A method for protecting energy storage data security in distribution networks based on cloud computing

Abstract

The present invention relates to the field of digital information transmission technology, and more specifically to a cloud computing-based method for securing energy storage data in a distribution network. The method comprises the following steps: collecting energy storage data from all child nodes and parent nodes of the distribution network, determining the proportion of energy storage data of each child node in the parent node, obtaining a grayscale map of the energy storage data based on the proportion, determining the regional importance of each child node based on the energy storage data of each child node and screening important areas, obtaining a frequency spectrum of the energy storage data of each node, determining the regional regularization importance of each child node in the important area based on the signal strength in the frequency spectrum and the regional importance of each child node, and encrypting and transmitting the grayscale map of the parent node's energy storage data based on the regional regularization importance of each child node in the important area. The present invention converts the energy storage data into a redundant grayscale map and encrypts the grayscale map, effectively improving the security of the energy storage data.

Description

Technical Field

[0001] The present invention relates to the technical field of digital information transmission, and in particular to a method for protecting the security of energy storage data in a distribution network based on cloud computing. Background Art

[0002] The distribution network is a complex and sophisticated system that receives electricity from the transmission grid or regional power plants. It distributes electricity to various regions and users step by step according to voltage levels to ensure that every corner of the network has access to a stable and reliable power supply. In the operation of the distribution network, the collection and analysis of energy storage data plays a vital role. This data not only includes users' energy usage, but also covers their behavioral patterns and energy consumption habits. Through in-depth analysis of this data, we can better understand user needs, optimize the allocation of power resources, and improve energy utilization efficiency.

[0003] However, energy storage data is sensitive. Once this information is leaked, not only will the user's privacy be violated, but the user's important data may also be threatened. Therefore, the security of energy storage data cannot be ignored. To protect energy storage data from unauthorized access and theft, data security protection is required to ensure data integrity and confidentiality. This is crucial to maintaining the stable operation of the power system and the interests of users. Summary of the Invention

[0004] The present invention provides a distribution network energy storage data security protection method based on cloud computing to solve existing problems.

[0005] The present invention provides a method for protecting energy storage data security in a distribution network based on cloud computing, which adopts the following technical solutions:

[0006] An embodiment of the present invention provides a method for protecting energy storage data security in a distribution network based on cloud computing, the method comprising the following steps:

[0007] Collect energy storage data of all child nodes and parent nodes in the distribution network;

[0008] Based on the energy storage data of each node and the path length between each node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined. Based on the proportion of the energy storage data of each child node in the energy storage data of the parent node, the energy storage data is converted into a grayscale image to obtain a grayscale image and a grayscale histogram of the energy storage data of the parent node;

[0009] Based on the energy storage data of each child node under the parent node, the regional importance of each child node is determined. The important areas are screened based on the regional importance of each child node. The spectrum of the energy storage data of each node in the distribution network is obtained. Based on the signal strength characteristics in the spectrum and the regional importance of each child node, the regional regularization importance of each child node in the important area is determined.

[0010] According to the regional regularization importance of each child node in the important area, the grayscale image of the parent node energy storage data is encrypted and transmitted.

[0011] Furthermore, the specific method for determining the proportion of the energy storage data of each child node in the energy storage data of the parent node is as follows:

[0012] According to the energy storage data of each child node under the parent node and the path length between the parent node and the child node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined.

[0013] Furthermore, the specific calculation method of the proportion of the energy storage data of each child node in the energy storage data of the parent node is:

[0014]

[0015] Where, Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data in Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Child nodes and parent nodes The length of the path between Indicates the parent node To the parent node The sum of the path lengths between all child nodes; Indicates the parent node The number of child nodes; Indicates the parent node energy storage data.

[0016] Furthermore, the determining of the regional importance of each sub-node and screening of important regions according to the regional importance of each sub-node include the following specific methods:

[0017] Determine the parent node based on the energy storage data of each child node under the parent node Next The regional importance of each child node;

[0018] The regional importance of each child node under the parent node is obtained, and the child nodes whose regional importance is greater than a preset first threshold are recorded as important child nodes, and the areas corresponding to the important child nodes are recorded as important areas.

[0019] Furthermore, the parent node Next The specific calculation method of the regional importance of each child node is:

[0020]

[0021] Where, Indicates the parent node Next The regional importance of each child node; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node The number of child nodes; Represents the maximum and minimum normalization function.

