Radar extrapolation power grid icing short-term calculation method and system

Abstract

The embodiment of the present invention provides a radar extrapolated short-term calculation method and system for power grid icing, the method comprising: obtaining radar measurement data measured at a radar monitoring point; performing inversion calculation on the radar measurement data; using inversion data fusion to calculate the initial field; performing extrapolation calculation on radar water vapor; and calculating the thickness of ice covering the transmission line. Through the above technical scheme, the radar reflectivity data is cleverly combined with water vapor for calculation, thereby realizing local single-point regional remote sensing monitoring, that is, ensuring the local information for extrapolation calculation, including surrounding information. In addition, the scheme has good versatility, and can be used for extrapolation prediction calculation of ice covering of power transmission lines in various areas prone to icing. In addition, it can realize timely warning of icing on transmission lines, thereby improving the pertinence and effectiveness of anti-icing work.

Description

Technical Field

[0001] The invention belongs to the field of power transmission and distribution, and in particular relates to a radar extrapolated short-term and impending calculation method and system for power grid icing. Background Art

[0002] In recent years, the power grid has frequently encountered icing disasters in winter, which has seriously affected the safety and security of power supply. In order to make good preparations for ice prevention, grasp the development trend of ice conditions, and enhance the ability of the power grid to resist rain, snow and ice, it is urgent to carry out accurate transmission line icing warning.

[0003] At present, power grid companies use micro-meteorological ice monitoring devices to obtain ice monitoring conditions at the current location, and propose a big data method to extrapolate the calculation method of ice. However, since only local monitoring conditions are considered, and changes in the surrounding environment are not considered, the ice extrapolation results are greatly deviated from the actual situation. The use of numerical ice forecasting technology for power grids can achieve short-term ice forecasts for three days, but for areas with complex terrain, ice may grow rapidly within a few hours, and the time granularity of short-term forecasts is based on days and cannot be refined to a few hours. At present, the meteorological department mainly uses short-term forecasting technology to make up for the forecast of the next few hours, but it is only used for summer rainstorm forecasts and cannot be directly used for winter ice forecasts. Summary of the invention

[0004] The purpose of the embodiment of the present invention is to provide a radar extrapolated short-term calculation method and system for power grid icing. According to the iced tower section of the transmission line, the radar deployment position is set, and radar active remote sensing detection is carried out. The detection data is integrated into the initial field of the numerical model, and dynamic extrapolation calculation is carried out to obtain the meteorological environment changes in the next few hours, and the icing model is used to carry out icing calculation.

[0005] In order to achieve the above-mentioned object, the first aspect of the present invention provides a radar extrapolated power grid icing short-term calculation method, comprising:

[0006] Acquire radar measurement data measured at radar monitoring points;

[0007] Performing inversion calculation on the radar measurement data;

[0008] Use inversion data fusion to calculate the initial field;

[0009] Physical extrapolation calculation of water vapor inverted by radar;

[0010] Calculate the thickness of ice covering the transmission lines.

[0011] In an embodiment of the present invention, the acquiring radar measurement data measured at a radar monitoring point includes:

[0012] Determine the transmission line tower section to be detected to set the detection point M;

[0013] Deploy the millimeter wave radar at the detection point M;

[0014] Taking the detection point M as the center and the millimeter wave radar detection range L as the radius, the transmission line tower section is measured;

[0015] A grid with a resolution of r is established, and the radar reflectivity data matrix R at the grid points is detected and obtained.

[0016] In an embodiment of the present invention, performing inversion calculation on the radar measurement data includes:

[0017] The air water content matrix W is calculated based on the radar reflectivity data matrix R using formula (1):

[0018] W=10 aR+b Formula (1)

[0019] Wherein, W is the water content matrix, R is the radar reflectivity data matrix, and a and b are calculation coefficient matrices.

[0020] In an embodiment of the present invention, the using of inversion data fusion to calculate the initial field comprises:

[0021] The meteorological initial field dataset {m} of the calculation area specified in the radar measurement data measured at the radar monitoring point is obtained from the Global Forecast System GFS or the European Centre for Medium-Range Weather Forecasts ECMWF, and the calculated inverted air moisture content W is fused into the initial field dataset {m} to obtain a fused dataset {M}.

[0022] In the embodiment of the present invention, the weather at least includes water vapor.

