CN113269509A - Construction method of electric power meteorological database - Google Patents
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Abstract
The application discloses a method for constructing an electric power meteorological database, which comprises the following steps: step 1: collecting electric power meteorological data, classifying the electric power meteorological data according to the professional characteristics and application scenes of the electric power meteorological, and dividing the electric power meteorological data into electric power data, meteorological data and basic data; step 2: and (3) performing data quality control, integration, reservation and coverage processing on the data classified in the step (1), and establishing an electric power meteorological database by using the processed data. According to the invention, through analyzing the electric power weather application scene, the classification work of the electric power weather related data is developed, the electric power weather data with different formats and attributes are processed class by class, the construction work of the electric power weather database is developed, the universality of the electric power weather database is improved, and the correlation analysis of the weather data and the power grid fault is facilitated.
Description
Technical Field
The invention belongs to the technical field of electric power meteorological data processing, and relates to a construction method of an electric power meteorological database.
Background
With the rapid development and continuous enlargement and extension of the scale of the power grid, global climate warming and circulation are abnormal, the risk of the disastrous weather increases year by year, and the influence of the disastrous weather on the safe operation of the power grid is larger and larger. The electric power weather is a cross subject formed by combining the electric power field and the weather field, is not only a weather service aiming at the electric power industry by a weather department, but also is a special weather forecast, weather monitoring, power grid disaster prediction and power grid disaster risk early warning work which are required to be carried out by the electric power production.
Since the occurrence of a large-scale rain, snow and ice disaster in south of 2008, a plurality of attempts and researches are carried out by some power units and meteorological units aiming at the application of meteorological data in the power industry, and various large and small meteorological forecasting systems for power production are established. All the systems are basically integrated, the processing and storage methods related to various data are called and called, a set of electric power meteorological system with strong universality is not formed, and an electric power meteorological database is not formed and defined. This causes repeated investment and construction of the electric power meteorological project, poor universality of electric power meteorological data storage, and difficulty in rapid reuse of data.
Disclosure of Invention
In order to solve the defects in the prior art, the application provides the electric power meteorological database construction method, through analyzing the electric power meteorological application scene, classification work of electric power meteorological related data is carried out, electric power meteorological data with different formats and attributes are processed class by class, construction work of the electric power meteorological database is carried out, the universality of the electric power meteorological database is improved, and relevance analysis of meteorological data and power grid faults is facilitated.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method of building an electric power weather database, the method comprising the steps of:
step 1: collecting electric power meteorological data, classifying the electric power meteorological data according to the professional characteristics and application scenes of the electric power meteorological, and dividing the electric power meteorological data into electric power data, meteorological data and basic data;
step 2: and (3) performing data quality control, integration, reservation and coverage processing on the data classified in the step (1), and establishing an electric power meteorological database by using the processed data.
The invention further comprises the following preferred embodiments:
preferably, the power data of step 1 includes power equipment defect data and grid fault data;
the power equipment defect data specifically includes:
the defect finding moment is the moment when the defect of certain equipment is found through links such as inspection, maintenance and the like;
defective device information including the name, model, and manufacturer information of the defective device;
the defective device voltage level refers to the voltage level of the defective device;
the commissioning time of the defective equipment and the commissioning time of the defective equipment;
the defective equipment belongs to, namely the name of the substation or line to which the defective equipment belongs;
defective parts, i.e. specific equipment parts where defects are found;
defect description, i.e. description of the defect situation;
defect causes, namely defect causes of the power equipment;
defect handling/elimination; processing the defects of the power equipment;
defect handling/defect elimination time, i.e., the time when defect handling for electrical equipment is completed.
