Power grid risk assessment method, device and equipment and storage medium

Abstract

The embodiment of the invention discloses a power grid risk assessment method and device, equipment and a storage medium. Comprising the following steps: dividing a target power grid region into a plurality of target power grid sub-regions, and obtaining meteorological data corresponding to the plurality of target power grid sub-regions; determining a meteorological disaster risk value corresponding to the target power grid sub-region based on the meteorological data; determining risk related information of power grid equipment in the target power grid sub-region; wherein the risk related information comprises importance information, anti-risk information and weather sensitive information; and determining a meteorological disaster risk assessment result of the target power grid sub-region based on the number of the power grid devices in the target power grid sub-region, the meteorological disaster risk value and the risk related information. According to the technical scheme, the accuracy of the meteorological disaster risk value and the accuracy of determining the risk-related information can be improved, so that the accuracy of meteorological disaster risk assessment is improved, and the stability of a power grid system is guaranteed.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of power grid technology, and in particular to a power grid risk assessment method, device, equipment and storage medium. Background Art

[0002] Grid equipment is generally deployed on the ground and is easily affected by meteorological disasters, which can lead to power outages and cause serious impacts on life, business, and public safety. Therefore, it is particularly important to study the impact of meteorological disasters on grid equipment.

[0003] The existing risk assessment method constructs power grid risk models corresponding to different meteorological disasters, and evaluates the impact of various meteorological disasters on the power grid separately. This method is not effective for assessing situations where multiple meteorological disasters are combined. Summary of the invention

[0004] The embodiments of the present invention provide a power grid risk assessment method, device, equipment and storage medium, which can assess the risk of a power grid being simultaneously affected by multiple meteorological disasters and improve the accuracy of risk assessment.

[0005] In a first aspect, an embodiment of the present invention provides a method for evaluating power grid risk, comprising:

[0006] Divide the target power grid area into a plurality of target power grid sub-areas, and obtain meteorological data corresponding to the plurality of target power grid sub-areas respectively; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity;

[0007] Determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a rainstorm risk value, a waterlogging risk value, a strong wind risk value, and an icing risk value;

[0008] Determine risk-related information of power grid equipment in the target power grid sub-area; wherein the risk-related information includes importance information, risk resistance information and meteorological sensitivity information;

[0009] Based on the number of the power grid devices in the target power grid sub-area, the meteorological disaster risk value and the risk-related information, a meteorological disaster risk assessment result of the target power grid sub-area is determined.

[0010] In a second aspect, an embodiment of the present invention further provides a power grid risk assessment device, the device comprising:

[0011] A region division module, used to divide the target power grid region into a plurality of target power grid sub-regions, and obtain meteorological data corresponding to the plurality of target power grid sub-regions; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity;

[0012] A meteorological disaster risk value determination module, configured to determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a rainstorm risk value, a waterlogging risk value, a strong wind risk value, and an icing risk value;

[0013] A risk related information determination module, used to determine risk related information of power grid equipment in the target power grid sub-area; wherein the risk related information includes importance information, risk resistance information and meteorological sensitivity information;

[0014] The risk assessment result determination module is used to determine the meteorological disaster risk assessment result of the target power grid sub-area based on the number of the power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information.

[0015] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power grid risk assessment method described in the embodiment of the present invention.

[0019] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power grid risk assessment method described in the embodiment of the present invention when executed.

[0020] The embodiment of the present invention discloses a power grid risk assessment method, device, equipment and storage medium, including: dividing a target power grid area into multiple target power grid sub-areas, and obtaining meteorological data corresponding to the multiple target power grid sub-areas respectively; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity; determining a meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a rainstorm risk value, a water accumulation risk value, a strong wind risk value and an icing risk value; determining risk-related information of power grid equipment in the target power grid sub-area; wherein the risk-related information includes importance information, risk resistance information and meteorological sensitivity information; based on the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information, determining the meteorological disaster risk assessment result of the target power grid sub-area. The above technical solution can evaluate the risk of the power grid being affected by multiple meteorological disasters at the same time. It specifically considers determining the meteorological disaster risk value corresponding to the target power grid sub-area based on meteorological data, which can improve the accuracy of the meteorological disaster risk value; at the same time, it also considers determining the risk-related information of the power grid equipment in the target power grid sub-area, which can improve the accuracy of the determination of risk-related information; finally, based on the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk assessment result of the target power grid sub-area is determined, which improves the accuracy of the meteorological disaster risk assessment. Compared with the prior art, the technical solution provided by this embodiment can improve the accuracy of the meteorological disaster risk value and the accuracy of the determination of risk-related information, thereby improving the accuracy of the meteorological disaster risk assessment, and further ensuring the stability of the power grid system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flow chart of a power grid risk assessment method in Embodiment 1 of the present invention;

[0022] Figure 2 is a flow chart of a power grid risk assessment method in Embodiment 2 of the present invention;

[0023] Figure 3 It is a structural schematic diagram of a power grid risk assessment device in Embodiment 3 of the present invention;

[0024] Figure 4 It is a structural schematic diagram of an electronic device in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0026] Embodiment 1

[0027] Figure 1 This is a flow chart of a power grid risk assessment method provided in the first embodiment of the present invention. This embodiment is applicable to the situation of assessing the meteorological disaster risk of the power grid. The method can be executed by a power grid risk assessment device, which can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server. Specifically, it includes the following steps:

[0028] S110: Divide the target power grid area into a plurality of target power grid sub-areas, and obtain meteorological data corresponding to the plurality of target power grid sub-areas respectively.

