Power grid operation disaster weather power supply emergency decision control system and method

Abstract

The invention relates to the technical field of power supply network disaster emergency processing, and discloses a power grid operation disaster weather power supply emergency decision control system and method, and the system comprises a power supply network disaster weather emergency inspection processing module, a power supply network disaster weather emergency processing countermeasure analysis module, and a power supply network disaster weather emergency operation control module. Based on an intelligent recognition algorithm, the type of disaster weather in a geographic area where a target power distribution network is located is accurate, emergency inspection equipment information needed for specific disaster weather is scientifically evaluated, and intelligent processing of power grid operation disaster weather power supply emergency decision control is achieved. Target power supply network object disaster emergency inspection path information is accurately searched based on an intelligent search algorithm, and power supply network disaster weather emergency inspection operation is autonomously and efficiently executed in combination with power supply network disaster emergency inspection equipment information, so that power supply emergency inspection operation is efficiently and accurately executed in electric power disaster weather; and the efficiency and reliability of power supply emergency processing in electric power disaster weather are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency response to disasters in power supply networks, and in particular to a power grid operation disaster weather power supply emergency decision control system and method. Background Art

[0002] The power grid emergency response plan for disaster weather mainly includes the following aspects: 1. Early warning and preparation, strengthen coordination and cooperation with the meteorological department, pay close attention to weather changes, issue warning information, and activate the emergency response mechanism; make preparations for disaster weather in advance, including load forecasting, emergency prediction, and notify important users to prepare emergency precautions in advance; 2. Equipment inspection and maintenance, strengthen inspections of power transmission and distribution equipment and substations to ensure that the equipment is in good operating condition; carry out special monitoring of areas prone to icing; complete equipment maintenance and commissioning in advance, such as commissioning of ice melting devices and emergency drills; 3. Emergency response and repair, strictly implement the emergency duty system to ensure that disasters can be reported and handled in a timely manner. , set up an emergency repair team, equip it with necessary repair equipment and materials, ensure rapid response and repair, dynamically replenish emergency material inventory, maintain vehicles, drones and other technical equipment, and ensure the smooth progress of repair work 4. Ensure power supply to important users, give priority to ensuring power supply to important users, such as hospitals, transportation hubs, water supply, heating, gas supply companies, etc., flexibly adjust the operation mode of the power grid to ensure that the power supply of important users is not affected; 5. Training and drills Strengthen emergency training and drills, improve the emergency response capabilities of operation and maintenance repair personnel, carry out paramilitary emergency training, and ensure the efficient operation of the repair team; through the above measures, we can effectively respond to the impact of disaster weather on the power grid and ensure the continuity and reliability of power supply. However, the existing power supply network disaster weather emergency processing system cannot realize the efficient and intelligent execution of power supply network emergency inspection operations based on different disaster weather types, nor can it accurately execute power supply emergency processing operations based on the dangerous characteristic types of disaster weather in the power supply network.

[0003] The Chinese invention patent application with the publication number CN116976594A discloses a method and system for evaluating the disaster response capability of a distribution network. By collecting meteorological data and the grid structure, ledger information, and equipment operation data of the distribution network, the system dynamically evaluates the pre-disaster response capability of the distribution network based on the characteristics of the damage of the distribution network through meteorological data; and combines the results of the dynamic evaluation to construct a feeder outage probability prediction model based on wind disasters, a lightning trip probability analysis model, a high temperature weather conductor time-varying outage model based on numerical weather forecasts, and a variety of weather conditions equipment outage models. This enables the prediction and analysis of disaster weather; however, the above power disaster monitoring simulation system cannot realize the autonomous and accurate execution of power disaster emergency detection and processing operations under different disaster environments. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the problem that the above-mentioned existing power supply network disaster weather emergency response system cannot realize the efficient and intelligent execution of power supply network emergency inspection operations based on different disaster weather types, and cannot accurately execute power supply emergency response operations based on the disaster weather hazard feature types of the power supply network, the above purpose is to accurately analyze the disaster weather type information, intelligently analyze the power supply network emergency inspection path information and emergency inspection equipment, efficiently and accurately execute the power supply network disaster emergency inspection operations, scientifically identify the power supply network disaster weather hazard feature types, accurately evaluate the power supply network disaster weather hazard feature emergency response plan, accurately search for power supply network emergency site objects, and accurately execute power supply emergency response operations.

[0006] (II) Technical solution

[0007] The present invention is implemented by the following technical scheme: a method for emergency decision-making and control of power supply in disaster weather of power grid operation, the method comprising the following steps:

[0008] S1. Collecting text data of power supply network object characteristics and text data of power supply network geographical weather characteristics;

[0009] S2. Analyze and process the disaster weather type of the geographical area where the power supply network is located based on the power supply network geographical weather characteristic text data and different types of disaster weather characteristic text data, and generate power supply network geographical disaster weather type analysis data; if no analysis data exists, directly terminate the power supply emergency processing operation;

[0010] S3. When it exists, analyze and process the information of emergency equipment required for disaster weather of the power supply network according to the power supply network geographical disaster weather type analysis data and the text data of emergency inspection equipment required for different types of disaster weather, and generate text data of disaster emergency inspection equipment for the power supply network;

[0011] S4, based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects, the disaster emergency inspection path data of the target power supply network object is analyzed and processed, and the disaster emergency inspection path data of the power supply network object is generated, and the power supply network disaster emergency inspection equipment text data is combined to perform the power supply network disaster weather emergency inspection operation;

[0012] S5, collecting the real-time image data of the power supply network disaster inspection and performing the dangerous feature object recognition processing of the power supply network in the disaster weather with the different dangerous feature image data of the power supply network disaster weather, and generating the dangerous feature recognition data of the power supply network disaster weather; if it does not exist, continue to perform the emergency inspection operation of the power supply network disaster weather until it is completed;

[0013] S6. When it exists, the emergency treatment plan identification processing of the power supply network disaster weather hazard feature object is performed according to the power supply network disaster weather hazard feature identification data and the power supply network disaster weather different hazard feature emergency treatment plan data, and the power supply network disaster weather hazard feature emergency treatment plan data is generated;

[0014] S7, collecting real-time spatial coordinate data of power supply network disaster emergency inspection and analyzing the optimal emergency site object required for power supply network disaster weather emergency treatment with the spatial coordinate data of the power supply network emergency site object, and generating power supply network disaster emergency optimal site object analysis data;

[0015] S8. Construct power supply network emergency handling guidance text data and execute power supply emergency handling operations.

[0016] Preferably, the operation steps of collecting the power supply network object characteristic text data and the power supply network geographical weather characteristic text data are as follows:

[0017] S11, collecting the name, line number and tower number text information of the target power supply network line online through the power monitoring platform and generating power supply network object feature text data Y;

[0018] The weather characteristic text information of the geographical area where the target power supply network line is located is collected online through the weather monitoring sensor and the power supply network geographical weather characteristic text data Z is generated. The weather monitoring sensor includes a temperature sensor, a humidity sensor, a wind direction and wind speed sensor and a precipitation measuring instrument. The power supply network geographical weather characteristic text data includes temperature text data, humidity text data, wind direction and wind speed text data and precipitation text data.

