A data management method and system for a smart grid

Abstract

The present invention relates to the field of power grid data security management, and provides a data management method and system for a smart grid. The geographical locations of power grid devices are obtained, and a ring-star model diagram is established based on the geographical locations of the power grid devices; the power consumption data is sliced into data slices based on the ring-star model diagram, and the priorities of the data slices are set; the power consumption data of all smart meters is randomly scrambled and exchanged based on the ring-star model diagram to obtain first scrambled data and a first exchange path; the first scrambled data of all concentrators is randomly scrambled and exchanged based on the ring-star model diagram to obtain second scrambled data and a second exchange path; the second scrambled data is restored and detected based on the second scrambled data and the second exchange path to obtain the power consumption data, and the power consumption data is stored in the data management center. When in use, the present invention can prevent data from being stolen during the transmission process, and ensure the integrity and consistency of the data.

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 smart grids. Background Art

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

[0003] Currently, traditional smart grids generally rely on smart meters to collect the electrical energy data of civil electricity. To transmit the data to the data management center of the smart grid, generally, concentrators are used to collect the data of smart meters within a preset range, and then multiple concentrators are connected to the data management center to form a star topology structure for data transmission. This data topology structure has a large number of individual data channels, which increases the risk of data on the transmission channels being hacked by hackers. Once the data is illegally obtained, the privacy of users may be leaked, thus triggering a series of security problems and making 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 smart grids to solve the deficiencies in the background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A data management method for smart grids, including the following steps:

[0006] Determine the management scope of the smart grid, obtain the geographical locations of grid devices within the management scope, where the geographical locations of grid devices include the geographical locations of smart meters, concentrators, and data management centers, and establish a ring-star model diagram based on the geographical locations of grid devices;

[0007] Based on the ring-star model diagram, obtain the electricity consumption data of smart meters in real time, slice the electricity consumption data to obtain data slices, extract the sensitive information of the data slices and set the data slice priorities to obtain electricity consumption feature data, and bind the electricity consumption feature data to the corresponding smart meters;

[0008] Based on the ring-star model diagram, randomly scramble and exchange the electricity consumption data of all smart meters within the management scope of the concentrator to obtain first scrambled data and a first exchange path, and transmit the first scrambled data to the concentrator;

[0009] Based on the ring-star model diagram, the first obfuscated data of all concentrators corresponding to the data management center is randomly obfuscated and exchanged again to obtain the second obfuscated data and the second exchange path, and the second obfuscated data is transmitted into the data management center;

[0010] Based on the second obfuscated data and the second exchange path, the data management center restores the second obfuscated data and performs detection to obtain the electricity consumption data of the corresponding user, and stores the electricity consumption data in the data management center.

[0011] In a preferred embodiment, the step of establishing a ring-star model diagram based on the geographical locations of grid devices includes:

[0012] Determine the management scope of the smart grid, obtain the geographical locations of smart meters, concentrators, and data management centers within the management scope as the geographical locations of grid devices, obtain the user numbers within the management scope, and bind the smart meters to the corresponding user numbers;

[0013] Based on the geographical locations of grid devices, connect multiple concentrators to the data management center, interconnect the multiple concentrators to form a loop, connect the smart meters within the management scope of the concentrator to the corresponding concentrator, and interconnect the multiple smart meters within the management scope of the corresponding concentrator to form a loop to obtain a ring-star model diagram.

[0014] In a preferred embodiment, the step of obtaining the electricity consumption data of smart meters in real time based on the ring-star model diagram, slicing the electricity consumption data to obtain data slices, extracting the sensitive information of the data slices and setting the data slice priorities to obtain electricity consumption characteristic data includes:

[0015] Based on the ring-star model diagram, obtain the electricity consumption data of the corresponding user through the smart meter. The electricity consumption data includes the electricity consumption and the corresponding electricity consumption time period, generate a hash value corresponding to the electricity consumption data, and bind the hash value to the electricity consumption data of the corresponding smart meter;

[0016] Slice the electricity consumption data of multiple corresponding smart meters within the management scope of the concentrator according to a preset quantity to obtain a number of equal-sized data slices, and number the storage locations of the smart meters and the data slices;

[0017] Extract the data slices with sensitive information in the electricity consumption data and mark them as high priority to obtain electricity consumption characteristic data. The sensitive information includes the electricity consumption value and the electricity consumption time period value, and bind the electricity consumption characteristic data to the corresponding smart meter.

