fully utilized by the load, while the lower the power factor is, the larger the proportion of reactive power is, the larger the proportion is used for periodic exchange between the power supply and the energy storage element, the real work is not consumed by the load, the electric energy utilization efficiency is low, and the electric energy can be directly obtained through the power factor meter.

It should be noted that the number of the substrates,Representing the relative deviation of the real-time voltage relative to the rated voltage in the voltage fluctuation range, multiplying the relative deviation by the weight coefficientRepresenting the contribution of the voltage factor to the base operating state index; Is the relative deviation of current, multiplied by the weight coefficient Representing the contribution of the current factor to the base operating state index; Directly reflects the influence of the power factor on the running state, and multiplies the power factor by the weight coefficient Representing the contribution of the power factor to the base operating state index; is equivalent temperature relative deviation multiplied by weight coefficient Representing the contribution of the equivalent temperature factor to the base operating state index. Finally, the four items are added to obtain a basic running state indexThis index quantifies the operating state of the electrical device by comprehensively considering the relative deviation of the plurality of operating factors, in combination with the respective weight coefficients.

The formula comprehensively considers key operation parameters such as voltage, current, power factor, equivalent temperature and the like, and can comprehensively reflect the operation state of the power equipment by comparing the key operation parameters with the rated value and combining the weight coefficient,The running health degree of the equipment can be quantified by the value, so that operation and maintenance personnel can intuitively know the current state of the equipment, potential problems can be found timely, the weight of each parameter can be adjusted according to actual conditions, a formula can adapt to the sensitivity difference of different equipment to each parameter, the evaluation accuracy is improved, the stable running of a power system is guaranteed, and the occurrence of faults is reduced.

Calculating a predicted electrical load impact indexThe specific steps of (a) are as follows:

The user electricity consumption data also comprises electricity consumption at peak time Electricity consumption during low electricity consumption。

It should be noted that the smart meter records the electricity consumption of each period when the period ends, and in this way, the electricity consumption at the peak time can be directly obtainedElectricity consumption during low electricity consumption。

According to the real-time average power consumptionElectricity consumption at peak timeElectricity consumption during electricity consumption valleyPeak for calculation Gu ChalvThe specific formula is as follows:

。

The historical power data also includes the power consumption of the previous period 。

According to the real-time electricity consumptionPower consumption in upper periodCalculating a load increase rateThe specific formula is as follows:

;

Wherein, Representing the period, and taking the value as a positive number.

Real-time electricity consumption according to current detection periodElectricity consumption at peak timePeak power supply Gu ChalvLoad increase rateAverage electricity consumptionCalculating a predicted electrical load impact indexThe specific formula is as follows:

;

It should be noted that the number of the substrates,Representing the average of the relative deviation of a plurality of real-time power consumption relative to the average power consumption in the power consumption range of the peak power consumption, and multiplying the average power consumption by a weight coefficientObtain the contribution of the real-time electricity consumption factors to the predicted electric load influence index,The contribution of the load increase rate factor to the predicted electrical load impact index is obtained,Obtaining the contribution of the power consumption peak Gu Chalv factor to the predicted electric load influence index, and finally adding the three factors to obtain the predicted electric load influence indexThis index quantifies the extent of the impact of the electrical load by comprehensively considering the relative deviation of the plurality of electrical load related factors in combination with the respective weight coefficients.

The formula comprehensively considers the factors such as real-time electricity consumption, electricity consumption peak Gu Chalv, load growth rate and the like, and can comprehensively reflect the comprehensive influence of the electric load by combining the relative deviation and the weight coefficient; The value can quantify the influence degree of the electric load on the system, so that operation and maintenance personnel of the electric system can intuitively know the current load condition, find potential problems in time, provide reference basis for power dispatching and equipment maintenance, adjust each parameter weight according to actual conditions, enable a formula to adapt to the sensitivity difference of different electric systems to each parameter, improve evaluation accuracy and ensure stable operation of the electric system.

Calculating a predicted power space complex indexThe specific steps of (a) are as follows:

;

Wherein, Is a constant term.

The formula is used for calculating the predicted power space comprehensive indexComprehensively consider the environmental impact indexBasic running state indexAnd an electrical load impact indexThree factors affect the state of the power system.

It should be noted that the number of the substrates,The sum of squares of the three exponentials is averaged.Is divided by adding three exponentsThe result of (2) takes the sine value divided byIn order to limit the results to a certain range,The value can beThe sine function here is to introduce a non-linear factor to more fully reflect the result of the three exponential synthesis.

