Electric power meteorological data fusion method and system

Abstract

The invention relates to an electric power meteorological data fusion method and system, and the method comprises the steps: S1, obtaining historical electric power meteorological data under different regional meteorological characteristics, and generating a comparison reference library; s2, performing accuracy verification on the newly collected electric power meteorological data based on the comparison reference library; s3, in the accuracy verification process, if the newly collected electric power meteorological data does not have accuracy deviation, the step S4 is executed; if the newly collected electric power meteorological data has accuracy deviation, supplementing and correcting the part with the accuracy deviation; and S4, marking and storing the newly collected electric power meteorological data according to the space-time coordinates. According to the method, accuracy analysis is carried out on the newly collected electric power meteorological data by using the comparison reference library, abnormal data can be corrected and supplemented while abnormal positioning is realized, the integrity and accuracy of the newly collected electric power meteorological data are ensured, and the overall evaluation effect after electric power meteorological data fusion is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power meteorological data fusion, and in particular to an electric power meteorological data fusion method and system. Background Art

[0002] Power meteorological data refers to scientific and technological data that integrates the ever-changing meteorological phenomena and the mutual influence of the geological environment, as well as related factors in power construction and operation. These data are the basis for high-quality power supply and the guarantee for safe operation. They are of great significance to the planning, design, operation and dispatching of power systems. At present, the power sector lacks efficient integration and standardized management of meteorological, status monitoring and other data with "many types and large quantities".

[0003] Although the existing technology can block and integrate multi-source power meteorological data collected from various meteorological data generation channels, directly realize the assimilation of multi-source heterogeneous observation data, and significantly improve the accuracy of power meteorological numerical weather forecasts, it lacks verification of data accuracy and cannot guarantee the effectiveness of power meteorological data after fusion.

[0004] It is not difficult to find that there is a lack of accuracy analysis of the existing power meteorological data before fusion, and when errors occur in some meteorological data, the data cannot be effectively filled and repaired, which leads to omissions in the power meteorological data during the fusion process, resulting in poor overall evaluation of the power meteorological data after fusion.

[0005] Therefore, it is necessary to improve the fusion method of power meteorological data in order to achieve accurate analysis of the newly collected power meteorological data and fill and patch the data, thereby effectively improving the overall evaluation effect after the fusion of power meteorological data. Summary of the invention

[0006] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the newly collected electric power meteorological data is not accurately analyzed and the data is not filled and repaired.

[0007] In order to solve the above technical problems, the present invention provides a method for fusion of electric power meteorological data, comprising:

[0008] Step S1: Obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library;

[0009] Step S2: verifying the accuracy of the newly collected power meteorological data based on the comparison reference library;

[0010] Step S3: During the accuracy verification process, if the newly collected power meteorological data has no accuracy deviation, go to step S4; if the newly collected power meteorological data has accuracy deviation, supplement and correct the part with accuracy deviation;

[0011] Step S4: Mark and store the newly collected power meteorological data according to the time and space coordinates.

[0012] In one embodiment of the present invention, the method of obtaining historical power meteorological data under different regional meteorological characteristics and generating a comparison reference library in step S1 includes:

[0013] Step S11: collecting historical power meteorological data including temperature, humidity, wind speed, wind direction and rainfall elements, wherein the temperature, humidity, wind speed, wind direction and rainfall are data collected at the same time and the same spatial coordinates, and used as a data packet;

[0014] Step S12: classifying the data packets according to the regional meteorological characteristics of the data collection;

[0015] Step S13: Eliminate data packets with abnormal data, and generate a comparison reference library containing several groups of data packets corresponding to meteorological characteristics of different regions.

