CN113344735B - Disaster prevention and reduction monitoring and early warning system of power grid equipment - Google Patents

Disaster prevention and reduction monitoring and early warning system of power grid equipment Download PDF

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CN113344735B
CN113344735B CN202110545646.8A CN202110545646A CN113344735B CN 113344735 B CN113344735 B CN 113344735B CN 202110545646 A CN202110545646 A CN 202110545646A CN 113344735 B CN113344735 B CN 113344735B
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CN113344735A (en
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赵彦阳
程凌森
何超林
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China Southern Power Grid Digital Grid Technology Guangdong Co ltd
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Southern Power Grid Digital Grid Research Institute Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment

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Abstract

The application provides a power grid equipment's disaster prevention and reduction monitoring early warning system includes: the data access layer is used for storing meteorological data and power grid equipment data; the analysis decision layer comprises a plurality of disaster analysis units and a message pushing module connected with the disaster analysis units, wherein each disaster analysis unit has a disaster type, and the disaster analysis processing corresponding to the disaster analysis units belonging to the same disaster type is different; the service layer comprises a plurality of service units; each business unit is provided with a disaster type and a disaster analysis unit which is triggered correspondingly; the disaster type of each service unit is consistent with the disaster type of the disaster analysis unit triggered by the service unit, and the disaster analysis units triggered by different service units are different; according to the disaster prevention and reduction monitoring and early warning system for the power grid equipment, overall monitoring and processing of various meteorological monitoring data can be achieved, and the disaster prevention and reduction monitoring and early warning efficiency for the power grid equipment is improved.

Description

Disaster prevention and reduction monitoring and early warning system of power grid equipment
Technical Field
The application relates to the technical field of power equipment, in particular to a disaster prevention and reduction monitoring and early warning system of power grid equipment.
Background
In the field of electric power, meteorological disasters can damage electric power equipment, so in order to monitor the influence of the meteorological disasters on the electric power equipment, the work of preventing and reducing the disasters on the electric power equipment is well done, and the distribution construction of environment monitoring devices for the electric power equipment is gradually increased so as to improve the perception capability on various disasters and hidden dangers. However, these monitoring devices are distributed, and meteorological data and service data are difficult to be effectively fused, so that a platform for comprehensive application and analysis of various monitoring data access is urgently needed, the power grid disaster risk is mastered in real time, the disaster prevention and reduction force is enhanced, the monitoring, early warning, evaluation and decision-making capability of the overall disaster process is improved, and a technical support is provided for disaster prevention and reduction monitoring early warning and management decision.
Disclosure of Invention
Therefore, it is necessary to provide a disaster prevention and reduction monitoring and early warning system for power grid equipment in order to solve the above technical problems.
A disaster prevention and reduction monitoring and early warning system of power grid equipment comprises: a data access layer, an analysis decision layer and a service layer;
the data access layer is used for storing meteorological data and power grid equipment data;
the analysis decision layer comprises a plurality of disaster analysis units and a message pushing module connected with the disaster analysis units, wherein each disaster analysis unit has a disaster type, and the disaster analysis units belonging to the same disaster type have different corresponding disaster analysis processes;
the service layer comprises a plurality of service units; each business unit is provided with a disaster type and a disaster analysis unit which is triggered correspondingly; the disaster type of each service unit is consistent with the disaster type of the disaster analysis unit triggered by the service unit, and the disaster analysis units triggered by different service units are different;
after a business unit included in the business layer is triggered by a user to generate a corresponding disaster analysis processing request, the business unit sends the disaster analysis processing request to the message pushing module, the message pushing module determines a disaster analysis unit corresponding to the triggered business unit based on the disaster analysis processing request, and triggers the disaster analysis unit to perform disaster analysis processing aiming at the disaster analysis processing request based on the meteorological data and power grid equipment data stored in the data access layer.
In one embodiment, the data access layer comprises a big data center; the meteorological data stored in the big data center comprise real-time weather data, historical weather data and forecast weather data, and the power grid equipment data comprise power grid equipment ledger data.
In one embodiment, the data access layer further comprises a local database without a firewall between the data access layer and each disaster analysis unit; the local database is used for storing the structured meteorological data acquired from a preset data source system and storing the unstructured ground surface deformation video data, which are acquired from the data source system and aim at the power grid equipment, in the big data center.
In one embodiment, a data source system for providing meteorological data to the local database comprises: the system comprises a lightning positioning system, an icing monitoring system and a mountain fire monitoring system;
the data source system for providing the surface deformation video data to the local database comprises: transmission line geological disasters monitor early warning system.
In one embodiment, the data access layer further comprises a GIS platform, and the GIS platform is used for storing GIS data;
and the disaster analysis unit is also used for carrying out disaster analysis processing aiming at the disaster analysis processing request based on the real-time weather data, the historical weather data, the forecast weather data, the power grid equipment ledger data and the GIS data.
In one embodiment, each disaster analysis unit of the analysis decision layer, each service unit of the service layer, and the local database are all located in a first area of a preset power grid cloud platform, and no firewall is located among the disaster analysis units, the service units, and the local database in the first area; the GIS platform and the big data center are located in a second area of the power grid cloud platform, and a cross-area firewall is arranged between the first area and the second area;
and each disaster analysis processing unit accesses GIS data of the GIS platform in the second area from the first area through the cross-area firewall, and accesses the real-time weather data, the historical weather data, the forecast weather data and the power grid equipment ledger data of the big data center.
