Data management method and system for smart power grid

Abstract

The invention relates to the field of power grid data security management, and provides a data management method and system for a smart power grid, and the method comprises the steps: obtaining the geographic position of power grid equipment, and building an annular star-shaped model diagram based on the geographic position of the power grid equipment; segmenting the power utilization data based on the annular star-shaped model graph to obtain data pieces, and setting priorities of the data pieces; performing random confusion exchange on the power utilization data of all the intelligent electric meters based on the annular star model diagram to obtain first confusion data and a first exchange path; performing random confusion exchange on the first confusion data of all concentrators based on the annular star model graph to obtain second confusion data and a second exchange path; and recovering and detecting the second confused data based on the second confused data and the second switching path to obtain power consumption data, and storing the power consumption data into the data management center. When the method is used, data can be prevented from being stolen in the transmission process, and the integrity and consistency of the data are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of power grid data security management, and more specifically, to a data management method and system for a smart grid. Background Art

[0002] With the rapid development of smart grids and the widespread application of new energy technologies, terminal devices such as smart meters, as an important part of smart grids, play an indispensable role in the collection and transmission of electricity consumption information in the electricity consumption link of smart grids, and their data security management is increasingly valued.

[0003] At present, traditional smart grids generally rely on smart meters to collect electricity data for civil electricity. Smart meters transmit data to the data management center of the smart grid. Generally, the smart meter data within a preset range is collected through a concentrator, and then connected to the data management center through multiple concentrators to form a star topology for data transmission. This data topology has a large number of single data channels, which increases the risk of data on the transmission channel being attacked by hackers. Once the data is illegally obtained, the user's privacy may be leaked, which will cause a series of security issues and make it difficult to meet the high requirements of modern smart grids for secure data transmission. Summary of the invention

[0004] The purpose of the present invention is to provide a data management method and system for a smart grid to address the deficiencies in the background technology.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a data management method for a smart grid, comprising the following steps: Determine the management scope of the smart grid, obtain the geographical location of the grid equipment within the management scope, the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator and the geographical location of the data management center, and establish a ring star model diagram based on the geographical location of the grid equipment; Based on the ring star model diagram, the electricity consumption data of the smart meter is obtained in real time, the electricity consumption data is sliced ​​to obtain data slices, sensitive information of the data slices is extracted and the priority of the data slices is set to obtain electricity consumption characteristic data, and the electricity consumption characteristic data is bound to the corresponding smart meter; Based on the ring star model diagram, the electricity consumption data of all smart meters within the management range of the concentrator are randomly confused and exchanged to obtain first confused data and a first exchange path, and the first confused data is transmitted to the concentrator; Based on the ring star model diagram, the first obfuscated data of all concentrators corresponding to the data management center are randomly obfuscated and exchanged again to obtain second obfuscated data and a second exchange path, and the second obfuscated data is transmitted to the data management center; Based on the second obfuscated data and the second exchange path, the data management center restores and detects the second obfuscated data to obtain the power usage data of the corresponding user, and stores the power usage data in the data management center.

[0006] In a preferred embodiment, the step of establishing a ring-shaped star model diagram based on the geographical location of the power grid equipment includes: Determine the management scope of the smart grid, obtain the geographical location of the smart meter, the geographical location of the concentrator, and the geographical location of the data management center within the management scope as the geographical location of the power grid equipment, obtain the user number within the management scope, and bind the smart meter to the corresponding user number; Based on the geographical location of the power grid equipment, multiple concentrators are connected to the data management center, and the multiple concentrators are interconnected to form a loop closed circuit. The smart meters within the management range of the concentrator are connected to the corresponding concentrators, and the multiple smart meters within the management range of the corresponding concentrators are interconnected to form a loop closed circuit to obtain a ring star model diagram.

[0007] In a preferred embodiment, the steps of acquiring the electricity consumption data of the smart meter in real time based on the ring star model diagram, slicing the electricity consumption data to obtain data slices, extracting sensitive information of the data slices and setting the priority of the data slices to obtain electricity consumption feature data include: Based on the ring star model diagram, the electricity consumption data of the corresponding user is obtained through the smart meter, the electricity consumption data includes the electricity consumption and the corresponding electricity consumption time period, a hash value corresponding to the electricity consumption data is generated, and the hash value is bound to the electricity consumption data of the corresponding smart meter; Slice the electricity consumption data of multiple smart meters corresponding to the management range of the concentrator according to a preset amount to obtain a number of data slices of equal amount, and number the storage locations of the smart meters and the data slices; Extract data pieces with sensitive information from the electricity usage data and mark them as high priority to obtain electricity usage feature data, wherein the sensitive information includes electricity usage values ​​and electricity usage time period values, and bind the electricity usage feature data to the corresponding smart meter.

