A method and device for fault location in smart grids

Abstract

This invention discloses a method and apparatus for fault location in a smart grid. The method includes: acquiring user repair request information; processing the user repair request information to obtain a regional fault value and a fault threshold; determining whether the regional fault value is greater than or equal to the fault threshold to obtain a first determination result; when the first determination result is yes, acquiring regional image information; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs; classifying and identifying the regional image information to obtain risk location information; the risk location information includes information of several risk points; the risk location information is used to indicate the location of faults in the smart grid. Therefore, this invention is beneficial for achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of fault location technology, and in particular to a method and apparatus for fault location in smart grids. Background Technology

[0002] The key to the intelligence of smart grids lies in the power supply phase. Many researchers in this field have been diligently studying how power is supplied, resulting in increasingly mature research on this phase. However, research on fault monitoring processes is still in its infancy. Existing fault monitoring processes are attached to existing circuit systems, adding current or voltage detection devices and then locating faults based on the acquired voltage or current data. However, due to cost constraints, it is impossible to deploy current or voltage detection devices on every branch line of the grid, and these devices are also prone to damage, leading to inaccurate fault location. Therefore, providing a smart grid fault location method and device to achieve accurate fault location, improve fault efficiency, and reduce grid maintenance costs is of paramount importance. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and apparatus for locating faults in a smart grid. This method and apparatus can obtain regional fault values ​​and fault thresholds by processing user repair request information, and then obtain risk location information for indicating fault location in the smart grid by comparing and judging the regional fault values ​​and fault thresholds and by comprehensively processing regional image information. This is beneficial for achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0004] To address the aforementioned technical problems, a first aspect of the present invention discloses a method for fault location in a smart grid, the method comprising:

[0005] Obtain user repair request information; the user repair request information includes several user repair requests;

[0006] The user's repair request information is processed to obtain the regional fault value and fault threshold;

[0007] Determine whether the fault value of the area is greater than or equal to the fault threshold to obtain a first determination result;

[0008] When the first judgment result is yes, regional image information is obtained; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs;

[0009] The image information of the region is classified and identified to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid.

[0010] As an optional implementation, in the first aspect of the present invention, processing the user repair request information to obtain a regional fault value and a fault threshold includes:

[0011] The user's repair request information is processed using a preset fault value model to obtain the regional fault value;

[0012] The user's repair request information is identified and processed to obtain power supply area information; the power supply area information includes the smart grid power supply area.

[0013] The power supply area information is processed to obtain the fault threshold.

[0014] As an optional implementation, in the first aspect of the present invention, the step of processing the user repair request information using a preset fault value model to obtain a regional fault value includes:

[0015] The user's repair request information is identified and processed to obtain user credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value;

[0016] The credit information of the household is corrected to obtain valid value information; the valid value information includes several valid values.

[0017] The effective value information is summed to obtain the regional fault value.

[0018] As an optional implementation, in the first aspect of the present invention, processing the power supply area information to obtain a fault threshold includes:

[0019] Based on the power supply area information, power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information.

[0020] The power demand information is processed to obtain the area resistance value;

[0021] The risk probability is obtained by matching the resistance values ​​of the region using a preset risk probability table.

[0022] The risk probabilities are matched using a preset regional threshold table to obtain the fault threshold.

[0023] As an optional implementation, in the first aspect of the present invention, the step of classifying and identifying the regional image information to obtain risk location information includes:

[0024] The image information of the region is classified to obtain a set of images to be used; the set of images to be used includes several images to be used; the images to be used include several high-risk point images; the images to be used are related to the label information of the high-risk point images.

[0025] The set of images to be used is processed by recognition and calculation to obtain risk location information.

[0026] As an optional implementation, in the first aspect of the present invention, the step of performing identification calculation processing on the set of image information to be used to obtain risk location information includes:

[0027] The set of image information to be used is transformed to obtain a set of feature array information; the set of feature array information includes several feature arrays; the feature arrays are related to the color value information of the high-risk point image information;

[0028] The risk location information is obtained by performing calculations on the feature array information set.