[0019] Preferably, the disaster weather type analysis and processing of the geographical area where the power supply network is located is performed based on the power supply network geographical weather characteristic text data and different types of disaster weather characteristic text data to generate power supply network geographical disaster weather type analysis data; when the power supply network geographical disaster weather type analysis data does not exist, the operation steps of directly ending the power supply emergency processing operation are as follows:

[0020] S21. Establish different types of disaster weather feature text data sets A = (a1,…,a o ,…,a ε ), o=1,2,3,…,ε; where a o represents the characteristic text data of different types of disaster weather corresponding to the oth type of disaster weather, ε represents the maximum number of disaster weather types, and the disaster weather types include typhoon weather, frost weather, flood weather, hail weather, blizzard weather and drought weather; the characteristic text data of different types of disaster weather represent the geographical weather characteristic text data corresponding to different types of disaster weather;

[0021] S22, compare the power grid geographical weather feature text data Z with the different types of disaster weather feature text data a in the different types of disaster weather feature text data set A. o Perform weather characteristic character matching to search for the different types of disaster weather characteristic text data a that match the power grid geographic weather characteristic text data Z o The corresponding disaster weather type is constructed, and the power supply network geographical disaster weather type analysis data A′ is constructed. The specific operation steps for generating the power supply network geographical disaster weather type analysis data A′ are as follows:

[0022] S221, initializing parameters and updating the maximum number of iterations T of the algorithm;

[0023] S222, initializing the position of the disaster weather identification seagull population, that is, updating the position of the disaster weather identification seagull population in the search space of the different types of disaster weather feature text data set A;

[0024] S223, calculate all the different types of disaster weather feature text data a in the different types of disaster weather feature text data set A. o and the fitness value of the power grid geographic weather feature text data Z, and retain the different types of disaster weather feature text data a with the largest fitness value with the power grid geographic weather feature text data Z in the search space of the different types of disaster weather feature text data set A o The global optimal position of

[0025] S224, migration, global search: The migration behavior of disaster weather identification seagulls mainly has three steps. The first is to meet the condition of avoiding collision between different disaster weather identification seagulls in the search space of the different types of disaster weather feature text data set A; the second is to calculate the different types of disaster weather feature text data a that match the power grid geographic weather feature text data Z in the search space of the different types of disaster weather feature text data set A. o The best location direction; third according to the power grid geographical weather characteristics text data Z matching the different types of disaster weather characteristics text data a o Move the direction of the best position to a new position;

[0026] S2241, calculating the new position J'(t) of the disaster weather identification seagull in the search space of the different types of disaster weather feature text data set A without colliding with the adjacent disaster weather identification seagull; J'(t) = ▽ × J(t), Where J(t) represents the current position of the disaster weather identification seagull in the search space of the different types of disaster weather feature text data set A, t represents the current iteration number; ▽ represents the motion behavior control factor of the disaster weather identification seagull in the space of the different types of disaster weather feature text data set A; represents the function that controls the frequency of changes in ▽, and T represents the maximum number of iterations;

[0027] S2242, calculating the different types of disaster weather feature text data a that matches the power grid geographic weather feature text data Z in the search space of the different types of disaster weather feature text data set A. o The optimal position direction X(t); X(t) = Π×(J best (t)-J(t)), Π=2×▽ 2 ×l, where J best (t) indicates that the different types of disaster weather feature text data set A is searched for the different types of disaster weather feature text data a that matches the power grid geographic weather feature text data Z in the search space. o The current best position of , J(t) is the current position of the disaster weather identification seagull in the search space of the different types of disaster weather feature text data set A; Π represents a random number that balances the global and local search capabilities, and l represents a random number in the interval [0,1];

[0028] S2243, according to the different types of disaster weather feature text data a that best matches the power grid geographical weather feature text data Z. o The direction of the optimal position is moved to a new position M(t), M(t) = |J'(t) + X(t)|, that is, according to the direction of the optimal position, the different types of disaster weather feature text data a matching the power grid geographic weather feature text data Z are searched in the search space of the different types of disaster weather feature text data set A. o new location;

[0029] S225. Attacking prey, local search, and identifying disaster weather. When attacking prey in the search space of the different types of disaster weather feature text data set A, the seagull performs spiral motion in the air. The new position of the disaster weather identifying seagull after attacking the prey is M'(t), M'(t) = M(t) + J. best (t), that is, the disaster weather recognition seagull searches for the different types of disaster weather feature text data a that matches the power grid geographic weather feature text data Z in the search space of the different types of disaster weather feature text data set A. o of prey;

[0030] S226: Determine whether the maximum number of iterations is met, and then output the different types of disaster weather feature text data a that best matches the power grid geographic weather feature text data Z. o ; If not satisfied, return to step S223;

[0031] S227, the different types of disaster weather characteristic text data a that best matches the power grid geographical weather characteristic text data Z output according to step S226 o Corresponding disaster weather types, and constructing the power grid geographical disaster weather type analysis data A′;

[0032] When Z and a o If the weather feature character matching is successful, it means that disaster weather occurs in the geographical area where the target power supply network line is located, then the power supply network geographical disaster weather type analysis data A′ is output as existing, and the disaster weather type is output;

[0033] When Z and a o If no weather characteristic characters are matched successfully, it means that no disaster weather occurs in the geographical area where the target power supply network line is located, and the output power supply network geographical disaster weather type analysis data A′ is non-existent, and the power supply emergency processing operation is directly terminated.

[0034] Preferably, when it exists, the operation steps of analyzing and processing the information of emergency equipment required for disaster weather of the power supply network are performed according to the power supply network geographical disaster weather type analysis data and the text data of emergency inspection equipment required for different types of disaster weather, and generating the text data of disaster emergency inspection equipment for the power supply network are as follows:

[0035] S31. Establish the text data set B of emergency inspection equipment required for different types of disaster weather = (b1,…,b o ,…,b ε ), where b o Represents text data of emergency inspection equipment required for different types of disaster weather corresponding to the oth type of disaster weather; the text data of emergency inspection equipment required for different types of disaster weather represents information of emergency inspection equipment required to deal with different types of disaster weather, and the emergency inspection equipment includes drones, shooting lenses, location sensors and weather monitoring sensors;

[0036] S32, when the power grid geographical disaster weather type analysis data A' exists, the KD tree nearest neighbor search algorithm is used to compare the power grid geographical disaster weather type analysis data A' with the text data set B of the emergency inspection equipment required for different types of disaster weather, the text data set B of the emergency inspection equipment required for different types of disaster weather, and the text data set B of the emergency inspection equipment required for different types of disaster weather. oPerform disaster weather type keyword matching to search for the emergency inspection equipment text data b required for different types of disaster weather corresponding to the power grid geographical disaster weather type analysis data A′ o , and construct the power supply network disaster emergency inspection equipment text data b".

[0037] Preferably, the disaster emergency inspection path analysis and processing of the target power supply network object is performed based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects, the disaster emergency inspection path data of the power supply network object is generated, and the operation steps of performing the power supply network disaster weather emergency inspection operation in combination with the power supply network disaster emergency inspection equipment text data are as follows:

[0038] S41. Establish emergency inspection path data set C = (c1, ..., c p ,…,c φ ), p=1,2,3,…,φ; where c p represents the emergency inspection path data of different power supply network objects corresponding to the p-th power supply network object, φ represents the maximum number of power supply network objects, and the emergency inspection path data of different power supply network objects represent the standard path data of emergency inspection operations performed on different power supply network lines under disaster weather conditions;

[0039] S42, using a breadth-first search algorithm to compare the power supply network object feature text data Y with the different power supply network object emergency inspection path data c in the different power supply network object emergency inspection path data set C. p Perform a keyword search for power supply network object characteristics, and analyze the emergency inspection path data c of different power supply network objects corresponding to the power supply network object characteristic text data Y. p And construct the disaster emergency inspection path data c′ of the power supply network object;

[0040] S43, the emergency inspection equipment performs the power supply network disaster weather emergency inspection operation according to the emergency inspection equipment corresponding to the power supply network disaster emergency inspection equipment text data b" and the emergency inspection path corresponding to the power supply network object disaster emergency inspection path data c'.

