CN116739185B - Real-time lightning area prediction and line early warning method and system based on lightning energy - Google Patents
Real-time lightning area prediction and line early warning method and system based on lightning energy Download PDFInfo
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Abstract
一种基于雷电能量的实时雷电区域预测和线路预警方法，包括：步骤1：获取待预测地区的雷电信息；步骤2：对从步骤1获取的雷电信息进行预处理，得到预处理后的雷电信息；步骤3：对从步骤2获取的预处理后的雷电信息基于空间网格划分得到各网格雷电数据；步骤4：根据步骤3得到的各网格雷电数据进行雷击区域预测和各网格雷电能量估算值；步骤5：根据步骤4的预测结果对各网格的电网线路实时预警。本发明仅通过探测最近的雷电数据就能够实现准确的雷电预测，无需采集大量种类的数据，同时通过合理的区域网格划分和时间量设置，能够对线路实现更准确的预警，并给工作人员预留足够的调控时间对电力设备进行调控。
A real-time lightning area prediction and line warning method based on lightning energy, including: Step 1: Obtain lightning information in the area to be predicted; Step 2: Preprocess the lightning information obtained from Step 1 to obtain preprocessed lightning information ; Step 3: Based on the spatial grid division of the preprocessed lightning information obtained from step 2, obtain the lightning data of each grid; Step 4: Predict the lightning strike area and predict the lightning of each grid based on the gray lightning data of each grid obtained in step 3. Energy estimation value; Step 5: Real-time warning for the power grid lines of each grid based on the prediction results of Step 4. This invention can achieve accurate lightning predictions only by detecting recent lightning data without collecting a large number of types of data. At the same time, through reasonable regional grid division and time setting, it can achieve more accurate early warning for lines and provide workers with Reserve sufficient control time to control power equipment.
Description
Technical Field
The invention belongs to the technical field of lightning stroke prediction, and particularly relates to a lightning area prediction and line early warning method and system based on lightning energy.
Background
At present, the climate change trend is obvious, the global land mine electric activity is continuously increased, and the global land mine electric activity is a great natural factor for endangering the safety of a power grid. The former research generally has two methods, namely, the motion trend of thundercloud is predicted based on the thought of clustering, the method cannot refine the lightning area and the area early warning level, a large number of invalid early warning can be caused, and in addition, satellite data required by the method is not easy to obtain; secondly, the lightning activity is predicted by machine learning of meteorological elements, but the prediction effect depends on the quality of a data set, the prediction result cannot be interpreted theoretically, and in addition, meteorological element data are not easy to obtain. The method is based on the lightning detection device, the region to be predicted is gridded, effective early warning can be carried out on the line only through a real-time lightning data combination algorithm, and the time advance of 30 minutes is enough for workers to carry out grid regulation. The prediction coverage means the ratio of the number of successfully predicted grids to the number of grids in which lightning strokes actually occur, and the prediction success rate means the ratio of the number of successfully predicted grids to the number of predicted grids. Under the condition that detection data are sufficient, the prediction coverage rate of the lightning area can reach 80%, the prediction success rate can reach 70%, and the reason why the effective prediction is not achieved is that one thundercloud is performed and the other thundercloud is just formed at the same time, so that the activity of the remote thundercloud cannot be predicted based on the existing lightning data; secondly, in the detection edge area, the invention predicts that lightning stroke occurs and actually does occur, but the calculated prediction effect is reduced because the lightning stroke data cannot be detected by the detector due to the too far distance. In the invention, the absolute value of the difference between the estimated energy of grid lightning and the actual energy of lightning is not more than 50, which guarantees the reliability of the early warning level of regional lines.
The prior patent 1 (CN 109738970B) discloses a method, a device and a storage medium for realizing lightning early warning based on lightning data mining, wherein the method comprises the following steps: s10, analyzing the intensity of an atmospheric electric field and radar echo, and starting a lightning early warning process when preset conditions are met; s20, collecting satellite cloud image data and lightning positioning data, combining the satellite cloud image data and the lightning positioning data, distinguishing and correcting, and performing cluster analysis on the lightning data to obtain the moving speed and direction of the thunderstorm cluster; s30, according to the currently obtained thunderstorm cluster distribution, calculating the moving speed and direction of the thunderstorm cluster by adopting a linear regression method, and predicting the occurrence position and quantity of thunder and lightning at the next moment; and S40, dividing the area into different grids, and carrying out lightning early warning of corresponding levels according to the predicted radar positions and the number. Technical drawbacks of prior patent 1 include: the grid area is not sufficiently refined, and the grid division size in the prior patent 1 is 625 km 2 A large number of power equipment can exist in each grid, so that a large number of invalid early warning is caused; in the prior art, lightning prediction is carried out by multi-source data, including atmospheric electric field intensity, radar echo, satellite cloud image data and lightning positioning data, and the data are various and are difficult to realize in practice.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a real-time lightning stroke area trend prediction method and a real-time lightning stroke area trend prediction system, which can predict a lightning stroke area at a preset time point in the future through real-time lightning data.
