CN105067904B - A kind of Lightning Warning data assessment method based on history lighting location data and power network Tripping data - Google Patents
A kind of Lightning Warning data assessment method based on history lighting location data and power network Tripping data Download PDFInfo
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Abstract
A kind of Lightning Warning data assessment method based on history lighting location data and power network Tripping data, Tripping data is obtained from power supply administration, mesh generation is carried out to Tripping data, so that it is determined that Tripping matrix；Lighting location data are obtained from lightning location system, corresponding Tripping matrix intercepts out the lighting location data of this area and makes lighting location matrix, and comparative analysis Tripping matrix and lighting location matrix obtain minimum trip current value；Correlation analysis is carried out by history Lightning Warning data and history lighting location data, the history Lightning Warning data early warning degree of accuracy can be obtained；When Lightning Warning is issued, Lightning Warning matrix, minimum trip current value and the early warning degree of accuracy just can be combined, tripping operation rate matrix is finally given, so as to realize a kind of assessment to history Lightning Warning data result.
Description
Technical Field
The invention relates to the technical field of lightning early warning, in particular to a lightning early warning evaluation method for realizing early warning by researching the correlation between historical post setting data and power grid tripping data.
Background
With the continuous development of power grids, the proportion of lightning accidents of power transmission lines, equipment and towers is continuously increased, and the traditional monitoring and early warning mode and management means cannot meet the requirements of reasonable planning, scientific management and high-quality service. While the development is achieved, the processing and statistics of the lightning disaster information also have certain problems, which are specifically shown in the following aspects. Such as: the lightning forecast data is not issued in time; the geographic position of the lightning forecast data is inaccurate; and the lightning stroke accident is not reported in time. The problems cause great difficulty in safe operation and maintenance of the power grid, and the operation and maintenance cost is high; on the other hand, the further rational planning and construction of the transmission line and the equipment are also influenced.
Thunder is a main factor causing tripping of a Yunnan power transmission line, and serves as a main supporter for 'west-east power transmission' and 'cloud-power transmission', safe and stable operation of a Yunnan power grid has a positive promoting effect on a clean energy transmission target of the province, and higher requirements are provided for thunder monitoring and protecting capacity of the Yunnan power grid. Compared with the traditional lightning protection technology, the lightning early warning is a necessary technology for realizing active defense of the power grid lightning damage, and can be used for making scheduling and emergency plans in advance according to early warning information before thunderstorm arrives, reasonably configuring the working states of a power transmission line, a transformer substation and a power plant, guaranteeing the safety of the power grid and reducing the economic loss brought to users due to power failure.
Disclosure of Invention
The purpose of the invention is: aiming at a power transmission line of a power grid system, an evaluation method based on historical lightning location and power grid tripping data relevance research is provided. The accuracy of the prediction of the historical thunder and lightning in the area can be obtained by researching the historical thunder and lightning location data; when lightning early warning is issued, the trip-out rate of the area when lightning occurs can be calculated by combining historical trip-out data and historical lightning prediction accuracy, so that the lightning early warning data can be evaluated.