[0029] As an optional implementation, in the first aspect of the present invention, the step of calculating and processing the feature array information set to obtain risk location information includes:

[0030] The feature array information set is processed by calculating the average value to obtain the standard deviation information set; the standard deviation information set includes several standard deviation information.

[0031] The risk location information is obtained by comparing the standard deviation information set with a preset standard deviation threshold.

[0032] A second aspect of this invention discloses a smart grid fault location device, the device comprising:

[0033] The acquisition module is used to acquire user repair request information; the user repair request information includes several user repair requests.

[0034] The first processing module is used to process the user's repair request information to obtain the regional fault value and fault threshold.

[0035] The judgment module is used to determine whether the fault value of the area is greater than or equal to the fault threshold, and to obtain a first judgment result;

[0036] The acquisition module is further configured to acquire regional image information when the first judgment result is yes; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs;

[0037] The second processing module is used to classify and identify the regional image information to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid.

[0038] As an optional implementation, in a second aspect of the present invention, the first processing module includes a first processing submodule, a second processing submodule, and a third processing submodule, wherein:

[0039] The first processing submodule is used to process the user's repair request information using a preset fault value model to obtain the regional fault value;

[0040] The second processing submodule is used to identify and process the user's repair request information to obtain power supply area information; the power supply area information includes the smart grid power supply area;

[0041] The third processing submodule is used to process the power supply area information to obtain the fault threshold.

[0042] As an optional implementation, in a second aspect of the present invention, the first processing submodule processes the user repair request information using a preset fault value model to obtain the regional fault value in the following specific way:

[0043] The user's repair request information is identified and processed to obtain user credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value;

[0044] The credit information of the household is corrected to obtain valid value information; the valid value information includes several valid values.

[0045] The effective value information is summed to obtain the regional fault value.

[0046] As an optional implementation, in the second aspect of the present invention, the third processing submodule processes the power supply area information to obtain the fault threshold in the following specific manner:

[0047] Based on the power supply area information, power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information.

[0048] The power demand information is processed to obtain the area resistance value;

[0049] The risk probability is obtained by matching the resistance values ​​of the region using a preset risk probability table.

[0050] The risk probabilities are matched using a preset regional threshold table to obtain the fault threshold.

[0051] As an optional implementation, in a second aspect of the present invention, the second processing module performs classification and recognition processing on the regional image information to obtain risk location information in the following specific manner:

[0052] The image information of the region is classified to obtain a set of images to be used; the set of images to be used includes several images to be used; the images to be used include several high-risk point images; the images to be used are related to the label information of the high-risk point images.

[0053] The set of images to be used is processed by recognition and calculation to obtain risk location information.

[0054] As an optional implementation, in a second aspect of the present invention, the second processing module performs identification and calculation processing on the set of image information to be used to obtain risk location information in the following specific manner:

[0055] The set of image information to be used is transformed to obtain a set of feature array information; the set of feature array information includes several feature arrays; the feature arrays are related to the color value information of the high-risk point image information;

[0056] The risk location information is obtained by performing calculations on the feature array information set.

[0057] As an optional implementation, in a second aspect of the present invention, the second processing module performs calculations on the feature array information set to obtain risk location information in the following specific manner:

[0058] The feature array information set is processed by calculating the average value to obtain the standard deviation information set; the standard deviation information set includes several standard deviation information.

[0059] The risk location information is obtained by comparing the standard deviation information set with a preset standard deviation threshold.

[0060] A third aspect of the present invention discloses another smart grid fault location device, the device comprising:

[0061] Memory containing executable program code;

[0062] A processor coupled to the memory;

[0063] The processor calls the executable program code stored in the memory to execute some or all of the steps in the smart grid fault location method disclosed in the first aspect of the present invention.

[0064] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in the smart grid fault location method disclosed in the first aspect of the present invention.