[0041] Preferably, the steps of collecting the real-time image data of the power supply network disaster inspection and performing the dangerous feature object identification processing of the power supply network in the disaster weather with the different dangerous feature image data of the power supply network disaster weather to generate the dangerous feature identification data of the power supply network disaster weather; when it does not exist, continuing to perform the emergency inspection operation of the power supply network disaster weather until completion are as follows:

[0042] S51. During the emergency inspection of the power grid during disaster weather, the real-time status images of the target power grid lines and power equipment are collected online through the camera mounted on the drone, and a data set of real-time images of the power grid disaster inspection is generated. where d u represents the u-th collected real-time image data of power grid disaster inspection, Indicates the maximum number of live images of power grid disaster inspection;

[0043] S52, establish a power grid disaster weather different dangerous characteristics image data set E = (e1, ..., e v ,…,e γ ), v = 1, 2, 3, ..., γ; where e v represents the different dangerous feature image data of the power grid disaster weather corresponding to the vth power grid disaster weather dangerous feature type, γ represents the maximum number of power grid disaster weather dangerous feature types, and the power grid disaster weather dangerous feature types include snow accumulation on the power grid line, temperature overload of the power grid line, swing amplitude overload of the power grid line, lightning strike on the power grid electric equipment, and swing of the power grid line contacting trees;

[0044] S53, the power supply network disaster inspection live image data set D is u The power grid disaster weather different dangerous feature image data set E of the power grid disaster weather different dangerous feature image data e v Perform image feature matching, and generate power grid disaster weather hazard feature identification data D′ based on the image feature matching results;

[0045] When u With e v If the image feature matching is successful, it means that there are disaster weather hazard features in the target power supply network line at the current location, then the power supply network disaster weather hazard feature identification data D′ is output as existence, and the power supply network disaster weather hazard feature type is output;

[0046] When u With e v If the image features are not matched successfully, it means that there is no disaster weather hazard feature in the target power supply network line at the current location, and the output power supply network disaster weather hazard feature identification data D′ is non-existent. At this time, continue to execute step S43 until the power supply network disaster weather emergency inspection operation is completed.

[0047] Preferably, when present, the emergency treatment plan identification processing of the power supply network disaster weather hazard feature object is performed according to the power supply network disaster weather hazard feature identification data and the power supply network disaster weather different hazard feature emergency treatment plan data, and the operation steps of generating the power supply network disaster weather hazard feature emergency treatment plan data are as follows:

[0048] S61. Establish a data set of emergency response plans for different dangerous characteristics of disaster weather in the power supply network E'=(e'1,…,e' v ,…,e' γ ), where e' v Represents emergency response plan data of different dangerous characteristics of disaster weather in the power supply network corresponding to the vth type of dangerous characteristics of disaster weather in the power supply network, wherein the emergency response plan data of different dangerous characteristics of disaster weather in the power supply network represents standard emergency response plan data corresponding to a specific type of dangerous characteristics of disaster weather in the power supply network;

[0049] S62, when the power grid disaster weather hazard feature identification data D' exists, a breadth-first search algorithm is used to compare the power grid disaster weather hazard feature identification data D' with the power grid disaster weather different hazard feature emergency treatment plan data set E'. v Perform character matching on the type of disaster weather hazard feature of the power grid, and search for the emergency treatment plan data e′ of different hazard features of disaster weather in the power grid corresponding to the disaster weather hazard feature identification data D′ of the power grid v , and generate emergency response plan data for disaster weather hazard characteristics of power supply network through data identification

[0050] Preferably, the operation steps of collecting the real-time spatial coordinate data of the power supply network disaster emergency inspection and performing optimal emergency site object analysis and processing required for the power supply network disaster weather emergency treatment with the spatial coordinate data of the power supply network emergency site object to generate the optimal site object analysis data for the power supply network disaster emergency are as follows:

[0051] S71, collecting spatial coordinate information of emergency inspection equipment with disaster weather hazard characteristics in the target power supply network line through a position sensor online and generating real-time spatial coordinate data f of emergency inspection of disasters in the power supply network, wherein the real-time spatial coordinate data f of emergency inspection of disasters in the power supply network includes the longitude, latitude and altitude of the space where the emergency inspection equipment is located;

[0052] S72: Establishing the spatial coordinate data set H of the power supply network emergency site object = (h1, ..., h n ,…,h η ), n=1,2,3,…,η; where h nrepresents the spatial coordinate data of the nth power supply network emergency site object, n represents the maximum number of power supply network emergency sites, the power supply network emergency site object spatial coordinate data represents the spatial coordinate data of the power supply network emergency maintenance site used to perform power supply emergency processing operations, and the power supply network emergency site object spatial coordinate data includes the longitude, latitude and altitude of the power supply network emergency site;

[0053] S73, using the spatial distance formula to measure the real-time spatial coordinate data f of the power supply network disaster emergency inspection and the spatial coordinate data h of the power supply network emergency site object in the power supply network emergency site object spatial coordinate data set H. n The distance value is obtained and the distance data set G = (g1,…,g n ,…,g η ), where g n represents the real-time spatial coordinate data f of the power supply network disaster emergency inspection and the spatial coordinate data h of the power supply network emergency site object n Corresponding power grid emergency inspection location and emergency site distance data, g n The unit is kilometers;

[0054] S74: the power supply network emergency inspection position and emergency site distance data set G are n Compare the distance values ​​and search for the distance data g between the emergency inspection location of the power supply network and the emergency site with the smallest distance value. n and the power supply network emergency site object spatial coordinate data set H of the power supply network emergency site object spatial coordinate data h n According to the number matching of the power supply network emergency site, search for the distance data g between the power supply network emergency inspection location and the emergency site with the smallest distance value. n The matching spatial coordinate data h of the power grid emergency site object n The corresponding power supply network emergency site object is identified through data identification to generate the power supply network disaster emergency optimal site object analysis data H′.

[0055] Preferably, the steps of constructing the power supply network emergency processing guidance text data and executing the power supply emergency processing operation are as follows:

[0056] S81, the power supply network disaster weather hazard feature identification data D′, the power supply network disaster weather hazard feature emergency treatment plan data The power grid disaster emergency optimal site object analysis data H is combined to construct the power grid emergency treatment guidance text data

[0057] S82. The power supply network emergency processing guidance text data K is transmitted to the power supply network emergency site through the Internet of Things communication network, and the internal staff of the power supply network emergency site performs power supply emergency processing operations.

[0058] A power grid operation disaster weather power supply emergency decision-making control system, used to implement the power grid operation disaster weather power supply emergency decision-making control method, the system includes a power grid disaster weather emergency inspection processing module, a power grid disaster weather emergency processing countermeasures analysis module, and a power grid disaster weather emergency operation control module;

[0059] The power supply network disaster weather emergency inspection processing module includes a power supply network object information collection unit, a power supply network geographical weather feature information collection unit, a different type of disaster weather feature information storage unit, a disaster weather type analysis unit, a different type of disaster weather required emergency inspection equipment information storage unit, a disaster weather emergency inspection equipment information analysis unit, different power supply network object emergency inspection path storage unit, power supply network object emergency inspection path analysis unit, power supply network disaster emergency inspection operation execution unit;

[0060] The power supply network object information collection unit collects power supply network object feature text data through the power monitoring platform; the power supply network geographic weather feature information collection unit collects power supply network geographic weather feature text data through weather monitoring sensors; the different types of disaster weather feature information storage unit stores different types of disaster weather feature text data based on big data; the disaster weather type analysis unit performs disaster weather type analysis and processing in the geographical area where the power supply network is located based on the power supply network geographic weather feature text data and different types of disaster weather feature text data, and generates power supply network geographic disaster weather type analysis data; the different types of disaster weather required emergency inspection equipment information storage unit is used to store different types of disaster weather required emergency inspection equipment text data based on big data; the disaster weather emergency inspection equipment information analysis unit, According to the power supply network geographical disaster weather type analysis data and the text data of emergency inspection equipment required for different types of disaster weather, the information of emergency equipment required for disaster weather of the power supply network is analyzed and processed to generate text data of disaster emergency inspection equipment of the power supply network; the emergency inspection path storage unit of different power supply network objects is used to store emergency inspection path data of different power supply network objects; the power supply network object emergency inspection path analysis unit performs disaster emergency inspection path analysis and processing of target power supply network objects based on the power supply network object feature text data and emergency inspection path data of different power supply network objects to generate disaster emergency inspection path data of power supply network objects; the power supply network disaster emergency inspection operation execution unit executes power supply network disaster weather emergency inspection operations according to the power supply network object disaster emergency inspection path data and the text data of disaster emergency inspection equipment of the power supply network;