[0008] In a preferred embodiment, the step of randomly mixing and exchanging the electricity consumption data of all smart meters within the management range of the concentrator based on the ring star model diagram to obtain first mixed data and a first exchange path includes: Establishing a data exchange path table corresponding to the smart meters within the management range of the concentrator as a first exchange path, wherein the first exchange path includes a first data node corresponding to the number of smart meters within the management range of the concentrator, and a first pointer, and binding the first exchange path to the corresponding concentrator; Traverse all smart meters within the management range of all concentrators and take the currently traversed smart meter as the target meter, take the smart meter connected to the target meter as the exchange meter, randomly select two data slices in the target meter as original data slices according to the order of data slice priority from high to low, and record the target meter number and the number of the data slice storage position as the first initial number on the first data node of the first exchange path, and transmit the two data slices of the original data slice to the corresponding exchange meter respectively. The exchange meter randomly selects a data slice as the exchange data slice according to the order of data slice priority from high to low and transmits it to the target meter, and records the number of the exchange meter and the number of the exchange data slice storage position as the first exchange number on the first data node of the first exchange path, and follows the pointing of the first pointer until all first data nodes complete the storage of the first initial number and the first exchange number of the corresponding smart meter. After repeating the expected number of traversal operations, the concentrator collects the electricity consumption data of all corresponding smart meters to obtain the first obfuscated data.

[0009] In a preferred embodiment, the step of randomly performing a confusion exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring-shaped star model diagram to obtain the second obfuscated data and the second exchange path includes: Dividing the first obfuscated data in the concentrator into a plurality of data segments of equal size according to a preset amount, and numbering the storage locations of the concentrators and the data segments; Establishing a data exchange path table corresponding to the concentrator of the data management center as a second exchange path, wherein the second exchange path includes a second data node of the number of concentrators corresponding to the data management center and a second pointer, and binding the second exchange path to the data management center; Traverse all concentrators and use the currently traversed concentrator as the target concentrator, use the concentrator connected to the target concentrator as the switching concentrator, randomly select two data segments in the target concentrator as original data segments, and record the target concentrator number and the number of the data segment storage location as the second initial number on the second data node of the second switching path, respectively transmit the two data segments of the original data segment to the corresponding switching concentrator, the switching concentrator randomly selects a data segment as the switching data segment and transmits it to the target electric meter, and records the number of the switching concentrator as the second switching number on the second data node of the second switching path, and follows the direction of the second pointer until all second data nodes complete the storage of the second initial number and the second switching number of the corresponding concentrator. After repeating the traversal operation for the expected number of times, the data management center collects the data of all corresponding concentrators to obtain the second obfuscated data.

[0010] In a preferred embodiment, the step of restoring the second obfuscated data based on the second obfuscated data and the second exchange path data management center and detecting to obtain the power consumption data of the corresponding user, and storing the power consumption data in the data management center includes: The second exchange path is processed in reverse order to obtain a second restoration path, and the second initial number corresponding to the second data node and the second exchange number are exchanged for data storage positions based on the second restoration path until all data segments are restored to the second initial number to obtain the first obfuscated data and the first exchange path; The first exchange path is processed in reverse order to obtain a first restoration path, and the first initial number corresponding to the first data node is exchanged with the first exchange number based on the first restoration path for the first data storage location until all data segments are restored to the first initial number to obtain the corresponding user's data to be detected; The data to be detected is detected to obtain the user's power consumption data and abnormal data, the power consumption data is stored in the data management center, and the abnormal data is resent.

[0011] In a preferred embodiment, the steps of detecting the data to be detected to obtain the user's power consumption data and abnormal data, storing the power consumption data in the data management center, and resending the abnormal data include: Generate a hash value of the data to be detected as a comparison hash value. If the comparison hash value is consistent with the hash value corresponding to the power consumption data, the data to be detected is determined to be the user's power consumption data; otherwise, the data to be detected is determined to be abnormal data. The user's electricity consumption data is stored in the data management center, and the data management center sends a data resend request to the smart meter corresponding to the abnormal data. After receiving the request, the smart meter resends it to the data management center through random confusion exchange and stores it.

[0012] The present invention also provides a data management system for a smart grid, comprising: Establish a module for determining the management scope of the smart grid, obtaining the geographical location of the grid equipment within the management scope, wherein the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator, and the geographical location of the data management center, and establishing a ring star model diagram based on the geographical location of the grid equipment; A partitioning module, connected to the establishing module, is used to obtain the power consumption data of the smart meter in real time based on the ring star model diagram, slice the power consumption data to obtain data slices, extract sensitive information of the data slices and set the priority of the data slices to obtain power consumption feature data, and bind the power consumption feature data to the corresponding smart meter; A first obfuscation module is connected to the division module and is used to randomly obfuscate and exchange the electricity consumption data of all smart meters within the management range of the concentrator based on the ring star model diagram to obtain first obfuscated data and a first exchange path, and transmit the first obfuscated data to the concentrator; The second obfuscation module is connected to the first obfuscation module and is used to randomly perform obfuscation exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring star model diagram to obtain second obfuscated data and a second exchange path, and transmit the second obfuscated data to the data management center; The storage module is connected to the second obfuscation module and is used to restore and detect the second obfuscated data based on the second obfuscated data and the second switching path data management center to obtain the power consumption data of the corresponding user, and store the power consumption data in the data management center.