[0065] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0066] In this embodiment of the invention, user repair request information is acquired; the user repair request information includes several user repair requests; the user repair request information is processed to obtain a regional fault value and a fault threshold; it is determined whether the regional fault value is greater than or equal to the fault threshold to obtain a first judgment result; when the first judgment result is yes, regional image information is acquired; the regional image information includes several high-risk point image information; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs; the regional image information is classified and identified to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid. It can be seen that this invention can obtain regional fault values ​​and fault thresholds by processing user repair request information, and then obtain risk location information for indicating the location of faults in the smart grid by comparing and judging the regional fault values ​​and fault thresholds and comprehensively processing the regional image information. This is beneficial for achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs. Attached Figure Description

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a flowchart illustrating a smart grid fault location method disclosed in an embodiment of the present invention;

[0069] Figure 2 This is a flowchart illustrating another smart grid fault location method disclosed in an embodiment of the present invention;

[0070] Figure 3 This is a schematic diagram of the structure of a smart grid fault location device disclosed in an embodiment of the present invention;

[0071] Figure 4 This is a schematic diagram of another smart grid fault location device disclosed in an embodiment of the present invention;

[0072] Figure 5 A schematic diagram of the structure of another smart grid fault location device disclosed in this embodiment of the invention. Detailed Implementation

[0073] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0074] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0075] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0076] This invention discloses a method and apparatus for fault location in smart grids. It can obtain regional fault values ​​and fault thresholds by processing user repair request information, and then obtain risk location information for indicating fault location in the smart grid by comparing and judging the regional fault values ​​and fault thresholds and comprehensively processing regional image information. This facilitates accurate fault location in smart grids, improves fault efficiency, and reduces grid maintenance costs. Detailed descriptions follow.

[0077] Example 1

[0078] Please see Figure 1 , Figure 1 This is a flowchart illustrating a smart grid fault location method disclosed in an embodiment of the present invention. Figure 1 The described smart grid fault location method is applied to fault handling systems, such as local servers or cloud servers used for smart grid fault location management, etc., and the embodiments of the present invention are not limited thereto. Figure 1 As shown, the smart grid fault location method may include the following operations:

[0079] 101. Obtain user repair request information.

[0080] In this embodiment of the invention, the aforementioned user repair request information includes several user repair requests.

[0081] 102. Process user repair request information to obtain regional fault values ​​and fault thresholds.

[0082] 103. Determine whether the fault value of the area is greater than or equal to the fault threshold to obtain the first judgment result.

[0083] 104. When the first judgment result is yes, obtain the region image information.

[0084] In this embodiment of the invention, the aforementioned regional image information includes image information of several high-risk points.

[0085] In this embodiment of the invention, the smart grid power supply area to which the above-mentioned regional image information belongs is consistent with the smart grid power supply area to which the user's repair request information belongs.

[0086] 105. Classify and identify the regional image information to obtain risk location information.

[0087] In this embodiment of the invention, the aforementioned risk location information includes several risk point information.

[0088] In this embodiment of the invention, the aforementioned risk location information is used to indicate the location of faults in the smart grid.

[0089] Optionally, the image information of the aforementioned area is obtained through the acquisition terminal.

[0090] Optionally, the settings of the above-mentioned data acquisition terminal are related to the historical fault information of the smart grid.

[0091] Optionally, for locations where more faults occur in the above historical fault information, the data collection terminals are set up relatively densely, and the data collection intervals are shorter.

[0092] As can be seen, the smart grid fault location method described in the embodiments of the present invention can obtain regional fault values ​​and fault thresholds by processing user repair request information, and then obtain risk location information for indicating fault location in the smart grid by comparing and judging the regional fault values ​​and fault thresholds and comprehensively processing regional image information. This is beneficial to achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0093] In an optional embodiment, step 102 above processes the user repair request information to obtain the regional fault value and fault threshold, including:

[0094] The user's repair request information is processed using a preset fault value model to obtain the regional fault value;

[0095] The user's repair request information is identified and processed to obtain power supply area information; the power supply area information includes the smart grid power supply area.

[0096] The power supply area information is processed to obtain the fault threshold.

[0097] Optionally, the above power supply area information also includes power supply area coding information.

[0098] Optionally, the aforementioned smart grid power supply area includes power supply units based on households, and / or power supply units based on buildings, and / or power supply units based on communities, and / or power supply units based on streets or towns, and / or power supply units based on counties or cities, and power supply units based on provinces. This embodiment of the invention does not limit the scope of the power supply area.

[0099] Optionally, the aforementioned smart grid power supply areas are pre-set in the database.