[0016] In one embodiment of the present invention, the method for verifying the accuracy of the newly collected power meteorological data based on the comparison reference library in step S2 includes:

[0017] Step S21: perform a similarity comparison between the newly collected power meteorological data and the data packets classified under the same regional meteorological characteristics:

[0018]

[0019] A={a1,a2,a3,a4,a5}

[0020] B={b1, b2, b3, b4, b5};

[0021] Wherein, d is the Euclidean distance, A is the newly collected power meteorological data set, a1 is the temperature element feature in the newly collected power meteorological data, a2 is the humidity element feature in the newly collected power meteorological data, a3 is the wind speed element feature in the newly collected power meteorological data, a4 is the wind direction element feature in the newly collected power meteorological data, a5 is the rainfall element feature in the newly collected power meteorological data, B is the data packet, b1 is the temperature element feature in the data packet, b2 is the humidity element feature in the data packet, b3 is the wind speed element feature in the data packet, b4 is the wind direction element feature in the data packet, and b5 is the rainfall element feature in the data packet;

[0022] Step S22: Set the first standard threshold R1 of the Euclidean distance. When there is one result in the calculation results of d(A, B) that is higher than the first standard threshold R1, it is judged that the newly collected power meteorological data has no accuracy deviation; when all the calculation results of d(A, B) are lower than the first standard threshold R1, it is judged that the newly collected power meteorological data has accuracy deviation.

[0023] In one embodiment of the present invention, if accuracy deviation occurs in step S3, the method for supplementing and correcting the part where the accuracy deviation occurs includes:

[0024] Step S31: Filtering ten groups of data packets whose calculation results in step S21 are closest to the first standard threshold R1 as reference data packets;

[0025] Step S32: performing a similarity comparison between the newly collected power meteorological data with accuracy deviation and all corresponding elements in the reference data package according to the Euclidean distance method, and formulating a second standard threshold R2 of the Euclidean distance corresponding to different elements;

[0026] Step S33: Filter the elements whose similarity comparison results in step S32 are lower than the second standard threshold R2 as abnormal elements, and sum and average all elements corresponding to the abnormal elements in the reference data packet, and finally use the average value as supplementary correction data to fill in the abnormal elements in the newly collected power meteorological data.

[0027] In one embodiment of the present invention, after determining the abnormal element in step S33, the method further includes: marking the meteorological data collection device where the abnormal element is located as suspicious according to the time-space coordinates, and determining that the meteorological data collection device may be faulty after the suspicious mark reaches a set number of times in succession;

[0028] Perform an on-site inspection to determine whether the meteorological data collection device is faulty. If the inspection result shows that the meteorological data collection device is normal, define the element data corresponding to the abnormal element judged as abnormal in step S33 in the meteorological data collected by the meteorological data collection device as abnormal repair data, and add the abnormal repair data as an updated data packet to the corresponding regional meteorological feature classification in the comparison reference library, and replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data. If the inspection result shows that the meteorological data collection device is faulty, repair or replace the meteorological data collection device.

[0029] In one embodiment of the present invention, the time-space coordinates in step S4 include the collection time and space coordinate information corresponding to the power meteorological data collection point.

[0030] In order to solve the above technical problems, the present invention provides an electric power meteorological data fusion system, including a data sorting module, an accuracy verification module and an electric power meteorological data storage module, wherein the data sorting module is connected to the accuracy verification module, and the accuracy verification module is connected to the electric power meteorological data storage module;

[0031] The data sorting module is used to obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library;

[0032] The accuracy verification module is used to verify the accuracy of newly collected power meteorological data based on the comparison reference library;

[0033] The electric power meteorological data storage module is used to mark and store newly collected electric power meteorological data according to time and space coordinates.

[0034] In one embodiment of the present invention, the accuracy verification module includes a supplementary correction unit, a continuous abnormality monitoring unit and a supplementary recording replacement unit, wherein the supplementary correction unit is connected to the continuous abnormality monitoring unit, and the continuous abnormality monitoring unit is connected to the supplementary recording replacement unit;

[0035] The supplement correction unit and the supplement recording replacement unit are both connected to the electric power meteorological data storage module;

[0036] The supplementary correction unit is used to supplement and correct the part of the newly collected power meteorological data with accuracy deviation when the accuracy deviation occurs;

[0037] The continuous abnormality monitoring unit is used to conduct on-site inspection and verification of the meteorological collection equipment corresponding to the same space-time coordinate when the meteorological data corresponding to the same space-time coordinate has a set number of continuous supplementary corrections;

[0038] The supplementary recording and replacement unit is used to define the element data corresponding to the abnormal elements in the meteorological data collected by the meteorological collection equipment as abnormal data packets when the meteorological collection equipment is detected on site and is normal, and to supplement the abnormal repair data into the corresponding regional meteorological feature classification in the comparison reference library as an updated data packet, and to replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data; at the same time, it is used to repair or replace the meteorological collection equipment after the meteorological collection equipment is detected on site and has a fault.

