A power data processing and storage method and system based on big data

Abstract

The application provides a power data processing and storage method and system based on big data, and the steps of the method include: acquiring power consumption data, randomly outputting a first standard pixel value for the regional consumption data of each power consumption area, and generating a first regional image based on the first standard pixel value; determining a first modification value based on the first value and the last value of the regional consumption data, determining a second standard pixel value based on the first modification value and the first standard pixel value, and generating a second regional image based on the second standard pixel value; determining a plurality of second modification values based on the values of adjacent bits of the regional consumption data of each power consumption area, modifying the pixel values of the corresponding regions in the second regional image based on the second modification values, and obtaining a data storage image; acquiring the data storage image and the first regional image corresponding to the same power consumption area, and storing the data storage image and the first regional image in a first storage position and a second storage position respectively.

Description

Technical Field

[0001] This application belongs to the field of data storage technology, and in particular relates to a method and system for processing and storing power data based on big data. Background Technology

[0002] Electricity consumption statistics refer to the statistical analysis of electricity consumption, including the statistical assessment of energy consumption of various electrical equipment and the power system. The main purpose of electricity consumption statistics is to help people better understand and grasp electricity consumption, providing a reference for power system optimization and energy conservation and emission reduction. Through the analysis and mining of electricity consumption statistics, bottlenecks and problems in electricity consumption can be identified, and corresponding energy conservation and emission reduction measures and methods can be proposed to improve the efficiency and sustainability of the power system.

[0003] Due to the diversity and complexity of power equipment, existing technologies employ distributed computing to distribute large amounts of data across different computing nodes for processing, thereby greatly improving statistical efficiency and data processing speed. However, during the processing of child nodes, data needs to be stored in advance, which poses a certain risk of data leakage. Summary of the Invention

[0004] This application provides a power data processing and storage method and system based on big data. This solution separates the data storage image and the first area image for storage, and encrypts and saves the data in the data storage image, thereby increasing data security and reducing the risk of data leakage.

[0005] In a first aspect, embodiments of this application provide a method for processing and storing power data based on big data, the method comprising the following steps: Acquire power consumption data, separate regional energy consumption data for each power consumption area from the power consumption data, and assign a regional label to each regional energy consumption data. For each power consumption area, the first standard pixel value is randomly output based on the regional energy consumption data. A first regional image is generated based on the first standard pixel value, and the pixel value of each pixel in the first regional image is the first standard pixel value. A first modified value is determined based on the first and last values ​​of the regional energy consumption data. A second standard pixel value is determined based on the first modified value and the first standard pixel value. A second regional image is generated based on the second standard pixel value. The pixel value of each pixel in the second regional image is the second standard pixel value. Based on the values ​​of adjacent bits of the regional energy consumption data of each power consumption area, multiple second modification values ​​are determined, and the pixel values ​​of the corresponding areas in the second regional image are modified based on the second modification values ​​to obtain the data storage image; Obtain a data storage image and a first area image corresponding to the same power consumption area, and store the data storage image and the first area image in a first storage location and a second storage location, respectively.

[0006] Using the above scheme, this scheme randomly outputs a first standard pixel value for the regional energy consumption data of each power consumption area to obtain a first regional image. Based on the first regional image, a first modified value is obtained, and a second regional image is further obtained. Based on the values ​​of each bit of the regional energy consumption data, a second modified value is obtained, and the second regional image is modified. The regional energy consumption data is stored in a data storage image, and the data storage image and the first regional image are stored separately. This scheme first uses the first regional image as a key to read the data storage image, and stores the data storage image and the first regional image separately, which initially increases the security of the data. Furthermore, the data is encrypted and stored in the data storage image, which further increases the security of the data. Even if the image carrying the data is leaked, the actual data is not easily leaked, reducing the risk of data leakage.

[0007] In some embodiments of the present invention, in the step of determining a first modified value based on the first and last values ​​of the regional energy consumption data, the average value of the first and last values ​​of the regional energy consumption data is calculated, and the first modified value is determined based on the average value of the first and last values ​​of the regional energy consumption data.

[0008] By adopting the above scheme, in the process of constructing the data storage image, the first modification value is determined by modifying the first and last values ​​of the energy consumption data of the region, and the basic pixel value of the data storage image is determined by the first modification value. This ensures that the data hidden in the data storage image cannot be parsed without obtaining the first region image.

[0009] In some embodiments of the present invention, in the step of determining a plurality of second modified values ​​based on the values ​​of adjacent bits of the regional energy consumption data for each power consumption area, the average value of each adjacent two bits of the regional energy consumption data is calculated, the average value of each adjacent two bits of the regional energy consumption data is taken as a second modified value, and a plurality of second modified values ​​are determined.