The invention adopts the following technical scheme.
A real-time lightning area prediction and line early warning method based on lightning energy comprises the following steps:
step 1: acquiring lightning information of a region to be predicted;
step 2: preprocessing the lightning information obtained from the step 1 to obtain preprocessed lightning information;
step 3: dividing the preprocessed lightning information obtained from the step 2 based on space grids to obtain lightning data of each grid;
step 4: carrying out lightning stroke area prediction and each grid lightning energy estimation value according to each grid lightning data obtained in the step 3;
step 5: and (3) early warning the grid lines of the grids in real time according to the prediction result of the step (4).
Preferably, the step 1 of acquiring real-time lightning information includes the following steps:
step 1.1: detecting lightning information of a region to be predicted by a lightning detection device, comprising: latitude and longitude of a lightning strike point, lightning strike time and lightning strike amplitude, wherein the lightning strike time comprises: year, month, day, hour, minute, second, microsecond;
Step 1.2: and reading the detected lightning information to a data processing platform.
Preferably, the preprocessing of the real-time lightning information in the step 2 includes the following steps:
step 2.1, dividing the lightning information read in the step 1 according to the date, and extracting the lightning information of the current day;
step 2.2, extracting the hours and minutes of the lightning strike in the lightning strike information of the current day, and calculating the distribution position of the lightning strike moment in one day by taking the minutes as a basic unitmin：
In the method, in the process of the invention,hfor the time of the hours in which the lightning strike occurs,mis the minute time for a lightning strike to occur.
Preferably, the step 3 of obtaining each grid lightning data based on space grid division of the preprocessed lightning information includes the following steps:
step 3.1, gridding the area to be predicted at set intervals in the longitudinal direction and the latitudinal direction;
step 3.2, according to the distribution position of the lightning strike time in one day obtained in the step 2.2, acquiring lightning data of 60 minutes of last continuous time, setting a time span period, and dividing the acquired lightning data into two groups of data of a k-1 period and a k period;
and 3.3, dividing the two groups of lightning data into corresponding grids according to the longitude and latitude of lightning stroke according to the grid division obtained in the step 3.1 and the two groups of lightning data obtained in the step 3.2, and obtaining the lightning data of each grid in the k-1 time period and the k time period.
Preferably, in the step 3.1, the longitudinal direction and the latitudinal direction are each meshed at intervals of 0.05 °;
in the step 3.2, the set time span period is 30 minutes.
Preferably, predicting the lightning strike area of the k+1 period and estimating each net gray electrical energy of the k+1 period in step 4 includes the steps of:
step 4.1, further subdividing each grid lightning data of the k-1 time period and the k time period obtained in the step 3.3 with a time interval of 10 minutes to obtain each grid lightning data of 4 time periods in total, wherein the method comprises the following steps: k-1 period, k-2/3 period, k-1/3 period, and k period;
step 4.2, according to the 4 time-interval grid lightning data obtained in step 4.1, respectively calculating 4 time-interval lightning energy to obtain k-1 time-interval lightning energy_total k-1 Total energy of lightning in k-2/3 period k-2/3 Total energy of lightning in k-1/3 period k-1/3 Energy_total of k-period lightning energy k And screening out time intervals meeting the conditionsThe total energy of the lightning in each period is calculated as follows:
where total is the total number of lightning strikes in the time period, including 4 time periods,A i an equivalent amplitude for each lightning strike during the time period;
Step 4.3, respectively calculating the total energy of lightning of each grid in k-1/3 time periods and k time periods according to the lightning data of each grid in 4 time periods obtained in the step 4.1;
according to the total energy of lightning in each grid of k-1/3 time period and k time period, obtaining the energy state of the two time periods k-1/3 And state k The state expression is as follows:
in the method, in the process of the invention,energy st grid lightning energy representing the s th grid in the longitude direction and the t th grid in the latitude direction;
step 4.4, estimating and obtaining the total energy energy_total of the k+1 time period according to the total energy value of the lightning, which satisfies the condition, of the latest continuous time period obtained in the step 4.2 k+1 ；
Step 4.5, energy State of k-1/3 period and k period obtained according to step 4.3 k-1/3 And state k Predicting a lightning stroke area of a k+1 period;
step 4.6, the total energy of the lightning in the k+1 period of time obtained in the step 4.4 is energy_total k+1 And 4.5, predicting the energy state of the k+1 time period in the lightning stroke area of the k+1 time period k+1 。
Preferably, in the step 4.2, screening the lightning total energy of the time interval meeting the condition comprises the following substeps:
step 4.2.1, setting a total energy list list_e and a time list list_x, and initializing the two lists to be empty lists;
step 4.2.2, respectively calculating total energy_total of 4 time intervals of lightning;
Step 4.2.3, if the total energy of the lightning corresponding to a certain period is greater than 0, adding the total energy of the lightning corresponding to the certain period to list_e, adding the starting time point of computing the total energy to list_x, wherein the time point is calculated in step 2.2min；
Step 4.2.4, if the energy_total corresponding to a certain period is equal to 0, resetting list_e and list_x to be empty lists, and returning to step 3.2.
