A weather disaster early warning method and system for a wind-solar pumped storage power station

Abstract

The application is suitable for the technical field of disaster warning, and particularly relates to a weather disaster warning method and system for a wind-solar-pumped storage power station, which comprises the following steps: delimiting a control area of the wind-solar-pumped storage power station, obtaining regional weather data with the control area as an object, and dividing the regional weather data into a plurality of elements, extracting risk factors, traversing occurrence times of the risk factors, and configuring a buffer range for the occurrence times, wherein the buffer range is defined as a flight time of a UAV; when the flight time arrives, a flight instruction is issued to the UAV, and a verification rule pre-embedded in the UAV is triggered to verify the regional weather data. The application can prevent weather disasters in advance by determining sensitive equipment, effectively prevent production equipment failure or accidents, ensure the normal operation of wind-solar-pumped storage work, optimize pumped storage scheduling by generating a warning notice, ensure the stability of the power grid, and improve the reliability and economy of the overall operation of the power generation system.

Description

Technical Field

[0001] The present invention relates to the field of disaster warning technology, and in particular to a meteorological disaster warning method and system for a wind-solar pumped-storage power station. Background Art

[0002] A wind-solar-pumped-storage power station refers to a comprehensive power station that combines wind power generation, photovoltaic power generation (solar energy) and pumped storage technology. A wind-solar-pumped-storage power station is highly dependent on weather conditions. The power generation of wind and solar energy is directly affected by meteorological conditions such as wind speed, solar radiation and temperature. In addition, extreme weather events such as typhoons, heavy rains and hail may also cause equipment damage or unstable power output, affecting the safety and stability of the power grid.

[0003] Meteorological data for wind and solar pumped-storage power stations are generally provided by public meteorological service providers. The generation of these meteorological data often relies on fixed meteorological stations, and the coverage area may be large, but their spatial resolution is low. They cannot accurately reflect the microclimate changes at the specific location of the wind and solar pumped-storage power stations, and cannot meet the high-precision and real-time requirements of wind and solar pumped-storage power stations for meteorological data.

[0004] Therefore, “how to use drones to focus on monitoring meteorological data at sensitive equipment” is the technical problem that the present invention needs to solve. Summary of the Invention

[0005] The purpose of the present invention is to provide a meteorological disaster warning method and system for a wind-solar-pumped-storage power station to solve the problem raised in the above background technology of "how to use drones to focus on monitoring meteorological data at sensitive equipment."

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A meteorological disaster early warning method for a wind-solar pumped-storage power station, the method comprising:

[0008] Delineating the control area of ​​the wind-solar-pumped-storage power station, obtaining regional meteorological data for the control area, dividing the data into several elements, extracting risk factors, traversing the occurrence time of the risk factors, and configuring a buffer range for the occurrence time, where the buffer range is defined as the flight time of the drone;

[0009] When the flight time arrives, a flight instruction is issued to the drone, triggering the verification rules pre-embedded in the drone to verify the regional meteorological data and generate a verification result;

[0010] If the verification result is true, calibrate the regional meteorological data and occurrence time, obtain the flight trajectory of the unmanned aerial vehicle, construct a risk verification area, delete the part of the risk verification area located outside the control area, dynamically correct the boundary of the risk verification area, find out the production equipment located in the risk verification area, configure the device resilience of each production equipment, compare the device resilience and the regional meteorological data, and mark the sensitive equipment;

[0011] In the risk verification area, define the sensitive equipment as a passing point, generate a flight route, and send the flight route to the unmanned aerial vehicle, collect real-time meteorological data along the side of the flight route, adjust the sensitive equipment, integrate the sensitive equipment, regional meteorological data and occurrence time, generate a warning notification, and push the warning notification to a preset terminal.

[0012] Further, the step of "defining the control area of the wind and light pumped storage power station, and obtaining regional meteorological data as an object of the control area" comprises:

[0013] Divide the control area into multiple levels, wherein the levels at least include: a core area, a buffer area and a peripheral monitoring area;

[0014] Establish a mapping between each level and regional meteorological data, wherein the regional meteorological data is provided by a meteorological service provider;

[0015] Determine the deployment position of the on-site meteorological sensor, obtain real-time monitoring data, and optimize the regional meteorological data.