[0010] Using the above scheme, each second modified value corresponds to the value of two adjacent data bits in the regional energy consumption data. However, the value cannot be directly obtained by parsing any one of the second modified values, which improves the data security of this scheme.

[0011] In some embodiments of the present invention, the step of modifying the pixel value of the corresponding region in the second region image based on the second modified value includes: For each of the second modified values, a modification array is generated, and the average value of the values ​​in the modification array corresponds to a second modified value; The pixel values ​​of the preset modification area in the second region image are modified based on the modification array.

[0012] By adopting the above scheme, each second modified value generates a modified array, and a second modified value can only be obtained from the modified array when the entire modified array is obtained, thus ensuring the security of the modified value and improving the security of the data.

[0013] In some embodiments of the present invention, in the step of modifying the pixel values ​​of a preset modification region in the second region image based on the modification array, the modification region includes multiple rows, and the corresponding row in the modification region is determined based on the positions of two adjacent values ​​of the energy consumption data of the region corresponding to the modification array.

[0014] In some embodiments of the present invention, the method further includes data parsing, the data parsing step comprising: obtaining a data storage image and a first region image corresponding to the same region label from the first storage location and the second storage location respectively; parsing the pixel values ​​of the first region image to obtain a first standard pixel value; and parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel value to obtain power consumption data.

[0015] In some embodiments of the present invention, the step of parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel value includes: The pixel values ​​of the regions outside the modification region in the second region image are analyzed to obtain the second standard pixel value. The first modification value is obtained based on the first standard pixel value and the second standard pixel value. The first equation is established based on the first modification value. The pixel values ​​of each row in the modified region of the second region image are analyzed, and the second modification value corresponding to each row is obtained based on the pixel value of each row. A second system of equations is constructed based on multiple second modification values. The first and second equations are combined into a third set of equations, and the numerical values ​​of regional energy consumption data are obtained by solving the third set of equations.

[0016] Using the above scheme, if we rely solely on the data storage image or the first region image, we cannot obtain the data. If we obtain the data storage image and the analytical method, we can only obtain the second set of equations, but we cannot solve the second set of equations. Only by obtaining the data storage image or the first region image simultaneously can we construct a third set of equations. By solving the third set of equations, we can obtain the values ​​of each data bit of the power consumption data, which provides higher data security.

[0017] In some embodiments of the present invention, in the step of obtaining the second modified value corresponding to each row based on the pixel value of each row, the difference between the second standard pixel value and each pixel value of the row is calculated to obtain the modified array corresponding to that row, and the average value of the modified array is calculated as the second modified value.

[0018] In some embodiments of the present invention, a first modified value is obtained based on the first standard pixel value and the second standard pixel value, and the difference between the first standard pixel value and the second standard pixel value is calculated to obtain the first modified value.

[0019] Secondly, embodiments of this application provide a power data processing and storage system based on big data. The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the power data processing and storage method based on big data.

[0020] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the text, or may be learned by practice of the invention. The objects and other advantages of the invention will become apparent from the description and the accompanying drawings.

[0021] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0022] The accompanying drawings are provided to further understand the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof.

[0023] In the attached diagram: Figure 1 This is a flowchart illustrating the first implementation of the big data-based power data processing and storage method. Figure 2 This is a flowchart illustrating the second implementation of the big data-based power data processing and storage method. Figure 3 This is a flowchart illustrating the third implementation of the big data-based power data processing and storage method. Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0024] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0025] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0026] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0027] Generally speaking, in the process of processing child nodes in existing distributed processing technologies, data needs to be stored in advance, which poses a certain risk of data leakage.

[0028] Therefore, in order to reduce the risk of data leakage, this application provides a power data processing and storage method based on big data.

[0029] Figure 1 This is a flowchart illustrating a power data processing and storage method based on big data, provided in one embodiment of this application.

[0030] like Figure 1 As shown in the figure, this application embodiment provides a power data processing and storage method based on big data, the steps of which include: Step S100: Obtain power consumption data, separate regional energy consumption data of each power consumption area from the power consumption data, and assign a regional label to each regional energy consumption data. In the specific implementation process, the power consumption data records the regional energy consumption data of each power consumption area, and the regional energy consumption data is the power consumption data of that power consumption area.

[0031] In the specific implementation process, the power consumption data obtained are all power consumption data per unit time, which can be 1 hour, 1 minute or 1 day, etc.