In one embodiment, a DMZ switch, an external network firewall and an external network device are deployed in a DMZ zone of the power grid cloud platform;
the disaster prevention and reduction monitoring and early warning system further comprises an external network access processing device for providing access to the external network device, wherein the external network access processing device is located in the first area, and the first area is also provided with a core switch;
and the external network access processing equipment provides corresponding external network access to the external network equipment through the external network firewall sequentially through the core switch and the DMZ switch.
In one embodiment, each disaster analysis processing unit accesses, from the first area via the core switch, the GIS data of the GIS platform located in the second area through the cross-area firewall, and accesses the real-time weather data, the historical weather data, the predicted weather data, and the grid equipment ledger data of the big data center.
In one embodiment, each disaster analysis unit is a disaster analysis unit with a micro-service architecture constructed based on the power grid cloud platform.
In one embodiment, the disaster types include a meteorological disaster type, a mountain fire disaster type, a typhoon disaster type, a lightning disaster type, a waterlogging disaster type, an earthquake disaster type, and an icing disaster type;
the business unit belonging to the meteorological disaster type comprises: a weather monitoring and early warning service unit;
the business unit belonging to the mountain fire disaster type comprises: the system comprises a mountain fire real-time monitoring business unit, a mountain fire comprehensive study and judgment business unit and a mountain fire decision command business unit;
the business unit belonging to the typhoon disaster type comprises: the system comprises a typhoon real-time monitoring service unit, a typhoon early warning analysis service unit, a typhoon damage assessment service unit and a typhoon decision support service unit;
the business unit belonging to the type of the lightning disaster comprises: the system comprises a thunder and lightning monitoring and positioning service unit, a thunder and lightning early warning service unit and a thunder and lightning decision support service unit;
the service unit belonging to the inland inundation disaster type comprises: the system comprises an inland inundation disaster monitoring service unit, an inland inundation disaster early warning service unit and an inland inundation comprehensive study and judgment service unit;
the business unit belonging to the earthquake disaster type comprises: the earthquake real-time monitoring service unit, the earthquake early warning evaluation service unit and the post-earthquake decision support service unit;
the business unit belonging to the icing disaster type comprises: the system comprises an icing condition monitoring service unit, an icing influence early warning service unit and an icing comprehensive evaluation service unit.
In the disaster prevention and reduction monitoring and early warning system for the power grid equipment, the disaster prevention and reduction monitoring and early warning system is constructed based on the data access layer, the analysis decision layer and the service layer, wherein the disaster prevention and reduction monitoring and early warning system uniformly acquires various meteorological data and power grid equipment data through the data access layer, and a user can trigger the disaster analysis unit of the corresponding analysis decision layer through the service unit of the service layer to perform disaster analysis processing corresponding to the belonged disaster type by using the corresponding meteorological data and power grid equipment data, so that overall monitoring processing on various meteorological monitoring data is realized, and the disaster prevention and reduction monitoring and early warning efficiency for the power grid equipment is improved.
Drawings
FIG. 1 is a diagram illustrating an internal structure of a computer device according to an embodiment;
fig. 2a is an architecture diagram of a disaster prevention and reduction monitoring and early warning system of a power grid device in an embodiment;
fig. 2b is an architecture diagram of a disaster prevention and reduction monitoring and early warning system of a power grid device in an embodiment;
FIG. 3 is a schematic flow chart of a disaster analysis processing method according to an embodiment;
fig. 4 is an architecture diagram of a disaster prevention and reduction monitoring and early warning system of a power grid device in another embodiment;
fig. 5 is a block diagram showing a configuration of a disaster analysis processing device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by a person skilled in the art that the embodiments described herein can be combined with other embodiments.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 1. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The disaster prevention and reduction monitoring and early warning system for the power grid equipment is based on a cloud platform, a big data center and an Internet of things platform, combines meteorological data service with characteristics of the power industry, carries out deep fusion and application of meteorological data and service data, provides refined application of meteorological and service for users, masters power grid disaster risks in real time, strengthens disaster prevention and reduction force, improves monitoring, early warning, evaluation and decision-making capacity of the overall disaster process, and provides technical support for disaster prevention and reduction monitoring, early warning and management decision-making.
The application provides a power grid equipment's disaster prevention and reduction monitoring early warning system includes: a data access layer, an analysis decision layer and a service layer.
The data access layer is used for storing meteorological data and power grid equipment data;
the analysis decision layer comprises a plurality of disaster analysis units and a message pushing module connected with the disaster analysis units, wherein each disaster analysis unit has a disaster type, and the disaster analysis units belonging to the same disaster type have different corresponding disaster analysis processes;
the service layer comprises a plurality of service units; each business unit is provided with a disaster type and a disaster analysis unit which is triggered correspondingly; the disaster type of each business unit is consistent with the disaster type of the disaster analysis unit triggered by the business unit, and the disaster analysis units triggered by different business units are different.