[0013] In the above technical solution, the technical effects and advantages provided by the present invention are: The present invention can improve the traditional star topology into a ring star topology. It solves the problem of a large number of single data channels in the traditional star topology, which leads to data theft in the transmission channel, through random confusion exchange technology. It can better protect the user's electricity privacy data and enhance the security and integrity of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0015] Figure 1 The present invention is a flow chart of the method.

[0016] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, the data management method for a smart grid described in this embodiment includes the following steps: S1. Determine the management scope of the smart grid, obtain the geographical location of the grid equipment within the management scope, the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator and the geographical location of the data management center, and establish a ring star model diagram based on the geographical location of the grid equipment; S2. Based on the ring star model diagram, the electricity consumption data of the smart meter is obtained in real time, the electricity consumption data is sliced ​​to obtain data slices, sensitive information of the data slices is extracted and the priority of the data slices is set to obtain electricity consumption characteristic data, and the electricity consumption characteristic data is bound to the corresponding smart meter; S3, based on the ring star model diagram, randomly confuse and exchange the electricity consumption data of all smart meters within the management range of the concentrator to obtain first obfuscated data and a first exchange path, and transmit the first obfuscated data to the concentrator; S4, based on the ring star model diagram, randomly perform obfuscation exchange on the first obfuscated data of all concentrators corresponding to the data management center to obtain second obfuscated data and a second exchange path, and transmit the second obfuscated data to the data management center; S5. Based on the second obfuscated data and the second exchange path, the data management center restores the second obfuscated data and detects to obtain the power consumption data of the corresponding user, and stores the power consumption data in the data management center; As described in the above steps S1-S5, at present, the traditional smart grid generally relies on smart meters to collect the electric energy data of civil electricity. The smart meters need to transmit the data to the data management center of the smart grid. Generally, the smart meter data within a preset range is collected through a concentrator, and then connected to the data management center through multiple concentrators to form a star topology for data transmission. This data topology has a large number of monomer data channels, which increases the risk of data being attacked by hackers on the transmission channel. Once the data is illegally obtained, the user's privacy may be leaked, which will cause a series of security problems. It is difficult to meet the high requirements of modern smart grids for data security transmission. The present application can improve the traditional star topology into a ring star topology, and solve the problem of the traditional star topology having a large number of monomer data channels, which leads to the theft of data on the transmission channel, through random confusion exchange technology. It can better protect the user's electricity privacy data and enhance the security and integrity of the data. In one embodiment, the step S1 of establishing a ring-shaped star model diagram based on the geographical location of the power grid equipment includes: S11, determining the management scope of the smart grid, obtaining the geographical locations of smart meters, concentrators and data management centers within the management scope as the geographical locations of power grid equipment, obtaining user numbers within the management scope, and binding the smart meters to the corresponding user numbers; S12, connecting multiple concentrators with a data management center based on the geographical location of the power grid equipment, interconnecting the multiple concentrators to form a closed loop, connecting smart meters within the management range of the concentrators with corresponding concentrators, and interconnecting multiple smart meters within the management range of the corresponding concentrators to form a closed loop to obtain a ring-shaped star model diagram; As described in the above steps S11-S12, firstly, the management scope of the smart grid is determined, and the geographical locations of the smart meters, the concentrators and the data management center are collected within the management scope as the geographical locations of the power grid equipment. The smart meters are used to collect the electricity consumption data of the users, and the concentrators are used to integrate the data of the smart meters within the management scope of the concentrators. The data management center is used to store the smart meter data integrated by the concentrators. The user numbers within the management scope are collected, and the smart meters are bound to the corresponding user numbers. Then, based on the geographical locations of the power grid equipment, multiple concentrators are connected to the data management center, and then multiple concentrators are interconnected to form a closed loop with no starting point and no end point. The management scope of the concentrator is set, and the smart meters within the management scope of the concentrator are connected to the corresponding concentrators. Multiple smart meters within the management scope of the corresponding concentrators are interconnected to form a closed loop with no starting point and no end point to obtain a ring-shaped star model diagram, which can optimize the traditional star topology structure, increase the transmission routes of the same-level nodes, and facilitate the data exchange of the same-level nodes, solve the problem of a large number of monomer data channels in the traditional star topology structure, and play an auxiliary role in the subsequent random confusion exchange operation; In one embodiment, the step S2 of acquiring the electricity consumption data of the smart meter in real time based on the ring star model diagram, slicing the electricity consumption data to obtain data slices, extracting sensitive information of the data slices and setting the priority of the data slices to obtain electricity consumption feature data includes: S21, based on the ring star model diagram, obtaining the electricity consumption data of the corresponding user through the smart meter, the electricity consumption data including the electricity consumption and the corresponding electricity consumption time period, generating a hash value corresponding to the electricity consumption data, and binding the hash value to the electricity consumption data of the corresponding smart meter; S22, dividing the electricity consumption data of the corresponding multiple smart meters within the management range of the concentrator into pieces according to a preset amount to obtain a number of data pieces of equal amount, and numbering the storage locations of the smart meters and the data pieces; S23, extracting data pieces with sensitive information from the electricity consumption data and marking them as high priority to obtain electricity consumption characteristic data, wherein the sensitive information includes the electricity consumption value and the electricity consumption time period value, and binding the electricity consumption characteristic data to the corresponding smart meter; As described in the above steps S21-S23, based on the ring star model diagram, the power consumption of the corresponding user is collected through the smart meter based on the corresponding power consumption time period as the power consumption data, and then a hash value of the power consumption data is generated. The hash value here can generate a fixed-length hash value through the SHA-256 hash algorithm to uniquely determine the power consumption data of the corresponding user, in preparation for the subsequent detection of data integrity, and then the hash value is bound to the corresponding power consumption data, and the power consumption data of the corresponding multiple smart meters within the management range of the concentrator are sliced ​​according to the preset amount to obtain a number of equal data slices, and then the smart meters and the storage locations of the data slices are numbered. For example, the preset amount is 10B, and the data amount of one smart meter is 10MB, then the power consumption data of the smart meter is divided into 10M data slices, and the 10M data slices are numbered, and the smart meters within the management range of the concentrator are numbered to obtain a unique number for each data slice, such as B 0001P0001 represents the data slice numbered P0001 corresponding to the smart meter numbered D0001. The probability of a high-priority data slice being selected in the subsequent random confusion exchange will increase. The priority from high to low indicates a decreasing priority. The specific value of the power consumption of the power consumption data and the specific value of the corresponding power consumption time period are identified and marked as power consumption characteristic data. Finally, the priority is set. For example, the power consumption in the power consumption data of one of the smart meters is 100Kwh, and the power consumption time period is 00:00~19:00. 