[0016] Further, the step of "cutting into several elements, extracting risk factors, traversing the occurrence time of the risk factors, and configuring the buffer range for the occurrence time as the flight time of the unmanned aerial vehicle" comprises:

[0017] Determine whether the element exceeds a set value, if it does, define the corresponding element as a risk factor, and insert a label generated by the risk factor into the control area;

[0018] Integrate all risk factors to generate a risk set, and embed the risk set in a warning notification.

[0019] Further, the step of "when the flight time arrives, issuing a flight instruction to the unmanned aerial vehicle, triggering the pre-embedded verification rule in the unmanned aerial vehicle, verifying the regional meteorological data, and generating a verification result" comprises:

[0020] Input the real-time meteorological data into the constructed numerical weather prediction model, and output the calibrated data;

[0021] Integrate the verification rule and the calibration data to verify the regional meteorological data, wherein the verification rule is to calculate the difference between the calibration data and the regional meteorological data;

[0022] According to the real-time meteorological data, the difference is dynamically updated, if the difference is less than the preset threshold, the verification result is defined as true, otherwise, it is defined as false.

[0023] Further, the step of "constructing a risk verification area" includes:

[0024] From the flight trajectory, a plurality of target points are randomly selected, and the risk score of each target point is determined according to the real-time meteorological data of the target point;

[0025] Integrate the target points with risk scores greater than the threshold, and use the spatial interpolation method to construct the risk verification area.

[0026] Further, the step of "dynamically correcting the boundary of the risk verification area, finding the production equipment located in the risk verification area, configuring the device resilience of each production equipment, and comparing the device resilience with the regional meteorological data to mark the sensitive equipment" includes:

[0027] A plurality of test points are selected from the boundary, the risk score of the test point is determined, and the boundary is corrected using the risk score;

[0028] Determine whether the risk factor in the regional meteorological data is greater than the device resilience, if so, the corresponding production equipment is defined as a sensitive equipment.

[0029] Further, the step of "integrating the sensitive equipment, regional meteorological data and occurrence time, generating a warning notification, and pushing the warning notification to a preset terminal" includes:

[0030] Create an emergency plan table, wherein the emergency plan table consists of a risk factor item, a scheme item and a production equipment item;

[0031] Based on the risk factor, query the emergency plan table, iterate out the scheme corresponding to the sensitive equipment, and start the scheme.

[0032] Further, the method further includes:

[0033] If the verification result is not true, adjust the buffer range using the calibration data;

[0034] After the end of the buffer range, delete the risk factor and cancel the flight instruction.

[0035] Further, the system includes:

[0036] The configuration module is configured to demarcate a control area of the wind-solar pumped storage power station, acquire regional meteorological data as an object of the control area, and divide the regional meteorological data into a plurality of elements, extract risk factors, traverse occurrence times of the risk factors, and configure a buffer range for the occurrence times, wherein the buffer range is defined as a flight time of a UAV;

[0037] The verification module is configured to issue a flight instruction to the UAV when the flight time arrives, trigger a pre-embedded verification rule in the UAV, verify the regional meteorological data, and generate a verification result.

[0038] The marking module is configured to calibrate the regional meteorological data and the occurrence times when the verification result is correct, acquire a flight trajectory of the UAV, construct a risk verification area, delete a part of the risk verification area located outside the control area, dynamically correct a boundary of the risk verification area, find out production equipment located in the risk verification area, configure a device resilience of each of the production equipment, compare the device resilience with the regional meteorological data, and mark sensitive equipment.

[0039] The pushing module is configured to define the sensitive equipment as a passing point in the risk verification area, generate a flight route, send the flight route to the UAV, collect real-time meteorological data along the flight route, adjust the sensitive equipment, integrate the sensitive equipment, the regional meteorological data, and the occurrence times, generate an early warning notification, and push the early warning notification to a preset terminal.

[0040] Further, the configuration module comprises:

[0041] The hierarchical unit is configured to divide the control area into a plurality of levels, wherein the levels at least include a core area, a buffer area, and a peripheral monitoring area.

[0042] The mapping unit is configured to establish a mapping between each of the levels and regional meteorological data, wherein the regional meteorological data is provided by a meteorological service provider.