[0023] The calculation formula for water vapor correction is defined as:

[0024] Q=q+λ(Wq)

[0025] Among them, Q is the corrected water vapor content matrix, q is the water vapor content matrix in the data set {m}, and λ is the weight coefficient.

[0026] In an embodiment of the present invention, the physical extrapolation calculation of the water vapor inverted by radar includes:

[0027] Establish a water vapor dynamics extrapolation calculation model;

[0028] According to the fused data set {M}, the established water vapor dynamics extrapolation model is used to calculate the future time data set {Mt};

[0029] Among them, for the water vapor content Q, the water vapor dynamics extrapolation calculation model is defined as the following extrapolation calculation formula:

[0030] in, represents the three-dimensional velocity field, Fq represents the water vapor content at the current grid point, and ▽Q represents the gradient of water vapor.

[0031] In an embodiment of the present invention, calculating the ice thickness of the transmission line includes:

[0032] According to the extrapolated water vapor content, the ice thickness of the line is calculated using the following ice calculation formula:

[0033] When the temperature is less than or equal to 0°C, ΔI=f(Q,S)

[0034] When the temperature is greater than 0°C, ΔI=0

[0035] The total ice thickness is

[0036] Where I is the total ice thickness, Q is the water vapor content at the grid point after extrapolation, S is the vertical conductor wind field after extrapolation, and f(Q,S) is the ice calculation model.

[0037] In the embodiment of the present invention, the step of determining the transmission line tower section to be detected to set the detection point M includes:

[0038] The 10 towers of the 500 kV line section are determined as the detection section, and the fifth tower of the 10 towers is set as the detection point M.

[0039] In the embodiment of the present invention, the detection range L of the millimeter wave radar is 5 km.

[0040] A second aspect of the present invention provides a radar extrapolated power grid icing short-term imminent calculation system, which is configured to execute the above-mentioned radar extrapolated power grid icing short-term imminent calculation method.

[0041] Through the above technical solution, the radar reflectivity data is cleverly combined with water vapor for calculation, realizing local single-point regional remote sensing monitoring, that is, ensuring the local information of the extrapolated calculation, including surrounding information. In addition, the solution has good versatility and can be used for the extrapolated prediction calculation of ice coverage of power transmission lines in various icing-prone areas. In addition, it can realize timely warning of ice coverage of transmission lines, improving the pertinence and effectiveness of anti-icing work.

[0042] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0044] Figure 1 A flowchart of a radar extrapolated power grid icing short-term calculation method according to an embodiment of the present invention is schematically shown;

[0045] Figure 2 The radar positions and grid points in a grid with a resolution of r established during the inversion calculation of the radar measurement data are schematically shown. DETAILED DESCRIPTION

[0046] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0047] The idea of ​​the embodiment of the present invention is to propose a radar extrapolated power grid icing short-term calculation method and system to solve the problem of predicting winter icing in the next few hours and improve the anti-icing warning capability of the power grid.

[0048] Figure 1 The flowchart of the radar extrapolation power grid icing short-term calculation method according to an embodiment of the present invention is schematically shown. Figure 1 As shown, in an embodiment of the present invention, a radar extrapolated power grid icing short-term calculation method (hereinafter referred to as "method") is provided, which may include the following steps.

[0049] In step S11, radar measurement data measured at the radar monitoring point is obtained;

[0050] In step S12, performing inversion calculation on the radar measurement data;

[0051] In step S13, the initial field is calculated using inversion data fusion;

[0052] In step S14, physical extrapolation calculation is performed on the water vapor inverted by the radar;

[0053] In step S15, the ice thickness of the transmission line is calculated.

[0054] Specifically, in the embodiment of the present invention, the radar may be a millimeter wave radar, and the acquiring of radar measurement data measured at the radar monitoring point may include:

[0055] Determine the transmission line tower section to be detected to set the detection point M;

[0056] Deploy the millimeter wave radar at the detection point M;

[0057] Taking the detection point M as the center and the millimeter wave radar detection range L as the radius, the transmission line tower section is measured;

[0058] A grid with a resolution of r is established, and a radar reflectivity data matrix R on the grid points is detected and obtained. FIG2 schematically shows the grid points and radar positions in the established grid. In one example, the resolution r can be, for example, 200mx200m, that is, each grid represents an area of ​​200mx200m. In another example, the resolution r can be 500mx500m, that is, each grid represents an area of ​​500mx500m.