Preferably, in the step 4.4, the lightning energy energy_total of the k+1 period is estimated by the lightning energy value satisfying the condition in the last continuous period k+1 Comprising the following substeps:
step 4.4.1, if the number of the elements of the total energy list list_e and the time list list_x obtained in step 4.2 is greater than or equal to 3, using the elements of the list_x as independent variablesxList_e is a dependent variableyFitting to obtain a functional formula of the time list list_e relative to the total energy list list_x;
step 4.4.2, if the goodness-of-fit coefficient R of the fitting function in step 4.4.1 2 Less than 60%, the next prediction is not performed, and the step 3.2 is returned;
step 4.4.3, if the goodness-of-fit coefficient R of the fitting function in step 4.4.1 2 60% or more, and estimating total energy of lightning in the k+1 period k+1 The formula is as follows:
In the method, in the process of the invention,x k+1 a, b and c are parameters obtained by fitting in the step 4.4.1 for the starting time point of the k+1 period;
step 4.4.4. If the number of elements of the list list_e and list_x obtained in step 4.4 is less than 3, the following prediction is not performed, and the process returns to step 3.2.
Preferably, in the step 4.4.1, during formation of the thundercloud, the total energy of lightning_total in the continuous period starts from 0, increases sharply and then decreases sharply, so as to calculate that the starting time point of the total energy of lightning_total is an x-axis independent variable, the energy_total is a y-axis dependent variable, and the fitted function is a parabolic equation or a one-time equation with a downward opening, where the equation is as follows:
wherein a, b, c are parameters of a parabolic equation, and the value range of a isWhen a is 0, the equation is a once equation.
Preferably, the energy state in the step 4.5 is obtained through the k-1/3 period and the k period k-1/3 And state k Predicting a lightning strike area for a k+1 period, comprising the sub-steps of:
step 4.5.1, calculating a difference matrix state_change of the energy states of the k period and the k-1/3 period, wherein the difference matrix state_change of the energy states of the k period and the k-1/3 period is as follows:
step 4.5.2, not considering two circles of grids at the outermost periphery, traversing all other grids, and selecting grids which are adjacent to each other in the left-right direction, namely, s-2 rows to s+2 rows and j-2 columns to j+2 columns, each time, to obtain a difference matrix state_change1 of the 25 grids as follows:
Step 4.5.3, setting a longitude positive direction list x 1 List x of negative directions of longitude 2 List y of latitude positive directions 1 Latitude negative direction list y 2 The initial lists are empty lists;
step 4.5.4, traversing all elements of state_Change1, setting a threshold, and adding m to x if the value of grid (m, n) is above the threshold 1 Adding n to y 1 The method comprises the steps of carrying out a first treatment on the surface of the If the value of grid (m, n) is less than the threshold value, then add m to x 2 Adding n to y 2 ；
Step 4.5.5, x obtained according to step 4.5.4 1 ，x 2 ，y 1 ，y 2 Respectively calculating the relative position x of the increase and decrease of the lightning energy 1c ，x 2c ，y 1c ，y 2c Wherein x is 1c And x 2c Indicating the relative position of the increase or decrease in longitudinal direction of the lightning energy, y 1c And y 2c The calculation formula for the relative position of the increase and decrease of the lightning energy in the latitude direction is as follows:
in the formula, sum functions represent elements for solving the list, and len functions represent the number of the elements for solving the list;
step 4.5.6, x obtained according to step 4.5.5 1c ，x 2c ，y 1c ，y 2c To predict the relative direction vector of the grid (s, j) thundercloud movement in step 4.5.2f。
Preferably, in the step 4.5.4, the grid size and the lightning energy change speed are comprehensively considered, the threshold 200 is set, if the grid lightning energy change does not exceed 200 within 10 minutes, the lightning cloud movement of the grid is considered to be insignificant, and if the grid lightning energy change exceeds 200 within 10 minutes, the step goes to the step 4.5.5.