[0029] In this embodiment, the target power grid area can be understood as the power grid area where the meteorological disaster risk assessment is to be performed; the target power grid sub-area can be understood as the power grid sub-area obtained after dividing the target power grid area according to a preset spatial resolution. The meteorological data can be understood as the weather forecast data corresponding to the power grid sub-area, and specifically, the meteorological data can include at least one of precipitation, water accumulation depth, wind speed, temperature and humidity.

[0030] Furthermore, one implementation method of dividing the target power grid area into multiple target power grid sub-areas can be described as: obtaining a preset spatial resolution; dividing the target power grid area according to the preset spatial resolution to obtain multiple target power grid sub-areas.

[0031] Continuing with the above description, the preset spatial resolution can be understood as the size of the regional division; wherein, for the convenience of calculation, the preset spatial resolution is set on the basis of the spatial resolution of the gridded forecast data corresponding to the target power grid area, wherein the spatial resolution of the gridded forecast data is known. Specifically, the preset spatial resolution may be consistent with the spatial resolution of the gridded forecast data corresponding to the target power grid area, or may be greater than the spatial resolution of the gridded forecast data corresponding to the target power grid area. Exemplarily, the preset spatial resolution may be a°×b°, wherein a°×b° may be expressed as a° latitude multiplied by b° longitude; assuming that the spatial resolution of the gridded forecast data corresponding to the target power grid area is 0.1°×0.1°, the preset spatial resolution may be 0.1°×0.1°, 0.01°×0.01°, 0.025°×0.025°, 0.05°×0.05°, etc., wherein the smaller the value of the spatial resolution, the larger the corresponding resolution.

[0032] Exemplarily, assuming that the acquired preset spatial resolution is 0.025°×0.025°, the target power grid area is divided into multiple target power grid sub-areas according to the preset spatial resolution of 0.025°×0.025°; wherein the size of the target power grid sub-area is 0.025°×0.025°.

[0033] In this embodiment, for obtaining meteorological data corresponding to multiple target power grid sub-areas, one implementation method can be described as: obtaining meteorological data corresponding to the target power grid area; interpolating the meteorological data corresponding to the target power grid area to obtain meteorological data corresponding to each target power grid sub-area.

[0034] Furthermore, the method of obtaining the meteorological data corresponding to the target power grid area may be: obtaining the precipitation, water accumulation depth, wind speed, temperature and humidity corresponding to the target power grid area.

[0035] Furthermore, the meteorological data corresponding to the target power grid area is interpolated to obtain the meteorological data corresponding to each target power grid sub-area. Specifically, the precipitation, water accumulation depth, wind speed, temperature and humidity corresponding to the target power grid area are interpolated using a preset interpolation method to obtain the precipitation, water accumulation depth, wind speed, temperature and humidity corresponding to each target power grid sub-area.

[0036] Continuing with the above description, the preset interpolation method can be cubic spline interpolation and linear interpolation, or other interpolation methods. Using the preset interpolation method to interpolate the meteorological data corresponding to the target power grid area can be understood as: interpolating the meteorological data corresponding to the target power grid area to each target power grid sub-area through the preset interpolation method, thereby obtaining the meteorological data corresponding to each target power grid sub-area.

[0037] S120. Determine a meteorological disaster risk value corresponding to the target power grid sub-area based on meteorological data.

[0038] In this embodiment, the meteorological disaster risk value can be understood as the risk of the target power grid sub-area being affected by meteorological disasters, and the risk is represented by a numerical value. For example, the meteorological disaster risk value can be 1 or 0, wherein 1 indicates that the target power grid sub-area has a meteorological disaster risk; 0 indicates that the target power grid sub-area does not have a meteorological disaster risk. Specifically, the meteorological disaster risk may include a rainstorm risk, a waterlogging risk, a strong wind risk, and an ice risk. Among them, the meteorological disaster risk value may include at least one of a rainstorm risk value, a waterlogging risk value, a strong wind risk value, and an ice risk value.

[0039] Furthermore, one implementation method of determining the meteorological disaster risk value corresponding to the target power grid sub-area based on meteorological data can be described as: comparing the meteorological data corresponding to the target power grid sub-area with a set threshold; and determining the meteorological disaster risk value corresponding to the target power grid sub-area based on the comparison result.