Further, as shown in fig. 2a, the disaster types include a meteorological disaster type, a mountain fire disaster type, a typhoon disaster type, a thunder disaster type, an inland inundation disaster type, an earthquake disaster type, and an icing disaster type; wherein, the disaster analysis unit that belongs to above-mentioned meteorological disaster type includes: a meteorological monitoring and early warning disaster analysis unit; the disaster analysis unit belonging to the mountain fire disaster type includes: the system comprises a mountain fire real-time monitoring disaster analysis unit, a mountain fire comprehensive study and judgment disaster analysis unit and a mountain fire decision and command disaster analysis unit; the disaster analysis unit belonging to the typhoon disaster type includes: the system comprises a typhoon real-time monitoring disaster analysis unit, a typhoon early warning and analyzing disaster analysis unit, a typhoon damage assessment disaster analysis unit and a typhoon decision support disaster analysis unit; the disaster analyzing unit belonging to the above lightning disaster type includes: the system comprises a thunder and lightning monitoring and positioning disaster analysis unit, a thunder and lightning early warning disaster analysis unit and a thunder and lightning decision support disaster analysis unit; the disaster analysis unit belonging to the above-mentioned inland inundation disaster type includes: the system comprises an inland inundation disaster monitoring and analyzing unit, an inland inundation disaster early warning and analyzing unit and an inland inundation comprehensive study and judgment disaster analyzing unit; the disaster analyzing unit belonging to the above earthquake disaster type includes: the earthquake early warning and evaluation disaster analysis system comprises an earthquake real-time monitoring disaster analysis unit, an earthquake early warning and evaluation disaster analysis unit and a post-earthquake decision support disaster analysis unit; the disaster analyzing unit belonging to the icing disaster type includes: the system comprises an icing condition monitoring disaster analysis unit, an icing influence early warning disaster analysis unit and an icing comprehensive assessment disaster analysis unit.
The service units belonging to the same disaster type in the service layer can be integrated in the same service module, for example, the service unit corresponding to the forest fire real-time monitoring disaster analysis unit, the service unit corresponding to the forest fire comprehensive research and judgment disaster analysis unit, and the service unit corresponding to the forest fire decision command disaster analysis unit are all integrated in the forest fire monitoring research and judgment decision service module, so that a user can perform different disaster analysis processing on the same disaster type.
In one embodiment, as shown in fig. 2b, the analysis decision layer may be referred to as an application layer, and the application layer includes applications corresponding to various disaster types, such as a meteorological scene application, a wildfire scene application, a typhoon scene application, a seismic scene application, an icing scene application, a geological scene application, a waterlogging scene application, and a lightning scene application.
Each of the above applications may include different processing units, which are specifically described as follows:
1. weather scene application:
Figure BDA0003073410830000061
urban weather monitoring: and weather live and forecast data are accessed, so that the comprehensive visual display of the city forecast data, the live data and historical data is realized, and the weather change condition of the area and the change condition of each weather element are visually displayed.
Figure BDA0003073410830000062
Equipment weather monitoring: the method supports accurate acquisition of the meteorological conditions of the location of the equipment assets, and service personnel can master the weather condition and the future change trend of the surrounding equipment such as a transformer substation and a power transmission line section which are important concerns in real time, assist in preparing operation and maintenance of the equipment and reasonably adjust a working plan.
Figure BDA0003073410830000063
Weather monitoring of a microclimate station: the information of the site and the weather actual situation and historical monitoring information monitored by the site can be obtained, so that the operation protection work can be reasonably carried out by the operators, and the disaster resistance can be effectively improved.
Figure BDA0003073410830000064
Public warning: and drawing a meteorological early warning layer to visually embody an early warning area, and performing rolling broadcast on early warning detailed information to remind a user of paying attention.
Figure BDA0003073410830000065
Early warning of equipment: according to the early warning range, the distribution condition of the equipment in the early warning range is checked, the weather early warning condition of the equipment is known in advance, different early warning types and levels are selected, the issuing function is clicked, the warning information is pushed by one key, and a user is informed to carry out related checking and protection work in time.
Figure BDA0003073410830000071
Forecasting and comparing meteorological historical elements: and randomly selecting a certain historical moment, checking the comparison condition of the actual condition (temperature, precipitation and wind speed) and the forecast data at the current moment, and evaluating the accuracy of the meteorological forecast data.
2. Typhoon scene application:
Figure BDA0003073410830000072
live typhoon monitoring: the typhoon real-time forecast data and the typhoon wind field structured data are accessed, information such as the typhoon center position, the center air pressure, the predicted path, the landing place, the landing time, the moving speed, the wind field distribution, the wind circle and the like is displayed, the typhoon change process is dynamically evolved according to the preset speed, business personnel are helped to quickly know the influence condition of the typhoon on the governed region, the working state is timely adjusted, and disaster-resistant preparation is well made.
Figure BDA0003073410830000073
Site monitoring: monitoring data of various weather monitoring stations are combined, distribution conditions of various weather devices such as national weather stations and microclimate stations in typhoon landing areas are provided, and weather live monitoring information and historically monitored weather information of the stations are checked.
Figure BDA0003073410830000074
Maximum wind velocity profile: and automatically drawing a maximum wind speed distribution map according to refined weather live data monitored by the site, visually embodying the typhoon movement condition and the distribution condition of typhoon key influence areas, and providing guidance for business personnel to timely avoid risks, post-disaster investigation, wind prevention reinforcement and other work.