[0061] The power grid disaster weather emergency response countermeasures analysis module includes a power grid disaster inspection real-time image acquisition unit, a power grid disaster weather different dangerous characteristics image storage unit, a power grid disaster weather dangerous characteristics information identification unit, a power grid disaster weather different dangerous characteristics emergency response plan storage unit, and a power grid disaster weather dangerous characteristics emergency response plan identification unit;

[0062] The power supply network disaster inspection live image acquisition unit is used to collect live image data of the power supply network disaster inspection through a camera mounted on an unmanned aerial vehicle; the power supply network disaster weather different dangerous characteristics image storage unit is used to store image data of different dangerous characteristics of the power supply network disaster weather based on big data; the power supply network disaster weather dangerous characteristics information identification unit performs dangerous characteristics object identification processing of the power supply network in disaster weather based on the live image data of the power supply network disaster inspection and the image data of different dangerous characteristics of the power supply network disaster weather, and generates power supply network disaster weather dangerous characteristics identification data; the power supply network disaster weather different dangerous characteristics emergency treatment plan storage unit is used to store emergency treatment plan data of different dangerous characteristics of the power supply network disaster weather based on big data; the power supply network disaster weather dangerous characteristics emergency treatment plan identification unit performs emergency treatment plan identification processing of the power supply network disaster weather dangerous characteristics object based on the power supply network disaster weather dangerous characteristics identification data and the power supply network disaster weather different dangerous characteristics emergency treatment plan data, and generates power supply network disaster weather dangerous characteristics emergency treatment plan data;

[0063] The power supply network disaster weather emergency operation control module includes a power supply network disaster emergency inspection location collection unit, a power supply network emergency site location storage unit, a power supply network emergency processing site object analysis unit, and a power supply emergency processing operation execution unit;

[0064] The power supply network disaster emergency inspection position acquisition unit collects real-time spatial coordinate data of the power supply network disaster emergency inspection through a position sensor; the power supply network emergency site position storage unit is used to store the spatial coordinate data of the power supply network emergency site object; the power supply network emergency processing site object analysis unit performs optimal emergency site object analysis and processing required for power supply network disaster weather emergency processing based on the real-time spatial coordinate data of the power supply network disaster emergency inspection and the spatial coordinate data of the power supply network emergency site object, and generates power supply network disaster emergency optimal site object analysis data; the power supply emergency processing operation execution unit is used to construct the power supply network emergency processing guidance text data and execute the power supply emergency processing operation.

[0065] (III) Beneficial effects

[0066] The present invention provides a power grid operation disaster weather power supply emergency decision control system and method. It has the following beneficial effects:

[0067] 1. Accurately obtain the target power supply network object characteristic information and geographic weather characteristic information through the power monitoring platform and weather monitoring sensors, and provide reliable data for the subsequent accurate analysis of disaster weather types, emergency inspection equipment and distribution network disaster inspection paths; accurately identify the type of disaster weather occurring in the geographical area where the target distribution network is located based on the intelligent recognition algorithm, and scientifically evaluate the emergency inspection equipment information required for specific disaster weather, so as to realize the intelligent processing of power grid operation disaster weather power supply emergency decision-making and control; accurately search for the target power supply network object disaster emergency inspection path information based on the intelligent search algorithm, and combine the power supply network disaster emergency inspection equipment information to autonomously and efficiently perform the power supply network disaster weather emergency inspection operations, so as to realize the efficient and accurate execution of power supply emergency inspection operations in power disaster weather, and improve the efficiency and reliability of power supply emergency handling in power disaster weather.

[0068] 2. By using the drone-mounted camera to dynamically collect the real-time image parameters of the power supply network disaster inspection and compare them with the image parameters of different dangerous characteristics of the power supply network in disaster weather, scientific online analysis of the dangerous characteristic objects of the power supply network in disaster weather can be carried out, so as to realize the intelligent analysis of the dangerous characteristics of power supply in disaster weather of the distribution network, and improve the accuracy of emergency response to power disaster weather; scientifically evaluate the emergency response plan information of different dangerous characteristics in disaster weather of the distribution network, realize accurate analysis of the emergency response plan of dangerous characteristics of disaster weather of the power supply network, and improve the quality and scientificity of emergency response to power disaster weather.

[0069] 3. Accurately collect the real-time spatial coordinates of the power supply network disaster emergency inspection and the spatial coordinates of the power supply network emergency site objects through position sensors, and combine numerical analysis to scientifically identify the power supply network emergency site objects with the shortest distance, so as to achieve the response speed and precise dispatching command of the distribution network disaster emergency response; scientifically construct the power supply network emergency response guidance information and independently and accurately feedback it to the power supply network emergency site objects, accurately and efficiently execute the power supply emergency response operations, and improve the applicability and efficiency of the power disaster weather emergency response operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A schematic diagram of a module of a power grid operation disaster weather power supply emergency decision-making control system provided by the present invention;

[0071] Figure 2 A flow chart of a method for emergency decision-making and control of power supply during disaster weather for power grid operation provided by the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] The embodiments of the power grid operation disaster weather power supply emergency decision control system and method are as follows:

[0074] Embodiment 1:

[0075] See also Figure 1 - Figure 2 , a power grid operation disaster weather power supply emergency decision-making control method, the method comprises the following steps:

[0076] S1. Collecting text data of power supply network object characteristics and text data of power supply network geographical weather characteristics;

[0077] S2. Analyze and process the disaster weather type of the geographical area where the power supply network is located based on the text data of geographical weather characteristics of the power supply network and the text data of characteristics of different types of disaster weather, and generate the analysis data of geographical disaster weather type of the power supply network; if it does not exist, directly terminate the power supply emergency processing operation;

[0078] S3. When it exists, analyze and process the information of emergency equipment required for disaster weather of the power supply network according to the analysis data of geographical disaster weather types of the power supply network and the text data of emergency inspection equipment required for different types of disaster weather, and generate text data of disaster emergency inspection equipment for the power supply network;

[0079] S4, based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects, the disaster emergency inspection path data of the target power supply network object is analyzed and processed, and the disaster emergency inspection path data of the power supply network object is generated, and the power supply network disaster emergency inspection equipment text data is combined to perform the power supply network disaster weather emergency inspection operation;

[0080] S5, collecting the real-time image data of the power supply network disaster inspection and performing the dangerous feature object recognition processing of the power supply network in the disaster weather with the different dangerous feature image data of the power supply network disaster weather, and generating the dangerous feature recognition data of the power supply network disaster weather; if it does not exist, continue to perform the emergency inspection operation of the power supply network disaster weather until it is completed;

[0081] S6. When it exists, the emergency treatment plan identification processing of the power supply network disaster weather hazard feature object is performed according to the power supply network disaster weather hazard feature identification data and the power supply network disaster weather different hazard feature emergency treatment plan data, and the power supply network disaster weather hazard feature emergency treatment plan data is generated;

[0082] S7, collecting real-time spatial coordinate data of power supply network disaster emergency inspection and analyzing the optimal emergency site object required for power supply network disaster weather emergency treatment with the spatial coordinate data of the power supply network emergency site object, and generating power supply network disaster emergency optimal site object analysis data;

[0083] S8. Construct power supply network emergency handling guidance text data and execute power supply emergency handling operations.

[0084] For further information, see Figure 1 - Figure 2 The steps for collecting the text data of power supply network object characteristics and the text data of power supply network geographical weather characteristics are as follows:

[0085] S11, collecting the name, line number and tower number text information of the target power supply network line online through the power monitoring platform and generating power supply network object feature text data Y;

[0086] The weather characteristic text information of the geographical area where the target power supply network line is located is collected online through weather monitoring sensors and the power supply network geographical weather characteristic text data Z is generated. The weather monitoring sensors include temperature sensors, humidity sensors, wind direction and wind speed sensors and precipitation measuring instruments. The power supply network geographical weather characteristic text data includes temperature text data, humidity text data, wind direction and wind speed text data and precipitation text data.