[0043] The optimization unit is configured to determine a deployment position of an on-site meteorological sensor, acquire real-time monitoring data, and optimize the regional meteorological data.

[0044] The definition unit is configured to determine whether the element exceeds a set value, and if so, define the corresponding element as a risk factor and insert a label generated by the risk factor into the control area.

[0045] The embedding unit is configured to integrate all the risk factors, generate a risk set, and embed the risk set in the early warning notification.

[0046] Compared with the prior art, the present application has the following advantages:

[0047] By acquiring regional meteorological data, power generation prediction can be optimized, power dispatching efficiency can be improved, power grid stability can be ensured, by determining risk factors, risks brought by extreme weather can be prevented, and data support for preventing meteorological disasters can be provided, by issuing flight instructions, real-time meteorological data of wind and light pumped storage power stations can be collected by using unmanned aerial vehicles, data precision can be improved, and disaster warning capability of wind and light pumped storage power stations can be enhanced, by constructing a risk verification area, dangerous areas can be divided, and power grid dispatching and operation can be optimized, stability of power supply can be ensured, by determining sensitive equipment, meteorological disasters can be prevented in advance, production equipment failures can be effectively prevented, and equipment stability of wind and light pumped storage power stations can be improved, by generating early warning notifications, data support can be provided for pumped storage dispatching, power grid stability can be ensured, and disaster resistance of wind and light pumped storage power stations can be greatly enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 A flowchart of a wind and light pumped storage power station meteorological disaster early warning method provided for the embodiment of the present application is provided.

[0049] Figure 2 A first sub-flowchart of a wind and light pumped storage power station meteorological disaster early warning method provided for the embodiment of the present application is provided.

[0050] Figure 3 A second sub-flowchart of a wind and light pumped storage power station meteorological disaster early warning method provided for the embodiment of the present application is provided.

[0051] Figure 4 A third sub-flowchart of a wind and light pumped storage power station meteorological disaster early warning method provided for the embodiment of the present application is provided.

[0052] Figure 5 A fourth sub-flowchart of a wind and light pumped storage power station meteorological disaster early warning method provided for the embodiment of the present application is provided.

[0053] Figure 6 A composition diagram of a wind and light pumped storage power station meteorological disaster early warning system provided for the embodiment of the present application is provided.

[0054] Figure 7 A composition diagram of a configuration module in a wind and light pumped storage power station meteorological disaster early warning system provided for the embodiment of the present application is provided.

[0055] Figure 8 A composition diagram of a verification module in a wind and light pumped storage power station meteorological disaster early warning system provided for the embodiment of the present application is provided.

[0056] Figure 9 A composition diagram of a marking module in a wind and light pumped storage power station meteorological disaster early warning system provided for the embodiment of the present application is provided.

[0057] Figure 10The composition block diagram of the push module of the wind-solar pumped storage power station meteorological disaster early warning system provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0059] In embodiment 1, Figure 1 The implementation flow of the wind-solar pumped storage power station meteorological disaster early warning method provided by the embodiment of the present application is shown, and the following is described in detail as follows:

[0060] S100: delineate the control area of the wind-solar pumped storage power station, obtain the regional meteorological data of the control area as the object, and divide it into several elements, extract the risk factor, traverse the occurrence time of the risk factor, and configure the buffer range for the occurrence time, define the buffer range as the flight time of the unmanned aerial vehicle.

[0061] According to the actual planning or facility layout of the wind-solar pumped storage power station, the control area of the wind-solar pumped storage power station is delineated, and the regional meteorological data containing the control area is determined, wherein the regional meteorological data can be obtained from a public channel, and the regional meteorological data at least includes wind, temperature, sunshine intensity, sunrise and sunset time, etc. The regional meteorological data is divided into several elements, such as wind element and rain element, if a certain element is greater than a preset threshold, the element is defined as a risk factor, and the occurrence time of the risk factor is determined by using the public channel; the buffer range can calibrate the regional meteorological data by using the unmanned aerial vehicle within a certain time before and after the occurrence of the risk factor.

[0062] Within the buffer range, the unmanned aerial vehicle is controlled to fly and collect real-time meteorological data in the control area, and the regional meteorological data is calibrated; in actual life, it should be noted that if the wind speed of the day is greater than the maximum take-off speed of the unmanned aerial vehicle, the meteorological data of the wind-solar pumped storage power station should be monitored in real time by using a mobile sensor, a monitoring vehicle or a meteorological balloon.