[0018] In a preferred embodiment, the step of randomly obfuscating and exchanging the electricity consumption data of all smart meters within the management scope of the concentrator based on the ring-star model diagram to obtain the first obfuscated data and the first exchange path includes:

[0019] Establish a data exchange path table corresponding to the smart meters within the concentrator management scope as the first exchange path. The first exchange path includes first data nodes corresponding to the number of smart meters within the concentrator management scope, a first pointer, and bind the first exchange path to the corresponding concentrator.

[0020] Traverse all the smart meters within the management scope of all concentrators and use the currently traversed smart meter as the target meter. Use the smart meters connected to the target meter as the exchange meters. Randomly select two data slices within the target meter as the original data slices in the order of decreasing data slice priority, and record the target meter number and the number of the data slice storage location on the first data node of the first exchange path as the first initial number. Transmit the two data slices of the original data slice to the corresponding exchange meters respectively. The exchange meters randomly select a data slice as the exchange data slice according to the order of decreasing data slice priority and transmit it to the target meter. Record the number of the exchange meter and the number of the storage location of the exchange data slice on the first data node of the first exchange path as the first exchange number. Follow the direction of the first pointer until all the first data nodes have completed the storage of the first initial number and the first exchange number corresponding to the smart meters. After repeating the traversal operation for the expected number of times, the concentrator collects the power consumption data of all the corresponding smart meters to obtain the first confused data.

[0021] In a preferred embodiment, the step of randomly confusing and exchanging the first confused data of all the concentrators corresponding to the data management center based on the ring-star model diagram to obtain the second confused data and the second exchange path includes:

[0022] Divide the first confused data in the concentrator into several equal data segments according to a preset amount, and number the concentrators and the storage locations of the data segments.

[0023] Establish a data exchange path table for the concentrators corresponding to the data management center as the second exchange path. The second exchange path includes second data nodes corresponding to the number of concentrators corresponding to the data management center, a second pointer, and bind the second exchange path to the data management center.

[0024] Traverse all concentrators and use the currently traversed concentrator as the target concentrator. Use the concentrators connected to the target concentrator as the switching concentrators. Randomly select two data segments within the target concentrator as the 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. Transmit the two data segments of the original data segments to the corresponding switching concentrators respectively. The switching concentrator randomly selects a data segment as the switching data segment and transmits it to the target electric meter. Record the number of the switching concentrator as the second switching number on the second data node of the second switching path. Follow the direction of the second pointer until all second data nodes have completed the storage of the second initial number and the second switching number corresponding to the 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.

[0025] In a preferred embodiment, the step of the data management center restoring and detecting the second obfuscated data based on the second obfuscated data and the second switching path to obtain the electricity consumption data of the corresponding user and storing the electricity consumption data into the data management center includes:

[0026] Perform reverse order processing on the second switching path to obtain the second restoration path. Based on the second restoration path, exchange the data storage positions of the second initial number and the second switching number corresponding to the second data node until all data segments are restored to the second initial number to obtain the first obfuscated data and the first switching path;

[0027] Perform reverse order processing on the first switching path to obtain the first restoration path. Based on the first restoration path, exchange the data storage positions of the first initial number and the first switching number corresponding to the first data node until all data segments are restored to the first initial number to obtain the data to be detected corresponding to the user;

[0028] Detect the data to be detected to obtain the electricity consumption data and abnormal data of the user. Store the electricity consumption data into the data management center and resend the abnormal data.

[0029] In a preferred embodiment, the step of detecting the data to be detected to obtain the electricity consumption data and abnormal data of the user, storing the electricity consumption data into the data management center, and resending the abnormal data includes:

[0030] Generate the hash value of the data to be detected as the comparison hash value. If the comparison hash value is consistent with the hash value corresponding to the electricity consumption data, determine the data to be detected as the electricity consumption data of the user; otherwise, determine the data to be detected as abnormal data;

[0031] Store the user's electricity consumption data 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 obfuscation exchange and stores it.