100, 00, 00, 19, 00 are marked as power consumption characteristic data, and the data slice corresponding to the power consumption characteristic data is set to the highest priority. The power consumption characteristic data is bound to the corresponding smart meter to collect the user's power consumption data in real time, generate a hash value corresponding to the power consumption data, identify the characteristic data of the power consumption data and set a high priority, which can better provide an operation object for subsequent random confusion exchange. In one embodiment, the step S3 of randomly mixing and exchanging the electricity consumption data of all smart meters within the management range of the concentrator based on the ring star model diagram to obtain first mixed data and a first exchange path includes: S31, establishing a data exchange path table corresponding to the smart meters within the management range of the concentrator as a first exchange path, wherein the first exchange path includes a first data node corresponding to the number of smart meters within the management range of the concentrator, and a first pointer, and binding the first exchange path to the corresponding concentrator; S32, traverse all smart meters within the management range of all concentrators and take the currently traversed smart meter as the target meter, take the smart meter connected to the target meter as the exchange meter, randomly select two data slices in the target meter according to the order of data slice priority from high to low as the original data slices, and record the target meter number and the number of the data slice storage location as the first initial number on the first data node of the first exchange path, respectively transmit the two data slices of the original data slice to the corresponding exchange meter, the exchange meter randomly selects a data slice as the exchange data slice according to the order of data slice priority from high to low and transmits it to the target meter, records the number of the exchange meter and the number of the exchange data slice storage location as the first exchange number on the first data node of the first exchange path, follow the pointing of the first pointer until all first data nodes complete the storage of the first initial number and the first exchange number of the corresponding smart meter, repeat the expected number of traversal operations, and then the concentrator collects the electricity consumption data of all corresponding smart meters to obtain the first obfuscated data; As described in the above steps S31-S32, firstly, a data exchange path corresponding to the smart meter within the management scope of the concentrator is established and marked as the first exchange path. The first exchange path here is used to record the destination of the data slice after the exchange, so that the subsequent data management center can integrate the data according to the first exchange path. The first exchange path includes a first data node corresponding to the number of smart meters within the management scope of the concentrator, a first pointer, and the first exchange path is bound to the corresponding concentrator. The first data node here is used to record the exchanged data slices in the smart meter. The first pointer here is used to mark the destination relationship of each data slice in the first data node. One smart meter corresponds to one first data node, and then all concentrators are traversed. All smart meters within the management range are managed, and the currently traversed smart meter is taken as the target meter, and the smart meter connected to the target meter is taken as the exchange meter. There are two exchange meters here. Then the target meter randomly selects two data slices in the target meter according to the order of priority from high to low and marks them as original data slices. The target meter number and the number of the data slice storage location are recorded as the first initial number on the first data node of the first exchange path, and the two data slices of the original data slice are respectively transmitted to the corresponding exchange meter. Here, the exchange meter corresponds to one target meter. The exchange meter randomly selects a data slice as the exchange data slice according to the priority of the data slice from high to low, and transmits the exchange data slice to the target meter. , then record the number of the exchanged meter and the number of the exchanged data slice as the first exchange number on the first data node of the first exchange path, and then use the first pointer to point the first initial number to the first exchange number to identify the direction of the data slice, and then follow the direction of the first pointer until all first data nodes complete the storage of the first initial number and the first exchange number of the corresponding smart meter, repeat the preset number of traversal of all smart meters within the management range of all concentrators, when the same first initial number appears, point the last first exchange number of the same first initial number in the first data node corresponding to the current target meter to the current first exchange number through the first pointer, for example, preset repeated traversal operation The first traversal obtains the first data node of a target meter as D0001P0001 pointing to D0002P0001. The second traversal obtains the first data node of the target meter as D0001P0001 pointing to D0055P0055. The first data node is modified to D0001P0001 pointing to D0002P0001 pointing to D0055P0055. The concentrator collects the electricity consumption data of all corresponding smart meters and integrates them to obtain the first obfuscated data and the first exchange path, which are used to safely desensitize the key data and transmit it to the third-party meter. The data is then transmitted, which can better protect the data privacy of the corresponding user and enhance the security and integrity of the data. In one embodiment, the step S4 of randomly performing a confusion exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring star model diagram to obtain the second obfuscated data and the second exchange path includes: S41, dividing the first obfuscated data in the concentrator into a plurality of data segments of equal size according to a preset amount, and numbering the storage locations of the concentrators and the data segments; S42, establishing a data exchange path table corresponding to the concentrator of the data management center as a second exchange path, wherein the second exchange path includes the second data nodes and the second pointer of the number of concentrators corresponding to the data management center, and binding the second exchange path to the data management center; S43, traverse all concentrators and use the currently traversed concentrator as the target concentrator, use the concentrator connected to the target concentrator as the switching concentrator, randomly select two data segments in the target concentrator as original data segments, and record the target concentrator number and the number of the data segment storage location as the second initial number on the second data node of the second switching path, respectively transmit the two data segments of the original data segment to the corresponding switching concentrator, the switching concentrator randomly selects a data segment as the switching data segment and transmits it to the target electric meter, and records the number of the switching concentrator as the second switching number on the second data node of the second switching path, and follows the direction of the second pointer until all second data nodes complete the storage of the second initial number and the second switching number of the corresponding concentrator. After repeating the expected number of traversal operations, the data management center collects the data of all corresponding concentrators to obtain the second obfuscated data; As described in the above steps S41-S43, first, the first obfuscated data in the concentrator is divided into several data segments according to the preset amount, and the concentrator and the corresponding data segments are numbered. For example, the first obfuscated data in a concentrator is 1GB, the preset amount is 10MB, the first obfuscated data is divided into 103 data segments and numbered, one of the data segments is numbered J0001D0001, and a data exchange path table corresponding to the concentrator is established in the data management center as the second exchange path. The second exchange path here is used to record the destination of the data segment after exchange, so that the subsequent data management center can integrate the data according to the second exchange path The second exchange path includes the second data nodes corresponding to the number of concentrators in the data management center, and the second pointer. The second exchange path is bound to the data management center. The second data node here is used to record the exchange data segments in the concentrator. The second pointer here is used to mark the destination relationship of each data segment in the second data node. One concentrator