Preferably, in the step 4.6, the total energy of the lightning is based on the k+1 period of time k+1 And a lightning strike region of the k+1 period predicts an energy state of the k+1 period k+1 Comprising the following substeps:
step 4.6.1, traversing all grids obtained in step 3.1, and predicting the energy state of the grids in the k+1 period k+1 When traversing to grid (s, j), the lightning energy of the grid over period k+1 is calculated by:
in the method, in the process of the invention,f(1) For the relative longitudinal direction of the grid (s, j) thundercloud movement obtained in step 4.5.6,f(2) The relative latitudinal direction of the grid (s, j) thundercloud movement obtained in step 4.5.6.
Step 4.6.2, traversing all grids obtained in step 3.1, and predicting the energy state of the grids in the k+2/3 period k+2/3 And cover the update state k+1 When traversing to grid (s, j), the lightning energy of the grid over the k+2/3 period is calculated by:
step 4.6.3, traversing all grids obtained in step 3.1, predicting the state of energy state in k+1/3 period k+1/3 And cover the update state k+1 When traversing to grid (s, j), the lightning energy of the grid over the k+1/3 period is calculated by:
preferably, the state k+1 Updating the overlay sequence further comprises: predicting lightning strike area and each grid lightning energy in a period of 30 minutes in future based on state quantity of the lightning cloud of the last 10 minutes k+1 Is the least reliable, state k+1/3 The highest reliability of (a) is achieved by sequentially using states k+1 ，state k+2/3 ，state k+1/3 To update the coverage to obtain the final state k+1 。
Preferably, in step 5, the real-time early warning is performed on the grid lines of each grid, including the following steps:
step 5.1, reading tower line information, including: the longitude and latitude of the pole tower and the name of the line where the pole tower is positioned;
step 5.2, calculating the number of lines in each grid according to the grid division result in the step 3.1 and the tower line information read in the step 5.1, and sequencing the lines from high to low according to the number of towers;
step 5.3, the lightning energy state of the k+1 period obtained according to step 4.6 k+1 Carrying out early warning grade division on the lines in each grid;
and 5.4, sequencing the lines of the total early warning list obtained in the step 5.3 from more to less, and displaying the lines on an early warning system interface in combination with the early warning level.
Preferably, a lightning energy of 50 means that in the area of a grid, at most one lightning stroke with an absolute value of 50kA occurs, setting 0 to 50, 50 to 100, 100 to 200, 200 to 500, 500 to ++infinity total 5 pre-warning intervals, the larger the lightning energy is, the higher the early warning level is:
if the energy of the grid (s, j) is between 0 and 50, the line of the grid does not perform early warning, and the early warning grade is green; if the energy of the grid (s, j) is 50-100, adding the line of the grid to a total early warning list, wherein the early warning grade is yellow; if the energy of the grid (s, j) is between 100 and 200, adding the line of the grid to a total early warning list, wherein the early warning grade is clear; if the energy of the grid (s, j) is 200-500, adding the line of the grid to a total early warning list, wherein the early warning grade is red; if the energy of the grid (s, j) is more than 500, adding the line of the grid to a total early warning list, wherein the early warning grade is purple.
The invention also provides a real-time lightning area prediction and line early warning system based on lightning energy, which comprises the following steps:
the data acquisition unit is used for acquiring real-time lightning information;
the preprocessing unit is used for extracting the current day lightning information from the read lightning information and calculating the current day lightning strike time distribution taking minutes as a unit;
the grid dividing unit is used for gridding the lightning information;
the prediction unit is used for predicting a lightning stroke area and estimating lightning energy of each grid;
and the early warning unit is used for early warning the grid lines of the grids in real time.
The invention also provides a terminal, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is used for operating according to the instruction to execute the steps of the real-time lightning area prediction and line early warning method.
The invention also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the real-time lightning area prediction and line pre-warning method.
Compared with the prior art, the lightning prediction and line early warning method provided by the invention has the beneficial effects that accurate lightning prediction can be realized only by detecting the latest lightning data, a large amount of data are not required to be acquired, and meanwhile, the grid area is thinned to 28 km through reasonable area grid division and time quantity setting 2 Each grid contains at most ten power transmission lines, the number of the power equipment in the grid is reasonable, the prediction time advance is 30 minutes, more accurate early warning can be realized on the lines, and enough regulation time is reserved for workers to regulate the power equipment.