[0032] The present invention also provides a data management system for a smart grid, including:

[0033] A building module, used to determine the management scope of the smart grid, obtain the geographical locations of grid devices within the management scope, where the geographical locations of grid devices include the geographical locations of smart meters, concentrators, and data management centers, and establish a ring-star model diagram based on the geographical locations of grid devices;

[0034] A partitioning module, connected to the building module, used to obtain the electricity consumption data of smart meters in real time based on the ring-star model diagram, slice the electricity consumption data to obtain data slices, extract the sensitive information of the data slices and set the data slice priorities to obtain electricity consumption feature data, and bind the electricity consumption feature data to the corresponding smart meters;

[0035] A first obfuscation module, connected to the partitioning module, used to perform random obfuscation exchange on the electricity consumption data of all smart meters within the management scope 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;

[0036] A second obfuscation module, connected to the first obfuscation module, used to perform random obfuscation exchange on the first obfuscated data of all concentrators corresponding to the data management center again 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;

[0037] A storage module, connected to the second obfuscation module, used to restore and detect the second obfuscated data by the data management center based on the second obfuscated data and the second exchange path data to obtain the electricity consumption data of the corresponding user, and store the electricity consumption data in the data management center.

[0038] In the above technical solution, the technical effects and advantages provided by the present invention:

[0039] The present invention can improve the traditional star topology structure into a ring-star topology structure. Through the random obfuscation exchange technology, it solves the problem that the traditional star topology structure has a large number of single data channels, resulting in data being stolen on the transmission channel, can better protect the user's electricity consumption privacy data, and enhances the security and integrity of the data. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments described in the present invention. For those of ordinary skill in the art, other accompanying drawings can also be obtained based on these drawings.

[0041] Figure 1 It is the method flow chart of the present invention.

[0042] Figure 2 It is the system block diagram of the present invention. Detailed implementation manners

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0044] Embodiment 1. Please refer to Figure 1 As shown, a data management method for a smart grid in this embodiment includes the following steps:

[0045] S1. Determine the management scope of the smart grid, obtain the geographical locations of grid devices within the management scope. The geographical locations of the grid devices include the geographical locations of smart meters, concentrators, and data management centers. Based on the geographical locations of the grid devices, establish a ring-star model diagram;

[0046] S2. Based on the ring-star model diagram, obtain the power consumption data of smart meters in real time, slice the power consumption data to obtain data slices, extract the sensitive information of the data slices and set the data slice priorities to obtain power consumption characteristic data, and bind the power consumption characteristic data to the corresponding smart meters;

[0047] S3. Based on the ring-star model diagram, randomly scramble and exchange the power consumption data of all smart meters within the management scope of the concentrator to obtain first scrambled data and a first exchange path, and transmit the first scrambled data to the concentrator;

[0048] S4. Based on the ring-star model diagram, randomly scramble and exchange the first scrambled data of all concentrators corresponding to the data management center again to obtain second scrambled data and a second exchange path, and transmit the second scrambled data to the data management center;

[0049] S5. Based on the second obfuscated data and the second exchange path data, the data management center restores the second obfuscated data and performs detection to obtain the power consumption data of the corresponding user, and stores the power consumption data into the data management center;

[0050] As described in the above steps S1 - S5, currently, traditional smart grids generally rely on smart meters to collect the electrical energy data of civil electricity. To transmit the data to the data management center of the smart grid, the smart meters generally collect the data of the smart meters within a preset range through concentrators, and then connect multiple concentrators to the data management center to form a star - shaped topology for data transmission. This data topology has a large number of individual data channels, which increases the risk of data being hacked on the transmission channels. Once the data is illegally obtained, the privacy of users may be leaked, leading to a series of security problems and making it difficult to meet the high requirements of modern smart grids for secure data transmission. However, this application can improve the traditional star - shaped topology to a ring - star topology. By using the random obfuscation and exchange technology, it solves the problem that the traditional star - shaped topology has a large number of individual data channels, resulting in data being stolen on the transmission channels, and can better protect the power consumption privacy data of users, enhancing the security and integrity of the data;