Preferably, the grid fault data specifically includes:
voltage class, i.e., the voltage class of the faulty line or device;
line or equipment name, i.e. the name of the faulty line or equipment;
the fault time is the date of the occurrence of the grid fault event and the time of the day, wherein the date adopts the Gregorian calendar date, and the time of the day adopts the Beijing time under a 24-hour timing system;
the recovery time, namely the date and the time of the day when the fault line or equipment recovers normal operation;
the fault reason is analyzed by a fault line patrol means;
the action condition of the automatic reclosing device, namely after the power grid fault occurs, the action condition of the automatic reclosing device is corresponding, and the action condition comprises whether the reclosing device is put into operation, whether the reclosing device successfully acts or not and whether the reclosing device is locked or not;
a failed site, i.e., the particular site or component that failed;
fault positioning information capable of reflecting fault position information;
fault clearing or handling conditions, handling conditions for fault events;
an operation and maintenance unit, namely an operation and maintenance unit to which a fault line or equipment belongs;
preferably, the meteorological data in step 1 comprises meteorological forecast data, meteorological live data, lightning positioning monitoring data and power transmission line monitoring data;
the weather forecast data comprises forecast release time, forecast time, air temperature, humidity, air speed, wind direction, air pressure, rainfall, illumination, fog, forecast of disastrous weather and early warning data of power grid weather disaster events;
the weather live data comprises weather element live data including weather site names, weather site codes, monitoring time, average air temperature, highest air temperature, lowest air temperature, humidity, wind speed, wind direction, maximum wind speed occurrence time, air pressure, rainfall, illumination and fog;
the lightning positioning monitoring data comprises lightning occurrence time, lightning end time, lightning occurrence position and lightning current amplitude;
the transmission line monitoring data refers to data representing the real-time state of the transmission line, which are acquired by various monitoring devices of the transmission line and comprise monitoring time, average temperature around the transmission line, highest temperature, lowest temperature, humidity, wind direction, maximum wind speed occurrence time, air pressure, rainfall, wire temperature, wire sag, wire icing thickness and insulator wind deflection angle.
Preferably, the basic data of step 1 includes: administrative region data, meteorological monitoring station data, tower data, power transmission line data and transformer substation information;
the administrative region data comprises provinces, local cities, city names, city codes, longitudes and latitudes;
the weather station data comprises a weather monitoring station number, a monitoring station name, a city code, longitude, latitude and station properties;
the tower data comprises the code, longitude, latitude, type, height, manufacturer, voltage grade and the line of the tower;
the power transmission line data comprises the name of the power transmission line, line codes, voltage grade, starting and stopping positions, crossing regions, length, height from the ground, wire specification, line types, loop codes, split numbers, arrangement forms and disaster prevention measures;
the substation information includes the name, code, longitude, latitude, and voltage class of the substation.
Preferably, the data quality control of step 2 includes: format check, missing test check, meteorological data limit check, main change range check, consistency check and quality control identification.
Preferably, the step 2 performs data integration processing, specifically:
the meteorological data of different sources, different formats and different types are integrated and stored, and the formats of the meteorological data are unified according to the data format requirements of the electric power meteorological database.
Preferably, the step 2 performs data retention processing, specifically:
at a certain period T1The meteorological data is subjected to the following retention processing:
if in period T1When a power grid fault event occurs, storing and retaining all meteorological data in a time period which is not less than 1 hour before and after the fault time, and not retaining other data;
if in period T1No grid fault event occurs, and the following data are calculated and stored:
each of the catastrophic weather forecast data;
early warning data of meteorological disaster events of each power grid;
wind: daily average wind speed, daily average wind direction, daily maximum wind speed, wind direction of daily maximum wind speed, time when daily maximum wind speed occurs, daily maximum wind speed, wind direction of daily maximum wind speed, and time when daily maximum wind speed occurs;
rainfall: rainfall for 12h and rainfall for 24 h;
air temperature: daily average air temperature, daily maximum air temperature, time when daily maximum air temperature appears, daily minimum air temperature, and time when daily minimum air temperature appears;
humidity: average daily relative humidity, maximum daily relative humidity, time of occurrence of maximum daily relative humidity, minimum daily relative humidity, time of occurrence of minimum daily relative humidity;
air pressure: daily average air pressure, daily minimum air pressure, daily maximum air pressure;
illumination: daily average total cloud number, daily maximum total radiation;
atomizing: daily minimum visibility;
other data is not reserved for storage.