[0022] Furthermore, the specific method of determining the regional regularization importance of each sub-node in the important region includes:

[0023] A Fourier transform is performed on the energy storage data of each node in the distribution network every day of the year to obtain a Fourier transform spectrum diagram. Based on the signal strength characteristics in the Fourier transform spectrum diagram of the sub-node and the regional importance of each sub-node, the regional regularization importance of each sub-node in the important area is determined.

[0024] Furthermore, the specific calculation method of the regional regularization importance of each sub-node in the important region is:

[0025]

[0026] Where, Indicates the important area The importance of regional regularization of each child node; Indicates the number of peaks in the Fourier transform spectrum; The spectrum of the Fourier transform is represented by The signal strength of the peak; Represents the average value of all signal intensities in the Fourier transformed spectrogram; Indicates the important area The regional importance of each child node; Represents an exponential function with a natural constant as its base.

[0027] Furthermore, the specific method of encrypting and transmitting the grayscale image of the parent node energy storage data is as follows:

[0028] Calculate the regional regularization importance of each child node in the important area, encrypt the parent node energy storage data grayscale map according to the regional regularization importance, and obtain the final parent node energy storage data grayscale map, the specific encryption method is: use the regional regularization importance of each child node in the important area as the height change weight of the column corresponding to each child node in the grayscale histogram, use the height change weight to change the height of each column in the grayscale histogram of the parent node energy storage data grayscale map, obtain the grayscale histogram of the first encrypted parent node energy storage data grayscale map, thereby obtaining the first encrypted parent node energy storage data grayscale map, and then use the chaotic encryption algorithm to encrypt the first encrypted parent node energy storage data grayscale map to obtain the final encrypted parent node energy storage data grayscale map;

[0029] Then, the final parent node energy storage data grayscale image is transmitted using the 5G network.

[0030] Furthermore, the energy storage data is converted into a grayscale image to obtain a grayscale image and a grayscale histogram of the parent node energy storage data, including the specific method of:

[0031] The parent node is treated as a rectangle, denoted as the parent node rectangle. The parent node rectangle is divided according to the proportion of the energy storage data of each child node under the parent node in the energy storage data of the parent node, to obtain several small rectangles representing the energy storage data of the child nodes. The grayscale value to be filled in each small rectangle is determined according to the proportion of the energy storage data of each child node under the parent node in the energy storage data of the parent node.

[0032] Each small rectangle is filled according to the grayscale value that needs to be filled in the small rectangles corresponding to all child nodes under each parent node, and the filled parent node rectangle is recorded as the parent node energy storage data grayscale map, and the grayscale histogram of the parent node energy storage data grayscale map is obtained.

[0033] Furthermore, the specific calculation method for determining the grayscale value that each small rectangle needs to be filled is:

[0034]

[0035] Where, Indicates the parent node Next The grayscale value that needs to be filled in the small rectangle corresponding to each child node; Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data.

[0036] The beneficial effects of the technical solution of the present invention are as follows: according to the energy storage data of each node and the path length between each node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined; according to the proportion of the energy storage data of each child node in the energy storage data of the parent node, the energy storage data is converted into a grayscale image to obtain a grayscale image and a grayscale histogram of the energy storage data of the parent node, which are used to better analyze the relationship between the energy storage data between the nodes; according to the energy storage data of each child node under the parent node, the regional importance of each child node is determined; according to the regional importance of each child node, important areas are screened, and a spectrum diagram of the energy storage data of each node in the distribution network is obtained; according to the signal strength characteristics in the spectrum diagram and the regional importance of each child node, the regional regularization importance of each child node in the important area is determined, which helps to understand the importance of the energy storage data of different nodes; according to the regional regularization importance of each child node in the important area, the grayscale image of the energy storage data of the parent node is encrypted and transmitted, thereby realizing security protection of the energy storage data, improving the confidentiality of the energy storage data, and protecting the energy storage data from other unknown access and theft. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 This is a flowchart of the steps of a cloud computing-based distribution network energy storage data security protection method of the present invention;

[0039] Figure 2 A schematic diagram of a distribution network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a cloud computing-based distribution network energy storage data security protection method proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0042] The following describes in detail a specific solution of a distribution network energy storage data security protection method based on cloud computing provided by the present invention with reference to the accompanying drawings.