[0051] In one embodiment, step S1 of establishing a ring - star model diagram based on the geographical locations of grid devices includes:

[0052] S11. Determine the management scope of the smart grid, obtain the geographical locations of smart meters, concentrators, and data management centers within the management scope as the geographical locations of grid devices, obtain the user numbers within the management scope, and bind the smart meters with the corresponding user numbers;

[0053] S12. Connect multiple concentrators to the data management center based on the geographical locations of grid devices, interconnect multiple concentrators to form a circular closed - loop, connect the smart meters within the management scope of each concentrator to the corresponding concentrator, and interconnect the multiple smart meters within the management scope of the corresponding concentrator to form a circular closed - loop to obtain a ring - star model diagram;

[0054] As described in the above steps S11 - S12, first determine the management scope of the smart grid. Collect the geographical locations of smart meters, concentrators, and data management centers within the management scope as the geographical locations of grid devices. Here, the smart meters are used to collect users' electricity consumption data, the concentrators are used to integrate the data of smart meters within the management scope of the concentrators, and the data management centers are used to store the integrated smart meter data of the concentrators. Collect the user numbers within the management scope, bind the smart meters with the corresponding user numbers, then connect multiple concentrators to the data management center based on the geographical locations of grid devices, and then interconnect the multiple concentrators to form a closed loop without a starting point or an ending point. Set the management scope of the concentrators, connect the smart meters within the management scope of the concentrators to the corresponding concentrators, and interconnect the multiple smart meters within the management scope of the corresponding concentrators to form a closed loop without a starting point or an ending point to obtain a ring - star model diagram, which can optimize the traditional star - type topology structure, increase the transmission routes of peer nodes, facilitate data exchange between peer nodes, solve the problem of a large number of single - body data channels existing in the traditional star - type topology structure, and play an auxiliary role in subsequent random confusion exchange operations;

[0055] In one embodiment, step S2 of obtaining the electricity consumption data of the smart meter in real - time based on the ring - star model diagram, fragmenting the electricity consumption data to obtain data fragments, extracting the sensitive information of the data fragments and setting the data fragment priorities to obtain the electricity consumption characteristic data includes:

[0056] S21. Obtain the electricity consumption data of the corresponding user through the smart meter based on the ring - star model diagram. The electricity consumption data includes the electricity consumption amount and the corresponding electricity consumption time period, generate the hash value corresponding to the electricity consumption data, and bind the hash value with the electricity consumption data of the corresponding smart meter;

[0057] S22. Fragment the electricity consumption data of multiple corresponding smart meters within the management scope of the concentrator according to a preset quantity to obtain a number of equal - amount data fragments, and number the storage locations of the smart meters and the data fragments;

[0058] S23. Extract the data fragments with sensitive information in the electricity consumption data and mark them as high - priority to obtain the electricity consumption characteristic data. The sensitive information includes the electricity consumption amount value and the electricity consumption time period value, and bind the electricity consumption characteristic data with the corresponding smart meter;

[0059] 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 smart meters as power consumption data based on the corresponding power consumption time period, and then the hash value of the power consumption data is generated. Here, the hash value can generate a hash value of a fixed length through the SHA - 256 hash algorithm, which is used to uniquely determine the power consumption data of the corresponding user and prepare for subsequent detection of data integrity. Then, the hash value is bound to the corresponding power consumption data. The power consumption data of multiple smart meters within the management range of the concentrator is sharded according to a preset quantity to obtain several equal - volume data slices. Then, the storage locations of the smart meters and the data slices are numbered. For example, if the preset quantity is 10B and the data volume of one smart meter is 10MB, then the power consumption data of this smart meter is divided into 10M data slices, and the 10M data slices are numbered. The smart meters within the management range of the concentrator are numbered to obtain a unique number for each data slice. For example, B0001P0001 represents the data slice numbered P0001 corresponding to the smart meter numbered D0001. Here, the probability of the high - priority data slice being selected in subsequent random scrambling and exchange increases. The priority decreases from high to low. Identify the specific value of the power consumption of the power consumption data and the specific value of the corresponding power consumption time period and mark them as power consumption characteristic data. Finally, set the priority. For example, the power consumption in the power consumption data of one smart meter is 100Kwh, and the power consumption time period is 00:00 - 19:00. Mark 100, 00, 00, 19, 00 as power consumption characteristic data. Set the priority of the data slice corresponding to the power consumption characteristic data to the highest. Bind the power consumption characteristic data to the corresponding smart meter, which is used to collect the user's power consumption data in real - time, generate the 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 scrambling and exchange;