[0100] In this optional embodiment, as an optional implementation method, the specific way to divide and determine any of the above-mentioned smart grid power supply areas is as follows:

[0101] Information on several power supply nodes is obtained through a connection channel with the power supply database; the power supply node information includes the power supply node and / or the power supply quantity.

[0102] All power supply node information is filtered using a preset power supply threshold to obtain a target power supply node information set; the target power supply node information set includes several target power supply node information sets.

[0103] For any target power supply node information, determine the virtual power supply area corresponding to that target power supply node information;

[0104] All virtual power supply areas are cumulatively processed to obtain the smart grid power supply area.

[0105] Optionally, the above power supply threshold is related to the power supply unit.

[0106] It is evident that the smart grid fault location method described in the embodiments of the present invention can obtain the fault threshold through comprehensive processing such as identifying user repair request information, which is conducive to achieving accurate fault location of the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0107] In another optional embodiment, the above-mentioned processing of user repair request information using a preset fault value model to obtain regional fault values ​​includes:

[0108] The user's repair request information is identified and processed to obtain the user's credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value;

[0109] The credit information of the customer is corrected to obtain the valid value information; the valid value information includes several valid values.

[0110] The effective value information is summed to obtain the regional fault value.

[0111] In this optional embodiment, as an optional implementation method, the specific way to identify and process user repair request information to obtain user credit information is as follows:

[0112] The user's repair request information is extracted and processed to obtain a user information set; the user information set includes several user information items.

[0113] For any given user information, the user's credit score is determined through matching.

[0114] Optionally, each of the above user information corresponds to a unique credit rating correction factor.

[0115] Optionally, the credit rating adjustment factor is related to the fault reporting situation.

[0116] Furthermore, the more false alarms a user's information receives, the smaller its credit rating correction coefficient becomes; conversely, the more correct fault reports a user's information receives, the larger its credit rating correction coefficient becomes.

[0117] As can be seen, the smart grid fault location method described in the embodiments of the present invention can obtain regional fault values ​​by comprehensively processing user repair request information such as identification, correction and summation. This is beneficial for achieving accurate fault location in the smart grid, improving fault efficiency and reducing grid maintenance costs.

[0118] In yet another optional embodiment, the above-described processing of the power supply area information to obtain a fault threshold includes:

[0119] Based on the power supply area information, the power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information.

[0120] The electricity demand information is processed to obtain the area resistance value;

[0121] The risk probability is obtained by matching the area resistance values ​​using a preset risk probability table.

[0122] The risk probability is matched using a preset regional threshold table to obtain the fault threshold.

[0123] Optionally, the above power request information is triggered by the unit currently using power.

[0124] Optionally, the resistance value of the above area is calculated based on the voltage and current of the power supply port.

[0125] Optionally, the number of units currently consuming electricity is inversely proportional to the area resistance value. Furthermore, the more units currently consuming electricity, the smaller the area resistance value.

[0126] Optionally, the risk probability obtained through the matching process is obtained by traversing a preset risk probability table and identifying the candidate probabilities in the risk probability table that match the area resistance value as the risk probability.

[0127] It is evident that the smart grid fault location method described in the embodiments of the present invention can obtain fault thresholds through comprehensive processing such as calculation and matching of power supply area information, which is more conducive to achieving accurate fault location of the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0128] Example 2

[0129] Please see Figure 2 , Figure 2 This is a flowchart illustrating another smart grid fault location method disclosed in an embodiment of the present invention. Figure 2 The described smart grid fault location method is applied to fault handling systems, such as local servers or cloud servers used for smart grid fault location management, etc., and the embodiments of the present invention are not limited thereto. Figure 2 As shown, the smart grid fault location method may include the following operations:

[0130] 201. Obtain user repair request information.

[0131] 202. Process user repair request information to obtain regional fault values ​​and fault thresholds.

[0132] 203. Determine whether the fault value of the area is greater than or equal to the fault threshold to obtain the first judgment result.

[0133] 204. When the first judgment result is yes, obtain the region image information.

[0134] 205. Classify the regional image information to obtain a set of image information to be used.

[0135] In this embodiment of the invention, the above-mentioned set of image information to be used includes several sets of image information to be used.