Figure BDA0003073410830000075
Typhoon early warning: the typhoon real-time information and the prediction path are fused, the regional conditions of the influence range of each stage of wind circle are statistically analyzed in real time, and the range of equipment damage and the influenced operation range which possibly occur in a typhoon strong wind area are highlighted. Before typhoon landing, the contents of a typhoon prediction path, weather forecast information, the wind resistance of equipment and the like are fused, the equipment distribution condition and damage risk calculation in a typhoon influence range is completed, the equipment distribution condition in a typhoon influence area and the condition of influenced power users are automatically analyzed, and an equipment damage risk list is formed. And (3) early warning production operation activities in the typhoon influence area by combining the development condition of the production activities, reminding operation and maintenance personnel to do typhoon prevention work when the typhoon does not enter a 24-hour warning line, and reminding users to do danger avoidance work in time after the typhoon enters the 24-hour warning line. The system automatically generates typhoon early warning reports and typhoon early warning short messages and timely informs relevant units and personnel of preparing disaster prevention and resistance. After typhoon landing, combining typhoon live scenes with forecasts, analyzing the influence of equipment and users from the coverage dimension of the wind circle and the lattice meteorological dimension, displaying the equipment and the users in a coverage range by using lattice meteorological data and different grades of wind circles, and reminding the users of equipment which is important to be informed of early warning and has urgent major defects and is not eliminated by combining the health state of the equipment.
Figure BDA0003073410830000081
Typhoon comparison: according to the landing point and platformSimilar typhoons are intelligently matched with information such as wind paths and wind power grades, and the influence conditions of the historical similar typhoons on a power grid are summarized and analyzed, so that reference opinions are provided for work such as disaster defense and emergency repair of the current typhoons.
Figure BDA0003073410830000082
And (3) trip analysis: the trip time, the outage time and the typhoon landing process are matched, support is provided for analyzing the cause of the trip after disaster, and the working efficiency of business personnel for positioning the cause of the line trip is improved.
Figure BDA0003073410830000083
And (3) fault emergency repair: the method comprises the steps of mastering the distribution lines damaged due to disasters and the power failure condition of a user, conducting background analysis on the fault reporting condition of the user, and providing information support for customer service personnel when fault reporting or customer complaints are handled by combining the typhoon influence condition of a fault reporting point.
3. Application of an icing scene:
Figure BDA0003073410830000084
and (3) icing monitoring: the monitoring information of the icing monitoring device of the power transmission line is acquired by combining an intelligent gateway with a mass time sequence data processing technology, the real-time and historical icing monitoring information (thickness, tension change and the like) of each phase of different lines is checked, the icing ratio is converted by combining the ice thickness design parameters of the lines, graded alarm is carried out according to the ratio value, a user is reminded of timely carrying out deicing melting work, and the loss of a power grid is reduced.
Figure BDA0003073410830000085
Early warning of equipment: and (3) carrying out rapid fitting and model training and prediction according to weather forecast information such as temperature, humidity and wind speed and relevant parameters such as coordinate position and altitude, so as to obtain the estimated ice thickness value of the ice coating in the micro-grid area at each time point in 72 hours in the future. Combining ice coating forecast, ice coating real-time monitoring and ice coating historyAnd the information is combined with the design ice thickness and other parameter values of the line, the tower-based tower grading early warning is carried out on the area which is possibly subjected to ice coating and key disasters, and an early warning tower list is generated. The system automatically generates an icing early warning report every day, and guides a user to perform the work of checking and cleaning the ice-proof tree barriers, checking the ice melting device, compiling the ice melting and removing plan and the like in advance.
Figure BDA0003073410830000086
Ice protection weak section: based on ice region distribution maps in different recurrence periods (30-year-first, 50-year-first and 100-year-first), historical ice-covering data are superposed for analysis, ice-proof weak sections are visually displayed through a visual means, pole tower equipment lists in the sections are intelligently identified, and business personnel are assisted to effectively carry out ice-proof reinforcement work.
Figure BDA0003073410830000087
Ice coating tripping: the method has the advantages that the trip information of the line is accessed, the running state of the power grid is timely sensed, monitoring data of the ice coating monitoring device and meteorological ice coating early warning information are fused based on the trip information of the line, the possibility that the trip event of the line is influenced by the ice coating of the line is intelligently analyzed, business personnel are assisted to quickly diagnose the reason of the ice coating of the line, and the working efficiency is improved.
Figure BDA0003073410830000091
And (3) ice melting strategy: the method comprises the steps of generating a line ice melting plan in an auxiliary mode based on freezing disaster prediction, meteorological data, line ice conditions and the like, carrying out priority ranking on ice melting work according to the importance degree of the ice melting line, dynamically generating a line ice melting strategy, guiding business personnel to rapidly carry out the ice melting and removing work, and reducing the influence of icing disasters.
Figure BDA0003073410830000092
Ice-coating daily newspaper: checking the ice melting information of the line, including ice melting line, device condition and implementation time; icing for querying manual ice observation condition and manual fillingAnd (4) carrying out daily report and on-site ice coating inspection condition information and conditions of each unit every day.
4. Application of the mountain fire scene:
Figure BDA0003073410830000093
monitoring mountain fire: based on big dipper satellite remote sensing monitoring data, mountain fire monitoring devices data and artifical ignition report data, carry out visual show and analysis, the system sends the ignition warning message automatic to the fortune dimension person in charge of nearest circuit, guides it to carry out the work of patrolling the line to provide APP and fill out the function and support the quick feedback field situation of the personnel of patrolling the line, form the closed-loop management of mountain ignition, supplementary service personnel effectively carry out mountain fire and deal with the work.