[0087] According to the text data of geographical weather characteristics of the power supply network and the text data of characteristics of different types of disaster weather, the disaster weather type analysis and processing of the geographical area where the power supply network is located is carried out to generate the analysis data of geographical disaster weather type of the power supply network; when it does not exist, the operation steps of directly ending the power supply emergency processing operation are as follows:

[0088] S21. Establish different types of disaster weather feature text data sets A = (a1,…,a o ,…,a ε ), o=1,2,3,…,ε; where a o represents the characteristic text data of different types of disaster weather corresponding to the oth type of disaster weather, ε represents the maximum number of disaster weather types, and the disaster weather types include typhoon weather, frost weather, flood weather, hail weather, blizzard weather and drought weather; the characteristic text data of different types of disaster weather represents the geographical weather characteristic text data corresponding to different types of disaster weather;

[0089] S22, compare the geographical weather feature text data Z of the power grid with the different types of disaster weather feature text data a in the different types of disaster weather feature text data set A. o Perform weather feature character matching to search for different types of disaster weather feature text data a that match the power grid geographic weather feature text data Zo The corresponding disaster weather type is constructed, and the power supply network geographical disaster weather type analysis data A′ is constructed. The specific operation steps for generating the power supply network geographical disaster weather type analysis data A′ are as follows:

[0090] S221, initializing parameters and updating the maximum number of iterations T of the algorithm;

[0091] S222, initializing the position of the disaster weather identification seagull population, that is, updating the position of the disaster weather identification seagull population in the search space of the different types of disaster weather feature text data sets A;

[0092] S223, calculate all the different types of disaster weather feature text data a in the different types of disaster weather feature text data set A. o The fitness value of the geographical weather feature text data Z of the power grid is retained, and the different types of disaster weather feature text data a with the largest fitness value of the geographical weather feature text data Z of the power grid is retained in the search space of the different types of disaster weather feature text data set A. o The global optimal position of

[0093] S224, Migration, Global Search: The migration behavior of disaster weather identification seagulls mainly has three steps. The first is to meet the conditions of avoiding collision between different disaster weather identification seagulls in the search space of different types of disaster weather feature text data sets A; the second is to calculate the different types of disaster weather feature text data a that match the power grid geographic weather feature text data Z in the search space of different types of disaster weather feature text data sets A; o The best location direction; third, according to the different types of disaster weather characteristics text data Z matching the power grid geographic weather characteristics text data a o Move the direction of the best position to a new position;

[0094] S2241. Calculate the new position J'(t) of the disaster weather recognition seagull in the search space of the different types of disaster weather feature text data sets A without colliding with the adjacent disaster weather recognition seagull; J'(t) = ▽ × J(t), Where J(t) represents the current position of the disaster weather recognition seagull in the search space of different types of disaster weather feature text data set A, t represents the current iteration number; ▽ represents the motion behavior control factor of the disaster weather recognition seagull in the space of different types of disaster weather feature text data set A; represents the function that controls the frequency of changes in ▽, and T represents the maximum number of iterations;

[0095] S2242, calculate different types of disaster weather feature text data a that match the power grid geographic weather feature text data Z in the search space of different types of disaster weather feature text data sets A.o The optimal position direction X(t); X(t) = Π×(J best (t)-J(t)), Π=2×▽ 2 ×l, where J best (t) represents the search space of different types of disaster weather feature text data set A to find different types of disaster weather feature text data a that matches the power grid geographic weather feature text data Z. o The current best position of , J(t) is the current position of the disaster weather identification seagull in the search space of different types of disaster weather feature text data set A; Π represents a random number that balances global and local search capabilities, and l represents a random number in the interval [0,1];

[0096] S2243, based on the different types of disaster weather feature text data a that best matches the power grid geographic weather feature text data Z. o The direction of the optimal position is moved to the new position M(t), M(t) = |J'(t) + X(t)|, that is, according to the direction of the optimal position, different types of disaster weather feature text data a matching the power grid geographic weather feature text data Z are searched in the search space of different types of disaster weather feature text data set A. o new location;

[0097] S225. Attacking prey, local search, and disaster weather recognition. When attacking prey in the search space of different types of disaster weather feature text data sets A, the seagull performs spiral motion in the air. The new position of the disaster weather recognition seagull after attacking the prey is M'(t), M'(t) = M(t) + J best (t), that is, the disaster weather recognition seagull searches for different types of disaster weather feature text data a that matches the power grid geographic weather feature text data Z in the search space of different types of disaster weather feature text data set A. o of prey;

[0098] S226: Determine whether the maximum number of iterations is met, and then output different types of disaster weather feature text data a that best matches the power grid geographic weather feature text data Z. o ; If not satisfied, return to step S223;

[0099] S227, different types of disaster weather feature text data a that best matches the power grid geographic weather feature text data Z output according to step S226 o Corresponding disaster weather types, and constructing the power grid geographical disaster weather type analysis data A′;

[0100] When Z and a oIf the weather feature character matching is successful, it means that disaster weather occurs in the geographical area where the target power supply network line is located, then the power supply network geographical disaster weather type analysis data A′ is output as existing, and the disaster weather type is output;

[0101] When Z and a o If no weather characteristic characters are matched successfully, it means that no disaster weather occurs in the geographical area where the target power supply network line is located, and the output power supply network geographical disaster weather type analysis data A′ is non-existent, and the power supply emergency processing operation is directly terminated.

[0102] When it exists, the information of emergency equipment required for disaster weather of the power supply network is analyzed and processed according to the analysis data of geographical disaster weather types of the power supply network and the text data of emergency inspection equipment required for different types of disaster weather. The operation steps for generating text data of disaster emergency inspection equipment of the power supply network are as follows:

[0103] S31. Establish the text data set B of emergency inspection equipment required for different types of disaster weather = (b1,…,b o ,…,b ε ), where b o The text data of emergency inspection equipment required for different types of disaster weather corresponding to the oth type of disaster weather; the text data of emergency inspection equipment required for different types of disaster weather represents the information of emergency inspection equipment required to deal with different types of disaster weather. The emergency inspection equipment includes drones, shooting lenses, location sensors and weather monitoring sensors;

[0104] S32, when the power grid geographical disaster weather type analysis data A' exists, the KD tree nearest neighbor search algorithm is used to compare the power grid geographical disaster weather type analysis data A' with the different types of disaster weather required emergency inspection equipment text data set B. o Perform keyword matching of disaster weather types and search for the text data b of emergency inspection equipment required for different types of disaster weather corresponding to the power grid geographical disaster weather type analysis data A′ o , and construct the power supply network disaster emergency inspection equipment text data b".

[0105] The operation steps of analyzing and processing the disaster emergency inspection path of the target power supply network object based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects, generating the disaster emergency inspection path data of the power supply network object and combining the power supply network disaster emergency inspection equipment text data to perform the power supply network disaster weather emergency inspection operation are as follows:

[0106] S41. Establish emergency inspection path data set C = (c1, ..., c p ,…,c φ), p=1,2,3,…,φ; where c p represents the emergency inspection path data of different power supply network objects corresponding to the p-th power supply network object, φ represents the maximum number of power supply network objects, and the emergency inspection path data of different power supply network objects represent the standard path data of emergency inspection operations performed on different power supply network lines under disaster weather conditions;

[0107] S42, using a breadth-first search algorithm to compare the power supply network object feature text data Y with the different power supply network object emergency inspection path data c in the different power supply network object emergency inspection path data set C. p Perform keyword search on power supply network object features and analyze the emergency inspection path data c of different power supply network objects corresponding to the power supply network object feature text data Y p And construct the disaster emergency inspection path data c′ of the power supply network object;

[0108] S43, the emergency inspection equipment performs the power supply network disaster weather emergency inspection operation according to the emergency inspection equipment corresponding to the power supply network disaster emergency inspection equipment text data b" and the emergency inspection path corresponding to the power supply network object disaster emergency inspection path data c'.