[0039] To solve the above technical problems, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned electric power meteorological data fusion method when executing the computer program.

[0040] In order to solve the above technical problems, the present invention provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned power meteorological data fusion method are implemented.

[0041] The above technical solution of the present invention has the following advantages compared with the prior art:

[0042] The present invention builds a comparison reference library based on historical power meteorological data and regional meteorological characteristics, and stores meteorological data in accordance with time and space coordinates. When acquiring newly collected power meteorological data, the comparison reference library is used to analyze the accuracy of the newly collected power meteorological data, and abnormality positioning is achieved. The abnormal data can also be corrected and supplemented to ensure the integrity and accuracy of the newly collected power meteorological data, and effectively improve the overall evaluation effect after the fusion of power meteorological data.

[0043] The present invention triggers a field inspection instruction of the corresponding meteorological collection equipment through continuous abnormal monitoring of abnormal element collection points (meteorological collection equipment), and promptly repairs the damaged meteorological collection equipment according to the field inspection results. When the field inspection results show that the equipment is not damaged, the data when the corresponding element is determined to be an abnormal element is determined as abnormal repair data, and the supplementary correction data is replaced again according to the time and space coordinates to further ensure the accuracy of the power meteorological data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings.

[0045] Figure 1 It is a schematic flow chart of the method of the present invention;

[0046] Figure 2 It is a schematic diagram of the original path framework distribution of the system of the present invention.

[0047] Explanation of the reference numerals in the specification: 1. Data sorting module; 2. Accuracy verification module; 201. Supplementary correction unit; 202. Continuous abnormality monitoring unit; 203. Supplementary recording and replacement unit; 3. Electric power meteorological data storage module. DETAILED DESCRIPTION

[0048] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0049] Embodiment 1

[0050] Reference Figure 1 The present invention relates to a method for fusion of electric power meteorological data, comprising:

[0051] Step S1: Obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library;

[0052] Step S2: verifying the accuracy of the newly collected power meteorological data based on the comparison reference library;

[0053] Step S3: During the accuracy verification process, if the newly collected power meteorological data has no accuracy deviation, go to step S4; if the newly collected power meteorological data has accuracy deviation, supplement and correct the part with accuracy deviation;

[0054] Step S4: Mark and store the newly collected power meteorological data according to the time and space coordinates.

[0055] Furthermore, the method of obtaining historical power meteorological data under different regional meteorological characteristics and generating a comparison reference library in step S1 includes:

[0056] Step S11: collecting historical power meteorological data including temperature, humidity, wind speed, wind direction and rainfall elements, wherein the temperature, humidity, wind speed, wind direction and rainfall are data collected at the same time and the same spatial coordinates, and used as a data packet;

[0057] Step S12: classifying the data packets according to the regional meteorological characteristics of the data collection;

[0058] Step S13: Eliminate data packets with abnormal data, and generate a comparison reference library containing several groups of data packets corresponding to meteorological characteristics of different regions.