Figure BDA0003073410830000094
Mountain fire early warning: and (3) evaluating the mountain fire risk within 48 hours in the future according to rainfall, humidity and other change conditions by using meteorological forecast data, issuing mountain fire risk prediction information, and performing short-term and medium-term prediction of the mountain fire risk. Based on the geographical information data of the power transmission corridor, the analysis of the space-time influence of the line closest to the fire point and the tower closest to the fire point is carried out, and the mountain fire grading early warning is carried out according to the corresponding distance range, so that a reference is provided for business personnel to carry out mountain fire line patrol work.
5. Lightning scene application:
Figure BDA0003073410830000095
lightning strike monitoring: based on thunder and lightning detection device data, carry out real-time supervision and analysis to information such as the thunderbolt position, the thunderbolt time, current amplitude, positive and negative polarity, the detection station quantity of falling the thunder and lightning, based on map show regional thunder and lightning distribution situation, intelligence analysis goes out the thunderbolt and transmits electricity corridor distance, judges out the transmission line that falls the thunder and lightning and influence through the distance. And (4) dotting and displaying according to different colors according to the lightning strike time, and comprehensively reflecting the lightning strike distribution in the area from two dimensions of time and space by combining the lightning strike position.
Figure BDA0003073410830000096
Equipment influence analysis: based on the lightning information, the distribution condition of the power grid equipment is fused, the power transmission equipment such as lines and towers affected in the range is analyzed and counted according to different buffer distances, and service personnel are supported to quickly know the lightning influence condition.
Figure BDA0003073410830000101
Tripping the line: and accessing the line trip information, intelligently diagnosing the line trip according to relevant information such as lightning falling distribution positions, lightning current amplitudes, the number of lightning detection stations, line voltage grades, design resistance and the like around the line, and intelligently judging whether the line trip is a lightning stroke trip or not and judging whether the line trip is a lightning stroke trip type or not. And (4) judging the abnormality of counterattack/shielding failure by combining the lightning-resistant horizontal value of the tower, finally giving a lightning protection improvement measure suggestion, and helping business personnel to quickly locate the trip reason and develop lightning protection work.
Figure BDA0003073410830000102
Lightning stroke reporting: according to the lightning stroke condition of the line, a lightning stroke fault analysis report of the power transmission line is automatically generated, so that the follow-up quick check is facilitated, the lightning protection summary work of business personnel is assisted, and the lightning protection capability of a unit is continuously improved.
6. Waterlogging scene
Figure BDA0003073410830000103
Rainfall early warning: the station house monitoring device data and the external meteorological data are accessed through the Internet of things platform, refined meteorological information is calculated and formed, and hourly rainfall, accumulated rainfall actual conditions and future rainfall forecast and trend are displayed. And counting and displaying all levels of waterlogging risk transformer substations and power distribution rooms in the areas corresponding to the rainfall amounts of different thresholds on a map according to the rainfall information.
Figure BDA0003073410830000104
Early warning of equipment: based on the water level warning information of the refined meteorological information, the intelligent substation and the power distribution room, early warning and statistical visualization display are carried out by combining waterlogging resistance risks. And issuing a real-time alarm to the intelligent power distribution room with the water level reaching a certain threshold value, and marking on a map.
Figure BDA0003073410830000105
Operation early warning: warning an equipment maintenance unit and operation related personnel in advance for the operations of rush repair, construction, power failure and the like which are carried out in an area with waterlogging risk; the construction operation planned to be developed is prompted by the service and weather early warning of equipment is provided, a basis is provided for operation risk assessment, high-risk operation is avoided, and operation risk level is reduced.
7. Earthquake scene
Figure BDA0003073410830000106
Influence analysis: according to the information of the position, the magnitude of earthquake, the crack degree and the like of the earthquake source, units possibly affected in a certain range by taking the center point of the earthquake source as the center of a circle, and equipment such as a transformer substation, a power transmission line, a power transmission tower and the like are counted, and classification is performed according to the magnitude of the earthquake intensity, so that information support is provided for development of emergency command work, and work such as allocation of resources such as goods and materials, rush-repair personnel and the like is assisted.
8. Geological scene
Figure BDA0003073410830000107
Disaster monitoring: in the sections susceptible to disasters, the earth surface deformation monitoring device is installed to sense satellite monitoring. Sensing and information acquisition are carried out through an Internet of things platform, the deformation of the ground surface around the power transmission line tower is tracked in real time, and multi-dimensional analysis and display are carried out; and (4) constructing a model for the monitored area through geological disaster and hidden danger information analysis, and displaying the deformation trend.
Figure BDA0003073410830000111
Disaster early warning: and reviewing historical geological disasters through analysis data of geological disaster monitoring, analyzing formation mechanism, surface morphology, structural characteristics and development characteristics of geological disasters such as landslides and collapses by using satellite remote sensing images in different periods, and establishing a geological disaster early warning model. And displaying the area which is interpreted by the satellite and is easy to cause the geological disaster, and reminding business personnel to perform early warning protection on the geological disaster by combining the distribution information of the line tower.
Figure BDA0003073410830000112
Geological report: and collecting geological disaster information and equipment damage conditions to generate an equipment damage analysis report. And (4) deeply fusing the geological disaster information and the digital power grid model to form a single-point geological analysis report of the station line point. The method can inquire the occurrence condition of the geological disaster and the surrounding environment condition in a certain area at any time, and provide auxiliary decision analysis for power grid planning.