The technical solution of the invention comprises the following steps:
step 1: acquiring power grid fault historical data caused by lightning disasters from a power supply bureau, extracting historical trip records in the power grid fault historical data, and carrying out grid division on historical trip towers to obtain trip matrixes A of all time periods;
and 2, step: acquiring historical lightning positioning data through a lightning positioning system server, extracting the lightning positioning data of the corresponding trip matrix part, and generating a corresponding lightning positioning matrix B;
and 3, step 3: comparing the lightning location matrix with the trip matrix to obtain the lowest current value X causing trip in the area;
and 4, step 4: acquiring lightning early warning data from a meteorological bureau, intercepting and manufacturing a lightning early warning matrix C of the area according to a trip matrix;
and 5: acquiring historical lightning early warning data of the area through meteorological bureau data, acquiring historical lightning positioning data of the area through a lightning positioning system, comparing the data, and analyzing to obtain the reporting pair times Na, the missing reporting times Nb and the empty reporting times Nc; analyzing and predicting accuracy according to the historical lightning positioning data and the historical lightning early warning data of the area, and calculating a predicted accuracy TS by a TS scoring method; the prediction accuracy is calculated as follows:
and calculating the average value of the prediction accuracy
And 6: dividing the current value of each point in the lightning early warning matrix by the minimum current value X and simultaneously multiplying the average value of the prediction accuracyAnd finally obtaining a matrix diagram D of the tripping occurrence rate of the matrix in the lightning early warning area. Finally, the tripping occurrence rate of each tower in the area can be determined according to the towers in the power grid. The trip occurrence rate is calculated as follows:
the invention has the advantages that:
1. in the assessment method, historical lightning location data are called for analysis, the accuracy of historical lightning early warning is obtained, and meanwhile, average value calculation is carried out, so that the accuracy can be controlled in a reasonable range.
2. The method combines a trip data part in the power grid system, and finally obtains the prediction of the trip rate by researching the relationship between trip and thunder, and the method is more suitable for the power grid system.
Drawings
FIG. 1 is a general flow diagram of the process of the present invention;
Detailed Description
The invention relates to a general flow chart of a lightning early warning data evaluation method based on historical lightning positioning data and power grid tripping data. The method is characterized in that: by calling historical lightning location data, the early warning accuracy of the lightning early warning data in a region within a period of time can be calculated. And extracting tripping data in the power grid historical fault data provided by a power supply bureau, and extracting the minimum current value at the moment of lightning disaster. And (4) combining the lightning early warning data, the minimum current value and the historical early warning accuracy average value to obtain the equipment trip-out rate of the early warning area, and taking the equipment trip-out rate as an evaluation mode of the lightning early warning in the area. The flow chart is shown in fig. 1.
1) Firstly, acquiring historical data of power grid faults caused by lightning disasters from a power supply bureau, screening records of trip parts in the historical data, and dividing the records into trip records of each lightning disaster occurrence moment; then, grid division is carried out on the tripping equipment at the occurrence moment of each thunder and lightning disaster, and a tripping matrix A of each disaster time period can be obtained;
2) Historical lightning positioning data can be obtained through the lightning positioning system server, and according to the trip matrix A, lightning positioning data of each disaster time period in the lightning positioning system can also be obtained and extracted to manufacture a corresponding lightning positioning matrix B;
3) Then, performing correlation analysis on the trip matrix A and the lightning positioning matrix B, obtaining current intensity data of each trip point correspondingly, and screening the data to obtain the minimum current intensity X of equipment trip caused in the current lightning disaster;
4) Then, when the lightning early warning is issued, the lightning early warning data can be obtained from a meteorological bureau; according to the trip matrix A, lightning early warning data of a corresponding area can be extracted, and a corresponding lightning early warning current intensity matrix chart C is manufactured;
5) In order to obtain the prediction accuracy of the historical lightning early warning data, the historical lightning early warning data of the area needs to be extracted from a meteorological office, and the reporting times Na, the missing reporting times Nb and the empty reporting times Nc in the historical lightning positioning data are obtained through analysis corresponding to the historical lightning positioning data obtained before; analyzing and predicting accuracy according to the historical lightning positioning data and the historical lightning early warning data of the area, and calculating a predicted accuracy TS by a TS scoring method; the calculation formula of the prediction accuracy TS is as follows:
in the obtained prediction accuracies TS, the average value thereof needs to be extracted as a reference, and therefore, when the number of prediction accuracies is calculated&2, the minimum value and the maximum value are removed and then the average value is calculated, thus obtaining a more accurate average prediction accuracy
6) Finally, the equipment trip-out rate of the area is obtained, and the current value of each point in the lightning early warning matrix C is divided by the lowest current valueX is simultaneously multiplied by the average of the prediction accuracyFinally obtaining a matrix diagram D of the tripping occurrence rate of which the matrix is a lightning early warning area; and determining the tripping occurrence rate of each tower device in the area by combining the tripping matrix D according to the tower devices in the power grid and the like. The trip occurrence rate is calculated as follows:
and finally, the evaluation of the historical lightning early warning data result is realized through the trip rate matrix.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
Firstly, intercepting trip data of a time point and making the trip data into a trip matrix A
Historical trip matrix A
Where 1 represents the location of the equipment where the trip occurred.