[0059] Furthermore, the method for verifying the accuracy of the newly collected power meteorological data based on the comparison reference library in step S2 includes:

[0060] Step S21: perform a similarity comparison between the newly collected power meteorological data and the data packets classified under the same regional meteorological characteristics:

[0061]

[0062] A={a1,a2,a3,a4,a5}

[0063] B={b1, b2, b3, b4, b5};

[0064] Wherein, d is the Euclidean distance, A is the newly collected power meteorological data set, a1 is the temperature element feature in the newly collected power meteorological data, a2 is the humidity element feature in the newly collected power meteorological data, a3 is the wind speed element feature in the newly collected power meteorological data, a4 is the wind direction element feature in the newly collected power meteorological data, a5 is the rainfall element feature in the newly collected power meteorological data, B is the data packet, b1 is the temperature element feature in the data packet, b2 is the humidity element feature in the data packet, b3 is the wind speed element feature in the data packet, b4 is the wind direction element feature in the data packet, and b5 is the rainfall element feature in the data packet;

[0065] Step S22: Set the first standard threshold R1 of the Euclidean distance. When there is only one result in the calculation results of d(A, B) that is higher than the first standard threshold R1, it is judged that the newly collected power meteorological data has no accuracy deviation; when all the calculation results of d(A, B) are lower than the first standard threshold R1, it is judged that the newly collected power meteorological data has an accuracy deviation. In short, the newly collected power meteorological data is to be compared with several groups of data packets in the same region by Euclidean distance. As long as one Euclidean distance comparison result is higher than the first standard threshold R1, the newly collected power meteorological data has no accuracy deviation. If all the Euclidean distance comparison results are lower than the first standard threshold R1, the newly collected power meteorological data has an accuracy deviation.

[0066] Furthermore, if an accuracy deviation occurs in step S3, the method for supplementing and correcting the part where the accuracy deviation occurs includes:

[0067] Step S31: Filtering ten groups of data packets whose calculation results in step S21 are closest to the first standard threshold R1 as reference data packets;

[0068] Step S32: performing a similarity comparison between the newly collected power meteorological data with accuracy deviation and all corresponding single elements in the reference data package (for example, comparing temperature elements with temperature elements, comparing wind speed elements with wind speed elements, etc.) according to the Euclidean distance method, and formulating a second standard threshold R2 of the Euclidean distance corresponding to different elements;

[0069] Step S33: Filter the elements whose similarity comparison results in step S32 are lower than the second standard threshold R2 as abnormal elements, and sum and average all normal elements corresponding to the abnormal elements in the reference data packet, and finally use the average value as supplementary correction data to fill in the abnormal elements in the newly collected power meteorological data.

[0070] Furthermore, after determining the abnormal element in step S33, the method further includes: marking the meteorological data collection device where the abnormal element is located as suspicious according to the time-space coordinates, and determining that the meteorological data collection device may be faulty after the suspicious mark reaches a set number of times in succession;

[0071] Perform an on-site inspection to determine whether the meteorological data collection device is faulty. If the inspection result shows that the meteorological data collection device is normal, define the element data corresponding to the abnormal element judged as abnormal in step S33 in the meteorological data collected by the meteorological data collection device as abnormal repair data, and add the abnormal repair data as an updated data packet to the corresponding regional meteorological feature classification in the comparison reference library, and replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data. If the inspection result shows that the meteorological data collection device is faulty, repair or replace the meteorological data collection device.

[0072] Furthermore, the time-space coordinates in step S4 include the collection time and space coordinate information corresponding to the power meteorological data collection point.

[0073] Embodiment 2

[0074] This embodiment provides an electric power meteorological data fusion system, including a data sorting module 1, an accuracy verification module 2 and an electric power meteorological data storage module 3, wherein the data sorting module 1 is connected to the accuracy verification module 2, and the accuracy verification module 2 is connected to the electric power meteorological data storage module 3;

[0075] The data sorting module 1 is used to obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library;

[0076] The accuracy verification module 2 is used to verify the accuracy of the newly collected power meteorological data based on the comparison reference library;

[0077] The electric power meteorological data storage module 3 is used to mark and store newly collected electric power meteorological data according to time and space coordinates.