[0040] Continuing with the above description, the meteorological data corresponding to the target power grid sub-area are precipitation, water accumulation depth, wind speed, temperature and humidity, where each meteorological data has a corresponding set threshold. Each meteorological data is compared with the corresponding set threshold, and the rainstorm risk value, water accumulation risk value, strong wind risk value and ice risk value corresponding to the target power grid sub-area are determined according to the comparison result.

[0041] S130. Determine risk-related information of power grid equipment in the target power grid sub-area.

[0042] In this embodiment, risk-related information can be understood as key information related to meteorological disaster risks. Among them, risk-related information can include importance information, risk resistance information and meteorological sensitivity information. Specifically, importance information is used to characterize the importance of power grid equipment in the target power grid sub-area; risk resistance information is used to characterize the risk resistance of power grid equipment in the target power grid sub-area; meteorological sensitivity information is used to characterize the sensitivity of power grid equipment in the target power grid sub-area to different meteorological disaster risks. Among them, importance information, risk resistance information and meteorological sensitivity information can be represented by numerical values.

[0043] Furthermore, one implementation method of determining risk-related information of power grid equipment in the target power grid sub-area can be described as: obtaining the number of each type of power grid equipment in the target power grid sub-area and the weights corresponding to each type of power grid equipment; for each type of power grid equipment, multiplying the number of power grid equipment by the weight to obtain a product result; accumulating multiple product results to obtain risk-related information.

[0044] S140. Determine a meteorological disaster risk assessment result for the target power grid sub-region based on the number of power grid equipment, meteorological disaster risk value, and risk-related information in the target power grid sub-region.

[0045] In this embodiment, the meteorological disaster risk assessment result can be a meteorological disaster risk assessment value, which uses a numerical value to represent the risk of the target power grid sub-area being affected by meteorological disasters; wherein, the larger the meteorological disaster risk assessment value, the greater the risk of the target power grid sub-area being affected by meteorological disasters.

[0046] Furthermore, based on the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and risk-related information, one implementation method of determining the meteorological disaster risk assessment result of the target power grid sub-area can be described as: the number of power grid equipment in the target power grid sub-area, the heavy rain risk value, the water accumulation risk value, the strong wind risk value, the icing risk value and risk-related information are calculated to obtain the meteorological disaster risk assessment result.

[0047] The technical solution of this embodiment divides the target power grid area into multiple target power grid sub-areas, and obtains meteorological data corresponding to the multiple target power grid sub-areas respectively; determines the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; determines the risk-related information of the power grid equipment in the target power grid sub-area; and determines the meteorological disaster risk assessment result of the target power grid sub-area based on the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information. The above technical solution determines the meteorological disaster risk value corresponding to the target power grid sub-area according to the meteorological data, which can improve the accuracy of the meteorological disaster risk value; at the same time, it also considers determining the risk-related information of the power grid equipment in the target power grid sub-area, which can improve the accuracy of the determination of the risk-related information; finally, based on the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information, the meteorological disaster risk assessment result of the target power grid sub-area is determined, which improves the accuracy of the meteorological disaster risk assessment. The technical solution provided by this embodiment can improve the accuracy of the meteorological disaster risk value and the accuracy of the determination of the risk-related information, thereby improving the accuracy of the meteorological disaster risk assessment, and then ensuring the stability of the power grid system.

[0048] Embodiment 2

[0049] Figure 2 This is a flow chart of a power grid risk assessment method provided in Embodiment 2 of the present invention. Based on the above embodiment, the method includes the following steps:

[0050] S210: Divide the target power grid area into a plurality of target power grid sub-areas, and obtain meteorological data corresponding to the plurality of target power grid sub-areas respectively.

[0051] S220. Determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data.

[0052] Among them, meteorological data may include precipitation, water accumulation depth, wind speed, temperature and humidity; meteorological disaster risk values ​​may include heavy rain risk value, water accumulation risk value, strong wind risk value and icing risk value.

[0053] In this embodiment, for determining the meteorological disaster risk value corresponding to the target power grid sub-area based on meteorological data, one implementation method can be described as the following steps:

[0054] a) determining a rainstorm risk value based on the precipitation and a first set threshold;

[0055] The first set threshold is a precipitation threshold; the rainstorm risk value includes a first rainstorm risk value or a second rainstorm risk value. Specifically, if there is a rainstorm risk in the target power grid sub-area, the rainstorm risk value is the first rainstorm risk value; if there is no rainstorm risk in the target power grid sub-area, the rainstorm risk value is the second rainstorm risk value. Exemplarily, the first rainstorm risk value can be represented by a value of 1, and the second rainstorm risk value can be represented by a value of 0.

[0056] In this embodiment, the method of determining the rainstorm risk value based on the precipitation and the first set threshold value can be: if the precipitation is greater than the first set threshold value, the rainstorm risk value is the first rainstorm risk value; if the precipitation is less than or equal to the first set threshold value, the rainstorm risk value is the second rainstorm risk value.