[0059] Specifically, in the embodiment of the present invention, performing inversion calculation on the radar measurement data may include:

[0060] The air water content matrix W is calculated based on the radar reflectivity data matrix R using formula (1):

[0061] W=10 aR+b Formula (1)

[0062] Wherein, W is the water content matrix, R is the radar reflectivity data matrix, and a and b are calculation coefficient matrices.

[0063] Specifically, in the embodiment of the present invention, the use of inversion data fusion to calculate the initial field may include:

[0064] The meteorological initial field data set {m} of the calculation area specified in the radar measurement data measured at the radar monitoring point is obtained from the Global Forecast System (GFS) or the European Centre for Medium-Range Weather Forecasts (ECMWF), and the calculated inverted air moisture content W is fused into the initial field data set {m} to obtain a fused data set {M}.

[0065] Specifically, in the embodiment of the present invention, the meteorology at least includes water vapor. In addition, the meteorology may also include wind speed, temperature, etc.

[0066] The calculation formula for water vapor correction is defined as formula (2):

[0067] Q=q+λ(Wq) Formula (2)

[0068] Wherein, Q is the corrected water vapor content matrix, q is the water vapor content matrix in the data set {m}, and λ is the weight coefficient. In one example, λ can be determined according to the ratio of the average water vapor content of the surrounding grid points of the current grid point to the water vapor content value of the current grid point.

[0069] Specifically, in the embodiment of the present invention, the physical extrapolation calculation of the water vapor inverted by the radar includes:

[0070] Establish a water vapor dynamics extrapolation calculation model;

[0071] According to the fused data set {M}, the established water vapor dynamics extrapolation model is used to calculate the future time data set {Mt};

[0072] Among them, for the water vapor content Q, the water vapor dynamics extrapolation calculation model is defined as the following extrapolation calculation formula:

[0073] in, represents the three-dimensional velocity field, Fq represents the water vapor content at the current grid point, and ▽Q represents the water vapor content gradient. According to this formula, the water vapor content at the current grid point at the next moment can be calculated.

[0074] Specifically, in an embodiment of the present invention, calculating the ice thickness of the transmission line includes:

[0075] According to the extrapolated water vapor content, the ice thickness of the line is calculated using the following ice calculation formula:

[0076] When the temperature is less than or equal to 0°C, ΔI=f(Q,S)

[0077] When the temperature is greater than 0°C, ΔI=0

[0078] The total ice thickness is

[0079] Where I is the total ice thickness, Q represents the water vapor content at the grid point after extrapolation, S represents the vertical conductor wind field after extrapolation, and f(Q,S) represents the ice calculation model, which may be known.

[0080] Specifically, in the embodiment of the present invention, the determining of the transmission line tower section to be detected to set the detection point M includes:

[0081] The 10 towers of the 500 kV line section are determined as the detection section, and the fifth tower of the 10 towers is set as the detection point M.

[0082] Specifically, in the embodiment of the present invention, the detection range L of the millimeter wave radar may be, for example, 3 km, 5 km, 8 km, etc., preferably, may be 5 km.

[0083] The following takes an ice-covered section of a 500 kV transmission line in Hunan Province as an example to further illustrate an embodiment of the present invention.

[0084] (1) Acquisition of radar monitoring point measurement data

[0085] The 1#-10# towers of the 500kV line section are determined as the detection section, and the detection point is set as the 5# tower of the line. With the 5# tower as the center and the millimeter wave radar detection range of 5km as the radius, the transmission line tower section is measured to obtain the radar reflectivity data matrix R.

[0086] (2) Inversion calculation of radar measurement data

[0087] According to the radar reflectivity data matrix R measured in step (1), the water content matrix W of the air is calculated:

[0088] W=10 aR+b

[0089] Among them, a and b are calculation coefficient matrices.

[0090] (3) Inversion data fusion calculation of initial field

[0091] Obtain the meteorological initial field data set {m} of wind speed, temperature, water vapor, etc. in the calculation area specified in step (1) from ECMWF, and fuse the air moisture content W calculated and inverted in step (2) into the initial field data set {m} to obtain the fused data set {M}. The calculation formula for water vapor correction is as follows:

[0092] Q=q+λ(Wq)

[0093] Among them, Q is the corrected water vapor content matrix, q is the water vapor content matrix in the data set {m}, and λ is the weight coefficient matrix.