[0043] See also Figure 1 , which shows a flowchart of a method for protecting energy storage data security in a distribution network based on cloud computing provided by one embodiment of the present invention, the method comprising the following steps:

[0044] Step S001: Collect energy storage data of all child nodes and parent nodes of the distribution network.

[0045] In order to implement the cloud computing-based distribution network energy storage data security protection method proposed in this embodiment, it is first necessary to collect distribution network energy storage data. The specific process is as follows:

[0046] The energy storage data of each node in the distribution network is obtained every day in a year. The energy storage data consists of the energy storage data of each node in a continuous time series. The obtained data is recorded as the distribution network energy storage data, such as Figure 2 The figure shows a schematic diagram of the distribution network of this embodiment, where node A is the parent node of child nodes a, b, and c, and Aa, Ab, and Ac are the path lengths between the parent node A and child nodes a, b, and c.

[0047] So far, the distribution network energy storage data has been obtained through the above method.

[0048] Step S002: Determine the proportion of the energy storage data of each child node in the energy storage data of the parent node based on the energy storage data of each node and the path length between each node; convert the energy storage data into a grayscale image based on the proportion of the energy storage data of each child node in the energy storage data of the parent node, and obtain a grayscale image and a grayscale histogram of the energy storage data of the parent node.

[0049] It should be noted that the distribution network usually distributes energy storage data from the parent node to each child node in a radially outward manner. For the energy storage data of the distribution network, under ideal conditions, the energy storage data of the parent node is the sum of the energy storage data of all child nodes. However, there is a certain loss during the energy storage data transmission process. In addition, in order to more intuitively represent the energy storage data relationship between each parent node and the child node after the energy storage data is transmitted, and to facilitate the subsequent analysis of the energy storage data between different nodes, this embodiment of the present invention constructs an energy storage data grayscale map to facilitate the security protection of the distribution network energy storage data. However, during the construction process, the grayscale values ​​of different nodes in the energy storage data grayscale map cannot be completely obtained based on the ratio of the energy storage data of the child node to the energy storage data of the parent node. It is necessary to consider the path length between the child node and the parent node, analyze the energy storage data loss during the transmission process, so as to improve the accuracy of the description of the energy storage data of the parent node and the child node, and then perform energy storage data conversion.

[0050] In step (2.1), based on the energy storage data of each node and the path length between each node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined.

[0051] It should be noted that when converting the distribution network energy storage data into a grayscale image, it is necessary to first determine the proportion of the energy storage data of each child node in the energy storage data of the parent node, and determine the grayscale value of the grayscale image of the parent node energy storage data based on the proportion.

[0052] Specifically, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined according to the energy storage data of each child node under the parent node and the path length between the parent node and the child node.

[0053] As an embodiment, a specific method for calculating the proportion of the energy storage data of each child node in the energy storage data of the parent node is as follows:

[0054]

[0055] Where, Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data in Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Child nodes and parent nodes The length of the path between Indicates the parent node To the parent node The sum of the path lengths between all child nodes; Indicates the parent node The number of child nodes; Indicates the parent node energy storage data.

[0056] It should be noted that Indicates the parent node Energy storage data loss of all child nodes, The larger the value, the more likely the parent node is The greater the loss of energy storage data during transmission to its child nodes. Indicates the parent node Next The path between the child nodes and the parent node, The larger the value, the The longer the path between a child node and its parent node, the more energy storage data will be lost during the transmission process. Indicates the parent node To the Energy storage data loss during transmission of each sub-node, The larger the value, the more likely the parent node is To the The greater the energy storage data loss during the transmission of the child nodes, the greater the corresponding parent node Next The energy storage data of the child nodes is in the parent node The larger the proportion of energy storage data.

[0057] In step (2.2), the energy storage data is converted into a grayscale image according to the proportion of the energy storage data of each child node in the energy storage data of the parent node, and the grayscale image and grayscale histogram of the energy storage data of the parent node are obtained.