[0057] Furthermore, if the precipitation is greater than the first set threshold, it indicates that there is a risk of heavy rain in the target power grid sub-area; if the precipitation is less than or equal to the first set threshold, it indicates that there is no risk of heavy rain in the target power grid sub-area.

[0058] Exemplarily, assuming that the precipitation is P and the first set threshold is e1, if the precipitation P is greater than the first set threshold e1, the rainstorm risk value is 1; if the precipitation P is less than or equal to the first set threshold e1, the rainstorm risk value is 0.

[0059] Furthermore, the first set threshold value may be determined by: obtaining the hourly historical precipitation corresponding to the target power grid area; performing interpolation processing on the hourly historical precipitation corresponding to the target power grid area using a preset interpolation method to obtain the hourly historical precipitation corresponding to each target power grid sub-area; for each target power grid sub-area, calculating the 95% quantile precipitation of the hourly historical precipitation, and using the 95% quantile precipitation as the first set threshold value.

[0060] Continuing with the above description, the hourly historical precipitation can be understood as the hourly precipitation in the target power grid area in the past n years, exemplarily n=30, and the hourly historical precipitation includes multiple precipitations.

[0061] b) determining a waterlogging risk value based on the waterlogging depth and a second set threshold;

[0062] Among them, the second set threshold is a pre-set water depth threshold; the water accumulation risk value includes a first water accumulation risk value or a second water accumulation risk value. Specifically, if there is a water accumulation risk in the target power grid sub-area, the water accumulation risk value is the first water accumulation risk value; if there is no water accumulation risk in the target power grid sub-area, the water accumulation risk value is the second water accumulation risk value. Exemplarily, the first water accumulation risk value can be represented by a value of 1, and the second water accumulation risk value can be represented by a value of 0.

[0063] In this embodiment, the method of determining the waterlogging risk value based on the waterlogging depth and the second set threshold value can be: if the waterlogging depth is greater than the second set threshold value, the waterlogging risk value is the first waterlogging risk value; if the waterlogging depth is less than or equal to the second set threshold value, the waterlogging risk value is the second waterlogging risk value.

[0064] Furthermore, if the water accumulation depth is greater than the second set threshold, it indicates that there is a risk of water accumulation in the target power grid sub-area; if the water accumulation depth is less than or equal to the second set threshold, it indicates that there is no risk of water accumulation in the target power grid sub-area.

[0065] For example, assuming that the water depth is W and the second threshold value is e2, if the water depth W is greater than the second threshold value e2, the water risk value is 1; if the water depth W is less than or equal to the second threshold value e2, the water risk value is 0. e2 may be 20 cm.

[0066] c) determining a strong wind risk value based on the wind speed and a third set threshold;

[0067] Among them, the third set threshold is a wind speed threshold set in advance; the strong wind risk value includes a first strong wind risk value or a second strong wind risk value. Specifically, if there is a strong wind risk in the target power grid sub-area, the strong wind risk value is the first strong wind risk value; if there is no strong wind risk in the target power grid sub-area, the strong wind risk value is the second strong wind risk value. Exemplarily, the first strong wind risk value can be represented by a value of 1, and the second strong wind risk value can be represented by a value of 0.

[0068] In this embodiment, the method for determining the strong wind risk value based on the wind speed and the third set threshold value can be: if the wind speed is greater than the third set threshold value, the strong wind risk value is the first strong wind risk value; if the wind speed is less than or equal to the third set threshold value, the strong wind risk value is the second strong wind risk value.

[0069] Furthermore, if the wind speed is greater than the third set threshold, it indicates that there is a strong wind risk in the target power grid sub-area; if the wind speed is less than or equal to the third set threshold, it indicates that there is no strong wind risk in the target power grid sub-area.

[0070] For example, assuming that the wind speed is V and the third threshold value is e3, if the wind speed V is greater than the third threshold value e3, the strong wind risk value is 1; if the wind speed V is less than or equal to the third threshold value e3, the strong wind risk value is 0. Among them, e3 can be 12m / s.

[0071] d) Determine the icing risk value based on precipitation, temperature and humidity;

[0072] Wherein, temperature is air temperature, humidity is relative humidity; and the icing risk value includes a first icing risk value or a second icing risk value. Specifically, if there is an icing risk in the target power grid sub-area, the icing risk value is the first icing risk value; if there is no icing risk in the target power grid sub-area, the icing risk value is the second icing risk value. Exemplarily, the first icing risk value can be represented by a value of 1, and the second icing risk value can be represented by a value of 0.

[0073] In this embodiment, the implementation method of determining the icing risk value based on precipitation, temperature and humidity can be described as: if the precipitation is greater than the fourth set threshold, the temperature is within the set range and the humidity is greater than the fifth set threshold, then the icing risk value is the first icing risk value; if the precipitation is less than or equal to the fourth set threshold, the temperature is not within the set range or the humidity is less than or equal to the fifth set threshold, then the icing risk value is the second icing risk value.