[0032] Step S200: For the regional energy consumption data of each power consumption area, a first standard pixel value is randomly output, and a first regional image is generated based on the first standard pixel value. The pixel value of each pixel in the first regional image is the first standard pixel value. In the specific implementation process, the first standard pixel value is greater than the preset standard threshold, which can be 50, 80 or 100, etc. In the step of randomly outputting the first standard pixel value for the regional energy consumption data of each power consumption area, the output first standard pixel value is greater than the standard threshold.

[0033] Step S300: Determine a first modified value based on the first and last values ​​of the regional energy consumption data; determine a second standard pixel value based on the first modified value and the first standard pixel value; generate a second regional image based on the second standard pixel value; the pixel value of each pixel in the second regional image is the second standard pixel value. In some embodiments of the present invention, after determining a second standard pixel value based on the first modified value and the first standard pixel value, the difference between the first standard pixel value and the first modified value is taken as the second standard pixel value.

[0034] Step S400: Determine multiple second modification values ​​based on the values ​​of adjacent bits of the regional energy consumption data of each power consumption area, and modify the pixel values ​​of the corresponding areas in the second regional image based on the second modification values ​​to obtain the data storage image; Step S500: Obtain the data storage image and the first area image corresponding to the same power consumption area, and store the data storage image and the first area image in the first storage location and the second storage location, respectively.

[0035] In some embodiments of the present invention, the data storage images corresponding to all power consumption areas are stored in a first storage location, and the first area images corresponding to all power consumption areas are stored in a second storage location.

[0036] Using the above scheme, this scheme randomly outputs a first standard pixel value for the regional energy consumption data of each power consumption area to obtain a first regional image. Based on the first regional image, a first modified value is obtained, and a second regional image is further obtained. Based on the values ​​of each bit of the regional energy consumption data, a second modified value is obtained, and the second regional image is modified. The regional energy consumption data is stored in a data storage image, and the data storage image and the first regional image are stored separately. This scheme first uses the first regional image as a key to read the data storage image, and stores the data storage image and the first regional image separately, which initially increases the security of the data. Furthermore, the data is encrypted and stored in the data storage image, which further increases the security of the data. Even if the image carrying the data is leaked, the actual data is not easily leaked, reducing the risk of data leakage.

[0037] In some embodiments of the present invention, in the step of determining a first modified value based on the first and last values ​​of the regional energy consumption data, the average value of the first and last values ​​of the regional energy consumption data is calculated, and the first modified value is determined based on the average value of the first and last values ​​of the regional energy consumption data.

[0038] In the specific implementation process, if the energy consumption data of the area is 1847, then the average value of 1 and 7 is calculated to be 4, and the first modified value is 4.

[0039] By adopting the above scheme, in the process of constructing the data storage image, the first modification value is determined by modifying the first and last values ​​of the energy consumption data of the region, and the basic pixel value of the data storage image is determined by the first modification value. This ensures that the data hidden in the data storage image cannot be parsed without obtaining the first region image.

[0040] In some embodiments of the present invention, in the step of determining a plurality of second modified values ​​based on the values ​​of adjacent bits of the regional energy consumption data for each power consumption area, the average value of each adjacent two bits of the regional energy consumption data is calculated, the average value of each adjacent two bits of the regional energy consumption data is taken as a second modified value, and a plurality of second modified values ​​are determined.

[0041] In the specific implementation process, if the energy consumption data of the region is 1847, then the average values ​​of 1 and 8, 8 and 4, and 4 and 7 are calculated respectively, which are 4.5, 6 and 5.5, and are used as three second modification values.

[0042] Using the above scheme, each second modified value corresponds to the value of two adjacent data bits in the regional energy consumption data. However, the value cannot be directly obtained by parsing any one of the second modified values, which improves the data security of this scheme.

[0043] In some embodiments of the present invention, the step of modifying the pixel value of the corresponding region in the second region image based on the second modified value includes: For each of the second modified values, a modification array is generated, and the average value of the values ​​in the modification array corresponds to a second modified value; The pixel values ​​of the preset modification area in the second region image are modified based on the modification array.

[0044] In the specific implementation process, the values ​​in the modified array are sequentially assigned to the pixel cells of a row in the modified area, and the pixel value of that pixel cell is modified.

[0045] By adopting the above scheme, the modified array is a randomly generated array with an average value equal to the second modified value, which ensures the randomness of the data. When the data storage image is stolen, it increases the difficulty of cracking the data and improves data security.

[0046] In some embodiments of the present invention, the pixel value of the corresponding pixel grid is subtracted from the corresponding value in the modified array.