corresponds to one second data node, and then all concentrators are traversed and the currently traversed concentrator is used as the target concentrator. The concentrator connected to the target concentrator is used as the exchange concentrator. There are two exchange concentrators here, and they are in a one-to-one relationship with the target concentrator. Two data segments in the target concentrator are randomly selected as the original Data segment, and record the target concentrator number and the number of the data segment storage location as the second initial number on the second data node of the second switching path, transmit the two data segments of the original data segment to the corresponding switching concentrator respectively, the switching concentrator randomly selects a data segment as the switching data segment and transmits it to the target electric meter, and records the number of the switching concentrator as the second switching number on the second data node of the second switching path, and then points the second initial number to the second switching number using a second pointer to identify the direction of the data segment, and then follows the direction of the second pointer until all second data nodes complete the storage of the second initial number and the second switching number of the corresponding concentrator, repeat the expected number of times to traverse all concentrator operations, when the same second initial number appears, point the last second switching number of the same second initial number in the second data node corresponding to the current target concentrator through the second pointer to the current second switching number, and finally the data management center collects the data of all corresponding concentrators and integrates them to obtain the second obfuscated data and the second switching path, which are used to perform obfuscated switching on the first obfuscated data and transmit it to the third-party concentrator, and finally transmit it to the data management center through the third-party concentrator, which can solve the problem that a large number of monomer data channels exist in the traditional star topology structure, resulting in data being stolen on the transmission channel; In one embodiment, the step S5 of restoring the second obfuscated data based on the second obfuscated data and the second exchange path data management center and detecting to obtain the power usage data of the corresponding user, and storing the power usage data in the data management center includes: S51, reverse the second exchange path to obtain a second restoration path, and exchange the data storage location of the second initial number corresponding to the second data node with the second exchange number based on the second restoration path until all data segments are restored to the second initial number to obtain the first obfuscated data and the first exchange path; S52, reverse the first exchange path to obtain a first restoration path, and exchange the data storage location of the first initial number corresponding to the first data node with the first exchange number based on the first restoration path until all data segments are restored to the first initial number to obtain the corresponding user's to-be-detected data; S53, detecting the data to be detected to obtain the user's power consumption data and abnormal data, storing the power consumption data in the data management center, and resending the abnormal data; In one embodiment, the step S53 of detecting the data to be detected to obtain the user's power consumption data and abnormal data, storing the power consumption data in the data management center, and retransmitting the abnormal data includes: S531, generating a hash value of the data to be detected as a comparison hash value, and if the comparison hash value is consistent with the hash value corresponding to the power consumption data, the data to be detected is determined to be the power consumption data of the user, otherwise the data to be detected is determined to be abnormal data; S532, storing the user's electricity consumption data in the data management center, and the data management center sending a data resending request to the smart meter corresponding to the abnormal data. After receiving the request, the smart meter resends it to the data management center through random confusion exchange and stores it; As described in the above steps S51-S53, the second exchange path is firstly reversed to obtain a second restoration path, and the second initial number corresponding to the second data node is exchanged with the second exchange number based on the second restoration path for the data storage position until all data segments are restored to the second initial number to obtain the first obfuscated data and the first exchange path. For example, a second data node in the second exchange path is J0001D0001 pointing to J0002D0002 pointing to J0003D0003, and after reverse processing, J0003D0003 pointing to J0002D0002 pointing to J0001D0001 is obtained, and then the data segment corresponding to J0003D0003 is exchanged with J0002D0002. 2, then the data segment corresponding to J0002D0002 is exchanged with the data segment corresponding to J0001D0001 to obtain the first obfuscated data and the first exchange path, and then the first exchange path is reversed to obtain the first restoration path, and the first initial number corresponding to the first data node is exchanged with the first exchange number based on the first restoration path until all data segments are restored to the first initial number to obtain the corresponding user's to-be-detected data. For example, a first data node in the first exchange path is D0001P0001 pointing to D0002P0002 pointing to D0003P0003, and D0003P0003 is obtained after reverse processing. Point to D0002P0002 and point to D0001P0001, then exchange the data segment corresponding to D0003P0003 with the data segment corresponding to D0002P0002, then exchange the data segment corresponding to D0002P0002 with the data segment corresponding to D0001P0001 to get the data to be detected, and then generate a hash value of the data to be detected as a comparison hash value. If the comparison hash value is consistent with the hash value corresponding to the electricity consumption data, the data to be detected is determined to be the user's electricity consumption data, otherwise the data to be detected is determined to be abnormal data. For example, the hash value corresponding to the data to be detected of a certain user is 4799BCec4036D2B5. If the data to be detected of the user is generated According to the hash value of 07B64142D767CaF8, it is determined to be abnormal data. If the hash value of the data to be detected generated by the user is 4799BCec4036D2B5, it is determined to be the electricity consumption data of the corresponding user. Finally, the user's electricity consumption data is stored in the data management center. The data management center sends a data retransmission request to the smart meter corresponding to the abnormal data. After receiving the request, the smart meter retransmits it to the data management center through random confusion exchange and stores it. The second obfuscated data and the first obfuscated data are respectively restored according to the second exchange path and the first exchange path to obtain the user's electricity consumption data, which can better enhance the privacy protection of user data, maintain data utility and improve system security. Example 2, please refer to Figure 2 As shown, the data management system for a smart grid described in this embodiment includes: Establish a module for determining the management scope of the smart grid, obtaining the geographical location of the grid equipment within the management scope, wherein the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator, and the geographical location of the data management center, and establishing a ring star model diagram based on the geographical location of the grid equipment; A partitioning module, connected to the establishing module, is used to obtain the power consumption data of the smart meter in real time based on the ring star model diagram, slice the power consumption data to obtain data slices, extract sensitive information of the data slices and set the priority of the data slices to obtain power consumption feature data, and bind the power consumption feature data to the corresponding smart meter; A first obfuscation module is connected to the division module and is used to randomly obfuscate and exchange the electricity consumption data of all smart meters within the management range of the concentrator based on the ring star model diagram to obtain first obfuscated data and a first exchange path, and transmit the first obfuscated data to the concentrator; The second obfuscation module is connected to the first obfuscation module and is used to randomly perform obfuscation exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring star model diagram to obtain second obfuscated data and a second exchange path, and transmit the second obfuscated data to the data management center; The storage module is connected to the second obfuscation module and is used to restore and detect the second obfuscated data based on the second obfuscated data and the second switching path data management center to obtain the power consumption data of the corresponding user, and store the power consumption data in the data management center.