[0074] Continuing with the above description, the fourth set threshold, the fifth set threshold and the set range are thresholds and ranges set in advance. Among them, only when the precipitation is greater than the fourth set threshold, the temperature is within the set range and the humidity is greater than the fifth set threshold, the ice risk value is the first ice risk value; as long as at least one of the three conditions of precipitation less than or equal to the fourth set threshold, temperature not within the set range or humidity less than or equal to the fifth set threshold is met, the ice risk value is the second ice risk value.

[0075] For example, assuming that the fourth set threshold is e4, the temperature is T, the humidity is S, the setting range is T1-T2, and the fifth set threshold is e5. If the precipitation P is greater than the fourth set threshold e4, the temperature T is in the setting range T1-T2, and the humidity S is greater than the fifth set threshold e5, the ice risk value is 1; if the precipitation P is less than or equal to the fourth set threshold e4, the temperature T is not in the setting range T1-T2, or the humidity S is less than or equal to the fifth set threshold e5, the ice risk value is 0. Among them, e4 can be 0 mm / h, T1-T2 can be -2-3°C, and e5 can be 70%.

[0076] S230, obtaining the quantities of different power grid devices in the target power grid sub-area and the importance weights and risk resistance weights of various types of power grid devices.

[0077] In this embodiment, the importance weight is used to characterize the importance of various types of power grid equipment. The larger the importance weight, the more important the type of power grid equipment is; the risk resistance weight is used to characterize the risk resistance of various types of power grid equipment. The larger the risk resistance weight, the more resistant the type of power grid equipment is to risks. Among them, the importance weight and risk resistance weight are expressed by numerical values. Optionally, the power grid equipment can be a low-voltage transformer, a high-voltage transformer, a tension tower, an ordinary tower, etc.

[0078] For example, taking a target power grid sub-area as an example, it is assumed that the target power grid sub-area contains three types of power grid equipment, namely r1 power grid equipment D1, r2 power grid equipment D2 and r3 power grid equipment D3. Among them, the importance weight and risk resistance weight of power grid equipment D1 are z1 and k1 respectively; the importance weight and risk resistance weight of power grid equipment D2 are z2 and k2 respectively; the importance weight and risk resistance weight of power grid equipment D3 are z3 and k3 respectively.

[0079] S240: Based on the importance weight, the quantities corresponding to each power grid device are integrated to obtain importance information.

[0080] In this embodiment, fusion can be understood as weighted summation. For example, based on the above example, the formula Z=z1*r1+z2*r2+z3*r3 is used to fuse the quantities corresponding to each power grid device to obtain the importance information Z.

[0081] S250. Based on the risk resistance weight, the quantities corresponding to each power grid device are integrated to obtain risk resistance information.

[0082] Exemplarily, based on the above example, the formula K=k1*r1+k2*r2+k3*r3 is used to merge the quantities corresponding to each power grid equipment to obtain the risk resistance information K.

[0083] S260. For each meteorological disaster risk, obtain the meteorological sensitivity weights of various types of power grid equipment to the meteorological disaster risk.

[0084] In this embodiment, the meteorological sensitivity weight is used to characterize the sensitivity of various types of power grid equipment to meteorological disaster risks. The larger the meteorological sensitivity weight, the more sensitive the type of power grid equipment is to meteorological disaster risks. The meteorological disaster risks may be heavy rain risk, water accumulation risk, strong wind risk, and ice risk.

[0085] Exemplarily, the meteorological sensitivity weights of power grid equipment D1 to heavy rain risk, waterlogging risk, strong wind risk and icing risk are y1, j1, q1 and b1 respectively; the meteorological sensitivity weights of power grid equipment D2 to heavy rain risk, waterlogging risk, strong wind risk and icing risk are y2, j2, q2 and b2 respectively; the meteorological sensitivity weights of power grid equipment D3 to heavy rain risk, waterlogging risk, strong wind risk and icing risk are y3, j3, q3 and b3 respectively.

[0086] S270. The quantities of various types of power grid equipment are integrated based on meteorological sensitivity weights to obtain meteorological sensitive sub-information of meteorological disaster risks.

[0087] In this embodiment, the number of various types of power grid equipment is integrated based on the meteorological sensitivity weights to obtain meteorological sensitive sub-information of meteorological disaster risks. For each meteorological disaster risk, the number of various types of power grid equipment is weighted summed based on the meteorological sensitivity weights of the various types of power grid equipment to the meteorological disaster risk to obtain the meteorological sensitive sub-information of the meteorological disaster risk.

[0088] Specifically, based on the meteorological sensitivity weights of various types of power grid equipment to the rainstorm risk, the number of various types of power grid equipment is weighted and summed to obtain the meteorological sensitive sub-information of the rainstorm risk. For example, the formula Y=y1*r1+y2*r2+y3*r3 is used to obtain the meteorological sensitive sub-information Y of the rainstorm risk.