[0058] Specifically, first, the parent node is regarded as a rectangle, recorded as the parent node rectangle, and the parent node rectangle is divided according to the proportion of the energy storage data of each child node under the parent node in the energy storage data of the parent node, to obtain several small rectangles representing the energy storage data of the child nodes. According to the proportion of the energy storage data of each child node under the parent node in the energy storage data of the parent node, the grayscale value that needs to be filled in each small rectangle is determined.

[0059] As an embodiment, the specific calculation method of the grayscale value that each small rectangle needs to be filled is:

[0060]

[0061] Where, Indicates the parent node Next The grayscale value that needs to be filled in the small rectangle corresponding to each child node; Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data.

[0062] It should be noted that the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data in the parent node Next The grayscale values ​​that need to be filled in the small rectangles corresponding to the child nodes are in direct proportion. The energy storage data of the child nodes is in the parent node The larger the proportion of energy storage data, the greater the The larger the The larger the value.

[0063] Then, each small rectangle is filled according to the grayscale value that needs to be filled in the small rectangles corresponding to all child nodes under each parent node, and the filled parent node rectangle is recorded as the parent node energy storage data grayscale map, and the grayscale histogram of the parent node energy storage data grayscale map is obtained.

[0064] At this point, the grayscale image and grayscale histogram of the parent node energy storage data are obtained through the above method.

[0065] Step S003: Determine the regional importance of each child node based on the energy storage data of each child node under the parent node, screen important areas based on the regional importance of each child node, obtain a spectrum diagram of the energy storage data of each node in the distribution network, and determine the regional regularization importance of each child node in the important area based on the signal strength characteristics in the spectrum diagram and the regional importance of each child node.

[0066] It should be noted that, under normal circumstances, the energy storage data corresponding to each sub-node of the distribution network is used to supply power to part of the area to which it belongs. Under normal circumstances, the electricity consumption in different areas is different. In order to adapt to the electricity consumption in different areas, the energy storage data of the corresponding nodes will also be different. The area with relatively higher energy storage data means that the energy demand in the area is relatively large or it is a critical electricity consumption area. If these energy storage data are tampered with or stolen, it may lead to uneven energy distribution or waste of resources, affecting the operating efficiency and stability of the power grid. Therefore, the more important the energy storage data of the corresponding sub-node is, the more it is necessary to ensure the security of the energy storage data to avoid data security issues such as tampering and theft.

[0067] In step (3.1), the regional importance of each child node is determined based on the energy storage data of each child node under the parent node, and the important areas are screened based on the regional importance of each child node.

[0068] It should be noted that, generally speaking, the higher the energy storage data, the more important the data is, and the more security protection should be strengthened. Therefore, it is necessary to first determine the regional importance of each sub-node and screen important areas based on the regional importance.

[0069] Specifically, the parent node is determined based on the energy storage data of each child node under the parent node. Next The regional importance of each child node.

[0070] As an example, the parent node Next The specific calculation method of the regional importance of each child node is:

[0071]

[0072] Where, Indicates the parent node Next The regional importance of each child node; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node The number of child nodes; Represents the maximum and minimum normalization function.

[0073] It should be noted that the maximum and minimum normalization function is used to normalize the parent node Normalize the energy storage data of all leaf nodes under The larger the value, the Next The greater the regional importance of the child nodes, The larger the value.

[0074] The regional importance of each child node under the parent node is obtained, and the child nodes whose regional importance is greater than a preset first threshold are recorded as important child nodes, and the areas corresponding to the important child nodes are recorded as important areas.

[0075] It should be noted that the value of the first threshold is preset to 0.8 based on experience and can be adjusted according to actual conditions. This embodiment does not impose any specific limitation.

[0076] In step (3.2), the Fourier transform spectrum of the energy storage data of each node in the distribution network is obtained, and the regional regularization importance of each sub-node in the important area is determined based on the signal strength characteristics in the spectrum and the regional importance of each sub-node.

[0077] It should be noted that the important areas selected based on the energy storage data of each sub-node are not completely representative. For users who use electricity regularly, higher energy storage data does not necessarily mean higher importance. Irregular electricity usage patterns may reveal users' work patterns or other personal information, which may be abused. Therefore, it is necessary to correct the important areas based on the regularity of the sub-nodes' electricity usage.

[0078] Specifically, a Fourier transform is first performed on the energy storage data of each node in the distribution network every day of the year to obtain a Fourier transform spectrum diagram. Then, the regional regularization importance of each sub-node in the important area is determined based on the signal strength characteristics in the Fourier transform spectrum diagram of the sub-node and the regional importance of each sub-node.