Secondly, extracting lightning location data at corresponding moments from the lightning location system, and making corresponding lightning location current value matrixes B
Lightning location current value matrix B
Comparing and analyzing the A, B matrix, the current value which causes the equipment to trip can be obtained, and the minimum value is 56.8.
Secondly, the early warning accuracy of the early warning data of the region needs to be calculated, and the data table is as follows:
TABLE 2 early warning data sheet
The average prediction accuracy can be obtained by calculation
Acquiring lightning early warning data of the area and manufacturing a lightning early warning matrix C
Thunder and lightning early warning matrix C
After comparative analysis, a trip rate matrix D is finally obtained
Trip rate matrix D
Claims (1)
1. A lightning early warning data evaluation method based on historical lightning location data and power grid trip data is characterized by comprising the following steps:
step 1: acquiring power grid fault historical data caused by lightning disasters from a power supply bureau, extracting historical trip records in the power grid fault historical data, and carrying out grid division on historical trip towers to obtain trip matrixes A of all time periods;
step 2: acquiring historical lightning positioning data through a lightning positioning system server, extracting the lightning positioning data of the corresponding trip matrix part, and generating a corresponding lightning positioning matrix B;
and step 3: comparing the lightning location matrix with the trip matrix to obtain the lowest current value X causing trip in a certain area;
and 4, step 4: acquiring lightning early warning data from a meteorological bureau, intercepting and manufacturing a lightning early warning matrix C of the area according to a trip matrix;
and 5: acquiring historical lightning early warning data of the area through meteorological bureau data, acquiring historical lightning positioning data of the area through a lightning positioning system, comparing the data, and analyzing to obtain the reporting pair times Na, the missing reporting times Nb and the empty reporting times Nc; analyzing and predicting accuracy according to the historical lightning positioning data and the historical lightning early warning data of the area, and calculating a predicted accuracy TS by a TS scoring method; the prediction accuracy is calculated as follows:
and calculating the average value of the prediction accuracy
Step 6: dividing the current value of each point in the lightning early warning matrix by the minimum current value X and simultaneously multiplying the average value of the prediction accuracyFinally obtaining a matrix diagram D of the tripping occurrence rate of which the matrix is a lightning early warning area; finally, according to the towers in the power grid, the tripping occurrence rate of each tower in the area can be determined, and the tripping occurrence rate is calculated in the following mode:
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| CN107782954B (en) * | 2017-09-29 | 2019-03-22 | 海南电网有限责任公司电力科学研究院 | A kind of transformer overvoltage method for early warning based on a large amount of overvoltage number data |
| CN112540235B (en) * | 2019-09-20 | 2023-02-17 | 中国石油化工股份有限公司 | Method and system for correcting lightning early warning threshold value and early warning evaluation method and system |
| CN111537827A (en) * | 2020-05-28 | 2020-08-14 | 武汉汉宁电力设计咨询有限责任公司 | Online safety and stability analysis system for power grid |
| CN113449913B (en) * | 2021-06-25 | 2022-10-28 | 上海电机学院 | Rail transit line tripping intelligent early warning system based on SCADA |
| CN116031847B (en) * | 2023-02-14 | 2023-12-12 | 安徽凯民电力技术有限公司 | Electric power system firewall device based on short-circuit fault rapid detection and positioning |
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