[0089] Specifically, based on the meteorological sensitivity weights of various types of power grid equipment to the risk of waterlogging, the number of various types of power grid equipment is weighted and summed to obtain the meteorological sensitive sub-information of waterlogging risk. For example, the formula J=j1*r1+j2*r2+j3*r3 is used to obtain the meteorological sensitive sub-information J of waterlogging risk.

[0090] Specifically, based on the meteorological sensitivity weights of various types of power grid equipment to strong wind risk, the number of various types of power grid equipment is weighted and summed to obtain the meteorological sensitive sub-information of strong wind risk. For example, the formula Q=q1*r1+q2*r2+q3*r3 is used to obtain the meteorological sensitive sub-information Q of strong wind risk.

[0091] Specifically, based on the meteorological sensitivity weights of various types of power grid equipment to icing risk, the number of various types of power grid equipment is weighted and summed to obtain meteorological sensitive sub-information of icing risk. For example, the meteorological sensitive sub-information B of icing risk can be obtained by using the formula B=b1*r1+b2*r2+b3*r3.

[0092] S280. Fusing meteorological disaster risk values ​​based on meteorological sensitive sub-information to obtain meteorological sensitive information.

[0093] In this embodiment, the meteorological disaster risk value is integrated based on the meteorological sensitive sub-information, and one implementation method of obtaining the meteorological sensitive information can be described as: based on the meteorological sensitive sub-information of heavy rain risk, water accumulation risk, strong wind risk and icing risk, the heavy rain risk value, water accumulation risk value, strong wind risk value and icing risk value are weightedly summed to obtain the meteorological sensitive information.

[0094] Continuing with the above description, the meteorological sensitive sub-information of heavy rain risk is the weight of the heavy rain risk value, the meteorological sensitive sub-information of waterlogging risk is the weight of the waterlogging risk value, the meteorological sensitive sub-information of strong wind risk is the weight of the strong wind risk value, and the meteorological sensitive sub-information of icing risk is the weight of the icing risk value.

[0095] For example, assuming that the heavy rain risk value, water accumulation risk value, strong wind risk value and icing risk value are X1, X2, X3 and X4 respectively, the formula M=Y*X1+J*X2+Q*X3+B*X4 can be used to perform weighted summation of the heavy rain risk value, water accumulation risk value, strong wind risk value and icing risk value to obtain the meteorological sensitive information M.

[0096] S290. Calculate the number of power grid equipment, meteorological disaster risk value and risk-related information in the target power grid sub-area through a preset calculation logic to obtain a meteorological disaster risk assessment result for the target power grid sub-area.

[0097] In this embodiment, the number of power grid equipment, meteorological disaster risk value and risk-related information in the target power grid sub-area are calculated through a preset operation logic to obtain a meteorological disaster risk assessment result of the target power grid sub-area. One implementation method can be described as: the number of power grid equipment, heavy rain risk value, water accumulation risk value, strong wind risk value and icing risk value as well as importance information, risk resistance information and meteorological sensitivity information in the target power grid sub-area are calculated through a preset operation logic to obtain a meteorological disaster risk assessment value of the target power grid sub-area.

[0098] Exemplarily, the number of power grid equipment in the target power grid sub-area (r1+r2+r3), the heavy rain risk value X1, the water accumulation risk value X2, the strong wind risk value X3 and the icing risk value X4, as well as the importance information Z, the anti-risk information K and the meteorological sensitivity information M are calculated through the preset operation logic in the following formula to obtain the meteorological disaster risk assessment value H of the target power grid sub-area.

[0099] H=[(r1+r2+r3)+Z+K]*(X1+X2+X3+X4)+M

[0100] Furthermore, the larger the meteorological disaster risk assessment value H is, the greater the risk of the target power grid sub-area being affected by meteorological disasters is.

[0101] Continuing with the above description, the above example only takes a certain target power grid sub-area as an example. In the solution of this embodiment, it is necessary to obtain the meteorological disaster risk assessment results of each target power grid sub-area in the target power grid area.