[0060] In one embodiment, step S3 of randomly scrambling and exchanging the power consumption data of all smart meters within the management range of the concentrator based on the ring - star model diagram to obtain the first scrambled data and the first exchange path includes:

[0061] S31. Establish a data exchange path table corresponding to the smart meters within the management range of the concentrator as the first exchange path. The first exchange path includes a first data node corresponding to the number of smart meters within the management range of the concentrator, a first pointer, and bind the first exchange path to the corresponding concentrator;

[0062] S32. Traverse all smart meters within the management scope of the concentrator and use the currently traversed smart meter as the target meter. Use the smart meters connected to the target meter as the exchange meters. Randomly select two data slices in the target meter as the original data slices according to the order of data slice priorities from high to low. Record the target meter number and the number of the data slice storage location on the first data node of the first exchange path as the first initial number. Transmit the two data slices of the original data slice to the corresponding exchange meters respectively. The exchange meters randomly select a data slice as the exchange data slice according to the order of data slice priorities from high to low and transmit it to the target meter. Record the exchange meter number and the number of the storage location of the exchange data slice on the first data node of the first exchange path as the first exchange number. Follow the direction of the first pointer until all first data nodes have completed the storage of the first initial number and the first exchange number of the corresponding smart meters. After repeating the traversal operation for the expected number of times, the concentrator collects the electricity consumption data of all corresponding smart meters to obtain the first obfuscated data;

[0063] As described in the above steps S31 - S32, first, establish a data exchange path within the scope of the concentrator management corresponding to the smart meters, which is marked as the first exchange path. The first exchange path is used to record the destination of the data slices after the exchange, facilitating the subsequent data management center to integrate 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 scope of the concentrator management, and a first pointer. Bind the first exchange path to the corresponding concentrator. The first data node is used to record the exchanged data slices in the smart meters, and the first pointer 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. Then, traverse all the smart meters within the scope of the concentrator management and use the currently traversed smart meter as the target meter, and use the smart meters connected to the target meter as the exchange meters. There are two exchange meters here. Then, the target meter randomly selects two data slices within the target meter according to the priority from high to low and marks them as the original data slices. Record the target meter number and the number of the data slice storage location on the first data node of the first exchange path as the first initial number. Transmit the two data slices of the original data slices to the corresponding exchange meters respectively. Each 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 exchange meter number and the number of the exchange data slice on the first data node of the first exchange path as the first exchange number. Then, use the first pointer to point the first initial number to the first exchange number to identify the direction of the data slice. Then, according to the direction pointed by the first pointer until all the first data nodes have completed the storage of the first initial number and the first exchange number corresponding to the smart meters, repeat the operation of traversing all the smart meters within the scope of the concentrator management for a preset number of times. When the same first initial number appears, point the last first exchange number with 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, if the preset repeated traversal operation is 2 times, the first data node obtained from the first traversal of a certain target meter is D0001P0001 pointing to D0002P0001, and the first data node obtained from the second traversal of the target meter is D0001P0001 pointing to D0055P0055, then modify the first data node to D0001P0001 pointing to D0002P0001 pointing to D0055P0055. The concentrator collects the power consumption data of all the corresponding smart meters and integrates them to obtain the first obfuscated data and the first exchange path, which are used to securely desensitize the key data and transmit it to the third - party meter, and then transmit the data, which can better protect the data privacy of the corresponding users and enhance the security and integrity of the data;

[0064] In one embodiment, step S4 of obtaining the second obfuscated data and the second exchange path by randomly obfuscating and exchanging the first obfuscated data of all concentrators corresponding to the data management center based on the ring-star model diagram includes:

