Power grid system data processing storage method

Abstract

The invention discloses a power grid system data processing and storage method, which comprises the following steps of: acquiring all data transmission paths of a total power grid system, and comprehensively collecting regions of which data is to be collected; a plurality of different electrode energy efficiency links are divided according to the difference values of the electric energy data of all the data transmission paths, and the data of different lines are different, so that the subsequent improvement of the calculation capability is facilitated; a plurality of data management nodes are arranged in the multiple electrode energy efficiency links, and distributed storage is achieved through the data management nodes; and the data management node divides data in the electrode energy efficiency link into different blocks for storage by adopting a data partitioning technology, and queries, reads and writes in the different blocks, so that the calculation power and the storage capacity are adjusted according to actual requirements, the elasticity and the expandability of the power grid data are effectively improved, and the data management efficiency is improved. And scale increase and diversified power distribution use of power grid data are fully dealt with.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid data, and in particular to a method for processing and storing power grid system data. Background Art

[0002] The grid system is an important part of the power system, which is responsible for transmitting and distributing the electricity generated by power plants to end users. In this process, the data collection and application of the grid system are aimed at ensuring the efficient operation of the power system and the optimal allocation of power resources. For example, in the existing technology, smart meter sensors and SCADA systems are used to collect power voltage, current and environmental value data in real time. These data are transmitted to the central processor of the grid system through wireless transmission carriers and stored in the database for stable storage. Subsequently, machine learning algorithms are used to conduct in-depth analysis of the data to predict load changes, detect abnormal conditions and perform fault diagnosis.

[0003] Grid data is the core data of the grid system. In order to prevent data loss, data is usually stored to ensure data security. However, the above-mentioned data storage processing method still has the following defects: 1. Due to the large-scale growth of grid data and the different levels of electricity use in different regions, there is a diversified distribution and use situation. Traditional relational databases cannot match different computing and storage capabilities according to the actual electricity use, resulting in the inability to achieve fast resolution speed and efficiency in reading, writing and large-scale data query; 2. Grid data generated in multiple regions and departments of the grid system often need to be stored centrally, but the existing regional sharing capabilities of grid data are poor, and the delay is serious, thereby reducing the overall utilization efficiency of grid data; 3. The protection mechanism of sensitive information involved in the existing grid data is poor, and the ability to deal with data leakage and attack risks is insufficient. Summary of the invention

[0004] The purpose of the present invention is to provide a data processing and storage method for a power grid system, which adjusts computing power and storage capacity according to actual needs, effectively improves the elasticity and scalability of power grid data, and fully copes with the growth in scale and diversified distribution of power grid data.

[0005] The technical solution of the present invention is achieved in this way:

[0006] A method for processing and reserving data in a power grid system, the method comprising the following steps:

[0007] Step S1: Acquire all data transmission paths of the total power grid system;

[0008] Step S2: dividing the power data of all the data transmission paths into a plurality of different electrical energy efficiency links according to the difference values ​​of the power data;

[0009] Step S3: respectively setting a plurality of data management nodes in a plurality of the electrical level energy efficiency links;

[0010] Step S4: the data management node uses data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage.

[0011] A further technical solution is that in step S1, all data transmission paths of the total power grid system are obtained, which specifically includes the following steps:

[0012] Step S101: calculating sub-data transmission paths corresponding to sub-grid systems in multiple areas;

[0013] Step S102: classifying and marking the sub-data transmission paths using a dimension table;

[0014] Step S103: classifying and counting the sub-data transmission paths that have been classified and marked, and generating different target numbers for different sub-data transmission paths;

[0015] Step S104: The sub-data transmission paths corresponding to all the target numbers are integrated into a total set for unified management.

[0016] A further technical solution is that the target number includes identification information of multiple departments in the region that manage the sub-data transmission path;

[0017] The department identification information includes the department's social credit code, name, and geographic location.

[0018] A further technical solution is that the multiple departments build data sharing platforms respectively, and the steps of building the data sharing platform are as follows:

[0019] Step S111: creating a sub-storage unit, and collecting the electric energy data of the sub-data transmission path and storing it in the storage unit;

[0020] Step S112: the storage unit compresses the electric energy data and deletes duplicate data to obtain net electric energy data;

[0021] Step S113: Virtualizing the sensitive information in the net electric energy data to obtain virtual data;

[0022] Step S114: each department generates a unique key through unified coordination to unlock the virtual data and obtain the real net power data;

[0023] Step S115: interconnecting the real net electric energy data among the departments.