[0047] By adopting the above scheme, each second modified value generates a modified array, and a second modified value can only be obtained from the modified array when the entire modified array is obtained, thus ensuring the security of the modified value and improving the security of the data.

[0048] In some embodiments of the present invention, in the step of modifying the pixel values ​​of a preset modification region in the second region image based on the modification array, the modification region includes multiple rows, and the corresponding row in the modification region is determined based on the positions of two adjacent values ​​of the energy consumption data of the region corresponding to the modification array.

[0049] In the specific implementation process, if the energy consumption data of the region is 1847, then the average values ​​of 1 and 8, 8 and 4, and 4 and 7 are calculated respectively, which are 4.5, 6 and 5.5, as three second modification values. Then, 4.5 obtained by 1 and 8 corresponds to the first row of the modified region, 6 obtained by 8 and 4 corresponds to the second row of the modified region, and 5.5 obtained by 4 and 7 corresponds to the third row of the modified region.

[0050] like Figure 2 As shown, in some embodiments of the present invention, the method further includes data parsing, the data parsing step including: step S600, obtaining a data storage image and a first region image corresponding to the same region label from the first storage location and the second storage location respectively, parsing the pixel values ​​of the first region image to obtain a first standard pixel value, and parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel value to obtain power consumption data.

[0051] like Figure 3 As shown, in some embodiments of the present invention, the data parsing step includes: step S610, obtaining a data storage image and a first region image corresponding to the same region label from the first storage location and the second storage location respectively, parsing the pixel values ​​of the first region image to obtain a first standard pixel value.

[0052] The steps for parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel values ​​include: Step S620: Analyze the pixel values ​​of the region outside the modification region in the second region image to obtain the second standard pixel value, obtain the first modification value based on the first standard pixel value and the second standard pixel value, and establish the first equation based on the first modification value; In the specific implementation process, the first modification value is 4, so the first equation is (a+d) / 2=4.

[0053] Step S630: Analyze the pixel values ​​of each row in the modified region of the second region image, obtain the second modification value corresponding to each row based on the pixel values ​​of each row, and construct a second set of equations based on multiple second modification values; In the specific implementation process, if the second modified values ​​are 4.5, 6 and 5.5 respectively, then the second system of equations is (a+b) / 2=4.5, (b+c) / 2=6, (c+d) / 2=5.5.

[0054] Step S640: Combine the first equation and the second equation set into a third equation set, and solve the third equation set to obtain the numerical value of regional energy consumption data.

[0055] In the specific implementation process, if the first equation is a+d=4, and the second set of equations includes a+b / 2=4.5, b+c=6, c+d=5.5, then the third set of equations is (a+d) / 2=4, (a+b) / 2=4.5, (b+c) / 2=6, (c+d) / 2=5.5. Analyzing the third set of equations, we get a=1, b=8, c=4, d=7, and the regional energy consumption data is 1847.

[0056] Using the above scheme, if we rely solely on the data storage image or the first region image, we cannot obtain the data. If we obtain the data storage image and the analytical method, we can only obtain the second set of equations, but we cannot solve the second set of equations. Only by obtaining the data storage image or the first region image simultaneously can we construct a third set of equations. By solving the third set of equations, we can obtain the values ​​of each data bit of the power consumption data, which provides higher data security.

[0057] In some embodiments of the present invention, in the step of obtaining the second modified value corresponding to each row based on the pixel value of each row, the difference between the second standard pixel value and each pixel value of the row is calculated to obtain the modified array corresponding to that row, and the average value of the modified array is calculated as the second modified value.

[0058] In some embodiments of the present invention, a first modified value is obtained based on the first standard pixel value and the second standard pixel value, and the difference between the first standard pixel value and the second standard pixel value is calculated to obtain the first modified value.

[0059] Secondly, embodiments of this application provide a power data processing and storage system based on big data. The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the power data processing and storage method based on big data.

[0060] Thirdly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the aforementioned power data processing and storage method based on big data.

[0061] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0062] like Figure 4 As shown, this application embodiment provides an electronic device, which includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the above-mentioned power data processing and storage method based on big data.

[0063] The electronic device may include a processor 1201 and a memory 1202 storing computer program instructions.

[0064] Specifically, the processor 1201 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0065] Memory 1202 may include mass storage for data or instructions. For example, and not limitingly, memory 1202 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 1202 may include removable or non-removable (or fixed) media. Where appropriate, memory 1202 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 1202 is non-volatile solid-state memory.