Fig. 3 shows a disaster analysis processing procedure of the disaster prevention and reduction monitoring and early warning system of the power grid device provided by the present application, which may include the following steps:
step S301, after a business unit included in the business layer is triggered by a user to generate a corresponding disaster analysis processing request; step S302, the service unit transmits the disaster analysis processing request to the message pushing module, step S303, the message pushing module determines a disaster analysis unit corresponding to the triggered service unit based on the disaster analysis processing request, and step S304, and triggers the disaster analysis unit to perform disaster analysis processing for the disaster analysis processing request based on the meteorological data and grid equipment data stored in the data access layer.
It should be understood that different disaster analysis units perform different disaster analysis processes, for example, the mountain fire real-time monitoring disaster analysis unit performs disaster analysis process of mountain fire real-time monitoring, the mountain fire comprehensive study and judgment disaster analysis unit performs disaster analysis process of mountain fire comprehensive study and judgment, and the mountain fire decision command disaster analysis unit performs disaster analysis process of mountain fire decision command.
In the disaster prevention and reduction monitoring and early warning system for the power grid equipment, the disaster prevention and reduction monitoring and early warning system is constructed based on the data access layer, the analysis decision layer and the service layer, wherein the disaster prevention and reduction monitoring and early warning system uniformly acquires various meteorological data and power grid equipment data through the data access layer, and a user can trigger the disaster analysis unit of the corresponding analysis decision layer through the service unit of the service layer to perform disaster analysis processing corresponding to the belonged disaster type by using the corresponding meteorological data and power grid equipment data, so that overall monitoring processing on various meteorological monitoring data is realized, and the disaster prevention and reduction monitoring and early warning efficiency for the power grid equipment is improved.
In one embodiment, the data access layer comprises a big data center; the meteorological data stored in the big data center comprise real-time weather data, historical weather data and forecast weather data, and the power grid equipment data comprise power grid equipment ledger data.
Furthermore, the data access layer also comprises a local database without a firewall between the data access layer and each disaster analysis unit; the local database is used for storing the structured meteorological data acquired from a preset data source system and storing the unstructured ground surface deformation video data, which are acquired from the data source system and are specific to the power grid equipment, in the big data center.
Further, the data source system for providing meteorological data to the local database comprises: the system comprises a lightning positioning system, an icing monitoring system and a mountain fire monitoring system; the data source system for providing the surface deformation video data to the local database comprises: transmission line geological disasters monitor early warning system.
In the embodiment, the large data center and the local database are used for respectively storing the corresponding data related to disaster analysis, so that the data storage format is ensured and the data availability is improved under the condition of reducing the data storage pressure.
Further, the data access layer further includes a GIS platform (Geographic Information System) for storing GIS data; the disaster analysis unit further performs disaster analysis processing for the disaster analysis processing request based on the real-time weather data, the historical weather data, the predicted weather data, the grid equipment ledger data, and the GIS data.
Therefore, if GIS data (such as power grid equipment space geographic information, landform, administrative region and the like) is needed in the disaster analysis and processing process, the GIS data can be called through a GIS platform, so that the normal operation of the disaster analysis and processing is ensured, and the storage pressure of the disaster prevention and reduction monitoring and early warning system of the power grid equipment is reduced.
Further, as shown in fig. 4, each disaster analysis unit of the analysis decision layer, each service unit of the service layer, and the local database are all located in a first area of a preset power grid cloud platform, and there is no firewall between the disaster analysis unit, the service unit, and the local database located in the first area; the GIS platform and the big data center are located in a second area of the power grid cloud platform, and a cross-area firewall is arranged between the first area and the second area; each disaster analysis processing unit accesses, from the first area through the cross-area firewall, the GIS data of the GIS platform located in the second area, and accesses the real-time weather data, the historical weather data, the predicted weather data, and the grid equipment ledger data of the big data center.
Further, a DMZ switch, an external network firewall and an external network device are deployed in a DMZ Zone (isolated Zone) of the power grid cloud platform; the disaster prevention and reduction monitoring and early warning system further comprises an external network access processing device for providing access to an external network device, wherein the external network access processing device is located in the first area, and the first area is further provided with a core switch; and the external network access processing equipment provides corresponding external network access to the external network equipment through the external network firewall sequentially through the core switch and the DMZ switch.
Further, each disaster analysis processing unit accesses, from the first area via the core switch, the GIS data of the GIS platform located in the second area through the cross-area firewall, and accesses the real-time weather data, the historical weather data, the predicted weather data, and the grid equipment ledger data of the big data center.
The disaster analysis unit can be deployed in 2 back-end servers and 5 analysis and calculation servers, and is also deployed with 2 data access servers to be in butt joint with a big data center and a GIS platform. The data server node is equivalent to a local database, and the service unit is deployed in an external network access device (equivalent to a WEB server)
Furthermore, each disaster analysis unit is a disaster analysis unit with a micro-service framework constructed based on the power grid cloud platform.
The power grid cloud platform may include a plurality of micro service components, as shown in fig. 2a, and specifically may include: load balancing, cloud service buses, docker container services, resource orchestration, distributed application services, data management, object storage services, table storage, cloud relational databases, time series databases, cloud database redis, distributed message queues, data transmission services.
It should be understood that, although the steps in the flowcharts of fig. 1 to 4 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 to 4 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages in other steps.