[0065] S41. Divide the first obfuscated data in the concentrator into a number of equal data segments according to a preset quantity, and number the concentrators and the storage locations of the data segments;

[0066] S42. Establish a data exchange path table for the concentrators corresponding to the data management center as the second exchange path. The second exchange path includes second data nodes corresponding to the number of concentrators in the data management center, a second pointer, and bind the second exchange path to the data management center;

[0067] S43. Traverse all concentrators and use the currently traversed concentrator as the target concentrator, use the concentrator connected to the target concentrator as the exchange concentrator, randomly select two data segments in the target concentrator as the original data segments, and record the target concentrator number and the number of the storage location of the data segment as the second initial number on the second data node of the second exchange path. Transmit the two data segments of the original data segment to the corresponding exchange concentrators respectively. The exchange concentrator randomly selects a data segment as the exchange data segment and transmits it to the target electricity meter, and records the number of the exchange concentrator as the second exchange number on the second data node of the second exchange path. According to the direction pointed by the second pointer, until all second data nodes have completed the storage of the second initial number and the second exchange number corresponding to the concentrators, 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;

[0068] As described in the above steps S41 - S43, first, divide the first obfuscated data in the concentrator into several data segments according to a preset amount, and number the concentrator and the corresponding data segments. For example, the first obfuscated data in a certain concentrator is 1GB, and 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. Establish a data exchange path table of the data management center corresponding to the concentrator as the second exchange path. The second exchange path here is used to record the destination of the data segments after exchange, so that the data management center can perform data integration according to the second exchange path later. The second exchange path includes the second data nodes corresponding to the number of concentrators in the data management center, and the second pointer. Bind the second exchange path to the data management center. The second data nodes here are used to record the exchanged data segments in the concentrator, and the second pointer is used to mark the destination relationship of each data segment in the second data nodes. One concentrator corresponds to one second data node. Then traverse all concentrators and use the currently traversed concentrator as the target concentrator, and use the concentrators connected to the target concentrator as the exchange concentrators. There are two exchange concentrators here, and they have a one-to-one relationship with the target concentrator. Randomly select two data segments in the target concentrator as the original data segments, and record the concentrator number and the number of the data segment storage location on the second data node of the second exchange path as the second initial number. Transmit the two data segments of the original data segments to the corresponding exchange concentrators respectively. The exchange concentrator randomly selects a data segment as the exchange data segment and transmits it to the target electric meter. Record the number of the exchange concentrator on the second data node of the second exchange path as the second exchange number. Then use the second pointer to point the second initial number to the second exchange number to identify the direction of the data segment. Then, according to the direction pointed by the second pointer, until all second data nodes have completed the storage of the second initial number and the second exchange number corresponding to the concentrator, repeat the operation of traversing all concentrators for the expected number of times. When the same second initial number appears, point the last second exchange number with the same second initial number in the second data node corresponding to the current target concentrator to the current second exchange number through the second pointer. Finally, the data management center collects the data of all corresponding concentrators and integrates them to obtain the second obfuscated data and the second exchange path, which are used to obfuscate and exchange 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 single data channels in the traditional star topology structure lead to data being stolen on the transmission channel;

[0069] In one embodiment, step S5 of the data management center restoring the second obfuscated data and performing detection to obtain the electricity consumption data of the corresponding user and storing the electricity consumption data in the data management center includes:

[0070] S51. Reverse the second exchange path to obtain a second restoration path. Based on the second restoration path, exchange the data storage positions of the second initial number corresponding to the second data node and the second exchange number until all data segments are restored to the second initial number, obtaining the first obfuscated data and the first exchange path;

[0071] S52. Reverse the first exchange path to obtain a first restoration path. Based on the first restoration path, exchange the data storage positions of the first initial number corresponding to the first data node and the first exchange number until all data segments are restored to the first initial number, obtaining the data to be detected for the corresponding user;

[0072] S53. Detect the data to be detected to obtain the user's power consumption data and abnormal data. Store the power consumption data in the data management center and resend the abnormal data;

[0073] In one embodiment, 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 resending the abnormal data includes:

[0074] S531. 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, determine that the data to be detected is the user's power consumption data; otherwise, determine that the data to be detected is abnormal data;