[0019] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data management method for a smart grid, characterized in that: The following steps are involved: Determine the management scope of the smart grid, obtain the geographical location of the grid equipment within the management scope, the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator and the geographical location of the data management center, and establish a ring star model diagram based on the geographical location of the grid equipment; Based on the ring star model diagram, the electricity consumption data of the smart meter is obtained in real time, the electricity consumption data is sliced ​​to obtain data slices, sensitive information of the data slices is extracted and the priority of the data slices is set to obtain electricity consumption characteristic data, and the electricity consumption characteristic data is bound to the corresponding smart meter; Based on the ring star model diagram, the electricity consumption data of all smart meters within the management range of the concentrator are randomly confused and exchanged to obtain first confused data and a first exchange path, and the first confused data is transmitted to the concentrator; Based on the ring star model diagram, the first obfuscated data of all concentrators corresponding to the data management center are randomly obfuscated and exchanged again to obtain second obfuscated data and a second exchange path, and the second obfuscated data is transmitted to the data management center; Based on the second obfuscated data and the second exchange path, the data management center restores and detects the second obfuscated data to obtain the power usage data of the corresponding user, and stores the power usage data in the data management center.

2. A data management method for a smart grid according to claim 1, characterized in that: The step of establishing a ring-shaped star model diagram based on the geographical location of the power grid equipment includes: Determine the management scope of the smart grid, obtain the geographical location of the smart meter, the geographical location of the concentrator, and the geographical location of the data management center within the management scope as the geographical location of the power grid equipment, obtain the user number within the management scope, and bind the smart meter to the corresponding user number; Based on the geographical location of the power grid equipment, multiple concentrators are connected to the data management center, and the multiple concentrators are interconnected to form a loop closed circuit. The smart meters within the management range of the concentrator are connected to the corresponding concentrators, and the multiple smart meters within the management range of the corresponding concentrators are interconnected to form a loop closed circuit to obtain a ring star model diagram.