Preferably, the step 2 performs data overlay processing, specifically:
based on the data retention processing, with a certain period T2The meteorological data are subjected to coverage processing, so that the data storage amount is further simplified, and the storage cost is saved;
period of data coverage T2Longer than the period T of data retention1，T2Taking 1 month, half year or 1 year;
the data overlay process includes the following:
storing the various disastrous weather forecast data, the various power grid meteorological disaster event early warning data, the wind, the rainfall, the air temperature, the moderate degree, the air pressure, the illumination and the fog which are related to the data retention processing;
if in period T2The method is characterized in that defects of power equipment are found, all the disastrous weather forecast data, all the power grid meteorological disaster event early warning data, wind, rainfall, air temperature, humidity, air pressure, illumination and fog in time periods which are not less than 1 week before and after the defect finding time are stored, and other meteorological data are covered by new data.
Preferably, in step 2, the electric power meteorological database further performs statistical analysis on the disastrous weather, the correlation information between the meteorological data and the power grid fault, time and environment-related power transmission line risk indexes, line risks under different conditions and power grid risks under different conditions, so as to realize correlation analysis between the meteorological data and the power grid fault;
the time and environment related transmission line risk indexes comprise: the method comprises the steps of regional power grid meteorological sensitivity, historical monthly fault frequency indexes in the same period, line fault frequency difference under the same voltage level, line fault high-risk sections, average outage time, average fault time interval and line short-term fault aggregation.
The beneficial effect that this application reached:
the invention organizes and utilizes the related mass data resources of the electric power weather scientifically, effectively and normatively, guides the work of defining, classifying, storing and controlling the quality of the electric power weather data, and has strong universality;
the effective utilization of the power meteorological data resources in power grid disaster prevention and reduction is promoted, and the comprehensive management level of the power meteorological related mass data resources can be improved.
Drawings
FIG. 1 is a flow chart of a method for constructing an electric power weather database according to the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 1, the method for constructing the electric power weather database of the present invention includes the following steps:
step 1: gather electric power meteorological data and according to electric power meteorological professional characteristics and applied scene, classify electric power meteorological data, divide into electric power meteorological data: power data, meteorological data and basic data;
1. the power data comprises power equipment defect data and power grid fault data;
power equipment defect data:
the defects of the power equipment reflect the quality abnormality phenomena generated by the power equipment such as the power transmission line and the like in the stages of transportation, construction, operation and maintenance and the like, and are usually caused by the accumulation effect of external environmental factors;
the defect finding moment is the moment when the defect of certain equipment is found through links such as inspection, maintenance and the like;
the defective device information comprises information of the name, the model, the manufacturer and the like of the defective device;
the defective device voltage level refers to the voltage level of the defective device;
the commissioning time of the defective equipment and the commissioning time of the defective equipment;
the defective equipment belongs to, namely the name of the substation or line to which the defective equipment belongs;
defective parts, i.e. specific equipment parts where defects are found;
describing defects; describing the defect condition;
defect causes, namely defect causes of the power equipment;
defect handling/elimination; processing the defects of the power equipment;
defect handling/defect elimination time, i.e., the time when defect handling for electrical equipment is completed.
Grid fault data:
the power grid fault data reflect the detailed conditions of power grid fault events and are objectively recorded and stored in the form of fault logs; the grid fault log mainly comprises the following contents:
voltage class, i.e., the voltage class of the faulty line or device;
line or equipment name, i.e. the name of the faulty line or equipment;
the fault time is the date of the occurrence of the grid fault event and the time of the day, wherein the date adopts the Gregorian calendar date, and the time of the day adopts the Beijing time under a 24-hour timing system; the fault time formats adopted in the fault logs are unified;
the recovery time, namely the date and the time of the day when the fault line or equipment recovers normal operation;
the fault causes are analyzed by means of fault line patrol and the like, wherein weather-related fault causes are classified in detail;
the action condition of the automatic reclosing device, namely after the power grid fault occurs, the action condition of the automatic reclosing device is corresponding, and the action condition comprises whether the reclosing device is put into operation, whether the reclosing device successfully acts or not and whether the reclosing device is locked or not;
a fault part, i.e. a specific part or element with a fault, such as a lead, a ground wire, an insulator, a tower, hardware fittings and the like;
fault location information, which can reflect information of the fault occurrence position, such as fault location information, fault tower number, fault line section and the like;
fault clearing or handling conditions, handling conditions for fault events;
and the operation and maintenance unit is the operation and maintenance unit to which the fault line or the equipment belongs.