[0066] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0067] The processor 1201 reads and executes computer program instructions stored in the memory 1202 to implement any of the battery thermal runaway parameter determination methods in the above embodiments.

[0068] In one example, the electronic device may also include a communication interface 1203 and a bus 1210. For example, Figure 4 As shown, the processor 1201, memory 1202, and communication interface 1203 are connected through bus 1210 and complete communication with each other.

[0069] The communication interface 1203 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0070] Bus 1210 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1210 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0071] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0072] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0073] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0074] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0075] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for processing and storing power data based on big data, characterized in that, The steps of the method include: Acquire power consumption data, separate regional energy consumption data for each power consumption area from the power consumption data, and assign a regional label to each regional energy consumption data. For each power consumption area, the first standard pixel value is randomly output based on the regional energy consumption data. A first regional image is generated based on the first standard pixel value, and the pixel value of each pixel in the first regional image is the first standard pixel value. A first modified value is determined based on the first and last values ​​of the regional energy consumption data. A second standard pixel value is determined based on the first modified value and the first standard pixel value. A second regional image is generated based on the second standard pixel value. The pixel value of each pixel in the second regional image is the second standard pixel value. Based on the values ​​of adjacent bits of the regional energy consumption data of each power consumption area, multiple second modification values ​​are determined, and the pixel values ​​of the corresponding areas in the second regional image are modified based on the second modification values ​​to obtain the data storage image. Obtain a data storage image and a first area image corresponding to the same power consumption area, and store the data storage image and the first area image in a first storage location and a second storage location, respectively.

2. The power data processing and storage method based on big data according to claim 1, characterized in that, In the step of determining the first modified value based on the first and last values ​​of the regional energy consumption data, the average value of the first and last values ​​of the regional energy consumption data is calculated, and the first modified value is determined based on the average value of the first and last values ​​of the regional energy consumption data.

3. The power data processing and storage method based on big data according to claim 1, characterized in that, In the step of determining multiple second modified values ​​based on the values ​​of adjacent bits of the regional energy consumption data for each power consumption area, the average value of each adjacent two bits of the regional energy consumption data is calculated, the average value of each adjacent two bits of the regional energy consumption data is taken as a second modified value, and multiple second modified values ​​are determined.

4. The power data processing and storage method based on big data according to claim 1, characterized in that, The steps of modifying the pixel values ​​of the corresponding region in the second region image based on the second modified value include: For each of the second modified values, a modification array is generated, and the average value of the values ​​in the modification array corresponds to a second modified value; The pixel values ​​of the preset modification area in the second region image are modified based on the modification array.

5. The power data processing and storage method based on big data according to claim 4, characterized in that, In the step of modifying the pixel values ​​of a preset modified region in the second region image based on the modified array, the modified region includes multiple rows, and the corresponding row in the modified region is determined based on the position of the two adjacent values ​​of the energy consumption data of the region corresponding to the modified array.

6. The power data processing and storage method based on big data according to claim 4 or 5, characterized in that, The method further includes data parsing, which includes: obtaining a data storage image and a first region image corresponding to the same region label from the first storage location and the second storage location respectively; parsing the pixel values ​​of the first region image to obtain a first standard pixel value; and parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel value to obtain power consumption data.

7. The power data processing and storage method based on big data according to claim 6, characterized in that, The steps for parsing the pixel values ​​of the modified region in the second region image based on the first standard pixel values ​​include: The pixel values ​​of the regions outside the modification region in the second region image are analyzed to obtain the second standard pixel values. The first modification value is obtained based on the first standard pixel value and the second standard pixel value. The first equation is established based on the first modification value. The pixel values ​​of each row in the modified region of the second region image are analyzed, and the second modification value corresponding to each row is obtained based on the pixel value of each row. A second system of equations is constructed based on multiple second modification values. The first and second equations are combined into a third set of equations, and the numerical values ​​of regional energy consumption data are obtained by solving the third set of equations.

8. The power data processing and storage method based on big data according to claim 7, characterized in that, In the step of obtaining the second modified value for each row based on the pixel value of each row, the difference between the second standard pixel value and each pixel value of the row is calculated to obtain the modified array corresponding to that row. The average value of the modified array is then calculated as the second modified value.

9. The power data processing and storage method based on big data according to claim 7, characterized in that, Based on the first standard pixel value and the second standard pixel value, a first modified value is obtained. The difference between the first standard pixel value and the second standard pixel value is calculated to obtain the first modified value.

10. A power data processing and storage system based on big data, characterized in that, The system includes a computer device, which includes a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the big data-based power data processing and storage method as described in any one of claims 1-9.

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