[0102] The technical solution of this embodiment divides the target power grid area into multiple target power grid sub-areas, and obtains meteorological data corresponding to the multiple target power grid sub-areas respectively; determines the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; obtains the corresponding quantities of different power grid equipment in the target power grid sub-area and the importance weights and risk resistance weights of each type of power grid equipment; fuses the corresponding quantities of each power grid equipment based on the importance weight to obtain importance information; fuses the corresponding quantities of each power grid equipment based on the risk resistance weight to obtain risk resistance information; for each meteorological disaster risk, obtains the meteorological sensitivity weights of each type of power grid equipment to the meteorological disaster risk; fuses the quantities of each type of power grid equipment based on the meteorological sensitivity weight to obtain meteorological sensitive sub-information of the meteorological disaster risk; fuses the meteorological disaster risk value based on the meteorological sensitive sub-information to obtain meteorological sensitive information; calculates the quantity of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and risk-related information through a preset calculation logic to obtain a meteorological disaster risk assessment result for the target power grid sub-area. The above technical solution determines the meteorological disaster risk value corresponding to the target power grid sub-area based on meteorological data, which can improve the accuracy of the meteorological disaster risk value; at the same time, the corresponding quantities of each power grid device are integrated according to the importance weight to obtain the importance information, which can improve the accuracy of the importance information; and, according to the anti-risk weight, the corresponding quantities of each power grid device are integrated to obtain the anti-risk information, which can improve the accuracy of the anti-risk information; then, based on the meteorological sensitivity weight, the number of various types of power grid equipment is integrated to obtain the meteorological sensitive sub-information of the meteorological disaster risk, and the meteorological disaster risk value is integrated according to the meteorological sensitive sub-information to obtain the meteorological sensitive information, which can improve the accuracy of the meteorological sensitive information; finally, the number of power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information are calculated through the preset operation logic, and the meteorological disaster risk assessment result of the target power grid sub-area can be accurately obtained. The technical solution provided in this embodiment can improve the accuracy of the meteorological disaster risk value, as well as the accuracy of the importance information, the anti-risk information and the meteorological sensitive information, so that the meteorological disaster risk assessment result of the target power grid sub-area can be accurately obtained, the accuracy of the meteorological disaster risk assessment is improved, and the stability of the power grid system is guaranteed.

[0103] Embodiment 3

[0104] Figure 3 A schematic diagram of the structure of a power grid risk assessment device provided in Embodiment 3 of the present invention is shown in FIG. Figure 3 As shown, the device comprises:

[0105] The area division module 310 is used to divide the target power grid area into multiple target power grid sub-areas, and obtain meteorological data corresponding to the multiple target power grid sub-areas respectively; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity;

[0106] A meteorological disaster risk value determination module 320 is used to determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a heavy rain risk value, a waterlogging risk value, a strong wind risk value and an icing risk value;

[0107] A risk-related information determination module 330 is used to determine risk-related information of power grid equipment in the target power grid sub-area; wherein the risk-related information includes importance information, risk resistance information and meteorological sensitivity information;

[0108] The risk assessment result determination module 340 is used to determine the meteorological disaster risk assessment result of the target power grid sub-area based on the number of the power grid equipment, the meteorological disaster risk value and the risk-related information in the target power grid sub-area.

[0109] Optionally, the meteorological disaster risk value determination module 320 may specifically include:

[0110] A rainstorm risk value determining unit, configured to determine a rainstorm risk value based on the precipitation and a first set threshold;

[0111] A waterlogging risk value determining unit, configured to determine a waterlogging risk value based on the waterlogging depth and a second set threshold;

[0112] a strong wind risk value determining unit, configured to determine a strong wind risk value based on the wind speed and a third set threshold;

[0113] An icing risk value determining unit is used to determine an icing risk value based on the precipitation, the temperature and the humidity.

[0114] Optionally, the rainstorm risk value includes a first rainstorm risk value or a second rainstorm risk value; the waterlogging risk value includes a first waterlogging risk value or a second waterlogging risk value; the strong wind risk value includes a first strong wind risk value or a second strong wind risk value; the icing risk value includes a first icing risk value or a second icing risk value.

[0115] Optionally, the icing risk value determining unit may be specifically used to:

[0116] If the precipitation is greater than a fourth set threshold, the temperature is within a set range, and the humidity is greater than a fifth set threshold, the icing risk value is a first icing risk value;

[0117] If the precipitation is less than or equal to a fourth set threshold, the temperature is not within a set range, or the humidity is less than or equal to a fifth set threshold, the icing risk value is a second icing risk value.

[0118] Optionally, the risk-related information determination module 330 may be specifically used to:

[0119] Obtain the number of different power grid devices in the target power grid sub-area and the importance weight and risk resistance weight of each type of power grid equipment;

[0120] Based on the importance weight, the quantities corresponding to each power grid device are integrated to obtain importance information;

[0121] Based on the anti-risk weight, the quantities corresponding to each power grid device are integrated to obtain anti-risk information.

[0122] Optionally, the risk-related information determination module 330 may be specifically used to:

[0123] For each meteorological disaster risk, obtain the meteorological sensitivity weights of various types of power grid equipment to meteorological disaster risks;

[0124] Based on the meteorological sensitivity weights, the quantities of various types of power grid equipment are integrated to obtain meteorological sensitivity sub-information of the meteorological disaster risk;

[0125] The meteorological disaster risk value is fused based on the meteorological sensitive sub-information to obtain meteorological sensitive information.

[0126] Optionally, the risk assessment result determination module 340 may be specifically used to:

[0127] The number of the power grid devices in the target power grid sub-area, the meteorological disaster risk value and the risk-related information are calculated through a preset calculation logic to obtain a meteorological disaster risk assessment result for the target power grid sub-area.

[0128] Optionally, the area division module 310 may be specifically used for:

[0129] Obtain meteorological data corresponding to the target power grid area;

[0130] The meteorological data corresponding to the target power grid area is interpolated to obtain meteorological data corresponding to each target power grid sub-area.