[0063] For example, the regional meteorological data of a certain wind-solar pumped storage power station is shown in the following table;

[0064]

[0065]

[0066] In the above table, the elements are wind speed 5.2 m / s, wind speed 4.6 m / s, wind speed 5.1 m / s, wind speed 24 m / s, and wind direction 270°, etc. If the warning wind speed of the wind and light pumped storage power station is 22 m / s (the warning wind speed is mainly used to remind the staff to pay attention to the wind change in time, but at this wind speed, it will not cause damage to the equipment), the risk factor is the wind speed 24 m / s, the corresponding time is the occurrence time, and the buffer range is 1 hour or 2 hours before and after the time A. The specific time is determined by the staff.

[0067] S200: When the flight time comes, the flight instruction is issued to the unmanned aerial vehicle, the verification rule pre-embedded in the unmanned aerial vehicle is triggered, the regional meteorological data is verified, and the verification result is generated.

[0068] When the flight time comes, the flight instruction is sent to the unmanned aerial vehicle integrated with the meteorological monitoring device, wherein the meteorological monitoring device includes but is not limited to temperature and humidity sensor, air pressure sensor, and wind speed and wind direction sensor, etc. Real-time meteorological data of the control area is collected by using the meteorological monitoring device; wherein the verification rule is a specific method of comparing the real-time meteorological data and the regional meteorological data; the regional meteorological data is verified by using the verification rule to determine whether the regional meteorological data is valid; for example, the collected real-time meteorological data is input into the numerical weather prediction model, and the predicted value at time A is output, and it is judged whether the predicted value is wind speed 24 m / s. If the difference between the two is less than the preset threshold, the verification result is valid.

[0069] S300: If the verification result is valid, calibrate the regional meteorological data and the occurrence time, obtain the flight trajectory of the unmanned aerial vehicle, construct the risk verification area, delete the part outside the control area in the risk verification area, dynamically correct the boundary of the risk verification area, find out the production equipment in the risk verification area, configure the equipment resilience of each production equipment, compare the equipment resilience and the regional meteorological data, and mark the sensitive equipment.

[0070] If the verification result is correct, the output result of the numerical weather prediction model is used to calibrate the regional meteorological data; in actual life, the wind and light pumped storage power station generally occupies a large area, and the local microclimate may be different; therefore, the meteorological data of the wind and light pumped storage power station needs to be finely processed, which also requires one or more risk verification zones to be divided; from the flight trajectory of the unmanned aerial vehicle, a plurality of target points are randomly selected, and the risk score is determined according to the real-time meteorological data of each target point; continue to detail the example in S100, if the early warning wind speed of the wind and light pumped storage power station is 22 m / s, the real-time wind speed of the target point A is 18 m / s, the real-time wind speed of the target point B is 10 m / s, and the real-time wind speed of the target point C is 20 m / s, wherein the difference in real-time wind speed may be caused by mountain shielding and wind turbulence, at this time the risk score of A can be determined as 3 points, the risk score of B can be determined as 0 points, and the risk score of C can be determined as 4 points. The specific risk score can be determined by querying the pre-constructed comparison table, and the comparison table is prepared by the staff, so that all target points with a risk score greater than 3 points can be used to construct a risk verification zone.

[0071] After the risk verification zone is delineated, the boundary of the risk verification zone is dynamically updated by the unmanned aerial vehicle, and it should be noted that since the meteorological data is dynamically changing, the boundary of the risk verification zone is also dynamically changing; the production equipment located in the risk verification zone and having a small equipment resilience to the regional meteorological data is determined as a sensitive equipment, wherein the equipment resilience is the bearing capacity of the equipment to meteorological disasters, and the greater the equipment resilience, the greater the wind resistance and temperature difference that can be resisted.

[0072] S400: In the risk verification zone, the sensitive equipment is defined as a passing point, a flight route is generated, and the flight route is sent to the unmanned aerial vehicle; real-time meteorological data along the side of the flight route is collected, the sensitive equipment is adjusted, the sensitive equipment, regional meteorological data and occurrence time are integrated, a warning notification is generated, and the warning notification is pushed to a preset terminal.