2. The meteorological data comprises meteorological forecast data, meteorological actual data, lightning positioning monitoring data and power transmission line monitoring data;
weather forecast data: the method comprises the steps of forecasting release time, forecasting time, air temperature, humidity, air speed, wind direction, air pressure, rainfall, illumination, fog, forecasting of disastrous weather and early warning data of power grid meteorological disaster events;
weather live data: weather element live data including weather station names, weather station codes, monitoring time, average air temperature, highest air temperature, lowest air temperature, humidity, wind speed, wind direction, maximum wind speed occurrence time, air pressure, rainfall, illumination and fog;
thunder and lightning location monitoring data: lightning positioning monitoring data including lightning occurrence time, lightning ending time, lightning occurrence position, lightning current amplitude and the like;
monitoring data of the power transmission line: the data representing the real-time state of the power transmission line are acquired by various monitoring devices of the power transmission line and comprise data such as monitoring time, average temperature around the power transmission line, highest temperature, lowest temperature, humidity, wind direction, maximum wind speed occurrence time, air pressure, rainfall, wire temperature, wire sag, wire icing thickness, insulator wind deflection angle and the like.
3. The basic data includes: administrative region data, meteorological monitoring station data, tower data, power transmission line data and transformer substation information;
administrative region data: including province, local city, city name, city code, longitude and latitude;
weather station data: the method comprises the steps of including weather monitoring station number, monitoring station name, city code, longitude, latitude and station property;
tower data: the method comprises the steps of encoding, longitude, latitude, type, height, manufacturer, voltage class and belonging line of a tower;
data of the power transmission line: the method comprises the following steps of name, line code, voltage grade, start-stop position, crossing region, length, ground height, wire specification, line type, loop code, split number, arrangement form and disaster prevention measure of the power transmission line;
information of the transformer substation: including the name, code, longitude, latitude, voltage class of the substation.
And recording and converting station information through a converting station table. The method mainly comprises the following steps: voltage class, code, name, longitude and latitude coordinates of the transformer substation, legend, geographical location information and the like.
Step 2: and (3) performing data quality control, integration, reservation and coverage processing on the data classified in the step (1), and establishing an electric power meteorological database by using the processed data.
And (3) data quality control: including format checking, missing inspection, meteorological data threshold checking, major variation range checking, consistency checking, quality control identification, and the like.
Data integration processing:
the meteorological data of different sources, formats and types are integrated and stored, and the formats of the meteorological data are unified according to the data format requirements of the power meteorological database.
And (3) data retention processing:
at a certain period T1The stored meteorological data is subjected to the following preservation processing (such as 1 day, 2 days and the like):
if in period T1When a power grid fault event occurs, storing all meteorological data in time periods which are not less than 1 hour before and after the fault time;
if in period T1No grid fault event occurs, and the following data are calculated and stored:
each of the catastrophic weather forecast data;
early warning data of meteorological disaster events of each power grid;
wind: daily average wind speed, daily average wind direction, daily maximum wind speed, wind direction of daily maximum wind speed, time when daily maximum wind speed occurs, daily maximum wind speed, wind direction of daily maximum wind speed, and time when daily maximum wind speed occurs;
rainfall: 1h rainfall, 3h rainfall, 6h rainfall, 12h rainfall, 24h rainfall, 1h average rainfall, 3h average rainfall, 6h average rainfall, 12h average rainfall, 24h average rainfall;
air temperature: daily average air temperature, daily maximum air temperature, time when daily maximum air temperature appears, daily minimum air temperature, and time when daily minimum air temperature appears;
humidity: average daily relative humidity, maximum daily relative humidity, time of occurrence of maximum daily relative humidity, minimum daily relative humidity, time of occurrence of minimum daily relative humidity;
air pressure: daily average air pressure, daily minimum air pressure, daily maximum air pressure;
illumination: daily average total cloud number, daily maximum total radiation;
atomizing: daily minimum visibility, daily average visibility.