[0078] Further, the accuracy verification module 2 includes a supplementary correction unit 201, a continuous abnormality monitoring unit 202 and a supplementary recording replacement unit 203, wherein the supplementary correction unit 201 is connected to the continuous abnormality monitoring unit 202, and the continuous abnormality monitoring unit 202 is connected to the supplementary recording replacement unit 203;

[0079] The supplement correction unit 201 and the supplement recording replacement unit 203 are both connected to the power meteorological data storage module 3;

[0080] The supplementary correction unit 201 is used to supplement and correct the part of the newly collected power meteorological data that has an accuracy deviation when the accuracy deviation occurs;

[0081] The continuous abnormality monitoring unit 202 is used to conduct a field inspection and verification of the meteorological collection equipment corresponding to the same space-time coordinate when the meteorological data corresponding to the same space-time coordinate has a set number of continuous supplementary corrections;

[0082] The supplementary recording and replacement unit 203 is used to define the element data corresponding to the abnormal elements in the meteorological data collected by the meteorological data collection device as abnormal repair data when the meteorological data collected by the meteorological data collection device is detected to be normal on the spot, and to supplement the abnormal repair data into the corresponding regional meteorological feature classification in the comparison reference library as an updated data packet, and to replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data; at the same time, it is used to repair or replace the meteorological data collection device after the meteorological data collection device is detected to be faulty on the spot.

[0083] Embodiment 3

[0084] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the electric power meteorological data fusion method described in Embodiment 1 are implemented.

[0085] Embodiment 4

[0086] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the electric power meteorological data fusion method described in the first embodiment are implemented.

[0087] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiment, complete software embodiment, or the embodiment in combination with software and hardware. Moreover, the present application can adopt the form of the computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can adopt various computer languages ​​to realize, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0088] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0089] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0090] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0091] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0092] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. A method for fusion of electric power meteorological data, characterized by: include: Step S1: Obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library; Step S2: verifying the accuracy of the newly collected power meteorological data based on the comparison reference library; Step S3: During the accuracy verification process, if the newly collected power meteorological data has no accuracy deviation, go to step S4; if the newly collected power meteorological data has accuracy deviation, supplement and correct the part with accuracy deviation; Step S4: Mark and store the newly collected power meteorological data according to the time and space coordinates.

2. The electric power meteorological data fusion method according to claim 1 is characterized in that: The method for obtaining historical power meteorological data under different regional meteorological characteristics and generating a comparison reference library in step S1 includes: Step S11: collecting historical power meteorological data including temperature, humidity, wind speed, wind direction and rainfall elements, wherein the temperature, humidity, wind speed, wind direction and rainfall are data collected at the same time and the same spatial coordinates, and used as a data packet; Step S12: classifying the data packets according to the regional meteorological characteristics of the data collection; Step S13: Eliminate data packets with abnormal data, and generate a comparison reference library containing several groups of data packets corresponding to meteorological characteristics of different regions.

3. The electric power meteorological data fusion method according to claim 2 is characterized in that: The method for verifying the accuracy of the newly collected power meteorological data based on the comparison reference library in step S2 includes: Step S21: perform a similarity comparison between the newly collected power meteorological data and the data packets classified under the same regional meteorological characteristics: A={a1,a2,a3,a4,a5} B={b1, b2, b3, b4, b5}; Wherein, d is the Euclidean distance, A is the newly collected power meteorological data set, a1 is the temperature element feature in the newly collected power meteorological data, a2 is the humidity element feature in the newly collected power meteorological data, a3 is the wind speed element feature in the newly collected power meteorological data, a4 is the wind direction element feature in the newly collected power meteorological data, a5 is the rainfall element feature in the newly collected power meteorological data, B is the data packet, b1 is the temperature element feature in the data packet, b2 is the humidity element feature in the data packet, b3 is the wind speed element feature in the data packet, b4 is the wind direction element feature in the data packet, and b5 is the rainfall element feature in the data packet; Step S22: Set the first standard threshold R1 of the Euclidean distance. When there is one result in the calculation results of d(A, B) that is higher than the first standard threshold R1, it is judged that the newly collected power meteorological data has no accuracy deviation; when all the calculation results of d(A, B) are lower than the first standard threshold R1, it is judged that the newly collected power meteorological data has accuracy deviation.