Finally, taking square root after adding the two parts to obtain the predicted power space comprehensive indexThis index quantifies the overall state of the power system by taking into account the sum of squares, averages, and nonlinear sinusoidal functional relationships of a number of factors.

The formula fuses the environmental impact indexBasic running state indexAnd an electrical load impact indexThe comprehensive influence of the power system by the environment, the self running state and the load condition is comprehensively reflected, the unilateral performance of single factor evaluation is avoided, the interaction relation among the factors can be captured by introducing a sine function to perform nonlinear processing, the comprehensive index can more accurately reflect the actual state of the power system, a more reliable basis is provided for the evaluation of the running state of the system, and the obtained result isThe value can be used as an intuitive comprehensive index, so that operation and maintenance personnel of the power system can conveniently and quickly know the overall operation condition of the system, discover potential problems in time, make reasonable operation and scheduling decisions and guarantee the stable operation of the power system.

Step 4, setting a power space situation pre-estimation index threshold valueEstimating an index according to the state of the power spaceAnd power space situation predictive index thresholdAnd judging whether to trigger the power space abnormality alarm information or not, and generating a corresponding evaluation report and an adjustment scheme.

Step 401, setting power space situation pre-estimation index thresholdPower space situation predictive index thresholdIncludes a first level thresholdSecond order thresholdAnd a three-level threshold, wherein,<;

It should be noted that, through statistical analysis of long-term historical operation data of the power system, under the normal and stable operation state of the system, the power space situation estimates the indexFalls within a relatively stable interval, the upper limit of which is set as a first level thresholdStatistics are made on small load fluctuations that occur historically, slight degradation in device performance due to local environmental changes, etc., and when these events occur,Will rise to a certain degree, and make statistics and analysis to determine the secondary thresholdStatistics are carried out on large-area power failure, serious equipment damage and the like which occur historically, before serious faults occur,There is generally a significant upward trend through the use of a solution to these pre-failuresAnalysis of the values, determination of the tertiary threshold。

Step 402, judging whether to trigger the power space risk alarm information, and generating a corresponding evaluation report and adjustment scheme, wherein the specific steps are as follows:

when the power space situation is estimated to be exponential ≤When the power space abnormality alarm information is not triggered;

When (when) < Power space situation prediction index >≤And triggering first-level power abnormality risk alarm information to generate a primary regulation instruction and a risk assessment report.

When the primary alarm is triggered, the power system has a certain degree of abnormality, but the abnormality degree is relatively light, and the system can be self-regulated within a certain range.

The primary regulating instruction is to perform primary regulation aiming at the current slight abnormal state of the system. For example, load adjustments to local equipment, fine adjustments to environmental control parameters, etc., in order to restore the system to a normal operating state. The risk assessment report mainly focuses on the analysis of the current abnormal situation, and the report content includes the investigation of possible factors causing the abnormality, such as whether the load of a certain area is slightly increased, the small amplitude of the change of the environmental parameters, etc. At the same time, the further influence of these factors on the system is estimated, and a preliminary coping strategy is proposed.

When (when)< Power space situation prediction index >And triggering the secondary power space abnormality alarm information to generate a medium-level adjustment instruction and a risk assessment report.

When the secondary alarm is triggered, the abnormal condition of the power system is serious, and the abnormal condition exceeds the range that the system can be regulated easily and requires deeper intervention. The medium level adjustment instructions involve the integrated adjustment of the various parts of the system. For example, it is necessary to redistribute the load of a part of the transmission line, greatly adjust the operation parameters of the related devices, start the standby devices to share the load, and so on, so as to ensure that the system can be restored to be stable. The report content includes a root cause analysis of the current severe anomalies, such as whether they are due to a combination of factors, such as equipment aging plus environmental degradation, etc. Meanwhile, the risk possibly faced by the system in the current abnormal state is comprehensively evaluated, including the evaluation of equipment damage risk, power failure risk and the like, and a corresponding comprehensive coping strategy is provided.

When (when)< Power space situation prediction index >And triggering three-level power space abnormality alarm information to generate an advanced regulation instruction and a risk assessment report.

When triggering the three-level alarm, the power system is in a very dangerous state, and serious faults such as large-area power failure, serious equipment damage and the like are very likely to occur.