[0073] The sensitive equipment is taken as a passing point, and the real-time meteorological data at the sensitive equipment is collected; if the real-time meteorological data exceeds the equipment resilience, a warning notification is generated, and the warning notification is pushed to a preset terminal, wherein the preset terminal is a terminal of the staff of the wind and light pumped storage power station.

[0074] In embodiment 2, Figure 2 The implementation process of the wind and light pumped storage power station meteorological disaster early warning method provided by the embodiment of the application is shown, and the steps of "delineating the control area of the wind and light pumped storage power station and obtaining the regional meteorological data as the object of the control area" are described in detail as follows:

[0075] S101: divide the control area into multiple levels, wherein the levels at least include: a core area, a buffer area and a peripheral monitoring area.

[0076] The control area is divided into multiple levels; in actual production, not all parts in the control area need to pay close attention to meteorological changes, and the core area is the part that is more sensitive to meteorological data in the wind-solar-pumped storage power station.

[0077] S102: establish a mapping between each level and regional meteorological data, wherein the regional meteorological data is provided by a meteorological service provider.

[0078] The regional meteorological data is divided to determine the regional meteorological data of each level.

[0079] S103: determine the deployment position of the on-site meteorological sensor, obtain real-time monitoring data, and optimize the regional meteorological data.

[0080] In the core area, multiple groups of on-site meteorological sensors are arranged, and the real-time monitoring data collected is used to optimize the regional meteorological data, further improving the accuracy of the regional meteorological data.

[0081] In embodiment 3, Figure 2 The wind-solar-pumped storage power station meteorological disaster early warning method provided by the embodiment of the application is shown, and the steps of "dividing into several elements, extracting risk factors, traversing the occurrence time of the risk factors, and configuring a buffer range for the occurrence time, defining the buffer range as the flight time of the unmanned aerial vehicle" are described in detail as follows:

[0082] S104: determine whether the element exceeds the set value, if it exceeds, define the corresponding element as a risk factor, and insert a label generated by the risk factor into the control area.

[0083] The configuration process of the set value includes: in each element, find the minimum device resilience, which is the set value; in other words, if the wind speed exceeds the set value, the wind-solar-pumped storage power station has a security risk.

[0084] S105: integrate all risk factors to generate a risk set, and embed the risk set in the early warning notification.

[0085] In the regional meteorological data, there may be no risk factor, or there may be multiple risk factors, if the risk factor is multiple, a risk set is generated.

[0086] In embodiment 4, Figure 3The implementation process of the meteorological disaster warning method for a wind-solar pumped storage power station provided by an embodiment of the present invention is shown. The following is a detailed description of "when the flight time arrives, issuing a flight instruction to the drone, triggering the verification rules pre-embedded in the drone, verifying the regional meteorological data, and generating a verification result" as follows:

[0087] S201: Input the real-time meteorological data into the constructed numerical weather forecast model, and output calibration data.

[0088] The real-time meteorological data collected by the drone is input into the numerical weather forecast model, and the output is calibration data, which is the meteorological forecast data for the wind, solar and pumped storage power stations. This meteorological forecast data is used to calibrate the regional meteorological data.

[0089] S202: Integrate the verification rule and calibration data to verify the regional meteorological data, wherein the verification rule is: calculate the difference between the calibration data and the regional meteorological data;

[0090] S203: Dynamically update the difference according to the real-time meteorological data. If the difference is less than a preset threshold, the verification result is defined as established; otherwise, it is defined as not established.

[0091] If the difference between the calibration data and the regional meteorological data is less than a preset threshold, the verification passes.

[0092] In Example 5, Figure 4 The implementation process of the meteorological disaster early warning method for a wind-solar pumped storage power station provided by an embodiment of the present invention is shown. The steps of "constructing a risk verification zone" are described in detail below:

[0093] S301: Randomly select a number of target points from the flight trajectory, and determine a risk score for each target point based on real-time meteorological data of the target points.

[0094] Determine the risk score of the target point based on the real-time meteorological data of the target point.

[0095] S302: Integrate the target points with risk scores greater than a threshold and construct a risk verification area using a spatial interpolation method.