[0094] (4) Extrapolation fast calculation

[0095] Establish a water vapor dynamic extrapolation calculation model. Based on the fused data set {M} calculated in step (3), use the dynamic extrapolation model to calculate the future time data set {Mt}

[0096] For the water vapor variable Q, the extrapolated calculation formula is as follows:

[0097]

[0098] in, represents the three-dimensional velocity field, Fq represents the water vapor content at the current grid point, and ▽Q represents the gradient of water vapor, so as to calculate the water vapor content at the current grid point at the next moment.

[0099] (5) Calculation of ice thickness on lines

[0100] Based on the water vapor content extrapolated and calculated in step (4), the ice thickness of the line is calculated using the ice calculation formula.

[0101] When the temperature is less than or equal to 0℃, ΔI=f(Q,S)

[0102] When the temperature is greater than 0°C, ΔI=0

[0103] The total ice thickness is

[0104] Where I is the total ice thickness, Q is the water vapor content at the grid point after extrapolation, S is the vertical conductor wind field after extrapolation, and f(Q,S) is the ice calculation model.

[0105] An embodiment of the present invention provides a radar extrapolated power grid icing short-term and imminent calculation system, which is configured to execute the radar extrapolated power grid icing short-term and imminent calculation method of the above embodiment.

[0106] Specifically, the computing system may include a memory and a processor, the memory may be configured to store program instructions and data, and the processor may call program instructions from the memory to execute the radar extrapolated power grid icing short-term calculation method of the above embodiment.

[0107] More specifically, the processor may be configured to:

[0108] Acquire radar measurement data measured at radar monitoring points;

[0109] Performing inversion calculation on the radar measurement data;

[0110] Use inversion data fusion to calculate the initial field;

[0111] Physical extrapolation calculation of water vapor inverted by radar;

[0112] Calculate the thickness of ice covering the transmission lines.

[0113] In an embodiment of the present invention, the acquiring radar measurement data measured at a radar monitoring point includes:

[0114] Determine the transmission line tower section to be detected to set the detection point M;

[0115] Deploy the millimeter wave radar at the detection point M;

[0116] Taking the detection point M as the center and the millimeter wave radar detection range L as the radius, the transmission line tower section is measured;

[0117] A grid with a resolution of r is established, and the radar reflectivity data matrix R at the grid points is detected and obtained.

[0118] In an embodiment of the present invention, performing inversion calculation on the radar measurement data includes:

[0119] The air water content matrix W is calculated based on the radar reflectivity data matrix R using formula (1):

[0120] W=10 aR+b Formula (1)

[0121] Wherein, W is the water content matrix, R is the radar reflectivity data matrix, and a and b are calculation coefficient matrices.

[0122] In an embodiment of the present invention, the using of inversion data fusion to calculate the initial field comprises:

[0123] The meteorological initial field dataset {m} of the calculation area specified in the radar measurement data measured at the radar monitoring point is obtained from the Global Forecast System GFS or the European Centre for Medium-Range Weather Forecasts ECMWF, and the calculated inverted air moisture content W is fused into the initial field dataset {m} to obtain a fused dataset {M}.

[0124] In the embodiment of the present invention, the weather at least includes water vapor.

[0125] The calculation formula for water vapor correction is defined as:

[0126] Q=q+λ(Wq) Formula (2)

[0127] Among them, Q is the corrected water vapor content matrix, q is the water vapor content matrix in the data set {m}, and λ is the weight coefficient matrix.

[0128] In an embodiment of the present invention, the physical extrapolation calculation of the water vapor inverted by radar includes:

[0129] Establish a water vapor dynamics extrapolation calculation model;

[0130] According to the fused data set {M}, the established water vapor dynamics extrapolation model is used to calculate the future time data set {Mt};

[0131] Among them, for the water vapor content Q, the water vapor dynamics extrapolation calculation model is defined as the following extrapolation calculation formula:

[0132] in, represents the three-dimensional velocity field, Fq represents the water vapor content at the current grid point, and ▽Q represents the gradient of water vapor.

[0133] In an embodiment of the present invention, calculating the ice thickness of the transmission line includes:

[0134] According to the extrapolated water vapor content, the ice thickness of the line is calculated using the following ice calculation formula:

[0135] When the temperature is less than or equal to 0°C, ΔI=f(Q,S)

[0136] When the temperature is greater than 0°C, ΔI=0

[0137] The total ice thickness is

[0138] Where I is the total ice thickness, Q is the water vapor content at the grid point after extrapolation, S is the vertical conductor wind field after extrapolation, and f(Q,S) is the ice calculation model.