Drawings
FIG. 1 is a flow chart of a lightning area prediction and line pre-warning method based on lightning energy in real time in the present invention;
FIG. 2 is a graph of the lightning energy variation over successive periods of time in the present invention;
FIG. 3 is a block diagram of a real-time lightning zone prediction and line early warning system based on lightning energy in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. The embodiments described herein are merely some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art without making any inventive effort, are within the scope of the present invention.
As shown in fig. 1, the invention provides a lightning energy-based real-time lightning area prediction and line early warning method, which comprises the following steps:
Step 1, acquiring lightning information of a region to be predicted;
the method for acquiring the real-time lightning information comprises the following steps of:
step 1.1: detecting, by a lightning detection device, lightning information to be predicted, including: latitude and longitude of a lightning strike point, lightning strike time and lightning strike amplitude, wherein the lightning strike time comprises: year, month, day, hour, minute, second, microsecond;
step 1.2: and reading the detected lightning information to a data processing platform.
Specifically, the lightning information of the latest date is the lightning related information sent by the latest day.
Step 2, preprocessing the real-time lightning information obtained from the step 1 to obtain preprocessed lightning information;
in the step 2, the real-time lightning information is preprocessed through a data processing platform, and the method comprises the following steps:
step 2.1, extracting the year, month and day of each piece of lightning information read in the step 1 through the existing year function, the Month function and the day function in the python language pandas library, and dividing the day according to the date to extract the lightning information of the day;
step 2.2, extracting the hours and minutes of the occurrence of the lightning stroke on the same day in the lightning information on the same day through the existing Hour function and minute function in the python language pandas library, and calculating the distribution position of the lightning stroke moment in the day by taking the minutes as a basic unit min；
The lightning information obtained in the step 1 is updated to a database in real time, based on the current time point, every 30 minutes, the lightning data 60 minutes before the current time point in the database is read, and the distribution position min of the lightning strike time in the day is calculated, wherein the distribution position of the lightning strike time in the day is calculatedminThe method meets the following conditions:
in the method, in the process of the invention,hfor the time of the hours in which the lightning strike occurs,mis the minute time for a lightning strike to occur.
The obtained distribution position min satisfies min epsilon 0,1440.
Step 3, dividing the preprocessed lightning information obtained from the step 2 based on space grids to obtain lightning data of each grid;
in the step 3, each grid lightning data is obtained by dividing the preprocessed lightning information based on space grids, and the method comprises the following steps:
step 3.1, gridding the area to be predicted at set intervals in the longitudinal direction and the latitudinal direction;
specifically, the region to be predicted is gridded at intervals of 0.05 degrees in the longitudinal direction and the latitudinal direction;
taking the Suzhou region as an example: the Suzhou is located between 119 DEG 55 DEG to 121 DEG 20 'of east longitude and 30 DEG 47 DEG to 32 DEG 02' of north latitude, the longitude direction is about 101 km, the latitude direction is about 111 km, and the grid area is about 28 square km;
step 3.2, according to the distribution position min of the lightning strike time in one day obtained in the step 2.2, acquiring the lightning data of 60 minutes which are continuous recently, setting a time span k and a time interval, and dividing the acquired lightning data into two groups of data of a k-1 period and a k period;
Specifically, the larger the time span k is, the more obvious the lightning activity rule is, and the obvious clustering effect is in space, but the time span is not too large, otherwise, the subsequent prediction effect is affected, so the time span is better for 30 minutes;
preferably, in the invention, the time span k is set to be 30 minutes, the acquired lightning data are divided into two groups, wherein 0-30 minutes is the last time (namely k-1 time period), and 30-60 are the current time (namely k time period);
and 3.3, dividing the two groups of lightning data into corresponding grids according to the longitude and latitude of lightning stroke according to the grid division obtained in the step 3.1 and the two groups of lightning data obtained in the step 3.2, and obtaining the lightning data of each grid in the k-1 time period and the k time period.
The smaller the grid side length is, the less obvious the lightning activity rule is obtained according to the lightning information in the grid, and the follow-up predictive analysis is not facilitated; the larger the grid, the worse the prediction effect, possibly leading to large-area ineffective prediction; through debugging, the longitude direction and the latitude direction are both spaced at 0.05 degrees, namely the grid area is about 28 square kilometers, so that the grid is suitable to be arranged;
and 4, carrying out lightning stroke area prediction and lightning energy estimation of each grid according to the lightning data of each grid obtained in the step 3.