In an embodiment, as shown in fig. 5, there is further provided a disaster prevention and reduction monitoring and early warning apparatus for a power grid device, where a service unit of the disaster prevention and reduction monitoring and early warning apparatus includes: a request generating module 501, configured to be triggered by a user to generate a corresponding disaster analysis processing request; a request sending module 502, configured to send the disaster analysis processing request to the message pushing module. And the message pushing module determines a disaster analysis unit corresponding to the triggered business unit based on the disaster analysis processing request, and triggers the disaster analysis unit to perform disaster analysis processing aiming at the disaster analysis processing request based on the meteorological data and power grid equipment data stored in the data access layer.
In one embodiment, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program: after a business unit included in the business layer is triggered by a user to generate a corresponding disaster analysis processing request, the business unit sends the disaster analysis processing request to the message pushing module, the message pushing module determines a disaster analysis unit corresponding to the triggered business unit based on the disaster analysis processing request, and triggers the disaster analysis unit to perform disaster analysis processing aiming at the disaster analysis processing request based on the meteorological data and power grid equipment data stored in the data access layer.
In one embodiment, the weather data stored in the big data center comprises real-time weather data, historical weather data and forecast weather data, and the grid equipment data comprises grid equipment ledger data.
In one embodiment, the computer device is further configured to perform the steps of: the method comprises the steps of storing structured meteorological data acquired from a preset data source system and storing unstructured surface deformation video data, which are acquired from the data source system and aim at the power grid equipment, in the big data center.
In one embodiment, a data source system for providing meteorological data to the local database comprises: the system comprises a lightning positioning system, an ice coating monitoring system and a mountain fire monitoring system; the data source system for providing the surface deformation video data to the local database comprises: transmission line geological disasters monitor early warning system.
In one embodiment, the data access layer further comprises a GIS platform, and the GIS platform is used for storing GIS data; the computer device is further configured to perform the steps of: and performing disaster analysis processing aiming at the disaster analysis processing request based on the real-time weather data, the historical weather data, the forecast weather data, the power grid equipment ledger data and the GIS data.
In one embodiment, each disaster analysis unit of the analysis decision layer, each service unit of the service layer, and the local database are all located in a first area of a preset power grid cloud platform, and no firewall is located among the disaster analysis units, the service units, and the local database in the first area; the GIS platform and the big data center are located in a second area of the power grid cloud platform, and a cross-area firewall is arranged between the first area and the second area. The computer device is further configured to perform the steps of: and accessing GIS data of the GIS platform in the second area from the first area through the cross-area firewall, and accessing the real-time weather data, the historical weather data, the forecast weather data and the power grid equipment standing book data of the big data center.
In one embodiment, a DMZ switch, an external network firewall and an external network device are deployed in a DMZ zone of the power grid cloud platform; the disaster prevention and reduction monitoring and early warning system further comprises an external network access processing device for providing access to the external network device, wherein the external network access processing device is located in the first area, and the first area is also provided with a core switch; and the external network access processing equipment provides corresponding external network access to the external network equipment through the external network firewall sequentially through the core switch and the DMZ switch.
In one embodiment, the computer device is further configured to perform the steps of: accessing, from the first zone via the core switch through the cross-zone firewall, GIS data of the GIS platform located in the second zone, and accessing the real-time weather data, the historical weather data, the predicted weather data, and the grid equipment ledger data of the big data center.
In one embodiment, each disaster analysis unit is a disaster analysis unit with a micro-service architecture constructed based on the power grid cloud platform.
In one embodiment, the disaster types include a meteorological disaster type, a mountain fire disaster type, a typhoon disaster type, a lightning disaster type, a waterlogging disaster type, an earthquake disaster type, and an icing disaster type;
the business unit belonging to the meteorological disaster type comprises: a weather monitoring and early warning service unit; the business unit belonging to the mountain fire disaster type comprises: the system comprises a mountain fire real-time monitoring business unit, a mountain fire comprehensive study and judgment business unit and a mountain fire decision command business unit; the business unit belonging to the typhoon disaster type comprises: the system comprises a typhoon real-time monitoring service unit, a typhoon early warning analysis service unit, a typhoon damage assessment service unit and a typhoon decision support service unit; the business unit belonging to the type of the lightning disaster comprises: the system comprises a thunder and lightning monitoring and positioning service unit, a thunder and lightning early warning service unit and a thunder and lightning decision support service unit; the service unit belonging to the inland inundation disaster type comprises: the system comprises an inland inundation disaster monitoring service unit, an inland inundation disaster early warning service unit and an inland inundation comprehensive study and judgment service unit; the business unit belonging to the earthquake disaster type comprises: the earthquake real-time monitoring service unit, the earthquake early warning evaluation service unit and the post-earthquake decision support service unit; the business unit belonging to the icing disaster type comprises: the system comprises an icing condition monitoring service unit, an icing influence early warning service unit and an icing comprehensive evaluation service unit.