4. The electric power meteorological data fusion method according to claim 3 is characterized in that: If an accuracy deviation occurs in step S3, the method for supplementing and correcting the portion where the accuracy deviation occurs includes: Step S31: Filtering ten groups of data packets whose calculation results in step S21 are closest to the first standard threshold R1 as reference data packets; Step S32: performing a similarity comparison between the newly collected power meteorological data with accuracy deviation and all corresponding elements in the reference data package according to the Euclidean distance method, and formulating a second standard threshold R2 of the Euclidean distance corresponding to different elements; Step S33: Filter the elements whose similarity comparison results in step S32 are lower than the second standard threshold R2 as abnormal elements, and sum and average all elements corresponding to the abnormal elements in the reference data packet, and finally use the average value as supplementary correction data to fill in the abnormal elements in the newly collected power meteorological data.

5. The electric power meteorological data fusion method according to claim 4 is characterized in that: After the abnormal element is determined in step S33, the method further includes: marking the meteorological data collection device corresponding to the power meteorological data collection point where the abnormal element is located as suspicious according to the time-space coordinates, and determining that the meteorological data collection device may be faulty after the suspicious mark reaches a set number of times in succession; Perform an on-site inspection to check whether the meteorological data collection device has a fault. If the inspection result shows that the meteorological data collection device is normal, define the element data corresponding to the abnormal element judged as abnormal in step S33 in the power meteorological data collected by the meteorological data collection device as abnormal repair data, and add the abnormal repair data as an update data packet to the corresponding regional meteorological feature classification in the comparison reference library, and replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data; if the inspection result shows that the meteorological data collection device has a fault, repair or replace the meteorological data collection device.

6. The electric power meteorological data fusion method according to claim 1 is characterized in that: The time-space coordinates in step S4 include the collection time and space coordinate information corresponding to the power meteorological data collection point.

7. An electric power meteorological data fusion system, characterized by: It comprises a data sorting module (1), an accuracy verification module (2) and an electric power meteorological data storage module (3), wherein the data sorting module (1) is connected to the accuracy verification module (2), and the accuracy verification module (2) is connected to the electric power meteorological data storage module (3); The data sorting module (1) is used to obtain historical power meteorological data under different regional meteorological characteristics and generate a comparison reference library; The accuracy verification module (2) is used to verify the accuracy of the newly collected power meteorological data based on the comparison reference library; The electric power meteorological data storage module (3) is used to mark and store newly collected electric power meteorological data according to time and space coordinates.

8. The electric power meteorological data fusion system according to claim 7 is characterized in that: The accuracy verification module (2) comprises a supplementary correction unit (201), a continuous abnormality monitoring unit (202) and a supplementary recording replacement unit (203), wherein the supplementary correction unit (201) is connected to the continuous abnormality monitoring unit (202), and the continuous abnormality monitoring unit (202) is connected to the supplementary recording replacement unit (203); The supplementary correction unit (201) and the supplementary recording replacement unit (203) are both connected to the electric power meteorological data storage module (3); The supplementary correction unit (201) is used to supplement and correct the part of the newly collected power meteorological data that has an accuracy deviation when the accuracy deviation occurs; The continuous abnormality monitoring unit (202) is used to conduct on-site inspection and verification of the meteorological collection equipment corresponding to the same space-time coordinate when the meteorological data corresponding to the same space-time coordinate has a set number of continuous supplementary corrections; The re-recording and replacement unit (203) is used to define the element data corresponding to the abnormal element in the meteorological data collected by the meteorological data collection device as abnormal repair data when the meteorological data collected by the meteorological data collection device is detected to be normal, and to re-record the abnormal repair data as an update data packet into the corresponding regional meteorological feature classification in the comparison reference library, and to replace the supplementary correction data of the corresponding time and space coordinates with the abnormal repair data; and is also used to repair or replace the meteorological data collection device after the meteorological data collection device is detected to be faulty in the field.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the electric power meteorological data fusion method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the electric power meteorological data fusion method according to any one of claims 1 to 6 are implemented.

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