And (3) data coverage processing:
based on the data retention processing, with a certain period T2The meteorological data are subjected to coverage processing, so that the data storage amount is further simplified, and the storage cost is saved;
period of data coverage T2Longer than the period T of data retention1，T2Taking 1 month, half year or 1 year;
the data overlay process includes the following:
storing various disastrous weather forecast data, various power grid meteorological disaster event early warning data, wind, rainfall, air temperature, moderate degree, air pressure, illumination, fog and other meteorological data related to data retention processing;
if in period T2The method is characterized in that defects of power equipment are found, all the disastrous weather forecast data, all the power grid meteorological disaster event early warning data, wind, rainfall, air temperature, humidity, air pressure, illumination and fog in time periods which are not less than 1 week before and after the defect finding time are stored, and other meteorological data are covered by new data, namely other data are covered and updated in real time.
In step 2, the electric power meteorological database further performs statistical analysis on the disastrous weather, the correlation information of the meteorological data and the power grid faults, time and environment-related power transmission line risk indexes, line risks under different conditions and power grid risks under different conditions, so as to realize correlation analysis of the meteorological data and the power grid faults;
the time and environment related transmission line risk indexes comprise: the method comprises the steps of regional power grid meteorological sensitivity, historical monthly fault frequency indexes in the same period, line fault frequency difference under the same voltage level, line fault high-risk sections, average outage time, average fault time interval and line short-term fault aggregation.
The meteorological data and power grid fault analysis method is specifically implemented as follows:
the weather forecast data is obtained based on global numerical forecast products (T639, NCEP and RJTD) and real-time ground observation data, and specifically comprises the following steps: firstly, performing interpolation processing on ground observation missing data, and performing quality control on numerical prediction products; then, dynamically evaluating the forecasting effect of each mode on different forecasting factors based on modes such as a mode direct output (DMO) method and an advanced DMO objective correction technology at home and abroad, and removing the early forecasting deviation of each mode; determining the contribution of each mode forecast effect to the integrated forecast and calculating a weight coefficient according to the mode forecast effect, making a multi-mode integrated forecast equation, and establishing a multi-mode integrated forecast system for different meteorological elements of different sites; and finally, carrying out post-processing on the integrated forecast product, and outputting refined objective forecast products of different sites twice a day, namely weather forecast data (including weather actual conditions, weather partition actual conditions, thunder information and strong wind information), wherein the refined objective forecast products are output for 1-3 days and 3 hours and for 4-7 days and 6 hours respectively.
And (3) performing disaster weather statistics:
TABLE 1 disastrous weather statistics
And (3) carrying out correlation information statistics on meteorological data and power grid faults:
(1) fault-associated weather truth
And recording result data of the weather-condition analysis when the fault occurs by using the fault-related weather-condition table.
TABLE 2 Fault-associated weather-truth table
(2) Fault-correlated lightning live
And recording result data of the lightning live condition analysis when the fault occurs by using the fault correlation lightning live condition table.
TABLE 3 Fault-associated thunder and lightning truth table
Time and environment related transmission line risk index statistics:
regional power grid meteorological sensitivity
TABLE 4 Meteorological sensitivity data sheet of regional power grid
② frequency index of failure of each month in historical synchronization
TABLE 5 data sheet of average downtime
③ circuit fault times difference under same voltage class
Table 6 line fault times difference data table under same voltage class
High risk section for line fault
TABLE 7 high risk zone data sheet for line fault
Average shut down time
TABLE 8 data sheet of average downtime
Mean time between failures
TABLE 9 mean time between failure data Table
Seventh, short-term fault accumulation of line
TABLE 10 short-term failure aggregation times table for lines
Line risk statistics under different conditions:
to record the calculated line risk under different conditions (statistical period including year, quarter, month, etc.).