[0096] Find all target points with risk scores greater than a threshold. These target points represent potential risk areas and are smoothed and estimated using spatial interpolation. Spatial interpolation can infer the risk values ​​of other points in the flight trajectory based on the risk scores of existing target points, thereby obtaining a continuous risk distribution map and delineating the risk verification area.

[0097] In Example 6, Figure 4The implementation process of the meteorological disaster early warning method for wind-solar pumped-storage power stations provided by an embodiment of the present invention is shown. The following details the steps of "dynamically correcting the boundaries of the risk verification area, finding the production equipment located in the risk verification area, configuring the equipment resilience of each production equipment, comparing the equipment resilience with regional meteorological data, and marking sensitive equipment".

[0098] S303: Selecting a number of test points from the boundary, determining risk scores of the test points, and modifying the boundary using the risk scores.

[0099] In the boundary of the risk verification area, a test point is selected, and the risk score of the test point is calculated, the test point is offset, and the boundary is corrected.

[0100] S304: Determine whether the risk factor in the regional meteorological data is greater than the equipment resilience. If so, define the corresponding production equipment as sensitive equipment.

[0101] In Example 7, Figure 5 The implementation process of the meteorological disaster warning method for wind-solar pumped storage power stations provided by an embodiment of the present invention is shown. The steps of "integrating the sensitive equipment, regional meteorological data and occurrence time, generating a warning notification, and pushing the warning notification to a preset terminal" are described in detail below:

[0102] S401: Create an emergency plan comparison table, wherein the emergency plan comparison table consists of risk factor items, plan items, and production equipment items.

[0103] Create an emergency plan comparison table, where the emergency plan comparison table is a collection of emergency plans.

[0104] S402: Based on the risk factors, query the emergency plan comparison table, traverse the plans corresponding to the sensitive equipment, and start the plans.

[0105] After determining the risk factor of a sensitive device, query the emergency plan comparison table, determine the plan, and use this plan to carry out emergency treatment of the sensitive equipment.

[0106] In Example 8, different from Example 1, in this embodiment of the present invention, the method further includes:

[0107] If the verification result is not established, adjusting the buffer range using the calibration data;

[0108] After the buffer range ends, the risk factor is deleted and the flight instruction is revoked.

[0109] If the verification is successful, it means that the prediction result of the regional meteorological data is accurate; otherwise, it means that the prediction result is wrong and there is a large deviation between the regional meteorological data and the actual situation. In this case, the calibration data will be used to increase the flight time of the drone and calibrate the regional meteorological data. If there is no risk factor in the calibrated regional meteorological data, the flight command will be revoked. In other words, the drone will be launched and the regional meteorological data will be calibrated only when it is predicted that there may be meteorological disasters within a certain period of time based on the regional meteorological data.

[0110] Figure 6 The following is a structural block diagram of a meteorological disaster warning system for a wind-solar pumped-storage power station provided by an embodiment of the present invention. The meteorological disaster warning system 1 for a wind-solar pumped-storage power station includes:

[0111] Configuration module 11 is used to delineate the control area of ​​the wind-solar-pumped-storage power station, obtain regional meteorological data for the control area, divide it into several elements, extract risk factors, traverse the occurrence time of the risk factors, and configure a buffer range for the occurrence time, defining the buffer range as the flight time of the drone;

[0112] The verification module 12 is configured to issue a flight instruction to the UAV when the flight time arrives, trigger the verification rules pre-embedded in the UAV, verify the regional meteorological data, and generate a verification result;

[0113] The marking module 13 is configured to, when the verification result is established, calibrate the regional meteorological data and occurrence time, obtain the flight trajectory of the drone, construct a risk verification zone, delete the portion of the risk verification zone that is outside the control area, dynamically modify the boundary of the risk verification zone, locate the production equipment within the risk verification zone, configure the equipment toughness of each production equipment, compare the equipment toughness with the regional meteorological data, and mark sensitive equipment;

[0114] The push module 14 is used to define the sensitive equipment as a waypoint in the risk verification area, generate a flight route, and send the flight route to the drone, collect real-time meteorological data along the flight route, adjust the sensitive equipment, integrate the sensitive equipment, regional meteorological data and occurrence time, generate an early warning notification, and push the early warning notification to a preset terminal.