[0131] The above device can execute the methods provided by all the above embodiments of the present invention, and has the corresponding functional modules and beneficial effects of executing the above methods. For technical details not described in detail in this embodiment, please refer to the methods provided by all the above embodiments of the present invention.

[0132] Embodiment 4

[0133] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0134] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0135] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0136] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a power grid risk assessment method.

[0137] In some embodiments, the power grid risk assessment method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the power grid risk assessment method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the power grid risk assessment method in any other appropriate manner (e.g., by means of firmware).

[0138] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0139] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0140] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0141] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0142] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0143] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0144] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0145] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A power grid risk assessment method, characterized in that: include: Divide the target power grid area into a plurality of target power grid sub-areas, and obtain meteorological data corresponding to the plurality of target power grid sub-areas respectively; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity; Determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a rainstorm risk value, a waterlogging risk value, a strong wind risk value, and an icing risk value; Determine risk-related information of power grid equipment in the target power grid sub-area; wherein the risk-related information includes importance information, risk resistance information and meteorological sensitivity information; Based on the number of the power grid devices in the target power grid sub-area, the meteorological disaster risk value and the risk-related information, a meteorological disaster risk assessment result of the target power grid sub-area is determined.

2. The method according to claim 1, characterized in that Determining the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data includes: Determining a rainstorm risk value based on the precipitation and a first set threshold; Determining a waterlogging risk value based on the waterlogging depth and a second set threshold; determining a strong wind risk value based on the wind speed and a third set threshold; determining an icing risk value based on the precipitation, the temperature, and the humidity; Among them, the heavy rain risk value includes the first heavy rain risk value or the second heavy rain risk value; the waterlogging risk value includes the first waterlogging risk value or the second waterlogging risk value; the strong wind risk value includes the first strong wind risk value or the second strong wind risk value; the icing risk value includes the first icing risk value or the second icing risk value.

3. The method according to claim 2, characterized in that Determining an icing risk value based on the precipitation, the temperature, and the humidity includes: If the precipitation is greater than a fourth set threshold, the temperature is within a set range, and the humidity is greater than a fifth set threshold, the icing risk value is a first icing risk value; If the precipitation is less than or equal to a fourth set threshold, the temperature is not within a set range, or the humidity is less than or equal to a fifth set threshold, the icing risk value is a second icing risk value.

4. The method according to claim 1, characterized in that: Determining risk-related information of power grid equipment in the target power grid sub-area, including: Obtain the number of different power grid devices in the target power grid sub-area and the importance weight and risk resistance weight of each type of power grid equipment; Based on the importance weight, the quantities corresponding to each power grid device are integrated to obtain importance information; Based on the anti-risk weight, the quantities corresponding to each power grid device are integrated to obtain anti-risk information.

5. The method according to claim 1, characterized in that Determining risk-related information of power grid equipment in the target power grid sub-area, including: For each meteorological disaster risk, obtain the meteorological sensitivity weights of various types of power grid equipment to meteorological disaster risks; Based on the meteorological sensitivity weights, the quantities of various types of power grid equipment are integrated to obtain meteorological sensitivity sub-information of the meteorological disaster risk; The meteorological disaster risk value is fused based on the meteorological sensitive sub-information to obtain meteorological sensitive information.

6. The method according to claim 1, characterized in that Determining a meteorological disaster risk assessment result of the target power grid sub-area based on the number of the power grid devices in the target power grid sub-area, the meteorological disaster risk value, and the risk-related information includes: The number of the power grid devices in the target power grid sub-area, the meteorological disaster risk value and the risk-related information are calculated through a preset calculation logic to obtain a meteorological disaster risk assessment result for the target power grid sub-area.

7. The method according to claim 1, characterized in that Acquiring meteorological data corresponding to a plurality of target power grid sub-areas, including: Obtain meteorological data corresponding to the target power grid area; The meteorological data corresponding to the target power grid area is interpolated to obtain meteorological data corresponding to each target power grid sub-area.

8. A power grid risk assessment device, characterized in that: include: A region division module, used to divide the target power grid region into a plurality of target power grid sub-regions, and obtain meteorological data corresponding to the plurality of target power grid sub-regions; wherein the meteorological data includes at least one of precipitation, water accumulation depth, wind speed, temperature and humidity; A meteorological disaster risk value determination module, configured to determine the meteorological disaster risk value corresponding to the target power grid sub-area based on the meteorological data; wherein the meteorological disaster risk value includes at least one of a rainstorm risk value, a waterlogging risk value, a strong wind risk value, and an icing risk value; A risk related information determination module, used to determine risk related information of power grid equipment in the target power grid sub-area; wherein the risk related information includes importance information, risk resistance information and meteorological sensitivity information; The risk assessment result determination module is used to determine the meteorological disaster risk assessment result of the target power grid sub-area based on the number of the power grid equipment in the target power grid sub-area, the meteorological disaster risk value and the risk-related information.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the power grid risk assessment method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power grid risk assessment method according to any one of claims 1 to 7 when executed.

Images