[0075] S532. Store the user's power consumption data in the data management center. 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 obfuscation exchange and stores it;

[0076] As described in the above steps S51 - S53, first, reverse the second exchange path to obtain the second restoration path. Based on the second restoration path, exchange the data storage positions of the second initial number corresponding to the second data node and the second exchange number 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 certain second data node in the second exchange path is J0001D0001 pointing to J0002D0002 pointing to J0003D0003. After reverse processing, it becomes J0003D0003 pointing to J0002D0002 pointing to J0001D0001. Then, exchange the data segments corresponding to J0003D0003 and J0002D0002, and then exchange the data segments corresponding to J0002D0002 and J0001D0001 to obtain the first obfuscated data and the first exchange path. Then, reverse the first exchange path to obtain the first restoration path. Based on the first restoration path, exchange the data storage positions of the first initial number corresponding to the first data node and the first exchange number until all data segments are restored to the first initial number to obtain the data to be detected for the corresponding user. For example, a certain first data node in the first exchange path is D0001P0001 pointing to D0002P0002 pointing to D0003P0003. After reverse processing, it becomes D0003P0003 pointing to D0002P0002 pointing to D0001P0001. Then, exchange the data segments corresponding to D0003P0003 and D0002P0002, and then exchange the data segments corresponding to D0002P0002 and D0001P0001 to obtain the data to be detected. Then, generate the hash value of the data to be detected as the comparison hash value. If the comparison hash value is consistent with the hash value corresponding to the electricity consumption data, then determine the data to be detected as the user's electricity consumption data; otherwise, determine the data to be detected as abnormal data. For example, if the hash value corresponding to the data to be detected of a certain user is 4799BCec4036D2B5, and if the generated hash value of the data to be detected of this user is 07B64142D767CaF8, then it is determined as abnormal data; if the generated hash value of the data to be detected of this user is 4799BCec4036D2B5, then it is determined as the electricity consumption data of the corresponding user. Finally, store the user's electricity consumption data in the data management center. The data management center sends a data re - transmission request to the smart meter corresponding to the abnormal data. After receiving the request, the smart meter re - transmits it to the data management center through random obfuscation exchange and stores it, which is used to restore the second obfuscated data and the first obfuscated data according to the second exchange path and the first exchange path respectively to obtain the user's electricity consumption data, which can better enhance the protection of user data privacy and has the functions of maintaining data utility and improving system security;

[0077] Example 2. Refer to Figure 2 As shown in the figure, a data management system for a smart grid in this embodiment includes:

[0078] A building module, configured to determine the management scope of the smart grid, obtain the geographical locations of grid devices within the management scope, where the geographical locations of grid devices include the geographical locations of smart meters, concentrators, and data management centers, and establish a ring-star model diagram based on the geographical locations of grid devices;

[0079] A partitioning module, connected to the building module, configured to obtain the power consumption data of smart meters in real time based on the ring-star model diagram, slice the power consumption data to obtain data slices, extract the sensitive information of the data slices and set the data slice priorities to obtain power consumption feature data, and bind the power consumption feature data to the corresponding smart meters;

[0080] A first obfuscation module, connected to the partitioning module, configured to randomly obfuscate and exchange the power consumption data of all smart meters within the management scope 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;

[0081] A second obfuscation module, connected to the first obfuscation module, configured to randomly obfuscate and exchange the first obfuscated data of all concentrators corresponding to the data management center again 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;

[0082] A storage module, connected to the second obfuscation module, configured to restore the second obfuscated data based on the second obfuscated data and the second exchange path data management center and perform detection to obtain the power consumption data of the corresponding user, and store the power consumption data in the data management center.

[0083] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to 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; 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, multiple concentrators are interconnected to form a closed loop, smart meters within the management range of the concentrator are connected to the corresponding concentrator, and multiple smart meters within the management range of the corresponding concentrator are interconnected to form a closed loop to obtain a ring star model diagram; 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; 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 use the currently traversed smart meter as the target meter, use 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, 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 position 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; 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 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.

3. 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.

4. 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.

5. A data management method for a smart grid as claimed in claim 4, 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.

6. 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 5, 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.

Images