[0109] Through the cooperation between the power supply network object information collection unit and the power supply network geographic weather feature information collection unit, the target power supply network object feature information and geographic weather feature information are accurately obtained through the power monitoring platform and weather monitoring sensors, providing reliable data for the subsequent accurate analysis of disaster weather types, emergency inspection equipment and distribution network disaster inspection paths; the disaster weather type analysis unit and the disaster weather emergency inspection equipment information analysis unit cooperate with each other, based on the intelligent recognition algorithm, accurately identify the type of disaster weather occurring in the geographical area where the target distribution network is located, and scientifically evaluate the emergency inspection equipment information required for specific disaster weather, so as to realize the intelligent processing of power grid operation disaster weather power supply emergency decision-making and control; the power supply network object emergency inspection path analysis unit and the power supply network disaster emergency inspection operation execution unit cooperate with each other, based on the intelligent search algorithm, accurately search out the target power supply network object disaster emergency inspection path information, and combine the power supply network disaster emergency inspection equipment information to autonomously and efficiently execute the power supply network disaster weather emergency inspection operation, so as to realize the efficient and accurate execution of power supply emergency inspection operations in power disaster weather, and improve the efficiency and reliability of power supply emergency handling in power disaster weather.

[0110] For further information, see Figure 1 - Figure 2 , collect the real-time image data of the power supply network disaster inspection and perform the dangerous feature object recognition processing of the power supply network in the disaster weather with the different dangerous feature image data of the power supply network disaster weather, and generate the power supply network disaster weather dangerous feature recognition data; when it does not exist, continue to perform the power supply network disaster weather emergency inspection operation until it is completed. The operation steps are as follows:

[0111] S51. During the emergency inspection of the power grid during disaster weather, the real-time status images of the target power grid lines and power equipment are collected online through the camera mounted on the drone, and a data set of real-time images of the power grid disaster inspection is generated. where d u represents the u-th collected real-time image data of power grid disaster inspection, Indicates the maximum number of live images of power grid disaster inspection;

[0112] S52, establish a power grid disaster weather different dangerous characteristics image data set E = (e1, ..., e v ,…,e γ ), v = 1, 2, 3, ..., γ; where e v represents the different dangerous feature image data of the power grid disaster weather corresponding to the vth power grid disaster weather dangerous feature type, γ represents the maximum number of power grid disaster weather dangerous feature types, and the power grid disaster weather dangerous feature types include snow accumulation on the power grid line, temperature overload of the power grid line, swing amplitude overload of the power grid line, lightning strike on the power grid electric equipment, and swing of the power grid line contacting trees;

[0113] S53, the power supply network disaster inspection live image data set D is used to collect the power supply network disaster inspection live image data d u Different dangerous characteristics image data set E of power grid disaster weather and different dangerous characteristics image data e of power grid disaster weather v Perform image feature matching, and generate power grid disaster weather hazard feature identification data D′ based on the image feature matching results;

[0114] When u With e v If the image feature matching is successful, it means that there are disaster weather hazard features in the target power supply network line at the current location, then the power supply network disaster weather hazard feature identification data D′ is output as existence, and the power supply network disaster weather hazard feature type is output;

[0115] When u With e v If the image features are not matched successfully, it means that there is no disaster weather hazard feature in the target power supply network line at the current location, and the output power supply network disaster weather hazard feature identification data D′ is non-existent. At this time, continue to execute step S43 until the power supply network disaster weather emergency inspection operation is completed.

[0116] When it exists, the emergency treatment plan identification processing of the power supply network disaster weather hazard feature object is performed according to the power supply network disaster weather hazard feature identification data and the power supply network disaster weather different hazard feature emergency treatment plan data, and the operation steps of generating the power supply network disaster weather hazard feature emergency treatment plan data are as follows:

[0117] S61. Establish a data set of emergency response plans for different dangerous characteristics of disaster weather in the power supply network E'=(e'1,…,e' v ,…,e' γ ), where e' v The emergency treatment plan data of different dangerous characteristics of disaster weather in the power supply network corresponding to the vth type of dangerous characteristics of disaster weather in the power supply network represents the standard emergency treatment plan data corresponding to the specific type of dangerous characteristics of disaster weather in the power supply network;

[0118] S62, when the power grid disaster weather hazard feature identification data D' exists, a breadth-first search algorithm is used to compare the power grid disaster weather hazard feature identification data D' with the power grid disaster weather different hazard feature emergency treatment plan data set E' of the power grid disaster weather different hazard feature emergency treatment plan data set E'. v Perform character matching on the type of disaster weather hazard feature of the power supply network, and search for the emergency treatment plan data e′ of different disaster weather hazard features of the power supply network corresponding to the disaster weather hazard feature identification data D′ of the power supply network v , and generate emergency response plan data for disaster weather hazard characteristics of power supply network through data identification

[0119] Through the cooperation of the power supply network disaster inspection real-time image acquisition unit and the power supply network disaster weather hazard feature information identification unit, the drone-mounted shooting lens dynamically collects the power supply network disaster inspection real-time image parameters and conducts online scientific analysis of the power supply network's hazard feature objects in disaster weather with the different hazard feature image parameters of the power supply network disaster weather, thereby realizing intelligent analysis of the distribution network's power supply hazard features in disaster weather, and improving the accuracy of emergency response to power disaster weather; the power supply network disaster weather hazard feature emergency response plan identification unit scientifically evaluates the emergency response plan information of different hazard features in disaster weather in the distribution network, realizes accurate analysis of the power supply network disaster weather hazard feature emergency response plan, and improves the quality and scientificity of emergency response to power disaster weather.

[0120] For further information, see Figure 1 - Figure 2 , collect the real-time spatial coordinate data of the power supply network disaster emergency inspection and analyze the optimal emergency site object required for the power supply network disaster weather emergency treatment with the spatial coordinate data of the power supply network emergency site object, and generate the optimal site object analysis data for the power supply network disaster emergency as follows:

[0121] S71, collecting spatial coordinate information of emergency inspection equipment with disaster weather hazard characteristics in the target power supply network line through position sensors online and generating real-time spatial coordinate data f of power supply network disaster emergency inspection, the real-time spatial coordinate data f of power supply network disaster emergency inspection includes the longitude, latitude and altitude of the space where the emergency inspection equipment is located;

[0122] S72: Establishing the spatial coordinate data set H of the power supply network emergency site object = (h1, ..., h n ,…,h η ), n=1,2,3,…,η; where h n represents the spatial coordinate data of the nth power supply network emergency site object, n represents the maximum number of power supply network emergency sites, the power supply network emergency site object spatial coordinate data represents the spatial coordinate data of the power supply network emergency maintenance site used to perform power supply emergency processing operations, and the power supply network emergency site object spatial coordinate data includes the longitude, latitude and altitude of the power supply network emergency site;

[0123] S73, using the spatial distance formula to measure the real-time spatial coordinate data f of the power supply network disaster emergency inspection and the spatial coordinate data h of the power supply network emergency site object in the power supply network emergency site object spatial coordinate data set H. n The distance value is obtained and the distance data set G = (g1,…,g n ,…,g η ), where g n represents the real-time spatial coordinate data f of the power supply network disaster emergency inspection and the spatial coordinate data h of the power supply network emergency site object n Corresponding power grid emergency inspection location and emergency site distance data, g n The unit is kilometers;

[0124] S74, the power supply network emergency inspection location and emergency site distance data g in the power supply network emergency inspection location and emergency site distance data set G n Compare the distance values ​​and search for the distance data g between the emergency inspection location of the power grid and the emergency site with the smallest distance value. n and the power supply network emergency site object spatial coordinate data set H of the power supply network emergency site object spatial coordinate data h n According to the number matching of the power supply network emergency site, search for the power supply network emergency inspection location with the smallest distance value and the emergency site distance data g n The matching power grid emergency site object spatial coordinate data h n The corresponding power supply network emergency site object is identified through data identification to generate the power supply network disaster emergency optimal site object analysis data H′.