[0115] Figure 7 The following is a structural block diagram of the meteorological disaster warning system for wind-solar pumped storage power stations provided by an embodiment of the present invention. The configuration module 11 includes:

[0116] A hierarchical unit 111 is configured to divide the control area into a plurality of levels, wherein the levels include at least a core area, a buffer area, and a peripheral monitoring area;

[0117] a mapping unit 112, configured to establish a mapping between each of the levels and regional meteorological data, wherein the regional meteorological data is provided by a meteorological service provider;

[0118] an optimization unit 113, configured to determine a deployment position of a field meteorological sensor, acquire real-time monitoring data, and optimize the regional meteorological data;

[0119] a definition unit 114, configured to determine whether the element exceeds a device resilience, and if so, define the corresponding element as a risk factor, and insert a label generated by the risk factor into the control region;

[0120] an embedding unit 115, configured to integrate all the risk factors, generate a risk set, and embed the risk set into an early warning notification.

[0121] Figure 8 A component structure block diagram of the wind-solar pumped storage power station meteorological disaster early warning system is shown, and the verification module 12 includes:

[0122] an output unit 121, configured to input the real-time meteorological data into the constructed numerical weather prediction model, and output calibrated data;

[0123] a calculation unit 122, configured to integrate the verification rule and the calibrated data, and verify the regional meteorological data, wherein the verification rule is that a difference between the calibrated data and the regional meteorological data is calculated;

[0124] an updating unit 123, configured to dynamically update the difference according to the real-time meteorological data, and if the difference is less than a preset threshold, define the verification result as being established, and if not, define the verification result as not being established.

[0125] Figure 9 A component structure block diagram of the wind-solar pumped storage power station meteorological disaster early warning system is shown, and the marking module 13 includes:

[0126] a selection unit 131, configured to randomly select a plurality of target points from the flight trajectory, and determine a risk score of each target point according to real-time meteorological data of the target point;

[0127] a construction unit 132, configured to integrate the target points with the risk score greater than a threshold, and construct a risk verification area by using a spatial interpolation method;

[0128] a correction unit 133, configured to select a plurality of test points from the boundary, determine a risk score of the test points, and correct the boundary by using the risk score;

[0129] The judging unit 134 is configured to judge whether the risk factor in the regional meteorological data is greater than the equipment toughness. If so, the corresponding production equipment is defined as a sensitive equipment.

[0130] Figure 10 The following is a structural block diagram of the meteorological disaster warning system for wind-solar pumped storage power stations provided by an embodiment of the present invention. The push module 14 includes:

[0131] A creating unit 141 is configured to create an emergency plan comparison table, wherein the emergency plan comparison table is composed of risk factor items, plan items, and production equipment items;

[0132] The starting unit 142 is configured to query the emergency plan comparison table according to the risk factor, traverse the plan corresponding to the sensitive device, and start the plan.

[0133] The configuration module 11 is mainly used to complete step S100, the verification module 12 is mainly used to complete step S200, the marking module 13 is mainly used to complete step S300, and the push module 14 is mainly used to complete step S400;

[0134] The layering unit 111 is mainly used to complete step S101, the mapping unit 112 is mainly used to complete step S102, the optimization unit 113 is mainly used to complete step S103, the definition unit 114 is mainly used to complete step S104, and the embedding unit 115 is mainly used to complete step S105;

[0135] The output unit 121 is mainly used to complete step S201, the calculation unit 122 is mainly used to complete step S202, and the updating unit 123 is mainly used to complete step S203;

[0136] The selection unit 131 is mainly used to complete step S301, the construction unit 132 is mainly used to complete step S302, the correction unit 133 is mainly used to complete step S303, and the judgment unit 134 is mainly used to complete step S304;

[0137] The creation unit 141 is mainly used to complete step S401, and the starting unit 142 is mainly used to complete step S402.