[0136] In this embodiment of the invention, the above-mentioned image information to be used includes image information of several high-risk points.

[0137] In this embodiment of the invention, the above-mentioned image information to be used is related to the label information of the high-risk point image information.

[0138] 206. Perform recognition and calculation processing on the set of image information to be used to obtain risk location information.

[0139] In this embodiment of the invention, the specific technical details and explanations of technical terms for steps 201-204 can be found in the detailed description of steps 101-104 in Embodiment 1, and will not be repeated here.

[0140] Optionally, the aforementioned high-risk point image information includes high-risk point images and / or, acquisition terminal label information, which is not limited in this embodiment of the invention.

[0141] Optionally, the above classification of regional image information is performed based on the label information of the acquisition end.

[0142] Optionally, the acquisition terminal label information corresponding to all the high-risk point image information in any of the above-mentioned image information to be used is consistent.

[0143] As can be seen, the smart grid fault location method described in the embodiments of the present invention can obtain regional fault values ​​and fault thresholds by processing user repair request information, and then obtain risk location information for indicating fault location in the smart grid by comparing and judging the regional fault values ​​and fault thresholds, as well as converting and calculating regional image information. This is beneficial for achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0144] In an optional embodiment, the above-described identification and calculation processing of the image information set to be used to obtain risk location information includes:

[0145] The image information set to be used is transformed to obtain a feature array information set; the feature array information set includes several feature arrays; the feature arrays are related to the color value information of the high-risk point image information;

[0146] The risk location information is obtained by performing calculations on the feature array information set.

[0147] In this optional embodiment, as an optional implementation method, the specific way to perform the above-mentioned transformation processing on the image information set to obtain the feature array information set is as follows:

[0148] For any image information to be used, sort all high-risk point image information in the image information to be used according to the acquisition time from earliest to latest to obtain an image sequence;

[0149] The high-risk point image information in the image sequence is converted sequentially to obtain the color value information set corresponding to the image information to be used; the color value information set includes several color value information; each color value information corresponds to a unique high-risk point image information; each color value information includes several color values;

[0150] The average value of the color value information set is calculated to obtain the feature value set corresponding to the image information to be used; the feature value set includes several feature values.

[0151] Based on the sequence information corresponding to the image sequence, all feature values ​​in the above feature value set are sorted to generate the feature array information corresponding to the image information to be used.

[0152] Optionally, the above-mentioned conversion processing of high-risk point image information in the image sequence is achieved by converting the color values ​​of the pixels of the high-risk point image using a preset conversion formula.

[0153] Optionally, the above color value conversion converts pixels to grayscale.

[0154] It is evident that the smart grid fault location method described in the embodiments of the present invention can obtain risk location information through comprehensive processing such as conversion and calculation of the image information set to be used, which is more conducive to achieving accurate fault location of the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0155] In another optional embodiment, the above-described calculation and processing of the feature array information set to obtain risk location information includes:

[0156] The feature array information set is processed by calculating the average value to obtain the standard deviation information set; the standard deviation information set includes several standard deviation information.

[0157] By comparing the standard deviation information set with a preset standard deviation threshold, risk location information is obtained.

[0158] Optionally, the above standard deviation information includes the standard deviation value and / or the data acquisition terminal label information, which is not limited in this embodiment of the invention.

[0159] Optionally, the above standard deviation represents the degree of dispersion of feature values ​​in the feature array information.

[0160] In this optional embodiment, as an optional implementation method, the specific way to obtain the risk location information by comparing the standard deviation information set using a preset standard deviation threshold is as follows:

[0161] For any standard deviation information, determine whether the standard deviation value corresponding to the standard deviation information is greater than or equal to the preset standard deviation threshold, and obtain the standard deviation judgment result;

[0162] When the standard deviation judgment result is yes, the risk location information is determined based on the data acquisition terminal label information corresponding to the standard deviation information.