In the disaster prevention and reduction monitoring and early warning system for the power grid equipment, the disaster prevention and reduction monitoring and early warning system is constructed based on the data access layer, the analysis decision layer and the service layer, wherein the disaster prevention and reduction monitoring and early warning system uniformly acquires various meteorological data and power grid equipment data through the data access layer, and a user can trigger the disaster analysis unit of the corresponding analysis decision layer through the service unit of the service layer to perform disaster analysis processing corresponding to the belonged disaster type by using the corresponding meteorological data and power grid equipment data, so that overall monitoring processing on various meteorological monitoring data is realized, and the disaster prevention and reduction monitoring and early warning efficiency for the power grid equipment is improved.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the respective embodiments described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not to be construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (7)

1. A disaster prevention and reduction monitoring and early warning system of power grid equipment is characterized by comprising the following components: a data access layer, an analysis decision layer and a service layer;
the data access layer is used for storing meteorological data and power grid equipment data;
the analysis decision layer comprises a plurality of disaster analysis units and a message pushing module connected with the plurality of disaster analysis units, wherein each disaster analysis unit has a disaster type, and the disaster analysis units belonging to the same disaster type have different corresponding disaster analysis processes;
the service layer comprises a plurality of service units; each business unit is provided with a disaster type and a disaster analysis unit which is triggered correspondingly; the disaster type of each service unit is consistent with the disaster type of the disaster analysis unit triggered by the service unit, and the disaster analysis units triggered by different service units are different;
after a business unit included in the business layer is triggered by a user to generate a corresponding disaster analysis processing request, the business unit sends the disaster analysis processing request to the message pushing module, the message pushing module determines a disaster analysis unit corresponding to the triggered business unit based on the disaster analysis processing request, and triggers the disaster analysis unit to perform disaster analysis processing aiming at the disaster analysis processing request based on meteorological data and power grid equipment data stored in the data access layer;
the data access layer comprises a big data center; the meteorological data stored in the big data center comprise real-time weather data, historical weather data and predicted weather data, and the power grid equipment data comprise power grid equipment ledger data; the data access layer also comprises a local database without a firewall between the data access layer and each disaster analysis unit; the local database is used for storing structured meteorological data acquired from a preset data source system and storing unstructured surface deformation video data, which are acquired from the data source system and are specific to the power grid equipment, in the big data center; the data source system for providing meteorological data to the local database comprises: the system comprises a lightning positioning system, an icing monitoring system and a mountain fire monitoring system; the data source system for providing the surface deformation video data to the local database comprises: transmission line geological disasters monitor early warning system.
2. The system of claim 1,
the data access layer also comprises a GIS platform, and the GIS platform is used for storing GIS data;
and the disaster analysis unit is also used for carrying out disaster analysis processing aiming at the disaster analysis processing request based on the real-time weather data, the historical weather data, the forecast weather data, the power grid equipment ledger data and the GIS data.
3. The system according to claim 2, wherein each disaster analysis unit of the analysis decision layer, each service unit of the service layer and the local database are all located in a first area of a preset power grid cloud platform, and no firewall is located among the disaster analysis units, the service units and the local database in the first area; the GIS platform and the big data center are located in a second area of the power grid cloud platform, and a cross-area firewall is arranged between the first area and the second area;
and each disaster analysis processing unit accesses GIS data of the GIS platform in the second area from the first area through the cross-area firewall, and accesses the real-time weather data, the historical weather data, the forecast weather data and the power grid equipment ledger data of the big data center.
4. The system of claim 3,
a DMZ switch, an external network firewall and external network equipment are deployed in a DMZ zone of the power grid cloud platform;
the disaster prevention and reduction monitoring and early warning system further comprises an external network access processing device for providing access to the external network device, wherein the external network access processing device is located in the first area, and the first area is also provided with a core switch;
and the external network access processing equipment provides corresponding external network access to the external network equipment through the external network firewall sequentially through the core switch and the DMZ switch.
5. The system of claim 4, wherein each disaster analysis processing unit accesses GIS data of the GIS platform located in the second zone from the first zone via the core switch through the cross-zone firewall and accesses the real-time weather data, the historical weather data, the predicted weather data, and the grid equipment ledger data of the big data center.
6. The system according to claim 3, wherein each disaster analysis unit is a disaster analysis unit with a micro-service architecture built based on the grid cloud platform.
7. The system of claim 1, wherein the disaster types include a weather disaster type, a mountain fire disaster type, a typhoon disaster type, a thunder disaster type, an inland inundation disaster type, an earthquake disaster type, and an icing disaster type;
the disaster analyzing unit belonging to the weather disaster type includes: a meteorological monitoring and early warning disaster analysis unit;
the disaster analysis unit belonging to the mountain fire disaster type includes: the system comprises a mountain fire real-time monitoring disaster analysis unit, a mountain fire comprehensive study and judgment disaster analysis unit and a mountain fire decision and command disaster analysis unit;
the disaster analyzing unit belonging to the typhoon disaster type includes: the system comprises a typhoon real-time monitoring disaster analysis unit, a typhoon early warning and analyzing disaster analysis unit, a typhoon damage assessment disaster analysis unit and a typhoon decision support disaster analysis unit;
the disaster analyzing unit belonging to the lightning disaster type includes: the system comprises a thunder and lightning monitoring and positioning disaster analysis unit, a thunder and lightning early warning disaster analysis unit and a thunder and lightning decision support disaster analysis unit;
the disaster analysis unit belonging to the inland inundation disaster type includes: the system comprises an inland inundation disaster monitoring and analyzing unit, an inland inundation disaster early warning and analyzing unit and an inland inundation comprehensive study and judgment disaster analyzing unit;
the disaster analyzing unit belonging to the seismic disaster type includes: the earthquake real-time monitoring disaster analysis unit, the earthquake early warning and evaluation disaster analysis unit and the decision support disaster analysis unit after the earthquake;
the disaster analyzing unit belonging to the icing disaster type includes: the system comprises an icing condition monitoring disaster analysis unit, an icing influence early warning disaster analysis unit and an icing comprehensive evaluation disaster analysis unit.
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