In step 4, predicting lightning strike area of k+1 time period and estimating electric energy of each net gray of k+1 time period, comprising the following steps:
step 4.1, further subdividing each grid lightning data of the k-1 time period and the k time period obtained in the step 3.3 with a time interval of 10 minutes to obtain each grid lightning data of 4 time periods in total, namely, 0-30 minutes (k-1 time period), 10-40 minutes (k-2/3 time period), 20-50 minutes (k-1/3 time period) and 30-60 minutes (k time period);
step 4.2, according to the 4 time-interval grid lightning data obtained in step 4.1, respectively calculating 4 time-interval lightning energy to obtain energy_total k-1 ，energy_total k-2/3 ，energy_total k-1/3 ，energy_total k Screening out the total energy of the thunder and lightning in time intervals meeting the conditions;
calculating 4 time-interval total energy of the thunder and lightning and screening the time-interval total energy meeting the condition according to the 4 time-interval total energy of the thunder and lightning, comprising the following substeps:
step 4.2.1, setting a total energy list list_e and a time list list_x, and initializing the two lists to be empty lists;
step 4.2.2, respectively calculating total energy_total of 4 time intervals of lightning;
the total energy of lightning in each period is calculated as follows:
in the formula, total is the period of timeThe total number of lightning strikes is calculated, A i For the amplitude of each lightning stroke, the purpose of squaring and re-rooting is to smooth the data curve without overlarge numerical difference between energy_total;
according to the above calculation formula, 4 total energy of thunder and lightning corresponding to each time period is obtained k-1 、energy_total k-2/3 、energy_total k-1/3 And energy_total k 。
Further, judging whether the total energy of the lightning respectively corresponding to 4 time periods is greater than 0, and when the total energy of the lightning is greater than 0 in the k-2/3 time period, the k-1/3 time period and the k time period k-2/3 、energy_total k-1/3 And energy_total k And if the lightning data are larger than 0, entering a step 4.2.3, otherwise returning to the step 3.2, and re-reading the real-time lightning data.
Step 4.2.3, if the total energy of the lightning corresponding to a certain period is greater than 0, adding the total energy of the lightning corresponding to the certain period to list_e, adding the starting time point of computing the total energy to list_x, wherein the time point is calculated in step 2.2min；
And 4.2.4, if the energy_total corresponding to a certain period is equal to 0, resetting list_e and list_x to be empty lists, and returning to the step 3.2 to continuously read the real-time lightning data.
It can be seen that if the total energy of lightning in successive periods is not equal to 0, the total energy list list_e and the time list list_x are not reset, so that the elements in the two lists obtained by fitting are at least 3.
Step 4.3, respectively calculating the total energy of lightning of each grid in k-1/3 time periods and k time periods according to the lightning data of each grid in 4 time periods obtained in the step 4.1;
the calculation mode of the lightning energy of each grid in different time periods refers to the calculation formula of the lightning energy of each time period in the step 4.2.2, but total in the calculation formula represents the lightning stroke number in the time period corresponding to each grid.
According to the total energy of lightning in each grid of k-1/3 time period and k time period, obtaining the energy state of the two time periods k-1/3 And state k The state expression is as follows:
in the method, in the process of the invention,energy st grid lightning energy representing the s th grid in the longitude direction and the t th grid in the latitude direction;
step 4.4, estimating the total lightning energy of the k+1 time period according to the total lightning energy value of the last continuous time period meeting the condition obtained in the step 4.2, which is not limited to the k-1 time period, the k-2/3 time period, the k-1/3 time period and the k time period k+1 ；
Estimating the total energy of the lightning in the k+1 period by the total energy value of the lightning satisfying the condition in the last continuous period k+1 Comprising the following substeps:
step 4.4.1, if the number of elements of list_e and list_x obtained in step 4.2 is greater than or equal to 3, the elements of list_x are taken as independent variablesxList_e is a dependent variable yTaking the starting time point of the energy_total as x and the total energy of the lightning in each period as y, fitting to obtain an equation between x and y, calculating a fitting goodness coefficient R2, and if the number of elements of the list list_e and list_x obtained in the step 4.2 is less than 3 or the fitting goodness coefficient R2 of the equation obtained by fitting is less than 60%, not carrying out the following prediction, and returning to the step 3.2;
specifically, during the formation of the thundercloud, the energy_total of the continuous period starts from 0, increases sharply and then decreases sharply, so that the starting time point of the energy_total is calculated as an x-axis independent variable, the energy_total is a y-axis dependent variable, and a parabolic equation or a primary equation can be fitted, as shown in fig. 1.
A parabolic or once-fitted equation with the opening down is as follows:
wherein a, b, c are parameters of a parabolic equation, and the value range of a isWhen a is 0, the equation is a once equation.
Step 4.4.2, estimating total energy of lightning in the k+1 period according to the equation obtained in step 4.4.1 k+1 The estimation formula is as follows:
in the method, in the process of the invention,x k+1 for the starting time point of the k+1 period, a, b, c are parameters obtained by fitting in step 4.4.1.