[0163] It is evident that the smart grid fault location method described in the embodiments of the present invention can obtain risk location information through comprehensive processing such as calculation and comparison of the feature array information set, which is more conducive to achieving accurate fault location of the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0164] Example 3

[0165] Please see Figure 3 , Figure 3 This is a structural schematic diagram of a smart grid fault location device disclosed in an embodiment of the present invention. Figure 3 The described apparatus can be applied to fault handling systems, such as local servers or cloud servers for smart grid fault location management, etc., and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the device may include:

[0166] The acquisition module 301 is used to acquire user repair request information; the user repair request information includes several user repair requests;

[0167] The first processing module 302 is used to process user repair request information to obtain regional fault values ​​and fault thresholds.

[0168] The judgment module 303 is used to determine whether the area fault value is greater than or equal to the fault threshold, and obtain the first judgment result;

[0169] The acquisition module 301 is also used to acquire regional image information when the first judgment result is yes; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user's repair request information belongs;

[0170] The second processing module 304 is used to classify and identify the regional image information to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid.

[0171] It is evident that implementation Figure 3 The described smart grid fault location device can obtain regional fault values ​​and fault thresholds by processing user repair request information. Then, by comparing and judging the regional fault values ​​and fault thresholds and comprehensively processing regional image information, it can obtain risk location information for indicating the location of faults in the smart grid. This is conducive to achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0172] In another alternative embodiment, such as Figure 4 As shown, the first processing module 302 includes a first processing submodule 3021, a second processing submodule 3022, and a third processing submodule 3023, wherein:

[0173] The first processing submodule 3021 is used to process user repair request information using a preset fault value model to obtain regional fault values.

[0174] The second processing submodule 3022 is used to identify and process user repair request information to obtain power supply area information; the power supply area information includes the power supply area of ​​the smart grid.

[0175] The third processing submodule 3023 is used to process the power supply area information to obtain the fault threshold.

[0176] It is evident that implementation Figure 4 The described smart grid fault location device can obtain fault thresholds through comprehensive processing such as identifying user repair request information, which is conducive to achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0177] In yet another alternative embodiment, such as Figure 4 As shown, the first processing submodule 3021 processes the user's repair request information using a preset fault value model to obtain the regional fault value in the following specific way:

[0178] The user's repair request information is identified and processed to obtain the user's credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value;

[0179] The credit information of the customer is corrected to obtain the valid value information; the valid value information includes several valid values.

[0180] The effective value information is summed to obtain the regional fault value.

[0181] It is evident that implementation Figure 4 The described smart grid fault location device can obtain regional fault values ​​by comprehensively processing user repair request information, such as identification, correction, and summation. This facilitates accurate fault location in the smart grid, improves fault efficiency, and reduces grid maintenance costs.

[0182] In yet another alternative embodiment, such as Figure 4 As shown, the third processing submodule 3023 processes the power supply area information to obtain the fault threshold in the following specific way:

[0183] Based on the power supply area information, the power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information.

[0184] The electricity demand information is processed to obtain the area resistance value;

[0185] The risk probability is obtained by matching the area resistance values ​​using a preset risk probability table.

[0186] The risk probability is matched using a preset regional threshold table to obtain the fault threshold.

[0187] It is evident that implementation Figure 4 The described smart grid fault location device can obtain fault thresholds through comprehensive processing such as calculation and matching of power supply area information, which is more conducive to achieving accurate fault location of smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0188] In yet another alternative embodiment, such as Figure 4 As shown, the second processing module 304 performs classification and recognition processing on the regional image information to obtain the risk location information in the following specific way:

[0189] The regional image information is classified and processed to obtain a set of images to be used; the set of images to be used includes several images to be used; the images to be used include several high-risk point images; the images to be used are related to the label information of the high-risk point images.

[0190] The set of image information to be used is processed for recognition and calculation to obtain risk location information.

[0191] It is evident that implementation Figure 4The described smart grid fault location device can obtain regional fault values ​​and fault thresholds by processing user repair request information. Then, through comprehensive processing such as comparing and judging regional fault values ​​and fault thresholds, and converting and calculating regional image information, it can obtain risk location information used to indicate the location of faults in the smart grid. This is conducive to achieving accurate fault location in the smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0192] In yet another alternative embodiment, such as Figure 4 As shown, the second processing module 304 performs recognition and calculation processing on the set of image information to be used to obtain the risk location information in the following specific way:

[0193] The image information set to be used is transformed to obtain a feature array information set; the feature array information set includes several feature arrays; the feature arrays are related to the color value information of the high-risk point image information;

[0194] The risk location information is obtained by performing calculations on the feature array information set.