3. A data management method for a smart grid according to claim 1, characterized in that: The steps of acquiring the electricity consumption data of the smart meter in real time based on the ring-shaped star model diagram, slicing the electricity consumption data to obtain data slices, extracting sensitive information of the data slices and setting the priority of the data slices to obtain electricity consumption feature data include: Based on the ring star model diagram, the electricity consumption data of the corresponding user is obtained through the smart meter, the electricity consumption data includes the electricity consumption and the corresponding electricity consumption time period, a hash value corresponding to the electricity consumption data is generated, and the hash value is bound to the electricity consumption data of the corresponding smart meter; Slice the electricity consumption data of multiple smart meters corresponding to the management range of the concentrator according to a preset amount to obtain a number of data slices of equal amount, and number the storage locations of the smart meters and the data slices; Extract data pieces with sensitive information from the electricity usage data and mark them as high priority to obtain electricity usage feature data, wherein the sensitive information includes electricity usage values ​​and electricity usage time period values, and bind the electricity usage feature data to the corresponding smart meter.

4. A data management method for a smart grid according to claim 1, characterized in that: The step of randomly mixing and exchanging the electricity consumption data of all smart meters within the management range of the concentrator based on the ring-shaped star model diagram to obtain first mixed data and a first exchange path includes: Establishing a data exchange path table corresponding to the smart meters within the management range of the concentrator as a first exchange path, wherein the first exchange path includes a first data node corresponding to the number of smart meters within the management range of the concentrator, and a first pointer, and binding the first exchange path to the corresponding concentrator; Traverse all smart meters within the management range of all concentrators and take the currently traversed smart meter as the target meter, take the smart meter connected to the target meter as the exchange meter, randomly select two data slices in the target meter as original data slices according to the order of data slice priority from high to low, and record the target meter number and the number of the data slice storage position as the first initial number on the first data node of the first exchange path, and transmit the two data slices of the original data slice to the corresponding exchange meter respectively. The exchange meter randomly selects a data slice as the exchange data slice according to the order of data slice priority from high to low and transmits it to the target meter, and records the number of the exchange meter and the number of the exchange data slice storage position as the first exchange number on the first data node of the first exchange path, and follows the pointing of the first pointer until all first data nodes complete the storage of the first initial number and the first exchange number of the corresponding smart meter. After repeating the expected number of traversal operations, the concentrator collects the electricity consumption data of all corresponding smart meters to obtain the first obfuscated data.