[0125] The steps for constructing the power supply network emergency handling guidance text data and executing the power supply emergency handling operation are as follows:

[0126] S81, the power supply network disaster weather hazard feature identification data D′, the power supply network disaster weather hazard feature emergency treatment plan data The optimal site object analysis data H of power grid disaster emergency is combined to construct the power grid emergency treatment guidance text data

[0127] S82. The power supply network emergency processing guidance text data K is transmitted to the power supply network emergency site through the Internet of Things communication network, and the internal staff of the power supply network emergency site performs the power supply emergency processing operation.

[0128] Through the cooperation of the power supply network disaster emergency inspection position collection unit and the power supply network emergency processing site object analysis unit, the real-time spatial coordinates of the power supply network disaster emergency inspection and the spatial coordinates of the power supply network emergency site object are accurately collected through the position sensor, and the power supply network emergency site object with the shortest distance is scientifically analyzed by numerical analysis, so as to achieve the response speed and precise dispatching command of the distribution network disaster emergency processing; the power supply emergency processing operation execution unit scientifically constructs the power supply network emergency processing guidance information and autonomously and accurately feeds back to the power supply network emergency site object, accurately and efficiently executes the power supply emergency processing operation, and improves the applicability and efficiency of the power disaster weather emergency processing operation.

[0129] Embodiment 2:

[0130] See also Figure 1 - Figure 2 , a power grid operation disaster weather power supply emergency decision-making control system, used to implement a power grid operation disaster weather power supply emergency decision-making control method, the system includes a power grid disaster weather emergency inspection processing module, a power grid disaster weather emergency processing countermeasures analysis module, and a power grid disaster weather emergency operation control module;

[0131] The power supply network disaster weather emergency inspection processing module includes a power supply network object information collection unit, a power supply network geographical weather feature information collection unit, different types of disaster weather feature information storage unit, a disaster weather type analysis unit, different types of disaster weather required emergency inspection equipment information storage unit, disaster weather emergency inspection equipment information analysis unit, different power supply network object emergency inspection path storage unit, power supply network object emergency inspection path analysis unit, power supply network disaster emergency inspection operation execution unit;

[0132] The power supply network object information collection unit collects the power supply network object feature text data through the power monitoring platform; the power supply network geographic weather feature information collection unit collects the power supply network geographic weather feature text data through the weather monitoring sensor; the different types of disaster weather feature information storage unit stores different types of disaster weather feature text data based on big data; the disaster weather type analysis unit analyzes and processes the disaster weather type of the geographical area where the power supply network is located based on the power supply network geographic weather feature text data and different types of disaster weather feature text data, and generates power supply network geographic disaster weather type analysis data; the emergency inspection equipment information storage unit required for different types of disaster weather is used to store the text data of emergency inspection equipment required for different types of disaster weather based on big data; the disaster weather emergency inspection equipment information analysis unit, According to the power supply network geographical disaster weather type analysis data and the text data of emergency inspection equipment required for different types of disaster weather, the information of emergency equipment required for disaster weather of the power supply network is analyzed and processed to generate the text data of disaster emergency inspection equipment of the power supply network; the emergency inspection path storage unit of different power supply network objects is used to store the emergency inspection path data of different power supply network objects; the power supply network object emergency inspection path analysis unit performs the disaster emergency inspection path analysis and processing of the target power supply network object based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects to generate the disaster emergency inspection path data of the power supply network object; the power supply network disaster emergency inspection operation execution unit executes the power supply network disaster weather emergency inspection operation according to the power supply network object disaster emergency inspection path data and the text data of disaster emergency inspection equipment of the power supply network;

[0133] The power supply network disaster weather emergency response countermeasures analysis module includes a power supply network disaster inspection real-time image acquisition unit, a power supply network disaster weather different dangerous characteristics image storage unit, a power supply network disaster weather dangerous characteristics information identification unit, a power supply network disaster weather different dangerous characteristics emergency response plan storage unit, and a power supply network disaster weather dangerous characteristics emergency response plan identification unit;

[0134] A power supply network disaster inspection live image acquisition unit, which uses a drone-mounted camera to collect live image data of power supply network disaster inspections; a power supply network disaster weather different dangerous feature image storage unit, which is used to store image data of different dangerous features of power supply network disaster weather based on big data; a power supply network disaster weather dangerous feature information identification unit, which performs identification processing of dangerous feature objects of the power supply network in disaster weather based on the live image data of power supply network disaster inspections and image data of different dangerous features of power supply network disaster weather, and generates identification data of dangerous features of power supply network disaster weather; a power supply network disaster weather different dangerous feature emergency treatment plan storage unit, which is used to store emergency treatment plan data of different dangerous features of power supply network disaster weather based on big data; a power supply network disaster weather dangerous feature emergency treatment plan identification unit, which performs identification processing of emergency treatment plan objects of power supply network disaster weather based on the power supply network disaster weather dangerous feature identification data and emergency treatment plan data of different dangerous features of power supply network disaster weather, and generates emergency treatment plan data of dangerous features of power supply network disaster weather;

[0135] The power supply network disaster weather emergency operation control module includes a power supply network disaster emergency inspection location collection unit, a power supply network emergency site location storage unit, a power supply network emergency processing site object analysis unit, and a power supply emergency processing operation execution unit;

[0136] The power supply network disaster emergency inspection position acquisition unit collects the real-time spatial coordinate data of the power supply network disaster emergency inspection through the position sensor; the power supply network emergency site position storage unit is used to store the spatial coordinate data of the power supply network emergency site object; the power supply network emergency processing site object analysis unit performs the optimal emergency site object analysis and processing required for the power supply network disaster weather emergency processing based on the real-time spatial coordinate data of the power supply network disaster emergency inspection and the spatial coordinate data of the power supply network emergency site object, and generates the power supply network disaster emergency optimal site object analysis data; the power supply emergency processing operation execution unit is used to construct the power supply network emergency processing guidance text data and execute the power supply emergency processing operation.

[0137] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power grid operation disaster weather power supply emergency decision-making control method, characterized in that: The method comprises the following steps: S1. Collecting text data of power supply network object characteristics and text data of power supply network geographical weather characteristics; S2. Analyze and process the disaster weather type of the geographical area where the power supply network is located based on the power supply network geographical weather characteristic text data and different types of disaster weather characteristic text data, and generate power supply network geographical disaster weather type analysis data; if no analysis data exists, directly terminate the power supply emergency processing operation; S3. When it exists, analyze and process the information of emergency equipment required for disaster weather of the power supply network according to the power supply network geographical disaster weather type analysis data and the text data of emergency inspection equipment required for different types of disaster weather, and generate text data of disaster emergency inspection equipment for the power supply network; S4, based on the power supply network object feature text data and the emergency inspection path data of different power supply network objects, the disaster emergency inspection path data of the target power supply network object is analyzed and processed, and the disaster emergency inspection path data of the power supply network object is generated, and the power supply network disaster emergency inspection equipment text data is combined to perform the power supply network disaster weather emergency inspection operation; S5, collecting the real-time image data of the power supply network disaster inspection and performing the dangerous feature object recognition processing of the power supply network in the disaster weather with the different dangerous feature image data of the power supply network disaster weather, and generating the dangerous feature recognition data of the power supply network disaster weather; if it does not exist, continue to perform the emergency inspection operation of the power supply network disaster weather until it is completed; S6. When it exists, the emergency treatment plan identification processing of the power supply network disaster weather hazard feature object is performed according to the power supply network disaster weather hazard feature identification data and the power supply network disaster weather different hazard feature emergency treatment plan data, and the power supply network disaster weather hazard feature emergency treatment plan data is generated; S7, collecting real-time spatial coordinate data of power supply network disaster emergency inspection and analyzing the optimal emergency site object required for power supply network disaster weather emergency treatment with the spatial coordinate data of the power supply network emergency site object, and generating power supply network disaster emergency optimal site object analysis data; S8. Construct power supply network emergency handling guidance text data and execute power supply emergency handling operations.

2. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 1, characterized in that: The S1 comprises the following steps: S11, collecting the name, line number and tower number text information of the target power supply network line online through the power monitoring platform and generating power supply network object feature text data Y; The weather characteristic text information of the geographical area where the target power supply network line is located is collected online through the weather monitoring sensor and the power supply network geographical weather characteristic text data Z is generated.

3. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 2 is characterized in that: The S2 comprises the following steps: S21. Establish different types of disaster weather feature text data sets A = (a1,…,a o ,…,a ε ), o=1,2,3,…,ε; where a o represents the characteristic text data of different types of disaster weather corresponding to the oth type of disaster weather, and ε represents the maximum number of disaster weather types; S22, the Z and the a in the A o Perform weather feature character matching to search for the a that matches the Z o The corresponding disaster weather type is constructed, and the power supply network geographical disaster weather type analysis data A′ is constructed. The specific operation steps for generating the power supply network geographical disaster weather type analysis data A′ are as follows: S221, initializing parameters and updating the maximum number of iterations T of the algorithm; S222, initializing the position of the disaster weather identification seagull population, that is, updating the position of the disaster weather identification seagull population in the A search space; S223, calculate all the a in A o and the fitness value of Z, and retain the a with the largest fitness value of Z in the A search space o The global optimal position of S224, migration, global search: The migration behavior of the disaster weather identification seagull mainly has three steps. The first is to meet the condition of avoiding collision between different disaster weather identification seagull individuals in the A search space; the second is to calculate the a that matches the Z in the A search space; o The best position direction; thirdly, according to the a matching with the Z o Move the direction of the best position to a new position; S2241, calculating a new position J'(t) of the disaster weather identification seagull that does not collide with an adjacent disaster weather identification seagull during its movement in the A search space; S2242, calculate the a that matches the Z in the A search space. o The optimal position direction X(t); S2243, according to the a that best matches the Z o Move the direction of the optimal position to the new position M(t); S225, attacking prey, local search, and identifying the disaster weather. When attacking prey in the A search space, the seagull performs a spiral motion in the air. The new position M'(t) of the disaster weather identifying seagull after attacking the prey is S226: Determine whether the maximum number of iterations is met, and then output the a that best matches the Z. o ; If not satisfied, return to step S223; S227, the a that best matches the Z output according to step S226 o Corresponding disaster weather types, and constructing the power grid geographical disaster weather type analysis data A′; When Z and a o If the weather feature character matching is successful, the power grid geographical disaster weather type analysis data A′ is output as existing, and the disaster weather type is output; When Z and a o If no weather characteristic characters are matched successfully, the output power supply network geographical disaster weather type analysis data A′ is non-existent, and the power supply emergency processing operation is directly terminated.

4. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 3 is characterized by: The S3 comprises the following steps: S31. Establish the text data set B of emergency inspection equipment required for different types of disaster weather = (b1,…,b o ,…,b ε ), where b o Represents the text data of emergency inspection equipment required for different types of disaster weather corresponding to the oth type of disaster weather; S32, when A' exists, use the KD tree nearest neighbor search algorithm to compare A' with b in B o Perform keyword matching of disaster weather types and search for the b corresponding to the A' o , and construct the power supply network disaster emergency inspection equipment text data b".

5. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 4 is characterized by: The S4 comprises the following steps: S41. Establish emergency inspection path data set C = (c1, ..., c p ,…,c φ ), p=1,2,3,…,φ; where c p represents the emergency inspection path data of different power supply network objects corresponding to the p-th power supply network object, and φ represents the maximum number of power supply network objects; S42, using a breadth-first search algorithm to compare the Y with the c in the C p Perform a keyword search for the power supply network object characteristics and analyze the c corresponding to the Y p And construct the disaster emergency inspection path data c′ of the power supply network object; S43, the emergency inspection equipment performs the disaster weather emergency inspection operation of the power supply network according to the emergency inspection equipment corresponding to b" and the emergency inspection path corresponding to c'.

6. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 5, characterized in that: The S5 comprises the following steps: S51. During the emergency inspection of the power grid during disaster weather, the real-time status images of the target power grid lines and power equipment are collected online through the camera mounted on the drone, and a data set of real-time images of the power grid disaster inspection is generated. where d u represents the u-th collected real-time image data of power grid disaster inspection, Indicates the maximum number of live images of power grid disaster inspection; S52, establish a power grid disaster weather different dangerous characteristics image data set E = (e1, ..., e v ,…,e γ ), v = 1, 2, 3, ..., γ; where e v represents the different dangerous characteristic image data of the disaster weather of the power supply network corresponding to the vth dangerous characteristic type of the disaster weather of the power supply network, and γ represents the maximum number of dangerous characteristic types of the disaster weather of the power supply network; S53, the d in the D u With the E in the e v Perform image feature matching, and generate power grid disaster weather hazard feature identification data D′ based on the image feature matching results; When u With e v If the image feature matching is successful, the power grid disaster weather hazard feature identification data D' is output as existing, and the power grid disaster weather hazard feature type is output; When u With e v If the image features are not matched successfully, the output power grid disaster weather hazard feature identification data D' is not present, and then the step S43 is continued to be executed until the power grid disaster weather emergency inspection operation is completed.

7. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 6, characterized in that: The S6 comprises the following steps: S61. Establish a data set of emergency response plans for different dangerous characteristics of disaster weather in the power supply network E'=(e'1,…,e' v ,…,e' γ ), where e' v Represents the emergency response plan data of different dangerous characteristics of disaster weather in the power supply network corresponding to the vth type of dangerous characteristics of disaster weather in the power supply network; S62, when D' exists, use a breadth-first search algorithm to search D' with e' in E v Perform character matching on the power grid disaster weather hazard feature type to search for the e′ corresponding to the D′ v , and generate emergency response plan data for disaster weather hazard characteristics of power supply network through data identification 8. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 7 is characterized by: The S7 comprises the following steps: S71, collecting spatial coordinate information of emergency inspection equipment that finds that there are disaster weather hazard characteristics in the target power supply network line through a position sensor online and generating real-time spatial coordinate data f of power supply network disaster emergency inspection; S72: Establishing the spatial coordinate data set H of the power supply network emergency site object = (h1, ..., h n ,…,h η ), n=1,2,3,…,η; where h n represents the spatial coordinate data of the nth power supply network emergency site object, and η represents the maximum number of power supply network emergency sites; S73, using the spatial distance formula to measure the f and the h in H n The distance value is obtained and the distance data set G = (g1,…,g n ,…,g η ), where g n Indicates that f and h n Corresponding power grid emergency inspection location and emergency site distance data, g n The unit is kilometers; S74, the g in the G n Compare the distance values ​​and search for the g with the smallest distance value. n and with the H in the h n According to the number matching of the emergency sites of the power supply network, search for the g with the smallest distance value n Matching the h n The corresponding power supply network emergency site object is identified through data identification to generate the power supply network disaster emergency optimal site object analysis data H′.

9. The method for emergency decision-making and control of power supply in disaster weather of power grid operation according to claim 8, characterized in that: The S8 comprises the following steps: S81, the D′, the The power supply network emergency handling guidance text data is constructed by combining the data with H′ S82. The K is transmitted to the power supply network emergency site through the Internet of Things communication network, and the internal staff of the power supply network emergency site performs power supply emergency processing operations.

10. A power grid operation disaster weather power supply emergency decision control system, used to implement a power grid operation disaster weather power supply emergency decision control method according to any one of claims 1 to 9, characterized in that: The system comprises a power supply network disaster weather emergency inspection processing module, a power supply network disaster weather emergency processing countermeasures analysis module, and a power supply network disaster weather emergency operation control module.

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