[0024] A further technical solution is that, in step S2, all the data transmission paths are divided into a plurality of different electric energy efficiency links according to the difference values ​​of the electric energy data, which specifically includes the following steps:

[0025] Step S201: dividing the difference value into a first difference value, a second difference value, a third difference value and a fourth difference value;

[0026] Step S202: assigning the electrode energy efficiency link to a first electrode energy efficiency link, a second electrode energy efficiency link, a third electrode energy efficiency link and a fourth electrode energy efficiency link according to the first difference, the second difference, the third difference and the fourth difference;

[0027] Step S203: Analyze the loads of the first electrical level energy efficiency link, the second electrical level energy efficiency link, the third electrical level energy efficiency link, and the fourth electrical level energy efficiency link to obtain a first load, a second load, a third load, and a fourth load.

[0028] The load is analyzed using the following formula:

[0029] P 计算 =∑(P i ×K i )+K c ×(P 总安装 -P i )

[0030] Among them, P 计算 is the calculated load; P i is the capacity of the i-th electrical equipment; K i is the required coefficient of the i-th electrical equipment; Kc is the constant term coefficient; P 总安装 is the total installed capacity of electrical equipment in the data transmission path.

[0031] A further technical solution is that in step S3, a plurality of data management nodes are respectively set in a plurality of the electrical level energy efficiency links, specifically comprising the following steps:

[0032] Step S301: respectively set the first electrode energy efficiency link, the second electrode energy efficiency link, the third electrode energy efficiency link and the fourth electrode energy efficiency link to correspond to the first subnode, the second subnode, the third subnode and the fourth subnode;

[0033] Step S302: The first sub-node, the second sub-node, the third sub-node and the fourth sub-node are integrated into the data management node.

[0034] A further technical solution is that the data management node further includes: a payment module, and the steps of building the payment module are as follows:

[0035] Step S311: Developing a user interactive payment framework and an interactive interface connected to the payment framework;

[0036] Step S312: creating a user authentication port and a payment interface in the payment architecture, wherein the user authentication port and the payment interface are interconnected with the interactive interface;

[0037] Step S313: creating a user-defined payment amount port in the payment interface, and interconnecting the customized payment amount port with the interactive interface;

[0038] Step S314: Create login encryption data at the user authentication port, and customize the payment amount using the key corresponding to the encryption data.

[0039] A further technical solution is that the encrypted data includes:

[0040] Collect user identity information, biometric information and obscured facial features, generate a first authentication port based on the user identity information, biometric information and obscured facial features, generate a second authentication port based on the first authentication port, and the second authentication port includes a voucher code generated by verifying the interactive payment architecture.

[0041] A further technical solution is that in step S4, the data management node uses data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage, which specifically includes the following steps:

[0042] Step S401: creating a first data storage block, a second data storage block, a third data storage block and a fourth data storage block in the data management node;

[0043] Step S402: the first sub-node, the second sub-node, the third sub-node and the fourth sub-node are correspondingly allocated to the first data storage block, the second data storage block, the third data storage block and the fourth data storage block.

[0044] A further technical solution is that the first data storage block, the second data storage block, the third data storage block and the fourth data storage block are correspondingly provided with a first snapshot copy, a second snapshot copy, a third snapshot copy and a fourth snapshot copy, and the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy all have metadata, and the metadata includes data received and recorded by the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy.

[0045] The beneficial effects of the present invention are:

[0046] 1. By acquiring all the data transmission paths of the total power grid system, the areas where data is to be collected are comprehensively collected; the data is divided into multiple different power-level energy efficiency links according to the difference values ​​of the electric energy data of all the data transmission paths, and the data of different lines are different, so as to facilitate the subsequent improvement of computing power; multiple data management nodes are respectively set in multiple power-level energy efficiency links, and distributed storage is realized through data management nodes; the data management nodes use data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage, and query and read and write in different blocks, so as to adjust the computing power and storage capacity according to actual needs, effectively improve the elasticity and scalability of power grid data, and fully cope with the growth in scale and diversified distribution of power grid data.