5. A data management method for a smart grid according to claim 1, characterized in that: The step of randomly performing a confusion exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring-shaped star model diagram to obtain the second obfuscated data and the second exchange path comprises: Dividing the first obfuscated data in the concentrator into a plurality of data segments of equal size according to a preset amount, and numbering the storage locations of the concentrators and the data segments; Establishing a data exchange path table corresponding to the concentrator of the data management center as a second exchange path, wherein the second exchange path includes a second data node of the number of concentrators corresponding to the data management center and a second pointer, and binding the second exchange path to the data management center; Traverse all concentrators and use the currently traversed concentrator as the target concentrator, use the concentrator connected to the target concentrator as the switching concentrator, randomly select two data segments in the target concentrator as original data segments, and record the target concentrator number and the number of the data segment storage location as the second initial number on the second data node of the second switching path, respectively transmit the two data segments of the original data segment to the corresponding switching concentrator, the switching concentrator randomly selects a data segment as the switching data segment and transmits it to the target electric meter, and records the number of the switching concentrator as the second switching number on the second data node of the second switching path, and follows the direction of the second pointer until all second data nodes complete the storage of the second initial number and the second switching number of the corresponding concentrator. After repeating the traversal operation for the expected number of times, the data management center collects the data of all corresponding concentrators to obtain the second obfuscated data.

6. A data management method for a smart grid according to claim 1, characterized in that: The step of restoring the second obfuscated data based on the second obfuscated data and the second exchange path data management center and detecting to obtain the power consumption data of the corresponding user, and storing the power consumption data in the data management center includes: The second exchange path is processed in reverse order to obtain a second restoration path, and the second initial number corresponding to the second data node and the second exchange number are exchanged for data storage positions based on the second restoration path until all data segments are restored to the second initial number to obtain the first obfuscated data and the first exchange path; The first exchange path is processed in reverse order to obtain a first restoration path, and the first initial number corresponding to the first data node is exchanged with the first exchange number based on the first restoration path for the first data storage location until all data segments are restored to the first initial number to obtain the corresponding user's data to be detected; The data to be detected is detected to obtain the user's power consumption data and abnormal data, the power consumption data is stored in the data management center, and the abnormal data is resent.

7. A data management method for a smart grid as claimed in claim 6, characterized in that: The steps of detecting the data to be detected to obtain the user's power consumption data and abnormal data, storing the power consumption data in the data management center, and resending the abnormal data include: Generate a hash value of the data to be detected as a comparison hash value. If the comparison hash value is consistent with the hash value corresponding to the power consumption data, the data to be detected is determined to be the user's power consumption data; otherwise, the data to be detected is determined to be abnormal data. The user's electricity consumption data is stored in the data management center, and the data management center sends a data resend request to the smart meter corresponding to the abnormal data. After receiving the request, the smart meter resends it to the data management center through random confusion exchange and stores it.

8. A data management system for a smart grid, used to implement a data management method for a smart grid according to any one of claims 1 to 7, characterized in that: include: Establish a module for determining the management scope of the smart grid, obtaining the geographical location of the grid equipment within the management scope, wherein the geographical location of the grid equipment includes the geographical location of the smart meter, the geographical location of the concentrator, and the geographical location of the data management center, and establishing a ring star model diagram based on the geographical location of the grid equipment; A partitioning module, connected to the establishing module, is used to obtain the power consumption data of the smart meter in real time based on the ring star model diagram, slice the power consumption data to obtain data slices, extract sensitive information of the data slices and set the priority of the data slices to obtain power consumption feature data, and bind the power consumption feature data to the corresponding smart meter; A first obfuscation module is connected to the division module and is used to randomly obfuscate and exchange the electricity consumption data of all smart meters within the management range of the concentrator based on the ring star model diagram to obtain first obfuscated data and a first exchange path, and transmit the first obfuscated data to the concentrator; The second obfuscation module is connected to the first obfuscation module and is used to randomly perform obfuscation exchange on the first obfuscated data of all concentrators corresponding to the data management center based on the ring star model diagram to obtain second obfuscated data and a second exchange path, and transmit the second obfuscated data to the data management center; The storage module is connected to the second obfuscation module and is used to restore and detect the second obfuscated data based on the second obfuscated data and the second switching path data management center to obtain the power consumption data of the corresponding user, and store the power consumption data in the data management center.

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