[0195] It is evident that implementation Figure 4 The described smart grid fault location device can obtain risk location information through comprehensive processing such as conversion and calculation of the image information set to be used, which is more conducive to achieving accurate fault location of smart grid, improving fault efficiency and reducing grid maintenance costs.

[0196] In yet another alternative embodiment, such as Figure 4 As shown, the second processing module 304 performs calculations on the feature array information set to obtain the risk location information in the following specific way:

[0197] The feature array information set is processed by calculating the average value to obtain the standard deviation information set; the standard deviation information set includes several standard deviation information.

[0198] By comparing the standard deviation information set with a preset standard deviation threshold, risk location information is obtained.

[0199] It is evident that implementation Figure 4 The described smart grid fault location device can obtain risk location information through comprehensive processing such as calculation and comparison of feature array information sets, which is more conducive to achieving accurate fault location of smart grid, improving fault efficiency, and reducing grid maintenance costs.

[0200] Example 4

[0201] Please see Figure 5 , Figure 5 This is a structural schematic diagram of another smart grid fault location device disclosed in an embodiment of the present invention. Wherein, Figure 5The described apparatus can be applied to fault handling systems, such as local servers or cloud servers for smart grid fault location management, etc., and the embodiments of the present invention are not limited thereto. Figure 5 As shown, the device may include:

[0202] Memory 401 storing executable program code;

[0203] Processor 402 coupled to memory 401;

[0204] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the smart grid fault location method described in Embodiment 1 or Embodiment 2.

[0205] Example 5

[0206] This invention discloses a computer read storage medium that stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the smart grid fault location method described in Embodiment 1 or Embodiment 2.

[0207] Example 6

[0208] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the smart grid fault location method described in Embodiment 1 or Embodiment 2.

[0209] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0210] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0211] Finally, it should be noted that the smart grid fault location method and device disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for fault location in a smart grid, characterized in that, The method includes: Obtain user repair request information; the user repair request information includes several user repair requests; The user's repair request information is processed to obtain the regional fault value and fault threshold; Determine whether the fault value of the area is greater than or equal to the fault threshold to obtain a first determination result; When the first judgment result is yes, regional image information is obtained; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs; The image information of the region is classified and identified to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid; The process of processing the user's repair request information to obtain the regional fault value and fault threshold includes: The user's repair request information is processed using a preset fault value model to obtain the regional fault value; The user's repair request information is identified and processed to obtain power supply area information; the power supply area information includes the smart grid power supply area and power supply area coding information. The power supply area information is processed to obtain the fault threshold; The process of processing the user's repair request information using a preset fault value model to obtain regional fault values ​​includes: The user's repair request information is identified and processed to obtain user credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value; The user credit information is corrected to obtain valid value information; the valid value information includes several valid values. The effective value information is summed to obtain the regional fault value; The process of identifying and processing the user's repair request information to obtain user credit information includes: The user's repair request information is extracted and processed to obtain a user information set; the user information set includes several user information items. For any given user information, the user credit score corresponding to that user information is determined through matching. Each piece of user information corresponds to a unique credit rating correction coefficient, which is related to the fault reporting situation; The process of processing power supply area information to obtain fault thresholds includes: Based on the power supply area information, the power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information. The electricity demand information is processed to obtain the area resistance value; The risk probability is obtained by matching the area resistance values ​​using a preset risk probability table. The risk probability is matched using a preset regional threshold table to obtain the fault threshold; The power request information is triggered by the unit currently using power, and the area resistance value is calculated based on the voltage and current of the power supply port. The unit currently using power is inversely proportional to the area resistance value. The specific method for dividing and determining any smart grid power supply area is as follows: Information on several power supply nodes is obtained through a connection channel with the power supply database; the power supply node information includes the power supply node and the power supply quantity. All power supply node information is filtered using a preset power supply threshold to obtain a target power supply node information set; the target power supply node information set includes several target power supply node information sets. For any target power supply node information, determine the virtual power supply area corresponding to the target power supply node information; The total power supply area of ​​all virtual power supply areas is accumulated to obtain the smart grid power supply area; The power supply threshold is related to the power supply unit.