[0047] 2. Build a data sharing platform, authorize trusted departments to interconnect and realize book data sharing, facilitate subsequent data analysis, and improve industry comparative analysis capabilities.

[0048] 3. Distributed sub-node storage improves the protection mechanism of sensitive information related to power grid data and effectively responds to data leakage and attack risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is the overall flow chart of the present invention;

[0050] Figure 2 is a flow chart of the method in S1 of the present invention;

[0051] Figure 3 is a flow chart of the method in S101;

[0052] Figure 4 is a flow chart of the method in S2 of the present invention;

[0053] Figure 5 is a flow chart of the method in S3 of the present invention;

[0054] Figure 6 A flow chart of the method for building a payment module;

[0055] Figure 7 This is a flow chart of the method in S4 of the present invention. DETAILED DESCRIPTION

[0056] In order to better understand the technical content of the present invention, specific embodiments are provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0057] In order to address the deficiencies of the background technology, the present invention provides a method for processing and reserving data in a power grid system. The present invention obtains all data transmission paths of the total power grid system to comprehensively collect areas where data is to be collected; the data is divided into a plurality of different power-level energy efficiency links according to the difference values ​​of the electric energy data of all the data transmission paths, and the data of different lines are different, so as to facilitate the subsequent improvement of computing power; a plurality of data management nodes are respectively set in the plurality of the power-level energy efficiency links, and distributed storage is realized through the data management nodes; the data management nodes use data partitioning technology to divide the data in the power-level energy efficiency links into different blocks for storage, and query and read and write in different blocks, so as to adjust the computing power and storage capacity according to actual needs, effectively improve the elasticity and scalability of power grid data, and fully cope with the growth in scale and diversified distribution of power grid data.

[0058] An implementation method provided by the present invention includes step S1: acquiring all data transmission paths of the total power grid system.

[0059] Specifically, the following steps are included: Step S101: Calculate the sub-data transmission paths corresponding to the sub-grid systems in multiple regions; Step S102: Classify and mark the sub-data transmission paths using a dimension table; Step S103: Classify and count the sub-data transmission paths that have been classified and marked, and generate different target numbers for different sub-data transmission paths; Step S104: Collect the sub-data transmission paths corresponding to all the target numbers into a total set for unified management. The target number includes identification information of multiple departments in the region that manage the sub-data transmission paths; the department identification information includes the social credit code, name and geographic location of the department.

[0060] Multiple regions include a jurisdiction divided into multiple subordinate areas, and the circuit power grids of these areas are uniformly managed by the power grid bureau. The sub-grid system is the power grid system of each subordinate area. The sub-grid system contains multiple lines, which are sub-data transmission paths. The sub-data transmission paths corresponding to the sub-grid systems in multiple subordinate areas are calculated by statistical methods. Further, the dimension table is used to mark each sub-data transmission path with English letters and Arabic data for marking and confirmation, such as A1, A2, A3, A4; B1, B2, B3, B4; C1, C2, C3, C4; D1, D2, D3, D4, etc. The same English letters are classified into one category to complete the statistics. For example, in a class A set, there are lines corresponding to A1, A2, and A3 respectively. A single line corresponds to an independent target number, which is a legal unit or family or illegal organization using a room, or a construction unit, or a unit that is not registered to use power distribution, and the address where the power distribution is used. Through the above steps, the comprehensiveness of all data transmission paths of the total power grid system is improved, which is convenient for subsequent analysis and processing.

[0061] Preferably, a plurality of the departments respectively build data sharing platforms, and the steps of building the data sharing platform are as follows: Step S111: Create a sub-storage unit, and store the electric energy data collected through the sub-data transmission path in the storage unit; Step S112: The storage unit compresses the collected electric energy data and deletes duplicate data to obtain net electric energy data; Step S113: Virtualize the sensitive information in the net electric energy data to obtain virtual data; Step S114: Each of the departments generates a unique key through unified coordination to unlock the virtual data and obtain the real net electric energy data; Step S115: Interconnect the real net electric energy data among the departments.