[0139] In the embodiment of the present invention, the step of determining the transmission line tower section to be detected to set the detection point M includes:

[0140] The 10 towers of the 500 kV line section are determined as the detection section, and the fifth tower of the 10 towers is set as the detection point M.

[0141] In the embodiment of the present invention, the detection range L of the millimeter wave radar is 5 km.

[0142] The method provided by the embodiment of the present invention can have the following beneficial effects:

[0143] 1. The embodiment of the present invention cleverly combines radar reflectivity data with water vapor for calculation, thereby realizing local single-point regional remote sensing monitoring, that is, ensuring the local information of the extrapolated calculation includes surrounding information.

[0144] 2. The embodiments of the present invention have good versatility and can be used for ice extrapolation prediction calculation of transmission lines in various icing-prone areas.

[0145] 3. The technical solution provided by the embodiment of the present invention can realize timely warning of icing on transmission lines, thereby improving the pertinence and effectiveness of anti-icing work.

[0146] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0151] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0152] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0153] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0154] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A radar extrapolated short-term calculation method for power grid icing, It is characterized in that include: Acquire radar measurement data measured at radar monitoring points; Performing inversion calculation on the radar measurement data; Use inversion data fusion to calculate the initial field; Physical extrapolation calculation of water vapor inverted by radar; Calculate ice thickness on transmission lines; The radar measurement data includes the radar reflectivity data matrix R, and the inversion calculation of the radar measurement data includes: The air water content matrix W is calculated from the radar reflectivity data matrix R using the following formula: W＝10 aR+b Wherein, W is the water content matrix, R is the radar reflectivity data matrix, and a and b are calculation coefficient matrices; The method of calculating the initial field by using inversion data fusion includes: obtaining a meteorological initial field data set {m} of a calculation area specified in radar measurement data measured at a radar monitoring point; fusing the calculated inverted air moisture content W into the initial field data set {m} to obtain a fused data set {M}; The physical extrapolation calculation of the water vapor inverted by the radar includes: establishing a water vapor dynamic extrapolation calculation model; according to the fused data set {M}, using the established water vapor dynamic extrapolation model to calculate the future time data set {Mt}; wherein, for the water vapor content Q, the water vapor dynamic extrapolation calculation model is defined as the following extrapolation calculation formula: in, represents the three-dimensional velocity field, Fq represents the water vapor content at the current grid point, Represents the gradient of water vapor; The calculation of ice thickness of the transmission line comprises: According to the extrapolated water vapor content, the ice thickness of the line is calculated using the following ice calculation formula: When the temperature is less than or equal to 0°C, ΔI=f(Q,S) When the temperature is greater than 0°C, ΔI=0 The total ice thickness is Where I is the total ice thickness, Q is the water vapor content at the grid point after extrapolation, S is the vertical conductor wind field after extrapolation, and f(Q,S) is the ice calculation model.

2. The method according to claim 1, It is characterized in that The obtaining of radar measurement data measured at the radar monitoring point comprises: Determine the transmission line tower section to be detected to set the detection point M; Deploy the millimeter wave radar at the detection point M; Taking the detection point M as the center and the millimeter wave radar detection range L as the radius, the transmission line tower section is measured; A grid with a resolution of r is established, and the radar reflectivity data matrix R at the grid points is detected and obtained.

3. The method according to claim 1, It is characterized in that The weather at least includes water vapor, The calculation formula for water vapor correction is defined as: Q=q+λ(Wq) Among them, Q is the corrected water vapor content matrix, q is the water vapor content matrix in the data set {m}, and λ is the weight coefficient matrix.

4. The method according to claim 2, It is characterized in that The step of determining the transmission line tower section to be detected to set the detection point M comprises: The 10 towers of the 500 kV line section are determined as the detection section, and the fifth tower of the 10 towers is set as the detection point M.

5. The method according to claim 4, It is characterized in that The detection range L of the millimeter wave radar is 5 km.

6. A radar extrapolated power grid icing short-term calculation system, It is characterized in that include: a memory configured to store program instructions; A processor is configured to call the program instructions from the memory and execute the radar extrapolated power grid icing short-term calculation method according to any one of claims 1 to 5.

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