Step 4.5, energy State of k-1/3 period and k period obtained according to step 4.3 k-1/3 And state k Predicting a lightning stroke area of a k+1 period;
predicting lightning strike area of k+1 time period according to step 4.5, by energy state of k-1/3 time period and k time period k-1/3 And state k Predicting a lightning strike area for a k+1 period, comprising the sub-steps of:
step 4.5.1, calculating a difference matrix state_change of the energy states of the k period and the k-1/3 period, wherein the calculation formula of the difference matrix state_change is as follows:
step 4.5.2, not considering two circles of grids at the outermost periphery of the area, traversing all other grids, selecting grids (s, j) which are adjacent to each other in the up-down and left-right directions each time, namely, s-2 rows to s+2 rows and j-2 columns to j+2 columns, and obtaining a difference matrix state_change1 of the 25 grids, wherein the difference matrix state_change1 of the 25 grids is as follows:
step 4.5.3, setting a longitude positive direction list x 1 List x of negative directions of longitude 2 List y of latitude positive directions 1 Latitude negative direction list y 2 The initial list is an empty list;
step 4.5.4, traversing all elements of state_Change1, setting a threshold, adding m to x if the value of grid (m, n) is greater than 200 1 Adding n to y 1 The method comprises the steps of carrying out a first treatment on the surface of the If the value of grid (m, n) is less than-200, then m is added to x 2 Adding n to y 2 ；
Wherein the grid (m, n) represents the grid of the mth row and the nth column, and the value of the grid (m, n) represents the variation value of the lightning energy in the grid.
If the value of the grid (m, n) belongs to [ -200,200]The lightning energy does not change significantly in a short time (10 minutes), and the thundercloud is considered not to move, i.e. the relative direction vectorfIs (0, 0) and no coordinates m or n of the network need be added to the list.
In step 4.5, the threshold 200 is specifically set, and if lightning energy in the same area changes greatly in adjacent time periods, the lightning cloud in the area is considered to move, and the lightning cloud moves in the direction of increasing energy.
As shown in fig. 2, considering the size of the grid and the speed of change of lightning energy comprehensively, setting a threshold 200, if the change of the lightning energy of the grid does not exceed 200 within 10 minutes, considering that the movement of the lightning cloud of the grid is not obvious, if the change of the lightning energy of the grid exceeds 200 within 10 minutes, entering a step 4.5.5, and predicting the movement direction of the lightning cloud of the grid according to the method of the step 4.5.5.
Step 4.5.5, x obtained according to step 4.5.4 1 ，x 2 ，y 1 ，y 2 Respectively calculating the relative position x of the increase and decrease of the lightning energy 1c ，x 2c ，y 1c ，y 2c Wherein x is 1c And x 2c Indicating the relative position of the increase or decrease in longitudinal direction of the lightning energy, y 1c And y 2c The calculation formula for the relative position of the increase or decrease in the latitudinal direction of the lightning energy is as follows:
In the formula, sum functions represent element sums for list determination, len functions represent the number of elements for list determination, and denominators are added by 1 to prevent denominators from being 0.
Step 4.5.6, x obtained according to step 4.5.5 1c ，x 2c ，y 1c ，y 2c To predict the relative direction vector of the grid (s, j) thundercloud movement in step 4.5.2f。
If x 1c Greater than x 2c And y is 1c Greater than y 2c ThenfIs (1, 1); if x 1c Greater than x 2c And y is 1c Equal to y 2c ThenfIs (1, 0); if x 1c Greater than x 2c And y is 1c Less than y 2c ThenfIs (1, -1); if x 1c Equal to x 2c And y is 1c Greater than y 2c ThenfIs (0, 1); if x 1c Equal to x 2c And y is 1c Equal to y 2c ThenfIs (0, 0); if x 1c Equal to x 2c And y is 1c Less than y 2c ThenfIs (0, -1); if x 1c Less than x 2c And y is 1c Greater than y 2c Thenf(-1, 1); if x 1c Less than x 2c And y is 1c Equal to y 2c Thenf(-1, 0); if x 1c Less than x 2c And y is 1c Less than y 2c Thenf(-1, -1);
wherein, the relative direction vector of the thundercloud movementfIs the abscissa of (2)f(1) And the ordinatef(2) The number of grids moving relative to the longitudinal direction and relative to the latitudinal direction are indicated, respectively, and the sign indicates both longitudinal and latitudinal directions.