[0062] The data sharing platform includes creating a sub-storage unit, which is a storage unit for the electric energy data of the sub-data transmission path. By storing the electric energy data of the sub-data transmission path, the initial storage of data is ensured to prevent data loss. At the same time, the initially stored electric energy data can identify and delete duplicate electric energy data using deduplication technology, further reducing the storage burden. The electric energy data that can be stored by deduplication technology is net electric energy data. Through the Denodo tool, the net electric energy data is virtualized, and the virtual data is encrypted in the storage unit. The virtual data corresponds to the department where the virtual data is located and provides a unique key to unlock the virtual data, and the net electric energy data consumed by the department is obtained through the virtual data to ensure data security. Among them, these net electric energy data are interconnected in other authorized and trusted departments to realize data sharing, which is convenient for subsequent data analysis and improves industry comparative analysis capabilities.

[0063] An implementation method provided by the present invention includes step S2: dividing the power data of all the data transmission paths into a plurality of different electrical energy efficiency links according to the difference values ​​of the power data.

[0064] Specifically, step S201: divide the difference value into a first difference, a second difference, a third difference and a fourth difference; step S202: assign the electric level energy efficiency link into a first electric level energy efficiency link, a second electric level energy efficiency link, a third electric level energy efficiency link and a fourth electric level energy efficiency link according to the first difference, the second difference, the third difference and the fourth difference; step S203: analyze the load of the first electric level energy efficiency link, the second electric level energy efficiency link, the third electric level energy efficiency link and the fourth electric level energy efficiency link to obtain the first load, the second load, the third load and the fourth load. The load adopts the following analytical formula:

[0065] P 计算 =∑(P i ×K i )+K c ×(P 总安装 -Pi )

[0066] Among them, P 计算 is the calculated load; P i is the capacity of the i-th electrical equipment; K i is the required coefficient of the i-th electrical equipment; Kc is the constant term coefficient; P 总安装 is the total installed capacity of electrical equipment in the data transmission path.

[0067] The first difference, the second difference, the third difference and the fourth difference represent the difference between A1 and B1, A2 and B2, A3 and B3, A4 and B4. These differences are used to identify the data transmission path, facilitate set statistics, and form the first electric level energy efficiency link, the second electric level energy efficiency link, the third electric level energy efficiency link and the fourth electric level energy efficiency link, wherein the electric energy data set contained in the first electric level energy efficiency link is {A1, A2, A3, A4} recorded as set A, the electric energy data set contained in the second electric level energy efficiency link is {B1, B2, B3, B4} recorded as set B, the electric energy data set contained in the third electric level energy efficiency link is {C1, C2, C3, C4} recorded as set C, and the electric energy data set contained in the fourth electric level energy efficiency link is {D1, D2, D3, D4} recorded as set D. Then, the sets A, B, C and D are assigned 15, 14, 13 and 12 respectively, which is convenient for distinguishing calculations. At the same time, the load analysis method is used to predict the consumption of electric energy data of the first-level energy efficiency link, the second-level energy efficiency link, the third-level energy efficiency link, and the fourth-level energy efficiency link, so as to make reasonable plans for future electricity consumption trends. For example, in the first-level energy efficiency link, the coefficient required for the second power-consuming equipment is 0.8, the constant term coefficient is 0.5, and the total number of installations is 10. Then the calculation of the first-level energy efficiency link is 4, which is convenient for helping to predict future power consumption and related costs.

[0068] An implementation method provided by the present invention includes step S3: setting a plurality of data management nodes in a plurality of the electrical level energy efficiency links respectively.

[0069] Specifically, step S301: respectively set the first electric level energy efficiency link, the second electric level energy efficiency link, the third electric level energy efficiency link and the fourth electric level energy efficiency link to correspond to the first sub-node, the second sub-node, the third sub-node and the fourth sub-node; step S302: integrate the first sub-node, the second sub-node, the third sub-node and the fourth sub-node into the data management node.

[0070] The data management node includes a first sub-node, a second sub-node, a third sub-node and a fourth sub-node. The first sub-node, the second sub-node, the third sub-node and the fourth sub-node can all be used to store electric energy data. The sub-nodes are distributed storage branches and are managed by the data management node. The sub-nodes improve storage capacity and facilitate users to improve data query capabilities.