2. The smart grid fault location method according to claim 1, characterized in that, The process of classifying and recognizing the image information of the region to obtain risk location information includes: The image information of the region is classified to obtain a set of images to be used; the set of images to be used includes several images to be used; the images to be used include several high-risk point images; the images to be used are related to the label information of the high-risk point images. The set of images to be used is processed for identification and calculation to obtain risk location information.

3. The smart grid fault location method according to claim 2, characterized in that, The process of identifying and calculating the set of images to be used to obtain risk location information includes: The set of image information to be used is transformed to obtain a set of feature array information; the set of feature array information includes several feature arrays; the feature arrays are related to the color value information of the high-risk point image information; The risk location information is obtained by performing calculations on the feature array information set.

4. The smart grid fault location method according to claim 3, characterized in that, The step of processing the feature array information set to obtain risk location information includes: The feature array information set is processed by calculating the average value to obtain the standard deviation information set; the standard deviation information set includes several standard deviation information. The risk location information is obtained by comparing the standard deviation information set with a preset standard deviation threshold.

5. A smart grid fault location device, characterized in that, The device includes: The acquisition module is used to acquire user repair request information; the user repair request information includes several user repair requests. The first processing module is used to process the user's repair request information to obtain the regional fault value and fault threshold. The judgment module is used to determine whether the fault value of the area is greater than or equal to the fault threshold, and to obtain a first judgment result; The acquisition module is further configured to acquire regional image information when the first judgment result is yes; the regional image information includes image information of several high-risk points; the smart grid power supply area to which the regional image information belongs is consistent with the smart grid power supply area to which the user repair request information belongs; The second processing module is used to classify and identify the regional image information to obtain risk location information; the risk location information includes several risk point information; the risk location information is used to indicate the location of faults in the smart grid; The first processing module includes a first processing submodule, a second processing submodule, and a third processing submodule, wherein: The first processing submodule is used to process the user's repair request information using a preset fault value model to obtain the regional fault value; The second processing submodule is used to identify and process the user's repair request information to obtain power supply area information; the power supply area information includes the smart grid power supply area; The third processing submodule is used to process the power supply area information to obtain a fault threshold. The first processing submodule processes the user repair request information using a preset fault value model to obtain the regional fault value in the following specific way: The user's repair request information is identified and processed to obtain user credit information; the user credit information includes several user credit scores; the user credit score is related to the user's credit value; The user credit information is corrected to obtain valid value information; the valid value information includes several valid values. The effective value information is summed to obtain the regional fault value; The specific method for identifying and processing the user's repair request information to obtain user credit information is as follows: The user's repair request information is extracted and processed to obtain a user information set; the user information set includes several user information items. For any given user information, the user credit score corresponding to that user information is determined through matching. Each piece of user information corresponds to a unique credit rating correction coefficient, which is related to the fault reporting situation; The third processing submodule processes the power supply area information to obtain the fault threshold in the following specific way: Based on the power supply area information, the power demand information is determined; the power demand information is related to the voltage and current conditions of the power supply area information. The electricity demand information is processed to obtain the area resistance value; The risk probability is obtained by matching the area resistance values ​​using a preset risk probability table. The risk probability is matched using a preset regional threshold table to obtain the fault threshold; The power request information is triggered by the unit currently using power, and the area resistance value is calculated based on the voltage and current of the power supply port. The unit currently using power is inversely proportional to the area resistance value. The specific method for dividing and determining any smart grid power supply area is as follows: Information on several power supply nodes is obtained through a connection channel with the power supply database; the power supply node information includes the power supply node and the power supply quantity. All power supply node information is filtered using a preset power supply threshold to obtain a target power supply node information set; the target power supply node information set includes several target power supply node information sets. For any target power supply node information, determine the virtual power supply area corresponding to the target power supply node information; The total power supply area of ​​all virtual power supply areas is accumulated to obtain the smart grid power supply area; The power supply threshold is related to the power supply unit.

6. A smart grid fault location device, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the smart grid fault location method as described in any one of claims 1-4.

7. A computer-storable medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the smart grid fault location method as described in any one of claims 1-4.

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