Step 4.6, the total energy of the lightning in the k+1 period of time obtained in the step 4.4 is energy_total k+1 And 4.5, predicting the energy state of the k+1 time period in the lightning stroke area of the k+1 time period k+1 。
In step 4.6, according to the total energy of lightning in the k+1 period k+1 And a lightning strike region of k+1 period, predicting an energy state of k+1 period k+1 The method specifically comprises the following substeps:
step 4.6.1, traversing all the steps 3.1 to obtainAll meshes reached, their energy state in k+1 period is predicted k+1 When traversing to grid (s, j), its lightning energy is calculated as follows:
in the method, in the process of the invention,f(1) For the relative longitudinal direction of the grid (s, j) thundercloud movement obtained in step 4.5.6,f(2) The relative latitudinal direction of the grid (s, j) thundercloud movement obtained in step 4.5.6.
Step 4.6.2, traversing all grids obtained in step 3.1, and predicting the energy state of the grids in the k+2/3 period k+2/3 And cover the update state k+1 When traversing to grid (s, j), its lightning energy is calculated by:
step 4.6.3, traversing all grids obtained in step 3.1, predicting the state of energy state in k+1/3 period k+1/3 And cover the update state k+1 When traversing to grid (s, j), its lightning energy is calculated by:
state k+1 the update coverage sequence is: considering that the moving speed of the thundercloud is generally not more than 0.5-1 km/min, and the moving speed of the thundercloud is generally not more than 6 grids within 30 minutes, the invention only considers 3 grids to be predicted outwards, and does not consider more grids to be predicted outwards, because the prediction reliability may be lower.
The invention predicts the lightning strike area and each grid lightning energy for 30 minutes in the future based on the state quantity of the thundercloud of the last 10 minutes, and state k+1 Is the least reliable, state k+1/3 The reliability of (2) is highest, so that the states are used in turn k+1 ，state k+2/3 ，state k+1/3 To update the coverage, estimate the final state k+1 。
And 5, early warning the grid lines of the grids in real time according to the prediction result of the step 4.
In step 5, the real-time early warning of the grid lines of each grid is carried out, and the method comprises the following steps:
step 5.1, reading tower line information in the area to be predicted, including: the longitude and latitude of the pole tower and the name of the line where the pole tower is positioned;
step 5.2, calculating the number of lines in each grid according to the grid division result in the step 3.1 and the tower line information read in the step 5.1, and sequencing the lines from high to low according to the number of towers;
taking the Suzhou area as an example, the number of lines of each grid is generally at most ten or more;
in step 5.3, the pre-warning level setting further includes: a lightning energy of 50 means that in an area of the grid of about 28 square kilometers, at most one lightning stroke with an absolute value of 50kA occurs, with a very low probability of affecting the line;
in addition, the total energy of lightning in a 30-minute time span in a region is mostly less than 500, so that 0 to 50 is set, 50-100, 100-200, 200-500, 500 to ++infinity of 5 pre-warning intervals, the larger the lightning energy is, the higher the early warning level is.
The lightning energy state of the k+1 period obtained according to step 4.6 k+1 If the energy of the grid (s, j) is between 0 and 50, the line of the grid does not perform early warning, and the early warning grade is green; if the energy of the grid (s, j) is 50-100, adding the line of the grid to a total early warning list, wherein the early warning grade is yellow; if the energy of the grid (s, j) is between 100 and 200, adding the line of the grid to a total early warning list, wherein the early warning grade is clear; if the energy of the grid (s, j) is 200-500, adding the line of the grid to a total early warning list, wherein the early warning grade is red; if the energy of the grid (s, j) is more than 500, adding the line of the grid to a total early warning list, wherein the early warning grade is purple;
and 5.4, sequencing the lines of the total early warning list obtained in the step 5.3 from more to less, and displaying the lines on an early warning system interface in combination with the early warning level.
As shown in fig. 3, a lightning area prediction and line early warning system based on lightning energy includes:
the data acquisition unit is used for acquiring real-time lightning information;
the preprocessing unit is used for extracting the current day lightning information from the read lightning information and calculating the current day lightning strike time distribution taking minutes as a unit;
The grid dividing unit is used for gridding the lightning information;
the prediction unit is used for predicting a lightning stroke area and estimating lightning energy of each grid;
and the early warning unit is used for early warning the grid lines of the grids in real time.
Compared with the prior art, the lightning prediction and line early warning method provided by the invention has the beneficial effects that accurate lightning prediction can be realized only by detecting the latest lightning data, a large amount of data are not required to be acquired, and meanwhile, the grid area is thinned to 28 km through reasonable area grid division and time quantity setting 2 Each grid contains at most ten power transmission lines, the number of the power equipment in the grid is reasonable, the prediction time advance is 30 minutes, more accurate early warning can be realized on the lines, and enough regulation time is reserved for workers to regulate the power equipment.
The present disclosure may be a system, method, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
Computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
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