[0071] Preferably, the data management node also includes: a payment module, and the steps of building the payment module are as follows: Step S311: Develop a user interactive payment architecture, and an interactive interface connected to the payment architecture; Step S312: Create a user authentication port and a payment interface in the payment architecture, and the user authentication port and the payment interface are interconnected with the interactive interface; Step S313: Create a user-defined payment amount port in the payment interface, and customize the payment amount port to be interconnected with the interactive interface; Step S314: Create login encrypted data in the user authentication port, and customize the payment amount through the key corresponding to the encrypted data.

[0072] In the data management node, a payment module for distribution users is provided. The core of the payment module is built with an interactive payment architecture. The distribution user logs in through the user authentication port of the interactive interface and enters the login encrypted data to enter the electricity purchase operation interface. In the interactive payment architecture, the distribution user initiates an electricity purchase application and inputs the purchase amount according to any of the custom payment amount ports. The user purchases appropriate electricity according to the purchase demand to enhance the user experience. At the same time, the encrypted data payment amount mentioned above is used during payment to improve the ability to make payments quickly.

[0073] Furthermore, the encrypted data includes: collecting user identity information, biometric information and obscured facial features, generating a first authentication port based on the user identity information, biometric information and obscured facial features, generating a second authentication port based on the first authentication port, and the second authentication port includes verifying the voucher code generated by the interactive payment architecture.

[0074] Among them, user identity information, biometric information and obscured facial features are collected. According to the user identity information, biometric information and obscured face, the user identity information includes ID number and mobile phone number; the biometric information includes face, fingerprint and iris; the obscured face is the feature when wearing a mask. After verification through the first authentication port, the interactive payment architecture generates a voucher code combining numbers and letters based on the information collected by the first authentication port to the smart device used by the power distribution user, and payment is made through the second authentication port according to the voucher code to improve payment security. In addition, when the device is trusted, payment is made directly through the first authentication port to improve payment convenience.

[0075] An implementation method provided by the present invention includes step S4: the data management node uses data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage.

[0076] Specifically, step S401: create a first data storage block, a second data storage block, a third data storage block and a fourth data storage block in the data management node; step S402: allocate the first sub-node, the second sub-node, the third sub-node and the fourth sub-node to the first data storage block, the second data storage block, the third data storage block and the fourth data storage block accordingly.

[0077] The first sub-node, the second sub-node, the third sub-node and the fourth sub-node are used to store electric energy data. The first data storage block, the second data storage block, the third data storage block and the fourth data storage block are used to back up the first sub-node, the second sub-node, the third sub-node and the fourth sub-node to store electric energy data to prevent data loss due to power grid system failure and inability to recover.

[0078] Preferably, the first data storage block, the second data storage block, the third data storage block and the fourth data storage block are correspondingly provided with a first snapshot copy, a second snapshot copy, a third snapshot copy and a fourth snapshot copy, and the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy all have metadata, and the metadata includes data received and recorded by the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy.

[0079] Metadata includes basic information and computer data information of individuals, departments, legal persons or non-legal persons. Snapshot technology is also an effective means to achieve rapid data recovery. By regularly creating data snapshots, the state of the data at a certain moment can be recorded, so that when an unexpected situation occurs in the data, the data can be quickly restored to its previous state. Snapshot technology not only shortens the time of data recovery, but also reduces the impact of the recovery process on system performance.

[0080] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing and reserving data in a power grid system, characterized in that: The method comprises the following steps: Step S1: Acquire all data transmission paths of the total power grid system; Step S2: dividing the power data of all the data transmission paths into a plurality of different electrical energy efficiency links according to the difference values ​​of the power data; Step S3: respectively setting a plurality of data management nodes in a plurality of the electrical level energy efficiency links; Step S4: the data management node uses data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage.

2. A method for processing and storing data in a power grid system according to claim 1, characterized in that: In step S1, all data transmission paths of the total power grid system are obtained, which specifically includes the following steps: Step S101: calculating sub-data transmission paths corresponding to sub-grid systems in multiple areas; Step S102: classifying and marking the sub-data transmission paths using a dimension table; Step S103: classifying and counting the sub-data transmission paths that have been classified and marked, and generating different target numbers for different sub-data transmission paths; Step S104: The sub-data transmission paths corresponding to all the target numbers are integrated into a total set for unified management.

3. A method for processing and storing data in a power grid system according to claim 2, characterized in that: The target number includes identification information of multiple departments in the area that manage the sub-data transmission paths; The department identification information includes the department's social credit code, name, and geographic location.