TABLE 11 line Risk under different conditions
And (3) power grid risk index statistics under different conditions:
used for recording the risk assessment indexes of the power grid calculated under different conditions (the statistical period comprises year, quarter, month and the like; the meteorological factors comprise thunder, strong wind, mountain fire, ice and snow and the like)
Table 12 grid risk indicators under different conditions
In order to carry out early warning work of electric power meteorological disasters with different time scales, the invention researches accidents caused by meteorological disasters on a power grid over the years, forms a favorite power grid accident set, carries out element disassembly and classification on meteorological data (meteorological stations, radars, satellites, terrain and the like) and power grid data (net racks, power transmission and transformation on-line monitoring, lightning positioning and the like) according to different rules, researches the corresponding relation among different data sources, aims to research the multi-source data integration of electric power meteorology, adopts a relational database as a carrier, and establishes an 'electric power meteorological database' integrating the meteorological data and the power grid data.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A construction method of an electric power meteorological database is characterized by comprising the following steps:
the method comprises the following steps:
step 1: collecting electric power meteorological data, classifying the electric power meteorological data according to the professional characteristics and application scenes of the electric power meteorological, and dividing the electric power meteorological data into electric power data, meteorological data and basic data;
step 2: and (3) performing data quality control, integration, reservation and coverage processing on the data classified in the step (1), and establishing an electric power meteorological database by using the processed data.
2. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
step 1, the electric power data comprise electric power equipment defect data and power grid fault data;
the power equipment defect data specifically includes:
the defect finding moment is the moment when the defect of certain equipment is found through links such as inspection, maintenance and the like;
defective device information including the name, model, and manufacturer information of the defective device;
the defective device voltage level refers to the voltage level of the defective device;
the commissioning time of the defective equipment and the commissioning time of the defective equipment;
the defective equipment belongs to, namely the name of the substation or line to which the defective equipment belongs;
defective parts, i.e. specific equipment parts where defects are found;
defect description, i.e. description of the defect situation;
defect causes, namely defect causes of the power equipment;
defect handling/elimination; processing the defects of the power equipment;
defect handling/defect elimination time, i.e., the time when defect handling for electrical equipment is completed.
3. The method for constructing the electric power meteorological database according to claim 2, wherein the method comprises the following steps:
the grid fault data specifically includes:
voltage class, i.e., the voltage class of the faulty line or device;
line or equipment name, i.e. the name of the faulty line or equipment;
the fault time is the date of the occurrence of the grid fault event and the time of the day, wherein the date adopts the Gregorian calendar date, and the time of the day adopts the Beijing time under a 24-hour timing system;
the recovery time, namely the date and the time of the day when the fault line or equipment recovers normal operation;
the fault reason is analyzed by a fault line patrol means;
the action condition of the automatic reclosing device, namely after the power grid fault occurs, the action condition of the automatic reclosing device is corresponding, and the action condition comprises whether the reclosing device is put into operation, whether the reclosing device successfully acts or not and whether the reclosing device is locked or not;
a failed site, i.e., the particular site or component that failed;
fault positioning information capable of reflecting fault position information;
fault clearing or handling conditions, handling conditions for fault events;
and the operation and maintenance unit is the operation and maintenance unit to which the fault line or the equipment belongs.
4. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
step 1, the meteorological data comprise meteorological forecast data, meteorological actual data, lightning positioning monitoring data and power transmission line monitoring data;
the weather forecast data comprises forecast release time, forecast time, air temperature, humidity, air speed, wind direction, air pressure, rainfall, illumination, fog, forecast of disastrous weather and early warning data of power grid weather disaster events;
the weather live data comprises weather element live data including weather site names, weather site codes, monitoring time, average air temperature, highest air temperature, lowest air temperature, humidity, wind speed, wind direction, maximum wind speed occurrence time, air pressure, rainfall, illumination and fog;
the lightning positioning monitoring data comprises lightning occurrence time, lightning end time, lightning occurrence position and lightning current amplitude;
the transmission line monitoring data refers to data representing the real-time state of the transmission line, which are acquired by various monitoring devices of the transmission line and comprise monitoring time, average temperature around the transmission line, highest temperature, lowest temperature, humidity, wind direction, maximum wind speed occurrence time, air pressure, rainfall, wire temperature, wire sag, wire icing thickness and insulator wind deflection angle.
5. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
step 1, the basic data comprises: administrative region data, meteorological monitoring station data, tower data, power transmission line data and transformer substation information;
the administrative region data comprises provinces, local cities, city names, city codes, longitudes and latitudes;
the weather station data comprises a weather monitoring station number, a monitoring station name, a city code, longitude, latitude and station properties;
the tower data comprises the code, longitude, latitude, type, height, manufacturer, voltage grade and the line of the tower;
the power transmission line data comprises the name of the power transmission line, line codes, voltage grade, starting and stopping positions, crossing regions, length, height from the ground, wire specification, line types, loop codes, split numbers, arrangement forms and disaster prevention measures;
the substation information includes the name, code, longitude, latitude, and voltage class of the substation.
6. The method for constructing the electric power weather database according to any one of the claims 1 to 5, wherein:
step 2, the data quality control comprises: format check, missing test check, meteorological data limit check, main change range check, consistency check and quality control identification.
7. The method for constructing the electric power meteorological database according to claim 6, wherein the method comprises the following steps:
the step 2 of performing data integration processing specifically comprises:
the meteorological data of different sources, different formats and different types are integrated and stored, and the formats of the meteorological data are unified according to the data format requirements of the electric power meteorological database.
8. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
the step 2 of performing data retention processing specifically includes:
at a certain period T1The meteorological data is subjected to the following retention processing:
if in period T1When a power grid fault event occurs, storing and retaining all meteorological data in a time period which is not less than 1 hour before and after the fault time, and not retaining other data;
if in period T1No grid fault event occurs, and the following data are calculated and stored:
each of the catastrophic weather forecast data;
early warning data of meteorological disaster events of each power grid;
wind: daily average wind speed, daily average wind direction, daily maximum wind speed, wind direction of daily maximum wind speed, time when daily maximum wind speed occurs, daily maximum wind speed, wind direction of daily maximum wind speed, and time when daily maximum wind speed occurs;
rainfall: rainfall for 12h and rainfall for 24 h;
air temperature: daily average air temperature, daily maximum air temperature, time when daily maximum air temperature appears, daily minimum air temperature, and time when daily minimum air temperature appears;
humidity: average daily relative humidity, maximum daily relative humidity, time of occurrence of maximum daily relative humidity, minimum daily relative humidity, time of occurrence of minimum daily relative humidity;
air pressure: daily average air pressure, daily minimum air pressure, daily maximum air pressure;
illumination: daily average total cloud number, daily maximum total radiation;
atomizing: daily minimum visibility;
other data is not reserved for storage.
9. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
the step 2 performs data coverage processing, specifically:
based on the data retention processing, with a certain period T2Covering the meteorological data;
period of data coverage T2Longer than the period T of data retention1，T2Taking 1 month, half year or 1 year;
the data overlay process includes the following:
storing the various disastrous weather forecast data, the various power grid meteorological disaster event early warning data, the wind, the rainfall, the air temperature, the moderate degree, the air pressure, the illumination and the fog which are related to the data retention processing;
if in period T2The method is characterized in that defects of power equipment are found, all the disastrous weather forecast data, all the power grid meteorological disaster event early warning data, wind, rainfall, air temperature, humidity, air pressure, illumination and fog in time periods which are not less than 1 week before and after the defect finding time are stored, and other meteorological data are covered by new data.
10. The method for constructing the electric power meteorological database according to claim 1, wherein the method comprises the following steps:
in step 2, the electric power meteorological database further performs statistical analysis on the disastrous weather, the correlation information of the meteorological data and the power grid faults, time and environment-related power transmission line risk indexes, line risks under different conditions and power grid risks under different conditions, so as to realize correlation analysis of the meteorological data and the power grid faults;
the time and environment related transmission line risk indexes comprise: the method comprises the steps of regional power grid meteorological sensitivity, historical monthly fault frequency indexes in the same period, line fault frequency difference under the same voltage level, line fault high-risk sections, average outage time, average fault time interval and line short-term fault aggregation.
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