[0138] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0139] The above embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but should not be understood as a limitation on the patent scope of the present application. It should be noted that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

[0140] The above merely describes the preferred embodiments of the present application and should not be used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A meteorological disaster early warning method for a wind-solar pumped storage power station, characterized in that: The method comprises: Delineating the control area of ​​the wind-solar-pumped-storage power station, obtaining regional meteorological data for the control area, dividing the data into several elements, extracting risk factors, traversing the occurrence time of the risk factors, and configuring a buffer range for the occurrence time, where the buffer range is defined as the flight time of the drone; When the flight time arrives, a flight instruction is issued to the drone, triggering the verification rules pre-embedded in the drone to verify the regional meteorological data and generate a verification result; If the verification result is positive, the regional meteorological data and occurrence time are calibrated, the flight trajectory of the drone is obtained, a risk verification zone is constructed, the portion of the risk verification zone outside the control area is deleted, the boundary of the risk verification zone is dynamically revised, the production equipment within the risk verification zone is found, the equipment resilience of each production equipment is configured, the equipment resilience is compared with the regional meteorological data, and sensitive equipment is marked; In the risk verification area, the sensitive equipment is defined as a waypoint, a flight route is generated, and the flight route is sent to a drone. The drone is used to collect real-time meteorological data along the flight route, adjust the sensitive equipment, integrate the sensitive equipment, regional meteorological data and occurrence time, generate an early warning notification, and push the early warning notification to a preset terminal; The step of "issuing a flight instruction to the drone when the flight time arrives, triggering a verification rule pre-embedded in the drone, verifying the regional meteorological data, and generating a verification result" includes: Inputting the real-time meteorological data into the constructed numerical weather forecast model and outputting calibration data; Integrating the verification rule and calibration data to verify the regional meteorological data, wherein the verification rule is: calculating the difference between the calibration data and the regional meteorological data; Dynamically updating the difference value according to the real-time meteorological data, and defining the verification result as established if the difference value is less than a preset threshold value, otherwise, defining it as not established; The step of "building a risk verification zone" includes: Randomly select a number of target points from the flight trajectory, and determine a risk score for each target point based on real-time meteorological data of the target points; The target points with risk scores greater than a threshold are integrated and a risk verification area is constructed using a spatial interpolation method.

2. The meteorological disaster early warning method for wind-solar pumped storage power station according to claim 1 is characterized in that: The step of "demarcating the control area of ​​the wind-solar pumped storage power station and obtaining regional meteorological data for the control area" includes: Dividing the control area into multiple levels, wherein the levels include at least: a core area, a buffer area, and a peripheral monitoring area; Establishing a mapping between each of the layers and regional meteorological data, wherein the regional meteorological data is provided by a meteorological service provider; Determine the deployment location of on-site meteorological sensors, obtain real-time monitoring data, and optimize the meteorological data in the area.

3. The meteorological disaster early warning method for wind-solar pumped storage power station according to claim 2 is characterized in that: The steps of "dividing into several elements, extracting risk factors, traversing the occurrence time of the risk factors, configuring a buffer range for the occurrence time, and defining the buffer range as the flight time of the drone" include: determining whether the factor exceeds a set value; if so, defining the corresponding factor as a risk factor, and inserting a label generated by the risk factor into the control area; All risk factors are integrated to generate a risk set, and the risk set is embedded in the early warning notification.

4. The meteorological disaster early warning method for a wind-solar pumped storage power station according to claim 1, characterized in that: The step of "dynamically correcting the boundary of the risk verification zone, finding the production equipment located in the risk verification zone, configuring the equipment resilience of each production equipment, comparing the equipment resilience with regional meteorological data, and marking sensitive equipment" includes: Selecting a plurality of test points from the boundary, determining risk scores for the test points, and modifying the boundary using the risk scores; It is determined whether the risk factor in the regional meteorological data is greater than the equipment toughness. If so, the corresponding production equipment is defined as sensitive equipment.

5. The meteorological disaster early warning method for wind-solar pumped storage power station according to claim 1 is characterized in that: The step of "integrating the sensitive equipment, regional meteorological data and occurrence time, generating an early warning notification, and pushing the early warning notification to a preset terminal" includes: Creating an emergency plan comparison table, wherein the emergency plan comparison table is composed of risk factor items, plan items, and production equipment items; Based on the risk factors, the emergency plan comparison table is queried to find the plans corresponding to the sensitive equipment, and the plans are activated.

6. The meteorological disaster early warning method for a wind-solar pumped storage power station according to claim 1, characterized in that: The method further comprises: If the verification result is not established, adjusting the buffer range using the calibration data; After the buffer range ends, the risk factor is deleted and the flight instruction is revoked.

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