4. A method for processing and storing data in a power grid system according to claim 3, characterized in that: The multiple departments respectively build data sharing platforms, and the steps of building the data sharing platform are as follows: Step S111: creating a sub-storage unit, and collecting the electric energy data of the sub-data transmission path and storing it in the storage unit; Step S112: the storage unit compresses the electric energy data and deletes duplicate data to obtain net electric energy data; Step S113: Virtualizing the sensitive information in the net electric energy data to obtain virtual data; Step S114: each department generates a unique key through unified coordination to unlock the virtual data and obtain the real net power data; Step S115: interconnecting the real net electric energy data among the departments.

5. A method for processing and storing data in a power grid system according to claim 1, characterized in that: The step S2, dividing all the data transmission paths into a plurality of different electric energy efficiency links according to the difference values ​​of the electric energy data, specifically comprises the following steps: Step S201: dividing the difference value into a first difference value, a second difference value, a third difference value and a fourth difference value; Step S202: assigning the electrode energy efficiency link to a first electrode energy efficiency link, a second electrode energy efficiency link, a third electrode energy efficiency link and a fourth electrode energy efficiency link according to the first difference, the second difference, the third difference and the fourth difference; Step S203: analyzing the loads of the first electrode energy efficiency link, the second electrode energy efficiency link, the third electrode energy efficiency link, and the fourth electrode energy efficiency link to obtain a first load, a second load, a third load, and a fourth load; The load is analyzed using the following formula: P 计算 =∑(P i ×K i )+K c ×(P 总安装 -P i ) Among them, P 计算 is the calculated load; P i is the capacity of the i-th electrical equipment; K i is the required coefficient of the i-th electrical equipment; Kc is the constant term coefficient; P 总安装 is the total installed capacity of electrical equipment in the data transmission path.

6. A method for processing and storing data in a power grid system according to claim 5, characterized in that: In the step S3, a plurality of data management nodes are respectively set in the plurality of the electric level energy efficiency links, specifically comprising the following steps: Step S301: respectively set the first electrode energy efficiency link, the second electrode energy efficiency link, the third electrode energy efficiency link and the fourth electrode energy efficiency link to correspond to the first subnode, the second subnode, the third subnode and the fourth subnode; Step S302: The first sub-node, the second sub-node, the third sub-node and the fourth sub-node are integrated into the data management node.

7. A method for processing and storing data in a power grid system according to claim 6, characterized in that: The data management node also includes: a payment module, and the steps of building the payment module are as follows: Step S311: Developing a user interactive payment framework and an interactive interface connected to the payment framework; Step S312: creating a user authentication port and a payment interface in the payment architecture, wherein the user authentication port and the payment interface are interconnected with the interactive interface; Step S313: creating a user-defined payment amount port in the payment interface, and interconnecting the customized payment amount port with the interactive interface; Step S314: Create login encryption data at the user authentication port, and customize the payment amount using the key corresponding to the encryption data.

8. A method for processing and storing data in a power grid system according to claim 7, characterized in that: The encrypted data includes: Collect user identity information, biometric information and obscured facial features, generate a first authentication port based on the user identity information, biometric information and obscured facial features, generate a second authentication port based on the first authentication port, and the second authentication port includes a voucher code generated by verifying the interactive payment architecture.

9. A method for processing and storing data in a power grid system according to claim 6, characterized in that: In step S4, the data management node uses data partitioning technology to divide the data in the power-level energy efficiency link into different blocks for storage, which specifically includes the following steps: Step S401: creating a first data storage block, a second data storage block, a third data storage block and a fourth data storage block in the data management node; Step S402: the first sub-node, the second sub-node, the third sub-node and the fourth sub-node are correspondingly allocated to the first data storage block, the second data storage block, the third data storage block and the fourth data storage block.

10. A method for processing and storing data in a power grid system according to claim 9, characterized in that: The first data storage block, the second data storage block, the third data storage block and the fourth data storage block are correspondingly provided with a first snapshot copy, a second snapshot copy, a third snapshot copy and a fourth snapshot copy, and the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy all have metadata, and the metadata includes data received and recorded by the first snapshot copy, the second snapshot copy, the third snapshot copy and the fourth snapshot copy.

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