[0079] As an embodiment, a specific method for calculating the regional regularization importance of each sub-node in the important region is as follows:

[0080]

[0081] Where, Indicates the important area The importance of regional regularization of each child node; Indicates the number of peaks in the Fourier transform spectrum; The spectrum of the Fourier transform is represented by The signal strength of the peak; Represents the average value of all signal intensities in the Fourier transformed spectrogram; Indicates the important area The regional importance of each child node; Represents an exponential function with a natural constant as its base.

[0082] It should be noted that if the energy storage data has regularity, there will be obvious peaks in the Fourier transform spectrum, and the greater the difference between the peak and the average value of all signal intensities, that is, The larger the value, the The larger the value, the more irregular the energy storage data. The larger the value of .

[0083] So far, the regional regularization importance of each sub-node in the important region is obtained through the above method.

[0084] Step S004: encrypt and transmit the grayscale image of the energy storage data of the parent node according to the regional regularization importance of each child node in the important area.

[0085] It should be noted that for energy storage data with greater regional regularity, greater protection should be given. The energy storage data can be protected by changing its area on the grayscale map, that is, increasing the height of the column in the grayscale histogram.

[0086] Specifically, first, the regional regularization importance of each child node in the important area is obtained according to the above steps, and the parent node energy storage data grayscale map is encrypted according to the regional regularization importance to obtain the final parent node energy storage data grayscale map. The specific encryption method is: the regional regularization importance of each child node in the important area is used as the height change weight of the column corresponding to each child node in the grayscale histogram, and the height change weight is used to change the height of each column in the grayscale histogram of the parent node energy storage data grayscale map to obtain the grayscale histogram of the first encrypted parent node energy storage data grayscale map, thereby obtaining the first encrypted parent node energy storage data grayscale map, and then use the chaotic encryption algorithm to encrypt the first encrypted parent node energy storage data grayscale map to obtain the final encrypted parent node energy storage data grayscale map.

[0087] Then, the final parent node energy storage data grayscale image is transmitted using the 5G network.

[0088] It should be noted that the chaotic encryption algorithm is an existing technology and will not be described in detail here.

[0089] When decrypting the final grayscale image of the parent node energy storage data, the specific method is: use the key automatically generated by the chaotic encryption algorithm to decrypt the final encrypted grayscale image of the parent node energy storage data to obtain the grayscale image and grayscale histogram of the parent node energy storage data after the first encryption, and then use the height of each column in the grayscale histogram of the grayscale image of the parent node energy storage data after the first encryption to divide by the height change weight to obtain the grayscale histogram of the parent node energy storage data grayscale image, and multiply the probability of the pixel corresponding to each column in the grayscale histogram of the parent node energy storage data grayscale image appearing in the grayscale image by the energy storage data of the parent node to obtain the energy storage data of the child node corresponding to each column.

[0090] At this point, this embodiment is completed.

[0091] It should be noted that the The model is only used to represent negative correlation and constrain the output of the model to be in In the specific implementation, it can be replaced by other models with the same purpose. This embodiment is only based on The model is described as an example without any specific limitation. is the input to the model.

[0092] 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 principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for protecting energy storage data security in a distribution network based on cloud computing, characterized in that: The method comprises the following steps: Collect energy storage data of all child nodes and parent nodes in the distribution network; Based on the energy storage data of each node and the path length between each node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined. Based on the proportion of the energy storage data of each child node in the energy storage data of the parent node, the energy storage data is converted into a grayscale image to obtain a grayscale image and a grayscale histogram of the energy storage data of the parent node; Based on the energy storage data of each child node under the parent node, the regional importance of each child node is determined. The important areas are screened based on the regional importance of each child node. The spectrum of the energy storage data of each node in the distribution network is obtained. Based on the signal strength characteristics in the spectrum and the regional importance of each child node, the regional regularization importance of each child node in the important area is determined. According to the regional regularization importance of each child node in the important area, the grayscale image of the parent node energy storage data is encrypted and transmitted.

2. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 1, characterized in that: The specific method for determining the proportion of the energy storage data of each child node in the energy storage data of the parent node includes: According to the energy storage data of each child node under the parent node and the path length between the parent node and the child node, the proportion of the energy storage data of each child node in the energy storage data of the parent node is determined.

3. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 2, characterized in that: The specific calculation method of the proportion of the energy storage data of each child node in the energy storage data of the parent node is: Where, Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data in Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Child nodes and parent nodes The length of the path between Indicates the parent node To the parent node The sum of the path lengths between all child nodes; Indicates the parent node The number of child nodes; Indicates the parent node energy storage data.

4. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 1, characterized in that: The specific method of determining the regional importance of each sub-node and screening the important regions according to the regional importance of each sub-node is as follows: Determine the parent node based on the energy storage data of each child node under the parent node Next The regional importance of each child node; The regional importance of each child node under the parent node is obtained, and the child nodes whose regional importance is greater than a preset first threshold are recorded as important child nodes, and the areas corresponding to the important child nodes are recorded as important areas.

5. A method for protecting energy storage data security in a distribution network based on cloud computing according to claim 4, characterized in that: The parent node Next The specific calculation method of the regional importance of each child node is: Where, Indicates the parent node Next The regional importance of each child node; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node Next Energy storage data of child nodes; Indicates the parent node The number of child nodes; Represents the maximum and minimum normalization function.

6. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 1, characterized in that: The specific method of determining the regional regularization importance of each sub-node in the important region includes: A Fourier transform is performed on the energy storage data of each node in the distribution network every day of the year to obtain a Fourier transform spectrum diagram. Based on the signal strength characteristics in the Fourier transform spectrum diagram of the sub-node and the regional importance of each sub-node, the regional regularization importance of each sub-node in the important area is determined.

7. A method for protecting energy storage data security in a distribution network based on cloud computing according to claim 6, characterized in that: The specific calculation method of the regional regularization importance of each sub-node in the important area is: Where, Indicates the important area The importance of regional regularization of each child node; Indicates the number of peaks in the Fourier transform spectrum; The spectrum of the Fourier transform is represented by The signal strength of the peak; Represents the average value of all signal intensities in the Fourier transformed spectrogram; Indicates the important area The regional importance of each child node; Represents an exponential function with a natural constant as its base.

8. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 1, characterized in that: The specific method of encrypting and transmitting the grayscale image of the parent node energy storage data is as follows: Calculate the regional regularization importance of each child node in the important area, encrypt the parent node energy storage data grayscale map according to the regional regularization importance, and obtain the final parent node energy storage data grayscale map, the specific encryption method is: use the regional regularization importance of each child node in the important area as the height change weight of the column corresponding to each child node in the grayscale histogram, use the height change weight to change the height of each column in the grayscale histogram of the parent node energy storage data grayscale map, obtain the grayscale histogram of the first encrypted parent node energy storage data grayscale map, thereby obtaining the first encrypted parent node energy storage data grayscale map, and then use the chaotic encryption algorithm to encrypt the first encrypted parent node energy storage data grayscale map to obtain the final encrypted parent node energy storage data grayscale map; Then, the final parent node energy storage data grayscale image is transmitted using the 5G network.

9. The method for protecting energy storage data security in a distribution network based on cloud computing according to claim 1, characterized in that: The energy storage data is converted into a grayscale image to obtain a grayscale image and a grayscale histogram of the parent node energy storage data, including the following specific methods: The parent node is treated as a rectangle, denoted as the parent node rectangle. Based on the proportion of the energy storage data of each child node under the parent node in the energy storage data of the parent node, the parent node rectangle is divided into several small rectangles representing the energy storage data of the child nodes. The grayscale value that needs to be filled in each small rectangle is determined; Each small rectangle is filled according to the grayscale value that needs to be filled in the small rectangles corresponding to all child nodes under each parent node, and the filled parent node rectangle is recorded as the parent node energy storage data grayscale map, and the grayscale histogram of the parent node energy storage data grayscale map is obtained.

10. A method for protecting energy storage data security in a distribution network based on cloud computing according to claim 9, characterized in that: The specific calculation method for determining the grayscale value that each small rectangle needs to be filled is: Where, Indicates the parent node Next The grayscale value that needs to be filled in the small rectangle corresponding to each child node; Indicates the parent node Next The energy storage data of the child nodes is in the parent node The proportion of energy storage data.

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