The advanced regulation command relates to emergency regulation and control of the whole power system, for example, temporary change of the topology structure of the power grid, emergency shutdown or switching operation of equipment, calling of an external emergency power supply and the like, so as to minimize loss caused by faults. The evaluation report content comprises detailed analysis of the current extremely dangerous state, such as the investigation of all factors causing the system to be endangered to collapse, including equipment faults, extreme environmental conditions, serious unbalance of loads and the like, and meanwhile, the evaluation report content can accurately evaluate the possible consequences caused by the serious faults, such as the power failure range, the power failure time, the influence on users and society and the like, and provides coping strategies, including the starting of emergency plans, the formulation of emergency repair schemes and the like.

Referring to fig. 3, the present invention provides an electric power space data auditing management system, including:

The data acquisition module is used for counting the actual number of the power equipment covered by the power system Collecting data sets of the areas where each power device is located, and counting the actual number of the data setsThe data set includes environmental monitoring data, base operating state data, consumer electricity data, and historical electricity data.

The data detection module is used for detecting the actual quantity of the power equipmentAnd the actual number of data setsComparing, judging whether the integrity of the data accords with the standard or not, and collecting the time stamp through the data setAnd receiving a time stampCalculating a time differenceBy time differenceAnd a time-efficiency thresholdComparing, judging whether the timeliness of the data meets the standard, calculating the deviation degree of the environmental data according to the environmental monitoring dataCalculating the fluctuation deviation degree of the electricity consumption according to the electricity consumption data of the userAccording to the deviation degree of the environmental dataAnd the degree of deviation of fluctuation of electricity consumptionCalculating a data deviation indexPresetting a data deviation thresholdIndex the data deviation degreeThreshold value of deviation from dataAnd determining whether to send out early warning according to the judging results of the integrity, the timeliness and the accuracy.

The data analysis module is used for re-acquiring the data when any one of the integrity, the timeliness and the accuracy of the data is out of the standards, and calculating and predicting an environmental impact index according to the environmental monitoring data when the integrity, the timeliness and the accuracy of the data are out of the standardsCalculating a base operating state index from the base operating state dataCalculating a predicted power load impact index according to the user power consumption data and the historical power dataAccording to the environmental impact indexBasic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated index。

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of 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.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.

Claims

1. The electric power space data auditing management method is characterized by comprising the following steps:

re-acquiring the data when any one of the integrity, timeliness and accuracy of the data is not in accordance with the standard, calculating a predictive environmental impact index from the environmental monitoring data when the integrity, timeliness and accuracy of the data are in accordance with the standard Calculating a base operating state index from the base operating state dataCalculating a predicted power load impact index according to the user power consumption data and the historical power dataIndex of environmental impactBasic running state indexIndex of electrical load impactCalculating the power space situation pre-estimated index;

2. The method for auditing and managing power space data according to claim 1, wherein:

Calculating a time difference The specific method of (a) is as follows:

。

3. The method for auditing and managing power space data according to claim 2, wherein the degree of deviation of the environmental data is calculated Degree of deviation of fluctuation of electricity consumptionAnd data bias indexThe method of (1) is as follows:

;

Calculating a data deviation index The specific method of (a) is as follows:

;

4. The method for auditing and managing power space data according to claim 3, wherein the specific method for determining whether to send out the early warning according to the judging result of the integrity, the timeliness and the accuracy is as follows:

The method for judging the data integrity comprises the following steps:

the specific steps for judging the accuracy of the data are as follows:

5. The method for auditing and managing power space data according to claim 4, wherein the predicted environmental impact index is calculatedThe specific steps of (a) are as follows:

;

6. The method for auditing and managing power space data according to claim 5, wherein the basic operation state index is calculatedThe specific steps of (a) are as follows:

;

Wherein, Representing the power factor, taking the value as;Representative voltage valueThe weight coefficient of (2) is 0.2-less≤0.4,Representative current valueThe weight coefficient of (2) is 0.1<≤0.3,Representing power factorThe weight coefficient of (2) is 0.1-0≤0.3,Representing the operating temperature valueThe weight coefficient of (2) is 0.3-0Is less than or equal to 0.5, and。

7. The method for audit management of electrical space data according to claim 6 wherein the predictive electrical load impact index is calculatedThe specific steps of (a) are as follows:

;

8. The method for auditing and managing power space data according to claim 7, wherein the calculation of the predicted power space comprehensive index is performedThe specific steps of (a) are as follows:

;

Wherein, Is a constant term.

9. The method for auditing and managing power space data according to claim 8, wherein the specific steps of judging whether to trigger power space risk alarm information and generating a corresponding evaluation report and adjustment scheme are as follows:

10. An electric power space data auditing management system is characterized by comprising: